diff --git a/galaxy/wrapper/test-data/bamCoverage_result6.bw b/galaxy/wrapper/test-data/bamCoverage_result6.bw
index e539b01669..d6f90cd657 100644
Binary files a/galaxy/wrapper/test-data/bamCoverage_result6.bw and b/galaxy/wrapper/test-data/bamCoverage_result6.bw differ
diff --git a/pixi.lock b/pixi.lock
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+  sha256: cbedb772ed74ff5be440fa8eee9bd49f64f6e3fc09436d9c7d8f1c287b121d77
+  requires_dist:
+  - numpy>=1.25
+  - furo ; extra == 'docs'
+  - sphinx>=7.2 ; extra == 'docs'
+  - sphinx-copybutton ; extra == 'docs'
+  - bokeh ; extra == 'bokeh'
+  - selenium ; extra == 'bokeh'
+  - contourpy[bokeh,docs] ; extra == 'mypy'
+  - bokeh ; extra == 'mypy'
+  - docutils-stubs ; extra == 'mypy'
+  - mypy==1.17.0 ; extra == 'mypy'
+  - types-pillow ; extra == 'mypy'
+  - contourpy[test-no-images] ; extra == 'test'
+  - matplotlib ; extra == 'test'
+  - pillow ; extra == 'test'
+  - pytest ; extra == 'test-no-images'
+  - pytest-cov ; extra == 'test-no-images'
+  - pytest-rerunfailures ; extra == 'test-no-images'
+  - pytest-xdist ; extra == 'test-no-images'
+  - wurlitzer ; extra == 'test-no-images'
+  requires_python: '>=3.11'
+- pypi: https://files.pythonhosted.org/packages/fe/3b/8ec5074bcfc450fe84273713b4b0a0dd47c0249358f5d82eb8104ffe2520/multidict-6.7.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
+  name: multidict
+  version: 6.7.1
+  sha256: 7eee46ccb30ff48a1e35bb818cc90846c6be2b68240e42a78599166722cea709
+  requires_dist:
+  - typing-extensions>=4.1.0 ; python_full_version < '3.11'
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/ff/9a/9afaade874b2fa6c752c36f1548f718b5b83af81ed9b76628329dab81c1b/rfc3986-2.0.0-py2.py3-none-any.whl
+  name: rfc3986
+  version: 2.0.0
+  sha256: 50b1502b60e289cb37883f3dfd34532b8873c7de9f49bb546641ce9cbd256ebd
+  requires_dist:
+  - idna ; extra == 'idna2008'
+  requires_python: '>=3.7'
diff --git a/pydeeptools/deeptools/bamCoverage2.py b/pydeeptools/deeptools/bamCoverage2.py
index 139f95ca83..64f4ecfb72 100644
--- a/pydeeptools/deeptools/bamCoverage2.py
+++ b/pydeeptools/deeptools/bamCoverage2.py
@@ -143,14 +143,12 @@ def main(args=None):
     if not args.normalizeUsing:
         args.normalizeUsing = 'None'
     if not args.Offset:
+        # no offset is encoded as 0,0
         args.Offset = [0, 0]
-    # in rust, no offset is encoded as 0,0
-    # in python code 1, -1 corresponds to no offset.
     elif len(args.Offset) == 1:
+        # a single offset value is encoded as (value, 0); 0 is otherwise never
         args.Offset = [args.Offset[0], 0]
     else:
-        if args.Offset[1] == -1:
-            args.Offset[1] = 0
         args.Offset = [args.Offset[0], args.Offset[1]]
 
     if not args.extendReads:
diff --git a/pydeeptools/deeptools/computeGCBias.py b/pydeeptools/deeptools/computeGCBias.py
index 65be21e036..2e20e6d8cf 100755
--- a/pydeeptools/deeptools/computeGCBias.py
+++ b/pydeeptools/deeptools/computeGCBias.py
@@ -3,6 +3,7 @@
 
 import time
 
+from pathlib import Path
 import multiprocessing
 import numpy as np
 import argparse
@@ -102,7 +103,7 @@ def getRequiredArgs():
                           help='BED file containing genomic regions for which '
                           'extra sampling is required because they are '
                           'underrepresented in the genome.',
-                          type=parserCommon.readableFile,
+                          type=Path,
                           metavar='BED file')
 
     plot = parser.add_argument_group('Diagnostic plot options')
diff --git a/pydeeptools/deeptools/computeMatrix.py b/pydeeptools/deeptools/computeMatrix.py
index 5ff67f831f..556c53daaf 100644
--- a/pydeeptools/deeptools/computeMatrix.py
+++ b/pydeeptools/deeptools/computeMatrix.py
@@ -425,5 +425,5 @@ def main(args=None):
         hm.save_matrix_values(args.outFileNameMatrix)
 
     if args.outFileSortedRegions:
-        with open(args.outFileSortedRegions, 'w') as f:
-            hm.save_BED(f)
+        with open(args.outFileSortedRegions, "w") as fh:
+            hm.save_BED(fh)
diff --git a/pydeeptools/deeptools/computeMatrix2.py b/pydeeptools/deeptools/computeMatrix2.py
index bbdd074b76..d972a6e71a 100644
--- a/pydeeptools/deeptools/computeMatrix2.py
+++ b/pydeeptools/deeptools/computeMatrix2.py
@@ -369,6 +369,7 @@ def computeMatrixOptArgs(case=["scale-regions", "reference-point"][0]):
         "-bl",
         help="A BED file containing regions that should be excluded from all analyses. Currently this works by rejecting genomic chunks that happen to overlap an entry. Consequently, for BAM files, if a read partially overlaps a blacklisted region or a fragment spans over it, then the read/fragment might still be considered.",
         metavar="BED file",
+        default='none',
         required=False,
     )
 
@@ -447,6 +448,8 @@ def process_args(args=None):
         )
     if not args.samplesLabel:
         args.samplesLabel = []
+    else:
+        args.samplesLabel = [i.strip('"').strip("'") for i in args.samplesLabel]
     if not args.sortUsingSamples:
         args.sortUsingSamples = []
 
@@ -461,7 +464,6 @@ def main(args=None):
 
     args = process_args(args)
     signal.signal(signal.SIGINT, signal.SIG_DFL)
-
     sorted_regions_file = args.outFileSortedRegions
 
     r_computematrix(
@@ -476,7 +478,7 @@ def main(args=None):
         args.regionBodyLength,
         args.binSize,
         args.missingDataAsZero,
-        args.keepExons,  # --metagene or not.
+        args.keepExons,
         args.transcriptID,
         args.exonID,
         args.transcript_id_designator,
@@ -485,6 +487,7 @@ def main(args=None):
         args.skipZeros,
         args.minThreshold,
         args.maxThreshold,
+        args.blackListFileName,
         args.averageTypeBins,
         args.sortRegions,
         args.sortUsing,
diff --git a/pydeeptools/deeptools/correctGCBias.py b/pydeeptools/deeptools/correctGCBias.py
index 99c725c4fc..c4e2476f1d 100755
--- a/pydeeptools/deeptools/correctGCBias.py
+++ b/pydeeptools/deeptools/correctGCBias.py
@@ -6,6 +6,7 @@
 import time
 import subprocess
 import sys
+from pathlib import Path
 
 import py2bit
 import pysam
@@ -91,7 +92,7 @@ def getRequiredArgs():
                           'computeGCBias containing '
                           'the observed and expected read frequencies per GC-'
                           'content.',
-                          type=parserCommon.readableFile,
+                          type=Path,
                           metavar='FILE',
                           required=True)
 
diff --git a/pydeeptools/deeptools/multiBamSummary2.py b/pydeeptools/deeptools/multiBamSummary2.py
index e229c29014..376d768c81 100644
--- a/pydeeptools/deeptools/multiBamSummary2.py
+++ b/pydeeptools/deeptools/multiBamSummary2.py
@@ -153,15 +153,6 @@ def bamcorrelate_args(case="bins"):
         "after removing the path and extension.",
     )
 
-    optional.add_argument(
-        "--genomeChunkSize",
-        type=int,
-        default=None,
-        help="Manually specify the size of the genome provided to each processor. "
-        "The default value of None specifies that this is determined by read "
-        "density of the BAM file.",
-    )
-
     if case == "bins":
         optional.add_argument(
             "--binSize",
diff --git a/pydeeptools/deeptools/parserCommon.py b/pydeeptools/deeptools/parserCommon.py
index 70b4aff219..e3c68183ab 100755
--- a/pydeeptools/deeptools/parserCommon.py
+++ b/pydeeptools/deeptools/parserCommon.py
@@ -2,7 +2,7 @@
 import os
 from importlib.metadata import version
 import multiprocessing
-
+from pathlib import Path
 
 def check_float_0_1(value):
     v = float(value)
@@ -436,7 +436,7 @@ def heatmapperMatrixArgs(args=None):
     required = parser.add_argument_group('Required arguments')
     required.add_argument('--matrixFile', '-m',
                           help='Matrix file from the computeMatrix tool.',
-                          type=readableFile,
+                          type=Path,
                           )
 
     required.add_argument('--outFileName', '-out', '-o',
diff --git a/pydeeptools/deeptools/plotHeatmap.py b/pydeeptools/deeptools/plotHeatmap.py
index 6432f9356e..da9f27ba9c 100755
--- a/pydeeptools/deeptools/plotHeatmap.py
+++ b/pydeeptools/deeptools/plotHeatmap.py
@@ -701,8 +701,8 @@ def main(args=None):
         hm.save_matrix(args.outFileNameMatrix)
 
     if args.outFileSortedRegions:
-        with open(args.outFileSortedRegions, 'w') as f:
-            hm.save_BED(f)
+        with open(args.outFileSortedRegions, "w") as fh:
+            hm.save_BED(fh)
 
     if not args.label_rotation:
         label_rotation=45.0
diff --git a/pydeeptools/deeptools/plotProfile.py b/pydeeptools/deeptools/plotProfile.py
index 0ac37fb81d..dcc711e126 100755
--- a/pydeeptools/deeptools/plotProfile.py
+++ b/pydeeptools/deeptools/plotProfile.py
@@ -9,7 +9,7 @@
 from math import ceil
 from deeptools import matplotlib_defaults
 import matplotlib.pyplot as plt
-from matplotlib.font_manager import FontProperties 
+from matplotlib.font_manager import FontProperties
 from matplotlib import colors as pltcolors
 import matplotlib.gridspec as gridspec
 
@@ -76,14 +76,14 @@ def process_args(args=None):
         args.plotHeight = 0.5
     elif args.plotHeight > 100:
         args.plotHeight = 100
-    
+
     if not args.label_rotation:
         args.label_rotation=45.0
     else:
         args.label_rotation= args.label_rotation
-    
+
     if args.ggplot:
-        plt.style.use('ggplot') 
+        plt.style.use('ggplot')
 
     return args
 
@@ -628,8 +628,8 @@ def main(args=None):
                                  averagetype=args.averageType)
 
     if args.outFileSortedRegions:
-        with open(args.outFileSortedRegions, 'w') as f:
-            hm.save_BED(f)
+        with open(args.outFileSortedRegions, "w") as fh:
+            hm.save_BED(fh)
 
     prof = Profile(hm, args.outFileName,
                    plot_title=args.plotTitle,
diff --git a/pydeeptools/deeptools/test/test_computeMatrix.py b/pydeeptools/deeptools/test/test_computeMatrix_referencepoint.py
similarity index 70%
rename from pydeeptools/deeptools/test/test_computeMatrix.py
rename to pydeeptools/deeptools/test/test_computeMatrix_referencepoint.py
index db54355a0e..9aa246913b 100644
--- a/pydeeptools/deeptools/test/test_computeMatrix.py
+++ b/pydeeptools/deeptools/test/test_computeMatrix_referencepoint.py
@@ -12,9 +12,13 @@
 ROOT = os.path.dirname(os.path.abspath(__file__)) + "/test_data/test_computematrix/"
 REGIONS_IN1 = ROOT + "input_computeMatrix_regions1.bed"
 REGIONS_IN2 = ROOT + "input_computeMatrix_regions2.bed"
+REGIONS_GTF = ROOT + "input_computeMatrix_regions3.gtf"
+REGIONS_BED12 = ROOT + "input_computeMatrix_regions4bed12.bed"
+BL = ROOT + "input_computeMatrix_blacklist.bed"
 BIGWIG_IN1 = ROOT + "input_computeMatrix_bw1.bw"
 BIGWIG_IN2 = ROOT + "input_computeMatrix_bw2.bw"
 BIGWIG_IN3 = ROOT + "input_computeMatrix_bw3.bw"
+BIGWIG_IN4 = ROOT + "input_computeMatrix_bw4.bw"
 
 def _parse_mat_gz(file_path: str) -> Tuple[Dict[str, Any], List[List[float]]]:
     """
@@ -80,6 +84,9 @@ def _compare_mat_gz(observed_file: str, expected_file: str) -> Tuple[List[str],
         if key not in obs_header:
             header_differences.append(f"Missing key in observed: {key}")
         elif key not in exp_header:
+            # scale-regions, no default has no 'startlabel' or 'endlabel' in json header
+            if key == 'startLabel' or key == 'endLabel':
+                continue
             header_differences.append(f"Missing key in expected: {key}")
         else:
             # Compare values
@@ -239,6 +246,28 @@ def test_compute_matrix_refpoint():
     mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
     assert mat_match, f"matrix mismatch: {mat_diffs}"
 
+def test_compute_matrix_refpoint2():
+    exp_npz = ROOT + "mat2.gz"
+    exp_mat = ROOT + "mat2.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 30 -a 30 --binSize 30
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
 def test_compute_matrix_refpoint_multibed():
     exp_npz = ROOT + "mat_multibed.gz"
     exp_mat = ROOT + "mat_multibed.tab"
@@ -747,94 +776,301 @@ def test_compute_matrix_refpoint_avgtypesum():
     mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
     assert mat_match, f"matrix mismatch: {mat_diffs}"
 
-# def test_compute_matrix_refpoint_missingdataaszero():
-#     exp_npz = ROOT + "mat_maz.gz"
-#     exp_mat = ROOT + "mat_maz.tab"
-
-#     _, outfile_npz = tempfile.mkstemp(suffix='.gz')
-#     _, outfile_mat = tempfile.mkstemp(suffix='.tab')
-#     args = f"""
-#     reference-point
-#     --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
-#     --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
-#     -b 210 -a 210 --binSize 30
-#     --missingDataAsZero
-#     -o {outfile_npz} --outFileNameMatrix {outfile_mat}
-#     """.split()
-#     cm.main(args)
-
-#     header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
-#     assert not header_differences, f"header mismatch: {header_differences}"
-#     assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
-
-#     mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
-#     assert mat_match, f"matrix mismatch: {mat_diffs}"
-
-# def test_compute_matrix_refpoint_multidiffbw():
-#     exp_npz = ROOT + "mat_multidiffbw.gz"
-#     exp_mat = ROOT + "mat_multidiffbw.tab"
-
-#     _, outfile_npz = tempfile.mkstemp(suffix='.gz')
-#     _, outfile_mat = tempfile.mkstemp(suffix='.tab')
-#     args = f"""
-#     reference-point
-#     --regionsFileName {REGIONS_IN1} {REGIONS_IN1}
-#     --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN2} {BIGWIG_IN2}
-#     -b 20 -a 20
-#     --sortRegions descend
-#     -o {outfile_npz} --outFileNameMatrix {outfile_mat}
-#     """.split()
-#     cm.main(args)
-
-#     header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
-#     assert not header_differences, f"header mismatch: {header_differences}"
-#     assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
-
-#     mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
-#     assert mat_match, f"matrix mismatch: {mat_diffs}"
-
-# def test_compute_matrix_with_reference_point_and_advance_options_1():
-#     """
-#     Test minimal command line args compute matrix with reference based
-#     mode along with advance options of sorting using sum and average
-#     type bin as sum
-#     """
-#     _, outfile = tempfile.mkstemp(suffix='.gz')
-#     args = f"reference-point --regionsFileName {REGIONS_IN1} --scoreFileName {BIGWIG_IN1} -o {outfile} -bs 10 --sortUsing sum --averageTypeBins sum -b 10 -a 10".split()
-#     print(' '.join(args))
-#     cm.main(args)
-
-#     archieve_file_size = os.path.getsize(OUT_ARCHIEVE1)
-#     expected_file_size = os.path.getsize(outfile)
-#     size_tolerance = 500
-#     size_difference = abs(archieve_file_size - expected_file_size)
-#     assert size_difference <= size_tolerance, "File size do not match"
-
-# def test_compute_matrix_with_reference_point_and_advance_options_2():
-#     """
-#     Test minimal command line args compute matrix with reference based mode
-#     with before and after region start length
-#     """
-#     _, outfile = tempfile.mkstemp(suffix='.gz')
-#     args = "reference-point --regionsFileName {} --scoreFileName {} -o {} -bs 10 -b 10 -a 10".format(REGIONS_IN2, BIGWIG_IN2, outfile).split()
-#     cm.main(args)
-
-#     archieve_file_size = os.path.getsize(OUT_ARCHIEVE2)
-#     expected_file_size = os.path.getsize(outfile)
-#     size_tolerance = 500
-#     size_difference = abs(archieve_file_size - expected_file_size)
-#     assert size_difference <= size_tolerance, "File size do not match"
-
-# def test_compute_matrix_with_scale_regions():
-#     """
-#     Test minimal command line args compute matrix with scale regions mode
-#     """
-#     _, outfile = tempfile.mkstemp(suffix='.gz')
-#     args = "scale-regions --regionsFileName {} --scoreFileName {} -o {}".format(REGIONS_IN2, BIGWIG_IN2, outfile).split()
-#     cm.main(args)
-
-#     archieve_file_size = os.path.getsize(OUT_ARCHIEVE3)
-#     expected_file_size = os.path.getsize(outfile)
-#     size_tolerance = 500
-#     size_difference = abs(archieve_file_size - expected_file_size)
-#     assert size_difference <= size_tolerance, "File size do not match"
+def test_compute_matrix_refpoint_missingdataaszero():
+    exp_npz = ROOT + "mat_maz.gz"
+    exp_mat = ROOT + "mat_maz.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 30 -a 30 --binSize 30
+    --missingDataAsZero
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_skipzeros():
+    exp_npz = ROOT + "mat_skipzeros.gz"
+    exp_mat = ROOT + "mat_skipzeros.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 210 -a 210 --binSize 30
+    --skipZeros
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_thresh():
+    exp_npz = ROOT + "mat_thresh.gz"
+    exp_mat = ROOT + "mat_thresh.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 210 -a 210 --binSize 30
+    --minThreshold 10000 --maxThreshold 50000
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_bl():
+    exp_npz = ROOT + "mat_bl.gz"
+    exp_mat = ROOT + "mat_bl.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 30 -a 30 --binSize 30
+    --blackListFileName {BL}
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_sampleslabel():
+    exp_npz = ROOT + "mat_sampleslabel.gz"
+    exp_mat = ROOT + "mat_sampleslabel.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 30 -a 30 --binSize 30
+    --samplesLabel "a" "b" "c" "d"
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_scale():
+    exp_npz = ROOT + "mat_scale.gz"
+    exp_mat = ROOT + "mat_scale.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 30 -a 30 --binSize 30
+    --scale 3
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_bed12():
+    exp_npz = ROOT + "mat_bed12.gz"
+    exp_mat = ROOT + "mat_bed12.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_BED12}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
+    -b 30 -a 30 --binSize 30
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_gtf():
+    exp_npz = ROOT + "mat_gtf.gz"
+    exp_mat = ROOT + "mat_gtf.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
+    -b 30 -a 30 --binSize 30
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_bed12mg():
+    exp_npz = ROOT + "mat_bed12mg.gz"
+    exp_mat = ROOT + "mat_bed12mg.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_BED12}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
+    -b 30 -a 30 --binSize 30
+    --metagene
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_gtfmg():
+    exp_npz = ROOT + "mat_gtfmg.gz"
+    exp_mat = ROOT + "mat_gtfmg.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
+    -b 30 -a 30 --binSize 30
+    --metagene
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_gtfmglarge():
+    exp_npz = ROOT + "mat_gtfmglarge.gz"
+    exp_mat = ROOT + "mat_gtfmglarge.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
+    -b 2000 -a 2000 --binSize 10
+    --metagene
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_gtflarge():
+    exp_npz = ROOT + "mat_gtflarge.gz"
+    exp_mat = ROOT + "mat_gtflarge.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
+    -b 2000 -a 2000 --binSize 10
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_refpoint_gtfmgid():
+    exp_npz = ROOT + "mat_gtfmg_id.gz"
+    exp_mat = ROOT + "mat_gtfmg_id.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    reference-point
+    --regionsFileName {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3}
+    -b 30 -a 30 --binSize 30
+    --metagene
+    --transcriptID gene
+    --exonID CDS
+    --transcript_id_designator gene_id
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
diff --git a/pydeeptools/deeptools/test/test_computeMatrix_scaleregions.py b/pydeeptools/deeptools/test/test_computeMatrix_scaleregions.py
new file mode 100644
index 0000000000..9c12bd594a
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_computeMatrix_scaleregions.py
@@ -0,0 +1,764 @@
+import deeptools.computeMatrix2 as cm
+import tempfile
+import os.path
+import json
+import numpy as np
+from typing import Dict, List, Any, Tuple
+from .test_computeMatrix_referencepoint import _parse_mat_gz, _compare_mat_gz, _compare_tab_files,_compare_bed_files
+
+ALLOWED_DELTA = 1.0
+ROOT = os.path.dirname(os.path.abspath(__file__)) + "/test_data/test_computematrix/"
+
+REGIONS_IN1 = ROOT + "input_computeMatrix_regions1.bed"
+REGIONS_IN2 = ROOT + "input_computeMatrix_regions2.bed"
+REGIONS_GTF = ROOT + "input_computeMatrix_regions3.gtf"
+REGIONS_BED12 = ROOT + "input_computeMatrix_regions4bed12.bed"
+BL = ROOT + "input_computeMatrix_blacklist.bed"
+BIGWIG_IN1 = ROOT + "input_computeMatrix_bw1.bw"
+BIGWIG_IN2 = ROOT + "input_computeMatrix_bw2.bw"
+BIGWIG_IN3 = ROOT + "input_computeMatrix_bw3.bw"
+BIGWIG_IN4 = ROOT + "input_computeMatrix_bw4.bw"
+
+def test_compute_matrix_scaleregions():
+    exp_npz = ROOT + "srmat.gz"
+    exp_mat = ROOT + "srmat.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1}
+    --scoreFileName {BIGWIG_IN1}
+    -b 20 -a 20
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_multireg():
+    exp_npz = ROOT + "srmat_multireg.gz"
+    exp_mat = ROOT + "srmat_multireg.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 20 -a 20
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_multireg2():
+    exp_npz = ROOT + "srmat_multireg2.gz"
+    exp_mat = ROOT + "srmat_multireg2.tab"
+    exp_bed = ROOT + "srmat_multireg2.bed"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    _, outfile_bed = tempfile.mkstemp(suffix='.bed')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 150 -a 195 --binSize 15 -m 150
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat} --outFileSortedRegions {outfile_bed}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+    bed_match, bed_diffs = _compare_bed_files(outfile_bed, exp_bed)
+    assert bed_match, f"bed mismatch: {bed_diffs}"
+
+def test_compute_matrix_scaleregions_reglabels():
+    exp_npz = ROOT + "srmat_reglabel.gz"
+    exp_mat = ROOT + "srmat_reglabel.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 500 -a 800 --binSize 20 -m 2400
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    --startLabel fakepeak_start
+    --endLabel fakepeak_end
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_unscaled():
+    exp_npz = ROOT + "srmat_unscaled.gz"
+    exp_mat = ROOT + "srmat_unscaled.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 500 -a 800 --binSize 20 -m 2400
+    --unscaled5prime 240 --unscaled3prime 40
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_unscaled2():
+    exp_npz = ROOT + "srmat_unscaled2.gz"
+    exp_mat = ROOT + "srmat_unscaled2.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 500 -a 800 --binSize 20 -m 200
+    --unscaled5prime 20 --unscaled3prime 120
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_unscaled3():
+    exp_npz = ROOT + "srmat_unscaled3.gz"
+    exp_mat = ROOT + "srmat_unscaled3.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+
+def test_compute_matrix_scaleregions_median():
+    exp_npz = ROOT + "srmat_med.gz"
+    exp_mat = ROOT + "srmat_med.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --averageTypeBins median
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_min():
+    exp_npz = ROOT + "srmat_min.gz"
+    exp_mat = ROOT + "srmat_min.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --averageTypeBins min
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_std():
+    exp_npz = ROOT + "srmat_std.gz"
+    exp_mat = ROOT + "srmat_std.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --averageTypeBins std
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_max():
+    exp_npz = ROOT + "srmat_max.gz"
+    exp_mat = ROOT + "srmat_max.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --averageTypeBins max
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+
+def test_compute_matrix_scaleregions_sum():
+    exp_npz = ROOT + "srmat_sum.gz"
+    exp_mat = ROOT + "srmat_sum.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --averageTypeBins sum
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_descend():
+    exp_npz = ROOT + "srmat_desc.gz"
+    exp_mat = ROOT + "srmat_desc.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_ascend():
+    exp_npz = ROOT + "srmat_ascend.gz"
+    exp_mat = ROOT + "srmat_ascend.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions ascend
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_sortno():
+    exp_npz = ROOT + "srmat_no.gz"
+    exp_mat = ROOT + "srmat_no.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions no
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_sortusum():
+    exp_npz = ROOT + "srmat_sortusum.gz"
+    exp_mat = ROOT + "srmat_sortusum.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing sum
+    --sortUsingSamples 3
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_sortumin():
+    exp_npz = ROOT + "srmat_sortumin.gz"
+    exp_mat = ROOT + "srmat_sortumin.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing min
+    --sortUsingSamples 3
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_sortumedian():
+    exp_npz = ROOT + "srmat_sortumedian.gz"
+    exp_mat = ROOT + "srmat_sortumedian.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing median
+    --sortUsingSamples 3
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_sortumean():
+    exp_npz = ROOT + "srmat_sortumean.gz"
+    exp_mat = ROOT + "srmat_sortumean.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing mean
+    --sortUsingSamples 3
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_sortumax():
+    exp_npz = ROOT + "srmat_sortumax.gz"
+    exp_mat = ROOT + "srmat_sortumax.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing max
+    --sortUsingSamples 3
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_sortulen():
+    exp_npz = ROOT + "srmat_sortulen.gz"
+    exp_mat = ROOT + "srmat_sortulen.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing region_length
+    --sortUsingSamples 3
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_missingdataaszero():
+    exp_npz = ROOT + "srmat_missingaszero.gz"
+    exp_mat = ROOT + "srmat_missingaszero.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing region_length
+    --sortUsingSamples 3
+    --missingDataAsZero
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_skipzeros():
+    exp_npz = ROOT + "srmat_skipzeros.gz"
+    exp_mat = ROOT + "srmat_skipzeros.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing region_length
+    --sortUsingSamples 3
+    --missingDataAsZero
+    --skipZeros
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_thresh():
+    exp_npz = ROOT + "srmat_thresh.gz"
+    exp_mat = ROOT + "srmat_thresh.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing region_length
+    --sortUsingSamples 3
+    --minThreshold 12000 --maxThreshold 25000
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_bl():
+    exp_npz = ROOT + "srmat_bl.gz"
+    exp_mat = ROOT + "srmat_bl.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 180 -a 180 --binSize 20 -m 1000
+    --unscaled5prime 20 --unscaled3prime 20
+    --sortRegions descend
+    --sortUsing region_length
+    --blackListFileName {BL}
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_label():
+    exp_npz = ROOT + "srmat_label.gz"
+    exp_mat = ROOT + "srmat_label.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 70 -a 140 --binSize 35 -m 420
+    --unscaled5prime 35 --unscaled3prime 70
+    --samplesLabel some_sample another_one athird this_one_failed
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_scale():
+    exp_npz = ROOT + "srmat_scale.gz"
+    exp_mat = ROOT + "srmat_scale.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_IN1} {REGIONS_IN2} {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 98 -a 422 --binSize 2 -m 842
+    --unscaled5prime 22 --unscaled3prime 44
+    --scale 0.78
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_bed12():
+    exp_npz = ROOT + "srmat_bed12.gz"
+    exp_mat = ROOT + "srmat_bed12.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_BED12}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 98 -a 422 --binSize 2 -m 842
+    --unscaled5prime 22 --unscaled3prime 44
+    --scale 0.78
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_bed12mg():
+    exp_npz = ROOT + "srmat_bed12mg.gz"
+    exp_mat = ROOT + "srmat_bed12mg.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_BED12}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 98 -a 422 --binSize 2 -m 842
+    --unscaled5prime 22 --unscaled3prime 44
+    --scale 0.78
+    --metagene
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
+
+def test_compute_matrix_scaleregions_gtfmg():
+    exp_npz = ROOT + "srmat_gtfmg.gz"
+    exp_mat = ROOT + "srmat_gtfmg.tab"
+
+    _, outfile_npz = tempfile.mkstemp(suffix='.gz')
+    _, outfile_mat = tempfile.mkstemp(suffix='.tab')
+    args = f"""
+    scale-regions
+    --regionsFileName {REGIONS_GTF}
+    --scoreFileName {BIGWIG_IN1} {BIGWIG_IN2} {BIGWIG_IN3} {BIGWIG_IN4}
+    -b 98 -a 422 --binSize 2 -m 842
+    --unscaled5prime 22 --unscaled3prime 44
+    --scale 0.78
+    --metagene
+    -o {outfile_npz} --outFileNameMatrix {outfile_mat}
+    """.split()
+    cm.main(args)
+
+    header_differences, data_differences, rowdiffdic = _compare_mat_gz(outfile_npz, exp_npz)
+    assert not header_differences, f"header mismatch: {header_differences}"
+    assert not data_differences, f"data mismatch: {data_differences}\nrowdiffdict: {rowdiffdic}"
+
+    mat_match, mat_diffs = _compare_tab_files(outfile_mat, exp_mat)
+    assert mat_match, f"matrix mismatch: {mat_diffs}"
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_blacklist.bed b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_blacklist.bed
new file mode 100644
index 0000000000..128aec6f78
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_blacklist.bed
@@ -0,0 +1,2 @@
+phiX174	877	1011
+phiX174	80	101
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_bw4.bw b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_bw4.bw
new file mode 100644
index 0000000000..e0434a5b46
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_bw4.bw differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_regions3.gtf b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_regions3.gtf
new file mode 100644
index 0000000000..88ceb41fb5
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_regions3.gtf
@@ -0,0 +1,22 @@
+phiX174	test	transcript	1	150	.	+	.	gene_id "gene_start"; transcript_id "tx_start";
+phiX174	test	exon	1	100	.	+	.	gene_id "gene_start"; transcript_id "tx_start"; exon_number "1";
+phiX174	test	transcript	300	900	.	+	.	gene_id "gene_plus_multi"; transcript_id "tx_plus_multi";
+phiX174	test	exon	300	380	.	+	.	gene_id "gene_plus_multi"; transcript_id "tx_plus_multi"; exon_number "1";
+phiX174	test	exon	500	620	.	+	.	gene_id "gene_plus_multi"; transcript_id "tx_plus_multi"; exon_number "2";
+phiX174	test	exon	800	900	.	+	.	gene_id "gene_plus_multi"; transcript_id "tx_plus_multi"; exon_number "3";
+phiX174	test	transcript	1400	1650	.	-	.	gene_id "gene_minus_single"; transcript_id "tx_minus_single";
+phiX174	test	exon	1400	1650	.	-	.	gene_id "gene_minus_single"; transcript_id "tx_minus_single"; exon_number "1";
+phiX174	test	transcript	2200	3100	.	-	.	gene_id "gene_minus_multi"; transcript_id "tx_minus_multi";
+phiX174	test	exon	2200	2350	.	-	.	gene_id "gene_minus_multi"; transcript_id "tx_minus_multi"; exon_number "1";
+phiX174	test	exon	2500	2650	.	-	.	gene_id "gene_minus_multi"; transcript_id "tx_minus_multi"; exon_number "2";
+phiX174	test	exon	2900	3100	.	-	.	gene_id "gene_minus_multi"; transcript_id "tx_minus_multi"; exon_number "3";
+phiX174	test	transcript	5000	5386	.	+	.	gene_id "gene_end"; transcript_id "tx_end";
+phiX174	test	exon	5000	5150	.	+	.	gene_id "gene_end"; transcript_id "tx_end"; exon_number "1";
+phiX174	test	exon	5300	5386	.	+	.	gene_id "gene_end"; transcript_id "tx_end"; exon_number "2";
+phiX174	test	gene	3400	3800	.	+	.	gene_id "gene_cds"; transcript_id "tx_cds";
+phiX174	test	transcript	3400	3800	.	+	.	gene_id "gene_cds"; transcript_id "tx_cds";
+phiX174	test	CDS	3400	3500	.	+	0	gene_id "gene_cds"; transcript_id "tx_cds";
+phiX174	test	CDS	3600	3800	.	+	0	gene_id "gene_cds"; transcript_id "tx_cds";
+phiX174	test	mRNA	3900	4400	.	-	.	gene_id "gene_mrna"; transcript_id "tx_mrna";
+phiX174	test	exon	3900	4050	.	-	.	gene_id "gene_mrna"; transcript_id "tx_mrna"; exon_number "1";
+phiX174	test	exon	4200	4400	.	-	.	gene_id "gene_mrna"; transcript_id "tx_mrna"; exon_number "2";
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_regions4bed12.bed b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_regions4bed12.bed
new file mode 100644
index 0000000000..986913af0f
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/input_computeMatrix_regions4bed12.bed
@@ -0,0 +1,5 @@
+phiX174	1	150	tx_start	0	+	1	150	0	1	149	0
+phiX174	299	900	tx_plus_multi	0	+	299	900	0	3	81,121,101	0,200,500
+phiX174	1399	1650	tx_minus_single	0	-	1399	1650	0	1	251	0
+phiX174	2199	3100	tx_minus_multi	0	-	2199	3100	0	3	151,151,201	0,300,700
+phiX174	4999	5386	tx_end	0	+	4999	5386	0	2	151,86	0,301
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat2.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat2.gz
new file mode 100644
index 0000000000..2abadfd9d4
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat2.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat2.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat2.tab
new file mode 100644
index 0000000000..aa96df3fb5
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat2.tab
@@ -0,0 +1,19 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw4	input_computeMatrix_bw4
+4.437e+05	5.346e+05	3.574e+05	9.631e+05	2.487e+05	3.483e+05	4.437e+05	nan
+4.063e+05	5.453e+05	3.916e+05	8.403e+05	4.173e+05	3.727e+05	4.063e+05	5.453e+05
+2.016e+05	1.534e+05	2.309e+05	1.035e+05	1.305e+05	2.178e+05	2.016e+05	1.534e+05
+1.524e+05	1.631e+05	5.082e+04	1.529e+05	6.736e+04	1.414e+05	1.524e+05	1.631e+05
+1.738e+05	1.24e+05	1.464e+05	1.509e+05	1.593e+05	7.276e+04	1.738e+05	1.24e+05
+1.55e+05	1.497e+05	9.8e+04	1.365e+05	2.472e+05	5.077e+04	1.55e+05	1.497e+05
+2.887e+05	3.528e+05	5.175e+05	2.392e+05	3.994e+05	4.456e+05	2.887e+05	3.528e+05
+1.604e+05	1.497e+05	7.005e+04	1.61e+05	9.725e+04	1.19e+05	1.604e+05	1.497e+05
+3.336e+05	3.849e+05	4.195e+05	3.587e+05	4.268e+05	3.999e+05	3.336e+05	3.849e+05
+1.534e+05	2.016e+05	1.035e+05	2.309e+05	2.178e+05	1.305e+05	1.534e+05	2.016e+05
+2.138e+04	1.187e+05	3.033e+04	4.546e+04	6488	2.751e+04	2.138e+04	1.187e+05
+3.058e+05	3.389e+05	3.02e+05	2.243e+05	3.807e+05	4.111e+05	3.058e+05	3.389e+05
+5.699e+05	4.667e+05	5.692e+05	7.361e+05	6.319e+05	3.086e+05	5.699e+05	4.667e+05
+4.378e+05	6.431e+05	5.011e+05	9.958e+05	3.867e+05	5.353e+05	4.246e+05	nan
+2.641e+05	3.154e+05	3.885e+05	4.542e+05	4.015e+05	3.915e+05	2.641e+05	3.154e+05
+1.895e+04	1.155e+05	2.549e+04	4.72e+04	7067	2.627e+04	1.895e+04	1.155e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.gz
index c21fd70763..f9b3c55b78 100644
Binary files a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.gz and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.tab
index 8f0ce5e2e7..7b4ef67d9e 100644
--- a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.tab
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_avgtypesum.tab
@@ -1,19 +1,19 @@
 #input_computeMatrix_regions1:8	input_computeMatrix_regions2:8
 #downstream:210	upstream:210	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
 input_computeMatrix_regions1:8	input_computeMatrix_regions2:8	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3
-14274230	10425000	8981540	12028840	16519620	16840390	13311920	16038470	23576550	25661532	21651912	19406532	18283850	15717700	14793479	7682630.5	9406057	9466363	16379770	20695980	10721285	28893644	17971450	21555804	10598602	14143370	10229223	17248628	10904870	11597411	11810780	15782730	15776054	15496430	7461621	10447591	30487974	33054780	17896510	30590314	21680238	20002218
-14755390	14755390	21170760	22133076	14915760	10264620	12189230	16359230	16680000	16359230	14434610	15878070	20689610	22293470	13411548	14249370	29921418	29761980	16724741	17054604	11746533	25209150	23485150	17177750	17314822	7046912	23469726	37795052	14595206	16276751	20384540	29177900	18053304	13251790	12518943	11181605	12904949	27174620	19619024	13556765	30347610	2106847.8
-7554112	9318340	10569345	12109044	9462690	8067352	6046503	4603046	4346422	4041692	5036079	4330380	1651961	nan	9675923	8448855	14342668	7910362.5	13659206	11932532	6926498	3106106.5	3897765.5	5917148.5	2160482.3	947678	1253992.1	nan	8187365.5	10091848	11606384	15623300	11709854	12360701	3913944.3	6534329.5	1648383.9	2449563.8	4354570	1124293.4	341155	nan
-nan	nan	nan	nan	400962.03	3849227	4570960	4891735	3849225	4410585	5693655	6736160	9382500	10906160	nan	nan	nan	nan	614810.2	1207788.5	1524610.5	4586875.5	4042904.5	3786099.8	5939140.5	9288750	13121654	11511266	nan	nan	nan	nan	78221.164	937509.75	2020896.1	4241342.5	2075052	3521686.3	5018321	8861400	11575832	15534878
-nan	nan	nan	208500.4	3464304.5	4378496	5212507	3720917	4346429	5501195	6479544	9318348	10392928	11772229	nan	nan	nan	280364.53	1415877	1063064.5	4393040	4528275.5	4020262	4987769.5	8729957	12869802	12639534	10178232	nan	nan	nan	77742.195	788082.94	1303613.9	4777990.5	2182780.3	2759830.8	5886992	7831132	11271210	14920776	11147660
-8981530	10425000	12349620	9462690	8500390	6094620	4651160	4490770	3849230	5132310	4330380	2084999	nan	nan	8571357	15231100	6971547.5	13754664	12766228	6839988	2940125	4095581.5	6383424.5	2185742	947678	1348759.9	nan	nan	9936735	11446728	15332213	11604102	13308472	3905997	7417325.5	1523237.6	1969149.8	4970458	1124293.4	453584.3	nan	nan
-9462690	12349620	10425000	8981530	7698460	7217300	8660760	10585390	14113840	15236530	17161150	17963080	17963080	16359240	13754664	6971547.5	15231100	8571357	8717303	10884771	15523822	7176741	16228765	16329338	10473264	28034676	16763286	16249793	11604102	15332213	11446728	9936735	7766678.5	5920432	11981281	13369136	17509564	14312946	13456715	11373791	11618180	17061498
-nan	nan	nan	nan	641539	4330380	4811540	4490770	4009610	4490780	5934230	7056930	9462690	11547700	nan	nan	nan	nan	1032867.4	947678	2101543	4829170.5	3436192.3	3493396.5	7128354.5	9987242	13436468	10100931	nan	nan	nan	nan	78819.875	1124293.4	2917499	3570530.3	1940391.9	4474006	3932486.8	10149236	11956608	16302505
-19470680	14627078	14242158	20144304	22389680	17995144	10008004	11547694	15589382	16680000	16359230	14947842	15108222	19021610	21740076	13465699	15041858	20907852	31914460	25737940	12586376	10762262	23656666	22536634	18526728	21586320	6942204	14742137	15129297	15402874	8857249	25455978	22079470	28367590	12805432	11995995	6129364.5	17637880	20955768	21019996	17088982	21574854
-nan	1651961	4330380	5036079	4041692	4346422	4603046	6046503	8067352	9462690	12109044	10569345	9318340	7554112	nan	1253992.1	947678	2160482.3	5917148.5	3897765.5	3106106.5	6926498	11932532	13659206	7910362.5	14342668	8448855	9675923	nan	341155	1124293.4	4354570	2449563.8	1648383.9	6534329.5	3913944.3	12360701	11709854	15623300	11606384	10091848	8187365.5
-nan	nan	nan	nan	nan	nan	256615.81	3560535.3	4426612	5132314	3752994	4362468	5549310	6543698	nan	nan	nan	nan	nan	nan	363975.94	1363854.9	1178451	4441499	4406932.5	3961721.5	5225612.5	8869655	nan	nan	nan	nan	nan	nan	77861.94	825439.7	1482934.4	4643828	2155848.3	2950294.5	5669824.5	8088699
-24025624	17257394	13183612	16455466	16647928	12798688	9174000	10168384	13568538	15589384	16936614	17289460	18797072	16519618	14520501	29410824	12133548	19245896	16610302	11724982	9059700	6727701.5	15178497	17860730	24694866	8917693	11013752	16102030	31550106	12433291	9100625	12511462	17635088	16395787	11421272	12333869	12276501	17455178	30623456	9725427	18482372	19075796
-19021620	23464266	23191620	16615845	15012006	13199646	17097006	14001575	12173196	9799499	10569351	9943850	10457087	12766622	29975002	19530820	21009058	10578818	14648136	11876436	17075616	22084308	16673780	14011896	11517919	3214557.8	7187886	13804096	9421683	13769404	25217886	14468671	10984639	8942365	18956986	9258461	8632729	5824101.5	9026688	13115220	7330393.5	19411738
-12381692	9799499	9510805	14129883	16872468	15717695	13135497	19294280	24747348	24603000	20256572	19214072	17722508	15525233	15518468	5826655	8062842	15286695	17243628	16819892	15031656	29873470	9123573	22263132	12189448	11578540	15922010	21690202	14346797	13607880	10814451	17018000	20468088	8004920	11599602	16058074	33706550	20050248	23627544	31018910	17664880	15201922
-4330380	5004002	4105846	4298306	4587008	6030464	7923006	9462690	12028852	10617460	9430610	7505996	7538072	8404144	947678	2152062.5	5761723	3831826.8	3161433.5	6955334.5	11654633	13627386	8223300.5	14046524	8408022	9995463	10304305	14800156	1124293.4	4149273.8	2609701.3	1690099.3	6239997.5	3916593.3	12044777	11745104	15720329	11659603	10143553	8327595	5790092.5	11598488
-nan	nan	nan	nan	nan	nan	208500.4	3464304.5	4378496	5212507	3720917	4346429	5501195	6479544	nan	nan	nan	nan	nan	nan	280364.53	1415877	1063064.5	4393040	4528275.5	4020262	4987769.5	8729957	nan	nan	nan	nan	nan	nan	77742.195	788082.94	1303613.9	4777990.5	2182780.3	2759830.8	5886992	7831132
+14274230.000000	10425000.000000	8981540.000000	12028840.000000	16519620.000000	16840390.000000	13311920.000000	16038470.000000	23576550.000000	25661532.000000	21651912.000000	19406532.000000	18283850.000000	15717700.000000	14793479.000000	7682630.500000	9406057.000000	9466363.000000	16379770.000000	20695980.000000	10721285.000000	28893644.000000	17971450.000000	21555804.000000	10598602.000000	14143370.000000	10229223.000000	17248628.000000	10904870.000000	11597411.000000	11810780.000000	15782730.000000	15776054.000000	15496430.000000	7461621.000000	10447591.000000	30487974.000000	33054780.000000	17896510.000000	30590314.000000	21680238.000000	20002218.000000
+14755390.000000	14755390.000000	21170760.000000	22133076.000000	14915760.000000	10264620.000000	12189230.000000	16359230.000000	16680000.000000	16359230.000000	14434610.000000	15878070.000000	20689610.000000	22293470.000000	13411548.000000	14249370.000000	29921418.000000	29761980.000000	16724741.000000	17054604.000000	11746533.000000	25209150.000000	23485150.000000	17177750.000000	17314822.000000	7046912.000000	23469726.000000	37795052.000000	14595206.000000	16276751.000000	20384540.000000	29177900.000000	18053304.000000	13251790.000000	12518943.000000	11181605.000000	12904949.000000	27174620.000000	19619024.000000	13556765.000000	30347610.000000	2106847.750000
+7554112.000000	9318340.000000	10569345.000000	12109044.000000	9462690.000000	8067352.000000	6046503.000000	4603046.000000	4346422.000000	4041692.000000	5036079.000000	4330380.000000	1651961.000000	nan	9675923.000000	8448855.000000	14342668.000000	7910362.500000	13659206.000000	11932532.000000	6926498.000000	3106106.500000	3897765.500000	5917148.500000	2160482.250000	947678.000000	1253992.125000	nan	8187365.500000	10091848.000000	11606384.000000	15623300.000000	11709854.000000	12360701.000000	3913944.250000	6534329.500000	1648383.875000	2449563.750000	4354570.000000	1124293.375000	341155.000000	nan
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+9462690.000000	12349620.000000	10425000.000000	8981530.000000	7698460.000000	7217300.000000	8660760.000000	10585390.000000	14113840.000000	15236530.000000	17161150.000000	17963080.000000	17963080.000000	16359240.000000	13754664.000000	6971547.500000	15231100.000000	8571357.000000	8717303.000000	10884771.000000	15523822.000000	7176741.000000	16228765.000000	16329338.000000	10473264.000000	28034676.000000	16763286.000000	16249793.000000	11604102.000000	15332213.000000	11446728.000000	9936735.000000	7766678.500000	5920432.000000	11981281.000000	13369136.000000	17509564.000000	14312946.000000	13456715.000000	11373791.000000	11618180.000000	17061498.000000
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+nan	1651961.000000	4330380.000000	5036079.000000	4041692.000000	4346422.000000	4603046.000000	6046503.000000	8067352.000000	9462690.000000	12109044.000000	10569345.000000	9318340.000000	7554112.000000	nan	1253992.125000	947678.000000	2160482.250000	5917148.500000	3897765.500000	3106106.500000	6926498.000000	11932532.000000	13659206.000000	7910362.500000	14342668.000000	8448855.000000	9675923.000000	nan	341155.000000	1124293.375000	4354570.000000	2449563.750000	1648383.875000	6534329.500000	3913944.250000	12360701.000000	11709854.000000	15623300.000000	11606384.000000	10091848.000000	8187365.500000
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+24025624.000000	17257394.000000	13183612.000000	16455466.000000	16647928.000000	12798688.000000	9174000.000000	10168384.000000	13568538.000000	15589384.000000	16936614.000000	17289460.000000	18797072.000000	16519618.000000	14520501.000000	29410824.000000	12133548.000000	19245896.000000	16610302.000000	11724982.000000	9059700.000000	6727701.500000	15178497.000000	17860730.000000	24694866.000000	8917693.000000	11013752.000000	16102030.000000	31550106.000000	12433291.000000	9100625.000000	12511462.000000	17635088.000000	16395787.000000	11421272.000000	12333869.000000	12276501.000000	17455178.000000	30623456.000000	9725427.000000	18482372.000000	19075796.000000
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+4330380.000000	5004002.000000	4105846.000000	4298306.000000	4587008.000000	6030464.000000	7923006.000000	9462690.000000	12028852.000000	10617460.000000	9430610.000000	7505996.000000	7538072.000000	8404144.000000	947678.000000	2152062.500000	5761723.000000	3831826.750000	3161433.500000	6955334.500000	11654633.000000	13627386.000000	8223300.500000	14046524.000000	8408022.000000	9995463.000000	10304305.000000	14800156.000000	1124293.375000	4149273.750000	2609701.250000	1690099.250000	6239997.500000	3916593.250000	12044777.000000	11745104.000000	15720329.000000	11659603.000000	10143553.000000	8327595.000000	5790092.500000	11598488.000000
+nan	nan	nan	nan	nan	nan	208500.406250	3464304.500000	4378496.000000	5212507.000000	3720917.000000	4346429.000000	5501195.000000	6479544.000000	nan	nan	nan	nan	nan	nan	280364.531250	1415877.000000	1063064.500000	4393040.000000	4528275.500000	4020262.000000	4987769.500000	8729957.000000	nan	nan	nan	nan	nan	nan	77742.195312	788082.937500	1303613.875000	4777990.500000	2182780.250000	2759830.750000	5886992.000000	7831132.000000
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12.gz
new file mode 100644
index 0000000000..04984bc025
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12.tab
new file mode 100644
index 0000000000..3f167f8bf2
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12.tab
@@ -0,0 +1,8 @@
+#genes:5
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+genes:5	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3
+1.604e+04	7.378e+04	1.968e+04	4.536e+04	7762	1.611e+04
+4.09e+05	3.491e+05	2.428e+05	4.978e+05	5.143e+05	3.833e+05
+5.4e+05	4.812e+05	6.707e+05	3.461e+05	9.391e+05	6.344e+05
+6.79e+05	5.934e+05	8.411e+05	2.471e+05	4.841e+05	1.312e+05
+2.422e+05	3.079e+05	3.497e+05	3.593e+05	2.978e+05	1.648e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12mg.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12mg.gz
new file mode 100644
index 0000000000..b8bf9da04e
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12mg.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12mg.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12mg.tab
new file mode 100644
index 0000000000..3f167f8bf2
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bed12mg.tab
@@ -0,0 +1,8 @@
+#genes:5
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+genes:5	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3
+1.604e+04	7.378e+04	1.968e+04	4.536e+04	7762	1.611e+04
+4.09e+05	3.491e+05	2.428e+05	4.978e+05	5.143e+05	3.833e+05
+5.4e+05	4.812e+05	6.707e+05	3.461e+05	9.391e+05	6.344e+05
+6.79e+05	5.934e+05	8.411e+05	2.471e+05	4.841e+05	1.312e+05
+2.422e+05	3.079e+05	3.497e+05	3.593e+05	2.978e+05	1.648e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bl.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bl.gz
new file mode 100644
index 0000000000..d79f50e81a
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bl.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bl.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bl.tab
new file mode 100644
index 0000000000..0aba48736c
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_bl.tab
@@ -0,0 +1,19 @@
+#input_computeMatrix_regions1:8	input_computeMatrix_regions2:8
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+input_computeMatrix_regions1:8	input_computeMatrix_regions2:8	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw4	input_computeMatrix_bw4
+nan	577385	nan	1052385.8	nan	142812.1	nan	nan
+406307.66	545307.7	391551.1	840305	417298.1	372720.16	406307.66	545307.7
+201550.1	153434.86	230883.27	103536.88	130464.805	217810.98	201550.1	153434.86
+152365.33	162389.63	50820.35	165147.88	67363.2	166486.03	152365.33	162389.63
+192462	124436.14	146975.77	149408.28	216797.02	72418.82	192462	124436.14
+155038.67	149692.33	98004.164	136519.39	247244.19	50774.586	155038.67	149692.33
+288692	352846.34	517460.72	239224.7	399376.03	445637.88	288692	352846.34
+160384.67	112269	70051.43	195434.69	97249.97	82634.43	160384.67	112269
+333600.13	384923.13	419545.88	358742.06	426847.72	399866.5	333600.13	384923.13
+153434.86	201550.1	103536.88	230883.27	217810.98	130464.805	153434.86	201550.1
+21384.65	118684.51	30331.328	45461.83	6488.4946	27514.656	21384.65	118684.51
+304033.53	338946.13	345415.56	224256.72	387534.47	411128.97	304033.53	338946.13
+569900.2	466719.16	569187.2	736143.6	631899.56	308615.38	569900.2	466719.16
+nan	645410.2	nan	993830.5	nan	548802.1	nan	nan
+264100.2	315423	388487.78	454246.2	401492.56	391503.47	264100.2	315423
+18954.582	115476.82	25487.686	47195.9	7067.472	26269.432	18954.582	115476.82
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtf.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtf.gz
new file mode 100644
index 0000000000..c3fd4f7876
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtf.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtf.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtf.tab
new file mode 100644
index 0000000000..93ba80538b
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtf.tab
@@ -0,0 +1,9 @@
+#genes:6
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+genes:6	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3
+nan	6.95e+04	nan	4.496e+04	nan	1.512e+04
+4.09e+05	3.491e+05	2.428e+05	4.978e+05	5.143e+05	3.833e+05
+5.4e+05	4.812e+05	6.707e+05	3.461e+05	9.391e+05	6.344e+05
+6.79e+05	5.934e+05	8.411e+05	2.471e+05	4.841e+05	1.312e+05
+2.422e+05	3.079e+05	3.497e+05	3.593e+05	2.978e+05	1.648e+05
+6.33e+05	4.844e+05	6.936e+05	7.602e+05	8.184e+05	8.93e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtflarge.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtflarge.gz
new file mode 100644
index 0000000000..eddf7c7a59
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtflarge.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtflarge.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtflarge.tab
new file mode 100644
index 0000000000..1b5958982d
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtflarge.tab
@@ -0,0 +1,9 @@
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg.gz
new file mode 100644
index 0000000000..3883d821ff
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg.tab
new file mode 100644
index 0000000000..93ba80538b
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg.tab
@@ -0,0 +1,9 @@
+#genes:6
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+genes:6	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3
+nan	6.95e+04	nan	4.496e+04	nan	1.512e+04
+4.09e+05	3.491e+05	2.428e+05	4.978e+05	5.143e+05	3.833e+05
+5.4e+05	4.812e+05	6.707e+05	3.461e+05	9.391e+05	6.344e+05
+6.79e+05	5.934e+05	8.411e+05	2.471e+05	4.841e+05	1.312e+05
+2.422e+05	3.079e+05	3.497e+05	3.593e+05	2.978e+05	1.648e+05
+6.33e+05	4.844e+05	6.936e+05	7.602e+05	8.184e+05	8.93e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg_id.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg_id.gz
new file mode 100644
index 0000000000..92947a04bb
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg_id.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg_id.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg_id.tab
new file mode 100644
index 0000000000..f198cb18e6
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmg_id.tab
@@ -0,0 +1,4 @@
+#genes:1
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+genes:1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3
+6.33e+05	4.844e+05	6.936e+05	7.602e+05	8.184e+05	8.93e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmglarge.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmglarge.gz
new file mode 100644
index 0000000000..74cd5f40d3
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmglarge.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmglarge.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmglarge.tab
new file mode 100644
index 0000000000..977fad6eb0
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_gtfmglarge.tab
@@ -0,0 +1,9 @@
+#genes:6
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e+04	1.048e+06	1.041e+06	2.419e+05	1.281e+06	7.898e+05	3.156e+05	4.594e+05	9.491e+05	8.859e+05	4.265e+05	4.106e+05	8.602e+05	9.097e+05	1.887e+05	7.791e+05	8.536e+05	9.712e+05	2.821e+05	4.939e+05	1.764e+05	6.92e+05	4.999e+05	2.103e+05	1.812e+05	9.478e+05	3.309e+05	4.351e+05	4.554e+05	1.228e+06	1.525e+06	1.305e+06	9.586e+05	7.553e+05	1.317e+06	1.202e+06	9.055e+05	1.183e+06	5.554e+05	7.576e+05	7.882e+05	9.821e+05	8.873e+05	6.558e+05	5.32e+05	4.353e+05	5.123e+05	5.219e+05	6.122e+05	4.265e+05	2.797e+05	3.359e+05	5.804e+05	3.369e+05	7.815e+04	1.622e+05	9.237e+05	4.33e+05	3.032e+05	3.943e+05	3.747e+05	5.44e+05	1.776e+05	2.864e+05	3.033e+05	1.253e+06	2.402e+05	9.553e+05	4.153e+05	1.181e+06	1.274e+06	7.883e+05	7.344e+05	5.014e+05	1.198e+06	9.664e+05	1.07e+06	1.265e+06	5.592e+05	1.006e+06	1.029e+06	5.936e+05	7.068e+05	6.722e+05	6.574e+05	8.094e+05	5.911e+05	6.335e+05	8.994e+05	2.086e+05	1.287e+05	1.287e+05	9.303e+05	1.019e+06	1.312e+05	7.1e+05	7.853e+05	7.853e+05	4.843e+05	2.963e+05	9.125e+05	4.478e+05	3.884e+05	1.532e+05	4.907e+05	1.412e+06	1.557e+06	7.294e+05	6.483e+05	1.953e+05	5.962e+05	1.137e+06	2.664e+05	1.7e+05	6.443e+05	6.97e+05	5.993e+05	5.998e+05	5.216e+05	3.79e+05	4.09e+05	3.749e+05	3.706e+05	5.471e+05	5.99e+05	1.197e+05	6.161e+05	1.187e+06	2.874e+05	3.522e+05	6.973e+05	4.886e+05	4.614e+05	5.287e+05	8.735e+05	6.272e+05	2.145e+05	1.1e+05	6.711e+05	5.162e+05	1.001e+06	1.418e+06	6.157e+05	5.596e+05	9.462e+05	7.854e+05	1.379e+05	6.655e+05	4.332e+05	4e+05	4.108e+05	1.457e+05	1.561e+05	3.164e+05	6.695e+05	3.576e+05	5.395e+05	6.92e+05	8.963e+05	6.587e+05	6.36e+05	8.164e+05	7.199e+05	8.135e+05	4.906e+05	3.324e+05	6.099e+05	1.654e+05	2.869e+05	3.063e+05	7.599e+04	1.162e+05	1.081e+05	4.27e+05	1.699e+05	5.038e+05	5.358e+05	5.348e+05	3.685e+05	3.501e+05	3.266e+05	8.737e+05	9.348e+05	8.733e+05	4.827e+05	5.896e+05	3.385e+05	7.925e+05	1.475e+05	5.464e+05	4.832e+05	5.427e+05	5.507e+05	3.94e+05	4.144e+05	5.021e+05	1.573e+05	4.78e+05	1.264e+06	3.054e+05	9.053e+05	4.076e+05	5.934e+05	9.812e+05	1.073e+06	9.258e+05	9.074e+05	2.341e+05	1.593e+05	8.64e+05	7.595e+05	4.389e+05	2.949e+05	1.747e+05	7.527e+05	1.248e+05	6.144e+05	3.394e+05	1.107e+06	3.693e+05	2.773e+05	7.013e+05	5.982e+05	2.504e+05	4.437e+05	5.032e+05	5.069e+05	5.773e+05	1.37e+05	8.812e+05	9.694e+05	1.021e+06	1.027e+06	4.518e+05	5.238e+05	1.009e+06	1.009e+06	4.494e+05	6.597e+05	6.899e+05	6.818e+05	8.424e+05	3.693e+05	3.757e+05	5.671e+05	3.538e+05	4.081e+05	1.96e+05	4.13e+05	4.398e+05	4.795e+04	2.333e+04	3.915e+05	2.776e+05	3.8e+05	3.933e+05	3.933e+05	2.915e+05	4.521e+05	3.907e+05	4.147e+05	4.49e+05	2.565e+05	5.832e+04	3.884e+05	6.373e+04	4.289e+05	4.66e+05	7.104e+05	2.308e+05	1.744e+05	5.326e+05	9.196e+05	8.961e+05	9.489e+05	7.612e+05	3.957e+05	4.842e+05	5.705e+05	5.224e+05	2.925e+05	3.933e+05	4.818e+05	5.266e+05	7.774e+04	3.375e+04	1.398e+05	1.516e+05	1.516e+05	2.12e+04	3.105e+04	3.376e+04	3.376e+04	3.376e+04	nan	1.602e+05	4.7e+05	5.034e+05	3.076e+05	2.859e+05	2.228e+05	1.037e+06	7.594e+05	4.199e+05	5.377e+05	9.162e+05	1.014e+06	8.114e+05	7.882e+05	2.575e+05	2.534e+04	6103	1.343e+06	7.766e+05	8.309e+05	4.404e+05	1.259e+05	7.876e+05	8.396e+05	2.655e+05	8.51e+05	1.003e+06	8.952e+05	8.291e+05	2.935e+05	7.414e+05	3.121e+05	7.694e+05	2.665e+05	9.926e+04	1.84e+05	4.963e+05	5.276e+05	1.691e+05	5.511e+05	5.979e+05	1.26e+05	3.394e+05	1.263e+06	1.363e+06	1.363e+06	3.092e+05	4.472e+05	1.1e+06	4.708e+05	1.038e+06	2.211e+05	3.685e+05	2.034e+05	5.028e+05	7.19e+05	3.286e+05	1.941e+05	5.872e+05	7.833e+05	1.213e+06	1.279e+06	1.698e+05	5.38e+05	5.926e+05	2.53e+05	6.961e+05	7.454e+05	8.289e+05	8.382e+05	1.499e+05	4.651e+05	4.038e+05	3.96e+05	8.455e+05	2.74e+05	6.827e+05	2.133e+05	7.836e+05	4.528e+05	2.118e+05	5.59e+05	5.928e+05	1.011e+06	4.852e+05	5.978e+05	5.391e+05	2.19e+05	1.844e+05	1.517e+05	1.113e+05	1.336e+06	1.538e+06	1.274e+06	1.583e+06	2.401e+05	1.134e+06	1.367e+06	9.157e+05	4.171e+05	1.253e+05	9.733e+04	3.937e+05	3.983e+05	3.852e+05	9.549e+05	7.088e+05	6.256e+05	9.817e+05	1.443e+05	8.502e+04	2.867e+05	7.939e+05	1.746e+05	6.478e+05	2.058e+05	2.994e+05	4.147e+05	4.257e+05	7.685e+04	3.223e+05	3.539e+05	4.887e+05	9.344e+05	5.612e+05	1.6e+05	2.545e+05	5.587e+05	3.396e+05	3.116e+05	3.417e+04	1.491e+05	1.171e+06	1.282e+06	4.422e+05	2.06e+05	1.175e+06	1.797e+05	1.504e+06	8.541e+05	1.599e+05	8.169e+05	4.047e+05	8.812e+05	1.105e+06	1.123e+06	2.228e+05	1.195e+06	3.164e+05	7.636e+05	7.515e+05	4.66e+05	4.352e+05	2.742e+05	6.134e+05	5.548e+05	1.233e+05	1.64e+05	6.677e+05	5.363e+05	9.295e+05	2.134e+05	3.492e+05	1.772e+05	2.387e+04	2.075e+05	9.287e+05	3.25e+05	8.987e+04	7.215e+04	7.89e+05	2.704e+05	3.622e+05	9.034e+05	1.1e+06	1.116e+06	2.91e+05	1.994e+05	6.865e+05	9.324e+05	1.129e+06	1.378e+06	7.383e+05	7.11e+05	6.504e+05	9.889e+05	1.114e+06	3.466e+05	8.9e+05	3.657e+05	7.302e+04	6.11e+05	1.046e+06	1.241e+06	1.064e+06	1.042e+06	1.042e+06	8.278e+05	8.04e+05	8.233e+05	8.883e+05	8.953e+05	8.953e+05	7.338e+05	7.596e+05	6.101e+05	7.15e+05	7.285e+05	1.05e+06	1.43e+05	8.8e+05	3.614e+05	1.254e+06	8.928e+05	1.191e+06	8.495e+05	8.271e+05	6.775e+05	7.268e+05	1.772e+05	1.153e+05	1.787e+05	6.371e+05	3.423e+05	6.142e+04	6.011e+05	2.315e+05	1.835e+05	6.573e+05	5.279e+05	5.665e+04	5.95e+05	8.538e+04	3.153e+05	4.89e+05	1.186e+06	1.093e+06	1.074e+06	1.093e+06	8.027e+05	1.785e+05	5.373e+05	2.359e+05	4.438e+05	2.825e+05	9.746e+05	2.874e+05	2.532e+05	9.823e+04	8.759e+05	2.063e+05	9.176e+05	1.609e+05	6.84e+05	7.525e+05	3.217e+05	9.382e+05	9.439e+05	5.543e+05	7.719e+05	1.175e+06	8.387e+05	4.482e+05	7.867e+05	1.227e+05	3.956e+05	1.734e+05	3.56e+05	4.811e+05	7.907e+05	5.684e+05	6.381e+05	1.61e+05	2.722e+05	2.906e+05	5.3e+05	6.274e+05	1.737e+05	4.887e+05	2.267e+05	2.179e+05	1.343e+05	1.247e+05	2.951e+05	3.14e+05	5.497e+05	6.152e+04	4378	5.49e+05	3.376e+05	7.562e+04	7.571e+05	9.42e+05	6.478e+05	1.885e+05	1.71e+05	2.539e+05	2.627e+05	4.903e+05	8.051e+05	4.053e+05	2.677e+05	7.302e+05	1.172e+06	6.597e+05	9.577e+04	3.68e+05	8.421e+05	5.01e+05	4.371e+05	1.146e+05	1.552e+05	7.284e+05	7.912e+05	2.03e+05	4.534e+05	1.644e+05	2.57e+05	4.511e+04	2.786e+05	7.082e+04	5.077e+05	3.409e+05	7.142e+05	9.243e+05	9.427e+05	1.277e+06	7.793e+05	2.421e+05	6.043e+05	5.475e+05	5.361e+05	4.582e+05	6.083e+05	5.939e+05	5.903e+05	8.372e+05	8.646e+05	8.714e+05	7.418e+05	1.034e+06	1.009e+06	2.182e+05	8.056e+05	8.806e+05	1.071e+06	9.444e+05	2.081e+05	9.184e+04	8.991e+05	4.28e+05	1.096e+05	4.818e+05	3.542e+05	3.351e+05	6.263e+04	2.833e+05	4.622e+05	3.423e+05	8.887e+04	6.24e+04	6.24e+04	3.696e+05	2.173e+05	3.621e+05	3.824e+05	3.084e+05	3.711e+05	2.907e+05	3.103e+05	1.48e+05	1.908e+05	6.57e+04	6.943e+05	2.513e+05	1.941e+05	4.914e+05	3.392e+05	3.436e+05	8.157e+05	7.484e+05	4.679e+05	4.681e+04	5.06e+05	3.458e+05	3.265e+05	5.13e+05	4.154e+05	6.163e+04	3.083e+05	1.662e+05	7.637e+04	6.854e+04	6.854e+04	5.217e+04	1.29e+04	8740	8740	8740	nan
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_maz.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_maz.gz
new file mode 100644
index 0000000000..615e442569
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_maz.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_maz.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_maz.tab
new file mode 100644
index 0000000000..648f61f221
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_maz.tab
@@ -0,0 +1,19 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw4	input_computeMatrix_bw4
+4.437e+05	5.346e+05	3.574e+05	9.631e+05	2.487e+05	3.483e+05	4.437e+05	0
+4.063e+05	5.453e+05	3.916e+05	8.403e+05	4.173e+05	3.727e+05	4.063e+05	5.453e+05
+2.016e+05	1.534e+05	2.309e+05	1.035e+05	1.305e+05	2.178e+05	2.016e+05	1.534e+05
+1.524e+05	1.631e+05	5.082e+04	1.529e+05	6.736e+04	1.414e+05	1.524e+05	1.631e+05
+1.738e+05	1.24e+05	1.464e+05	1.509e+05	1.593e+05	7.276e+04	1.738e+05	1.24e+05
+1.55e+05	1.497e+05	9.8e+04	1.365e+05	2.472e+05	5.077e+04	1.55e+05	1.497e+05
+2.887e+05	3.528e+05	5.175e+05	2.392e+05	3.994e+05	4.456e+05	2.887e+05	3.528e+05
+1.604e+05	1.497e+05	7.005e+04	1.61e+05	9.725e+04	1.19e+05	1.604e+05	1.497e+05
+3.336e+05	3.849e+05	4.195e+05	3.587e+05	4.268e+05	3.999e+05	3.336e+05	3.849e+05
+1.534e+05	2.016e+05	1.035e+05	2.309e+05	2.178e+05	1.305e+05	1.534e+05	2.016e+05
+8554	1.187e+05	1.213e+04	4.546e+04	2595	2.751e+04	8554	1.187e+05
+3.058e+05	3.389e+05	3.02e+05	2.243e+05	3.807e+05	4.111e+05	3.058e+05	3.389e+05
+5.699e+05	4.667e+05	5.692e+05	7.361e+05	6.319e+05	3.086e+05	5.699e+05	4.667e+05
+4.378e+05	6.431e+05	5.011e+05	9.958e+05	3.867e+05	5.353e+05	2.689e+05	0
+2.641e+05	3.154e+05	3.885e+05	4.542e+05	4.015e+05	3.915e+05	2.641e+05	3.154e+05
+6950	1.155e+05	9345	4.72e+04	2591	2.627e+04	6950	1.155e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_sampleslabel.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_sampleslabel.gz
new file mode 100644
index 0000000000..08a6e137c5
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_sampleslabel.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_sampleslabel.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_sampleslabel.tab
new file mode 100644
index 0000000000..44e2335d19
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_sampleslabel.tab
@@ -0,0 +1,19 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	a	a	b	b	c	c	d	d
+4.437e+05	5.346e+05	3.574e+05	9.631e+05	2.487e+05	3.483e+05	4.437e+05	nan
+4.063e+05	5.453e+05	3.916e+05	8.403e+05	4.173e+05	3.727e+05	4.063e+05	5.453e+05
+2.016e+05	1.534e+05	2.309e+05	1.035e+05	1.305e+05	2.178e+05	2.016e+05	1.534e+05
+1.524e+05	1.631e+05	5.082e+04	1.529e+05	6.736e+04	1.414e+05	1.524e+05	1.631e+05
+1.738e+05	1.24e+05	1.464e+05	1.509e+05	1.593e+05	7.276e+04	1.738e+05	1.24e+05
+1.55e+05	1.497e+05	9.8e+04	1.365e+05	2.472e+05	5.077e+04	1.55e+05	1.497e+05
+2.887e+05	3.528e+05	5.175e+05	2.392e+05	3.994e+05	4.456e+05	2.887e+05	3.528e+05
+1.604e+05	1.497e+05	7.005e+04	1.61e+05	9.725e+04	1.19e+05	1.604e+05	1.497e+05
+3.336e+05	3.849e+05	4.195e+05	3.587e+05	4.268e+05	3.999e+05	3.336e+05	3.849e+05
+1.534e+05	2.016e+05	1.035e+05	2.309e+05	2.178e+05	1.305e+05	1.534e+05	2.016e+05
+2.138e+04	1.187e+05	3.033e+04	4.546e+04	6488	2.751e+04	2.138e+04	1.187e+05
+3.058e+05	3.389e+05	3.02e+05	2.243e+05	3.807e+05	4.111e+05	3.058e+05	3.389e+05
+5.699e+05	4.667e+05	5.692e+05	7.361e+05	6.319e+05	3.086e+05	5.699e+05	4.667e+05
+4.378e+05	6.431e+05	5.011e+05	9.958e+05	3.867e+05	5.353e+05	4.246e+05	nan
+2.641e+05	3.154e+05	3.885e+05	4.542e+05	4.015e+05	3.915e+05	2.641e+05	3.154e+05
+1.895e+04	1.155e+05	2.549e+04	4.72e+04	7067	2.627e+04	1.895e+04	1.155e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_scale.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_scale.gz
new file mode 100644
index 0000000000..73d2c0d5a3
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_scale.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_scale.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_scale.tab
new file mode 100644
index 0000000000..e4522be770
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_scale.tab
@@ -0,0 +1,19 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8
+#downstream:30	upstream:30	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw4	input_computeMatrix_bw4
+1.331e+06	1.604e+06	1.072e+06	2.889e+06	7.462e+05	1.045e+06	1.331e+06	nan
+1.219e+06	1.636e+06	1.175e+06	2.521e+06	1.252e+06	1.118e+06	1.219e+06	1.636e+06
+6.047e+05	4.603e+05	6.926e+05	3.106e+05	3.914e+05	6.534e+05	6.047e+05	4.603e+05
+4.571e+05	4.892e+05	1.525e+05	4.587e+05	2.021e+05	4.241e+05	4.571e+05	4.892e+05
+5.213e+05	3.721e+05	4.393e+05	4.528e+05	4.778e+05	2.183e+05	5.213e+05	3.721e+05
+4.651e+05	4.491e+05	2.94e+05	4.096e+05	7.417e+05	1.523e+05	4.651e+05	4.491e+05
+8.661e+05	1.059e+06	1.552e+06	7.177e+05	1.198e+06	1.337e+06	8.661e+05	1.059e+06
+4.812e+05	4.491e+05	2.102e+05	4.829e+05	2.917e+05	3.571e+05	4.812e+05	4.491e+05
+1.001e+06	1.155e+06	1.259e+06	1.076e+06	1.281e+06	1.2e+06	1.001e+06	1.155e+06
+4.603e+05	6.047e+05	3.106e+05	6.926e+05	6.534e+05	3.914e+05	4.603e+05	6.047e+05
+6.415e+04	3.561e+05	9.099e+04	1.364e+05	1.947e+04	8.254e+04	6.415e+04	3.561e+05
+9.174e+05	1.017e+06	9.06e+05	6.728e+05	1.142e+06	1.233e+06	9.174e+05	1.017e+06
+1.71e+06	1.4e+06	1.708e+06	2.208e+06	1.896e+06	9.258e+05	1.71e+06	1.4e+06
+1.314e+06	1.929e+06	1.503e+06	2.987e+06	1.16e+06	1.606e+06	1.274e+06	nan
+7.923e+05	9.463e+05	1.165e+06	1.363e+06	1.204e+06	1.175e+06	7.923e+05	9.463e+05
+5.686e+04	3.464e+05	7.646e+04	1.416e+05	2.12e+04	7.881e+04	5.686e+04	3.464e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_skipzeros.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_skipzeros.gz
new file mode 100644
index 0000000000..08f2a27d86
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_skipzeros.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_skipzeros.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_skipzeros.tab
new file mode 100644
index 0000000000..cf767e688b
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_skipzeros.tab
@@ -0,0 +1,19 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8
+#downstream:210	upstream:210	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4
+4.758e+05	3.475e+05	2.994e+05	4.01e+05	5.507e+05	5.613e+05	4.437e+05	5.346e+05	7.859e+05	8.554e+05	7.217e+05	6.469e+05	6.095e+05	5.239e+05	4.931e+05	2.561e+05	3.135e+05	3.155e+05	5.46e+05	6.899e+05	3.574e+05	9.631e+05	5.99e+05	7.185e+05	3.533e+05	4.714e+05	3.41e+05	5.75e+05	3.635e+05	3.866e+05	3.937e+05	5.261e+05	5.259e+05	5.165e+05	2.487e+05	3.483e+05	1.016e+06	1.102e+06	5.966e+05	1.02e+06	7.227e+05	6.667e+05	4.758e+05	3.475e+05	2.994e+05	4.01e+05	5.507e+05	5.613e+05	4.437e+05	nan	nan	nan	nan	nan	nan	4.812e+05
+4.918e+05	4.918e+05	7.057e+05	7.378e+05	4.972e+05	3.422e+05	4.063e+05	5.453e+05	5.56e+05	5.453e+05	4.812e+05	5.293e+05	6.897e+05	7.431e+05	4.471e+05	4.75e+05	9.974e+05	9.921e+05	5.575e+05	5.685e+05	3.916e+05	8.403e+05	7.828e+05	5.726e+05	5.772e+05	2.349e+05	7.823e+05	1.26e+06	4.865e+05	5.426e+05	6.795e+05	9.726e+05	6.018e+05	4.417e+05	4.173e+05	3.727e+05	4.302e+05	9.058e+05	6.54e+05	4.519e+05	1.012e+06	7.023e+04	4.918e+05	4.918e+05	7.057e+05	7.378e+05	4.972e+05	3.422e+05	4.063e+05	5.453e+05	5.56e+05	5.453e+05	4.812e+05	5.293e+05	6.897e+05	7.431e+05
+2.518e+05	3.106e+05	3.523e+05	4.036e+05	3.154e+05	2.689e+05	2.016e+05	1.534e+05	1.449e+05	1.347e+05	1.679e+05	1.443e+05	6.118e+04	nan	3.225e+05	2.816e+05	4.781e+05	2.637e+05	4.553e+05	3.978e+05	2.309e+05	1.035e+05	1.299e+05	1.972e+05	7.202e+04	3.159e+04	4.644e+04	nan	2.729e+05	3.364e+05	3.869e+05	5.208e+05	3.903e+05	4.12e+05	1.305e+05	2.178e+05	5.495e+04	8.165e+04	1.452e+05	3.748e+04	1.264e+04	nan	2.518e+05	3.106e+05	3.523e+05	4.036e+05	3.154e+05	2.689e+05	2.016e+05	1.534e+05	1.449e+05	1.347e+05	1.679e+05	1.443e+05	6.118e+04	nan
+nan	nan	nan	nan	2.673e+04	1.283e+05	1.524e+05	1.631e+05	1.283e+05	1.47e+05	1.898e+05	2.245e+05	3.128e+05	3.635e+05	nan	nan	nan	nan	4.099e+04	4.026e+04	5.082e+04	1.529e+05	1.348e+05	1.262e+05	1.98e+05	3.096e+05	4.374e+05	3.837e+05	nan	nan	nan	nan	5215	3.125e+04	6.736e+04	1.414e+05	6.917e+04	1.174e+05	1.673e+05	2.954e+05	3.859e+05	5.178e+05	nan	nan	nan	nan	2.673e+04	1.283e+05	1.524e+05	1.631e+05	1.283e+05	1.47e+05	1.898e+05	2.245e+05	3.128e+05	3.635e+05
+nan	nan	nan	1.895e+04	1.155e+05	1.459e+05	1.738e+05	1.24e+05	1.449e+05	1.834e+05	2.16e+05	3.106e+05	3.464e+05	3.924e+05	nan	nan	nan	2.549e+04	4.72e+04	3.544e+04	1.464e+05	1.509e+05	1.34e+05	1.663e+05	2.91e+05	4.29e+05	4.213e+05	3.393e+05	nan	nan	nan	7067	2.627e+04	4.345e+04	1.593e+05	7.276e+04	9.199e+04	1.962e+05	2.61e+05	3.757e+05	4.974e+05	3.716e+05	nan	nan	nan	1.895e+04	1.155e+05	1.459e+05	1.738e+05	1.24e+05	1.449e+05	1.834e+05	2.16e+05	3.106e+05	3.464e+05	3.924e+05
+2.994e+05	3.475e+05	4.117e+05	3.154e+05	2.833e+05	2.032e+05	1.55e+05	1.497e+05	1.283e+05	1.711e+05	1.443e+05	6.95e+04	nan	nan	2.857e+05	5.077e+05	2.324e+05	4.585e+05	4.255e+05	2.28e+05	9.8e+04	1.365e+05	2.128e+05	7.286e+04	3.159e+04	4.496e+04	nan	nan	3.312e+05	3.816e+05	5.111e+05	3.868e+05	4.436e+05	1.302e+05	2.472e+05	5.077e+04	6.564e+04	1.657e+05	3.748e+04	1.512e+04	nan	nan	2.994e+05	3.475e+05	4.117e+05	3.154e+05	2.833e+05	2.032e+05	1.55e+05	1.497e+05	1.283e+05	1.711e+05	1.443e+05	6.95e+04	nan	nan
+3.154e+05	4.117e+05	3.475e+05	2.994e+05	2.566e+05	2.406e+05	2.887e+05	3.528e+05	4.705e+05	5.079e+05	5.72e+05	5.988e+05	5.988e+05	5.453e+05	4.585e+05	2.324e+05	5.077e+05	2.857e+05	2.906e+05	3.628e+05	5.175e+05	2.392e+05	5.41e+05	5.443e+05	3.491e+05	9.345e+05	5.588e+05	5.417e+05	3.868e+05	5.111e+05	3.816e+05	3.312e+05	2.589e+05	1.973e+05	3.994e+05	4.456e+05	5.837e+05	4.771e+05	4.486e+05	3.791e+05	3.873e+05	5.687e+05	3.154e+05	4.117e+05	3.475e+05	2.994e+05	2.566e+05	2.406e+05	2.887e+05	3.528e+05	4.705e+05	5.079e+05	5.72e+05	5.988e+05	5.988e+05	5.453e+05
+nan	nan	nan	nan	3.208e+04	1.443e+05	1.604e+05	1.497e+05	1.337e+05	1.497e+05	1.978e+05	2.352e+05	3.154e+05	3.849e+05	nan	nan	nan	nan	5.164e+04	3.159e+04	7.005e+04	1.61e+05	1.145e+05	1.164e+05	2.376e+05	3.329e+05	4.479e+05	3.367e+05	nan	nan	nan	nan	3941	3.748e+04	9.725e+04	1.19e+05	6.468e+04	1.491e+05	1.311e+05	3.383e+05	3.986e+05	5.434e+05	nan	nan	nan	nan	3.208e+04	1.443e+05	1.604e+05	1.497e+05	1.337e+05	1.497e+05	1.978e+05	2.352e+05	3.154e+05	3.849e+05
+6.49e+05	4.876e+05	4.747e+05	6.715e+05	7.463e+05	5.998e+05	3.336e+05	3.849e+05	5.196e+05	5.56e+05	5.453e+05	4.983e+05	5.036e+05	6.341e+05	7.247e+05	4.489e+05	5.014e+05	6.969e+05	1.064e+06	8.579e+05	4.195e+05	3.587e+05	7.886e+05	7.512e+05	6.176e+05	7.195e+05	2.314e+05	4.914e+05	5.043e+05	5.134e+05	2.952e+05	8.485e+05	7.36e+05	9.456e+05	4.268e+05	3.999e+05	2.043e+05	5.879e+05	6.985e+05	7.007e+05	5.696e+05	7.192e+05	6.49e+05	4.876e+05	4.747e+05	6.715e+05	7.463e+05	5.998e+05	3.336e+05	3.849e+05	5.196e+05	5.56e+05	5.453e+05	4.983e+05	5.036e+05	6.341e+05
+nan	6.118e+04	1.443e+05	1.679e+05	1.347e+05	1.449e+05	1.534e+05	2.016e+05	2.689e+05	3.154e+05	4.036e+05	3.523e+05	3.106e+05	2.518e+05	nan	4.644e+04	3.159e+04	7.202e+04	1.972e+05	1.299e+05	1.035e+05	2.309e+05	3.978e+05	4.553e+05	2.637e+05	4.781e+05	2.816e+05	3.225e+05	nan	1.264e+04	3.748e+04	1.452e+05	8.165e+04	5.495e+04	2.178e+05	1.305e+05	4.12e+05	3.903e+05	5.208e+05	3.869e+05	3.364e+05	2.729e+05	nan	6.118e+04	1.443e+05	1.679e+05	1.347e+05	1.449e+05	1.534e+05	2.016e+05	2.689e+05	3.154e+05	4.036e+05	3.523e+05	3.106e+05	2.518e+05
+nan	nan	nan	nan	nan	nan	2.138e+04	1.187e+05	1.476e+05	1.711e+05	1.251e+05	1.454e+05	1.85e+05	2.181e+05	nan	nan	nan	nan	nan	nan	3.033e+04	4.546e+04	3.928e+04	1.48e+05	1.469e+05	1.321e+05	1.742e+05	2.957e+05	nan	nan	nan	nan	nan	nan	6488	2.751e+04	4.943e+04	1.548e+05	7.186e+04	9.834e+04	1.89e+05	2.696e+05	nan	nan	nan	nan	nan	nan	2.138e+04	1.187e+05	1.476e+05	1.711e+05	1.251e+05	1.454e+05	1.85e+05	2.181e+05
+8.009e+05	5.752e+05	4.395e+05	5.485e+05	5.549e+05	4.266e+05	3.058e+05	3.389e+05	4.523e+05	5.196e+05	5.646e+05	5.763e+05	6.266e+05	5.507e+05	4.84e+05	9.804e+05	4.045e+05	6.415e+05	5.537e+05	3.908e+05	3.02e+05	2.243e+05	5.059e+05	5.954e+05	8.232e+05	2.973e+05	3.671e+05	5.367e+05	1.052e+06	4.144e+05	3.034e+05	4.17e+05	5.878e+05	5.465e+05	3.807e+05	4.111e+05	4.092e+05	5.818e+05	1.021e+06	3.242e+05	6.161e+05	6.359e+05	nan	nan	4.38e+05	5.485e+05	5.549e+05	4.266e+05	3.058e+05	3.389e+05	4.523e+05	5.196e+05	5.646e+05	5.763e+05	6.266e+05	5.507e+05
+6.341e+05	7.821e+05	7.731e+05	5.539e+05	5.004e+05	4.4e+05	5.699e+05	4.667e+05	4.058e+05	3.266e+05	3.523e+05	3.315e+05	3.486e+05	4.256e+05	9.992e+05	6.51e+05	7.003e+05	3.526e+05	4.883e+05	3.959e+05	5.692e+05	7.361e+05	5.558e+05	4.671e+05	3.839e+05	1.072e+05	2.396e+05	4.601e+05	3.141e+05	4.59e+05	8.406e+05	4.823e+05	3.662e+05	2.981e+05	6.319e+05	3.086e+05	2.878e+05	1.941e+05	3.009e+05	4.372e+05	2.443e+05	6.471e+05	6.341e+05	7.821e+05	7.731e+05	5.539e+05	5.004e+05	4.4e+05	5.699e+05	4.667e+05	4.058e+05	3.266e+05	3.523e+05	3.315e+05	3.486e+05	4.256e+05
+4.127e+05	3.266e+05	3.17e+05	4.71e+05	5.624e+05	5.239e+05	4.378e+05	6.431e+05	8.249e+05	8.201e+05	6.752e+05	6.405e+05	5.908e+05	5.175e+05	5.173e+05	1.942e+05	2.688e+05	5.096e+05	5.748e+05	5.607e+05	5.011e+05	9.958e+05	3.041e+05	7.421e+05	4.063e+05	3.86e+05	5.307e+05	7.23e+05	4.782e+05	4.536e+05	3.605e+05	5.673e+05	6.823e+05	2.668e+05	3.867e+05	5.353e+05	1.124e+06	6.683e+05	7.876e+05	1.034e+06	5.888e+05	5.067e+05	4.127e+05	3.266e+05	3.17e+05	4.71e+05	5.624e+05	5.239e+05	4.246e+05	nan	nan	nan	nan	nan	nan	5.193e+05
+1.443e+05	1.668e+05	1.369e+05	1.433e+05	1.529e+05	2.01e+05	2.641e+05	3.154e+05	4.01e+05	3.539e+05	3.144e+05	2.502e+05	2.513e+05	2.801e+05	3.159e+04	7.174e+04	1.921e+05	1.277e+05	1.054e+05	2.318e+05	3.885e+05	4.542e+05	2.741e+05	4.682e+05	2.803e+05	3.332e+05	3.435e+05	4.933e+05	3.748e+04	1.383e+05	8.699e+04	5.634e+04	2.08e+05	1.306e+05	4.015e+05	3.915e+05	5.24e+05	3.887e+05	3.381e+05	2.776e+05	1.93e+05	3.866e+05	1.443e+05	1.668e+05	1.369e+05	1.433e+05	1.529e+05	2.01e+05	2.641e+05	3.154e+05	4.01e+05	3.539e+05	3.144e+05	2.502e+05	2.513e+05	2.801e+05
+nan	nan	nan	nan	nan	nan	1.895e+04	1.155e+05	1.459e+05	1.738e+05	1.24e+05	1.449e+05	1.834e+05	2.16e+05	nan	nan	nan	nan	nan	nan	2.549e+04	4.72e+04	3.544e+04	1.464e+05	1.509e+05	1.34e+05	1.663e+05	2.91e+05	nan	nan	nan	nan	nan	nan	7067	2.627e+04	4.345e+04	1.593e+05	7.276e+04	9.199e+04	1.962e+05	2.61e+05	nan	nan	nan	nan	nan	nan	1.895e+04	1.155e+05	1.459e+05	1.738e+05	1.24e+05	1.449e+05	1.834e+05	2.16e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_thresh.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_thresh.gz
new file mode 100644
index 0000000000..5d0a3e5031
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_thresh.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/mat_thresh.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_thresh.tab
new file mode 100644
index 0000000000..afc8cbc201
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/mat_thresh.tab
@@ -0,0 +1,14 @@
+#input_computeMatrix_regions1.bed:6	input_computeMatrix_regions2.bed:5
+#downstream:210	upstream:210	body:0	bin size:30	unscaled 5 prime:0	unscaled 3 prime:0
+input_computeMatrix_regions1.bed:6	input_computeMatrix_regions2.bed:5	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw1	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw2	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw3	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4	input_computeMatrix_bw4
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat.gz
new file mode 100644
index 0000000000..77e3438a30
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat.tab
new file mode 100644
index 0000000000..067446c5d3
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat.tab
@@ -0,0 +1,11 @@
+#genes:8
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_ascend.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_ascend.gz
new file mode 100644
index 0000000000..6669b3d156
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_ascend.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_ascend.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_ascend.tab
new file mode 100644
index 0000000000..e1f2e21dbb
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_ascend.tab
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+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12.tab
new file mode 100644
index 0000000000..56149a56cc
--- /dev/null
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	2.502e+04	2.502e+04	2.502e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.557e+05	2.557e+05	2.557e+05	2.557e+05	2.905e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	2.295e+05	1.337e+05	1.337e+05	1.337e+05	1.337e+05	2.384e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	1.733e+05	3439	3439	3439	3439	1.164e+04	1.984e+04	1.984e+04	1.984e+04	1.984e+04	1.785e+05	3.371e+05	3.371e+05	3.371e+05	3.371e+05	2.701e+05	2.031e+05	2.031e+05	2.031e+05	2.031e+05	2.549e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	2.626e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	2.139e+04	2.139e+04	2.139e+04	2.139e+04	2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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12mg.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12mg.gz
new file mode 100644
index 0000000000..38236e2950
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12mg.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12mg.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12mg.tab
new file mode 100644
index 0000000000..f32e9481e4
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bed12mg.tab
@@ -0,0 +1,8 @@
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	2.502e+04	2.502e+04	2.502e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.557e+05	2.557e+05	2.557e+05	2.557e+05	2.905e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	2.295e+05	1.337e+05	1.337e+05	1.337e+05	1.337e+05	2.384e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	1.733e+05	3439	3439	3439	3439	1.164e+04	1.984e+04	1.984e+04	1.984e+04	1.984e+04	1.785e+05	3.371e+05	3.371e+05	3.371e+05	3.371e+05	2.701e+05	2.031e+05	2.031e+05	2.031e+05	2.031e+05	2.549e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	2.626e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.18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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bl.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bl.gz
new file mode 100644
index 0000000000..7ceae2e8be
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bl.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bl.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bl.tab
new file mode 100644
index 0000000000..71ffccfe27
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_bl.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1:8	input_computeMatrix_regions2:8	input_computeMatrix_regions3:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_desc.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_desc.gz
new file mode 100644
index 0000000000..63d8931ea5
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_desc.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_desc.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_desc.tab
new file mode 100644
index 0000000000..ef2ce6edc6
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_desc.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	5.196e+05	7.23e+05	8.385e+05	8.217e+05	6.864e+05	6.48e+05	6.095e+05	5.581e+05	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05	2.616e+05	4.103e+05	4.383e+05	1.731e+05	4.412e+05	2.501e+05	3.76e+05	4.27e+05	5.175e+05	3.214e+05	2.147e+05	5.588e+05	7.091e+05	2.686e+05	9.378e+05	6.918e+05	3.514e+05	5.597e+05	3.724e+05	2.497e+05	6.477e+05	6.206e+05	6.817e+05	5.193e+05	2.37e+05	3.573e+05	1.286e+05	6.129e+05	5.864e+05	6.181e+05	3.451e+05	9.179e+05	8.843e+05	1.906e+05	7.744e+05	4.285e+05	5.146e+05	2.434e+05	5.107e+05	8.407e+05	5.425e+05	1.658e+05	4.258e+05	5.02e+05	3.575e+05	2.766e+05	6.116e+05	2.224e+05	4.005e+05	4.605e+05	2.616e+05	5.655e+05	9.173e+05	1.306e+06	5.128e+05	2.218e+05	5.08e+05	6.651e+05	7.656e+05	7.244e+05	7.988e+05	4.262e+05	4.642e+05	5.496e+05	2.491e+05	1.174e+06	9.009e+05	8.651e+05	7.893e+05	5.541e+05	5.085e+05	2.946e+05	5.358e+05	2.912e+05	2.38e+05	3.56e+05	1.442e+05	3.515e+05	3.994e+05	3.657e+05	5.99e+05	4.125e+05	6.591e+05	3.828e+05	3.353e+05	4.96e+05	2.479e+05	6.072e+05	6.313e+05	3.908e+05	7.219e+05	8.847e+05	5.182e+05	4.54e+05	3.751e+05	4.592e+05	3.698e+05	5.801e+05	7.189e+05	3.127e+05	2.308e+05	3.954e+05	8.206e+05	1.258e+06	5.797e+05	7.784e+05	1.056e+06	7.101e+05	5.756e+05	5.5e+05	4.893e+05	2.118e+05	2.624e+05	3.51e+05	2.984e+05	3.883e+05	2.763e+05	3.965e+05	3.064e+05	7.213e+05	5.487e+05	9.28e+05	4.585e+05	4.816e+05	7.69e+05	4.444e+05	5.978e+05	9.439e+05	5.861e+05	6.012e+05	1.46e+05	3.623e+05	3.283e+05	5.979e+05	2.213e+05	1.363e+06	7.775e+05	8.227e+05	7.513e+05	2.591e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	4.17e+05	nan	nan	nan	nan	nan	nan	nan	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05
+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.33e+05	6.278e+05	8.122e+05	8.435e+05	7.137e+05	6.451e+05	6.14e+05	5.453e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	8.928e+04	1.437e+05	1.64e+05	1.407e+05	1.143e+05	2.262e+05	4.234e+05	4.53e+05	2.924e+05	4.351e+05	2.913e+05	3.816e+05	2.818e+05	4.328e+05	3.756e+05	2.613e+05	5.973e+05	5.977e+05	3.456e+05	9.047e+05	6.549e+05	4.235e+05	4.511e+05	3.519e+05	3.201e+05	8.762e+05	5.864e+05	4.554e+05	3.166e+05	3.548e+05	1.243e+05	5.85e+05	6.55e+05	5.454e+05	4.976e+05	1.013e+06	3.917e+05	7.999e+05	3.752e+05	4.857e+05	2.745e+05	5.496e+05	7.808e+05	4.225e+05	2.598e+05	4.877e+05	3.72e+05	2.307e+05	6.442e+05	2.96e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	1.271e+05	1.372e+05	7.565e+04	6.91e+04	2.472e+05	1.374e+05	4.29e+05	3.643e+05	5.28e+05	3.863e+05	3.518e+05	2.861e+05	2.239e+05	3.122e+05	3.683e+05	5.231e+05	5.202e+05	5.334e+05	4.432e+05	3.329e+05	4.652e+05	3.622e+05	6.531e+05	5.516e+05	3.102e+05	1.045e+06	6.657e+05	3.13e+05	4.069e+05	4.768e+05	3.648e+05	5.06e+05	7.55e+05	2.744e+05	4.167e+05	4.607e+05	1.056e+06	9.155e+05	6.409e+05	1.004e+06	7.568e+05	6.221e+05	5.132e+05	3.487e+05	2.406e+05	2.319e+05	4.031e+05	3.495e+05	3.509e+05	3.323e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.236e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
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+2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	5.079e+05	7.481e+05	8.495e+05	7.398e+05	6.458e+05	6.136e+05	5.267e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05	4.6e+04	3.939e+04	3.159e+04	7.197e+04	1.287e+05	2.032e+05	9.229e+04	1.671e+05	9.075e+04	2.463e+05	3.189e+05	4.421e+05	3.496e+05	4.012e+05	2.764e+05	3.905e+05	3.193e+05	4.649e+05	3.481e+05	3.906e+05	6.323e+05	3.951e+05	7.939e+05	6.343e+05	4.906e+05	3.602e+05	3.116e+05	6.24e+05	6.331e+05	4.967e+05	4.27e+05	3.429e+05	1.813e+05	5.57e+05	6.723e+05	4.321e+05	8.49e+05	7.309e+05	5.605e+05	4.714e+05	4.704e+05	3.282e+05	5.831e+05	7.72e+05	1.927e+05	4.237e+05	5.04e+05	2.286e+05	5.576e+05	3.017e+05	3.845e+05	4.021e+05	3.834e+05	7.39e+05	1.299e+06	4.869e+05	2.31e+05	7.417e+05	6.365e+05	7.484e+05	7.834e+05	3.855e+05	4.87e+05	4.994e+05	3.617e+05	1.174e+06	9.278e+05	8.47e+05	7.408e+05	5.18e+05	4615	3.187e+04	3.748e+04	1.002e+05	1.65e+05	7.499e+04	5.974e+04	8.493e+04	2.645e+05	7.494e+04	3.126e+05	3.9e+05	5.326e+05	3.962e+05	3.569e+05	3.045e+05	1.876e+05	3.716e+05	3.976e+05	5.907e+05	5.215e+05	4.584e+05	3.248e+05	4.48e+05	4.784e+05	4.991e+05	5.089e+05	6.781e+05	7.068e+05	4.551e+05	4.725e+05	4.838e+05	3.988e+05	4.924e+05	6.316e+05	2.556e+05	3.735e+05	8.769e+05	1.154e+06	5.802e+05	9.715e+05	7.596e+05	6.706e+05	3.576e+05	3.543e+05	2.332e+05	4.039e+05	2.694e+05	3.802e+05	3.132e+05	3.105e+05	7.053e+05	7.676e+05	6.738e+05	4.082e+05	7.087e+05	5.844e+05	7.164e+05	6.516e+05	5.946e+05	1.45e+05	3.955e+05	3.354e+05	5.455e+05	3.502e+05	1.363e+06	6.888e+05	8.144e+05	7.242e+05	2.651e+05	2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	4.17e+05	nan	nan	nan	nan	nan	4.812e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05
+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
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+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmg.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmg.gz
new file mode 100644
index 0000000000..4fea720c81
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmg.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmg.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmg.tab
new file mode 100644
index 0000000000..77c2291c69
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmg.tab
@@ -0,0 +1,9 @@
+#genes:6
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	2.502e+04	2.502e+04	2.502e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.557e+05	2.557e+05	2.557e+05	2.557e+05	2.905e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	2.295e+05	1.337e+05	1.337e+05	1.337e+05	1.337e+05	2.384e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	1.733e+05	3439	3439	3439	3439	1.164e+04	1.984e+04	1.984e+04	1.984e+04	1.984e+04	1.785e+05	3.371e+05	3.371e+05	3.371e+05	3.371e+05	2.701e+05	2.031e+05	2.031e+05	2.031e+05	2.031e+05	2.549e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	2.626e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	2.139e+04	2.139e+04	2.139e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	2.688e+04	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.182e+05	1.1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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmgid.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmgid.gz
new file mode 100644
index 0000000000..a06351e10e
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmgid.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmgid.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_gtfmgid.tab
new file mode 100644
index 0000000000..fbb5a736b6
--- /dev/null
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_label.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_label.gz
new file mode 100644
index 0000000000..9dc289e6e2
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_label.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_label.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_label.tab
new file mode 100644
index 0000000000..631c590bb9
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_label.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:140	upstream:70	body:420	bin size:35	unscaled 5 prime:35	unscaled 3 prime:70
+input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	some_sample	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	another_one	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	athird	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed	this_one_failed
+5.636e+05	4.537e+05	5.659e+05	8.084e+05	8.272e+05	6.741e+05	6.342e+05	5.716e+05	5.045e+05	3.786e+05	3.572e+05	4.578e+05	4.967e+05	4.471e+05	4.598e+05	5.545e+05	5.82e+05	7.034e+05	7.492e+05	6.713e+05	5.064e+05	6.74e+05	4.138e+05	9.561e+05	4.3e+05	6.777e+05	4.335e+05	3.239e+05	5.21e+05	7.751e+05	3.516e+05	3.536e+05	5.262e+05	2.189e+05	5.61e+05	2.492e+05	5.075e+05	2.923e+05	5.197e+05	1.154e+06	7.209e+05	2.479e+05	6.423e+05	2.593e+05	4.779e+05	1.089e+06	7.589e+05	7.98e+05	9.55e+05	5.943e+05	5.603e+05	3.449e+05	2.514e+05	3.908e+05	2.66e+05	3.532e+05	3.634e+05	3.862e+05	6.353e+05	9.025e+05	1.728e+05	9.235e+05	5.7e+05	5.636e+05	4.537e+05	nan	nan	nan	nan	nan	nan	5.042e+05	3.786e+05	3.572e+05	4.578e+05	4.967e+05	4.471e+05	4.598e+05	5.545e+05	5.82e+05	7.034e+05	7.492e+05	6.713e+05	5.064e+05
+3.345e+05	3.987e+05	5.453e+05	5.35e+05	6.852e+05	4.889e+05	4.196e+05	6.201e+05	6.533e+05	4.452e+05	4.951e+05	5.879e+05	5.219e+05	2.716e+05	3.469e+05	2.131e+05	1.627e+05	1.443e+05	1.443e+05	1.581e+05	1.169e+05	4.143e+05	4.222e+05	7.832e+05	5.31e+05	7.098e+05	4.097e+05	4.161e+05	4.697e+05	6.53e+05	4.464e+05	5.439e+05	4.599e+05	5.325e+05	3.686e+05	3.861e+05	2.816e+05	1.202e+05	1.449e+05	1.659e+05	6.456e+04	4.645e+04	3.812e+05	3.762e+05	3.564e+05	6.434e+05	6.541e+05	3.635e+05	3.342e+05	7.236e+05	6.636e+05	4.972e+05	5.786e+05	4.88e+05	4.717e+05	3.078e+05	4.173e+05	2.205e+05	2.161e+05	5.533e+04	1.138e+05	8.871e+04	2.68e+04	3.345e+05	3.987e+05	5.453e+05	5.35e+05	6.852e+05	4.889e+05	4.196e+05	5.112e+05	4.5e+05	4.452e+05	4.951e+05	5.879e+05	5.219e+05	2.716e+05	3.469e+05	2.131e+05	1.627e+05	1.443e+05	1.443e+05	1.581e+05	1.169e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+9.852e+04	1.512e+05	1.558e+05	1.706e+05	3.485e+05	2.697e+05	4.374e+05	5.832e+05	5.818e+05	4.01e+05	4.957e+05	7.013e+05	6.124e+05	4.112e+05	4.709e+05	5.545e+05	5.82e+05	7.034e+05	7.492e+05	6.713e+05	5.064e+05	4.475e+04	4.807e+04	1.59e+05	1.829e+05	4.04e+05	3.502e+05	4.766e+05	5.819e+05	4.489e+05	4.332e+05	4.871e+05	6.66e+05	4.641e+05	4.488e+05	3.812e+05	5.075e+05	2.923e+05	5.197e+05	1.154e+06	7.209e+05	2.479e+05	2.256e+04	6.309e+04	1.33e+05	1.603e+05	4.339e+05	2.874e+05	5.178e+05	4.158e+05	6.185e+05	4.313e+05	4.688e+05	7.234e+05	7.958e+05	2.969e+05	3.706e+05	3.862e+05	6.353e+05	9.025e+05	1.728e+05	9.235e+05	5.7e+05	9.852e+04	1.512e+05	1.558e+05	1.706e+05	3.485e+05	2.697e+05	4.374e+05	5.832e+05	5.818e+05	4.01e+05	4.957e+05	4.17e+05	4.812e+05	4.112e+05	4.709e+05	5.545e+05	5.82e+05	7.034e+05	7.492e+05	6.713e+05	5.064e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+2.612e+05	2.795e+05	3.62e+05	5.346e+05	5.796e+05	5.711e+05	3.844e+05	5.051e+05	6.598e+05	6.743e+05	4.473e+05	4.549e+05	5.072e+05	6.993e+05	5.453e+05	5.453e+05	5.453e+05	3.987e+05	3.345e+05	6.37e+05	7.332e+05	3.176e+05	4.916e+05	2.158e+05	5.681e+05	5.483e+05	5.264e+05	3.807e+05	5.14e+05	6.16e+05	4.89e+05	4.928e+05	4.054e+05	4.029e+05	7.911e+05	4.567e+05	7.481e+05	7.832e+05	4.222e+05	4.143e+05	9.675e+05	8.414e+05	2.032e+05	3.857e+05	4.685e+05	4.639e+05	4.775e+05	6.303e+05	4.314e+05	4.982e+05	7.43e+05	7.466e+05	4.241e+05	3.385e+05	4.332e+05	6.197e+05	6.755e+05	5.67e+05	3.564e+05	3.762e+05	3.812e+05	1.079e+06	7.197e+05	2.612e+05	2.795e+05	3.62e+05	5.346e+05	5.796e+05	5.711e+05	3.844e+05	5.051e+05	4.241e+05	nan	4.263e+05	4.549e+05	5.072e+05	6.993e+05	5.453e+05	5.453e+05	5.453e+05	3.987e+05	3.345e+05	6.37e+05	7.332e+05
+1.169e+05	1.581e+05	1.443e+05	1.77e+05	3.514e+05	2.672e+05	4.444e+05	5.839e+05	5.809e+05	3.98e+05	4.976e+05	7.042e+05	6.112e+05	4.112e+05	4.709e+05	5.545e+05	5.82e+05	7.034e+05	7.492e+05	6.713e+05	5.064e+05	4.645e+04	6.456e+04	1.659e+05	1.9e+05	4.022e+05	3.551e+05	4.693e+05	5.861e+05	4.572e+05	4.224e+05	4.918e+05	6.679e+05	4.631e+05	4.488e+05	3.812e+05	5.075e+05	2.923e+05	5.197e+05	1.154e+06	7.209e+05	2.479e+05	2.68e+04	8.871e+04	1.138e+05	1.685e+05	4.337e+05	2.907e+05	5.15e+05	4.143e+05	6.203e+05	4.354e+05	4.671e+05	7.291e+05	7.946e+05	2.969e+05	3.706e+05	3.862e+05	6.353e+05	9.025e+05	1.728e+05	9.235e+05	5.7e+05	1.169e+05	1.581e+05	1.443e+05	1.77e+05	3.514e+05	2.672e+05	4.444e+05	5.839e+05	5.809e+05	3.98e+05	4.976e+05	4.17e+05	4.812e+05	4.112e+05	4.709e+05	5.545e+05	5.82e+05	7.034e+05	7.492e+05	6.713e+05	5.064e+05
+6.576e+05	3.441e+05	3.918e+05	5.362e+05	5.466e+05	5.27e+05	5.028e+05	6.706e+05	7.511e+05	6.819e+05	5.848e+05	5.368e+05	4.361e+05	4.829e+05	5.008e+05	3.712e+05	3.62e+05	4.839e+05	5.435e+05	6.287e+05	6.617e+05	1.03e+06	4.009e+05	4.117e+05	7.881e+05	7.292e+05	6.672e+05	2.743e+05	7.25e+05	1.116e+06	4.95e+05	3.664e+05	3.761e+05	3.786e+05	3.877e+05	4.011e+05	4.738e+05	2.127e+05	7.412e+05	6.093e+05	2.811e+05	4.7e+05	1.164e+06	4.017e+05	3.706e+05	3.459e+05	5.672e+05	7.974e+05	5.448e+05	8.845e+05	2.116e+05	8.71e+05	6.993e+05	3.106e+05	2.918e+05	3.99e+05	3.821e+05	2.306e+05	2.841e+05	4.137e+05	6.741e+05	8.924e+05	8.009e+05	6.576e+05	3.441e+05	3.918e+05	5.362e+05	5.466e+05	5.27e+05	5.028e+05	6.706e+05	7.511e+05	6.819e+05	5.848e+05	5.368e+05	4.361e+05	4.829e+05	5.008e+05	3.712e+05	3.62e+05	4.839e+05	4.812e+05	nan	nan
+1.333e+05	1.544e+05	2.03e+05	3.415e+05	2.706e+05	4.967e+05	5.879e+05	5.287e+05	4.107e+05	6.026e+05	6.83e+05	4.186e+05	4.772e+05	6.435e+05	5.817e+05	5.471e+05	5.389e+05	3.941e+05	3.409e+05	6.507e+05	7.332e+05	1.299e+05	1.261e+05	2.376e+05	4.036e+05	3.463e+05	4.834e+05	5.456e+05	5.478e+05	3.781e+05	5.999e+05	5.103e+05	4.833e+05	3.742e+05	5.721e+05	6.076e+05	7.453e+05	7.997e+05	4.152e+05	4.054e+05	1.009e+06	8.464e+05	6.486e+04	1.925e+05	1.63e+05	4.264e+05	2.971e+05	4.857e+05	4.881e+05	5.818e+05	4.965e+05	5.731e+05	7.786e+05	3.66e+05	3.621e+05	5.846e+05	6.844e+05	5.348e+05	3.527e+05	3.724e+05	3.949e+05	1.136e+06	6.643e+05	1.333e+05	1.544e+05	2.03e+05	3.415e+05	2.706e+05	4.967e+05	5.879e+05	5.287e+05	4.107e+05	4.927e+05	nan	4.119e+05	4.772e+05	6.435e+05	5.817e+05	5.471e+05	5.389e+05	3.941e+05	3.409e+05	6.507e+05	7.332e+05
+nan	2.138e+04	1.224e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.636e+05	1.925e+05	1.86e+05	1.764e+05	1.7e+05	1.604e+05	1.411e+05	1.123e+05	1.333e+05	1.544e+05	2.03e+05	2.933e+05	3.446e+05	3.794e+05	nan	3.033e+04	4.348e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	7.774e+04	1.47e+05	1.042e+05	4.001e+04	1.23e+05	2.475e+05	2.267e+05	1.954e+05	1.299e+05	1.261e+05	2.376e+05	4.268e+05	4.162e+05	3.555e+05	nan	6488	2.894e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	1.092e+05	2.168e+05	2.272e+05	2.428e+05	1.583e+05	3.165e+04	5.204e+04	8.263e+04	6.486e+04	1.925e+05	1.63e+05	3.945e+05	4.672e+05	4.081e+05	nan	2.138e+04	1.224e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.636e+05	1.925e+05	1.86e+05	1.764e+05	1.7e+05	1.604e+05	1.411e+05	1.123e+05	1.333e+05	1.544e+05	2.03e+05	2.933e+05	3.446e+05	3.794e+05
+4.729e+05	3.125e+05	3.451e+05	4.954e+05	5.669e+05	6.039e+05	5.768e+05	5.947e+05	5.169e+05	4.113e+05	2.69e+05	2.569e+05	3.424e+05	3.646e+05	2.594e+05	1.81e+05	1.453e+05	1.324e+05	1.654e+05	1.388e+05	3.029e+04	4.637e+05	2.834e+05	2.728e+05	5.671e+05	6.173e+05	3.142e+05	4.578e+05	7.466e+05	5.566e+05	3.81e+05	4.412e+05	3.349e+05	3.695e+05	3.47e+05	3.553e+05	1.616e+05	1.272e+05	1.91e+05	6.648e+04	3.456e+04	4.809e+04	5.183e+05	3.946e+05	4.204e+05	4.901e+05	7.368e+05	5.126e+05	4.142e+05	4.255e+05	5.147e+05	5.227e+05	3.382e+05	2.573e+05	3.561e+05	4.705e+05	3.415e+05	1.861e+05	7.539e+04	7.491e+04	1.356e+05	3.534e+04	4366	4.729e+05	3.125e+05	3.451e+05	4.954e+05	5.669e+05	6.039e+05	5.768e+05	5.947e+05	5.169e+05	4.113e+05	2.69e+05	2.569e+05	3.424e+05	3.646e+05	2.594e+05	1.81e+05	1.453e+05	1.324e+05	1.654e+05	1.388e+05	3.029e+04
+4.573e+05	5.549e+05	4.688e+05	4.237e+05	5.871e+05	5.604e+05	5.998e+05	5.899e+05	6.99e+05	5.548e+05	6.275e+05	5.845e+05	5.082e+05	5.829e+05	5.621e+05	7.424e+05	4.867e+05	5.018e+05	5.632e+05	4.381e+05	3.07e+05	4.867e+05	4.979e+05	7.645e+05	4.665e+05	5.347e+05	5.897e+05	6.947e+05	5.509e+05	7.714e+05	6.226e+05	5.574e+05	6.392e+05	6.048e+05	5.437e+05	4.772e+05	7.157e+05	7.358e+05	5.052e+05	5.714e+05	4.241e+05	2.985e+05	2.429e+05	6.293e+05	2.652e+05	4.224e+05	6.125e+05	5.406e+05	8.323e+05	4.724e+05	6.381e+05	4.215e+05	6.745e+05	5.705e+05	6.055e+05	5.004e+05	6.068e+05	8.423e+05	3.599e+05	2.417e+05	6.308e+05	5.542e+05	4.087e+05	4.573e+05	5.549e+05	4.688e+05	4.237e+05	5.871e+05	5.604e+05	5.998e+05	5.899e+05	6.99e+05	5.548e+05	6.275e+05	5.845e+05	5.082e+05	5.829e+05	4.202e+05	nan	4.197e+05	5.018e+05	5.632e+05	4.381e+05	3.07e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	1.895e+04	1.196e+05	1.482e+05	2.37e+05	3.38e+05	2.922e+05	5.318e+05	5.9e+05	5.465e+05	3.714e+05	5.191e+05	7.591e+05	5.522e+05	4.157e+05	4.807e+05	4.344e+05	5.361e+05	5.875e+05	6.553e+05	7.556e+05	nan	2.549e+04	4.497e+04	1.24e+05	2.991e+05	3.533e+05	3.49e+05	5.675e+05	5.185e+05	5.207e+05	3.718e+05	6.177e+05	5.574e+05	5.484e+05	3.574e+05	4.283e+05	3.578e+05	3.731e+05	3.762e+05	4.741e+05	1.01e+06	nan	7067	2.787e+04	8.916e+04	2.872e+05	3.902e+05	3.497e+05	4.533e+05	5.155e+05	5.741e+05	4.792e+05	4.055e+05	8.704e+05	6.661e+05	2.987e+05	4.07e+05	2.829e+05	3.134e+05	6.979e+05	8.557e+05	3.292e+05	nan	1.895e+04	1.196e+05	1.482e+05	2.37e+05	3.38e+05	2.922e+05	5.318e+05	5.9e+05	5.465e+05	3.714e+05	5.163e+05	nan	4.804e+05	4.157e+05	4.807e+05	4.344e+05	5.361e+05	5.875e+05	6.553e+05	7.556e+05
+nan	nan	8.019e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.684e+05	1.925e+05	1.925e+05	1.443e+05	1.443e+05	1.627e+05	2.131e+05	3.07e+05	3.712e+05	nan	nan	4.305e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	8.928e+04	1.47e+05	1.47e+05	1.659e+05	1.449e+05	1.202e+05	2.816e+05	4.311e+05	3.537e+05	nan	nan	1.831e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	1.271e+05	2.168e+05	2.168e+05	1.138e+05	5.533e+04	2.161e+05	2.205e+05	3.717e+05	5.176e+05	nan	nan	8.019e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.684e+05	1.925e+05	1.925e+05	1.443e+05	1.443e+05	1.627e+05	2.131e+05	3.07e+05	3.712e+05
+3.166e+05	3.987e+05	3.501e+05	2.687e+05	2.578e+05	2.856e+05	4.096e+05	5.05e+05	5.843e+05	5.895e+05	5.606e+05	6.11e+05	5.707e+05	5.379e+05	4.529e+05	3.276e+05	3.322e+05	5.27e+05	5.591e+05	4.445e+05	6.095e+05	4.508e+05	2.777e+05	4.793e+05	3.039e+05	3.17e+05	4.09e+05	3.557e+05	6.059e+05	5.307e+05	7.452e+05	4.86e+05	3.386e+05	4.862e+05	6.861e+05	5.091e+05	2.284e+05	1.847e+05	5.765e+05	6.864e+05	4.184e+05	9.746e+05	4.199e+05	5.284e+05	3.738e+05	2.846e+05	2.347e+05	3.703e+05	5.42e+05	5.028e+05	3.994e+05	4.443e+05	4.67e+05	5.674e+05	5.36e+05	7.957e+05	4.03e+05	4.421e+05	3.613e+05	5.326e+05	5.656e+05	3.216e+05	5.488e+05	3.166e+05	3.987e+05	3.501e+05	2.687e+05	2.578e+05	2.856e+05	4.096e+05	5.05e+05	5.843e+05	5.895e+05	5.606e+05	6.11e+05	5.707e+05	5.379e+05	4.529e+05	3.276e+05	3.322e+05	5.27e+05	5.591e+05	4.437e+05	nan
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_max.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_max.gz
new file mode 100644
index 0000000000..24ac721ca9
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_max.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_max.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_max.tab
new file mode 100644
index 0000000000..06df6d7c9a
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_max.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.651e+05	7.057e+05	7.378e+05	8.019e+05	7.057e+05	4.651e+05	3.368e+05	3.689e+05	4.33e+05	5.774e+05	5.934e+05	5.934e+05	5.293e+05	5.613e+05	7.698e+05	7.698e+05	7.859e+05	6.576e+05	6.095e+05	5.453e+05	4.812e+05	4.972e+05	5.132e+05	5.132e+05	4.01e+05	4.491e+05	5.613e+05	6.095e+05	6.736e+05	7.378e+05	8.661e+05	8.661e+05	7.859e+05	5.774e+05	5.934e+05	5.774e+05	5.453e+05	3.528e+05	3.689e+05	5.453e+05	5.453e+05	5.934e+05	5.934e+05	6.576e+05	5.774e+05	6.255e+05	6.255e+05	6.415e+05	5.613e+05	4.972e+05	4.17e+05	2.887e+05	3.047e+05	3.047e+05	3.689e+05	4.17e+05	4.17e+05	3.368e+05	3.368e+05	2.085e+05	1.604e+05	1.604e+05	1.443e+05	1.604e+05	1.925e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+04	nan	7.773e+05	1.262e+06	1.443e+06	1.174e+06	1.174e+06	4.505e+05	5.496e+05	6.062e+05	7.292e+05	8.837e+05	1.042e+06	1.042e+06	8.732e+05	3.524e+05	1.443e+06	1.443e+06	1.298e+06	9.006e+05	8.012e+05	4.467e+05	7.429e+05	7.429e+05	7.935e+05	7.935e+05	4.569e+05	8.061e+05	1.043e+06	8.287e+05	7.723e+05	7.723e+05	1.586e+06	7.393e+05	1.052e+06	1.052e+06	7.52e+05	7.94e+05	7.364e+05	5.396e+05	4.971e+05	8.327e+05	8.1e+05	1.013e+06	6.852e+05	5.494e+05	8.091e+05	9.83e+05	1.005e+06	1.005e+06	1.063e+06	7.74e+05	6.04e+05	5.175e+05	4.374e+05	5.11e+05	5.11e+05	6.466e+05	4.869e+05	4.869e+05	4.551e+05	2.534e+05	7.241e+04	2.614e+05	1.954e+05	2.475e+05	1.47e+05	3.159e+04	3.159e+04	8.361e+04	1.968e+04	nan	3.958e+05	1.109e+06	1.17e+06	1.363e+06	1.363e+06	3.69e+05	5.979e+05	5.273e+05	5.299e+05	2.044e+05	8.262e+05	1.012e+06	1.012e+06	8.644e+05	1.492e+06	1.492e+06	1.02e+06	1.02e+06	1.128e+06	5.034e+05	5.034e+05	4.458e+05	8.281e+05	8.281e+05	3.589e+05	6.149e+05	9.541e+05	7.856e+05	1.327e+06	9.223e+05	1.352e+06	1.521e+06	1.256e+06	7.591e+05	3.494e+05	1.096e+06	7.163e+05	5.75e+05	5.75e+05	8.178e+05	1.056e+06	1.132e+06	8.703e+05	8.833e+05	1.021e+06	7.453e+05	7.453e+05	7.773e+05	9.083e+05	6.055e+05	6.055e+05	3.994e+05	3.037e+05	4.409e+05	4.63e+05	6.086e+05	6.133e+05	6.485e+05	6.485e+05	3.353e+05	2.462e+05	5.57e+04	8.263e+04	8.263e+04	2.428e+05	3.748e+04	3.748e+04	3.748e+04	7762	nan	4.651e+05	7.057e+05	7.378e+05	8.019e+05	7.057e+05	4.651e+05	3.368e+05	3.689e+05	4.33e+05	5.774e+05	5.934e+05	5.934e+05	5.293e+05	5.613e+05	7.698e+05	7.698e+05	7.859e+05	6.576e+05	6.095e+05	5.453e+05	4.812e+05	4.972e+05	5.132e+05	5.132e+05	4.01e+05	4.491e+05	5.613e+05	nan	nan	nan	nan	nan	nan	4.33e+05	5.934e+05	5.774e+05	5.453e+05	3.528e+05	3.689e+05	5.453e+05	5.453e+05	5.934e+05	5.934e+05	6.576e+05	5.774e+05	6.255e+05	6.255e+05	6.415e+05	5.613e+05	4.972e+05	4.17e+05	2.887e+05	3.047e+05	3.047e+05	3.689e+05	4.17e+05	4.17e+05	3.368e+05	3.368e+05	2.085e+05	1.604e+05	1.604e+05	1.443e+05	1.604e+05	1.925e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+04	nan
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+nan	nan	nan	nan	nan	4.812e+04	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.604e+05	1.604e+05	1.764e+05	2.085e+05	3.368e+05	3.368e+05	4.17e+05	4.17e+05	3.689e+05	2.887e+05	3.047e+05	2.887e+05	3.047e+05	4.17e+05	4.972e+05	5.613e+05	6.415e+05	6.415e+05	6.255e+05	6.255e+05	5.934e+05	6.576e+05	5.934e+05	5.934e+05	5.934e+05	5.453e+05	4.33e+05	3.528e+05	3.849e+05	5.613e+05	5.934e+05	5.934e+05	4.491e+05	7.538e+05	8.661e+05	8.661e+05	7.698e+05	6.736e+05	6.736e+05	6.095e+05	5.613e+05	4.491e+05	4.01e+05	5.132e+05	5.132e+05	4.972e+05	4.972e+05	4.812e+05	5.613e+05	6.095e+05	5.934e+05	6.576e+05	7.859e+05	7.538e+05	7.698e+05	6.736e+05	5.613e+05	4.972e+05	4.972e+05	5.934e+05	nan	nan	nan	nan	nan	8.361e+04	8.361e+04	3.159e+04	1.47e+05	2.475e+05	2.475e+05	2.614e+05	2.06e+05	2.534e+05	4.551e+05	4.869e+05	4.869e+05	6.466e+05	4.701e+05	5.11e+05	3.146e+05	5.175e+05	5.175e+05	6.04e+05	7.74e+05	1.063e+06	7.515e+05	1.005e+06	9.83e+05	6.233e+05	8.091e+05	5.494e+05	6.852e+05	1.013e+06	1.013e+06	8.327e+05	8.327e+05	5.396e+05	1.718e+05	7.364e+05	7.94e+05	7.52e+05	7.846e+05	1.052e+06	9.139e+05	1.586e+06	5.723e+05	7.723e+05	8.287e+05	8.626e+05	1.043e+06	8.061e+05	3.946e+05	6.865e+05	7.935e+05	5.522e+05	7.429e+05	6.137e+05	4.821e+05	8.012e+05	3.186e+05	9.006e+05	5.19e+05	1.298e+06	1.443e+06	5.481e+05	3.524e+05	3.393e+05	7.844e+05	8.732e+05	nan	nan	nan	nan	nan	7762	3.748e+04	3.748e+04	2.168e+05	2.428e+05	8.263e+04	5.57e+04	3.353e+05	3.353e+05	6.485e+05	6.485e+05	6.133e+05	6.086e+05	6.086e+05	4.409e+05	4.409e+05	3.994e+05	3.994e+05	6.055e+05	6.055e+05	9.083e+05	7.773e+05	6.641e+05	7.453e+05	6.313e+05	1.021e+06	8.833e+05	8.703e+05	1.132e+06	1.132e+06	1.056e+06	8.178e+05	5.75e+05	4.776e+05	7.163e+05	1.096e+06	3.494e+05	7.591e+05	1.256e+06	1.521e+06	1.521e+06	9.223e+05	1.327e+06	1.327e+06	9.541e+05	9.541e+05	6.149e+05	3.589e+05	3.266e+05	8.281e+05	3.659e+05	4.458e+05	5.034e+05	5.034e+05	1.128e+06	5.545e+05	1.02e+06	7.882e+05	1.985e+05	1.492e+06	8.458e+05	3.953e+05	8.644e+05	9.231e+05	1.012e+06	nan	nan	nan	nan	nan	4.812e+04	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.604e+05	1.604e+05	1.764e+05	2.085e+05	3.368e+05	3.368e+05	4.17e+05	4.17e+05	3.689e+05	2.887e+05	3.047e+05	2.887e+05	3.047e+05	4.17e+05	4.972e+05	5.613e+05	6.415e+05	6.415e+05	6.255e+05	6.255e+05	5.934e+05	6.576e+05	5.934e+05	5.934e+05	5.934e+05	5.453e+05	4.33e+05	3.528e+05	3.849e+05	5.613e+05	5.934e+05	5.934e+05	4.33e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.613e+05	4.491e+05	4.01e+05	5.132e+05	5.132e+05	4.972e+05	4.972e+05	4.812e+05	5.613e+05	6.095e+05	5.934e+05	6.576e+05	7.859e+05	7.538e+05	7.698e+05	6.736e+05	5.613e+05	4.972e+05	4.972e+05	5.934e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	4.812e+04	1.443e+05	1.443e+05	1.925e+05	1.764e+05	1.443e+05	1.604e+05	2.085e+05	2.727e+05	3.368e+05	4.01e+05	4.17e+05	3.689e+05	3.528e+05	3.047e+05	3.047e+05	2.887e+05	3.368e+05	4.972e+05	5.613e+05	5.613e+05	6.415e+05	6.255e+05	6.255e+05	5.774e+05	6.576e+05	6.576e+05	5.934e+05	5.934e+05	5.453e+05	5.453e+05	3.689e+05	3.528e+05	4.651e+05	5.613e+05	5.934e+05	5.132e+05	5.774e+05	7.859e+05	8.661e+05	8.661e+05	7.378e+05	6.736e+05	6.255e+05	5.774e+05	5.613e+05	4.491e+05	4.01e+05	5.132e+05	5.132e+05	4.972e+05	4.651e+05	4.812e+05	5.453e+05	5.774e+05	6.095e+05	6.576e+05	7.859e+05	7.859e+05	7.538e+05	7.698e+05	6.736e+05	nan	nan	nan	nan	nan	nan	nan	nan	8.361e+04	8.361e+04	3.159e+04	1.47e+05	2.475e+05	1.954e+05	2.614e+05	2.534e+05	4.284e+05	4.551e+05	4.869e+05	6.466e+05	6.466e+05	5.11e+05	3.715e+05	4.374e+05	5.175e+05	6.04e+05	7.74e+05	1.063e+06	1.063e+06	1.005e+06	1.005e+06	9.83e+05	8.091e+05	3.428e+05	5.494e+05	1.013e+06	1.013e+06	8.1e+05	8.327e+05	4.971e+05	5.396e+05	7.126e+05	7.364e+05	7.94e+05	7.52e+05	1.052e+06	1.052e+06	7.393e+05	1.586e+06	5.723e+05	7.723e+05	8.287e+05	8.626e+05	1.043e+06	8.061e+05	4.569e+05	6.865e+05	7.935e+05	7.429e+05	7.429e+05	6.137e+05	4.467e+05	8.012e+05	8.012e+05	3.186e+05	9.006e+05	1.298e+06	1.298e+06	1.443e+06	5.481e+05	nan	nan	nan	nan	nan	nan	nan	nan	7762	3.748e+04	3.748e+04	2.428e+05	2.428e+05	8.263e+04	2.462e+05	3.353e+05	3.958e+05	6.485e+05	6.133e+05	5.162e+05	6.086e+05	4.113e+05	4.409e+05	3.037e+05	3.994e+05	4.37e+05	6.055e+05	9.083e+05	9.083e+05	2.983e+05	7.453e+05	7.453e+05	1.021e+06	8.776e+05	8.833e+05	1.132e+06	1.132e+06	1.056e+06	8.178e+05	5.75e+05	5.75e+05	7.163e+05	8.598e+05	1.096e+06	3.494e+05	7.591e+05	1.256e+06	1.521e+06	1.352e+06	9.223e+05	1.327e+06	9.262e+05	9.541e+05	7.711e+05	6.149e+05	3.589e+05	3.266e+05	8.281e+05	4.458e+05	4.458e+05	5.034e+05	5.034e+05	1.128e+06	1.128e+06	9.564e+05	1.02e+06	7.882e+05	1.985e+05	1.492e+06	8.458e+05	nan	nan	nan	nan	nan	nan	nan	nan	4.812e+04	1.443e+05	1.443e+05	1.925e+05	1.764e+05	1.443e+05	1.604e+05	2.085e+05	2.727e+05	3.368e+05	4.01e+05	4.17e+05	3.689e+05	3.528e+05	3.047e+05	3.047e+05	2.887e+05	3.368e+05	4.972e+05	5.613e+05	5.613e+05	6.415e+05	6.255e+05	6.255e+05	5.774e+05	6.576e+05	6.576e+05	5.934e+05	5.934e+05	5.453e+05	5.453e+05	3.689e+05	3.528e+05	4.651e+05	5.613e+05	5.934e+05	5.132e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.613e+05	4.491e+05	4.01e+05	5.132e+05	5.132e+05	4.972e+05	4.651e+05	4.812e+05	5.453e+05	5.774e+05	6.095e+05	6.576e+05	7.859e+05	7.859e+05	7.538e+05	7.698e+05	6.736e+05
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_med.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_med.gz
new file mode 100644
index 0000000000..cb4e28c5fd
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_med.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_med.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_med.tab
new file mode 100644
index 0000000000..d576594213
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_med.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
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+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.453e+05	5.293e+05	4.972e+05	4.972e+05	6.736e+05	7.538e+05	7.859e+05	5.934e+05	5.774e+05	5.453e+05	4.491e+05	4.651e+05	4.972e+05	3.849e+05	3.689e+05	3.528e+05	4.812e+05	5.774e+05	6.255e+05	6.415e+05	8.019e+05	8.18e+05	5.774e+05	4.33e+05	5.132e+05	5.613e+05	4.651e+05	3.368e+05	3.208e+05	4.491e+05	5.132e+05	5.934e+05	5.934e+05	6.415e+05	5.453e+05	6.255e+05	5.613e+05	5.453e+05	4.972e+05	4.972e+05	3.368e+05	2.887e+05	2.406e+05	2.406e+05	2.887e+05	3.528e+05	4.01e+05	3.208e+05	2.406e+05	2.085e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	8.661e+05	4.902e+05	7.844e+05	2.611e+05	5.481e+05	1.241e+06	5.19e+05	2.909e+05	4.821e+05	4.467e+05	4.405e+05	7.429e+05	5.522e+05	4.569e+05	3.608e+05	3.517e+05	8.626e+05	6.216e+05	1.309e+05	3.71e+05	5.455e+05	1.44e+05	1.052e+06	3.679e+05	5.235e+05	6.655e+05	7.126e+05	1.718e+05	2.583e+05	4.008e+05	7.671e+05	1.013e+06	2.813e+05	3.428e+05	6.233e+05	3.467e+05	9.131e+05	2.501e+05	3.341e+05	7.74e+05	7.494e+04	5.175e+05	3.365e+05	3.088e+05	3.428e+05	4.383e+05	3.492e+05	4.551e+05	3.931e+05	2.534e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	7.977e+05	8.232e+05	9.231e+05	8.368e+05	8.458e+05	6103	7.882e+05	5.545e+05	7.184e+05	2.859e+05	1.694e+05	4.458e+05	3.104e+05	2.954e+05	2.739e+05	2.885e+05	7.711e+05	5.287e+05	9.262e+05	8.397e+05	4.321e+05	1.004e+06	1.428e+05	2.944e+05	3.226e+05	8.598e+05	6.309e+05	4.069e+05	5.313e+05	2.247e+05	6.881e+05	1.132e+06	1.772e+05	8.776e+05	6.313e+05	2.083e+05	6.641e+05	2.983e+05	3.508e+05	5.727e+05	4.37e+05	3.994e+05	1.874e+05	2.711e+05	3.021e+05	4.896e+05	5.162e+05	3.627e+05	3.326e+05	2.9e+04	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.453e+05	5.293e+05	4.972e+05	4.972e+05	6.736e+05	7.538e+05	7.859e+05	5.934e+05	5.774e+05	5.453e+05	4.491e+05	4.651e+05	4.972e+05	3.849e+05	3.689e+05	3.528e+05	4.812e+05	nan	nan	nan	nan	nan	nan	4.17e+05	5.132e+05	5.613e+05	4.651e+05	3.368e+05	3.208e+05	4.491e+05	5.132e+05	5.934e+05	5.934e+05	6.415e+05	5.453e+05	6.255e+05	5.613e+05	5.453e+05	4.972e+05	4.972e+05	3.368e+05	2.887e+05	2.406e+05	2.406e+05	2.887e+05	3.528e+05	4.01e+05	3.208e+05	2.406e+05	2.085e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	1.604e+04	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.123e+05	1.443e+05	1.604e+05	2.085e+05	2.406e+05	3.208e+05	4.01e+05	3.528e+05	3.528e+05	2.566e+05	2.566e+05	2.406e+05	2.887e+05	3.368e+05	4.972e+05	4.972e+05	5.453e+05	6.255e+05	6.095e+05	5.774e+05	5.613e+05	6.415e+05	5.934e+05	5.934e+05	5.132e+05	4.491e+05	3.689e+05	3.368e+05	3.528e+05	5.453e+05	5.613e+05	5.132e+05	4.33e+05	5.774e+05	8.019e+05	8.661e+05	7.378e+05	6.415e+05	6.095e+05	5.774e+05	4.812e+05	3.528e+05	3.689e+05	3.689e+05	5.132e+05	4.972e+05	4.651e+05	4.651e+05	5.453e+05	5.774e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	1.968e+04	3.159e+04	3.159e+04	3.159e+04	9.349e+04	1.954e+05	7.409e+04	7.241e+04	2.534e+05	3.931e+05	4.551e+05	3.492e+05	4.064e+05	3.746e+05	3.715e+05	3.088e+05	4.374e+05	5.175e+05	7.494e+04	7.74e+05	3.341e+05	2.501e+05	8.858e+05	9.131e+05	3.467e+05	3.121e+05	3.428e+05	2.813e+05	1.013e+06	7.671e+05	4.008e+05	4.971e+05	2.63e+05	1.427e+05	7.126e+05	6.655e+05	5.235e+05	3.679e+05	1.052e+06	4.416e+05	5.187e+05	3.71e+05	3.864e+05	1.309e+05	6.216e+05	8.626e+05	3.517e+05	3.608e+05	4.569e+05	1.611e+05	9.53e+04	7.429e+05	2.393e+05	4.467e+05	4.821e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	7762	3.748e+04	3.748e+04	3.748e+04	2.298e+05	8.263e+04	5.57e+04	2.462e+05	2.9e+04	3.326e+05	3.627e+05	5.162e+05	5.162e+05	3.826e+05	3.021e+05	2.711e+05	3.037e+05	3.994e+05	4.37e+05	5.727e+05	3.508e+05	2.983e+05	2.7e+05	6.641e+05	2.083e+05	8.776e+05	6.638e+05	1.772e+05	1.132e+06	6.881e+05	2.247e+05	3.909e+05	5.313e+05	3.844e+05	6.309e+05	8.598e+05	3.226e+05	2.944e+05	1.428e+05	1.004e+06	1.352e+06	6.037e+05	8.924e+05	7.856e+05	5.287e+05	7.711e+05	2.885e+05	2.739e+05	2.739e+05	2.954e+05	3.659e+05	4.458e+05	3.364e+05	2.859e+05	7.184e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	1.604e+04	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.123e+05	1.443e+05	1.604e+05	2.085e+05	2.406e+05	3.208e+05	4.01e+05	3.528e+05	3.528e+05	2.566e+05	2.566e+05	2.406e+05	2.887e+05	3.368e+05	4.972e+05	4.972e+05	5.453e+05	6.255e+05	6.095e+05	5.774e+05	5.613e+05	6.415e+05	5.934e+05	5.934e+05	5.132e+05	4.491e+05	3.689e+05	3.368e+05	3.528e+05	5.453e+05	5.613e+05	5.132e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	4.812e+05	3.528e+05	3.689e+05	3.689e+05	5.132e+05	4.972e+05	4.651e+05	4.651e+05	5.453e+05	5.774e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.844e+05	1.604e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.604e+05	2.085e+05	2.005e+05	2.727e+05	3.208e+05	3.368e+05	4.17e+05	3.528e+05	3.609e+05	2.887e+05	nan	nan	nan	1.968e+04	5.76e+04	3.159e+04	3.159e+04	9.349e+04	2.215e+05	1.954e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	4.398e+04	2.534e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	1.74e+05	5.265e+05	4.383e+05	1.731e+05	nan	nan	nan	7762	3941	3.748e+04	3.748e+04	2.168e+05	5.714e+04	8.263e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	2.462e+05	2.9e+04	3.326e+05	3.412e+05	2.736e+05	5.57e+05	5.162e+05	2.946e+05	4.63e+05	3.021e+05	nan	nan	nan	1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.844e+05	1.604e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.604e+05	2.085e+05	2.005e+05	2.727e+05	3.208e+05	3.368e+05	4.17e+05	3.528e+05	3.609e+05	2.887e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
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+1.604e+04	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.123e+05	1.443e+05	1.524e+05	1.604e+05	2.085e+05	2.406e+05	3.208e+05	4.01e+05	3.528e+05	3.528e+05	2.406e+05	2.566e+05	2.887e+05	3.047e+05	4.17e+05	4.972e+05	5.293e+05	6.095e+05	6.255e+05	5.453e+05	5.934e+05	5.934e+05	5.934e+05	5.132e+05	5.293e+05	3.689e+05	3.368e+05	3.528e+05	5.453e+05	5.774e+05	4.812e+05	5.132e+05	7.859e+05	8.661e+05	7.378e+05	6.415e+05	6.095e+05	5.132e+05	4.812e+05	3.528e+05	3.528e+05	4.972e+05	4.972e+05	4.651e+05	4.491e+05	5.453e+05	5.934e+05	6.255e+05	7.859e+05	7.538e+05	6.255e+05	4.972e+05	4.972e+05	5.293e+05	5.453e+05	5.293e+05	4.17e+05	3.528e+05	3.368e+05	4.651e+05	7.057e+05	7.698e+05	6.897e+05	6.095e+05	4.651e+05	1.968e+04	3.159e+04	3.159e+04	3.159e+04	9.349e+04	1.954e+05	7.409e+04	1.677e+05	4.398e+04	2.534e+05	3.931e+05	4.551e+05	3.492e+05	4.064e+05	3.428e+05	3.715e+05	3.146e+05	5.175e+05	5.175e+05	7.494e+04	7.74e+05	3.341e+05	9.131e+05	3.467e+05	6.233e+05	3.121e+05	2.813e+05	6.852e+05	7.671e+05	4.008e+05	4.971e+05	2.63e+05	1.427e+05	7.126e+05	6.655e+05	4.315e+05	9.185e+05	7.393e+05	5.187e+05	3.71e+05	3.864e+05	1.309e+05	6.216e+05	8.061e+05	1.175e+05	3.946e+05	6.865e+05	9.53e+04	7.429e+05	4.405e+05	4.467e+05	3.186e+05	2.909e+05	5.19e+05	1.241e+06	3.556e+05	2.611e+05	7.844e+05	4.902e+05	8.661e+05	7.216e+05	2.227e+05	5.779e+05	5.496e+05	4.505e+05	1.174e+06	9.009e+05	7.744e+05	5.47e+05	3.733e+05	7762	3.748e+04	3.748e+04	3.748e+04	2.298e+05	8.263e+04	5.57e+04	4.831e+04	2.462e+05	2.9e+04	3.326e+05	3.627e+05	5.162e+05	5.162e+05	3.021e+05	4.113e+05	1.874e+05	3.994e+05	3.994e+05	6.055e+05	5.727e+05	3.508e+05	2.967e+05	2.083e+05	6.313e+05	2.584e+05	4.501e+05	8.703e+05	6.881e+05	2.247e+05	3.909e+05	5.313e+05	3.844e+05	6.309e+05	8.598e+05	3.226e+05	2.186e+05	1.004e+06	1.352e+06	6.037e+05	8.924e+05	7.856e+05	5.287e+05	2.885e+05	3.589e+05	2.739e+05	2.954e+05	3.104e+05	4.458e+05	1.694e+05	2.859e+05	7.184e+05	9.564e+05	7.882e+05	6103	6.971e+05	8.368e+05	9.231e+05	8.232e+05	7.977e+05	1.411e+05	5.286e+05	3.283e+05	5.979e+05	3.69e+05	1.363e+06	3.338e+05	8.227e+05	7.513e+05	2.889e+05	1.604e+04	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.123e+05	1.443e+05	1.524e+05	1.604e+05	2.085e+05	2.406e+05	3.208e+05	4.01e+05	3.528e+05	3.528e+05	2.406e+05	2.566e+05	2.887e+05	3.047e+05	4.17e+05	4.972e+05	5.293e+05	6.095e+05	6.255e+05	5.453e+05	5.934e+05	5.934e+05	5.934e+05	5.132e+05	5.293e+05	3.689e+05	3.368e+05	3.528e+05	5.453e+05	5.774e+05	4.812e+05	4.17e+05	nan	nan	nan	nan	nan	4.812e+05	4.812e+05	3.528e+05	3.528e+05	4.972e+05	4.972e+05	4.651e+05	4.491e+05	5.453e+05	5.934e+05	6.255e+05	7.859e+05	7.538e+05	6.255e+05	4.972e+05	4.972e+05	5.293e+05	5.453e+05	5.293e+05	4.17e+05	3.528e+05	3.368e+05	4.651e+05	7.057e+05	7.698e+05	6.897e+05	6.095e+05	4.651e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	1.604e+04	1.443e+05	1.443e+05	1.764e+05	1.604e+05	1.443e+05	1.604e+05	2.085e+05	2.085e+05	3.208e+05	3.368e+05	4.17e+05	3.528e+05	2.887e+05	2.406e+05	2.406e+05	2.887e+05	3.047e+05	4.17e+05	4.972e+05	5.293e+05	6.255e+05	5.613e+05	6.255e+05	5.453e+05	5.934e+05	5.934e+05	5.934e+05	5.934e+05	5.293e+05	4.33e+05	3.368e+05	3.047e+05	3.849e+05	5.453e+05	5.774e+05	4.812e+05	4.491e+05	7.538e+05	8.18e+05	8.34e+05	6.576e+05	6.255e+05	6.095e+05	5.132e+05	4.812e+05	3.528e+05	3.689e+05	3.849e+05	4.972e+05	4.972e+05	4.651e+05	4.812e+05	5.453e+05	5.613e+05	6.014e+05	5.694e+05	6.415e+05	7.859e+05	7.538e+05	7.618e+05	6.255e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.968e+04	3.159e+04	3.159e+04	4.001e+04	1.954e+05	7.409e+04	7.241e+04	2.534e+05	2.534e+05	4.325e+05	4.561e+05	1.74e+05	4.701e+05	3.428e+05	3.088e+05	3.365e+05	5.175e+05	5.175e+05	7.494e+04	7.74e+05	7.515e+05	2.501e+05	9.131e+05	3.467e+05	6.233e+05	3.121e+05	2.813e+05	6.852e+05	1.013e+06	7.671e+05	4.971e+05	2.607e+05	2.583e+05	1.718e+05	6.655e+05	6.655e+05	4.315e+05	7.846e+05	9.139e+05	1.44e+05	5.187e+05	3.71e+05	3.864e+05	1.309e+05	6.216e+05	8.061e+05	1.175e+05	3.608e+05	4.569e+05	5.522e+05	9.53e+04	7.429e+05	3.818e+04	4.467e+05	4.821e+05	1.658e+05	2.909e+05	7.098e+05	5.19e+05	1.241e+06	1.342e+06	3.556e+05	nan	nan	nan	nan	nan	nan	nan	nan	7762	3.748e+04	3.748e+04	2.168e+05	8.263e+04	5.57e+04	1.603e+05	2.9e+04	3.326e+05	2.866e+05	5.007e+05	5.162e+05	4.63e+05	3.021e+05	2.711e+05	1.874e+05	3.994e+05	3.994e+05	6.055e+05	5.727e+05	7.773e+05	2.967e+05	6.641e+05	2.083e+05	6.313e+05	2.584e+05	4.501e+05	8.703e+05	1.132e+06	2.573e+05	3.909e+05	4.611e+05	4.069e+05	4.776e+05	6.309e+05	8.598e+05	3.226e+05	2.944e+05	7.89e+05	1.004e+06	4.321e+05	8.397e+05	9.262e+05	7.856e+05	5.287e+05	2.885e+05	3.589e+05	2.739e+05	2.954e+05	3.104e+05	3.659e+05	4.458e+05	5.034e+05	2.859e+05	2.508e+05	7.184e+05	5.545e+05	9.882e+05	7.882e+05	6103	1.094e+06	7.714e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.604e+04	1.443e+05	1.443e+05	1.764e+05	1.604e+05	1.443e+05	1.604e+05	2.085e+05	2.085e+05	3.208e+05	3.368e+05	4.17e+05	3.528e+05	2.887e+05	2.406e+05	2.406e+05	2.887e+05	3.047e+05	4.17e+05	4.972e+05	5.293e+05	6.255e+05	5.613e+05	6.255e+05	5.453e+05	5.934e+05	5.934e+05	5.934e+05	5.934e+05	5.293e+05	4.33e+05	3.368e+05	3.047e+05	3.849e+05	5.453e+05	5.774e+05	4.812e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	4.812e+05	3.528e+05	3.689e+05	3.849e+05	4.972e+05	4.972e+05	4.651e+05	4.812e+05	5.453e+05	5.613e+05	6.014e+05	5.694e+05	6.415e+05	7.859e+05	7.538e+05	7.618e+05	6.255e+05
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_min.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_min.gz
new file mode 100644
index 0000000000..eff78101af
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_min.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_min.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_min.tab
new file mode 100644
index 0000000000..027d002e9a
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_min.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.01e+05	6.095e+05	6.736e+05	7.057e+05	7.057e+05	3.208e+05	3.368e+05	3.528e+05	4.17e+05	5.293e+05	5.293e+05	5.132e+05	4.651e+05	4.651e+05	5.613e+05	7.217e+05	6.255e+05	5.453e+05	5.453e+05	4.812e+05	3.528e+05	4.651e+05	4.812e+05	3.208e+05	3.208e+05	3.368e+05	4.812e+05	5.132e+05	5.934e+05	6.255e+05	7.378e+05	7.859e+05	5.774e+05	4.17e+05	4.33e+05	5.453e+05	3.528e+05	2.566e+05	3.047e+05	3.689e+05	4.972e+05	4.972e+05	5.132e+05	5.613e+05	5.132e+05	5.453e+05	5.453e+05	5.293e+05	4.651e+05	4.17e+05	3.047e+05	2.245e+05	2.245e+05	2.245e+05	2.566e+05	3.208e+05	3.368e+05	2.887e+05	1.925e+05	1.764e+05	1.283e+05	1.443e+05	1.123e+05	1.123e+05	1.764e+05	1.443e+05	1.443e+05	4.812e+04	1.604e+04	nan	3.309e+05	3.167e+05	2.869e+05	6.275e+05	1.174e+06	4.768e+04	5.496e+05	3.222e+05	1.232e+05	7.139e+05	4.406e+05	3.543e+05	3.393e+05	9.123e+04	3.524e+05	1.241e+06	5.19e+05	1.398e+05	1.306e+04	3.818e+04	3.818e+04	9.53e+04	4.091e+04	1.611e+05	9.225e+04	9.225e+04	2.407e+05	1.309e+05	6.327e+04	2.556e+05	1.165e+05	5.115e+04	7.393e+05	2.727e+05	2.727e+05	2.36e+05	6.223e+04	1.427e+05	8214	2.458e+05	8.112e+04	8.112e+04	9.19e+04	2.874e+05	1.925e+05	1.925e+05	8.858e+05	4.569e+04	2.36e+05	7.494e+04	3.873e+04	3.365e+05	1.914e+05	1.914e+05	3351	1.74e+05	1.74e+05	4.325e+05	1.772e+05	1.772e+05	1.555e+04	7.409e+04	7.409e+04	1.954e+05	4.001e+04	3.159e+04	3.159e+04	3.159e+04	1.968e+04	nan	1.224e+05	3.931e+05	4.755e+05	1.922e+05	1.363e+06	7.353e+04	5.979e+05	1.293e+05	1.947e+05	8.758e+04	2.346e+05	2.346e+05	2.02e+05	9.597e+04	3.953e+05	6103	1.985e+05	3.867e+05	2.157e+05	2.859e+05	7.741e+04	3.659e+05	6.116e+04	9.485e+04	1.15e+05	1.13e+05	1.316e+04	4.562e+05	4.562e+05	6.037e+05	2.636e+05	7.89e+05	1.428e+05	1.023e+05	1.023e+05	8.698e+04	3.844e+05	1.992e+05	2.376e+05	4.796e+04	4.796e+04	6.881e+05	1.772e+05	1.565e+05	5.36e+04	5.36e+04	1.766e+05	2.7e+05	1.722e+05	1.722e+05	2.944e+05	3.037e+05	1.01e+05	6.466e+04	2.802e+05	7.304e+04	5.007e+05	1.844e+05	2.866e+05	2.9e+04	1.603e+05	4.092e+04	5.57e+04	3.165e+04	2.168e+05	3.748e+04	3.748e+04	119.7	7762	nan	4.01e+05	6.095e+05	6.736e+05	7.057e+05	7.057e+05	3.208e+05	3.368e+05	3.528e+05	4.17e+05	5.293e+05	5.293e+05	5.132e+05	4.651e+05	4.651e+05	5.613e+05	7.217e+05	6.255e+05	5.453e+05	5.453e+05	4.812e+05	3.528e+05	4.651e+05	4.812e+05	3.208e+05	3.208e+05	3.368e+05	4.812e+05	nan	nan	nan	nan	nan	nan	4.17e+05	4.33e+05	5.453e+05	3.528e+05	2.566e+05	3.047e+05	3.689e+05	4.972e+05	4.972e+05	5.132e+05	5.613e+05	5.132e+05	5.453e+05	5.453e+05	5.293e+05	4.651e+05	4.17e+05	3.047e+05	2.245e+05	2.245e+05	2.245e+05	2.566e+05	3.208e+05	3.368e+05	2.887e+05	1.925e+05	1.764e+05	1.283e+05	1.443e+05	1.123e+05	1.123e+05	1.764e+05	1.443e+05	1.443e+05	4.812e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.604e+05	1.123e+05	1.443e+05	1.283e+05	1.764e+05	1.925e+05	2.887e+05	3.368e+05	3.208e+05	2.887e+05	2.245e+05	2.406e+05	2.245e+05	2.887e+05	3.047e+05	4.17e+05	4.651e+05	4.972e+05	5.613e+05	5.453e+05	5.132e+05	5.132e+05	5.613e+05	5.132e+05	5.132e+05	4.972e+05	4.33e+05	3.208e+05	3.047e+05	2.566e+05	3.849e+05	5.453e+05	4.33e+05	4.17e+05	4.491e+05	7.538e+05	7.698e+05	6.576e+05	6.255e+05	5.934e+05	4.812e+05	4.812e+05	3.368e+05	3.368e+05	3.208e+05	4.812e+05	4.812e+05	3.528e+05	3.528e+05	4.812e+05	5.613e+05	5.453e+05	6.255e+05	7.859e+05	7.217e+05	7.538e+05	6.255e+05	5.293e+05	4.651e+05	4.812e+05	5.293e+05	nan	nan	nan	nan	nan	1.968e+04	3.159e+04	3.159e+04	3.159e+04	4.001e+04	7.409e+04	7.409e+04	1.555e+04	1.772e+05	1.772e+05	4.325e+05	1.74e+05	1.74e+05	3351	3351	1.914e+05	3.146e+05	3.873e+04	3.873e+04	7.494e+04	2.36e+05	4.569e+04	4.569e+04	3.467e+05	1.925e+05	2.874e+05	9.19e+04	9.19e+04	6.852e+05	8.112e+04	2.458e+05	8214	2.583e+05	6.223e+04	6.223e+04	2.36e+05	2.727e+05	2.727e+05	7.846e+05	5.115e+04	5.115e+04	1.165e+05	2.556e+05	6.327e+04	2.407e+05	4.668e+05	1.175e+05	9.225e+04	1.611e+05	4.091e+04	9.53e+04	9.53e+04	3.818e+04	3.818e+04	1.306e+04	2.909e+05	1.398e+05	5.19e+05	1.241e+06	1.241e+06	3.556e+05	2.611e+05	9.123e+04	6.078e+05	3.543e+05	nan	nan	nan	nan	nan	119.7	119.7	3.748e+04	3.748e+04	3.165e+04	3.165e+04	4.092e+04	1.603e+05	2.9e+04	2.866e+05	1.844e+05	5.007e+05	7.304e+04	2.802e+05	6.466e+04	1.01e+05	1.01e+05	2.944e+05	2.944e+05	5.727e+05	1.722e+05	2.7e+05	1.766e+05	2.083e+05	5.36e+04	1.565e+05	2.584e+05	1.772e+05	8.703e+05	2.573e+05	4.796e+04	2.376e+05	4.069e+05	1.992e+05	8.698e+04	8.698e+04	1.023e+05	1.023e+05	1.428e+05	7.89e+05	2.636e+05	2.636e+05	6.037e+05	4.562e+05	5.174e+05	1.316e+04	1.13e+05	1.13e+05	9.485e+04	6.116e+04	3.104e+05	7.741e+04	7.741e+04	2.157e+05	2.157e+05	3.867e+05	9.564e+05	7.882e+05	6103	6103	6.971e+05	9.597e+04	8.368e+05	2.02e+05	8.823e+05	nan	nan	nan	nan	nan	1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.604e+05	1.123e+05	1.443e+05	1.283e+05	1.764e+05	1.925e+05	2.887e+05	3.368e+05	3.208e+05	2.887e+05	2.245e+05	2.406e+05	2.245e+05	2.887e+05	3.047e+05	4.17e+05	4.651e+05	4.972e+05	5.613e+05	5.453e+05	5.132e+05	5.132e+05	5.613e+05	5.132e+05	5.132e+05	4.972e+05	4.33e+05	3.208e+05	3.047e+05	2.566e+05	3.849e+05	5.453e+05	4.33e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	4.812e+05	3.368e+05	3.368e+05	3.208e+05	4.812e+05	4.812e+05	3.528e+05	3.528e+05	4.812e+05	5.613e+05	5.453e+05	6.255e+05	7.859e+05	7.217e+05	7.538e+05	6.255e+05	5.293e+05	4.651e+05	4.812e+05	5.293e+05
+nan	nan	nan	1.604e+04	1.604e+04	1.443e+05	1.443e+05	1.443e+05	1.123e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.764e+05	1.925e+05	2.406e+05	2.887e+05	2.887e+05	4.01e+05	3.208e+05	3.208e+05	2.566e+05	nan	nan	nan	1.968e+04	1.968e+04	3.159e+04	3.159e+04	3.159e+04	4.001e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	1.555e+04	2.06e+05	1.772e+05	3.931e+05	4.325e+05	3.492e+05	1.74e+05	1.74e+05	3.428e+05	3351	nan	nan	nan	7762	119.7	3.748e+04	3.748e+04	3.748e+04	3.165e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	2.9e+04	2.9e+04	2.866e+05	1.844e+05	3.627e+05	5.007e+05	7.304e+04	2.802e+05	2.802e+05	nan	nan	nan	1.604e+04	1.604e+04	1.443e+05	1.443e+05	1.443e+05	1.123e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.764e+05	1.925e+05	2.406e+05	2.887e+05	2.887e+05	4.01e+05	3.208e+05	3.208e+05	2.566e+05
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+1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.604e+05	1.123e+05	1.123e+05	1.283e+05	1.283e+05	1.764e+05	1.925e+05	2.727e+05	2.887e+05	3.208e+05	2.887e+05	2.245e+05	2.245e+05	2.245e+05	2.887e+05	4.17e+05	4.651e+05	4.972e+05	5.613e+05	5.453e+05	5.132e+05	5.453e+05	5.613e+05	5.132e+05	4.972e+05	4.33e+05	3.208e+05	2.566e+05	2.566e+05	4.651e+05	5.132e+05	4.17e+05	4.17e+05	5.774e+05	8.18e+05	6.576e+05	6.255e+05	5.934e+05	4.812e+05	4.491e+05	3.368e+05	3.208e+05	3.849e+05	4.812e+05	3.528e+05	3.528e+05	4.812e+05	5.613e+05	5.453e+05	6.255e+05	7.217e+05	5.613e+05	4.651e+05	4.651e+05	5.132e+05	5.293e+05	4.33e+05	3.689e+05	3.368e+05	3.208e+05	3.208e+05	7.057e+05	7.057e+05	6.736e+05	4.01e+05	4.01e+05	1.968e+04	3.159e+04	3.159e+04	3.159e+04	4.001e+04	1.954e+05	7.409e+04	7.241e+04	1.555e+04	2.06e+05	1.772e+05	3.931e+05	1.74e+05	1.74e+05	3351	1.914e+05	1.914e+05	3.365e+05	3.873e+04	7.494e+04	2.36e+05	4.569e+04	4.569e+04	3.467e+05	1.925e+05	2.874e+05	9.19e+04	2.813e+05	8.112e+04	2.458e+05	8214	1.427e+05	6.223e+04	2.36e+05	5.235e+05	2.727e+05	3.679e+05	1.44e+05	5.115e+04	1.165e+05	2.556e+05	6.327e+04	2.407e+05	4.668e+05	9.225e+04	3.608e+05	4.091e+04	4.091e+04	9.53e+04	3.818e+04	3.818e+04	1.306e+04	1.398e+05	5.19e+05	1.241e+06	3.524e+05	9.123e+04	3.393e+05	3.543e+05	4.406e+05	7.139e+05	1.232e+05	3.222e+05	4.768e+04	4.768e+04	1.174e+06	6.275e+05	2.869e+05	3.167e+05	3.309e+05	119.7	119.7	3.748e+04	3.748e+04	3.165e+04	3.165e+04	5.57e+04	4.092e+04	1.603e+05	2.9e+04	2.9e+04	1.844e+05	3.627e+05	7.304e+04	2.802e+05	6.466e+04	1.01e+05	3.037e+05	2.944e+05	5.727e+05	1.722e+05	2.7e+05	1.766e+05	2.083e+05	5.36e+04	1.565e+05	1.772e+05	1.772e+05	2.573e+05	4.796e+04	2.376e+05	1.992e+05	1.992e+05	8.698e+04	1.314e+05	1.023e+05	1.428e+05	1.428e+05	4.321e+05	2.636e+05	6.037e+05	4.562e+05	5.174e+05	1.316e+04	1.13e+05	9.485e+04	6.116e+04	6.116e+04	7.741e+04	7.741e+04	2.157e+05	2.157e+05	3.867e+05	1.985e+05	6103	3.953e+05	9.597e+04	2.02e+05	2.346e+05	2.044e+05	8.758e+04	1.947e+05	1.293e+05	7.353e+04	7.353e+04	1.363e+06	1.922e+05	3.931e+05	1.224e+05	1.224e+05	1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.604e+05	1.123e+05	1.123e+05	1.283e+05	1.283e+05	1.764e+05	1.925e+05	2.727e+05	2.887e+05	3.208e+05	2.887e+05	2.245e+05	2.245e+05	2.245e+05	2.887e+05	4.17e+05	4.651e+05	4.972e+05	5.613e+05	5.453e+05	5.132e+05	5.453e+05	5.613e+05	5.132e+05	4.972e+05	4.33e+05	3.208e+05	2.566e+05	2.566e+05	4.651e+05	5.132e+05	4.17e+05	4.17e+05	nan	nan	nan	nan	nan	4.812e+05	4.491e+05	3.368e+05	3.208e+05	3.849e+05	4.812e+05	3.528e+05	3.528e+05	4.812e+05	5.613e+05	5.453e+05	6.255e+05	7.217e+05	5.613e+05	4.651e+05	4.651e+05	5.132e+05	5.293e+05	4.33e+05	3.689e+05	3.368e+05	3.208e+05	3.208e+05	7.057e+05	7.057e+05	6.736e+05	4.01e+05	4.01e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.123e+05	1.123e+05	1.283e+05	1.604e+05	1.925e+05	2.727e+05	2.887e+05	3.528e+05	3.208e+05	2.566e+05	2.245e+05	2.245e+05	2.245e+05	2.887e+05	4.17e+05	4.651e+05	4.972e+05	5.453e+05	5.453e+05	5.453e+05	5.132e+05	5.613e+05	5.613e+05	5.132e+05	4.972e+05	5.132e+05	3.689e+05	3.047e+05	2.566e+05	3.528e+05	4.651e+05	5.132e+05	4.17e+05	4.17e+05	5.774e+05	7.859e+05	7.378e+05	6.415e+05	6.255e+05	5.774e+05	4.812e+05	4.491e+05	3.368e+05	3.208e+05	3.208e+05	4.812e+05	4.651e+05	3.528e+05	4.491e+05	4.812e+05	5.453e+05	5.774e+05	5.453e+05	6.255e+05	7.217e+05	7.217e+05	6.736e+05	5.613e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.968e+04	3.159e+04	3.159e+04	3.159e+04	4.001e+04	7.409e+04	1.555e+04	1.555e+04	1.772e+05	3.931e+05	3.492e+05	1.74e+05	3.428e+05	3351	1.914e+05	1.914e+05	3.365e+05	3.873e+04	7.494e+04	2.36e+05	2.501e+05	4.569e+04	8.858e+05	1.925e+05	1.925e+05	2.874e+05	9.19e+04	2.813e+05	8.112e+04	4.008e+05	2.458e+05	8214	1.427e+05	6.223e+04	2.36e+05	5.235e+05	2.727e+05	3.679e+05	7.393e+05	5.115e+04	1.165e+05	2.556e+05	6.327e+04	6.327e+04	2.407e+05	4.668e+05	9.225e+04	9.225e+04	1.611e+05	4.091e+04	9.53e+04	4.405e+05	3.818e+04	3.818e+04	4.467e+05	1.306e+04	1.398e+05	1.398e+05	5.19e+05	1.241e+06	5.481e+05	3.524e+05	nan	nan	nan	nan	nan	nan	nan	nan	119.7	119.7	3.748e+04	3.748e+04	3.165e+04	5.57e+04	4.092e+04	2.9e+04	2.9e+04	1.844e+05	3.627e+05	7.304e+04	7.304e+04	2.802e+05	6.466e+04	1.01e+05	3.037e+05	2.944e+05	5.727e+05	1.722e+05	2.983e+05	2.7e+05	1.766e+05	5.36e+04	5.36e+04	1.565e+05	1.772e+05	1.772e+05	2.573e+05	4.796e+04	4.796e+04	2.376e+05	1.992e+05	3.844e+05	8.698e+04	1.314e+05	1.023e+05	1.428e+05	1.428e+05	7.89e+05	2.636e+05	6.037e+05	8.397e+05	4.562e+05	5.174e+05	1.316e+04	1.13e+05	1.15e+05	9.485e+04	6.116e+04	3.104e+05	7.741e+04	1.694e+05	2.859e+05	2.157e+05	3.867e+05	3.867e+05	7.882e+05	1.985e+05	6103	6103	3.953e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.604e+04	4.812e+04	1.443e+05	1.443e+05	1.123e+05	1.123e+05	1.283e+05	1.604e+05	1.925e+05	2.727e+05	2.887e+05	3.528e+05	3.208e+05	2.566e+05	2.245e+05	2.245e+05	2.245e+05	2.887e+05	4.17e+05	4.651e+05	4.972e+05	5.453e+05	5.453e+05	5.453e+05	5.132e+05	5.613e+05	5.613e+05	5.132e+05	4.972e+05	5.132e+05	3.689e+05	3.047e+05	2.566e+05	3.528e+05	4.651e+05	5.132e+05	4.17e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	4.491e+05	3.368e+05	3.208e+05	3.208e+05	4.812e+05	4.651e+05	3.528e+05	4.491e+05	4.812e+05	5.453e+05	5.774e+05	5.453e+05	6.255e+05	7.217e+05	7.217e+05	6.736e+05	5.613e+05
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+5.934e+05	5.774e+05	4.972e+05	4.972e+05	4.17e+05	3.528e+05	2.727e+05	1.764e+05	2.085e+05	2.887e+05	2.887e+05	3.368e+05	3.368e+05	3.368e+05	3.047e+05	3.047e+05	2.887e+05	2.406e+05	2.406e+05	3.047e+05	2.727e+05	2.245e+05	2.245e+05	2.245e+05	2.566e+05	3.208e+05	4.17e+05	4.17e+05	4.972e+05	4.972e+05	4.812e+05	4.812e+05	5.774e+05	5.613e+05	5.293e+05	5.293e+05	4.651e+05	4.491e+05	4.491e+05	4.01e+05	4.01e+05	3.689e+05	3.689e+05	2.727e+05	2.727e+05	3.047e+05	3.047e+05	2.727e+05	2.727e+05	1.925e+05	1.443e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	6.415e+04	3.208e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.879e+05	6.809e+05	3.147e+05	3.147e+05	3.278e+05	1.715e+05	4409	4409	2.604e+05	3.933e+05	2.801e+05	2.801e+05	4.712e+05	3.818e+05	3.818e+05	4.184e+05	4.524e+05	2.348e+05	3.872e+04	3.872e+04	3.872e+04	2.334e+04	2.334e+04	2.334e+04	4.651e+05	4.651e+05	7.376e+05	1.744e+05	1.744e+05	1.744e+05	1.744e+05	5.724e+05	9.582e+05	8.892e+05	8.892e+05	9.555e+05	7.396e+05	3.575e+05	3.575e+05	4.983e+05	4.983e+05	5.161e+05	5.161e+05	2.677e+05	2.677e+05	4.073e+05	4.073e+05	4.901e+05	5.306e+05	2.742e+04	2.742e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	6713	6713	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.311e+05	8.806e+05	1.281e+05	8.781e+04	8.11e+04	8.11e+04	3.235e+04	3.235e+04	6.24e+04	6.24e+04	6.24e+04	1.966e+05	1.966e+05	1.966e+05	3.805e+05	3.826e+05	3.001e+05	3.001e+05	2.809e+05	2.809e+05	2.809e+05	1.296e+05	1.296e+05	1.296e+05	5.105e+04	5.105e+04	7.657e+05	1.941e+05	1.941e+05	1.941e+05	1.941e+05	3.186e+05	3.186e+05	3.186e+05	3.464e+05	8.678e+05	7.351e+05	4.382e+05	4.382e+05	3329	3329	3.218e+05	3.218e+05	3.218e+05	3.27e+05	5.337e+05	4.022e+05	2.379e+04	2.379e+04	2.379e+04	1.469e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.035e+04	8740	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.934e+05	5.774e+05	4.972e+05	4.972e+05	4.17e+05	3.528e+05	2.727e+05	1.764e+05	2.085e+05	2.887e+05	2.887e+05	3.368e+05	3.368e+05	3.368e+05	3.047e+05	3.047e+05	2.887e+05	2.406e+05	2.406e+05	3.047e+05	2.727e+05	2.245e+05	2.245e+05	2.245e+05	2.566e+05	3.208e+05	4.17e+05	4.17e+05	4.972e+05	4.972e+05	4.812e+05	4.812e+05	5.774e+05	5.613e+05	5.293e+05	5.293e+05	4.651e+05	4.491e+05	4.491e+05	4.01e+05	4.01e+05	3.689e+05	3.689e+05	2.727e+05	2.727e+05	3.047e+05	3.047e+05	2.727e+05	2.727e+05	1.925e+05	1.443e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	6.415e+04	3.208e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_missingaszero.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_missingaszero.gz
new file mode 100644
index 0000000000..1c5cbba226
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_missingaszero.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_missingaszero.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_missingaszero.tab
new file mode 100644
index 0000000000..cfe4768c10
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_missingaszero.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg.gz
new file mode 100644
index 0000000000..e5433b7e8e
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg.tab
new file mode 100644
index 0000000000..9c0d177fe2
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:20	upstream:20	body:1000	bin size:10	unscaled 5 prime:0	unscaled 3 prime:0
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+6.576e+05	5.854e+05	5.052e+05	4.812e+05	4.812e+05	4.812e+05	4.812e+05	4.812e+05	4.812e+05	4.892e+05	5.132e+05	5.132e+05	5.854e+05	6.095e+05	6.014e+05	5.774e+05	5.774e+05	6.496e+05	6.736e+05	6.736e+05	6.736e+05	6.736e+05	7.097e+05	7.217e+05	7.498e+05	8.34e+05	8.34e+05	8.099e+05	8.019e+05	8.26e+05	8.982e+05	8.982e+05	8.019e+05	7.698e+05	7.658e+05	7.538e+05	7.538e+05	7.779e+05	7.859e+05	7.779e+05	7.538e+05	7.538e+05	7.057e+05	6.897e+05	6.415e+05	4.972e+05	4.972e+05	4.731e+05	4.651e+05	4.571e+05	4.33e+05	4.33e+05	4.33e+05	4.33e+05	4.29e+05	4.17e+05	4.17e+05	4.05e+05	4.01e+05	3.97e+05	3.849e+05	3.849e+05	3.609e+05	3.528e+05	3.729e+05	4.33e+05	4.33e+05	4.09e+05	4.01e+05	4.01e+05	4.01e+05	4.01e+05	4.13e+05	4.17e+05	3.97e+05	3.368e+05	3.368e+05	3.729e+05	3.849e+05	3.97e+05	4.33e+05	4.33e+05	5.774e+05	6.255e+05	6.175e+05	5.934e+05	5.934e+05	6.776e+05	7.057e+05	6.977e+05	6.736e+05	6.736e+05	6.616e+05	6.576e+05	6.576e+05	6.576e+05	6.576e+05	6.335e+05	6.255e+05	5.934e+05	4.972e+05	4.972e+05	4.17e+05	4.491e+05	1.019e+06	1.312e+05	5.971e+05	7.853e+05	7.853e+05	7.853e+05	7.853e+05	7.853e+05	7.853e+05	7.017e+05	4.509e+05	4.509e+05	3.221e+05	2.791e+05	4.551e+05	9.829e+05	9.829e+05	5.37e+05	3.884e+05	3.884e+05	3.884e+05	3.884e+05	1.924e+05	1.271e+05	2.281e+05	5.311e+05	5.311e+05	1.266e+06	1.51e+06	1.523e+06	1.563e+06	1.563e+06	8.682e+05	6.368e+05	6.4e+05	6.496e+05	6.496e+05	2.71e+05	1.448e+05	2.702e+05	6.463e+05	6.463e+05	1.055e+06	1.192e+06	9.348e+05	1.636e+05	1.636e+05	1.689e+05	1.707e+05	3.023e+05	6.97e+05	6.97e+05	6.97e+05	6.97e+05	6.698e+05	5.884e+05	5.884e+05	5.979e+05	6.011e+05	5.79e+05	5.128e+05	5.128e+05	4.013e+05	3.641e+05	3.766e+05	4.14e+05	4.14e+05	3.814e+05	3.706e+05	3.706e+05	3.706e+05	3.706e+05	5.177e+05	5.667e+05	5.757e+05	6.026e+05	6.026e+05	2.002e+05	6.609e+04	2.189e+05	6.772e+05	6.772e+05	1.102e+06	1.243e+06	9.778e+05	1.812e+05	1.812e+05	3.237e+05	3.712e+05	4.618e+05	7.336e+05	7.336e+05	5.294e+05	4.614e+05	4.614e+05	4.614e+05	4.614e+05	5.175e+05	5.362e+05	6.299e+05	9.11e+05	9.11e+05	5.957e+05	1.722e+05	8.04e+05	8.233e+05	8.778e+05	8.953e+05	8.953e+05	8.953e+05	8.953e+05	8.953e+05	8.953e+05	8.504e+05	7.158e+05	7.158e+05	7.523e+05	7.645e+05	7.216e+05	5.929e+05	5.929e+05	6.946e+05	7.285e+05	7.285e+05	7.285e+05	7.285e+05	9.964e+05	1.086e+06	8.238e+05	3.829e+04	3.829e+04	7.397e+05	9.735e+05	8.034e+05	2.934e+05	2.934e+05	1.094e+06	1.361e+06	1.231e+06	8.408e+05	8.408e+05	1.133e+06	1.23e+06	1.125e+06	8.072e+05	8.072e+05	8.238e+05	8.293e+05	7.872e+05	6.606e+05	6.606e+05	7.157e+05	7.341e+05	5.794e+05	1.153e+05	1.153e+05	1.153e+05	1.153e+05	1.329e+05	1.857e+05	1.857e+05	5.619e+05	6.873e+05	5.915e+05	3.04e+05	3.04e+05	1.019e+05	3.447e+04	1.919e+05	6.641e+05	6.641e+05	3.036e+05	1.835e+05	1.835e+05	1.835e+05	1.835e+05	5.783e+05	7.1e+05	6.594e+05	5.076e+05	5.076e+05	1.318e+05	6539	1.7e+05	6.604e+05	6.604e+05	1.812e+05	2.15e+04	1.031e+05	3.48e+05	3.48e+05	4.655e+05	5.047e+05	6.939e+05	1.262e+06	1.262e+06	1.121e+06	1.074e+06	1.074e+06	1.074e+06	1.074e+06	1.09e+06	1.095e+06	1.013e+06	7.703e+05	7.703e+05	1.128e+05	5.845e+05	6.576e+05	5.854e+05	5.052e+05	4.812e+05	4.812e+05	4.812e+05	4.812e+05	4.812e+05	4.812e+05	4.892e+05	5.132e+05	5.132e+05	5.854e+05	6.095e+05	6.014e+05	5.774e+05	5.774e+05	6.496e+05	6.736e+05	6.736e+05	6.736e+05	6.736e+05	7.097e+05	7.217e+05	7.498e+05	8.34e+05	8.34e+05	8.099e+05	8.019e+05	8.26e+05	8.982e+05	8.982e+05	8.019e+05	7.698e+05	7.658e+05	7.538e+05	7.538e+05	7.779e+05	7.859e+05	7.779e+05	7.538e+05	7.538e+05	7.057e+05	6.897e+05	6.415e+05	4.972e+05	4.972e+05	4.731e+05	4.651e+05	4.571e+05	4.33e+05	4.33e+05	4.33e+05	4.33e+05	4.29e+05	4.17e+05	4.17e+05	4.05e+05	4.01e+05	3.97e+05	3.849e+05	3.849e+05	3.609e+05	3.528e+05	3.729e+05	4.33e+05	4.33e+05	4.09e+05	4.01e+05	4.01e+05	4.01e+05	4.01e+05	4.13e+05	4.17e+05	3.97e+05	3.368e+05	3.368e+05	3.729e+05	3.849e+05	3.97e+05	4.33e+05	4.33e+05	5.774e+05	6.255e+05	6.175e+05	5.934e+05	5.934e+05	6.776e+05	7.057e+05	6.977e+05	6.736e+05	6.736e+05	6.616e+05	6.576e+05	6.576e+05	6.576e+05	6.576e+05	6.335e+05	6.255e+05	5.934e+05	4.972e+05	4.972e+05	4.17e+05	4.491e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.bed b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.bed
new file mode 100644
index 0000000000..9ca0aa5b99
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.bed
@@ -0,0 +1,23 @@
+#chrom	start	end	name	score	strand	thickStart	thickEnd	itemRGB	blockCount	blockSizes	blockStarts	deepTools_group
+phiX174	1000	1500	CG11023	0.0	+	1000	1500	0	1	500	0	input_computeMatrix_regions1
+phiX174	150	1750	cda5	0.0	-	150	1750	0	1	1600	0	input_computeMatrix_regions1
+phiX174	150	177	cda8	0.0	-	150	177	0	1	27	0	input_computeMatrix_regions1
+phiX174	75	1500	cda9	0.0	+	75	1500	0	1	1425	0	input_computeMatrix_regions1
+phiX174	101	175	C11023	0.0	+	101	175	0	1	74	0	input_computeMatrix_regions1
+phiX174	125	150	ca5	0.0	-	125	150	0	1	25	0	input_computeMatrix_regions1
+phiX174	450	1750	ca8	0.0	+	450	1750	0	1	1300	0	input_computeMatrix_regions1
+phiX174	80	1500	cda9_r1	0.0	+	80	1500	0	1	1420	0	input_computeMatrix_regions1
+phiX174	1243	1788	CG11023_new	0.0	-	1243	1788	0	1	545	0	input_computeMatrix_regions2
+phiX174	177	1752	cda5_new	0.0	+	177	1752	0	1	1575	0	input_computeMatrix_regions2
+phiX174	12	177	cda8_new	0.0	+	12	177	0	1	165	0	input_computeMatrix_regions2
+phiX174	123	854	cda9_new	0.0	-	123	854	0	1	731	0	input_computeMatrix_regions2
+phiX174	988	4301	C11023_new	0.0	-	988	4301	0	1	3313	0	input_computeMatrix_regions2
+phiX174	1011	1080	ca5_new	0.0	+	1011	1080	0	1	69	0	input_computeMatrix_regions2
+phiX174	236	240	ca8_new	0.0	.	236	240	0	1	4	0	input_computeMatrix_regions2
+phiX174	11	1423	cda9_new_r1	0.0	.	11	1423	0	1	1412	0	input_computeMatrix_regions2
+phiX174	0	150	tx_start	.	+	0	150	0	1	150	0	input_computeMatrix_regions3
+phiX174	299	900	tx_plus_multi	.	+	299	900	0	1	601	0	input_computeMatrix_regions3
+phiX174	1399	1650	tx_minus_single	.	-	1399	1650	0	1	251	0	input_computeMatrix_regions3
+phiX174	2199	3100	tx_minus_multi	.	-	2199	3100	0	1	901	0	input_computeMatrix_regions3
+phiX174	4999	5386	tx_end	.	+	4999	5386	0	1	387	0	input_computeMatrix_regions3
+phiX174	3399	3800	tx_cds	.	+	3399	3800	0	1	401	0	input_computeMatrix_regions3
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.gz
new file mode 100644
index 0000000000..9b40a4baaa
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.tab
new file mode 100644
index 0000000000..d8079cfe31
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_multireg2.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:195	upstream:150	body:150	bin size:15	unscaled 5 prime:0	unscaled 3 prime:0
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+1.39e+05	1.7e+05	2.064e+05	1.989e+05	2.459e+05	3.111e+05	3.133e+05	3.176e+05	4.01e+05	4.17e+05	3.261e+05	2.491e+05	3.176e+05	4.878e+05	5.835e+05	5.731e+05	6.006e+05	5.52e+05	4.443e+05	3.313e+05	4.918e+05	5.56e+05	5.56e+05	5.881e+05	5.025e+05	4.491e+05	4.277e+05	5.346e+05	6.362e+05	7.752e+05	8.34e+05	8.447e+05	8.34e+05	6.985e+04	1.298e+05	2.502e+05	2.077e+05	4.023e+05	4.303e+05	4.403e+05	4.746e+05	3.116e+05	1.74e+05	3.911e+05	3.296e+05	3.827e+05	5.383e+05	6.321e+05	5.52e+05	3.196e+05	6.32e+05	4.784e+05	2.358e+05	7.206e+05	4.028e+05	7.084e+05	6.137e+05	6.452e+05	3.256e+05	5.068e+05	9.631e+05	1.006e+06	7.975e+05	1.13e+05	3.629e+05	1.096e+06	1.752e+05	2.996e+05	4.942e+04	2.112e+05	3.624e+05	5.037e+05	2.629e+05	5.131e+05	5.124e+05	5.162e+05	3.581e+05	2.299e+05	4.175e+05	5.346e+05	4.086e+05	4.72e+05	4.812e+05	7.083e+05	4.629e+05	4.259e+05	6.878e+05	2.683e+05	9.384e+05	4.528e+05	3.315e+05	1.847e+05	4.493e+05	3.483e+05	5.137e+05	9.446e+05	1.176e+06	1.409e+06	3.759e+05	1.39e+05	1.7e+05	2.064e+05	1.989e+05	2.459e+05	3.111e+05	3.133e+05	3.176e+05	4.01e+05	4.17e+05	3.261e+05	2.491e+05	3.176e+05	4.878e+05	5.835e+05	5.731e+05	6.006e+05	5.52e+05	4.443e+05	3.313e+05	4.918e+05	5.56e+05	5.56e+05	5.881e+05	5.025e+05	4.491e+05	4.17e+05	nan	nan	nan	nan	nan	nan
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+5.635e+05	5.036e+05	5.656e+05	4.94e+05	4.127e+05	3.657e+05	3.315e+05	2.149e+05	2.277e+05	2.566e+05	3.144e+05	3.097e+05	2.632e+05	3.98e+05	5.317e+05	4.573e+05	3.474e+05	2.43e+05	9.294e+04	3.454e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	7.293e+05	5.33e+05	4.327e+05	4.317e+05	3.456e+05	3.325e+05	3.237e+05	1.703e+04	3.593e+05	3.401e+05	3.779e+05	3.935e+05	2.103e+05	4.386e+05	7.008e+05	6.199e+05	4.397e+05	2.863e+05	1.196e+05	3.168e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.034e+06	4.481e+05	3.309e+05	6.151e+05	2.188e+05	4.116e+05	2.544e+05	1.997e+05	4.273e+05	1.683e+05	1.77e+05	3.46e+05	2.499e+05	3.074e+05	3.843e+05	4.941e+05	4.302e+05	2.402e+05	6.929e+04	1.194e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.635e+05	5.036e+05	5.656e+05	4.94e+05	4.127e+05	3.657e+05	3.315e+05	2.149e+05	2.277e+05	2.566e+05	3.144e+05	3.097e+05	2.632e+05	3.98e+05	5.317e+05	4.573e+05	3.474e+05	2.43e+05	9.294e+04	3.454e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_no.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_no.gz
new file mode 100644
index 0000000000..873e38753f
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_no.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_no.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_no.tab
new file mode 100644
index 0000000000..2bccab0e08
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_no.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
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+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
+nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	1.059e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.925e+05	1.925e+05	1.925e+05	1.818e+05	1.764e+05	1.764e+05	1.764e+05	1.657e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.337e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.55e+05	1.604e+05	1.604e+05	1.604e+05	1.39e+05	1.283e+05	1.283e+05	1.612e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05	nan	nan	nan	nan	nan	nan	nan	nan	3.033e+04	5.24e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.085e+05	1.47e+05	1.47e+05	1.47e+05	7.566e+04	4.001e+04	4.001e+04	4.001e+04	1.783e+05	2.475e+05	2.475e+05	2.475e+05	2.128e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.145e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.989e+05	2.614e+05	2.614e+05	2.614e+05	1.354e+05	7.241e+04	7.241e+04	9.075e+04	2.463e+05	2.766e+05	4.201e+05	4.441e+05	4.341e+05	2.003e+05	4.916e+05	4.16e+05	2.319e+05	nan	nan	nan	nan	nan	nan	nan	nan	6488	2.253e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	1.57e+05	2.168e+05	2.168e+05	2.168e+05	2.341e+05	2.428e+05	2.428e+05	2.428e+05	1.02e+05	3.165e+04	3.165e+04	3.165e+04	6.564e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.468e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.585e+04	4.092e+04	4.092e+04	4.092e+04	1.205e+05	1.603e+05	1.603e+05	2.645e+05	7.494e+04	3.092e+05	4.296e+05	3.164e+05	5.363e+05	5.139e+05	3.27e+05	4.209e+05	3.371e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	1.059e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.925e+05	1.925e+05	1.925e+05	1.818e+05	1.764e+05	1.764e+05	1.764e+05	1.657e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.337e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.55e+05	1.604e+05	1.604e+05	1.604e+05	1.39e+05	1.283e+05	1.283e+05	1.612e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05
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+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_reglabel.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_reglabel.gz
new file mode 100644
index 0000000000..7e67bc7e78
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_reglabel.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_reglabel.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_reglabel.tab
new file mode 100644
index 0000000000..35d5062e8d
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_reglabel.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:800	upstream:500	body:2400	bin size:20	unscaled 5 prime:0	unscaled 3 prime:0
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+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.604e+04	3.849e+04	1.443e+05	1.443e+05	1.7e+05	1.652e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	2.005e+05	2.085e+05	2.807e+05	3.168e+05	3.408e+05	4.13e+05	3.609e+05	3.528e+05	2.967e+05	2.366e+05	2.767e+05	2.406e+05	2.727e+05	2.927e+05	3.488e+05	4.37e+05	4.892e+05	5.212e+05	5.253e+05	6.135e+05	5.894e+05	5.814e+05	6.135e+05	5.373e+05	5.654e+05	6.375e+05	5.894e+05	5.734e+05	5.734e+05	5.253e+05	5.293e+05	4.691e+05	3.729e+05	3.328e+05	3.087e+05	3.368e+05	4.651e+05	5.533e+05	5.734e+05	5.253e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.968e+04	5.224e+04	3.159e+04	3.159e+04	8.97e+04	1.515e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	2.06e+05	2.06e+05	2.06e+05	2.06e+05	2.06e+05	2.06e+05	2.06e+05	2.06e+05	2.416e+05	2.591e+05	4.174e+05	4.44e+05	4.448e+05	2.178e+05	4.684e+05	4.224e+05	2.151e+05	3.907e+05	2.516e+05	3.815e+05	4.722e+05	3.978e+05	3.304e+05	2.497e+05	6.395e+05	6.739e+05	5.218e+05	3.365e+05	9.223e+05	8.065e+05	3.081e+05	5.621e+05	4.302e+05	3.806e+05	2.536e+05	3.823e+05	9.31e+05	4.856e+05	6.97e+05	4.313e+05	4.588e+05	1.981e+05	3.7e+05	1.371e+05	5.56e+05	4.685e+05	6.943e+05	6.148e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	7762	5427	3.748e+04	3.748e+04	1.374e+05	1.292e+05	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	3.353e+05	3.353e+05	3.353e+05	3.353e+05	3.353e+05	3.353e+05	3.353e+05	3.353e+05	1.056e+05	2.725e+05	4.044e+05	3.45e+05	5.225e+05	5.124e+05	3.177e+05	4.537e+05	3.239e+05	2.454e+05	2.71e+05	1.949e+05	3.755e+05	3.731e+05	4.435e+05	5.973e+05	4.726e+05	5.849e+05	5.509e+05	2.838e+05	3.285e+05	5.907e+05	1.696e+05	5.844e+05	5.53e+05	5.694e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2.727e+05	2.406e+05	3.208e+05	3.448e+05	3.849e+05	4.09e+05	3.128e+05	3.288e+05	2.566e+05	2.005e+05	1.925e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.203e+05	1.524e+05	1.764e+05	1.443e+05	1.443e+05	6.415e+04	1.604e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	1.604e+04	9.623e+04	1.443e+05	1.443e+05	1.844e+05	1.363e+05	1.283e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.047e+05	3.441e+05	4.17e+05	4.389e+05	4.972e+05	4.826e+05	5.132e+05	5.264e+05	5.176e+05	5.409e+05	6.24e+05	6.27e+05	5.613e+05	6.036e+05	5.599e+05	6.255e+05	6.08e+05	5.482e+05	5.293e+05	5.541e+05	5.818e+05	6.401e+05	6.445e+05	5.686e+05	5.934e+05	5.861e+05	5.278e+05	5.934e+05	5.584e+05	5.045e+05	5.212e+05	5.38e+05	4.841e+05	4.374e+05	3.805e+05	3.251e+05	3.528e+05	3.076e+05	3.222e+05	2.829e+05	3.645e+05	4.214e+05	5.052e+05	5.541e+05	5.511e+05	5.686e+05	5.905e+05	5.205e+05	4.812e+05	4.316e+05	4.228e+05	4.841e+05	5.774e+05	6.576e+05	7.698e+05	8.034e+05	8.486e+05	8.427e+05	8.602e+05	7.786e+05	7.378e+05	6.561e+05	6.386e+05	6.386e+05	6.561e+05	6.109e+05	6.014e+05	5.92e+05	5.366e+05	4.899e+05	5.468e+05	4.884e+05	4.491e+05	3.514e+05	3.485e+05	3.878e+05	3.587e+05	3.47e+05	3.528e+05	4.549e+05	5.03e+05	5.089e+05	4.87e+05	4.957e+05	4.972e+05	4.651e+05	4.447e+05	3.791e+05	4.607e+05	4.812e+05	5.132e+05	5.453e+05	5.555e+05	5.73e+05	6.036e+05	5.949e+05	5.453e+05	6.547e+05	6.547e+05	7.859e+05	7.626e+05	7.363e+05	7.538e+05	7.626e+05	7.086e+05	6.386e+05	5.73e+05	5.322e+05	4.972e+05	4.666e+05	4.841e+05	5.059e+05	5.526e+05	5.57e+05	5.212e+05	5.643e+05	5.628e+05	5.336e+05	5.686e+05	5.336e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05	4.972e+05	5.052e+05	6.576e+05	6.656e+05	6.496e+05	6.736e+05	4.972e+05	4.972e+05	5.212e+05	5.212e+05	5.293e+05	4.812e+05	3.929e+05	4.411e+05	5.132e+05	6.095e+05	6.736e+05	5.934e+05	6.736e+05	8.18e+05	8.741e+05	8.581e+05	7.217e+05	5.052e+05	3.769e+05	4.651e+05	6.415e+05	7.458e+05	7.779e+05	6.496e+05	4.972e+05	nan	nan	1.968e+04	5.76e+04	3.159e+04	3.159e+04	9.349e+04	2.215e+05	1.348e+05	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	1.731e+05	4.412e+05	2.501e+05	3.76e+05	4.27e+05	5.175e+05	3.873e+04	5.559e+05	7.494e+04	2.656e+05	7.74e+05	5.294e+05	6.494e+05	6.653e+05	5.997e+05	3.869e+05	8.286e+04	9.174e+05	8.858e+05	9.195e+05	8.673e+05	3.467e+05	2.906e+05	3.883e+05	7.162e+05	5.38e+05	2.964e+05	3.277e+05	5.118e+05	1.335e+05	2.813e+05	3.18e+05	7.448e+05	1.013e+06	6.741e+05	3.929e+05	7.885e+05	5.868e+05	3.022e+05	6.727e+05	5.581e+05	5.266e+04	2.63e+05	2.839e+05	4.674e+05	1.506e+05	1.319e+05	3.579e+05	7.245e+05	4.635e+05	5.094e+05	7.59e+05	5.727e+05	7.312e+05	4.315e+05	2.813e+05	4.437e+05	8.576e+05	1.052e+06	9.894e+05	8.266e+05	4.146e+05	8.491e+04	3.912e+05	1.392e+06	2.501e+05	5.723e+05	3.605e+05	3.496e+05	6.671e+05	2.689e+05	9.403e+04	4.798e+05	7.157e+05	3.792e+05	6.93e+05	1.01e+06	5.192e+05	8.061e+05	3.304e+05	1.129e+05	1.655e+05	3.731e+05	4.229e+05	5.717e+05	3.999e+05	5.636e+05	2.462e+05	4.592e+05	1.368e+05	9.53e+04	7.429e+05	6.879e+05	4.877e+05	4.044e+05	3.818e+04	2.425e+05	4.467e+05	4.693e+05	7.142e+05	1.564e+05	2.908e+05	2.909e+05	2.089e+05	8.312e+05	5.19e+05	8.024e+05	1.272e+06	1.241e+06	1.351e+06	8.736e+05	4.081e+05	3.53e+05	2.694e+05	9.123e+04	3.637e+05	6.399e+05	8.086e+05	6.845e+05	4.161e+05	7.66e+05	9.46e+05	5.953e+05	7.916e+05	8.909e+05	7.293e+05	4.262e+05	4.642e+05	5.496e+05	2.491e+05	1.174e+06	9.009e+05	8.651e+05	7.893e+05	5.541e+05	2.101e+05	6.717e+05	5.951e+05	1.048e+06	4.541e+05	5.307e+05	5.025e+05	6.679e+05	8.453e+05	6.384e+05	3.121e+05	6.296e+05	3.667e+05	3.832e+05	5.946e+05	3.775e+05	1.102e+06	2.079e+05	8.521e+05	4.333e+05	4.66e+05	5.555e+05	8.849e+05	6.201e+05	7.295e+05	3.242e+05	6.102e+05	5.911e+05	1.064e+06	3.754e+05	9.371e+05	nan	nan	7762	1.88e+04	3.748e+04	3.748e+04	2.298e+05	5.714e+04	6.917e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	2.912e+05	2.38e+05	3.56e+05	1.442e+05	3.515e+05	3.994e+05	2.944e+05	4.523e+05	6.055e+05	5.966e+05	5.727e+05	3.906e+05	5.402e+05	6.042e+05	6.222e+05	4.289e+05	2.752e+05	2.942e+05	1.766e+05	6.715e+05	6.477e+05	2.083e+05	1.52e+05	3.162e+05	8.263e+05	5.496e+05	6.154e+05	4.273e+05	7.697e+05	4.894e+05	1.772e+05	2.402e+05	9.18e+05	1.132e+06	9.709e+05	4.923e+05	6.567e+05	5.063e+05	1.605e+05	6.561e+05	4.685e+05	2.515e+05	5.313e+05	5.597e+05	3.691e+05	2.751e+05	4.437e+05	5.352e+05	6.736e+05	3.342e+05	5.787e+05	1.031e+06	3.067e+05	3.052e+05	3.494e+05	1.198e+05	3.789e+05	5.91e+05	1.428e+05	6.486e+05	1.022e+06	9.064e+05	1.333e+06	1.398e+06	5.994e+05	2.79e+05	9.223e+05	6.251e+05	8.493e+05	1.011e+06	1.181e+06	7.126e+05	6.209e+05	6.393e+05	5.246e+05	8.381e+05	1.842e+05	7.022e+05	2.885e+05	5.693e+05	1.577e+05	2.924e+05	1.728e+05	2.979e+05	2.107e+05	2.042e+05	6.344e+05	2.703e+05	2.651e+05	3.609e+05	3.659e+05	4.458e+05	3.788e+05	1.025e+05	2.908e+05	5.034e+05	3.946e+05	2.859e+05	2.412e+05	8.793e+05	7.929e+05	4.169e+05	5.545e+05	9.622e+05	9.778e+05	7.882e+05	5.738e+05	1.11e+05	6103	8.165e+05	9.861e+05	8.052e+05	4.772e+05	1.232e+05	8.644e+05	7.791e+05	3.331e+05	9.473e+05	9.648e+05	8.554e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5	1.15e+05	1.15e+05	3.589e+05	3.589e+05	1.622e+05	1.13e+05	4.141e+05	6.149e+05	5.064e+05	4.562e+05	5.885e+05	6.301e+05	9.959e+05	9.391e+05	7.506e+05	4.214e+05	1.273e+06	1.006e+06	7.961e+05	3.585e+05	2.969e+05	3.029e+05	4.976e+05	6.247e+05	5.792e+05	4.668e+05	3.137e+05	5.345e+05	3.353e+05	5.462e+05	4.274e+05	5.279e+05	1.066e+06	6.67e+05	2.727e+05	5.996e+05	5.323e+05	7.551e+05	1.944e+05	3.962e+05	5.057e+05	2.693e+05	4.617e+05	6.099e+05	4.228e+05	5.842e+05	5.465e+05	3.525e+05	5.966e+05	6.736e+05	6.014e+05	5.02e+05	4.411e+05	3.913e+05	4.908e+05	5.309e+05	5.212e+05	5.196e+05	4.972e+05	5.132e+05	6.72e+05	6.512e+05	6.624e+05	6.463e+05	4.972e+05	4.988e+05	4.475e+05	6.64e+05	7.185e+05	7.442e+05	6.816e+05	3.801e+05	3.384e+05	3.528e+05	3.593e+05	3.689e+05	3.785e+05	4.17e+05	4.17e+05	4.33e+05	4.33e+05	5.052e+05	5.293e+05	5.533e+05	5.774e+05	5.581e+05	5.293e+05	5.325e+05	5.453e+05	5.453e+05	5.934e+05	5.934e+05	5.453e+05	5.293e+05	5.212e+05	5.132e+05	5.333e+05	5.934e+05	5.806e+05	5.293e+05	5.293e+05	4.972e+05	4.972e+05	4.852e+05	4.812e+05	4.731e+05	4.651e+05	4.731e+05	4.972e+05	5.036e+05	5.293e+05	5.293e+05	5.613e+05	5.613e+05	6.095e+05	6.255e+05	6.496e+05	6.736e+05	6.977e+05	7.698e+05	7.698e+05	7.538e+05	7.538e+05	7.538e+05	7.538e+05	7.298e+05	7.217e+05	7.538e+05	7.859e+05	7.859e+05	7.859e+05	7.859e+05	6.255e+05	6.255e+05	6.576e+05	6.576e+05	5.734e+05	5.453e+05	5.694e+05	5.934e+05	5.974e+05	6.095e+05	6.095e+05	5.774e+05	5.774e+05	5.646e+05	5.613e+05	5.493e+05	5.453e+05	5.453e+05	5.453e+05	5.293e+05	4.812e+05	4.812e+05	4.812e+05	4.812e+05	4.555e+05	4.491e+05	3.769e+05	3.528e+05	4.09e+05	4.651e+05	4.651e+05	4.651e+05	4.651e+05	4.972e+05	4.972e+05	4.972e+05	4.972e+05	4.876e+05	4.812e+05	4.972e+05	5.132e+05	5.092e+05	4.972e+05	4.972e+05	5.132e+05	5.132e+05	4.106e+05	3.849e+05	3.464e+05	3.208e+05	3.448e+05	3.689e+05	3.649e+05	3.528e+05	3.528e+05	4.01e+05	4.01e+05	3.496e+05	3.368e+05	3.464e+05	3.528e+05	4.459e+05	5.212e+05	4.812e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	4.236e+05	4.852e+05	5.758e+05	5.557e+05	5.196e+05	3.857e+05	2.991e+05	3.264e+05	3.424e+05	4.29e+05	5.253e+05	5.1e+05	5.79e+05	5.533e+05	5.822e+05	6.351e+05	5.918e+05	5.365e+05	5.846e+05	5.974e+05	5.83e+05	6.215e+05	5.541e+05	5.245e+05	4.908e+05	4.691e+05	3.889e+05	3.039e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.011e+05	2.048e+05	2.147e+05	2.628e+05	3.294e+05	3.084e+05	3.183e+05	3.941e+05	4.17e+05	3.775e+05	3.294e+05	3.639e+05	3.183e+05	2.64e+05	2.282e+05	2.727e+05	2.677e+05	2.369e+05	2.541e+05	2.887e+05	2.912e+05	3.171e+05	3.862e+05	4.285e+05	4.972e+05	4.775e+05	5.416e+05	5.071e+05	5.379e+05	6.193e+05	6.107e+05	5.854e+05	5.601e+05	6.255e+05	6.033e+05	5.33e+05	5.453e+05	5.737e+05	6.329e+05	6.324e+05	5.737e+05	5.934e+05	5.317e+05	5.934e+05	5.416e+05	5.095e+05	5.33e+05	4.972e+05	4.367e+05	3.578e+05	3.356e+05	3.195e+05	3.22e+05	2.936e+05	3.726e+05	4.651e+05	5.515e+05	5.515e+05	5.737e+05	5.687e+05	4.96e+05	4.441e+05	4.244e+05	5.132e+05	5.774e+05	7.612e+05	8.007e+05	8.513e+05	8.414e+05	8.291e+05	7.501e+05	6.667e+05	6.354e+05	6.551e+05	6.304e+05	5.984e+05	5.922e+05	5.28e+05	4.997e+05	5.212e+05	4.565e+05	3.491e+05	3.664e+05	3.677e+05	3.602e+05	3.454e+05	4.639e+05	5.018e+05	5.009e+05	4.91e+05	4.947e+05	4.651e+05	4.047e+05	4.269e+05	4.812e+05	5.132e+05	5.453e+05	5.65e+05	5.922e+05	5.984e+05	5.663e+05	6.452e+05	7.242e+05	7.767e+05	7.341e+05	7.538e+05	7.6e+05	6.588e+05	5.91e+05	5.367e+05	4.898e+05	4.731e+05	4.935e+05	5.441e+05	5.564e+05	5.243e+05	5.811e+05	5.391e+05	5.589e+05	5.224e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05	4.908e+05	5.245e+05	6.56e+05	6.64e+05	6.528e+05	6.544e+05	4.972e+05	5.004e+05	5.212e+05	5.245e+05	5.293e+05	4.619e+05	4.026e+05	4.443e+05	5.245e+05	6.223e+05	6.608e+05	5.95e+05	6.897e+05	8.26e+05	8.693e+05	8.581e+05	7.009e+05	4.86e+05	3.849e+05	4.779e+05	6.544e+05	7.49e+05	7.65e+05	6.383e+05	4.828e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	4.6e+04	3.939e+04	3.159e+04	7.197e+04	1.287e+05	2.032e+05	9.229e+04	1.671e+05	9.075e+04	2.425e+05	2.358e+05	2.932e+05	4.04e+05	4.469e+05	4.415e+05	4.751e+05	3.438e+05	1.74e+05	4.648e+05	4.482e+05	4.31e+05	1.6e+05	3.938e+05	3.57e+05	2.501e+05	2.862e+05	4.141e+05	4.2e+05	5.175e+05	4.438e+05	2.561e+05	2.784e+05	1.748e+05	7.74e+05	4.429e+05	8.796e+05	4.625e+05	4.815e+05	9.287e+04	9.771e+05	8.994e+05	9.669e+05	3.467e+05	2.755e+05	4.908e+05	7.184e+05	3.026e+05	3.215e+05	4.545e+05	1.647e+05	2.813e+05	6.483e+05	1.013e+06	5.112e+05	6.088e+05	7.155e+05	3.233e+05	6.973e+05	3.843e+05	1.258e+05	2.598e+05	4.569e+05	1.539e+05	1.044e+05	6.231e+05	5.44e+05	5.003e+05	7.535e+05	5.938e+05	5.794e+05	3.093e+05	4.641e+05	9.185e+05	1.052e+06	8.736e+05	4.645e+05	7.972e+04	6.469e+05	1.021e+06	3.97e+05	3.833e+05	4.543e+05	5.348e+05	1.182e+05	3.456e+05	7.172e+05	3.286e+05	9.042e+05	7.55e+05	7.278e+05	2.976e+05	1.059e+05	2.781e+05	4.016e+05	5.452e+05	3.632e+05	5.957e+05	2.375e+05	2.71e+05	1.451e+05	7.429e+05	5.801e+05	5.737e+05	3.818e+04	2.425e+05	4.467e+05	5.558e+05	4.375e+05	2.246e+05	2.698e+05	4.324e+05	6.658e+05	6.303e+05	1.276e+06	1.241e+06	1.343e+06	4.888e+05	3.539e+05	2.821e+05	1.485e+05	4.735e+05	7.436e+05	7.535e+05	4.17e+05	8.721e+05	8.141e+05	6.262e+05	8.989e+05	7.404e+05	3.855e+05	4.87e+05	4.994e+05	3.617e+05	1.174e+06	9.278e+05	8.47e+05	7.408e+05	5.18e+05	2.606e+05	6.947e+05	5.925e+05	9.567e+05	4.865e+05	5.181e+05	5.012e+05	7.23e+05	7.768e+05	6.315e+05	3.819e+05	5.996e+05	3.202e+05	4.24e+05	5.698e+05	4.736e+05	9.988e+05	2.406e+05	8.014e+05	4.373e+05	5.282e+05	6.196e+05	8.133e+05	6.367e+05	6.969e+05	2.85e+05	7.067e+05	6.29e+05	9.503e+05	4.485e+05	8.747e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	4615	3.187e+04	3.748e+04	1.002e+05	1.65e+05	7.499e+04	5.974e+04	8.493e+04	2.645e+05	9.967e+04	9.906e+04	3.618e+05	3.202e+05	5.493e+05	2.53e+05	5.169e+05	5.19e+05	5.162e+05	2.435e+05	5.15e+05	4.068e+05	2.92e+05	3.861e+05	1.515e+05	3.56e+05	1.402e+05	2.142e+05	3.478e+05	3.994e+05	3.832e+05	3.492e+05	5.407e+05	6.008e+05	5.727e+05	3.262e+05	7.522e+05	4.821e+05	5.194e+05	2.766e+05	2.69e+05	4.204e+05	7.266e+05	2.083e+05	1.369e+05	4.535e+05	8.582e+05	4.338e+05	4.965e+05	7.321e+05	3.451e+05	1.772e+05	7.838e+05	1.132e+06	8.932e+05	3.567e+05	8.235e+05	1.363e+05	6.809e+05	3.555e+05	3.731e+05	5.615e+05	3.879e+05	3.063e+05	4.202e+05	6.567e+05	4.217e+05	5.625e+05	9.852e+05	1.902e+05	3.37e+05	1.593e+05	4.017e+05	4.51e+05	1.428e+05	1.148e+06	8.883e+05	1.362e+06	1.224e+06	3.673e+05	6.69e+05	6.829e+05	8.6e+05	1.16e+06	9.517e+05	5.575e+05	6.412e+05	5.261e+05	7.37e+05	3.921e+05	3.999e+05	4.991e+05	2.265e+05	1.901e+05	2.698e+05	2.375e+05	2.182e+05	6.425e+05	1.57e+05	3.446e+05	3.721e+05	4.458e+05	2.474e+05	1.481e+05	5.034e+05	3.946e+05	2.859e+05	4.263e+05	9.39e+05	4.888e+05	6.034e+05	9.808e+05	8.773e+05	7.04e+05	1.245e+05	6103	1.202e+06	7.428e+05	6.032e+05	1.65e+05	8.58e+05	5.194e+05	7.567e+05	9.82e+05	8.55e+05	4.157e+05	6.714e+05	4.767e+05	4.435e+05	1.196e+05	3.955e+05	3.354e+05	5.455e+05	3.502e+05	1.363e+06	6.888e+05	8.144e+05	7.242e+05	2.651e+05	4.159e+05	4.555e+05	4.697e+05	1.078e+06	5.951e+05	5.548e+05	5.354e+05	8.009e+05	4.229e+05	4.392e+05	6.268e+05	4.654e+05	5.296e+05	3.183e+05	6.417e+05	6.954e+05	5.306e+05	1.808e+05	2.6e+05	1.486e+06	1.317e+06	7.978e+05	1.021e+06	2.059e+05	2.917e+05	4.52e+05	8.066e+05	7.637e+05	9.423e+04	5.573e+05	4.092e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.011e+05	2.048e+05	2.147e+05	2.628e+05	3.294e+05	3.084e+05	3.183e+05	3.941e+05	4.17e+05	3.775e+05	3.294e+05	3.639e+05	3.183e+05	2.64e+05	2.282e+05	2.727e+05	2.677e+05	2.369e+05	2.541e+05	2.887e+05	2.912e+05	3.171e+05	3.862e+05	4.285e+05	4.972e+05	4.775e+05	5.416e+05	5.071e+05	5.379e+05	6.193e+05	6.107e+05	5.854e+05	5.601e+05	6.255e+05	6.033e+05	5.33e+05	5.453e+05	5.737e+05	6.329e+05	6.324e+05	5.737e+05	5.934e+05	5.317e+05	5.934e+05	5.416e+05	5.095e+05	5.33e+05	4.972e+05	4.367e+05	3.578e+05	3.356e+05	3.195e+05	3.22e+05	2.936e+05	3.726e+05	4.651e+05	5.515e+05	5.515e+05	5.737e+05	5.687e+05	4.96e+05	4.441e+05	4.17e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	4.997e+05	5.212e+05	4.565e+05	3.491e+05	3.664e+05	3.677e+05	3.602e+05	3.454e+05	4.639e+05	5.018e+05	5.009e+05	4.91e+05	4.947e+05	4.651e+05	4.047e+05	4.269e+05	4.812e+05	5.132e+05	5.453e+05	5.65e+05	5.922e+05	5.984e+05	5.663e+05	6.452e+05	7.242e+05	7.767e+05	7.341e+05	7.538e+05	7.6e+05	6.588e+05	5.91e+05	5.367e+05	4.898e+05	4.731e+05	4.935e+05	5.441e+05	5.564e+05	5.243e+05	5.811e+05	5.391e+05	5.589e+05	5.224e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05	4.908e+05	5.245e+05	6.56e+05	6.64e+05	6.528e+05	6.544e+05	4.972e+05	5.004e+05	5.212e+05	5.245e+05	5.293e+05	4.619e+05	4.026e+05	4.443e+05	5.245e+05	6.223e+05	6.608e+05	5.95e+05	6.897e+05	8.26e+05	8.693e+05	8.581e+05	7.009e+05	4.86e+05	3.849e+05	4.779e+05	6.544e+05	7.49e+05	7.65e+05	6.383e+05	4.828e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.684e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05	2.35e+05	2.783e+05	2.374e+05	2.791e+05	2.943e+05	3.601e+05	4.451e+05	4.86e+05	5.245e+05	5.301e+05	6.215e+05	5.878e+05	5.83e+05	6.087e+05	5.341e+05	5.702e+05	6.423e+05	5.846e+05	5.654e+05	5.814e+05	5.172e+05	5.325e+05	4.579e+05	3.617e+05	3.312e+05	3.039e+05	3.496e+05	4.812e+05	5.533e+05	5.782e+05	5.14e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.033e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	8.928e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	1.47e+05	1.47e+05	1.47e+05	4.001e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.475e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	1.555e+04	2.06e+05	2.06e+05	2.06e+05	2.06e+05	2.06e+05	2.463e+05	2.766e+05	4.201e+05	4.441e+05	4.341e+05	2.003e+05	4.916e+05	4.16e+05	2.319e+05	3.705e+05	2.521e+05	3.837e+05	4.903e+05	3.499e+05	3.34e+05	3.196e+05	5.857e+05	6.837e+05	5.134e+05	4.12e+05	9.132e+05	7.498e+05	2.927e+05	6.237e+05	3.78e+05	4.068e+05	2.268e+05	4.226e+05	9.638e+05	4.61e+05	6.603e+05	4.745e+05	3.763e+05	2.231e+05	3.585e+05	1.291e+05	6.234e+05	4.614e+05	6.801e+05	6.056e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	6488	119.7	119.7	119.7	119.7	119.7	119.7	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	1.271e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	3.165e+04	3.165e+04	3.165e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	2.462e+05	3.353e+05	3.353e+05	3.353e+05	3.353e+05	3.353e+05	7.494e+04	3.092e+05	4.296e+05	3.164e+05	5.363e+05	5.139e+05	3.27e+05	4.209e+05	3.371e+05	2.483e+05	2.37e+05	2.151e+05	3.85e+05	3.626e+05	4.746e+05	5.94e+05	4.325e+05	6.028e+05	5.457e+05	2.836e+05	3.652e+05	5.452e+05	1.541e+05	6.811e+05	5.386e+05	5.7e+05	4.195e+05	4.198e+05	1.093e+06	6.04e+05	5.835e+05	4.058e+05	4.013e+05	5.025e+05	3.594e+05	4.032e+05	6.366e+05	4.39e+05	7.228e+05	3.033e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.684e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05	2.35e+05	2.783e+05	2.374e+05	2.791e+05	2.943e+05	3.601e+05	4.451e+05	4.86e+05	5.245e+05	5.301e+05	6.215e+05	5.878e+05	5.83e+05	6.087e+05	5.341e+05	5.702e+05	6.423e+05	5.846e+05	5.654e+05	5.814e+05	5.172e+05	5.325e+05	4.579e+05	3.617e+05	3.312e+05	3.039e+05	3.496e+05	4.812e+05	5.533e+05	5.782e+05	5.14e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.17e+05	4.972e+05	5.132e+05	5.132e+05	5.934e+05	5.934e+05	5.774e+05	6.255e+05	5.453e+05	5.533e+05	6.255e+05	6.014e+05	5.934e+05	5.533e+05	5.453e+05	5.212e+05	4.972e+05	4.01e+05	3.368e+05	3.208e+05	3.047e+05	4.25e+05	5.533e+05	5.613e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.968e+04	1.968e+04	1.968e+04	1.968e+04	1.968e+04	1.968e+04	1.968e+04	1.968e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	8.361e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	1.47e+05	1.47e+05	1.47e+05	1.47e+05	4.001e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.475e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	1.731e+05	4.412e+05	2.501e+05	3.76e+05	4.27e+05	5.175e+05	3.214e+05	7.494e+04	7.74e+05	6.494e+05	5.428e+05	1.479e+05	9.452e+05	9.481e+05	3.467e+05	4.079e+05	5.606e+05	3.151e+05	3.206e+05	2.813e+05	8.491e+05	5.47e+05	7.885e+05	3.233e+05	6.649e+05	1.356e+05	3.99e+05	1.572e+05	3.874e+05	4.862e+05	7.298e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	7762	7762	7762	7762	7762	7762	7762	7762	119.7	119.7	119.7	119.7	119.7	119.7	119.7	119.7	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	3.165e+04	3.165e+04	3.165e+04	3.165e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	2.912e+05	2.38e+05	3.56e+05	1.442e+05	3.515e+05	3.994e+05	3.657e+05	6.055e+05	5.727e+05	5.402e+05	5.641e+05	2.842e+05	2.367e+05	7.047e+05	2.083e+05	3.424e+05	5.889e+05	5.68e+05	6.667e+05	1.772e+05	1.001e+06	9.103e+05	6.567e+05	1.363e+05	6.043e+05	3.844e+05	4.909e+05	3.384e+05	5.503e+05	3.589e+05	9.777e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	1.604e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	4.812e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.17e+05	4.972e+05	5.132e+05	5.132e+05	5.934e+05	5.934e+05	5.774e+05	6.255e+05	5.453e+05	5.533e+05	6.255e+05	6.014e+05	5.934e+05	5.533e+05	5.453e+05	5.212e+05	4.972e+05	4.01e+05	3.368e+05	3.208e+05	3.047e+05	4.25e+05	5.533e+05	5.613e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.123e+04	1.395e+05	1.443e+05	1.66e+05	1.7e+05	1.147e+05	1.427e+05	1.451e+05	1.66e+05	2.069e+05	2.149e+05	2.999e+05	3.071e+05	3.633e+05	4.162e+05	3.657e+05	3.528e+05	3.272e+05	3.208e+05	3.593e+05	3.689e+05	3.561e+05	3.528e+05	3.015e+05	2.887e+05	2.63e+05	2.566e+05	2.31e+05	2.245e+05	2.374e+05	2.406e+05	2.919e+05	3.047e+05	2.662e+05	2.566e+05	2.438e+05	2.406e+05	2.277e+05	2.245e+05	2.759e+05	2.887e+05	2.887e+05	2.887e+05	2.887e+05	2.887e+05	3.015e+05	3.047e+05	3.304e+05	3.368e+05	4.01e+05	4.17e+05	4.17e+05	4.17e+05	4.812e+05	4.972e+05	4.972e+05	4.972e+05	4.715e+05	4.651e+05	5.421e+05	5.613e+05	5.1e+05	4.972e+05	5.229e+05	5.293e+05	5.421e+05	5.453e+05	6.223e+05	6.415e+05	6.287e+05	6.255e+05	5.742e+05	5.613e+05	5.998e+05	6.095e+05	5.581e+05	5.453e+05	6.095e+05	6.255e+05	6.255e+05	6.255e+05	5.87e+05	5.774e+05	5.261e+05	5.132e+05	5.389e+05	5.453e+05	5.581e+05	5.613e+05	5.87e+05	5.934e+05	6.447e+05	6.576e+05	6.447e+05	6.415e+05	5.774e+05	5.613e+05	5.87e+05	5.934e+05	5.934e+05	5.934e+05	5.293e+05	5.132e+05	5.774e+05	5.934e+05	5.934e+05	5.934e+05	5.164e+05	4.972e+05	5.1e+05	5.132e+05	5.261e+05	5.293e+05	5.421e+05	5.453e+05	4.683e+05	4.491e+05	4.362e+05	4.33e+05	3.817e+05	3.689e+05	3.304e+05	3.208e+05	3.464e+05	3.528e+05	3.144e+05	3.047e+05	3.304e+05	3.368e+05	2.727e+05	2.566e+05	3.336e+05	3.528e+05	3.785e+05	3.849e+05	5.052e+05	5.533e+05	5.854e+05	4.972e+05	4.25e+05	5.132e+05	6.656e+05	8.019e+05	8.5e+05	8.18e+05	6.977e+05	6.335e+05	6.496e+05	6.014e+05	5.453e+05	5.212e+05	4.651e+05	3.448e+05	3.769e+05	3.448e+05	4.491e+05	5.052e+05	4.892e+05	4.812e+05	4.09e+05	4.651e+05	5.132e+05	5.533e+05	5.934e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	5.212e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	4.996e+04	3.419e+04	3.159e+04	8.351e+04	1.387e+05	1.98e+05	8.016e+04	1.67e+05	1.041e+05	2.51e+05	2.941e+05	4.228e+05	4.442e+05	4.234e+05	1.827e+05	5.521e+05	6.466e+05	4.544e+05	4.064e+05	4.574e+05	4.701e+05	3.683e+05	3.428e+05	7.124e+04	3351	4.094e+05	5.11e+05	3.994e+05	3.715e+05	3.213e+05	3.088e+05	2.149e+05	1.914e+05	2.899e+05	3.146e+05	4.128e+05	4.374e+05	3.567e+05	3.365e+05	4.813e+05	5.175e+05	5.175e+05	5.175e+05	5.175e+05	5.175e+05	1.345e+05	3.873e+04	4.909e+05	6.04e+05	1.808e+05	7.494e+04	7.494e+04	7.494e+04	6.342e+05	7.74e+05	7.74e+05	7.74e+05	3.436e+05	2.36e+05	8.975e+05	1.063e+06	4.799e+05	3.341e+05	6.68e+05	7.515e+05	3.504e+05	2.501e+05	8.658e+04	4.569e+04	8.128e+05	1.005e+06	9.095e+05	8.858e+05	9.077e+05	9.131e+05	9.69e+05	9.83e+05	4.739e+05	3.467e+05	3.467e+05	3.467e+05	2.233e+05	1.925e+05	5.372e+05	6.233e+05	7.72e+05	8.091e+05	4.115e+05	3.121e+05	2.923e+05	2.874e+05	3.317e+05	3.428e+05	5.081e+05	5.494e+05	1.834e+05	9.19e+04	2.434e+05	2.813e+05	2.813e+05	2.813e+05	6.044e+05	6.852e+05	9.474e+05	1.013e+06	1.013e+06	1.013e+06	2.675e+05	8.112e+04	6.299e+05	7.671e+05	8.014e+05	8.1e+05	4.827e+05	4.008e+05	2.768e+05	2.458e+05	7.154e+05	8.327e+05	5.642e+05	4.971e+05	1.06e+05	8214	2.12e+05	2.63e+05	2.593e+05	2.583e+05	4.833e+05	5.396e+05	2.221e+05	1.427e+05	1.659e+05	1.718e+05	8.414e+04	6.223e+04	7.245e+05	4.508e+05	6.588e+05	5.918e+05	3.203e+05	9.185e+05	9.831e+05	4.416e+05	2.849e+05	8.511e+05	4.717e+05	5.14e+05	2.248e+05	4.798e+05	4.311e+05	9.528e+05	6.365e+05	2.346e+05	2.265e+05	4.257e+05	4.238e+05	4.172e+05	3.237e+05	4.191e+05	5.917e+05	3.259e+05	2.425e+05	4.644e+05	4.071e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	7.66e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	4142	3.561e+04	3.748e+04	1.182e+05	1.465e+05	8.009e+04	5.705e+04	9.539e+04	2.82e+05	4.431e+04	3.458e+05	4.549e+05	2.879e+05	5.501e+05	5.155e+05	1.617e+05	7.304e+04	5.015e+05	6.086e+05	4.921e+05	4.63e+05	3.168e+05	2.802e+05	2.977e+05	3.021e+05	3.895e+05	4.113e+05	1.34e+05	6.466e+04	3.657e+05	4.409e+05	3.051e+05	2.711e+05	1.35e+05	1.01e+05	1.701e+05	1.874e+05	2.804e+05	3.037e+05	3.802e+05	3.994e+05	3.994e+05	3.994e+05	3.994e+05	3.994e+05	3.154e+05	2.944e+05	4.085e+05	4.37e+05	5.718e+05	6.055e+05	6.055e+05	6.055e+05	5.793e+05	5.727e+05	5.727e+05	5.727e+05	2.523e+05	1.722e+05	7.611e+05	9.083e+05	4.623e+05	3.508e+05	6.92e+05	7.773e+05	3.941e+05	2.983e+05	2.757e+05	2.7e+05	2.913e+05	2.967e+05	2.006e+05	1.766e+05	5.666e+05	6.641e+05	7.291e+05	7.453e+05	3.157e+05	2.083e+05	2.083e+05	2.083e+05	8.453e+04	5.36e+04	5.158e+05	6.313e+05	9.433e+05	1.021e+06	3.295e+05	1.565e+05	7.334e+05	8.776e+05	3.822e+05	2.584e+05	7.583e+05	8.833e+05	5.367e+05	4.501e+05	2.318e+05	1.772e+05	1.772e+05	1.772e+05	7.317e+05	8.703e+05	1.08e+06	1.132e+06	1.132e+06	1.132e+06	7.77e+05	6.881e+05	3.434e+05	2.573e+05	8.964e+05	1.056e+06	2.496e+05	4.796e+04	1.894e+05	2.247e+05	6.992e+05	8.178e+05	4.763e+05	3.909e+05	2.682e+05	2.376e+05	4.725e+05	5.313e+05	5.662e+05	5.75e+05	4.405e+05	4.069e+05	2.407e+05	1.992e+05	4.219e+05	4.776e+05	4.03e+05	3.844e+05	6.736e+05	4.734e+05	6.135e+05	3.36e+05	1.984e+05	4.51e+05	6.992e+05	8.966e+05	1.437e+06	3.479e+05	7.63e+05	8.661e+05	1.127e+06	6.209e+05	5.23e+05	4.836e+05	5.298e+05	3.639e+05	2.37e+05	3.003e+05	1.951e+05	4.447e+05	3.382e+05	4.059e+05	2.616e+05	3.364e+05	3.946e+05	2.508e+05	9.233e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	5.289e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.123e+04	1.395e+05	1.443e+05	1.66e+05	1.7e+05	1.147e+05	1.427e+05	1.451e+05	1.66e+05	2.069e+05	2.149e+05	2.999e+05	3.071e+05	3.633e+05	4.162e+05	3.657e+05	3.528e+05	3.272e+05	3.208e+05	3.593e+05	3.689e+05	3.561e+05	3.528e+05	3.015e+05	2.887e+05	2.63e+05	2.566e+05	2.31e+05	2.245e+05	2.374e+05	2.406e+05	2.919e+05	3.047e+05	2.662e+05	2.566e+05	2.438e+05	2.406e+05	2.277e+05	2.245e+05	2.759e+05	2.887e+05	2.887e+05	2.887e+05	2.887e+05	2.887e+05	3.015e+05	3.047e+05	3.304e+05	3.368e+05	4.01e+05	4.17e+05	4.17e+05	4.17e+05	4.812e+05	4.972e+05	4.972e+05	4.972e+05	4.715e+05	4.651e+05	5.421e+05	5.613e+05	5.1e+05	4.972e+05	5.229e+05	5.293e+05	5.421e+05	5.453e+05	6.223e+05	6.415e+05	6.287e+05	6.255e+05	5.742e+05	5.613e+05	5.998e+05	6.095e+05	5.581e+05	5.453e+05	6.095e+05	6.255e+05	6.255e+05	6.255e+05	5.87e+05	5.774e+05	5.261e+05	5.132e+05	5.389e+05	5.453e+05	5.581e+05	5.613e+05	5.87e+05	5.934e+05	6.447e+05	6.576e+05	6.447e+05	6.415e+05	5.774e+05	5.613e+05	5.87e+05	5.934e+05	5.934e+05	5.934e+05	5.293e+05	5.132e+05	5.774e+05	5.934e+05	5.934e+05	5.934e+05	5.164e+05	4.972e+05	5.1e+05	5.132e+05	5.261e+05	5.293e+05	5.421e+05	5.453e+05	4.683e+05	4.491e+05	4.362e+05	4.33e+05	3.817e+05	3.689e+05	3.304e+05	3.208e+05	3.464e+05	3.528e+05	3.144e+05	3.047e+05	3.304e+05	3.368e+05	2.727e+05	2.566e+05	3.336e+05	3.528e+05	3.785e+05	3.849e+05	5.052e+05	5.533e+05	5.854e+05	4.972e+05	4.25e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.212e+05	4.651e+05	3.448e+05	3.769e+05	3.448e+05	4.491e+05	5.052e+05	4.892e+05	4.812e+05	4.09e+05	4.651e+05	5.132e+05	5.533e+05	5.934e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	5.212e+05
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_scale.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_scale.gz
new file mode 100644
index 0000000000..4cfb5c9ce6
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_scale.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_scale.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_scale.tab
new file mode 100644
index 0000000000..ba4d8a7bf2
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_scale.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:422	upstream:98	body:842	bin size:2	unscaled 5 prime:22	unscaled 3 prime:44
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4e+04	4.854e+04	5.559e+05	5.559e+05	5.559e+05	5.744e+05	5.744e+05	5.744e+05	1.841e+05	1.841e+05	1.841e+05	4.354e+05	5.191e+05	5.191e+05	5.859e+05	6.194e+05	6.194e+05	4.787e+05	4.084e+05	4.084e+05	4.975e+05	5.866e+05	5.866e+05	5.032e+05	3.366e+05	3.366e+05	2.953e+05	2.127e+05	2.127e+05	2.313e+05	2.87e+05	2.87e+05	2.87e+05	6.12e+05	6.12e+05	6.12e+05	8.209e+05	8.209e+05	8.209e+05	8.209e+05	8.209e+05	8.209e+05	7.398e+05	7.128e+05	7.128e+05	6.22e+05	5.766e+05	5.766e+05	2.671e+05	1.123e+05	1.123e+05	7.611e+04	3.99e+04	3.99e+04	1.615e+05	4.046e+05	4.046e+05	6.82e+05	1.237e+06	1.237e+06	8.549e+05	9.089e+04	9.089e+04	9.089e+04	4.464e+05	4.464e+05	4.464e+05	2.894e+05	2.894e+05	2.894e+05	1.994e+05	1.994e+05	1.994e+05	5.016e+05	6.024e+05	6.024e+05	4.017e+05	3.014e+05	3.014e+05	1.334e+05	4.935e+04	4.935e+04	8.453e+04	1.021e+05	1.021e+05	2.836e+05	6.464e+05	6.464e+05	5.925e+05	4.848e+05	4.848e+05	3.858e+05	1.878e+05	1.878e+05	1.878e+05	6.728e+05	6.728e+05	6.728e+05	8.136e+05	8.136e+05	8.136e+05	3.641e+05	3.641e+05	3.641e+05	6.288e+05	6.288e+05	6.288e+05	3.925e+05	2.743e+05	2.743e+05	1.525e+05	9.167e+04	9.167e+04	7.853e+04	7.196e+04	7.196e+04	1.767e+05	2.814e+05	2.814e+05	2.902e+05	3.078e+05	3.078e+05	3.24e+05	3.563e+05	3.563e+05	4.011e+05	5.355e+05	5.355e+05	5.355e+05	1.256e+05	1.256e+05	1.256e+05	6.19e+05	6.19e+05	6.19e+05	3.191e+04	3.191e+04	3.191e+04	3.31e+05	4.307e+05	4.307e+05	1.931e+05	7.434e+04	7.434e+04	7.434e+04	7.434e+04	7.434e+04	3.269e+05	5.794e+05	5.794e+05	5.794e+05	5.794e+05	5.794e+05	5.008e+05	3.436e+05	3.436e+05	3.774e+05	4.787e+05	4.787e+05	4.787e+05	2.978e+04	2.978e+04	2.978e+04	2.978e+04	2.978e+04	2.978e+04	3.485e+05	3.485e+05	3.485e+05	3.485e+05	3.485e+05	3.485e+05	3.669e+05	3.761e+05	3.761e+05	3.761e+05	6.25e+05	6.25e+05	6.25e+05	6.25e+05	6.25e+05	1.019e+04	1.019e+04	1.019e+04	1.019e+04	1.019e+04	2.485e+05	2.485e+05	2.485e+05	2.485e+05	2.485e+05	2.269e+05	2.269e+05	2.269e+05	2.269e+05	2.269e+05	1.09e+05	1.09e+05	1.09e+05	1.09e+05	1.09e+05	7.025e+05	7.025e+05	7.025e+05	7.025e+05	7.025e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	1.013e+06	1.013e+06	1.013e+06	1.013e+06	1.013e+06	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	1.126e+06	1.126e+06	1.126e+06	1.126e+06	1.126e+06	4.275e+05	4.275e+05	4.275e+05	4.275e+05	4.275e+05	2.773e+05	2.773e+05	2.773e+05	2.773e+05	2.773e+05	2.749e+05	2.749e+05	2.749e+05	2.749e+05	2.749e+05	2.036e+05	2.036e+05	2.036e+05	2.036e+05	2.036e+05	7.116e+04	7.116e+04	7.116e+04	7.116e+04	7.116e+04	2.647e+05	2.647e+05	2.647e+05	2.647e+05	2.647e+05	4.741e+05	4.741e+05	4.741e+05	4.741e+05	4.741e+05	6.118e+05	6.118e+05	6.118e+05	6.118e+05	6.118e+05	6.811e+05	6.811e+05	6.811e+05	6.811e+05	6.811e+05	2.764e+05	2.764e+05	2.764e+05	2.764e+05	2.764e+05	3.824e+05	3.824e+05	3.824e+05	3.824e+05	3.824e+05	8.127e+05	8.127e+05	8.127e+05	8.127e+05	8.127e+05	6.755e+05	6.755e+05	6.755e+05	6.755e+05	6.755e+05	3.436e+05	3.436e+05	3.436e+05	3.436e+05	3.436e+05	7.202e+05	7.202e+05	7.202e+05	7.202e+05	7.202e+05	6.893e+05	6.893e+05	6.893e+05	6.893e+05	6.893e+05	5.569e+05	5.569e+05	5.569e+05	5.569e+05	5.569e+05	5.688e+05	5.688e+05	5.688e+05	5.688e+05	5.688e+05	9.609e+04	9.609e+04	9.609e+04	9.609e+04	9.609e+04	2.513e+05	2.513e+05	2.513e+05	2.513e+05	2.513e+05	4.728e+05	4.728e+05	4.728e+05	4.728e+05	4.728e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	3.719e+04	3.719e+04	3.719e+04	3.719e+04	3.719e+04	3.514e+05	3.514e+05	3.514e+05	3.514e+05	3.514e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	4.895e+05	4.895e+05	4.895e+05	4.895e+05	4.895e+05	1.126e+06	1.126e+06	1.126e+06	1.126e+06	1.126e+06	2.238e+05	2.238e+05	2.238e+05	2.238e+05	2.238e+05	9.843e+05	9.843e+05	9.843e+05	9.843e+05	9.843e+05	2.47e+05	2.47e+05	2.47e+05	2.47e+05	2.47e+05	6.063e+05	6.063e+05	6.063e+05	6.063e+05	6.063e+05	2.581e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	6055	6055	6055	6055	6055	3074	93.4	93.4	93.4	93.4	1.466e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	9.917e+04	1.691e+05	1.691e+05	1.691e+05	1.691e+05	1.792e+05	1.894e+05	1.894e+05	1.894e+05	1.894e+05	1.07e+05	2.468e+04	2.468e+04	2.468e+04	2.468e+04	6.445e+04	6.445e+04	6.445e+04	6.445e+04	6.445e+04	6.445e+04	5.045e+04	4.345e+04	4.345e+04	4.345e+04	4.345e+04	4.345e+04	3.768e+04	3.192e+04	3.192e+04	6.296e+04	1.25e+05	1.25e+05	1.474e+05	1.92e+05	1.92e+05	2.152e+05	2.615e+05	2.615e+05	2.615e+05	2.262e+04	2.262e+04	2.262e+04	2.262e+04	2.262e+04	2.262e+04	2.594e+05	2.594e+05	2.594e+05	2.964e+05	3.087e+05	3.087e+05	2.519e+05	2.235e+05	2.235e+05	4.117e+05	5.059e+05	5.059e+05	2.645e+05	1.438e+05	1.438e+05	1.902e+05	2.829e+05	2.829e+05	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05	1.594e+05	6.832e+04	6.832e+04	6.832e+04	6.832e+04	6.832e+04	1.519e+05	1.519e+05	1.519e+05	1.519e+05	1.519e+05	4.133e+05	4.133e+05	4.133e+05	4.133e+05	4.133e+05	4.113e+05	4.113e+05	4.113e+05	4.113e+05	4.113e+05	1.009e+05	1.009e+05	1.009e+05	1.009e+05	1.009e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	5.735e+04	5.735e+04	5.735e+04	5.735e+04	5.735e+04	2.878e+05	2.878e+05	2.878e+05	2.878e+05	2.878e+05	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.499e+05	1.499e+05	1.499e+05	1.499e+05	1.499e+05	3.709e+05	3.709e+05	3.709e+05	3.709e+05	3.709e+05	9.125e+05	9.125e+05	9.125e+05	9.125e+05	9.125e+05	3.066e+05	3.066e+05	3.066e+05	3.066e+05	3.066e+05	8.654e+05	8.654e+05	8.654e+05	8.654e+05	8.654e+05	9.55e+04	9.55e+04	9.55e+04	9.55e+04	9.55e+04	3.087e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.251e+04	1.251e+04	1.251e+04	1.251e+04	1.251e+04	2.502e+04	3.753e+04	3.753e+04	3.753e+04	3.753e+04	7.506e+04	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.314e+05	1.501e+05	1.501e+05	1.501e+05	1.501e+05	1.439e+05	1.376e+05	1.376e+05	1.376e+05	1.376e+05	1.314e+05	1.251e+05	1.251e+05	1.251e+05	1.251e+05	8.757e+04	8.757e+04	8.757e+04	8.757e+04	8.757e+04	8.757e+04	1.042e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.188e+05	1.251e+05	1.251e+05	1.168e+05	1.001e+05	1.001e+05	1.084e+05	1.251e+05	1.251e+05	1.293e+05	1.376e+05	1.376e+05	1.376e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.501e+05	1.501e+05	1.501e+05	1.783e+05	1.877e+05	1.877e+05	2.043e+05	2.127e+05	2.127e+05	2.46e+05	2.627e+05	2.627e+05	2.544e+05	2.502e+05	2.502e+05	2.419e+05	2.252e+05	2.252e+05	2.377e+05	2.627e+05	2.627e+05	2.794e+05	3.128e+05	3.128e+05	3.128e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	2.752e+05	2.752e+05	2.752e+05	2.502e+05	2.502e+05	2.502e+05	2.752e+05	2.877e+05	2.877e+05	2.794e+05	2.752e+05	2.752e+05	2.419e+05	2.252e+05	2.252e+05	2.127e+05	2.002e+05	2.002e+05	1.918e+05	1.751e+05	1.751e+05	1.793e+05	1.877e+05	1.877e+05	2.002e+05	2.377e+05	2.377e+05	2.377e+05	2.002e+05	2.002e+05	2.002e+05	1.877e+05	1.877e+05	1.877e+05	1.751e+05	1.751e+05	1.751e+05	2.127e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.314e+05	2.377e+05	2.377e+05	2.46e+05	2.627e+05	2.627e+05	2.836e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.628e+05	3.628e+05	3.628e+05	4.191e+05	4.378e+05	4.378e+05	4.045e+05	3.878e+05	3.878e+05	4.045e+05	4.128e+05	4.128e+05	4.191e+05	4.253e+05	4.253e+05	4.504e+05	5.004e+05	5.004e+05	4.962e+05	4.879e+05	4.879e+05	4.754e+05	4.378e+05	4.378e+05	4.378e+05	4.754e+05	4.754e+05	4.754e+05	4.253e+05	4.253e+05	4.253e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.629e+05	4.504e+05	4.504e+05	4.17e+05	4.003e+05	4.003e+05	4.128e+05	4.253e+05	4.253e+05	4.295e+05	4.378e+05	4.378e+05	4.462e+05	4.629e+05	4.629e+05	4.795e+05	5.129e+05	5.129e+05	5.129e+05	5.004e+05	5.004e+05	5.004e+05	4.378e+05	4.378e+05	4.378e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.212e+05	4.003e+05	4.003e+05	4.42e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.378e+05	3.878e+05	3.878e+05	3.92e+05	4.003e+05	4.003e+05	4.045e+05	4.128e+05	4.128e+05	4.16e+05	4.253e+05	4.253e+05	4.253e+05	3.503e+05	3.503e+05	3.503e+05	3.378e+05	3.378e+05	3.378e+05	2.877e+05	2.877e+05	2.877e+05	2.627e+05	2.502e+05	2.502e+05	2.669e+05	2.752e+05	2.752e+05	2.502e+05	2.377e+05	2.377e+05	2.502e+05	2.627e+05	2.627e+05	2.419e+05	2.002e+05	2.002e+05	2.252e+05	2.752e+05	2.752e+05	2.815e+05	3.002e+05	3.002e+05	3.002e+05	3.628e+05	3.628e+05	3.628e+05	4.253e+05	4.253e+05	4.253e+05	4.378e+05	4.378e+05	4.378e+05	4.285e+05	4.253e+05	4.253e+05	4.42e+05	4.504e+05	4.504e+05	4.587e+05	4.629e+05	4.629e+05	4.316e+05	4.003e+05	4.003e+05	3.92e+05	3.753e+05	3.753e+05	3.628e+05	3.378e+05	3.378e+05	3.346e+05	3.253e+05	3.253e+05	3.253e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.753e+05	3.753e+05	3.753e+05	4.378e+05	4.378e+05	4.378e+05	3.753e+05	3.753e+05	3.753e+05	3.503e+05	3.503e+05	3.503e+05	3.002e+05	2.752e+05	2.752e+05	2.669e+05	2.627e+05	2.627e+05	2.961e+05	3.128e+05	3.128e+05	2.94e+05	2.752e+05	2.752e+05	2.794e+05	2.877e+05	2.877e+05	2.752e+05	2.502e+05	2.502e+05	2.627e+05	3.002e+05	3.002e+05	3.002e+05	4.003e+05	4.003e+05	4.003e+05	3.878e+05	3.878e+05	3.878e+05	4.003e+05	4.003e+05	4.003e+05	3.816e+05	3.753e+05	3.753e+05	3.836e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05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99e+04	4.854e+04	4.854e+04	3.868e+05	5.559e+05	5.559e+05	5.682e+05	5.744e+05	5.744e+05	3.792e+05	1.841e+05	1.841e+05	2.958e+05	5.191e+05	5.191e+05	5.525e+05	6.194e+05	6.194e+05	5.666e+05	4.084e+05	4.084e+05	4.084e+05	5.866e+05	5.866e+05	5.866e+05	3.366e+05	3.366e+05	3.366e+05	2.127e+05	2.127e+05	2.127e+05	2.622e+05	2.87e+05	2.87e+05	5.037e+05	6.12e+05	6.12e+05	7.164e+05	8.209e+05	8.209e+05	8.209e+05	8.209e+05	8.209e+05	7.849e+05	7.128e+05	7.128e+05	6.788e+05	5.766e+05	5.766e+05	5.766e+05	1.123e+05	1.123e+05	1.123e+05	3.99e+04	3.99e+04	3.99e+04	4.046e+05	4.046e+05	4.046e+05	9.594e+05	1.237e+06	1.237e+06	4.729e+05	9.089e+04	9.089e+04	3.279e+05	4.464e+05	4.464e+05	3.941e+05	2.894e+05	2.894e+05	2.594e+05	1.994e+05	1.994e+05	3.001e+05	6.024e+05	6.024e+05	6.024e+05	3.014e+05	3.014e+05	3.014e+05	4.935e+04	4.935e+04	4.935e+04	1.021e+05	1.021e+05	1.021e+05	4.65e+05	6.464e+05	6.464e+05	5.387e+05	4.848e+05	4.848e+05	2.868e+05	1.878e+05	1.878e+05	3.494e+05	6.728e+05	6.728e+05	7.198e+05	8.136e+05	8.136e+05	6.638e+05	3.641e+05	3.641e+05	3.641e+05	6.288e+05	6.288e+05	6.288e+05	2.743e+05	2.743e+05	2.743e+05	9.167e+04	9.167e+04	9.167e+04	7.689e+04	7.196e+04	7.196e+04	2.116e+05	2.814e+05	2.814e+05	2.99e+05	3.078e+05	3.078e+05	3.24e+05	3.563e+05	3.563e+05	4.161e+05	5.355e+05	5.355e+05	3.989e+05	1.256e+05	1.256e+05	1.256e+05	6.19e+05	6.19e+05	6.19e+05	3.191e+04	3.191e+04	3.191e+04	4.307e+05	4.307e+05	4.307e+05	1.634e+05	7.434e+04	7.434e+04	7.434e+04	7.434e+04	7.434e+04	4.111e+05	5.794e+05	5.794e+05	5.794e+05	5.794e+05	5.794e+05	5.008e+05	3.436e+05	3.436e+05	3.886e+05	4.787e+05	4.787e+05	4.787e+05	2.978e+04	2.978e+04	2.978e+04	2.978e+04	2.978e+04	2.978e+04	3.485e+05	3.485e+05	3.485e+05	3.485e+05	3.485e+05	3.485e+05	3.669e+05	3.761e+05	3.761e+05	3.761e+05	6.25e+05	6.25e+05	6.25e+05	6.25e+05	6.25e+05	1.019e+04	1.019e+04	1.019e+04	1.019e+04	1.019e+04	2.485e+05	2.485e+05	2.485e+05	2.485e+05	2.485e+05	2.269e+05	2.269e+05	2.269e+05	2.269e+05	2.269e+05	1.09e+05	1.09e+05	1.09e+05	1.09e+05	1.09e+05	7.025e+05	7.025e+05	7.025e+05	7.025e+05	7.025e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	4.048e+05	1.013e+06	1.013e+06	1.013e+06	1.013e+06	1.013e+06	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	9.677e+05	1.126e+06	1.126e+06	1.126e+06	1.126e+06	1.126e+06	4.275e+05	4.275e+05	4.275e+05	4.275e+05	4.275e+05	2.773e+05	2.773e+05	2.773e+05	2.773e+05	2.773e+05	2.749e+05	2.749e+05	2.749e+05	2.749e+05	2.749e+05	2.036e+05	2.036e+05	2.036e+05	2.036e+05	2.036e+05	7.116e+04	7.116e+04	7.116e+04	7.116e+04	7.116e+04	2.647e+05	2.647e+05	2.647e+05	2.647e+05	2.647e+05	4.741e+05	4.741e+05	4.741e+05	4.741e+05	4.741e+05	6.118e+05	6.118e+05	6.118e+05	6.118e+05	6.118e+05	6.811e+05	6.811e+05	6.811e+05	6.811e+05	6.811e+05	2.764e+05	2.764e+05	2.764e+05	2.764e+05	2.764e+05	3.824e+05	3.824e+05	3.824e+05	3.824e+05	3.824e+05	8.127e+05	8.127e+05	8.127e+05	8.127e+05	8.127e+05	6.755e+05	6.755e+05	6.755e+05	6.755e+05	6.755e+05	3.436e+05	3.436e+05	3.436e+05	3.436e+05	3.436e+05	7.202e+05	7.202e+05	7.202e+05	7.202e+05	7.202e+05	6.893e+05	6.893e+05	6.893e+05	6.893e+05	6.893e+05	5.569e+05	5.569e+05	5.569e+05	5.569e+05	5.569e+05	5.688e+05	5.688e+05	5.688e+05	5.688e+05	5.688e+05	9.609e+04	9.609e+04	9.609e+04	9.609e+04	9.609e+04	2.513e+05	2.513e+05	2.513e+05	2.513e+05	2.513e+05	4.728e+05	4.728e+05	4.728e+05	4.728e+05	4.728e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	4.287e+05	3.719e+04	3.719e+04	3.719e+04	3.719e+04	3.719e+04	3.514e+05	3.514e+05	3.514e+05	3.514e+05	3.514e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	9.16e+05	4.895e+05	4.895e+05	4.895e+05	4.895e+05	4.895e+05	1.126e+06	1.126e+06	1.126e+06	1.126e+06	1.126e+06	2.238e+05	2.238e+05	2.238e+05	2.238e+05	2.238e+05	9.843e+05	9.843e+05	9.843e+05	9.843e+05	9.843e+05	2.47e+05	2.47e+05	2.47e+05	2.47e+05	2.47e+05	6.063e+05	6.063e+05	6.063e+05	6.063e+05	6.063e+05	2.581e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	6055	6055	6055	6055	6055	93.4	93.4	93.4	93.4	93.4	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	2.923e+04	1.691e+05	1.691e+05	1.691e+05	1.691e+05	1.691e+05	1.894e+05	1.894e+05	1.894e+05	1.894e+05	1.894e+05	2.468e+04	2.468e+04	2.468e+04	2.468e+04	2.468e+04	6.445e+04	6.445e+04	6.445e+04	6.445e+04	6.445e+04	6.445e+04	5.745e+04	4.345e+04	4.345e+04	4.345e+04	4.345e+04	4.345e+04	4.345e+04	3.192e+04	3.192e+04	3.192e+04	1.25e+05	1.25e+05	1.25e+05	1.753e+05	1.92e+05	1.92e+05	2.383e+05	2.615e+05	2.615e+05	1.022e+05	2.262e+04	2.262e+04	2.262e+04	2.262e+04	2.262e+04	1.016e+05	2.594e+05	2.594e+05	2.758e+05	3.087e+05	3.087e+05	3.087e+05	2.235e+05	2.235e+05	2.235e+05	5.059e+05	5.059e+05	5.059e+05	1.438e+05	1.438e+05	1.438e+05	2.482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	1.594e+05	1.594e+05	1.594e+05	1.594e+05	1.594e+05	6.832e+04	6.832e+04	6.832e+04	6.832e+04	6.832e+04	1.519e+05	1.519e+05	1.519e+05	1.519e+05	1.519e+05	4.133e+05	4.133e+05	4.133e+05	4.133e+05	4.133e+05	4.113e+05	4.113e+05	4.113e+05	4.113e+05	4.113e+05	1.009e+05	1.009e+05	1.009e+05	1.009e+05	1.009e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	5.735e+04	5.735e+04	5.735e+04	5.735e+04	5.735e+04	2.878e+05	2.878e+05	2.878e+05	2.878e+05	2.878e+05	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.499e+05	1.499e+05	1.499e+05	1.499e+05	1.499e+05	3.709e+05	3.709e+05	3.709e+05	3.709e+05	3.709e+05	9.125e+05	9.125e+05	9.125e+05	9.125e+05	9.125e+05	3.066e+05	3.066e+05	3.066e+05	3.066e+05	3.066e+05	8.654e+05	8.654e+05	8.654e+05	8.654e+05	8.654e+05	9.55e+04	9.55e+04	9.55e+04	9.55e+04	9.55e+04	3.087e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.251e+04	1.251e+04	1.251e+04	1.251e+04	1.251e+04	3.753e+04	3.753e+04	3.753e+04	3.753e+04	3.753e+04	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.501e+05	1.501e+05	1.501e+05	1.501e+05	1.501e+05	1.376e+05	1.376e+05	1.376e+05	1.376e+05	1.376e+05	1.251e+05	1.251e+05	1.251e+05	1.251e+05	1.251e+05	8.757e+04	8.757e+04	8.757e+04	8.757e+04	8.757e+04	8.757e+04	9.591e+04	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.251e+05	1.251e+05	1.251e+05	1.001e+05	1.001e+05	1.001e+05	1.188e+05	1.251e+05	1.251e+05	1.334e+05	1.376e+05	1.376e+05	1.543e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.585e+05	1.501e+05	1.501e+05	1.626e+05	1.877e+05	1.877e+05	1.877e+05	2.127e+05	2.127e+05	2.127e+05	2.627e+05	2.627e+05	2.627e+05	2.502e+05	2.502e+05	2.502e+05	2.314e+05	2.252e+05	2.252e+05	2.502e+05	2.627e+05	2.627e+05	2.961e+05	3.128e+05	3.128e+05	3.19e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.086e+05	2.752e+05	2.752e+05	2.69e+05	2.502e+05	2.502e+05	2.502e+05	2.877e+05	2.877e+05	2.877e+05	2.752e+05	2.752e+05	2.752e+05	2.377e+05	2.252e+05	2.252e+05	2.085e+05	2.002e+05	2.002e+05	1.835e+05	1.751e+05	1.751e+05	1.814e+05	1.877e+05	1.877e+05	2.043e+05	2.377e+05	2.377e+05	2.252e+05	2.002e+05	2.002e+05	1.97e+05	1.877e+05	1.877e+05	1.877e+05	1.751e+05	1.751e+05	1.751e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.335e+05	2.377e+05	2.377e+05	2.502e+05	2.627e+05	2.627e+05	2.836e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.409e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.628e+05	3.628e+05	3.628e+05	4.378e+05	4.378e+05	4.378e+05	4.045e+05	3.878e+05	3.878e+05	4.045e+05	4.128e+05	4.128e+05	4.212e+05	4.253e+05	4.253e+05	4.504e+05	5.004e+05	5.004e+05	4.962e+05	4.879e+05	4.879e+05	4.754e+05	4.378e+05	4.378e+05	4.378e+05	4.754e+05	4.754e+05	4.754e+05	4.253e+05	4.253e+05	4.253e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.629e+05	4.504e+05	4.504e+05	4.17e+05	4.003e+05	4.003e+05	4.087e+05	4.253e+05	4.253e+05	4.295e+05	4.378e+05	4.378e+05	4.462e+05	4.629e+05	4.629e+05	4.629e+05	5.129e+05	5.129e+05	5.129e+05	5.004e+05	5.004e+05	5.004e+05	4.378e+05	4.378e+05	4.378e+05	4.566e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.212e+05	4.003e+05	4.003e+05	4.316e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.378e+05	3.878e+05	3.878e+05	3.878e+05	4.003e+05	4.003e+05	4.003e+05	4.128e+05	4.128e+05	4.128e+05	4.253e+05	4.253e+05	4.253e+05	3.69e+05	3.503e+05	3.503e+05	3.419e+05	3.378e+05	3.378e+05	3.044e+05	2.877e+05	2.877e+05	2.69e+05	2.502e+05	2.502e+05	2.585e+05	2.752e+05	2.752e+05	2.627e+05	2.377e+05	2.377e+05	2.439e+05	2.627e+05	2.627e+05	2.627e+05	2.002e+05	2.002e+05	2.002e+05	2.752e+05	2.752e+05	2.752e+05	2.94e+05	3.002e+05	3.002e+05	3.419e+05	3.628e+05	3.628e+05	4.045e+05	4.253e+05	4.253e+05	4.316e+05	4.378e+05	4.378e+05	4.337e+05	4.253e+05	4.253e+05	4.337e+05	4.504e+05	4.504e+05	4.535e+05	4.629e+05	4.629e+05	4.629e+05	4.003e+05	4.003e+05	4.003e+05	3.753e+05	3.753e+05	3.753e+05	3.378e+05	3.378e+05	3.378e+05	3.294e+05	3.253e+05	3.253e+05	3.253e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.753e+05	3.753e+05	3.753e+05	3.962e+05	4.378e+05	4.378e+05	4.17e+05	3.753e+05	3.753e+05	3.753e+05	3.503e+05	3.503e+05	3.503e+05	2.752e+05	2.752e+05	2.752e+05	2.627e+05	2.627e+05	2.627e+05	3.002e+05	3.128e+05	3.128e+05	2.877e+05	2.752e+05	2.752e+05	2.836e+05	2.877e+05	2.877e+05	2.752e+05	2.502e+05	2.502e+05	2.669e+05	3.002e+05	3.002e+05	3.336e+05	4.003e+05	4.003e+05	4.003e+05	3.878e+05	3.878e+05	3.878e+05	4.003e+05	4.003e+05	4.003e+05	3.753e+05	3.753e+05	3.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13e+05	4.113e+05	4.113e+05	4.113e+05	2.561e+05	1.009e+05	1.009e+05	1.009e+05	1.009e+05	2.836e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	4.664e+05	2.619e+05	5.735e+04	5.735e+04	5.735e+04	5.735e+04	1.726e+05	2.878e+05	2.878e+05	2.878e+05	2.878e+05	6.754e+05	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	1.063e+06	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.251e+04	1.251e+04	1.251e+04	1.251e+04	1.251e+04	2.502e+04	3.753e+04	3.753e+04	3.753e+04	3.753e+04	7.506e+04	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.251e+05	1.501e+05	1.501e+05	1.501e+05	1.376e+05	1.376e+05	1.376e+05	1.251e+05	1.251e+05	1.251e+05	8.757e+04	8.757e+04	8.757e+04	8.757e+04	8.757e+04	8.757e+04	1.042e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.126e+05	1.168e+05	1.251e+05	1.251e+05	1.168e+05	1.001e+05	1.001e+05	1.001e+05	1.251e+05	1.251e+05	1.251e+05	1.376e+05	1.376e+05	1.376e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.626e+05	1.543e+05	1.501e+05	1.501e+05	1.689e+05	1.877e+05	1.877e+05	1.96e+05	2.127e+05	2.127e+05	2.294e+05	2.627e+05	2.627e+05	2.627e+05	2.502e+05	2.502e+05	2.502e+05	2.252e+05	2.252e+05	2.252e+05	2.533e+05	2.627e+05	2.627e+05	2.961e+05	3.128e+05	3.128e+05	3.211e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.086e+05	2.752e+05	2.752e+05	2.69e+05	2.502e+05	2.502e+05	2.502e+05	2.877e+05	2.877e+05	2.877e+05	2.752e+05	2.752e+05	2.752e+05	2.377e+05	2.252e+05	2.252e+05	2.085e+05	2.002e+05	2.002e+05	1.835e+05	1.751e+05	1.751e+05	1.793e+05	1.877e+05	1.877e+05	2.043e+05	2.377e+05	2.377e+05	2.283e+05	2.002e+05	2.002e+05	2.002e+05	1.877e+05	1.877e+05	1.877e+05	1.751e+05	1.751e+05	1.751e+05	2.127e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.252e+05	2.293e+05	2.377e+05	2.377e+05	2.46e+05	2.627e+05	2.627e+05	2.783e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.711e+05	3.628e+05	3.628e+05	4.003e+05	4.378e+05	4.378e+05	4.212e+05	3.878e+05	3.878e+05	3.961e+05	4.128e+05	4.128e+05	4.128e+05	4.253e+05	4.253e+05	4.253e+05	5.004e+05	5.004e+05	5.004e+05	4.879e+05	4.879e+05	4.879e+05	4.545e+05	4.378e+05	4.378e+05	4.629e+05	4.754e+05	4.754e+05	4.504e+05	4.253e+05	4.253e+05	4.462e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.879e+05	4.504e+05	4.504e+05	4.504e+05	4.003e+05	4.003e+05	4.003e+05	4.253e+05	4.253e+05	4.253e+05	4.337e+05	4.378e+05	4.378e+05	4.545e+05	4.629e+05	4.629e+05	4.879e+05	5.129e+05	5.129e+05	5.087e+05	5.004e+05	5.004e+05	4.795e+05	4.378e+05	4.378e+05	4.378e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.16e+05	4.003e+05	4.003e+05	4.42e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.629e+05	4.378e+05	3.878e+05	3.878e+05	3.92e+05	4.003e+05	4.003e+05	4.034e+05	4.128e+05	4.128e+05	4.128e+05	4.253e+05	4.253e+05	4.253e+05	3.503e+05	3.503e+05	3.503e+05	3.409e+05	3.378e+05	3.378e+05	3.044e+05	2.877e+05	2.877e+05	2.627e+05	2.502e+05	2.502e+05	2.585e+05	2.752e+05	2.752e+05	2.627e+05	2.377e+05	2.377e+05	2.439e+05	2.627e+05	2.627e+05	2.627e+05	2.002e+05	2.002e+05	2.002e+05	2.752e+05	2.752e+05	2.752e+05	2.94e+05	3.002e+05	3.002e+05	3.419e+05	3.628e+05	3.628e+05	4.045e+05	4.253e+05	4.253e+05	4.295e+05	4.378e+05	4.378e+05	4.337e+05	4.253e+05	4.253e+05	4.253e+05	4.504e+05	4.504e+05	4.504e+05	4.629e+05	4.629e+05	4.629e+05	4.003e+05	4.003e+05	4.003e+05	3.836e+05	3.753e+05	3.753e+05	3.503e+05	3.378e+05	3.378e+05	3.315e+05	3.253e+05	3.253e+05	3.253e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.753e+05	3.753e+05	3.753e+05	4.17e+05	4.378e+05	4.378e+05	3.962e+05	3.753e+05	3.753e+05	3.67e+05	3.503e+05	3.503e+05	3.253e+05	2.752e+05	2.752e+05	2.721e+05	2.627e+05	2.627e+05	2.627e+05	3.128e+05	3.128e+05	3.128e+05	2.752e+05	2.752e+05	2.752e+05	2.846e+05	2.877e+05	2.877e+05	2.627e+05	2.502e+05	2.502e+05	2.836e+05	3.002e+05	3.002e+05	3.336e+05	4.003e+05	4.003e+05	3.962e+05	3.878e+05	3.878e+05	3.909e+05	4.003e+05	4.003e+05	4.003e+05	3.753e+05	3.753e+05	3.753e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.878e+05	3.711e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.19e+05	2.752e+05	2.752e+05	2.752e+05	2.752e+05	3.127e+05	3.503e+05	3.503e+05	3.503e+05	3.503e+05	3.628e+05	3.753e+05	3.753e+05	3.753e+05	3.753e+05	3.753e+05	3.753e+05	3.753e+05	3.753e+05	3.753e+05	4.003e+05	4.253e+05	4.253e+05	4.253e+05	4.253e+05	4.253e+05	4.253e+05	4.253e+05	4.253e+05	4.253e+05	4.316e+05	4.378e+05	4.378e+05	4.378e+05	4.378e+05	4.441e+05	4.504e+05	4.504e+05	4.504e+05	4.504e+05	4.629e+05	4.7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	2.502e+04	2.502e+04	2.502e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	2.557e+05	2.557e+05	2.557e+05	2.557e+05	2.905e+05	3.253e+05	3.253e+05	3.253e+05	3.253e+05	2.295e+05	1.337e+05	1.337e+05	1.337e+05	1.337e+05	2.384e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	3.431e+05	1.733e+05	3439	3439	3439	3439	1.164e+04	1.984e+04	1.984e+04	1.984e+04	1.984e+04	1.785e+05	3.371e+05	3.371e+05	3.371e+05	3.371e+05	2.701e+05	2.031e+05	2.031e+05	2.031e+05	2.031e+05	2.549e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	3.067e+05	2.626e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	2.185e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	3.676e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	2.978e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.263e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	3.529e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	1.831e+05	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.02e+04	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	3.333e+05	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	1.82e+04	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.697e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	3.628e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	5.753e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	1.361e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	4.465e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	7.474e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	6.936e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	7.453e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	5.769e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	2.789e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	3.887e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.512e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	4.026e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	2.088e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.177e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	3.823e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	4.139e+05	2.139e+04	2.139e+04	2.139e+04	2.139e+04	2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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_skipzeros.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_skipzeros.gz
new file mode 100644
index 0000000000..10d54048ab
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_skipzeros.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_skipzeros.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_skipzeros.tab
new file mode 100644
index 0000000000..1a3bc619ca
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_skipzeros.tab
@@ -0,0 +1,22 @@
+#input_computeMatrix_regions1.bed:6	input_computeMatrix_regions2.bed:7	input_computeMatrix_regions3.gtf:6
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortulen.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortulen.gz
new file mode 100644
index 0000000000..be7b807e90
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortulen.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortulen.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortulen.tab
new file mode 100644
index 0000000000..920c8186e5
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortulen.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.33e+05	6.278e+05	8.122e+05	8.435e+05	7.137e+05	6.451e+05	6.14e+05	5.453e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	8.928e+04	1.437e+05	1.64e+05	1.407e+05	1.143e+05	2.262e+05	4.234e+05	4.53e+05	2.924e+05	4.351e+05	2.913e+05	3.816e+05	2.818e+05	4.328e+05	3.756e+05	2.613e+05	5.973e+05	5.977e+05	3.456e+05	9.047e+05	6.549e+05	4.235e+05	4.511e+05	3.519e+05	3.201e+05	8.762e+05	5.864e+05	4.554e+05	3.166e+05	3.548e+05	1.243e+05	5.85e+05	6.55e+05	5.454e+05	4.976e+05	1.013e+06	3.917e+05	7.999e+05	3.752e+05	4.857e+05	2.745e+05	5.496e+05	7.808e+05	4.225e+05	2.598e+05	4.877e+05	3.72e+05	2.307e+05	6.442e+05	2.96e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	1.271e+05	1.372e+05	7.565e+04	6.91e+04	2.472e+05	1.374e+05	4.29e+05	3.643e+05	5.28e+05	3.863e+05	3.518e+05	2.861e+05	2.239e+05	3.122e+05	3.683e+05	5.231e+05	5.202e+05	5.334e+05	4.432e+05	3.329e+05	4.652e+05	3.622e+05	6.531e+05	5.516e+05	3.102e+05	1.045e+06	6.657e+05	3.13e+05	4.069e+05	4.768e+05	3.648e+05	5.06e+05	7.55e+05	2.744e+05	4.167e+05	4.607e+05	1.056e+06	9.155e+05	6.409e+05	1.004e+06	7.568e+05	6.221e+05	5.132e+05	3.487e+05	2.406e+05	2.319e+05	4.031e+05	3.495e+05	3.509e+05	3.323e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.236e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
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+3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.373e+05	5.613e+05	5.533e+05	5.132e+05	4.731e+05	4.972e+05	4.972e+05	5.212e+05	5.293e+05	5.421e+05	5.613e+05	5.613e+05	6.255e+05	6.255e+05	6.544e+05	6.736e+05	6.977e+05	7.698e+05	7.698e+05	7.538e+05	7.538e+05	7.538e+05	7.538e+05	7.474e+05	7.217e+05	7.217e+05	7.698e+05	7.859e+05	7.859e+05	7.859e+05	7.859e+05	6.255e+05	6.255e+05	6.496e+05	6.576e+05	6.295e+05	5.453e+05	5.453e+05	5.934e+05	5.934e+05	6.014e+05	6.095e+05	6.014e+05	5.774e+05	5.774e+05	5.646e+05	5.613e+05	5.533e+05	5.453e+05	5.453e+05	5.453e+05	5.453e+05	4.972e+05	4.812e+05	4.812e+05	4.587e+05	4.146e+05	4.828e+05	4.9e+05	5.052e+05	4.395e+05	3.464e+05	3.761e+05	3.504e+05	4.707e+05	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	6.819e+05	9.54e+05	4.223e+05	8.288e+05	4.735e+05	9.123e+04	9.123e+04	2.186e+05	2.611e+05	2.976e+05	3.524e+05	3.524e+05	3.556e+05	3.556e+05	4.711e+05	5.481e+05	7.719e+05	1.443e+06	1.443e+06	1.241e+06	1.241e+06	1.241e+06	1.241e+06	1.252e+06	1.298e+06	1.298e+06	7.138e+05	5.19e+05	5.19e+05	5.19e+05	5.19e+05	9.006e+05	9.006e+05	3.3e+05	1.398e+05	1.776e+05	2.909e+05	2.909e+05	3.186e+05	3.186e+05	1.658e+05	1.306e+04	2.101e+05	8.012e+05	8.012e+05	5.459e+05	4.821e+05	4.644e+05	4.467e+05	4.467e+05	4.467e+05	4.467e+05	1.403e+05	3.818e+04	3.818e+04	3.461e+05	6.068e+05	3.867e+05	3.21e+05	4.232e+05	4.386e+05	4.209e+05	2.143e+05	2.69e+05	6.483e+05	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	5.422e+05	5.162e+05	8.527e+05	9.675e+05	5.194e+05	8.644e+05	8.644e+05	2.881e+05	9.597e+04	2.157e+05	3.953e+05	3.953e+05	8.458e+05	8.458e+05	7.566e+05	6.971e+05	8.958e+05	1.492e+06	1.492e+06	6103	6103	6103	6103	4.458e+04	1.985e+05	1.985e+05	6.408e+05	7.882e+05	7.882e+05	7.882e+05	7.882e+05	1.02e+06	1.02e+06	9.723e+05	9.564e+05	8.559e+05	5.545e+05	5.545e+05	3.867e+05	3.867e+05	5.526e+05	7.184e+05	8.208e+05	1.128e+06	1.128e+06	3.982e+05	2.157e+05	2.508e+05	2.859e+05	2.859e+05	2.859e+05	2.859e+05	4.49e+05	5.034e+05	5.034e+05	3.151e+05	2.8e+05	4.019e+05	3.229e+05	4.564e+05	1.967e+05	2.897e+05	2.369e+05	3.727e+05	5.16e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.373e+05	5.613e+05	5.533e+05	5.132e+05	4.731e+05	4.972e+05	4.972e+05	5.212e+05	5.293e+05	5.421e+05	5.613e+05	5.613e+05	6.255e+05	6.255e+05	6.544e+05	6.736e+05	6.977e+05	7.698e+05	7.698e+05	7.538e+05	7.538e+05	7.538e+05	7.538e+05	7.474e+05	7.217e+05	7.217e+05	7.698e+05	7.859e+05	7.859e+05	7.859e+05	7.859e+05	6.255e+05	6.255e+05	6.496e+05	6.576e+05	6.295e+05	5.453e+05	5.453e+05	5.934e+05	5.934e+05	6.014e+05	6.095e+05	6.014e+05	5.774e+05	5.774e+05	5.646e+05	5.613e+05	5.533e+05	5.453e+05	5.453e+05	5.453e+05	5.453e+05	4.972e+05	4.812e+05	4.812e+05	4.587e+05	4.146e+05	4.828e+05	4.9e+05	5.052e+05	4.395e+05	3.464e+05	3.761e+05	3.504e+05	4.707e+05
+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumax.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumax.gz
new file mode 100644
index 0000000000..90ddf5d5f8
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumax.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumax.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumax.tab
new file mode 100644
index 0000000000..c5ffbd3178
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumax.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	5.196e+05	7.23e+05	8.385e+05	8.217e+05	6.864e+05	6.48e+05	6.095e+05	5.581e+05	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05	2.616e+05	4.103e+05	4.383e+05	1.731e+05	4.412e+05	2.501e+05	3.76e+05	4.27e+05	5.175e+05	3.214e+05	2.147e+05	5.588e+05	7.091e+05	2.686e+05	9.378e+05	6.918e+05	3.514e+05	5.597e+05	3.724e+05	2.497e+05	6.477e+05	6.206e+05	6.817e+05	5.193e+05	2.37e+05	3.573e+05	1.286e+05	6.129e+05	5.864e+05	6.181e+05	3.451e+05	9.179e+05	8.843e+05	1.906e+05	7.744e+05	4.285e+05	5.146e+05	2.434e+05	5.107e+05	8.407e+05	5.425e+05	1.658e+05	4.258e+05	5.02e+05	3.575e+05	2.766e+05	6.116e+05	2.224e+05	4.005e+05	4.605e+05	2.616e+05	5.655e+05	9.173e+05	1.306e+06	5.128e+05	2.218e+05	5.08e+05	6.651e+05	7.656e+05	7.244e+05	7.988e+05	4.262e+05	4.642e+05	5.496e+05	2.491e+05	1.174e+06	9.009e+05	8.651e+05	7.893e+05	5.541e+05	5.085e+05	2.946e+05	5.358e+05	2.912e+05	2.38e+05	3.56e+05	1.442e+05	3.515e+05	3.994e+05	3.657e+05	5.99e+05	4.125e+05	6.591e+05	3.828e+05	3.353e+05	4.96e+05	2.479e+05	6.072e+05	6.313e+05	3.908e+05	7.219e+05	8.847e+05	5.182e+05	4.54e+05	3.751e+05	4.592e+05	3.698e+05	5.801e+05	7.189e+05	3.127e+05	2.308e+05	3.954e+05	8.206e+05	1.258e+06	5.797e+05	7.784e+05	1.056e+06	7.101e+05	5.756e+05	5.5e+05	4.893e+05	2.118e+05	2.624e+05	3.51e+05	2.984e+05	3.883e+05	2.763e+05	3.965e+05	3.064e+05	7.213e+05	5.487e+05	9.28e+05	4.585e+05	4.816e+05	7.69e+05	4.444e+05	5.978e+05	9.439e+05	5.861e+05	6.012e+05	1.46e+05	3.623e+05	3.283e+05	5.979e+05	2.213e+05	1.363e+06	7.775e+05	8.227e+05	7.513e+05	2.591e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	4.17e+05	nan	nan	nan	nan	nan	nan	nan	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05
+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.33e+05	6.278e+05	8.122e+05	8.435e+05	7.137e+05	6.451e+05	6.14e+05	5.453e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	8.928e+04	1.437e+05	1.64e+05	1.407e+05	1.143e+05	2.262e+05	4.234e+05	4.53e+05	2.924e+05	4.351e+05	2.913e+05	3.816e+05	2.818e+05	4.328e+05	3.756e+05	2.613e+05	5.973e+05	5.977e+05	3.456e+05	9.047e+05	6.549e+05	4.235e+05	4.511e+05	3.519e+05	3.201e+05	8.762e+05	5.864e+05	4.554e+05	3.166e+05	3.548e+05	1.243e+05	5.85e+05	6.55e+05	5.454e+05	4.976e+05	1.013e+06	3.917e+05	7.999e+05	3.752e+05	4.857e+05	2.745e+05	5.496e+05	7.808e+05	4.225e+05	2.598e+05	4.877e+05	3.72e+05	2.307e+05	6.442e+05	2.96e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	1.271e+05	1.372e+05	7.565e+04	6.91e+04	2.472e+05	1.374e+05	4.29e+05	3.643e+05	5.28e+05	3.863e+05	3.518e+05	2.861e+05	2.239e+05	3.122e+05	3.683e+05	5.231e+05	5.202e+05	5.334e+05	4.432e+05	3.329e+05	4.652e+05	3.622e+05	6.531e+05	5.516e+05	3.102e+05	1.045e+06	6.657e+05	3.13e+05	4.069e+05	4.768e+05	3.648e+05	5.06e+05	7.55e+05	2.744e+05	4.167e+05	4.607e+05	1.056e+06	9.155e+05	6.409e+05	1.004e+06	7.568e+05	6.221e+05	5.132e+05	3.487e+05	2.406e+05	2.319e+05	4.031e+05	3.495e+05	3.509e+05	3.323e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.236e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
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+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumean.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumean.gz
new file mode 100644
index 0000000000..5a7ae4483c
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumean.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumean.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumean.tab
new file mode 100644
index 0000000000..d7d57a326f
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumean.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	5.196e+05	7.23e+05	8.385e+05	8.217e+05	6.864e+05	6.48e+05	6.095e+05	5.581e+05	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05	2.616e+05	4.103e+05	4.383e+05	1.731e+05	4.412e+05	2.501e+05	3.76e+05	4.27e+05	5.175e+05	3.214e+05	2.147e+05	5.588e+05	7.091e+05	2.686e+05	9.378e+05	6.918e+05	3.514e+05	5.597e+05	3.724e+05	2.497e+05	6.477e+05	6.206e+05	6.817e+05	5.193e+05	2.37e+05	3.573e+05	1.286e+05	6.129e+05	5.864e+05	6.181e+05	3.451e+05	9.179e+05	8.843e+05	1.906e+05	7.744e+05	4.285e+05	5.146e+05	2.434e+05	5.107e+05	8.407e+05	5.425e+05	1.658e+05	4.258e+05	5.02e+05	3.575e+05	2.766e+05	6.116e+05	2.224e+05	4.005e+05	4.605e+05	2.616e+05	5.655e+05	9.173e+05	1.306e+06	5.128e+05	2.218e+05	5.08e+05	6.651e+05	7.656e+05	7.244e+05	7.988e+05	4.262e+05	4.642e+05	5.496e+05	2.491e+05	1.174e+06	9.009e+05	8.651e+05	7.893e+05	5.541e+05	5.085e+05	2.946e+05	5.358e+05	2.912e+05	2.38e+05	3.56e+05	1.442e+05	3.515e+05	3.994e+05	3.657e+05	5.99e+05	4.125e+05	6.591e+05	3.828e+05	3.353e+05	4.96e+05	2.479e+05	6.072e+05	6.313e+05	3.908e+05	7.219e+05	8.847e+05	5.182e+05	4.54e+05	3.751e+05	4.592e+05	3.698e+05	5.801e+05	7.189e+05	3.127e+05	2.308e+05	3.954e+05	8.206e+05	1.258e+06	5.797e+05	7.784e+05	1.056e+06	7.101e+05	5.756e+05	5.5e+05	4.893e+05	2.118e+05	2.624e+05	3.51e+05	2.984e+05	3.883e+05	2.763e+05	3.965e+05	3.064e+05	7.213e+05	5.487e+05	9.28e+05	4.585e+05	4.816e+05	7.69e+05	4.444e+05	5.978e+05	9.439e+05	5.861e+05	6.012e+05	1.46e+05	3.623e+05	3.283e+05	5.979e+05	2.213e+05	1.363e+06	7.775e+05	8.227e+05	7.513e+05	2.591e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	4.17e+05	nan	nan	nan	nan	nan	nan	nan	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05
+nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.33e+05	6.278e+05	8.122e+05	8.435e+05	7.137e+05	6.451e+05	6.14e+05	5.453e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	8.928e+04	1.437e+05	1.64e+05	1.407e+05	1.143e+05	2.262e+05	4.234e+05	4.53e+05	2.924e+05	4.351e+05	2.913e+05	3.816e+05	2.818e+05	4.328e+05	3.756e+05	2.613e+05	5.973e+05	5.977e+05	3.456e+05	9.047e+05	6.549e+05	4.235e+05	4.511e+05	3.519e+05	3.201e+05	8.762e+05	5.864e+05	4.554e+05	3.166e+05	3.548e+05	1.243e+05	5.85e+05	6.55e+05	5.454e+05	4.976e+05	1.013e+06	3.917e+05	7.999e+05	3.752e+05	4.857e+05	2.745e+05	5.496e+05	7.808e+05	4.225e+05	2.598e+05	4.877e+05	3.72e+05	2.307e+05	6.442e+05	2.96e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	1.271e+05	1.372e+05	7.565e+04	6.91e+04	2.472e+05	1.374e+05	4.29e+05	3.643e+05	5.28e+05	3.863e+05	3.518e+05	2.861e+05	2.239e+05	3.122e+05	3.683e+05	5.231e+05	5.202e+05	5.334e+05	4.432e+05	3.329e+05	4.652e+05	3.622e+05	6.531e+05	5.516e+05	3.102e+05	1.045e+06	6.657e+05	3.13e+05	4.069e+05	4.768e+05	3.648e+05	5.06e+05	7.55e+05	2.744e+05	4.167e+05	4.607e+05	1.056e+06	9.155e+05	6.409e+05	1.004e+06	7.568e+05	6.221e+05	5.132e+05	3.487e+05	2.406e+05	2.319e+05	4.031e+05	3.495e+05	3.509e+05	3.323e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.236e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
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+2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	5.079e+05	7.481e+05	8.495e+05	7.398e+05	6.458e+05	6.136e+05	5.267e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05	4.6e+04	3.939e+04	3.159e+04	7.197e+04	1.287e+05	2.032e+05	9.229e+04	1.671e+05	9.075e+04	2.463e+05	3.189e+05	4.421e+05	3.496e+05	4.012e+05	2.764e+05	3.905e+05	3.193e+05	4.649e+05	3.481e+05	3.906e+05	6.323e+05	3.951e+05	7.939e+05	6.343e+05	4.906e+05	3.602e+05	3.116e+05	6.24e+05	6.331e+05	4.967e+05	4.27e+05	3.429e+05	1.813e+05	5.57e+05	6.723e+05	4.321e+05	8.49e+05	7.309e+05	5.605e+05	4.714e+05	4.704e+05	3.282e+05	5.831e+05	7.72e+05	1.927e+05	4.237e+05	5.04e+05	2.286e+05	5.576e+05	3.017e+05	3.845e+05	4.021e+05	3.834e+05	7.39e+05	1.299e+06	4.869e+05	2.31e+05	7.417e+05	6.365e+05	7.484e+05	7.834e+05	3.855e+05	4.87e+05	4.994e+05	3.617e+05	1.174e+06	9.278e+05	8.47e+05	7.408e+05	5.18e+05	4615	3.187e+04	3.748e+04	1.002e+05	1.65e+05	7.499e+04	5.974e+04	8.493e+04	2.645e+05	7.494e+04	3.126e+05	3.9e+05	5.326e+05	3.962e+05	3.569e+05	3.045e+05	1.876e+05	3.716e+05	3.976e+05	5.907e+05	5.215e+05	4.584e+05	3.248e+05	4.48e+05	4.784e+05	4.991e+05	5.089e+05	6.781e+05	7.068e+05	4.551e+05	4.725e+05	4.838e+05	3.988e+05	4.924e+05	6.316e+05	2.556e+05	3.735e+05	8.769e+05	1.154e+06	5.802e+05	9.715e+05	7.596e+05	6.706e+05	3.576e+05	3.543e+05	2.332e+05	4.039e+05	2.694e+05	3.802e+05	3.132e+05	3.105e+05	7.053e+05	7.676e+05	6.738e+05	4.082e+05	7.087e+05	5.844e+05	7.164e+05	6.516e+05	5.946e+05	1.45e+05	3.955e+05	3.354e+05	5.455e+05	3.502e+05	1.363e+06	6.888e+05	8.144e+05	7.242e+05	2.651e+05	2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	4.17e+05	nan	nan	nan	nan	nan	4.812e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05
+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
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+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumedian.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumedian.gz
new file mode 100644
index 0000000000..259ad1276c
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumedian.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumedian.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumedian.tab
new file mode 100644
index 0000000000..48613a9c34
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumedian.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	5.196e+05	7.23e+05	8.385e+05	8.217e+05	6.864e+05	6.48e+05	6.095e+05	5.581e+05	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05	2.616e+05	4.103e+05	4.383e+05	1.731e+05	4.412e+05	2.501e+05	3.76e+05	4.27e+05	5.175e+05	3.214e+05	2.147e+05	5.588e+05	7.091e+05	2.686e+05	9.378e+05	6.918e+05	3.514e+05	5.597e+05	3.724e+05	2.497e+05	6.477e+05	6.206e+05	6.817e+05	5.193e+05	2.37e+05	3.573e+05	1.286e+05	6.129e+05	5.864e+05	6.181e+05	3.451e+05	9.179e+05	8.843e+05	1.906e+05	7.744e+05	4.285e+05	5.146e+05	2.434e+05	5.107e+05	8.407e+05	5.425e+05	1.658e+05	4.258e+05	5.02e+05	3.575e+05	2.766e+05	6.116e+05	2.224e+05	4.005e+05	4.605e+05	2.616e+05	5.655e+05	9.173e+05	1.306e+06	5.128e+05	2.218e+05	5.08e+05	6.651e+05	7.656e+05	7.244e+05	7.988e+05	4.262e+05	4.642e+05	5.496e+05	2.491e+05	1.174e+06	9.009e+05	8.651e+05	7.893e+05	5.541e+05	5.085e+05	2.946e+05	5.358e+05	2.912e+05	2.38e+05	3.56e+05	1.442e+05	3.515e+05	3.994e+05	3.657e+05	5.99e+05	4.125e+05	6.591e+05	3.828e+05	3.353e+05	4.96e+05	2.479e+05	6.072e+05	6.313e+05	3.908e+05	7.219e+05	8.847e+05	5.182e+05	4.54e+05	3.751e+05	4.592e+05	3.698e+05	5.801e+05	7.189e+05	3.127e+05	2.308e+05	3.954e+05	8.206e+05	1.258e+06	5.797e+05	7.784e+05	1.056e+06	7.101e+05	5.756e+05	5.5e+05	4.893e+05	2.118e+05	2.624e+05	3.51e+05	2.984e+05	3.883e+05	2.763e+05	3.965e+05	3.064e+05	7.213e+05	5.487e+05	9.28e+05	4.585e+05	4.816e+05	7.69e+05	4.444e+05	5.978e+05	9.439e+05	5.861e+05	6.012e+05	1.46e+05	3.623e+05	3.283e+05	5.979e+05	2.213e+05	1.363e+06	7.775e+05	8.227e+05	7.513e+05	2.591e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	4.17e+05	nan	nan	nan	nan	nan	nan	nan	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05
+nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.33e+05	6.278e+05	8.122e+05	8.435e+05	7.137e+05	6.451e+05	6.14e+05	5.453e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	8.928e+04	1.437e+05	1.64e+05	1.407e+05	1.143e+05	2.262e+05	4.234e+05	4.53e+05	2.924e+05	4.351e+05	2.913e+05	3.816e+05	2.818e+05	4.328e+05	3.756e+05	2.613e+05	5.973e+05	5.977e+05	3.456e+05	9.047e+05	6.549e+05	4.235e+05	4.511e+05	3.519e+05	3.201e+05	8.762e+05	5.864e+05	4.554e+05	3.166e+05	3.548e+05	1.243e+05	5.85e+05	6.55e+05	5.454e+05	4.976e+05	1.013e+06	3.917e+05	7.999e+05	3.752e+05	4.857e+05	2.745e+05	5.496e+05	7.808e+05	4.225e+05	2.598e+05	4.877e+05	3.72e+05	2.307e+05	6.442e+05	2.96e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	1.271e+05	1.372e+05	7.565e+04	6.91e+04	2.472e+05	1.374e+05	4.29e+05	3.643e+05	5.28e+05	3.863e+05	3.518e+05	2.861e+05	2.239e+05	3.122e+05	3.683e+05	5.231e+05	5.202e+05	5.334e+05	4.432e+05	3.329e+05	4.652e+05	3.622e+05	6.531e+05	5.516e+05	3.102e+05	1.045e+06	6.657e+05	3.13e+05	4.069e+05	4.768e+05	3.648e+05	5.06e+05	7.55e+05	2.744e+05	4.167e+05	4.607e+05	1.056e+06	9.155e+05	6.409e+05	1.004e+06	7.568e+05	6.221e+05	5.132e+05	3.487e+05	2.406e+05	2.319e+05	4.031e+05	3.495e+05	3.509e+05	3.323e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.236e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
+2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	5.079e+05	7.481e+05	8.495e+05	7.398e+05	6.458e+05	6.136e+05	5.267e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05	4.6e+04	3.939e+04	3.159e+04	7.197e+04	1.287e+05	2.032e+05	9.229e+04	1.671e+05	9.075e+04	2.463e+05	3.189e+05	4.421e+05	3.496e+05	4.012e+05	2.764e+05	3.905e+05	3.193e+05	4.649e+05	3.481e+05	3.906e+05	6.323e+05	3.951e+05	7.939e+05	6.343e+05	4.906e+05	3.602e+05	3.116e+05	6.24e+05	6.331e+05	4.967e+05	4.27e+05	3.429e+05	1.813e+05	5.57e+05	6.723e+05	4.321e+05	8.49e+05	7.309e+05	5.605e+05	4.714e+05	4.704e+05	3.282e+05	5.831e+05	7.72e+05	1.927e+05	4.237e+05	5.04e+05	2.286e+05	5.576e+05	3.017e+05	3.845e+05	4.021e+05	3.834e+05	7.39e+05	1.299e+06	4.869e+05	2.31e+05	7.417e+05	6.365e+05	7.484e+05	7.834e+05	3.855e+05	4.87e+05	4.994e+05	3.617e+05	1.174e+06	9.278e+05	8.47e+05	7.408e+05	5.18e+05	4615	3.187e+04	3.748e+04	1.002e+05	1.65e+05	7.499e+04	5.974e+04	8.493e+04	2.645e+05	7.494e+04	3.126e+05	3.9e+05	5.326e+05	3.962e+05	3.569e+05	3.045e+05	1.876e+05	3.716e+05	3.976e+05	5.907e+05	5.215e+05	4.584e+05	3.248e+05	4.48e+05	4.784e+05	4.991e+05	5.089e+05	6.781e+05	7.068e+05	4.551e+05	4.725e+05	4.838e+05	3.988e+05	4.924e+05	6.316e+05	2.556e+05	3.735e+05	8.769e+05	1.154e+06	5.802e+05	9.715e+05	7.596e+05	6.706e+05	3.576e+05	3.543e+05	2.332e+05	4.039e+05	2.694e+05	3.802e+05	3.132e+05	3.105e+05	7.053e+05	7.676e+05	6.738e+05	4.082e+05	7.087e+05	5.844e+05	7.164e+05	6.516e+05	5.946e+05	1.45e+05	3.955e+05	3.354e+05	5.455e+05	3.502e+05	1.363e+06	6.888e+05	8.144e+05	7.242e+05	2.651e+05	2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	4.17e+05	nan	nan	nan	nan	nan	4.812e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05
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+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumin.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumin.gz
new file mode 100644
index 0000000000..7e81488091
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumin.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumin.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumin.tab
new file mode 100644
index 0000000000..361e94d107
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortumin.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+3.448e+05	3.288e+05	2.967e+05	3.689e+05	5.052e+05	5.533e+05	5.854e+05	4.972e+05	4.25e+05	5.132e+05	5.774e+05	7.342e+05	7.788e+05	8.073e+05	8.468e+05	8.483e+05	8.483e+05	8.34e+05	7.627e+05	7.217e+05	6.558e+05	6.415e+05	6.255e+05	6.683e+05	6.351e+05	6.006e+05	6.041e+05	5.916e+05	5.489e+05	5.004e+05	5.079e+05	5.435e+05	4.776e+05	4.491e+05	3.528e+05	3.368e+05	3.938e+05	3.635e+05	3.635e+05	3.4e+05	3.564e+05	4.419e+05	5.079e+05	5.008e+05	5.068e+05	4.829e+05	4.972e+05	4.972e+05	4.687e+05	4.651e+05	3.778e+05	4.17e+05	4.669e+05	4.812e+05	5.068e+05	5.453e+05	5.489e+05	5.631e+05	5.774e+05	6.095e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	2.526e+05	2.607e+05	3.411e+05	1.17e+05	7.245e+05	4.508e+05	6.588e+05	5.918e+05	3.203e+05	9.185e+05	1.052e+06	9.293e+05	7.781e+05	3.424e+05	8.829e+04	3.109e+05	9.929e+05	1.096e+06	2.178e+05	5.321e+05	3.582e+05	2.556e+05	7.723e+05	4.293e+05	1.279e+05	1.159e+05	5.961e+05	7.136e+05	4.523e+05	4.895e+05	9.228e+05	9.151e+05	5.045e+05	8.061e+05	3.517e+05	1.175e+05	9.506e+04	3.011e+05	3.833e+05	4.32e+05	5.844e+05	4.53e+05	3.719e+05	6.263e+05	1.432e+05	5.014e+05	9.53e+04	9.53e+04	6.709e+05	7.429e+05	5.077e+05	5.56e+05	2.94e+05	3.818e+04	2.016e+05	4.467e+05	4.546e+05	5.176e+05	8.012e+05	1.306e+04	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	3.142e+05	5.531e+05	3.03e+05	4.31e+05	6.736e+05	4.734e+05	6.135e+05	3.36e+05	1.984e+05	4.51e+05	1.428e+05	1.132e+06	8.927e+05	9.325e+05	1.314e+06	1.427e+06	9.433e+05	3.759e+05	4.1e+05	8.586e+05	6.299e+05	8.397e+05	8.924e+05	1.279e+06	1.006e+06	5.606e+05	6.758e+05	6.366e+05	5.224e+05	6.988e+05	6.405e+05	1.816e+05	7.174e+05	2.885e+05	6.149e+05	1.13e+05	3.316e+05	1.692e+05	2.21e+05	3.056e+05	1.979e+05	1.84e+05	4.73e+05	6.577e+05	1.11e+05	3.165e+05	3.659e+05	3.659e+05	4.369e+05	4.458e+05	1.593e+05	1.387e+05	3.549e+05	5.034e+05	4.164e+05	2.859e+05	2.703e+05	3.171e+05	1.128e+06	7.184e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	3.448e+05	3.288e+05	2.967e+05	3.689e+05	5.052e+05	5.533e+05	5.854e+05	4.972e+05	4.25e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	4.812e+05	5.079e+05	5.435e+05	4.776e+05	4.491e+05	3.528e+05	3.368e+05	3.938e+05	3.635e+05	3.635e+05	3.4e+05	3.564e+05	4.419e+05	5.079e+05	5.008e+05	5.068e+05	4.829e+05	4.972e+05	4.972e+05	4.687e+05	4.651e+05	3.778e+05	4.17e+05	4.669e+05	4.812e+05	5.068e+05	5.453e+05	5.489e+05	5.631e+05	5.774e+05	6.095e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	1.604e+04	3.849e+04	1.443e+05	1.443e+05	1.7e+05	1.652e+05	1.139e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.564e+05	2.005e+05	2.085e+05	2.807e+05	3.168e+05	3.408e+05	4.13e+05	3.609e+05	3.528e+05	2.967e+05	nan	nan	nan	1.968e+04	5.224e+04	3.159e+04	3.159e+04	8.97e+04	1.515e+05	1.894e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.739e+04	2.416e+05	2.591e+05	4.174e+05	4.44e+05	4.448e+05	2.178e+05	4.684e+05	4.224e+05	2.151e+05	nan	nan	nan	7762	5427	3.748e+04	3.748e+04	1.374e+05	1.292e+05	8.129e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	2.47e+05	1.056e+05	2.725e+05	4.044e+05	3.45e+05	5.225e+05	5.124e+05	3.177e+05	4.537e+05	3.239e+05	nan	nan	nan	1.604e+04	3.849e+04	1.443e+05	1.443e+05	1.7e+05	1.652e+05	1.139e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.564e+05	2.005e+05	2.085e+05	2.807e+05	3.168e+05	3.408e+05	4.13e+05	3.609e+05	3.528e+05	2.967e+05
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
+nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	1.059e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.925e+05	1.925e+05	1.925e+05	1.818e+05	1.764e+05	1.764e+05	1.764e+05	1.657e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.337e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.55e+05	1.604e+05	1.604e+05	1.604e+05	1.39e+05	1.283e+05	1.283e+05	1.612e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05	nan	nan	nan	nan	nan	nan	nan	nan	3.033e+04	5.24e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.085e+05	1.47e+05	1.47e+05	1.47e+05	7.566e+04	4.001e+04	4.001e+04	4.001e+04	1.783e+05	2.475e+05	2.475e+05	2.475e+05	2.128e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.145e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.989e+05	2.614e+05	2.614e+05	2.614e+05	1.354e+05	7.241e+04	7.241e+04	9.075e+04	2.463e+05	2.766e+05	4.201e+05	4.441e+05	4.341e+05	2.003e+05	4.916e+05	4.16e+05	2.319e+05	nan	nan	nan	nan	nan	nan	nan	nan	6488	2.253e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	1.57e+05	2.168e+05	2.168e+05	2.168e+05	2.341e+05	2.428e+05	2.428e+05	2.428e+05	1.02e+05	3.165e+04	3.165e+04	3.165e+04	6.564e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.468e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.585e+04	4.092e+04	4.092e+04	4.092e+04	1.205e+05	1.603e+05	1.603e+05	2.645e+05	7.494e+04	3.092e+05	4.296e+05	3.164e+05	5.363e+05	5.139e+05	3.27e+05	4.209e+05	3.371e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	1.059e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.925e+05	1.925e+05	1.925e+05	1.818e+05	1.764e+05	1.764e+05	1.764e+05	1.657e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.337e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.55e+05	1.604e+05	1.604e+05	1.604e+05	1.39e+05	1.283e+05	1.283e+05	1.612e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortusum.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortusum.gz
new file mode 100644
index 0000000000..788fa1d790
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortusum.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortusum.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortusum.tab
new file mode 100644
index 0000000000..452613faae
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sortusum.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	5.196e+05	7.23e+05	8.385e+05	8.217e+05	6.864e+05	6.48e+05	6.095e+05	5.581e+05	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05	2.616e+05	4.103e+05	4.383e+05	1.731e+05	4.412e+05	2.501e+05	3.76e+05	4.27e+05	5.175e+05	3.214e+05	2.147e+05	5.588e+05	7.091e+05	2.686e+05	9.378e+05	6.918e+05	3.514e+05	5.597e+05	3.724e+05	2.497e+05	6.477e+05	6.206e+05	6.817e+05	5.193e+05	2.37e+05	3.573e+05	1.286e+05	6.129e+05	5.864e+05	6.181e+05	3.451e+05	9.179e+05	8.843e+05	1.906e+05	7.744e+05	4.285e+05	5.146e+05	2.434e+05	5.107e+05	8.407e+05	5.425e+05	1.658e+05	4.258e+05	5.02e+05	3.575e+05	2.766e+05	6.116e+05	2.224e+05	4.005e+05	4.605e+05	2.616e+05	5.655e+05	9.173e+05	1.306e+06	5.128e+05	2.218e+05	5.08e+05	6.651e+05	7.656e+05	7.244e+05	7.988e+05	4.262e+05	4.642e+05	5.496e+05	2.491e+05	1.174e+06	9.009e+05	8.651e+05	7.893e+05	5.541e+05	5.085e+05	2.946e+05	5.358e+05	2.912e+05	2.38e+05	3.56e+05	1.442e+05	3.515e+05	3.994e+05	3.657e+05	5.99e+05	4.125e+05	6.591e+05	3.828e+05	3.353e+05	4.96e+05	2.479e+05	6.072e+05	6.313e+05	3.908e+05	7.219e+05	8.847e+05	5.182e+05	4.54e+05	3.751e+05	4.592e+05	3.698e+05	5.801e+05	7.189e+05	3.127e+05	2.308e+05	3.954e+05	8.206e+05	1.258e+06	5.797e+05	7.784e+05	1.056e+06	7.101e+05	5.756e+05	5.5e+05	4.893e+05	2.118e+05	2.624e+05	3.51e+05	2.984e+05	3.883e+05	2.763e+05	3.965e+05	3.064e+05	7.213e+05	5.487e+05	9.28e+05	4.585e+05	4.816e+05	7.69e+05	4.444e+05	5.978e+05	9.439e+05	5.861e+05	6.012e+05	1.46e+05	3.623e+05	3.283e+05	5.979e+05	2.213e+05	1.363e+06	7.775e+05	8.227e+05	7.513e+05	2.591e+05	4.09e+05	3.849e+05	3.448e+05	3.208e+05	2.406e+05	2.727e+05	2.486e+05	2.566e+05	2.887e+05	3.208e+05	4.33e+05	4.844e+05	5.293e+05	5.806e+05	5.971e+05	5.909e+05	5.793e+05	5.485e+05	6.306e+05	5.885e+05	5.613e+05	5.485e+05	5.286e+05	4.478e+05	3.454e+05	3.156e+05	3.362e+05	5.023e+05	5.601e+05	5.441e+05	4.388e+05	4.17e+05	nan	nan	nan	nan	nan	nan	nan	5.12e+05	4.112e+05	3.663e+05	3.477e+05	4.632e+05	4.972e+05	4.882e+05	4.189e+05	4.709e+05	5.389e+05	5.823e+05	5.832e+05	6.858e+05	7.564e+05	7.589e+05	6.452e+05	5.254e+05	4.779e+05	5.447e+05	5.357e+05	5.502e+05	5.533e+05	4.25e+05	3.609e+05	3.368e+05	3.929e+05	7.057e+05	7.538e+05	7.057e+05	6.576e+05	4.33e+05
+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.33e+05	6.278e+05	8.122e+05	8.435e+05	7.137e+05	6.451e+05	6.14e+05	5.453e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	8.928e+04	1.437e+05	1.64e+05	1.407e+05	1.143e+05	2.262e+05	4.234e+05	4.53e+05	2.924e+05	4.351e+05	2.913e+05	3.816e+05	2.818e+05	4.328e+05	3.756e+05	2.613e+05	5.973e+05	5.977e+05	3.456e+05	9.047e+05	6.549e+05	4.235e+05	4.511e+05	3.519e+05	3.201e+05	8.762e+05	5.864e+05	4.554e+05	3.166e+05	3.548e+05	1.243e+05	5.85e+05	6.55e+05	5.454e+05	4.976e+05	1.013e+06	3.917e+05	7.999e+05	3.752e+05	4.857e+05	2.745e+05	5.496e+05	7.808e+05	4.225e+05	2.598e+05	4.877e+05	3.72e+05	2.307e+05	6.442e+05	2.96e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	1.271e+05	1.372e+05	7.565e+04	6.91e+04	2.472e+05	1.374e+05	4.29e+05	3.643e+05	5.28e+05	3.863e+05	3.518e+05	2.861e+05	2.239e+05	3.122e+05	3.683e+05	5.231e+05	5.202e+05	5.334e+05	4.432e+05	3.329e+05	4.652e+05	3.622e+05	6.531e+05	5.516e+05	3.102e+05	1.045e+06	6.657e+05	3.13e+05	4.069e+05	4.768e+05	3.648e+05	5.06e+05	7.55e+05	2.744e+05	4.167e+05	4.607e+05	1.056e+06	9.155e+05	6.409e+05	1.004e+06	7.568e+05	6.221e+05	5.132e+05	3.487e+05	2.406e+05	2.319e+05	4.031e+05	3.495e+05	3.509e+05	3.323e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.236e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
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+2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	5.079e+05	7.481e+05	8.495e+05	7.398e+05	6.458e+05	6.136e+05	5.267e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05	4.6e+04	3.939e+04	3.159e+04	7.197e+04	1.287e+05	2.032e+05	9.229e+04	1.671e+05	9.075e+04	2.463e+05	3.189e+05	4.421e+05	3.496e+05	4.012e+05	2.764e+05	3.905e+05	3.193e+05	4.649e+05	3.481e+05	3.906e+05	6.323e+05	3.951e+05	7.939e+05	6.343e+05	4.906e+05	3.602e+05	3.116e+05	6.24e+05	6.331e+05	4.967e+05	4.27e+05	3.429e+05	1.813e+05	5.57e+05	6.723e+05	4.321e+05	8.49e+05	7.309e+05	5.605e+05	4.714e+05	4.704e+05	3.282e+05	5.831e+05	7.72e+05	1.927e+05	4.237e+05	5.04e+05	2.286e+05	5.576e+05	3.017e+05	3.845e+05	4.021e+05	3.834e+05	7.39e+05	1.299e+06	4.869e+05	2.31e+05	7.417e+05	6.365e+05	7.484e+05	7.834e+05	3.855e+05	4.87e+05	4.994e+05	3.617e+05	1.174e+06	9.278e+05	8.47e+05	7.408e+05	5.18e+05	4615	3.187e+04	3.748e+04	1.002e+05	1.65e+05	7.499e+04	5.974e+04	8.493e+04	2.645e+05	7.494e+04	3.126e+05	3.9e+05	5.326e+05	3.962e+05	3.569e+05	3.045e+05	1.876e+05	3.716e+05	3.976e+05	5.907e+05	5.215e+05	4.584e+05	3.248e+05	4.48e+05	4.784e+05	4.991e+05	5.089e+05	6.781e+05	7.068e+05	4.551e+05	4.725e+05	4.838e+05	3.988e+05	4.924e+05	6.316e+05	2.556e+05	3.735e+05	8.769e+05	1.154e+06	5.802e+05	9.715e+05	7.596e+05	6.706e+05	3.576e+05	3.543e+05	2.332e+05	4.039e+05	2.694e+05	3.802e+05	3.132e+05	3.105e+05	7.053e+05	7.676e+05	6.738e+05	4.082e+05	7.087e+05	5.844e+05	7.164e+05	6.516e+05	5.946e+05	1.45e+05	3.955e+05	3.354e+05	5.455e+05	3.502e+05	1.363e+06	6.888e+05	8.144e+05	7.242e+05	2.651e+05	2.925e+04	1.299e+05	1.443e+05	1.612e+05	1.732e+05	1.195e+05	1.395e+05	1.468e+05	1.612e+05	2.037e+05	2.288e+05	3.13e+05	3.777e+05	3.667e+05	3.363e+05	2.426e+05	2.646e+05	2.701e+05	3.218e+05	4.532e+05	5.079e+05	5.463e+05	6.043e+05	5.966e+05	5.557e+05	5.95e+05	6.03e+05	5.676e+05	5.365e+05	5.055e+05	3.716e+05	3.259e+05	3.492e+05	5.319e+05	5.67e+05	4.615e+05	4.17e+05	nan	nan	nan	nan	nan	4.812e+05	4.972e+05	3.632e+05	3.497e+05	4.737e+05	4.962e+05	4.579e+05	4.46e+05	5.373e+05	5.882e+05	6.058e+05	7.549e+05	7.548e+05	6.317e+05	5.004e+05	5.013e+05	5.469e+05	5.562e+05	5.389e+05	4.186e+05	3.577e+05	3.352e+05	4.314e+05	7.057e+05	7.57e+05	7.025e+05	6.271e+05	4.475e+05
+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
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+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_std.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_std.gz
new file mode 100644
index 0000000000..dd71d318d9
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_std.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_std.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_std.tab
new file mode 100644
index 0000000000..331cb4e733
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_std.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+1.891e+04	2.394e+04	1.748e+04	4.104e+04	3.406e+04	1.87e+04	3.99e+04	3.436e+04	3.905e+04	0	2.391e+04	7245	0	1.122e+04	3.175e+04	0	0	2.381e+04	2.245e+04	0	1.449e+04	2.174e+04	0	1.122e+04	3.175e+04	0	0	3.968e+04	0	0	7937	3.367e+04	0	7246	1.449e+04	0	2.245e+04	7937	0	0	2.381e+04	2.806e+04	0	4.536e+04	1.122e+04	0	1.449e+04	2.898e+04	0	2.806e+04	2.381e+04	0	0	0	0	0	1.449e+04	1.449e+04	0	0	0	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.795e+05	4489	2.661e+05	1.061e+05	6.43e+04	1.331e+05	2.166e+05	2.034e+05	6.888e+04	0	4.216e+04	8.633e+04	0	3.13e+04	1.811e+04	0	0	1.077e+05	6.86e+04	0	1.755e+05	1.825e+05	0	1.577e+05	4394	0	0	2.787e+05	0	0	1.97e+05	1.35e+05	0	3.116e+04	2.993e+04	0	7.553e+04	1.891e+05	0	0	3.97e+04	2.183e+04	0	1.171e+05	4.885e+04	0	3.742e+04	1.831e+04	0	1.761e+05	3483	0	0	0	0	0	6.543e+04	1.222e+04	0	0	0	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.818e+05	1.051e+05	4.068e+05	4.467e+05	2.156e+05	1.21e+05	1.506e+05	1.13e+05	1.423e+05	0	1.272e+05	9.359e+04	0	6.434e+04	1069	0	0	3.903e+04	3.432e+04	0	1.478e+04	8.314e+04	0	2.381e+04	7.253e+04	0	0	2.829e+05	0	0	1.634e+05	7.2e+04	0	1.253e+04	2.356e+05	0	4.644e+04	1.47e+05	0	0	2.764e+05	8.401e+04	0	2463	7.232e+04	0	5.939e+04	1.71e+05	0	1.106e+05	9.553e+04	0	0	0	0	0	8215	1.88e+04	0	0	0	nan	nan	nan	nan	nan	nan	nan	nan	nan	1.891e+04	2.394e+04	1.748e+04	4.104e+04	3.406e+04	1.87e+04	3.99e+04	3.436e+04	3.905e+04	0	2.391e+04	7245	0	1.122e+04	3.175e+04	0	0	2.381e+04	2.245e+04	0	1.449e+04	2.174e+04	0	1.122e+04	3.175e+04	0	0	3.968e+04	0	0	7937	3.367e+04	0	7246	1.449e+04	0	2.245e+04	7937	0	0	2.381e+04	2.806e+04	0	4.536e+04	1.122e+04	0	1.449e+04	2.898e+04	0	2.806e+04	2.381e+04	0	0	0	0	0	1.449e+04	1.449e+04	0	0	0	nan	nan	nan	nan	nan	nan	nan	nan	nan
+2.655e+04	4.676e+04	2.083e+04	2.806e+04	8019	3.244e+04	3496	7979	3.99e+04	2.097e+04	0	1.587e+04	0	0	1.553e+04	4.347e+04	0	0	2.381e+04	3.713e+04	0	1.449e+04	4.347e+04	0	0	7937	1.122e+04	0	1.389e+04	3.175e+04	0	0	1.553e+04	1.449e+04	0	0	7937	5304	0	7246	1.449e+04	0	0	1.587e+04	0	0	6945	3.968e+04	0	0	2.329e+04	8.695e+04	0	1.122e+04	5.556e+04	1.061e+04	0	7245	0	0	6.415e+04	1.604e+04	5.614e+04	7.217e+04	1.604e+04	2.406e+04	2.406e+04	2.406e+04	1.604e+04	3.208e+04	3.944e+05	1.251e+05	1.225e+05	1.458e+04	1.277e+05	1.471e+05	1.742e+05	4.431e+05	4.91e+05	1.641e+05	0	1.655e+05	0	0	3.407e+05	2.686e+05	0	0	1.293e+05	1.336e+05	0	4.424e+05	2.359e+04	0	0	6361	1.766e+05	0	2.172e+05	2.7e+05	0	0	3433	2.377e+05	0	0	5.373e+04	4201	0	3.99e+04	6.716e+04	0	0	2.149e+04	0	0	8.492e+04	1.777e+04	0	0	2.958e+05	2.558e+05	0	3.717e+05	9.402e+04	1.198e+05	0	1.23e+05	0	0	1.874e+05	2.118e+05	3.156e+05	2.827e+05	4.681e+05	2.125e+05	3.472e+05	1.659e+05	6001	2.224e+04	1.578e+05	1.885e+05	4.256e+05	3.322e+05	3.047e+05	1.36e+05	4.704e+04	1.184e+05	1.068e+04	1.522e+04	0	8.881e+04	0	0	8.305e+04	6.127e+04	0	0	1.768e+05	3.464e+05	0	4.225e+05	3.072e+05	0	0	2.572e+05	1.363e+05	0	1.833e+05	1.097e+04	0	0	3.556e+04	2.795e+05	0	0	3.483e+04	1.659e+05	0	1.732e+05	1.218e+05	0	0	2.378e+05	0	0	2.28e+05	1.001e+05	0	0	3.165e+05	2.886e+05	0	1.142e+05	7.754e+04	2.503e+05	0	8.462e+04	0	0	1.621e+05	2.359e+05	1.37e+05	3.961e+05	2.831e+04	4.419e+05	4.419e+05	3.428e+05	2.393e+05	3.784e+04	2.655e+04	4.676e+04	2.083e+04	2.806e+04	8019	3.244e+04	3496	7979	3.99e+04	2.097e+04	0	1.587e+04	0	0	1.553e+04	4.347e+04	0	0	2.381e+04	3.713e+04	0	1.449e+04	4.347e+04	0	0	7937	1.122e+04	0	1.389e+04	3.175e+04	0	0	1.553e+04	1.449e+04	0	0	7937	5304	0	7246	1.449e+04	0	0	1.587e+04	0	0	6945	3.968e+04	0	0	2.329e+04	8.695e+04	0	1.122e+04	5.556e+04	1.061e+04	0	7245	0	0	6.415e+04	1.604e+04	5.614e+04	7.217e+04	1.604e+04	2.406e+04	2.406e+04	2.406e+04	1.604e+04	3.208e+04
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sum.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sum.gz
new file mode 100644
index 0000000000..74963a0948
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sum.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sum.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sum.tab
new file mode 100644
index 0000000000..4509d5d42b
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_sum.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1:8	input_computeMatrix_regions2:8	input_computeMatrix_regions3:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_thresh.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_thresh.gz
new file mode 100644
index 0000000000..2c497fee5c
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_thresh.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_thresh.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_thresh.tab
new file mode 100644
index 0000000000..59b6965734
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_thresh.tab
@@ -0,0 +1,22 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:3
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.33e+05	6.278e+05	8.122e+05	8.435e+05	7.137e+05	6.451e+05	6.14e+05	5.453e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	8.928e+04	1.437e+05	1.64e+05	1.407e+05	1.143e+05	2.262e+05	4.234e+05	4.53e+05	2.924e+05	4.351e+05	2.913e+05	3.816e+05	2.818e+05	4.328e+05	3.756e+05	2.613e+05	5.973e+05	5.977e+05	3.456e+05	9.047e+05	6.549e+05	4.235e+05	4.511e+05	3.519e+05	3.201e+05	8.762e+05	5.864e+05	4.554e+05	3.166e+05	3.548e+05	1.243e+05	5.85e+05	6.55e+05	5.454e+05	4.976e+05	1.013e+06	3.917e+05	7.999e+05	3.752e+05	4.857e+05	2.745e+05	5.496e+05	7.808e+05	4.225e+05	2.598e+05	4.877e+05	3.72e+05	2.307e+05	6.442e+05	2.96e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	1.271e+05	1.372e+05	7.565e+04	6.91e+04	2.472e+05	1.374e+05	4.29e+05	3.643e+05	5.28e+05	3.863e+05	3.518e+05	2.861e+05	2.239e+05	3.122e+05	3.683e+05	5.231e+05	5.202e+05	5.334e+05	4.432e+05	3.329e+05	4.652e+05	3.622e+05	6.531e+05	5.516e+05	3.102e+05	1.045e+06	6.657e+05	3.13e+05	4.069e+05	4.768e+05	3.648e+05	5.06e+05	7.55e+05	2.744e+05	4.167e+05	4.607e+05	1.056e+06	9.155e+05	6.409e+05	1.004e+06	7.568e+05	6.221e+05	5.132e+05	3.487e+05	2.406e+05	2.319e+05	4.031e+05	3.495e+05	3.509e+05	3.323e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.206e+05	1.472e+05	1.639e+05	2.028e+05	2.795e+05	3.13e+05	3.97e+05	3.576e+05	3.402e+05	2.44e+05	2.703e+05	2.538e+05	2.934e+05	3.803e+05	4.812e+05	5.15e+05	5.711e+05	5.988e+05	5.946e+05	5.625e+05	5.673e+05	6.255e+05	5.78e+05	5.694e+05	5.144e+05	4.806e+05	3.557e+05	3.22e+05	3.368e+05	5.212e+05	5.673e+05	5.075e+05	4.236e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.097e+05	3.786e+05	3.736e+05	3.78e+05	5.052e+05	4.924e+05	4.382e+05	4.55e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
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+1.427e+05	1.451e+05	1.66e+05	2.069e+05	2.149e+05	2.999e+05	3.071e+05	3.633e+05	4.162e+05	3.416e+05	3.645e+05	3.47e+05	2.829e+05	2.479e+05	2.312e+05	2.756e+05	2.741e+05	2.45e+05	2.275e+05	2.833e+05	2.887e+05	2.931e+05	3.164e+05	3.769e+05	4.17e+05	4.753e+05	4.972e+05	4.68e+05	5.507e+05	5.059e+05	5.351e+05	5.89e+05	6.322e+05	5.788e+05	6.007e+05	5.511e+05	6.255e+05	6.135e+05	5.541e+05	5.278e+05	5.541e+05	5.827e+05	6.459e+05	6.43e+05	5.643e+05	5.934e+05	5.667e+05	5.497e+05	5.934e+05	5.322e+05	5.092e+05	5.278e+05	5.366e+05	4.462e+05	4.155e+05	3.488e+05	3.383e+05	3.222e+05	3.281e+05	2.7e+05	3.689e+05	5.052e+05	5.533e+05	5.854e+05	4.972e+05	4.25e+05	5.132e+05	6.656e+05	8.019e+05	8.5e+05	8.016e+04	1.67e+05	1.041e+05	2.51e+05	2.941e+05	4.228e+05	4.442e+05	4.234e+05	1.827e+05	5.149e+05	4.643e+05	3.12e+05	9.564e+04	4.729e+05	3.454e+05	2.448e+05	2.698e+05	4.039e+05	3.549e+05	5.024e+05	5.175e+05	3.869e+05	2.443e+05	3.395e+05	7.494e+04	5.833e+05	7.74e+05	2.849e+05	9.414e+05	4.479e+05	5.692e+05	1.572e+05	6.05e+05	9.182e+05	9.082e+05	9.767e+05	3.467e+05	3.081e+05	3.492e+05	7.078e+05	5.38e+05	2.956e+05	3.327e+05	5.306e+05	1.091e+05	2.813e+05	4.159e+05	8.342e+05	1.013e+06	4.2e+05	5.956e+05	8.061e+05	3.867e+05	3.525e+05	7.412e+05	2.934e+05	1.472e+05	2.6e+05	4.629e+05	2.088e+05	1.17e+05	7.245e+05	4.508e+05	6.588e+05	5.918e+05	3.203e+05	9.185e+05	9.831e+05	4.416e+05	2.849e+05	5.705e+04	9.539e+04	2.82e+05	4.431e+04	3.458e+05	4.549e+05	2.879e+05	5.501e+05	5.155e+05	3.362e+05	4.763e+05	2.822e+05	3.22e+05	3.168e+05	2.214e+05	3.483e+05	1.628e+05	1.638e+05	2.825e+05	3.914e+05	3.994e+05	3.707e+05	3.462e+05	5.213e+05	6.055e+05	5.817e+05	5.727e+05	2.086e+05	8.154e+05	4.672e+05	6.031e+05	2.855e+05	2.856e+05	2.094e+05	5.755e+05	7.379e+05	2.083e+05	1.696e+05	2.637e+05	8.085e+05	5.496e+05	6.372e+05	3.71e+05	8.265e+05	4.252e+05	1.772e+05	4.082e+05	9.895e+05	1.132e+06	8.497e+05	3.65e+05	9.836e+05	6.403e+04	3.326e+05	7.014e+05	3.27e+05	3.978e+05	5.591e+05	4.527e+05	2.338e+05	4.31e+05	6.736e+05	4.734e+05	6.135e+05	3.36e+05	1.984e+05	4.51e+05	6.992e+05	8.966e+05	1.437e+06	1.427e+05	1.451e+05	1.66e+05	2.069e+05	2.149e+05	2.999e+05	3.071e+05	3.633e+05	4.162e+05	3.416e+05	3.645e+05	3.47e+05	2.829e+05	2.479e+05	2.312e+05	2.756e+05	2.741e+05	2.45e+05	2.275e+05	2.833e+05	2.887e+05	2.931e+05	3.164e+05	3.769e+05	4.17e+05	4.753e+05	4.972e+05	4.68e+05	5.507e+05	5.059e+05	5.351e+05	5.89e+05	6.322e+05	5.788e+05	6.007e+05	5.511e+05	6.255e+05	6.135e+05	5.541e+05	5.278e+05	5.541e+05	5.827e+05	6.459e+05	6.43e+05	5.643e+05	5.934e+05	5.667e+05	5.497e+05	5.934e+05	5.322e+05	5.092e+05	5.278e+05	5.366e+05	4.462e+05	4.155e+05	3.488e+05	3.383e+05	3.222e+05	3.281e+05	2.7e+05	3.689e+05	5.052e+05	5.533e+05	5.854e+05	4.972e+05	4.25e+05	nan	nan	nan	nan
+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.164e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.47e+05	1.47e+05	1.47e+05	1.47e+05	9.349e+04	4.001e+04	4.001e+04	4.001e+04	4.001e+04	2.475e+05	2.475e+05	2.475e+05	2.475e+05	2.215e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.348e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.677e+05	4.398e+04	2.297e+05	2.153e+05	4.108e+05	4.438e+05	4.715e+05	2.616e+05	4.103e+05	4.383e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3941	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	2.168e+05	2.168e+05	2.168e+05	2.168e+05	2.298e+05	2.428e+05	2.428e+05	2.428e+05	2.428e+05	3.165e+04	3.165e+04	3.165e+04	3.165e+04	5.714e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.917e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.831e+04	2.032e+05	1.821e+05	1.808e+05	3.412e+05	4.165e+05	4.88e+05	5.085e+05	2.946e+05	5.358e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.925e+05	1.925e+05	1.925e+05	1.925e+05	1.844e+05	1.764e+05	1.764e+05	1.764e+05	1.764e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.363e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.283e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.524e+05	1.443e+05	1.925e+05	2.005e+05	2.566e+05	3.288e+05	3.128e+05	4.09e+05	3.849e+05	3.448e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled.gz
new file mode 100644
index 0000000000..49c1936937
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled.tab
new file mode 100644
index 0000000000..92ecccc423
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:800	upstream:500	body:2400	bin size:20	unscaled 5 prime:240	unscaled 3 prime:40
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	3.412e+05	3.659e+05	4.014e+05	4.458e+05	3.23e+05	1.05e+05	2.436e+05	5.034e+05	4.792e+05	2.859e+05	2.859e+05	2.157e+05	9.233e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	5.289e+05	5.279e+05	5.153e+05	1.411e+05	5.286e+05	3.636e+05	3.357e+05	8.659e+05	1.363e+06	3.338e+05	7.815e+05	6.159e+05	2.889e+05	6.388e+05	2.336e+05	7.16e+05	1.27e+06	3.194e+05	4.039e+05	7.472e+05	8.382e+05	2.91e+05	3.943e+05	5.502e+05	4.455e+05	6.309e+05	3.95e+05	8.246e+05	5.195e+05	3.574e+05	1.663e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	3.208e+04	1.443e+05	1.443e+05	1.684e+05	1.684e+05	1.123e+05	1.443e+05	1.443e+05	1.684e+05	2.085e+05	2.165e+05	3.047e+05	3.047e+05	3.689e+05	4.17e+05	3.368e+05	3.689e+05	3.544e+05	2.958e+05	2.63e+05	2.317e+05	2.358e+05	2.833e+05	2.759e+05	2.477e+05	2.326e+05	2.531e+05	2.887e+05	2.887e+05	2.935e+05	3.119e+05	3.528e+05	4.17e+05	4.25e+05	4.972e+05	4.972e+05	4.651e+05	5.517e+05	5.043e+05	5.229e+05	5.417e+05	6.127e+05	6.308e+05	5.87e+05	5.881e+05	5.774e+05	5.809e+05	6.255e+05	6.095e+05	5.581e+05	5.204e+05	5.485e+05	5.649e+05	5.998e+05	6.576e+05	6.415e+05	5.613e+05	5.902e+05	5.934e+05	5.293e+05	5.756e+05	5.934e+05	5.293e+05	5.068e+05	5.221e+05	5.373e+05	5.025e+05	4.427e+05	4.117e+05	3.545e+05	3.279e+05	3.432e+05	3.083e+05	3.288e+05	2.566e+05	3.528e+05	3.849e+05	4.571e+05	5.364e+05	5.581e+05	5.489e+05	5.678e+05	5.881e+05	5.453e+05	4.954e+05	4.571e+05	4.259e+05	4.17e+05	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	4.812e+05	5.052e+05	5.435e+05	4.747e+05	4.384e+05	3.512e+05	3.368e+05	4.01e+05	3.528e+05	3.673e+05	3.261e+05	3.721e+05	4.847e+05	5.02e+05	5.079e+05	4.94e+05	4.901e+05	4.972e+05	4.829e+05	4.651e+05	4.277e+05	3.817e+05	4.562e+05	4.812e+05	4.883e+05	5.453e+05	5.453e+05	5.613e+05	5.934e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	5.212e+05	5.694e+05	5.533e+05	4.812e+05	3.929e+05	3.448e+05	3.288e+05	5.854e+05	7.057e+05	7.698e+05	6.897e+05	5.052e+05	5.052e+05	4.651e+05	6.014e+05	6.496e+05	6.576e+05	6.656e+05	5.774e+05	4.972e+05	5.132e+05	5.212e+05	5.373e+05	5.293e+05	3.849e+05	4.411e+05	4.571e+05	5.694e+05	6.736e+05	6.095e+05	6.014e+05
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled2.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled2.gz
new file mode 100644
index 0000000000..be582d0d68
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled2.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled2.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled2.tab
new file mode 100644
index 0000000000..cfeb66f8f9
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled2.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:800	upstream:500	body:200	bin size:20	unscaled 5 prime:20	unscaled 3 prime:120
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diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled3.gz b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled3.gz
new file mode 100644
index 0000000000..88ffaefce2
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled3.gz differ
diff --git a/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled3.tab b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled3.tab
new file mode 100644
index 0000000000..781f8a9ea5
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_computematrix/srmat_unscaled3.tab
@@ -0,0 +1,25 @@
+#input_computeMatrix_regions1.bed:8	input_computeMatrix_regions2.bed:8	input_computeMatrix_regions3.gtf:6
+#downstream:180	upstream:180	body:1000	bin size:20	unscaled 5 prime:20	unscaled 3 prime:20
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+4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.081e+05	5.701e+05	6.327e+05	6.555e+05	8.059e+05	8.283e+05	6.545e+05	4.424e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan	5.541e+05	7.893e+05	8.651e+05	9.009e+05	1.174e+06	2.491e+05	5.496e+05	4.642e+05	4.262e+05	7.988e+05	7.62e+05	6.258e+05	6.901e+05	2.362e+05	6.277e+05	1.28e+06	6.801e+05	2.708e+05	4.326e+05	2.886e+05	4.318e+05	4.295e+05	3.603e+05	4.79e+05	3.117e+05	4.043e+05	7.731e+05	5.462e+05	2.536e+05	4.504e+05	7.365e+05	2.968e+05	9.774e+05	5.188e+05	5.595e+05	5.759e+05	4.566e+05	2.922e+05	2.177e+05	5.057e+05	5.632e+05	8.577e+05	2.332e+05	3.906e+05	5.651e+05	3.877e+05	9.326e+05	4.029e+05	6.009e+05	5.415e+05	2.29e+05	5.116e+05	3.526e+05	3.183e+05	2.877e+05	4.498e+05	3.012e+05	4.512e+05	3.458e+05	2.357e+05	4.398e+04	1.677e+05	1.348e+05	2.215e+05	9.349e+04	3.159e+04	3.159e+04	5.76e+04	1.968e+04	nan	2.591e+05	7.513e+05	8.227e+05	7.775e+05	1.363e+06	2.213e+05	5.979e+05	3.283e+05	3.623e+05	1.46e+05	6.028e+05	7.086e+05	6.994e+05	5.355e+05	8.502e+05	2.399e+05	8.174e+05	6.45e+05	6.745e+05	3.701e+05	2.587e+05	4.072e+05	3.392e+05	3.065e+05	2.497e+05	3.401e+05	5.778e+05	6.033e+05	9.309e+05	7.861e+05	6.439e+05	1.167e+06	5.643e+05	3.788e+05	2.625e+05	6.777e+05	5.641e+05	3.776e+05	4.224e+05	4.086e+05	5.885e+05	1.028e+06	2.876e+05	6.564e+05	5.82e+05	2.367e+05	4.633e+05	3.816e+05	5.453e+05	5.424e+05	4.556e+05	3.963e+05	1.987e+05	2.729e+05	3.405e+05	3.966e+05	5.332e+05	4.032e+05	3.585e+05	1.376e+05	2.032e+05	4.831e+04	6.917e+04	5.714e+04	2.298e+05	3.748e+04	3.748e+04	1.88e+04	7762	nan	4.33e+05	6.576e+05	7.057e+05	7.538e+05	7.057e+05	3.929e+05	3.368e+05	3.609e+05	4.25e+05	5.533e+05	5.543e+05	5.448e+05	4.951e+05	5.117e+05	6.586e+05	7.478e+05	7.352e+05	5.996e+05	5.815e+05	5.205e+05	4.29e+05	4.806e+05	4.972e+05	4.263e+05	3.673e+05	3.809e+05	5.079e+05	nan	nan	nan	nan	nan	nan	4.246e+05	5.262e+05	5.603e+05	4.491e+05	3.104e+05	3.358e+05	4.496e+05	5.182e+05	5.639e+05	5.805e+05	6.286e+05	5.417e+05	6.034e+05	5.841e+05	5.862e+05	5.148e+05	4.734e+05	3.569e+05	2.866e+05	2.452e+05	2.535e+05	3.125e+05	3.579e+05	3.937e+05	3.161e+05	2.432e+05	1.976e+05	1.443e+05	1.524e+05	1.283e+05	1.363e+05	1.844e+05	1.443e+05	1.443e+05	9.623e+04	1.604e+04	nan
+nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
+nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.325e+05	6.118e+05	8.042e+05	8.477e+05	7.205e+05	6.444e+05	6.163e+05	5.499e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05	nan	nan	nan	nan	nan	4.099e+04	4.459e+04	3.159e+04	6.044e+04	1.186e+05	1.961e+05	1.41e+05	9.029e+04	2.358e+05	3.738e+05	4.485e+05	3.432e+05	3.926e+05	3.489e+05	3.379e+05	2.673e+05	4.17e+05	4.32e+05	2.642e+05	5.742e+05	5.593e+05	4.042e+05	7.811e+05	7.155e+05	3.805e+05	5.022e+05	3.728e+05	2.695e+05	9.158e+05	5.416e+05	4.664e+05	3.608e+05	3.601e+05	1.301e+05	5.725e+05	6.337e+05	5.633e+05	4.712e+05	1.012e+06	4.533e+05	7.709e+05	3.702e+05	4.77e+05	2.587e+05	5.484e+05	7.829e+05	4.471e+05	2.547e+05	4.998e+05	3.58e+05	2.421e+05	6.517e+05	3.012e+05	3.617e+05	4.286e+05	3.048e+05	5.202e+05	5.19e+05	1.269e+06	1.342e+06	4.518e+05	3.067e+05	2.153e+05	6.961e+05	6.138e+05	nan	nan	nan	nan	nan	5215	2.814e+04	3.748e+04	8.231e+04	1.835e+05	7.12e+04	5.042e+04	2.41e+05	1.079e+05	3.726e+05	3.794e+05	5.428e+05	3.777e+05	3.956e+05	2.662e+05	2.647e+05	2.788e+05	3.806e+05	4.855e+05	5.821e+05	4.861e+05	4.744e+05	2.884e+05	5.14e+05	2.89e+05	6.546e+05	5.974e+05	2.852e+05	1.055e+06	6.421e+05	3.566e+05	4.236e+05	5.025e+05	3.515e+05	5.272e+05	7.517e+05	2.765e+05	3.821e+05	4.129e+05	1.037e+06	9.821e+05	6.209e+05	9.719e+05	7.762e+05	6.161e+05	5.378e+05	3.549e+05	2.36e+05	2.295e+05	4.025e+05	3.481e+05	3.61e+05	3.232e+05	3.275e+05	7.211e+05	4.706e+05	9.882e+05	7.882e+05	1.023e+05	7.49e+05	7.714e+05	2.456e+05	8.506e+05	5.625e+05	9.471e+05	nan	nan	nan	nan	nan	2.673e+04	1.203e+05	1.443e+05	1.564e+05	1.764e+05	1.236e+05	1.501e+05	1.535e+05	2.032e+05	2.538e+05	3.139e+05	3.843e+05	3.735e+05	3.448e+05	2.509e+05	2.697e+05	2.475e+05	2.916e+05	3.665e+05	4.743e+05	5.086e+05	5.536e+05	6.037e+05	5.929e+05	5.722e+05	5.608e+05	6.289e+05	5.808e+05	5.697e+05	5.144e+05	4.892e+05	3.618e+05	3.299e+05	3.276e+05	5.086e+05	5.649e+05	5.19e+05	4.246e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.109e+05	3.826e+05	3.723e+05	3.73e+05	5.064e+05	4.92e+05	4.414e+05	4.514e+05	5.327e+05	5.843e+05	5.694e+05	6.415e+05	7.859e+05	7.378e+05	7.618e+05	6.496e+05	5.453e+05	4.812e+05	4.892e+05	5.613e+05
+nan	nan	nan	1.604e+04	3.849e+04	1.443e+05	1.443e+05	1.7e+05	1.652e+05	1.139e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.564e+05	2.005e+05	2.085e+05	2.807e+05	3.168e+05	3.408e+05	4.13e+05	3.609e+05	3.528e+05	2.967e+05	nan	nan	nan	1.968e+04	5.224e+04	3.159e+04	3.159e+04	8.97e+04	1.515e+05	1.894e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	2.614e+05	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.241e+04	7.739e+04	2.416e+05	2.591e+05	4.174e+05	4.44e+05	4.448e+05	2.178e+05	4.684e+05	4.224e+05	2.151e+05	nan	nan	nan	7762	5427	3.748e+04	3.748e+04	1.374e+05	1.292e+05	8.129e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	4.092e+04	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	1.603e+05	2.47e+05	1.056e+05	2.725e+05	4.044e+05	3.45e+05	5.225e+05	5.124e+05	3.177e+05	4.537e+05	3.239e+05	nan	nan	nan	1.604e+04	3.849e+04	1.443e+05	1.443e+05	1.7e+05	1.652e+05	1.139e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.283e+05	1.564e+05	2.005e+05	2.085e+05	2.807e+05	3.168e+05	3.408e+05	4.13e+05	3.609e+05	3.528e+05	2.967e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	1.059e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.925e+05	1.925e+05	1.925e+05	1.818e+05	1.764e+05	1.764e+05	1.764e+05	1.657e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.337e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.55e+05	1.604e+05	1.604e+05	1.604e+05	1.39e+05	1.283e+05	1.283e+05	1.612e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05	nan	nan	nan	nan	nan	nan	nan	nan	3.033e+04	5.24e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	3.159e+04	1.085e+05	1.47e+05	1.47e+05	1.47e+05	7.566e+04	4.001e+04	4.001e+04	4.001e+04	1.783e+05	2.475e+05	2.475e+05	2.475e+05	2.128e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.954e+05	1.145e+05	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	7.409e+04	1.989e+05	2.614e+05	2.614e+05	2.614e+05	1.354e+05	7.241e+04	7.241e+04	9.075e+04	2.463e+05	2.766e+05	4.201e+05	4.441e+05	4.341e+05	2.003e+05	4.916e+05	4.16e+05	2.319e+05	nan	nan	nan	nan	nan	nan	nan	nan	6488	2.253e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	3.748e+04	1.57e+05	2.168e+05	2.168e+05	2.168e+05	2.341e+05	2.428e+05	2.428e+05	2.428e+05	1.02e+05	3.165e+04	3.165e+04	3.165e+04	6.564e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	8.263e+04	6.468e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	5.57e+04	4.585e+04	4.092e+04	4.092e+04	4.092e+04	1.205e+05	1.603e+05	1.603e+05	2.645e+05	7.494e+04	3.092e+05	4.296e+05	3.164e+05	5.363e+05	5.139e+05	3.27e+05	4.209e+05	3.371e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.138e+04	1.059e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.764e+05	1.925e+05	1.925e+05	1.925e+05	1.818e+05	1.764e+05	1.764e+05	1.764e+05	1.657e+05	1.604e+05	1.604e+05	1.604e+05	1.283e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.123e+05	1.337e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.443e+05	1.55e+05	1.604e+05	1.604e+05	1.604e+05	1.39e+05	1.283e+05	1.283e+05	1.612e+05	2.037e+05	2.117e+05	2.903e+05	3.119e+05	3.52e+05	4.146e+05	3.512e+05	3.561e+05	2.871e+05
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+nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.764e+05	6.851e+05	8.328e+05	8.191e+05	6.796e+05	6.438e+05	6.023e+05	5.18e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05	nan	nan	nan	nan	nan	nan	nan	nan	2.549e+04	5.5e+04	3.159e+04	7.588e+04	1.863e+05	1.056e+05	1.237e+05	2.182e+05	3.037e+05	4.307e+05	4.398e+05	2.772e+05	4.698e+05	2.816e+05	3.016e+05	3.492e+05	4.84e+05	3.774e+05	2.562e+05	6.175e+05	6.333e+05	4.259e+05	9.241e+05	3.945e+05	5.751e+05	3.132e+05	3.116e+05	5.393e+05	6.587e+05	6.647e+05	5.248e+05	2.048e+05	3.165e+05	3.065e+05	5.345e+05	6.702e+05	4.526e+05	7.251e+05	9.358e+05	2.394e+05	7.581e+05	4.039e+05	4.456e+05	4.339e+05	5.698e+05	7.696e+05	2.506e+05	3.352e+05	4.324e+05	4.558e+05	2.491e+05	6.21e+05	2.396e+05	3.037e+05	5.176e+05	3.348e+05	2.779e+05	5.771e+05	6.359e+05	1.261e+06	1.238e+06	4.225e+05	nan	nan	nan	nan	nan	nan	nan	nan	7067	2.067e+04	3.748e+04	1.419e+05	9.302e+04	6.268e+04	1.422e+05	1.585e+05	2.96e+05	3.828e+05	4.913e+05	4.354e+05	4.312e+05	3.349e+05	2.575e+05	1.863e+05	3.817e+05	3.753e+05	5.97e+05	4.741e+05	6.189e+05	2.873e+05	4.972e+05	2.45e+05	6.129e+05	4.575e+05	5.297e+05	5.754e+05	9.355e+05	4.753e+05	4.748e+05	4.126e+05	3.699e+05	5.21e+05	4.835e+05	6.177e+05	2.525e+05	4.216e+05	6.787e+05	1.202e+06	6.195e+05	7.798e+05	1.051e+06	6.546e+05	6.833e+05	3.625e+05	3.574e+05	2.38e+05	2.292e+05	4.063e+05	3.766e+05	2.846e+05	3.865e+05	3.62e+05	3.772e+05	8.121e+05	5.561e+05	9.629e+05	6.997e+05	7.343e+04	8.527e+05	7.262e+05	nan	nan	nan	nan	nan	nan	nan	nan	1.895e+04	1.01e+05	1.443e+05	1.681e+05	1.409e+05	1.36e+05	1.489e+05	1.931e+05	2.211e+05	3.142e+05	3.356e+05	4.038e+05	3.469e+05	2.956e+05	2.513e+05	2.503e+05	2.768e+05	3.116e+05	4.378e+05	4.948e+05	5.258e+05	6.077e+05	5.768e+05	6.095e+05	5.419e+05	6.053e+05	6.014e+05	5.637e+05	5.548e+05	5.293e+05	4.289e+05	3.368e+05	3.006e+05	4.004e+05	5.483e+05	5.714e+05	4.697e+05	4.17e+05	nan	nan	nan	nan	nan	nan	4.812e+05	5.006e+05	3.629e+05	3.637e+05	4.158e+05	4.983e+05	4.901e+05	4.233e+05	4.699e+05	5.229e+05	5.581e+05	5.958e+05	5.79e+05	6.608e+05	7.763e+05	7.426e+05	7.498e+05	6.327e+05
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+6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.546e+05	6.858e+05	6.059e+05	4.714e+05	3.809e+05	3.045e+05	2.439e+05	2.074e+05	3.288e+05	3.933e+05	2.99e+05	3.347e+05	4.712e+05	3.946e+05	3.975e+05	4.184e+05	4.524e+05	3.281e+05	2.068e+05	3.872e+04	3.162e+05	3.119e+05	2.334e+04	4.096e+05	4.702e+05	4.651e+05	7.376e+05	4.963e+05	1.744e+05	1.744e+05	4.019e+05	6.275e+05	9.582e+05	9.089e+05	9.082e+05	9.555e+05	7.705e+05	5.759e+05	3.575e+05	4.983e+05	5.441e+05	5.696e+05	5.161e+05	3.505e+05	2.876e+05	4.073e+05	4.664e+05	5.017e+05	5.306e+05	9.931e+04	3.043e+04	3.446e+04	1.516e+05	1.516e+05	1.516e+05	1.516e+05	4.81e+04	1.444e+04	3.376e+04	3.376e+04	3.376e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan	5.119e+05	9.756e+05	5.762e+05	4.955e+05	2.688e+05	4.18e+05	1.989e+05	3.728e+05	2.156e+05	6.24e+04	3.469e+05	3.446e+05	1.966e+05	3.542e+05	3.814e+05	3.826e+05	3.001e+05	3.452e+05	3.65e+05	2.809e+05	3.043e+05	2.61e+05	1.296e+05	1.879e+05	1.348e+05	5.105e+04	7.657e+05	5.208e+05	1.941e+05	1.941e+05	3.829e+05	4.95e+05	3.186e+05	3.384e+05	4.954e+05	8.678e+05	7.541e+05	6.079e+05	4.382e+05	3329	3.225e+05	5.276e+05	3.218e+05	3.253e+05	3.565e+05	5.337e+05	4.398e+05	2.941e+05	2.379e+04	2.948e+05	2.572e+05	1.469e+05	6.854e+04	6.854e+04	6.854e+04	6.854e+04	5.555e+04	3.846e+04	8740	8740	8740	nan	nan	nan	nan	nan	nan	nan	nan	nan	6.111e+05	6.038e+05	5.092e+05	5.525e+05	4.539e+05	3.721e+05	3.168e+05	2.101e+05	2.462e+05	2.887e+05	3.422e+05	3.483e+05	3.368e+05	3.643e+05	3.414e+05	3.047e+05	2.887e+05	2.612e+05	2.497e+05	3.047e+05	2.818e+05	2.589e+05	2.245e+05	2.52e+05	2.841e+05	3.208e+05	4.17e+05	4.514e+05	4.972e+05	4.972e+05	4.88e+05	4.949e+05	5.774e+05	5.659e+05	5.522e+05	5.293e+05	4.743e+05	4.582e+05	4.491e+05	4.01e+05	4.285e+05	4.376e+05	3.689e+05	3.047e+05	2.772e+05	3.047e+05	3.276e+05	3.185e+05	2.727e+05	2.039e+05	1.718e+05	1.443e+05	9.623e+04	9.623e+04	9.623e+04	9.623e+04	7.332e+04	5.499e+04	3.208e+04	3.208e+04	3.208e+04	nan	nan	nan	nan	nan	nan	nan	nan	nan
+6.832e+05	5.934e+05	6.055e+05	5.581e+05	5.212e+05	6.271e+05	6.423e+05	6.488e+05	6.215e+05	4.86e+05	4.812e+05	4.949e+05	5.132e+05	6.095e+05	5.894e+05	6.049e+05	6.736e+05	6.736e+05	6.942e+05	7.358e+05	8.34e+05	8.111e+05	8.294e+05	8.982e+05	7.698e+05	7.607e+05	7.584e+05	7.859e+05	7.618e+05	7.263e+05	6.897e+05	4.972e+05	4.771e+05	4.56e+05	4.33e+05	4.33e+05	4.262e+05	4.15e+05	4.01e+05	3.895e+05	3.758e+05	3.528e+05	4.33e+05	4.147e+05	4.01e+05	4.01e+05	4.13e+05	3.826e+05	3.368e+05	3.849e+05	4.15e+05	4.88e+05	6.255e+05	5.98e+05	6.415e+05	7.017e+05	6.736e+05	6.622e+05	6.576e+05	6.576e+05	5.613e+05	4.33e+05	4.892e+05	6.977e+05	7.859e+05	6.977e+05	6.175e+05	4.25e+05	4.17e+05	5.613e+05	9.12e+05	1.017e+06	6.502e+05	6.648e+05	7.002e+05	7.664e+05	1.687e+05	5.295e+05	5.753e+05	7.476e+05	7.853e+05	6.42e+05	4.509e+05	2.791e+05	7.19e+05	8.13e+05	3.884e+05	3.884e+05	2.764e+05	1.776e+05	5.311e+05	1.231e+06	1.525e+06	1.563e+06	6.368e+05	6.441e+05	5.775e+05	1.448e+05	5.209e+05	8.801e+05	1.192e+06	1.636e+05	1.68e+05	3.211e+05	6.97e+05	6.97e+05	6.504e+05	5.9e+05	6.011e+05	5.38e+05	4.703e+05	3.641e+05	4.14e+05	3.892e+05	3.706e+05	3.706e+05	5.177e+05	5.821e+05	6.026e+05	6.609e+04	4.48e+05	8.389e+05	1.243e+06	3.329e+05	2.626e+05	4.165e+05	7.336e+05	5.391e+05	4.614e+05	4.614e+05	7.236e+05	3.839e+05	4.187e+05	7.747e+05	9.902e+05	7.763e+05	4.156e+05	5.659e+05	4.06e+05	1.383e+05	7.246e+05	8.197e+05	7.302e+05	6.278e+05	3.42e+05	1.144e+06	1.053e+06	9.349e+05	8.136e+05	8.918e+05	8.953e+05	8.184e+05	7.158e+05	7.645e+05	6.572e+05	6.317e+05	7.285e+05	7.285e+05	8.816e+05	9.548e+05	3.829e+04	7.063e+05	7.792e+05	2.934e+05	1.361e+06	1.064e+06	8.965e+05	1.23e+06	9.13e+05	8.167e+05	8.293e+05	6.606e+05	7.066e+05	5.573e+05	1.153e+05	1.153e+05	1.455e+05	2.484e+05	6.873e+05	4.135e+05	2.27e+05	3.447e+04	6.641e+05	3.895e+05	1.835e+05	1.835e+05	5.783e+05	6.232e+05	5.076e+05	6539	4.152e+05	4.778e+05	2.15e+04	3.013e+05	4.151e+05	5.993e+05	1.262e+06	1.128e+06	1.074e+06	1.074e+06	9.324e+05	3.486e+05	3.342e+05	6.576e+05	2.306e+05	5.223e+05	5.64e+05	4.097e+05	5.132e+05	9.741e+05	6.832e+05	5.934e+05	6.055e+05	5.581e+05	5.212e+05	6.271e+05	6.423e+05	6.488e+05	6.215e+05	4.86e+05	4.812e+05	4.949e+05	5.132e+05	6.095e+05	5.894e+05	6.049e+05	6.736e+05	6.736e+05	6.942e+05	7.358e+05	8.34e+05	8.111e+05	8.294e+05	8.982e+05	7.698e+05	7.607e+05	7.584e+05	7.859e+05	7.618e+05	7.263e+05	6.897e+05	4.972e+05	4.771e+05	4.56e+05	4.33e+05	4.33e+05	4.262e+05	4.15e+05	4.01e+05	3.895e+05	3.758e+05	3.528e+05	4.33e+05	4.147e+05	4.01e+05	4.01e+05	4.13e+05	3.826e+05	3.368e+05	3.849e+05	4.15e+05	4.88e+05	6.255e+05	5.98e+05	6.415e+05	7.017e+05	6.736e+05	6.622e+05	6.576e+05	6.576e+05	5.613e+05	4.33e+05	4.892e+05	6.977e+05	7.859e+05	6.977e+05	6.175e+05	4.25e+05	4.17e+05	5.613e+05
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/bed12.bed b/pydeeptools/deeptools/test/test_data/test_mbs/bed12.bed
new file mode 100644
index 0000000000..bd24509bd4
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/bed12.bed
@@ -0,0 +1,2 @@
+3R	0	1000	first	0	+	0	1000	0	3	50,111,21,	0,399,979,
+3R	99	1100	second	0	-	99	1100	0	3	51,111,21,	0,400,980,
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_counts.tsv b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_counts.tsv
new file mode 100644
index 0000000000..6eb9049117
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_counts.tsv
@@ -0,0 +1,10 @@
+#'chr'	'start'	'end'	'test1.bam'	'test1.bam'
+3R	1	50	1.0	1.0
+3R	1	1000	144.0	144.0
+3R	1	1000	144.0	144.0
+3R	100	150	6.0	6.0
+3R	100	1100	143.0	143.0
+3R	400	510	22.0	22.0
+3R	500	610	25.0	25.0
+3R	980	1000	1.0	1.0
+3R	1080	1100	0.0	0.0
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_counts2.tsv b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_counts2.tsv
new file mode 100644
index 0000000000..8120b1cd4c
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_counts2.tsv
@@ -0,0 +1,6 @@
+#'chr'	'start'	'end'	'testA.bam'	'testB.bam'
+3R	1	50	0.0	0.0
+3R	1	200	2.0	4.0
+3R	1	200	2.0	4.0
+3R	100	150	1.0	1.0
+3R	100	200	2.0	3.0
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_sf.txt b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_sf.txt
new file mode 100644
index 0000000000..f659e0db72
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_sf.txt
@@ -0,0 +1,3 @@
+sample	scalingFactor
+test1.bam	1.0000
+test1.bam	1.0000
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_sf2.txt b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_sf2.txt
new file mode 100644
index 0000000000..3899045383
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/bedmode_sf2.txt
@@ -0,0 +1,3 @@
+sample	scalingFactor
+testA.bam	1.3161
+testB.bam	0.7598
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/binmode_counts.tsv b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_counts.tsv
new file mode 100644
index 0000000000..faf27de713
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_counts.tsv
@@ -0,0 +1,151 @@
+#'chr'	'start'	'end'	'test1.bam'	'test1.bam'
+3R	0	10	1.0	1.0
+3R	10	20	1.0	1.0
+3R	20	30	1.0	1.0
+3R	30	40	1.0	1.0
+3R	40	50	1.0	1.0
+3R	50	60	1.0	1.0
+3R	60	70	0.0	0.0
+3R	70	80	1.0	1.0
+3R	80	90	2.0	2.0
+3R	90	100	3.0	3.0
+3R	100	110	3.0	3.0
+3R	110	120	4.0	4.0
+3R	120	130	4.0	4.0
+3R	130	140	4.0	4.0
+3R	140	150	4.0	4.0
+3R	150	160	7.0	7.0
+3R	160	170	10.0	10.0
+3R	170	180	17.0	17.0
+3R	180	190	21.0	21.0
+3R	190	200	21.0	21.0
+3R	200	210	20.0	20.0
+3R	210	220	17.0	17.0
+3R	220	230	17.0	17.0
+3R	230	240	12.0	12.0
+3R	240	250	8.0	8.0
+3R	250	260	7.0	7.0
+3R	260	270	8.0	8.0
+3R	270	280	8.0	8.0
+3R	280	290	7.0	7.0
+3R	290	300	5.0	5.0
+3R	300	310	6.0	6.0
+3R	310	320	6.0	6.0
+3R	320	330	5.0	5.0
+3R	330	340	4.0	4.0
+3R	340	350	5.0	5.0
+3R	350	360	4.0	4.0
+3R	360	370	3.0	3.0
+3R	370	380	4.0	4.0
+3R	380	390	6.0	6.0
+3R	390	400	8.0	8.0
+3R	400	410	8.0	8.0
+3R	410	420	10.0	10.0
+3R	420	430	12.0	12.0
+3R	430	440	13.0	13.0
+3R	440	450	13.0	13.0
+3R	450	460	12.0	12.0
+3R	460	470	11.0	11.0
+3R	470	480	10.0	10.0
+3R	480	490	9.0	9.0
+3R	490	500	7.0	7.0
+3R	500	510	6.0	6.0
+3R	510	520	5.0	5.0
+3R	520	530	5.0	5.0
+3R	530	540	5.0	5.0
+3R	540	550	6.0	6.0
+3R	550	560	6.0	6.0
+3R	560	570	5.0	5.0
+3R	570	580	9.0	9.0
+3R	580	590	10.0	10.0
+3R	590	600	10.0	10.0
+3R	600	610	14.0	14.0
+3R	610	620	14.0	14.0
+3R	620	630	14.0	14.0
+3R	630	640	11.0	11.0
+3R	640	650	8.0	8.0
+3R	650	660	10.0	10.0
+3R	660	670	5.0	5.0
+3R	670	680	6.0	6.0
+3R	680	690	8.0	8.0
+3R	690	700	8.0	8.0
+3R	700	710	11.0	11.0
+3R	710	720	9.0	9.0
+3R	720	730	15.0	15.0
+3R	730	740	14.0	14.0
+3R	740	750	12.0	12.0
+3R	750	760	13.0	13.0
+3R	760	770	12.0	12.0
+3R	770	780	13.0	13.0
+3R	780	790	6.0	6.0
+3R	790	800	6.0	6.0
+3R	800	810	6.0	6.0
+3R	810	820	4.0	4.0
+3R	820	830	3.0	3.0
+3R	830	840	1.0	1.0
+3R	840	850	3.0	3.0
+3R	850	860	5.0	5.0
+3R	860	870	15.0	15.0
+3R	870	880	22.0	22.0
+3R	880	890	23.0	23.0
+3R	890	900	26.0	26.0
+3R	900	910	25.0	25.0
+3R	910	920	26.0	26.0
+3R	920	930	18.0	18.0
+3R	930	940	11.0	11.0
+3R	940	950	9.0	9.0
+3R	950	960	6.0	6.0
+3R	960	970	6.0	6.0
+3R	970	980	3.0	3.0
+3R	980	990	1.0	1.0
+3R	990	1000	1.0	1.0
+3R	1000	1010	1.0	1.0
+3R	1010	1020	1.0	1.0
+3R	1020	1030	0.0	0.0
+3R	1030	1040	0.0	0.0
+3R	1040	1050	0.0	0.0
+3R	1050	1060	0.0	0.0
+3R	1060	1070	0.0	0.0
+3R	1070	1080	0.0	0.0
+3R	1080	1090	0.0	0.0
+3R	1090	1100	0.0	0.0
+3R	1100	1110	0.0	0.0
+3R	1110	1120	0.0	0.0
+3R	1120	1130	0.0	0.0
+3R	1130	1140	0.0	0.0
+3R	1140	1150	0.0	0.0
+3R	1150	1160	0.0	0.0
+3R	1160	1170	0.0	0.0
+3R	1170	1180	0.0	0.0
+3R	1180	1190	0.0	0.0
+3R	1190	1200	0.0	0.0
+3R	1200	1210	0.0	0.0
+3R	1210	1220	0.0	0.0
+3R	1220	1230	0.0	0.0
+3R	1230	1240	0.0	0.0
+3R	1240	1250	0.0	0.0
+3R	1250	1260	0.0	0.0
+3R	1260	1270	0.0	0.0
+3R	1270	1280	0.0	0.0
+3R	1280	1290	0.0	0.0
+3R	1290	1300	0.0	0.0
+3R	1300	1310	0.0	0.0
+3R	1310	1320	0.0	0.0
+3R	1320	1330	0.0	0.0
+3R	1330	1340	0.0	0.0
+3R	1340	1350	0.0	0.0
+3R	1350	1360	0.0	0.0
+3R	1360	1370	0.0	0.0
+3R	1370	1380	0.0	0.0
+3R	1380	1390	0.0	0.0
+3R	1390	1400	0.0	0.0
+3R	1400	1410	0.0	0.0
+3R	1410	1420	0.0	0.0
+3R	1420	1430	0.0	0.0
+3R	1430	1440	0.0	0.0
+3R	1440	1450	0.0	0.0
+3R	1450	1460	0.0	0.0
+3R	1460	1470	0.0	0.0
+3R	1470	1480	0.0	0.0
+3R	1480	1490	0.0	0.0
+3R	1490	1500	0.0	0.0
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/binmode_counts2.tsv b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_counts2.tsv
new file mode 100644
index 0000000000..6112396311
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_counts2.tsv
@@ -0,0 +1,21 @@
+#'chr'	'start'	'end'	'testA.bam'	'testB.bam'
+3R	0	10	0.0	0.0
+3R	10	20	0.0	0.0
+3R	20	30	0.0	0.0
+3R	30	40	0.0	0.0
+3R	40	50	0.0	0.0
+3R	50	60	0.0	1.0
+3R	60	70	0.0	1.0
+3R	70	80	0.0	1.0
+3R	80	90	0.0	1.0
+3R	90	100	0.0	1.0
+3R	100	110	1.0	1.0
+3R	110	120	1.0	1.0
+3R	120	130	1.0	1.0
+3R	130	140	1.0	1.0
+3R	140	150	1.0	1.0
+3R	150	160	1.0	2.0
+3R	160	170	1.0	2.0
+3R	170	180	1.0	2.0
+3R	180	190	1.0	2.0
+3R	190	200	1.0	2.0
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/binmode_sf.txt b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_sf.txt
new file mode 100644
index 0000000000..f659e0db72
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_sf.txt
@@ -0,0 +1,3 @@
+sample	scalingFactor
+test1.bam	1.0000
+test1.bam	1.0000
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/binmode_sf2.txt b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_sf2.txt
new file mode 100644
index 0000000000..9b9f199040
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/binmode_sf2.txt
@@ -0,0 +1,3 @@
+sample	scalingFactor
+testA.bam	1.1892
+testB.bam	0.8409
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/blacklist.bed b/pydeeptools/deeptools/test/test_data/test_mbs/blacklist.bed
new file mode 100644
index 0000000000..d9c7444c0e
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/blacklist.bed
@@ -0,0 +1 @@
+3R	500	1000
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test.bed b/pydeeptools/deeptools/test/test_data/test_mbs/test.bed
new file mode 100644
index 0000000000..9eac11d5af
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/test.bed
@@ -0,0 +1,9 @@
+3R	1	1000
+3R	1	1000
+3R	1	50
+3R	400	510
+3R	980	1000
+3R	100	1100
+3R	100	150
+3R	500	610
+3R	1080	1100
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test.gtf b/pydeeptools/deeptools/test/test_data/test_mbs/test.gtf
new file mode 100644
index 0000000000..18587cf68f
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/test.gtf
@@ -0,0 +1,9 @@
+3R	deepTools	gene	1	1000	.	.	0	gene_id "example";
+3R	deepTools	transcript	1	1000	.	+	0	gene_id example; transcript_id "first";
+3R	deepTools	exon	1	50	.	+	0	gene_id example; transcript_id "first";
+3R	deepTools	exon	400	510	.	+	0	gene_id example; transcript_id "first";
+3R	deepTools	exon	980	1000	.	+	0	gene_id example; transcript_id "first";
+3R	deepTools	transcript	100	1100	.	-	0	gene_id example; transcript_id "second";
+3R	deepTools	exon	100	150	.	-	0	gene_id example; transcript_id "second";
+3R	deepTools	exon	500	610	.	-	0	gene_id example; transcript_id "second";
+3R	deepTools	exon	1080	1100	.	-	0	gene_id example; transcript_id "second";
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test1.bam b/pydeeptools/deeptools/test/test_data/test_mbs/test1.bam
new file mode 100644
index 0000000000..ba9f13eb1e
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/test1.bam differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test1.bam.bai b/pydeeptools/deeptools/test/test_data/test_mbs/test1.bam.bai
new file mode 100644
index 0000000000..a846febd97
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/test1.bam.bai differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test1.cram b/pydeeptools/deeptools/test/test_data/test_mbs/test1.cram
new file mode 100644
index 0000000000..e951b47056
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/test1.cram differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test1.cram.crai b/pydeeptools/deeptools/test/test_data/test_mbs/test1.cram.crai
new file mode 100644
index 0000000000..aa84bd282f
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/test1.cram.crai differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test2.bed b/pydeeptools/deeptools/test/test_data/test_mbs/test2.bed
new file mode 100644
index 0000000000..6ab3724d54
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/test2.bed
@@ -0,0 +1,2 @@
+3R	1	1000
+3R	1	1500
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testA.bam b/pydeeptools/deeptools/test/test_data/test_mbs/testA.bam
new file mode 100644
index 0000000000..c4cbca9454
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testA.bam differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testA.bam.bai b/pydeeptools/deeptools/test/test_data/test_mbs/testA.bam.bai
new file mode 100644
index 0000000000..e43c017e66
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testA.bam.bai differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testA.cram b/pydeeptools/deeptools/test/test_data/test_mbs/testA.cram
new file mode 100644
index 0000000000..97335492d5
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testA.cram differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testA.cram.crai b/pydeeptools/deeptools/test/test_data/test_mbs/testA.cram.crai
new file mode 100644
index 0000000000..ce54a97b9d
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testA.cram.crai differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testB.bam b/pydeeptools/deeptools/test/test_data/test_mbs/testB.bam
new file mode 100644
index 0000000000..f1ac616b78
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testB.bam differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testB.bam.bai b/pydeeptools/deeptools/test/test_data/test_mbs/testB.bam.bai
new file mode 100644
index 0000000000..3510ccc819
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testB.bam.bai differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testB.cram b/pydeeptools/deeptools/test/test_data/test_mbs/testB.cram
new file mode 100644
index 0000000000..7bc11ce374
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testB.cram differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/testB.cram.crai b/pydeeptools/deeptools/test/test_data/test_mbs/testB.cram.crai
new file mode 100644
index 0000000000..8177fe22ac
Binary files /dev/null and b/pydeeptools/deeptools/test/test_data/test_mbs/testB.cram.crai differ
diff --git a/pydeeptools/deeptools/test/test_data/test_mbs/test_customids.gtf b/pydeeptools/deeptools/test/test_data/test_mbs/test_customids.gtf
new file mode 100644
index 0000000000..7fca2a5335
--- /dev/null
+++ b/pydeeptools/deeptools/test/test_data/test_mbs/test_customids.gtf
@@ -0,0 +1,9 @@
+3R	deepTools	gene	1	1000	.	.	0	gene_id "example";
+3R	deepTools	mRNA	1	1000	.	+	0	gene_id "example"; ID "first";
+3R	deepTools	CDS	1	50	.	+	0	gene_id "example"; ID "first";
+3R	deepTools	CDS	400	510	.	+	0	gene_id "example"; ID "first";
+3R	deepTools	CDS	980	1000	.	+	0	gene_id "example"; ID "first";
+3R	deepTools	mRNA	100	1100	.	-	0	gene_id "example"; ID "second";
+3R	deepTools	CDS	100	150	.	-	0	gene_id "example"; ID "second";
+3R	deepTools	CDS	500	610	.	-	0	gene_id "example"; ID "second";
+3R	deepTools	CDS	1080	1100	.	-	0	gene_id "example"; ID "second";
diff --git a/pydeeptools/deeptools/test/test_multiBamSummary.py b/pydeeptools/deeptools/test/test_multiBamSummary.py
index e5ad496284..85ff43b3ba 100644
--- a/pydeeptools/deeptools/test/test_multiBamSummary.py
+++ b/pydeeptools/deeptools/test/test_multiBamSummary.py
@@ -1,54 +1,495 @@
 import deeptools.multiBamSummary2 as mbs
 import numpy as np
 import numpy.testing as nt
+import math
+import csv
 
 import os.path
-from os import unlink
 import tempfile
 
-ROOT = os.path.dirname(os.path.abspath(__file__)) + "/test_data/"
-BAM = ROOT + "test1.bam"
-CRAM = ROOT + "test1.cram"
+ROOT = os.path.dirname(os.path.abspath(__file__)) + "/test_data/test_mbs/"
+BAM = ROOT + "test1"
 GTF = ROOT + "test.gtf"
-BAMA = ROOT + "testA.bam"
-BAMB = ROOT + "testB.bam"
+BED = ROOT + "test.bed"
+BED2 = ROOT + "test2.bed"
+BED12 = ROOT + "bed12.bed"
 
+BAMA = ROOT + "testA"
+BAMB = ROOT + "testB"
+BLACKLIST = ROOT + "blacklist.bed"
+GTF2 = ROOT + "test_customids.gtf"
 
-def test_multiBamSummary_gtf():
+def compare_tsv(exp_tsv, obs_tsv, delta=1.0):
+    with open(exp_tsv) as e, open(obs_tsv) as o:
+        exp = list(csv.reader(e, delimiter="\t"))
+        obs = list(csv.reader(o, delimiter="\t"))
+
+    assert len(exp) == len(obs), f"row count differs: {len(exp)} != {len(obs)}"
+
+    for i, (erow, orow) in enumerate(zip(exp, obs)):
+        assert len(erow) == len(orow), f"col count differs on row {i}"
+        for j, (a, b) in enumerate(zip(erow, orow)):
+            try:
+                assert math.isclose(float(a), float(b), abs_tol=delta), \
+                    f"row {i}, col {j}: {a} != {b}"
+            except ValueError:
+                a = a.replace('.cram', '').replace('.bam', '')
+                b = b.replace('.cram', '').replace('.bam', '')
+                assert a == b, f"row {i}, col {j}: {a!r} != {b!r}"
+
+def test_multiBamSummary_bedmode_gtf():
     _, outfile = tempfile.mkstemp(suffix=".npz")
-    #for fname in [BAM, CRAM]:
-    for fname in [BAM]:
-        args = 'BED-file --BED {0} -b {1} {1} -o {2}'.format(GTF, fname, outfile).split()
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {GTF} -b {fname} {fname} -o {outfile}".split()
         mbs.main(args)
         resp = np.load(outfile)
         matrix = resp['matrix']
 
-        nt.assert_allclose(matrix, np.array([[144.0, 144.0],
-                                             [143.0, 143.0]]))
-        unlink(outfile)
+        nt.assert_allclose(matrix, np.array([[144.0, 144.0],[143.0, 143.0]]))
 
+def test_multiBamSummary_bedmode_bed():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile}".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[1.0, 1.0], [144.0, 144.0], [144.0, 144.0], [6.0, 6.0], [143.0, 143.0], [22.0, 22.0], [25.0, 25.0], [1.0, 1.0], [0.0, 0.0]]
+            )
+        )
 
-def test_multiBamSummary_metagene():
+def test_multiBamSummary_bedmode_multibed():
     _, outfile = tempfile.mkstemp(suffix=".npz")
-    #for fname in [BAM, CRAM]:
-    for fname in [BAM]:
-        args = 'BED-file --BED {0} -b {1} {1} -o {2} --metagene'.format(GTF, fname, outfile).split()
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} {GTF} {BED} -b {fname} {fname} -o {outfile}".split()
         mbs.main(args)
         resp = np.load(outfile)
         matrix = resp['matrix']
 
-        nt.assert_allclose(matrix, np.array([[24.0, 24.0],
-                                             [31.0, 31.0]]))
-        unlink(outfile)
+        nt.assert_allclose(matrix,
+            np.array(
+                [[144.0, 144.0], [1.0, 1.0], [1.0, 1.0], [144.0, 144.0], [144.0, 144.0], [144.0, 144.0], [144.0, 144.0], [143.0, 143.0], [6.0, 6.0], [6.0, 6.0], [143.0, 143.0], [143.0, 143.0], [22.0, 22.0], [22.0, 22.0], [25.0, 25.0], [25.0, 25.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0]]
+            )
+        )
 
+def test_multiBamSummary_bedmode_diffbam():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname1 = BAMA + fname
+        fname2 = BAMB + fname
+        args = f"BED-file --BED {BED} -b {fname1} {fname2} -o {outfile}".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[0.0, 0.0], [2.0, 4.0], [2.0, 4.0], [1.0, 1.0], [2.0, 3.0]]
+            )
+        )
+
+def test_multiBamSummary_bedmode_labels():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname1 = BAMA + fname
+        fname2 = BAMB + fname
+        args = f"BED-file --BED {BED} -b {fname1} {fname2} -o {outfile} --labels bam_part1 bam2".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        labels = resp['labels']
+        decoded_labels = [bytes(lab).decode('ascii').rstrip('\x00') for lab in labels]
+
+        assert decoded_labels == ['bam_part1', 'bam2']
 
-def test_multiBamSummary_scalingFactors():
-    _, outfile = tempfile.mkstemp(suffix=".txt")
-    _, outfile2 = tempfile.mkstemp(suffix=".npz")
-    args = 'bins --binSize 50 -b {} {} --scalingFactors {} -o {} --verbose'.format(BAMA, BAMB, outfile, outfile2).split()
-    mbs.main(args)
-    resp = open(outfile).read().strip().split('\n')
-    assert resp == ["Sample\tscalingFactor", "testA.bam\t1.1892071", "testB.bam\t0.8408964"]
-    nt.assert_equal(resp, ["Sample\tscalingFactor", "testA.bam\t1.1892071", "testB.bam\t0.8408964"])
-    unlink(outfile)
-    unlink(outfile2)
+def test_multiBamSummary_bedmode_smartlabels():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname1 = BAMA + fname
+        fname2 = BAMB + fname
+        args = f"BED-file --BED {BED} -b {fname1} {fname2} -o {outfile} --smartLabels".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        labels = resp['labels']
+        decoded_labels = [bytes(lab).decode('ascii').rstrip('\x00') for lab in labels]
+
+        assert decoded_labels == ['testA', 'testB']
+
+def test_multiBamSummary_bedmode_region():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile} --region 3R:500:1000".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[144.0, 144.0], [144.0, 144.0], [143.0, 143.0], [22.0, 22.0], [25.0, 25.0], [1.0, 1.0]]
+            )
+        )
+
+def test_multiBamSummary_bedmode_blacklist():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile} --blackListFileName {BLACKLIST}".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[1.0, 1.0], [59.0, 59.0], [59.0, 59.0], [6.0, 6.0], [58.0, 58.0], [16.0, 16.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+            )
+        )
+
+def test_multiBamSummary_bedmode_outcounts_sf():
+    exp_count = ROOT + "bedmode_counts.tsv"
+    exp_sf = ROOT + "bedmode_sf.txt"
+
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    _, osf = tempfile.mkstemp(suffix=".txt")
+    _, ocount = tempfile.mkstemp(suffix=".tsv")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile} --outRawCounts {ocount} --scalingFactors {osf}".split()
+        mbs.main(args)
+        compare_tsv(exp_count, ocount)
+        compare_tsv(exp_sf, osf)
+
+def test_multiBamSummary_bedmode_outcounts_sf2():
+    exp_count = ROOT + "bedmode_counts2.tsv"
+    exp_sf = ROOT + "bedmode_sf2.txt"
+
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    _, osf = tempfile.mkstemp(suffix=".txt")
+    _, ocount = tempfile.mkstemp(suffix=".tsv")
+    for fname in ['.bam', '.cram']:
+        fname1 = BAMA + fname
+        fname2 = BAMB + fname
+        args = f"BED-file --BED {BED} -b {fname1} {fname2} -o {outfile} --outRawCounts {ocount} --scalingFactors {osf}".split()
+        mbs.main(args)
+        compare_tsv(exp_count, ocount)
+        compare_tsv(exp_sf, osf)
+
+def test_multiBamSummary_bedmode_center_ext():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile} -e 40 --centerReads".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[1.0, 1.0], [144.0, 144.0], [144.0, 144.0], [6.0, 6.0], [143.0, 143.0], [22.0, 22.0], [25.0, 25.0], [1.0, 1.0], [0.0, 0.0]]
+            )
+        )
+
+def test_multiBamSummary_bedmode_center_ext2():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile} -e 80 --centerReads".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[1.0, 1.0], [144.0, 144.0], [144.0, 144.0], [7.0, 7.0], [143.0, 143.0], [23.0, 23.0], [22.0, 22.0], [3.0, 3.0], [0.0, 0.0]]
+            )
+        )
+
+def test_multiBamSummary_bedmode_center_ext3():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile} -e 150".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[3.0, 3.0], [144.0, 144.0], [144.0, 144.0], [16.0, 16.0], [144.0, 144.0], [35.0, 35.0], [41.0, 41.0], [16.0, 16.0], [0.0, 0.0]]
+            )
+        )
+
+def test_multiBamSummary_bedmode_center_ext4():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"BED-file --BED {BED} -b {fname} {fname} -o {outfile} --centerReads -e 150".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix,
+            np.array(
+                [[1.0, 1.0], [144.0, 144.0], [144.0, 144.0], [10.0, 10.0], [143.0, 143.0], [23.0, 23.0], [23.0, 23.0], [5.0, 5.0], [0.0, 0.0]]
+            )
+        )
+
+def test_multiBamSummary_gtf_customids():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"BED-file --BED {GTF2} -b {fname} {fname} -o {outfile} "
+            "--transcriptID mRNA --exonID CDS --transcript_id_designator ID"
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix, np.array([[144.0, 144.0], [143.0, 143.0]]))
+
+def test_multiBamSummary_gtf_customids_metagene():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"BED-file --BED {GTF2} -b {fname} {fname} -o {outfile} --metagene "
+            "--transcriptID mRNA --exonID CDS --transcript_id_designator ID"
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+
+        nt.assert_allclose(matrix, np.array([[25.0, 25.0], [31.0, 31.0]]))
+
+def test_multiBamSummary_bedmode_readfilters():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"BED-file --BED {BED2} -b {fname} {fname} -o {outfile} "
+            "--samFlagInclude 16 --samFlagExclude 1024 "
+            "--minFragmentLength 40 --maxFragmentLength 60 "
+            "--minMappingQuality 20"
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array([[36.0, 36.0], [36.0, 36.0]]))
+
+def test_multiBamSummary_bedmode_gtfmg():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"BED-file --BED {GTF} -b {fname} {fname} -o {outfile} "
+            "--metagene "
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array([[25.0, 25.0], [31.0, 31.0]]))
+
+def test_multiBamSummary_bedmode_bed12mg():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"BED-file --BED {BED12} -b {fname} {fname} -o {outfile} "
+            "--metagene "
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array([[25.0, 25.0], [31.0, 31.0]]))
+
+def test_multiBamSummary_binmode():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"bins --binSize 10 -b {fname} {fname} -o {outfile}"
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [7.0, 7.0], [10.0, 10.0], [17.0, 17.0], [21.0, 21.0], [21.0, 21.0], [20.0, 20.0], [17.0, 17.0], [17.0, 17.0], [12.0, 12.0], [8.0, 8.0], [7.0, 7.0], [8.0, 8.0], [8.0, 8.0], [7.0, 7.0], [5.0, 5.0], [6.0, 6.0], [6.0, 6.0], [5.0, 5.0], [4.0, 4.0], [5.0, 5.0], [4.0, 4.0], [3.0, 3.0], [4.0, 4.0], [6.0, 6.0], [8.0, 8.0], [8.0, 8.0], [10.0, 10.0], [12.0, 12.0], [13.0, 13.0], [13.0, 13.0], [12.0, 12.0], [11.0, 11.0], [10.0, 10.0], [9.0, 9.0], [7.0, 7.0], [6.0, 6.0], [5.0, 5.0], [5.0, 5.0], [5.0, 5.0], [6.0, 6.0], [6.0, 6.0], [5.0, 5.0], [9.0, 9.0], [10.0, 10.0], [10.0, 10.0], [14.0, 14.0], [14.0, 14.0], [14.0, 14.0], [11.0, 11.0], [8.0, 8.0], [10.0, 10.0], [5.0, 5.0], [6.0, 6.0], [8.0, 8.0], [8.0, 8.0], [11.0, 11.0], [9.0, 9.0], [15.0, 15.0], [14.0, 14.0], [12.0, 12.0], [13.0, 13.0], [12.0, 12.0], [13.0, 13.0], [6.0, 6.0], [6.0, 6.0], [6.0, 6.0], [4.0, 4.0], [3.0, 3.0], [1.0, 1.0], [3.0, 3.0], [5.0, 5.0], [15.0, 15.0], [22.0, 22.0], [23.0, 23.0], [26.0, 26.0], [25.0, 25.0], [26.0, 26.0], [18.0, 18.0], [11.0, 11.0], [9.0, 9.0], [6.0, 6.0], [6.0, 6.0], [3.0, 3.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode2():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"bins --binSize 18 -b {fname} {fname} -o {outfile}"
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [4.0, 4.0], [4.0, 4.0], [8.0, 8.0], [18.0, 18.0], [22.0, 22.0], [21.0, 21.0], [19.0, 19.0], [10.0, 10.0], [8.0, 8.0], [9.0, 9.0], [6.0, 6.0], [6.0, 6.0], [8.0, 8.0], [5.0, 5.0], [4.0, 4.0], [8.0, 8.0], [9.0, 9.0], [12.0, 12.0], [15.0, 15.0], [14.0, 14.0], [11.0, 11.0], [7.0, 7.0], [6.0, 6.0], [5.0, 5.0], [6.0, 6.0], [8.0, 8.0], [12.0, 12.0], [14.0, 14.0], [14.0, 14.0], [11.0, 11.0], [11.0, 11.0], [6.0, 6.0], [9.0, 9.0], [12.0, 12.0], [15.0, 15.0], [15.0, 15.0], [14.0, 14.0], [12.0, 12.0], [6.0, 6.0], [5.0, 5.0], [3.0, 3.0], [5.0, 5.0], [22.0, 22.0], [26.0, 26.0], [27.0, 27.0], [18.0, 18.0], [9.0, 9.0], [6.0, 6.0], [3.0, 3.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode3():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"bins --binSize 18 --distanceBetweenBins 3 -b {fname} {fname} -o {outfile}"
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [3.0, 3.0], [4.0, 4.0], [4.0, 4.0], [8.0, 8.0], [20.0, 20.0], [21.0, 21.0], [19.0, 19.0], [12.0, 12.0], [8.0, 8.0], [9.0, 9.0], [6.0, 6.0], [6.0, 6.0], [6.0, 6.0], [3.0, 3.0], [8.0, 8.0], [9.0, 9.0], [14.0, 14.0], [14.0, 14.0], [12.0, 12.0], [9.0, 9.0], [6.0, 6.0], [6.0, 6.0], [6.0, 6.0], [10.0, 10.0], [14.0, 14.0], [14.0, 14.0], [11.0, 11.0], [11.0, 11.0], [8.0, 8.0], [12.0, 12.0], [15.0, 15.0], [14.0, 14.0], [14.0, 14.0], [8.0, 8.0], [6.0, 6.0], [3.0, 3.0], [3.0, 3.0], [21.0, 21.0], [26.0, 26.0], [28.0, 28.0], [17.0, 17.0], [7.0, 7.0], [4.0, 4.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode_labels():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname1 = BAMA + fname
+        fname2 = BAMB + fname
+        args = f"bins --binSize 10 -b {fname1} {fname2} -o {outfile} --labels bam_part1 bam2".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        labels = resp['labels']
+        decoded_labels = [bytes(lab).decode('ascii').rstrip('\x00') for lab in labels]
+
+        assert decoded_labels == ['bam_part1', 'bam2']
+
+def test_multiBamSummary_binmode_smartlabels():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname1 = BAMA + fname
+        fname2 = BAMB + fname
+        args = f"bins --binSize 10 -b {fname1} {fname2} -o {outfile} --smartLabels".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        labels = resp['labels']
+        decoded_labels = [bytes(lab).decode('ascii').rstrip('\x00') for lab in labels]
+
+        assert decoded_labels == ['testA', 'testB']
+
+def test_multiBamSummary_binmode_region():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"bins --binSize 10 -b {fname} {fname} -o {outfile} --region 3R:500:1000 ".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[1.0, 1.0], [1.0, 1.0], [3.0, 3.0], [4.0, 4.0], [6.0, 6.0], [6.0, 6.0], [5.0, 5.0], [9.0, 9.0], [10.0, 10.0], [10.0, 10.0], [14.0, 14.0], [14.0, 14.0], [14.0, 14.0], [11.0, 11.0], [8.0, 8.0], [10.0, 10.0], [5.0, 5.0], [6.0, 6.0], [8.0, 8.0], [8.0, 8.0], [11.0, 11.0], [9.0, 9.0], [15.0, 15.0], [14.0, 14.0], [12.0, 12.0], [13.0, 13.0], [12.0, 12.0], [13.0, 13.0], [6.0, 6.0], [6.0, 6.0], [6.0, 6.0], [4.0, 4.0], [3.0, 3.0], [1.0, 1.0], [3.0, 3.0], [5.0, 5.0], [15.0, 15.0], [22.0, 22.0], [23.0, 23.0], [26.0, 26.0], [25.0, 25.0], [26.0, 26.0], [18.0, 18.0], [11.0, 11.0], [9.0, 9.0], [6.0, 6.0], [5.0, 5.0], [2.0, 2.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode_blacklist():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"bins --binSize 10 -b {fname} {fname} -o {outfile} --blackListFileName {BLACKLIST} ".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [7.0, 7.0], [10.0, 10.0], [17.0, 17.0], [21.0, 21.0], [21.0, 21.0], [20.0, 20.0], [17.0, 17.0], [17.0, 17.0], [12.0, 12.0], [8.0, 8.0], [7.0, 7.0], [8.0, 8.0], [8.0, 8.0], [7.0, 7.0], [5.0, 5.0], [6.0, 6.0], [6.0, 6.0], [5.0, 5.0], [4.0, 4.0], [5.0, 5.0], [4.0, 4.0], [3.0, 3.0], [4.0, 4.0], [6.0, 6.0], [8.0, 8.0], [8.0, 8.0], [10.0, 10.0], [12.0, 12.0], [13.0, 13.0], [13.0, 13.0], [11.0, 11.0], [8.0, 8.0], [6.0, 6.0], [4.0, 4.0], [2.0, 2.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode_outcounts_sf():
+    exp_count = ROOT + "binmode_counts.tsv"
+    exp_sf = ROOT + "binmode_sf.txt"
+
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    _, osf = tempfile.mkstemp(suffix=".txt")
+    _, ocount = tempfile.mkstemp(suffix=".tsv")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"bins --binSize 10 -b {fname} {fname} -o {outfile} --outRawCounts {ocount} --scalingFactors {osf}".split()
+        mbs.main(args)
+        compare_tsv(exp_count, ocount)
+        compare_tsv(exp_sf, osf)
+
+def test_multiBamSummary_binmode_outcounts_sf2():
+    exp_count = ROOT + "binmode_counts2.tsv"
+    exp_sf = ROOT + "binmode_sf2.txt"
+
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    _, osf = tempfile.mkstemp(suffix=".txt")
+    _, ocount = tempfile.mkstemp(suffix=".tsv")
+    for fname in ['.bam', '.cram']:
+        fname1 = BAMA + fname
+        fname2 = BAMB + fname
+        args = f"bins --binSize 10 -b {fname1} {fname2} -o {outfile} --outRawCounts {ocount} --scalingFactors {osf}".split()
+        mbs.main(args)
+        compare_tsv(exp_count, ocount)
+        compare_tsv(exp_sf, osf)
+
+def test_multiBamSummary_binmode_center_ext():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"bins --binSize 10 -b {fname} {fname} -o {outfile} --centerReads --extendReads 20 ".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [7.0, 7.0], [10.0, 10.0], [17.0, 17.0], [21.0, 21.0], [21.0, 21.0], [20.0, 20.0], [17.0, 17.0], [17.0, 17.0], [12.0, 12.0], [8.0, 8.0], [7.0, 7.0], [8.0, 8.0], [8.0, 8.0], [7.0, 7.0], [5.0, 5.0], [6.0, 6.0], [6.0, 6.0], [5.0, 5.0], [4.0, 4.0], [5.0, 5.0], [4.0, 4.0], [3.0, 3.0], [4.0, 4.0], [6.0, 6.0], [8.0, 8.0], [8.0, 8.0], [10.0, 10.0], [12.0, 12.0], [13.0, 13.0], [13.0, 13.0], [12.0, 12.0], [11.0, 11.0], [10.0, 10.0], [9.0, 9.0], [7.0, 7.0], [6.0, 6.0], [5.0, 5.0], [5.0, 5.0], [5.0, 5.0], [6.0, 6.0], [6.0, 6.0], [5.0, 5.0], [9.0, 9.0], [10.0, 10.0], [10.0, 10.0], [14.0, 14.0], [14.0, 14.0], [14.0, 14.0], [11.0, 11.0], [8.0, 8.0], [10.0, 10.0], [5.0, 5.0], [6.0, 6.0], [8.0, 8.0], [8.0, 8.0], [11.0, 11.0], [9.0, 9.0], [15.0, 15.0], [14.0, 14.0], [12.0, 12.0], [13.0, 13.0], [12.0, 12.0], [13.0, 13.0], [6.0, 6.0], [6.0, 6.0], [6.0, 6.0], [4.0, 4.0], [3.0, 3.0], [1.0, 1.0], [3.0, 3.0], [5.0, 5.0], [15.0, 15.0], [22.0, 22.0], [23.0, 23.0], [26.0, 26.0], [25.0, 25.0], [26.0, 26.0], [18.0, 18.0], [11.0, 11.0], [9.0, 9.0], [6.0, 6.0], [6.0, 6.0], [3.0, 3.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode_center_ext2():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"bins --binSize 10 -b {fname} {fname} -o {outfile} --centerReads --extendReads 80 ".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[0.0, 0.0], [0.0, 0.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [4.0, 4.0], [6.0, 6.0], [7.0, 7.0], [10.0, 10.0], [11.0, 11.0], [18.0, 18.0], [20.0, 20.0], [19.0, 19.0], [18.0, 18.0], [16.0, 16.0], [16.0, 16.0], [11.0, 11.0], [9.0, 9.0], [8.0, 8.0], [9.0, 9.0], [7.0, 7.0], [7.0, 7.0], [5.0, 5.0], [5.0, 5.0], [8.0, 8.0], [6.0, 6.0], [6.0, 6.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [7.0, 7.0], [8.0, 8.0], [10.0, 10.0], [10.0, 10.0], [11.0, 11.0], [11.0, 11.0], [9.0, 9.0], [10.0, 10.0], [10.0, 10.0], [11.0, 11.0], [10.0, 10.0], [8.0, 8.0], [8.0, 8.0], [8.0, 8.0], [6.0, 6.0], [5.0, 5.0], [7.0, 7.0], [7.0, 7.0], [7.0, 7.0], [6.0, 6.0], [9.0, 9.0], [11.0, 11.0], [11.0, 11.0], [12.0, 12.0], [12.0, 12.0], [12.0, 12.0], [9.0, 9.0], [9.0, 9.0], [9.0, 9.0], [7.0, 7.0], [6.0, 6.0], [5.0, 5.0], [9.0, 9.0], [10.0, 10.0], [11.0, 11.0], [13.0, 13.0], [15.0, 15.0], [16.0, 16.0], [12.0, 12.0], [11.0, 11.0], [7.0, 7.0], [5.0, 5.0], [3.0, 3.0], [2.0, 2.0], [3.0, 3.0], [1.0, 1.0], [12.0, 12.0], [16.0, 16.0], [20.0, 20.0], [25.0, 25.0], [26.0, 26.0], [28.0, 28.0], [18.0, 18.0], [15.0, 15.0], [12.0, 12.0], [8.0, 8.0], [7.0, 7.0], [5.0, 5.0], [4.0, 4.0], [3.0, 3.0], [2.0, 2.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode_center_ext3():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"bins --binSize 10 -b {fname} {fname} -o {outfile} --extendReads 150 ".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [5.0, 5.0], [7.0, 7.0], [9.0, 9.0], [11.0, 11.0], [11.0, 11.0], [12.0, 12.0], [13.0, 13.0], [14.0, 14.0], [15.0, 15.0], [18.0, 18.0], [19.0, 19.0], [26.0, 26.0], [30.0, 30.0], [30.0, 30.0], [30.0, 30.0], [30.0, 30.0], [31.0, 31.0], [30.0, 30.0], [31.0, 31.0], [29.0, 29.0], [29.0, 29.0], [29.0, 29.0], [29.0, 29.0], [29.0, 29.0], [31.0, 31.0], [29.0, 29.0], [25.0, 25.0], [21.0, 21.0], [17.0, 17.0], [17.0, 17.0], [17.0, 17.0], [18.0, 18.0], [18.0, 18.0], [18.0, 18.0], [17.0, 17.0], [18.0, 18.0], [21.0, 21.0], [23.0, 23.0], [24.0, 24.0], [23.0, 23.0], [22.0, 22.0], [24.0, 24.0], [23.0, 23.0], [24.0, 24.0], [26.0, 26.0], [25.0, 25.0], [25.0, 25.0], [24.0, 24.0], [23.0, 23.0], [23.0, 23.0], [22.0, 22.0], [23.0, 23.0], [25.0, 25.0], [22.0, 22.0], [23.0, 23.0], [23.0, 23.0], [23.0, 23.0], [20.0, 20.0], [20.0, 20.0], [21.0, 21.0], [22.0, 22.0], [22.0, 22.0], [22.0, 22.0], [22.0, 22.0], [24.0, 24.0], [24.0, 24.0], [28.0, 28.0], [26.0, 26.0], [21.0, 21.0], [22.0, 22.0], [27.0, 27.0], [31.0, 31.0], [31.0, 31.0], [32.0, 32.0], [33.0, 33.0], [32.0, 32.0], [31.0, 31.0], [31.0, 31.0], [33.0, 33.0], [34.0, 34.0], [31.0, 31.0], [37.0, 37.0], [32.0, 32.0], [34.0, 34.0], [34.0, 34.0], [34.0, 34.0], [27.0, 27.0], [23.0, 23.0], [21.0, 21.0], [20.0, 20.0], [19.0, 19.0], [17.0, 17.0], [16.0, 16.0], [15.0, 15.0], [14.0, 14.0], [12.0, 12.0], [10.0, 10.0], [5.0, 5.0], [4.0, 4.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode_center_ext4():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = f"bins --binSize 10 -b {fname} {fname} -o {outfile} --centerReads --extendReads 150 ".split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[0.0, 0.0], [0.0, 0.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [5.0, 5.0], [7.0, 7.0], [8.0, 8.0], [8.0, 8.0], [8.0, 8.0], [8.0, 8.0], [8.0, 8.0], [7.0, 7.0], [8.0, 8.0], [13.0, 13.0], [16.0, 16.0], [19.0, 19.0], [18.0, 18.0], [17.0, 17.0], [15.0, 15.0], [12.0, 12.0], [9.0, 9.0], [8.0, 8.0], [7.0, 7.0], [7.0, 7.0], [7.0, 7.0], [7.0, 7.0], [7.0, 7.0], [7.0, 7.0], [8.0, 8.0], [9.0, 9.0], [8.0, 8.0], [6.0, 6.0], [6.0, 6.0], [3.0, 3.0], [4.0, 4.0], [5.0, 5.0], [6.0, 6.0], [8.0, 8.0], [8.0, 8.0], [11.0, 11.0], [12.0, 12.0], [13.0, 13.0], [12.0, 12.0], [12.0, 12.0], [14.0, 14.0], [11.0, 11.0], [9.0, 9.0], [8.0, 8.0], [8.0, 8.0], [6.0, 6.0], [4.0, 4.0], [5.0, 5.0], [5.0, 5.0], [4.0, 4.0], [6.0, 6.0], [11.0, 11.0], [10.0, 10.0], [13.0, 13.0], [12.0, 12.0], [13.0, 13.0], [11.0, 11.0], [6.0, 6.0], [9.0, 9.0], [7.0, 7.0], [7.0, 7.0], [5.0, 5.0], [6.0, 6.0], [10.0, 10.0], [7.0, 7.0], [10.0, 10.0], [10.0, 10.0], [10.0, 10.0], [10.0, 10.0], [15.0, 15.0], [19.0, 19.0], [16.0, 16.0], [17.0, 17.0], [18.0, 18.0], [19.0, 19.0], [11.0, 11.0], [8.0, 8.0], [7.0, 7.0], [8.0, 8.0], [9.0, 9.0], [12.0, 12.0], [12.0, 12.0], [12.0, 12.0], [11.0, 11.0], [10.0, 10.0], [10.0, 10.0], [5.0, 5.0], [4.0, 4.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
+
+def test_multiBamSummary_binmode_readfilters():
+    _, outfile = tempfile.mkstemp(suffix=".npz")
+    for fname in ['.bam', '.cram']:
+        fname = BAM + fname
+        args = (
+            f"bins --binSize 5 -b {fname} {fname} -o {outfile} "
+            "--samFlagInclude 16 --samFlagExclude 1024 "
+            "--minFragmentLength 40 --maxFragmentLength 60 "
+            "--minMappingQuality 20"
+        ).split()
+        mbs.main(args)
+        resp = np.load(outfile)
+        matrix = resp['matrix']
+        nt.assert_allclose(matrix, np.array(
+            [[0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [4.0, 4.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [5.0, 5.0], [4.0, 4.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [3.0, 3.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [4.0, 4.0], [4.0, 4.0], [5.0, 5.0], [5.0, 5.0], [5.0, 5.0], [5.0, 5.0], [5.0, 5.0], [5.0, 5.0], [4.0, 4.0], [4.0, 4.0], [3.0, 3.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [2.0, 2.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [5.0, 5.0], [5.0, 5.0], [7.0, 7.0], [8.0, 8.0], [8.0, 8.0], [9.0, 9.0], [9.0, 9.0], [10.0, 10.0], [10.0, 10.0], [10.0, 10.0], [11.0, 11.0], [6.0, 6.0], [6.0, 6.0], [4.0, 4.0], [3.0, 3.0], [3.0, 3.0], [2.0, 2.0], [2.0, 2.0], [1.0, 1.0], [1.0, 1.0], [2.0, 2.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
+        ))
diff --git a/pydeeptools/deeptools/test/test_plotcorrelation.py b/pydeeptools/deeptools/test/test_plotcorrelation.py
index 6cfc7051d7..cc05ed7364 100644
--- a/pydeeptools/deeptools/test/test_plotcorrelation.py
+++ b/pydeeptools/deeptools/test/test_plotcorrelation.py
@@ -4,6 +4,7 @@
 from os import unlink
 from matplotlib.testing.compare import compare_images
 import tempfile
+import pytest
 
 ROOT = os.path.dirname(os.path.abspath(__file__)) + "/test_data/"
 COR_DATA_IN1 = ROOT + "multiBamSummary_result1.npz"
@@ -14,6 +15,9 @@
 COR_PLOT_GG_2 = ROOT + "plotCorrelation_result2_ggplot.png"
 
 
+@pytest.mark.filterwarnings(
+    "ignore:Attempting to set identical low and high xlims:UserWarning"
+)
 def test_correlation_plot_with_minimal_options():
     """
     Test minimal command line args for correlation plot
diff --git a/src/alignmentsieve.rs b/src/alignmentsieve.rs
index 2b69957d79..9631e2769b 100644
--- a/src/alignmentsieve.rs
+++ b/src/alignmentsieve.rs
@@ -4,6 +4,7 @@ use pyo3::prelude::*;
 use pyo3::types::PyList;
 use rust_htslib::bam::record::CigarString;
 use rust_htslib::bam::{self, Header, Read, Reader, Writer};
+use std::collections::HashMap;
 use std::fs::File;
 use std::io::{BufWriter, Write};
 use std::path::Path;
@@ -60,11 +61,15 @@ pub fn r_alignmentsieve(
     // Load blacklist regions if provided
     let blacklist_regions = if blacklist != "None" {
         let isbed = is_bed_or_gtf(blacklist);
-        let chrom_keys: Vec<&String> = chrom_names.iter().collect();
+        let chrom_bounds: HashMap<String, u32> = chrom_names
+            .iter()
+            .cloned()
+            .zip(chrom_sizes.iter().map(|&x| x as u32))
+            .collect();
         match isbed.as_str() {
             "gtf" => panic!("Error: Please provide a bed file for the blacklist."),
             "bed" => {
-                let (bls, _) = read_bedfile(&blacklist.to_string(), false, chrom_keys);
+                let (bls, _) = read_bedfile(&blacklist.to_string(), false, &chrom_bounds);
                 Some(bls)
             }
             _ => panic!("Error: Cannot determine filetype of blacklist file."),
diff --git a/src/bamcompare.rs b/src/bamcompare.rs
index 98afc61323..67cd738b72 100644
--- a/src/bamcompare.rs
+++ b/src/bamcompare.rs
@@ -74,7 +74,7 @@ pub fn r_bamcompare(
             "gtf" => panic!("Error: Please provide a bed file for the blacklist."),
             "bed" => {
                 let (bls, _) =
-                    read_bedfile(&blacklist.to_string(), false, chromsizes.keys().collect());
+                    read_bedfile(&blacklist.to_string(), false, &chromsizes);
                 blacklistregions = Some(bls);
             }
             _ => panic!("Error: Cannot determine filetype of blacklist file."),
@@ -138,7 +138,7 @@ pub fn r_bamcompare(
                     .par_iter()
                     .map(|i| {
                         bam_pileup(
-                            bamfile, &i, &binsize, &ispe, &ignorechr, alfilter, false, false, true, 0,
+                            bamfile, &i, &binsize, &binsize, &ispe, &ignorechr, alfilter, false, false, true, 0,
                         )
                     })
                     .reduce(
diff --git a/src/bamcoverage.rs b/src/bamcoverage.rs
index dbb8755f17..60016d09fe 100644
--- a/src/bamcoverage.rs
+++ b/src/bamcoverage.rs
@@ -132,7 +132,7 @@ pub fn r_bamcoverage(
             "gtf" => panic!("Error: Please provide a bed file for the blacklist."),
             "bed" => {
                 let (bls, _) =
-                    read_bedfile(&blacklist.to_string(), false, chromsizes.keys().collect());
+                    read_bedfile(&blacklist.to_string(), false, &chromsizes);
                 backlistregions = Some(bls);
             }
             _ => panic!("Error: Cannot determine filetype of blacklist file."),
@@ -171,7 +171,7 @@ pub fn r_bamcoverage(
             .par_iter()
             .map(|i| {
                 bam_pileup(
-                    bamifile, &i, &binsize, &ispe, &ignorechr, &filters, collapse, false, true, _smoothlength,
+                    bamifile, &i, &binsize, &binsize, &ispe, &ignorechr, &filters, collapse, false, true, _smoothlength,
                 )
             })
             .reduce(
diff --git a/src/calc.rs b/src/calc.rs
index 608df96949..0af033bd88 100644
--- a/src/calc.rs
+++ b/src/calc.rs
@@ -21,15 +21,15 @@ pub fn median(mut nvec: Vec<u32>) -> f32 {
 }
 
 pub fn mean_float(fvec: &[&f32]) -> f32 {
-    let mut sum = 0.0f32;
+    let mut sum = 0.0f64;
     let mut count = 0usize;
     for &&v in fvec {
         if v.is_finite() {
-            sum += v;
+            sum += v as f64;
             count += 1;
         }
     }
-    if count == 0 { 0.0 } else { sum / count as f32 }
+    if count == 0 { 0.0 } else { (sum / count as f64) as f32 }
 }
 
 pub fn median_float(fvec: &[&f32]) -> f32 {
diff --git a/src/computematrix.rs b/src/computematrix.rs
index 3e6602ca58..77db7174bc 100644
--- a/src/computematrix.rs
+++ b/src/computematrix.rs
@@ -4,6 +4,7 @@ use crate::filehandler::{
     bwintervals, chrombounds_from_bw, header_matrix, is_bed_or_gtf, read_bedfile, read_gtffile,
     write_matrix,
 };
+use crate::filtering::BlacklistIndex;
 use itertools::Itertools;
 use pyo3::prelude::*;
 use pyo3::types::PyList;
@@ -11,6 +12,7 @@ use rayon::ThreadPoolBuilder;
 use rayon::prelude::*;
 use std::collections::HashMap;
 use std::path::Path;
+use std::sync::Arc;
 
 #[pyfunction]
 pub fn r_computematrix(
@@ -35,6 +37,7 @@ pub fn r_computematrix(
     skipzeros: bool,       // skip regions with all zeros. Default is false.
     minthresh: f32,        // minimum threshold to keep a region. If not set it will equal 0.0
     maxthresh: f32,        // maximum threshold to keep a region. if not set it will equal 0.0
+    blacklist: &str,       // path to blacklist BED file, or "None"
     averagetypebins: &str, // operation to summarize values over bins. Default is mean.
     sortregions: &str, // either ascend, descend or keep. Default is keep (and ignores sortusing).
     sortusing: &str, // metric to sort on. Either mean median max min sum region_length. Default is mean.
@@ -124,6 +127,23 @@ pub fn r_computematrix(
         )
     }
 
+    // If there is a blacklist, read it and build an index.
+    let blacklist_index: Option<Arc<BlacklistIndex>> = if blacklist != "none" {
+        let isbed = is_bed_or_gtf(blacklist);
+        match isbed.as_str() {
+            "gtf" => panic!("Error: Please provide a bed file for the blacklist."),
+            "bed" => {
+                let (bls, _) =
+                    read_bedfile(&blacklist.to_string(), false, &chromsizes);
+                let idx = BlacklistIndex::from_regions(&bls);
+                Some(Arc::new(idx))
+            }
+            _ => panic!("Error: Cannot determine filetype of blacklist file."),
+        }
+    } else {
+        None
+    };
+
     // Get the 'basepaths' of the bed files to use as labels later on
     let mut regionlabels: Vec<String> = Vec::new();
     for bed in region_files.iter() {
@@ -215,23 +235,27 @@ pub fn r_computematrix(
 
             match ftype.as_str() {
                 "gtf" => read_gtffile(r, &gtfparse, chromsizes.keys().collect()),
-                "bed" => read_bedfile(r, metagene, chromsizes.keys().collect()),
+                "bed" => read_bedfile(r, metagene, &chromsizes),
                 _ => panic!("Only .bed and .gtf files are allowed (as determined by the number of columns). File = {}", ftype),
             }
         })
         .collect();
 
     // Merge regions and region sizes
-    for (reg, regsize) in region_data.into_iter() {
+    // Track which group (region file) each region belongs to, by index.
+    let mut group_of_region: Vec<usize> = Vec::with_capacity(cursor);
+    for (group_idx, (reg, regsize)) in region_data.into_iter().enumerate() {
         let n = reg.len();
         regions.extend(reg);
         regionsizes.insert(regsize.0.clone(), regsize.1);
 
         if n > 0 {
             regionslices.push((cursor, cursor + n - 1));
+            group_of_region.extend(std::iter::repeat(group_idx).take(n));
             cursor += n;
         }
     }
+
     // Define slop regions, which contain the actual 'bins' to query the bigwig files.
     let slopregions = pool.install(|| {
         regions
@@ -245,7 +269,15 @@ pub fn r_computematrix(
     let matrix: Vec<Vec<f32>> = pool.install(|| {
         bw_files
             .par_iter()
-            .map(|i| bwintervals(&i, &regions, &slopregions, &scale_regions))
+            .map(|i| {
+                bwintervals(
+                    &i,
+                    &regions,
+                    &slopregions,
+                    &scale_regions,
+                    blacklist_index.as_deref(),
+                )
+            })
             .reduce(
                 || vec![vec![]; regions.len()],
                 |mut acc, vec_of_vecs| {
@@ -261,10 +293,9 @@ pub fn r_computematrix(
         sortusing,
         sort_using_samples,
         regions,
-        regionslices,
+        group_of_region,
         matrix,
         scale_regions,
-        regionsizes,
         ofile,
         outfilenamematrix,
         outfilesortedregions,
@@ -294,24 +325,86 @@ fn slop_region(
     region.get_anchor_bins(scale_regions, chromend)
 }
 
-#[allow(unused_mut)]
-#[allow(unused_assignments)]
+fn should_skip_row(row: &[f32], scale_regions: &Scalingregions) -> bool {
+    if scale_regions.skipzero && row.iter().all(|&x| x == 0.0) {
+        return true;
+    }
+    if scale_regions.minthresh != 0.0
+        && !row.iter().any(|&x| x.is_nan())
+        && row.iter().any(|&x| x <= scale_regions.minthresh)
+    {
+        return true;
+    }
+    if scale_regions.maxthresh != 0.0
+        && !row.iter().any(|&x| x.is_nan())
+        && row.iter().any(|&x| x >= scale_regions.maxthresh)
+    {
+        return true;
+    }
+    false
+}
+
+fn recompute_regionsizes(
+    group_of_region: &[usize],
+    scale_regions: &Scalingregions,
+) -> (HashMap<String, u32>, Vec<(usize, usize)>) {
+    let mut filtered_regionsizes: HashMap<String, u32> = HashMap::new();
+    for label in &scale_regions.regionlabels {
+        filtered_regionsizes.insert(label.clone(), 0);
+    }
+    for &group_idx in group_of_region {
+        *filtered_regionsizes
+            .get_mut(&scale_regions.regionlabels[group_idx])
+            .unwrap() += 1;
+    }
+
+    // Build filtered regionslices in label order, matching the sorting logic expectations.
+    let mut slices: Vec<(usize, usize)> = Vec::new();
+    let mut cursor = 0usize;
+    for label in &scale_regions.regionlabels {
+        let count = *filtered_regionsizes.get(label).unwrap() as usize;
+        if count > 0 {
+            slices.push((cursor, cursor + count - 1));
+            cursor += count;
+        }
+    }
+
+    (filtered_regionsizes, slices)
+}
+
 fn matrix_dump(
     sortregions: &str,
     sortusing: &str,
     sort_using_samples: Vec<u32>,
     regions: Vec<Region>,
-    regionslices: Vec<(usize, usize)>,
+    group_of_region: Vec<usize>,
     matrix: Vec<Vec<f32>>,
     scale_regions: Scalingregions,
-    regionsizes: HashMap<String, u32>,
     ofile: &str,
     outfilenamematrix: Option<String>,
     outfilesortedregions: Option<String>,
     verbose: bool,
 ) {
-    // Takes a pre-computed matrix, resorts it if requested, and writes it to file.
-    // Resort the matrix, if this is requested.
+    // Filter rows first (before sorting/header generation) so group_boundaries are correct.
+    let keep_indices: Vec<usize> = (0..matrix.len())
+        .filter(|&i| !should_skip_row(&matrix[i], &scale_regions))
+        .collect();
+
+    if verbose {
+        println!(
+            "Filtering: {} regions -> {} regions",
+            regions.len(),
+            keep_indices.len()
+        );
+    }
+
+    let filtered_matrix: Vec<Vec<f32>> = keep_indices.iter().map(|&i| matrix[i].clone()).collect();
+    let filtered_regions: Vec<Region> = keep_indices.iter().map(|&i| regions[i].clone()).collect();
+    let filtered_group_of_region: Vec<usize> =
+        keep_indices.iter().map(|&i| group_of_region[i]).collect();
+    let (filtered_regionsizes, filtered_regionslices) =
+        recompute_regionsizes(&filtered_group_of_region, &scale_regions);
+
     if sortregions != "keep" {
         if verbose {
             println!(
@@ -319,12 +412,10 @@ fn matrix_dump(
                 sortregions, sortusing
             );
         }
-        // If sortusingsamples is set, we need a vector to subset the columns of interest
         let mut cols_of_interest: Vec<usize> = Vec::new();
         if !sort_using_samples.is_empty() {
             let cols_per_sample = scale_regions.cols_expected / scale_regions.bwfiles;
             for sample_ix in sort_using_samples.iter() {
-                // Note that sort_using_samples is assumed to be 1-index. Hence we need to subtract 1.
                 let start = (sample_ix - 1) * cols_per_sample as u32;
                 let end = start + cols_per_sample as u32;
                 cols_of_interest.extend(start as usize..end as usize);
@@ -333,21 +424,21 @@ fn matrix_dump(
         if verbose {
             println!(
                 "regionslices: {} slices for {} regions",
-                regionslices.len(),
-                regions.len()
+                filtered_regionslices.len(),
+                filtered_regions.len()
             );
         }
-        let mut sortedix: Vec<usize>;
+        let sortedix: Vec<usize>;
         if sortregions == "no" {
             if verbose && (sortusing != "mean" || !sort_using_samples.is_empty()) {
                 println!(
                     "sortRegions is 'no': sorting by genomic coordinates (chrom, start, end). sortUsing/sortUsingSamples are ignored."
                 );
             }
-            sortedix = regionslices
+            sortedix = filtered_regionslices
                 .iter()
                 .flat_map(|(start, end)| {
-                    let rslice = &regions[*start..*end + 1];
+                    let rslice = &filtered_regions[*start..*end + 1];
                     rslice
                         .iter()
                         .enumerate()
@@ -369,10 +460,10 @@ fn matrix_dump(
                     sort_using_samples
                 );
             }
-            sortedix = regionslices
+            sortedix = filtered_regionslices
                 .iter()
                 .flat_map(|(start, end)| {
-                    let rslice = &regions[*start..*end+1];
+                    let rslice = &filtered_regions[*start..*end+1];
                     let tix = rslice
                         .iter()
                         .enumerate()
@@ -392,10 +483,10 @@ fn matrix_dump(
                 })
                 .collect();
         } else {
-            sortedix = regionslices
+            sortedix = filtered_regionslices
                 .iter()
                 .flat_map(|(start, end)| {
-                    let rslice = &matrix[*start..*end+1];
+                    let rslice = &filtered_matrix[*start..*end+1];
                     let tix = rslice
                         .iter()
                         .enumerate()
@@ -405,22 +496,34 @@ fn matrix_dump(
                             } else {
                                 cols_of_interest
                                     .iter()
-                                    .filter_map(|&index| vals.get(index))  // `vec.get(index)` returns Option<&T>
+                                    .filter_map(|&index| vals.get(index))
                                     .collect()
                             };
-                            let metric = match sortusing {
-                                "mean" => mean_float(&subset),
-                                "median" => median_float(&subset),
-                                "max" => max_float(&subset),
-                                "min" => min_float(&subset),
-                                "sum" => sum_float(&subset),
-                                _ => panic!("Sortusing should be either mean, median, max, min, sum or region_length. Not {}", sortusing),
+                            let all_missing = subset.iter().all(|v| !v.is_finite());
+                            let metric = if all_missing {
+                                f32::NAN
+                            } else {
+                                match sortusing {
+                                    "mean" => mean_float(&subset),
+                                    "median" => median_float(&subset),
+                                    "max" => max_float(&subset),
+                                    "min" => min_float(&subset),
+                                    "sum" => sum_float(&subset),
+                                    _ => panic!("Sortusing should be either mean, median, max, min, sum or region_length. Not {}", sortusing),
+                                }
                             };
                             (ix + *start, metric)
                         })
                         .collect::<Vec<_>>()
                         .iter()
-                        .sorted_by(|ix, metric| ix.1.partial_cmp(&metric.1).unwrap())
+                        .sorted_by(|a, b| match (a.1.is_nan(), b.1.is_nan()) {
+                            (true, true) => std::cmp::Ordering::Equal,
+                            // NaN metrics (all-missing rows) sort last in ascending order,
+                            // matching numpy's argsort behavior for nan-containing arrays.
+                            (true, false) => std::cmp::Ordering::Greater,
+                            (false, true) => std::cmp::Ordering::Less,
+                            (false, false) => a.1.partial_cmp(&b.1).unwrap(),
+                        })
                         .map(|(ix, _)| *ix)
                         .collect::<Vec<usize>>();
                     match sortregions {
@@ -431,79 +534,88 @@ fn matrix_dump(
                 })
                 .collect();
         }
-        // assert sorted ix length == matrix length == regions length
         assert_eq!(
             sortedix.len(),
-            matrix.len(),
+            filtered_matrix.len(),
             "Length of sorted indices does not match matrix length: {} != {}",
             sortedix.len(),
-            matrix.len()
+            filtered_matrix.len()
         );
         assert_eq!(
             sortedix.len(),
-            regions.len(),
+            filtered_regions.len(),
             "Length of sorted indices does not match regions length: {} ! = {}",
             sortedix.len(),
-            regions.len()
+            filtered_regions.len()
         );
 
-        // Reorder matrix & regions
-        let sortedmatrix: Vec<Vec<f32>> = sortedix.iter().map(|ix| matrix[*ix].clone()).collect();
-        let sortedregions: Vec<Region> =
-            sortedix.into_iter().map(|ix| regions[ix].clone()).collect();
+        let sortedmatrix: Vec<Vec<f32>> = sortedix
+            .iter()
+            .map(|ix| filtered_matrix[*ix].clone())
+            .collect();
+        let sortedregions: Vec<Region> = sortedix
+            .into_iter()
+            .map(|ix| filtered_regions[ix].clone())
+            .collect();
         write_matrix(
-            header_matrix(&scale_regions, &regionsizes, sortregions, sortusing),
-            sortedmatrix.clone(),
+            header_matrix(
+                &scale_regions,
+                &filtered_regionsizes,
+                sortregions,
+                sortusing,
+            ),
+            &sortedmatrix,
             ofile,
-            sortedregions.clone(),
+            &sortedregions,
             &scale_regions,
         );
 
-        // outFileNameMatrix - write raw matrix tab file
         if let Some(ref matrix_file) = outfilenamematrix {
             crate::filehandler::write_matrix_values(
                 matrix_file,
                 &sortedmatrix,
                 &scale_regions,
-                &regionsizes,
+                &filtered_regionsizes,
             );
         }
 
-        // outFileSortedRegions - write sorted BED file
         if let Some(ref bed_file) = outfilesortedregions {
             crate::filehandler::write_sorted_regions_bed(
                 bed_file,
                 &sortedregions,
                 &scale_regions,
-                &regionsizes,
+                &filtered_regionsizes,
             );
         }
     } else {
         write_matrix(
-            header_matrix(&scale_regions, &regionsizes, sortregions, sortusing),
-            matrix.clone(),
+            header_matrix(
+                &scale_regions,
+                &filtered_regionsizes,
+                sortregions,
+                sortusing,
+            ),
+            &filtered_matrix,
             ofile,
-            regions.clone(),
+            &filtered_regions,
             &scale_regions,
         );
 
-        // outFileNameMatrix - write raw matrix tab file
         if let Some(ref matrix_file) = outfilenamematrix {
             crate::filehandler::write_matrix_values(
                 matrix_file,
-                &matrix,
+                &filtered_matrix,
                 &scale_regions,
-                &regionsizes,
+                &filtered_regionsizes,
             );
         }
 
-        // outFileSortedRegions - write regions BED file
         if let Some(ref bed_file) = outfilesortedregions {
             crate::filehandler::write_sorted_regions_bed(
                 bed_file,
-                &regions,
+                &filtered_regions,
                 &scale_regions,
-                &regionsizes,
+                &filtered_regionsizes,
             );
         }
     }
diff --git a/src/covcalc.rs b/src/covcalc.rs
index 4f1a385b70..8c9a4794fb 100644
--- a/src/covcalc.rs
+++ b/src/covcalc.rs
@@ -1,6 +1,5 @@
 use crate::filtering::Alignmentfilters;
 use core::panic;
-use ndarray::Array1;
 use rust_htslib::bam::ext::BamRecordExtensions;
 use rust_htslib::bam::{IndexedReader, Read};
 use std::cmp::{max, min};
@@ -51,47 +50,42 @@ pub fn parse_regions(region: &str, bam_ifile: Vec<&str>) -> (Vec<Region>, HashMa
         !validchroms.is_empty(),
         "No chromosomes found that are present in all bam files. Did you mix references ?"
     );
-    // Read header from first bam file
-    let bam = IndexedReader::from_path(bam_ifile[0]).unwrap();
-    let header = bam.header().clone();
-    let mut chromregions: Vec<Region> = Vec::new();
-    let mut chromsizes = HashMap::new();
-    if region == "None" {
-        // if regions is empty, we default to all chromosomes, full length
+    let mut chromsizes: HashMap<String, u32> = HashMap::new();
+    for bam in bam_ifile.iter() {
+        let bam = IndexedReader::from_path(bam).unwrap();
+        let header = bam.header().clone();
         for tid in 0..header.target_count() {
             let chromname = String::from_utf8(header.tid2name(tid).to_vec())
                 .expect("Invalid UTF-8 in chromosome name");
-            let chromlen = header
-                .target_len(tid)
-                .expect("Error retrieving length for chromosome");
-            // If chromname is not in validchroms, skip it.
             if !validchroms.contains(&chromname) {
                 continue;
             }
+            let chromlen = header
+                .target_len(tid)
+                .expect("Error retrieving length for chromosome") as u32;
+            chromsizes
+                .entry(chromname)
+                .and_modify(|len| *len = (*len).min(chromlen))
+                .or_insert(chromlen);
+        }
+    }
+    let mut chromregions: Vec<Region> = Vec::new();
+    if region == "None" {
+        // if regions is empty, we default to all chromosomes, full length
+        for (chromname, chromlen) in chromsizes.iter() {
             let _reg = Region {
                 chrom: chromname.clone(),
                 start: Revalue::U(0),
-                end: Revalue::U(chromlen as u32),
+                end: Revalue::U(*chromlen),
                 score: String::from("."),
                 strand: String::from("."),
                 name: format!("{}:{}-{}", chromname, 0, chromlen),
-                regionlength: chromlen as u32,
+                regionlength: *chromlen,
             };
             chromregions.push(_reg);
-            chromsizes.insert(chromname.to_string(), chromlen as u32);
         }
     } else {
-        // populate chromsizes
-        for tid in 0..header.target_count() {
-            let chromname = String::from_utf8(header.tid2name(tid).to_vec())
-                .expect("Invalid UTF-8 in chromosome name");
-            let chromlen = header
-                .target_len(tid)
-                .expect("Error retrieving length for chromosome");
-            if validchroms.contains(&chromname) {
-                chromsizes.insert(chromname, chromlen as u32);
-            }
-        }
+        // chromsizes is already fully populated above.
         // Either the region is just a chromosome, or it is a 'true region' i.e. chr:start:end
         // first test if the region is a chromosome alone
         let parts = region.split(":").collect::<Vec<&str>>();
@@ -158,6 +152,38 @@ pub fn parse_regions(region: &str, bam_ifile: Vec<&str>) -> (Vec<Region>, HashMa
     return (chromregions, chromsizes);
 }
 
+pub fn filter_regions_by_supregion(regions: Vec<Region>, supregion: &str) -> Vec<Region> {
+    if supregion == "None" {
+        return regions;
+    }
+    let parts: Vec<&str> = supregion.split(":").collect();
+    let chromname = parts[0];
+    let bounds: Option<(u32, u32)> = if parts.len() >= 3 {
+        Some((
+            parts[1]
+                .parse::<u32>()
+                .expect("Error reading supplied start position."),
+            parts[2]
+                .parse::<u32>()
+                .expect("Error reading supplied end position."),
+        ))
+    } else {
+        None
+    };
+    regions
+        .into_iter()
+        .filter(|r| {
+            if r.chrom != chromname {
+                return false;
+            }
+            match bounds {
+                Some((start, end)) => r.get_startu() < end && r.get_endu() > start,
+                None => true,
+            }
+        })
+        .collect()
+}
+
 /// Main workhorse for bamCoverage and bamCompare
 /// Calculates coverage either per bp (bs = 1) or over bins (bs > 1)
 #[allow(unused_assignments)]
@@ -167,6 +193,7 @@ pub fn bam_pileup<'a>(
     bam_ifile: &str,            // the bam file to consider.
     regionvec: &'a Vec<Region>, // Vector with regions to calculate coverage from.
     provbs: &u32, // Provisional bin size, in case we have gene mode later on this gets omitted.
+    binstep: &u32, // Distance from the start of one bin to the start of the next (bins mode only).
     ispe: &bool,  // Wether or not the bam file is paired end or single end.
     ignorechr: &Vec<String>, // chromosomes to ignore for normalization calculation.
     filters: &Alignmentfilters, // a struct with filtering settings.
@@ -227,8 +254,16 @@ pub fn bam_pileup<'a>(
                 regstruct.get_endu(),
             );
         }
-        bam.fetch((region.0.as_str(), region.1, region.2))
-            .expect(&format!("Error fetching region: {:?}", region));
+        if gene_mode && filters.manipulate {
+            let pad = filters.extendreadslen.max(1);
+            let fetch_start = region.1.saturating_sub(pad);
+            let fetch_end = region.2 + pad;
+            bam.fetch((region.0.as_str(), fetch_start, fetch_end))
+                .expect(&format!("Error fetching region: {:?}", region));
+        } else {
+            bam.fetch((region.0.as_str(), region.1, region.2))
+                .expect(&format!("Error fetching region: {:?}", region));
+        }
         let mut counts: Vec<u32>;
         let mut startstr: String = region.1.to_string();
         let mut endstr: String = region.2.to_string();
@@ -240,10 +275,8 @@ pub fn bam_pileup<'a>(
                     counts = vec![0u32; 1];
                     for record in bam.records() {
                         let mut record = record.expect("Error parsing record.");
-                        if filters.filter {
-                            if filters.filter_record(&record, &region.0.as_str()) {
-                                continue;
-                            }
+                        if filters.filter_record(&record, &region.0.as_str()) {
+                            continue;
                         }
                         if !ignorechr.contains(&region.0) {
                             if record.is_unmapped() {
@@ -265,6 +298,17 @@ pub fn bam_pileup<'a>(
                                 }
                             }
                         }
+                        if filters.manipulate {
+                            let manipulated_blockpos = filters.manipulate_record(&record);
+                            let overlaps = manipulated_blockpos
+                                .map(|positions| {
+                                    positions.iter().any(|&x| x >= region.1 && x < region.2)
+                                })
+                                .unwrap_or(false);
+                            if !overlaps {
+                                continue;
+                            }
+                        }
                         counts[0] += 1;
                     }
                 }
@@ -288,17 +332,26 @@ pub fn bam_pileup<'a>(
                         .map(|(&s, &e)| (s, e))
                         .collect();
                     for exon in exons {
-                        bam.fetch((regstruct.chrom.as_str(), exon.0, exon.1))
-                            .expect(&format!(
-                                "Error fetching region: {}:{},{}",
-                                regstruct.chrom, exon.0, exon.1
-                            ));
+                        if filters.manipulate {
+                            let pad = filters.extendreadslen.max(1);
+                            let fetch_start = exon.0.saturating_sub(pad);
+                            let fetch_end = exon.1 + pad;
+                            bam.fetch((regstruct.chrom.as_str(), fetch_start, fetch_end))
+                                .expect(&format!(
+                                    "Error fetching region: {}:{},{}",
+                                    regstruct.chrom, exon.0, exon.1
+                                ));
+                        } else {
+                            bam.fetch((regstruct.chrom.as_str(), exon.0, exon.1))
+                                .expect(&format!(
+                                    "Error fetching region: {}:{},{}",
+                                    regstruct.chrom, exon.0, exon.1
+                                ));
+                        }
                         for record in bam.records() {
                             let mut record = record.expect("Error parsing record.");
-                            if filters.filter {
-                                if filters.filter_record(&record, region.0.as_str()) {
-                                    continue;
-                                }
+                            if filters.filter_record(&record, region.0.as_str()) {
+                                continue;
                             }
                             if !ignorechr.contains(&region.0) {
                                 if record.is_unmapped() {
@@ -320,6 +373,17 @@ pub fn bam_pileup<'a>(
                                     }
                                 }
                             }
+                            if filters.manipulate {
+                                let manipulated_blockpos = filters.manipulate_record(&record);
+                                let overlaps = manipulated_blockpos
+                                    .map(|positions| {
+                                        positions.iter().any(|&x| x >= exon.0 && x < exon.1)
+                                    })
+                                    .unwrap_or(false);
+                                if !overlaps {
+                                    continue;
+                                }
+                            }
                             counts[0] += 1;
                         }
                     }
@@ -331,16 +395,35 @@ pub fn bam_pileup<'a>(
             }
         } else {
             // populate the bg vector with 0 counts over all bins
-            counts = vec![0u32; (region.2 - region.1).div_ceil(*binsize) as usize];
+            let step: u32 = *binstep;
+            let nbins: u32 = if step == *binsize {
+                (region.2 - region.1).div_ceil(*binsize)
+            } else {
+                let span = region.2 - region.1;
+                if span >= *binsize {
+                    (span - *binsize) / step + 1
+                } else {
+                    0
+                }
+            };
+            counts = vec![0u32; nbins as usize];
             let mut bin_indices: Vec<usize> = Vec::with_capacity(512);
 
+            let bin_index_for = |pos: u32| -> Option<usize> {
+                let offset = pos - region.1;
+                let ix = offset / step;
+                if offset - ix * step < *binsize {
+                    Some(ix as usize)
+                } else {
+                    None
+                }
+            };
+
             for record in bam.records() {
                 let mut record = record.expect("Error parsing record.");
 
-                if filters.filter {
-                    if filters.filter_record(&record, region.0.as_str()) {
-                        continue;
-                    }
+                if filters.filter_record(&record, region.0.as_str()) {
+                    continue;
                 }
                 bin_indices.clear();
 
@@ -350,9 +433,10 @@ pub fn bam_pileup<'a>(
                         continue;
                     }
                     for &x in &manipulated_blockpos.unwrap() {
-                        let ix = ((x - region.1) / binsize) as usize;
-                        if ix < counts.len() {
-                            bin_indices.push(ix);
+                        if let Some(ix) = bin_index_for(x) {
+                            if ix < counts.len() {
+                                bin_indices.push(ix);
+                            }
                         }
                     }
                 } else {
@@ -363,9 +447,10 @@ pub fn bam_pileup<'a>(
                             && (x[0] as u32) <= region.2
                         {
                             for pos in x[0] as u32..x[1] as u32 {
-                                let ix = ((pos - region.1) / binsize) as usize;
-                                if ix < counts.len() {
-                                    bin_indices.push(ix);
+                                if let Some(ix) = bin_index_for(pos) {
+                                    if ix < counts.len() {
+                                        bin_indices.push(ix);
+                                    }
                                 }
                             }
                         }
@@ -458,7 +543,7 @@ pub fn bam_pileup<'a>(
 
                 for (ix, count) in smoothed.into_iter().skip(1).enumerate() {
                     bin = (ix + 1) as u32; // offset of 1 due to skip(1)
-                    start = (bin * binsize) + region.1;
+                    start = (bin * (*binstep)) + region.1;
                     end = min(start + binsize, region.2);
                     if count != lcov {
                         push_line(&region.0, lstart, lend, lcov);
@@ -474,7 +559,7 @@ pub fn bam_pileup<'a>(
                 push_line(&region.0, start, end, smoothed[0]);
                 for (ix, count) in smoothed.into_iter().skip(1).enumerate() {
                     let bin = (ix + 1) as u32;
-                    start = (bin * binsize) + region.1;
+                    start = (bin * (*binstep)) + region.1;
                     end = min(start + binsize, region.2);
                     push_line(&region.0, start, end, count);
                 }
@@ -652,7 +737,9 @@ impl Region {
                 scale_regions.regionbodylength != 0,
                 "scale-regions mode, but regionbodylength is 0."
             );
-            if self.regionlength - (scale_regions.unscaled5prime + scale_regions.unscaled3prime)
+            if self
+                .regionlength
+                .saturating_sub(scale_regions.unscaled5prime + scale_regions.unscaled3prime)
                 < scale_regions.binsize
             {
                 println!(
@@ -686,14 +773,23 @@ impl Region {
                             if binix + scale_regions.binsize as i64 <= 0 {
                                 // Entirely upstream of chromosome start -> invalid
                                 leftbins.push(Bin::Conbin(0, 0));
+                            } else if binix < 0 && binix + scale_regions.binsize as i64 > 0 {
+                                // starting point is negative, but bin end is positive, keep valid but truncate
+                                let end =
+                                    min((binix + scale_regions.binsize as i64) as u32, chromend);
+                                let start = max(binix, 0) as u32;
+                                let pad = scale_regions.binsize - (end - start);
+                                leftbins.push(Bin::PaddedConbin(start, end, pad));
                             } else if binix >= 0 && binix as u32 > chromend {
                                 // Entirely downstream of chromosome end -> invalid
                                 leftbins.push(Bin::Conbin(0, 0));
                             } else if (binix + scale_regions.binsize as i64) as u32 > chromend {
                                 // bin is partially downstream of chromosome end -> keep valid but truncate
-                                let end = min(binix as u32 + scale_regions.binsize, chromend);
+                                let end =
+                                    min((binix + scale_regions.binsize as i64) as u32, chromend);
                                 let start = max(binix, 0) as u32;
-                                leftbins.push(Bin::Conbin(start, end));
+                                let pad = scale_regions.binsize - (end - start);
+                                leftbins.push(Bin::PaddedConbin(start, end, pad));
                             } else {
                                 // bin is valid -> keep as is
                                 let start = max(binix, 0) as u32;
@@ -718,7 +814,8 @@ impl Region {
                                 rightbins.push(Bin::Conbin(0, 0));
                             } else if (binix as u32 + scale_regions.binsize) > upper_bound {
                                 // bin straddles the valid boundary -> keep only the valid portion
-                                rightbins.push(Bin::Conbin(binix as u32, upper_bound));
+                                let pad = scale_regions.binsize - (upper_bound - binix as u32);
+                                rightbins.push(Bin::PaddedConbin(binix as u32, upper_bound, pad));
                             } else {
                                 // fully within bounds
                                 rightbins.push(Bin::Conbin(
@@ -832,7 +929,8 @@ impl Region {
                             } else if (binix + scale_regions.binsize as i64) as u32 > chromend {
                                 // bin straddles chromend -> truncate
                                 let end = min(binix as u32 + scale_regions.binsize, chromend);
-                                rightbins.push(Bin::Conbin(binix as u32, end));
+                                let pad = scale_regions.binsize - (end - binix as u32);
+                                rightbins.push(Bin::PaddedConbin(binix as u32, end, pad));
                             } else {
                                 rightbins.push(Bin::Conbin(
                                     binix as u32,
@@ -855,10 +953,9 @@ impl Region {
                                 leftbins.push(Bin::Conbin(0, 0));
                             } else if binix < lower_bound {
                                 // bin straddles the lower boundary -> keep only the valid portion
-                                leftbins.push(Bin::Conbin(
-                                    lower_bound as u32,
-                                    (binix + scale_regions.binsize as i64) as u32,
-                                ));
+                                let end = (binix + scale_regions.binsize as i64) as u32;
+                                let pad = scale_regions.binsize - (end - lower_bound as u32);
+                                leftbins.push(Bin::PaddedConbin(lower_bound as u32, end, pad));
                             } else {
                                 // fully within bounds
                                 leftbins.push(Bin::Conbin(
@@ -1018,29 +1115,21 @@ impl Region {
                         }
                         let bodystart = *start + scale_regions.unscaled5prime;
                         let bodyend = *end - scale_regions.unscaled3prime;
-
-                        // Get the bins over the body length. These need to be scaled, so similar to deeptools < 4, linspace is used.
                         let neededbins =
                             (scale_regions.regionbodylength / scale_regions.binsize) as usize;
-                        // There's multiple options here:
-                        // transcriptlength >= regionbodylength -> linspace
-                        // regionbodylength / binsize > transcriptlength <= regionbodylength -> 1 >= binsize > binsize.
-                        // transcriptlength <= regionbodylength / binsize -> index repetitions with binsize of one.
-                        let scaledbinsize = min(
-                            max((bodyend - bodystart) / neededbins as u32, 1),
-                            scale_regions.binsize,
-                        );
-                        innerbins.extend(
-                            Array1::linspace(
-                                bodystart as f32,
-                                (bodyend - scaledbinsize) as f32,
-                                neededbins,
-                            )
-                            .mapv(|x| x.floor() as u32)
-                            .map(|x| Bin::Conbin(*x, *x + scaledbinsize))
-                            .into_iter()
-                            .collect::<Vec<_>>(),
-                        );
+                        let bodylength = (bodyend - bodystart) as f64;
+                        let step = bodylength / neededbins as f64;
+
+                        let mut edges: Vec<u32> = (0..neededbins)
+                            .map(|i| (bodystart as f64 + i as f64 * step).floor() as u32)
+                            .collect();
+                        edges.push(bodyend); // include exact endpoint
+
+                        for i in 0..neededbins {
+                            let s = edges[i];
+                            let e = std::cmp::max(edges[i + 1], s + 1);
+                            innerbins.push(Bin::Conbin(s, e));
+                        }
                         // Combine the vectors and return
                         let mut combined_bins = Vec::new();
                         if scale_regions.unscaled5prime > 0 {
@@ -1060,10 +1149,10 @@ impl Region {
                             .collect();
                         let mut un5bins: Vec<Bin> = Vec::new();
                         let mut un3bins: Vec<Bin> = Vec::new();
+
                         if scale_regions.unscaled5prime > 0 {
                             let mut walked_bps: u32 = 0;
                             let mut lastanchor: u32 = start[0];
-
                             while walked_bps < scale_regions.unscaled5prime {
                                 let (bin, retanch) = refpoint_exonwalker(
                                     &exons,
@@ -1081,7 +1170,6 @@ impl Region {
                         if scale_regions.unscaled3prime > 0 {
                             let mut walked_bps: u32 = 0;
                             let mut lastanchor: u32 = *end.last().unwrap();
-
                             while walked_bps < scale_regions.unscaled3prime {
                                 let (bin, retanch) = refpoint_exonwalker(
                                     &exons,
@@ -1098,79 +1186,28 @@ impl Region {
                         }
                         un3bins.reverse();
 
-                        let bodystart: u32;
-                        let bodyend: u32;
-                        if scale_regions.unscaled5prime > 0 {
-                            bodystart = un5bins.last().unwrap().get_end() - 1;
-                        } else {
-                            bodystart = *start.first().unwrap();
-                        }
-                        if scale_regions.unscaled3prime > 0 {
-                            bodyend = un3bins.first().unwrap().get_start();
-                        } else {
-                            bodyend = *end.last().unwrap();
-                        }
-                        let truebodylength = self.regionlength
-                            - scale_regions.unscaled5prime
-                            - scale_regions.unscaled3prime;
                         let neededbins =
                             (scale_regions.regionbodylength / scale_regions.binsize) as usize;
-                        let scaledbinsize = min(
-                            max(truebodylength / neededbins as u32, 1),
-                            scale_regions.binsize,
+                        let body_exons = chop_exons(
+                            &exons,
+                            scale_regions.unscaled5prime,
+                            scale_regions.unscaled3prime,
                         );
-                        // Things are a bit tricky now, as we can do a linspace over the region, but we don't have a notion of the exons.
-                        // I think easiest is to just pull a hashmap over the entire region, get linspace from hashmap to vec, and be done with it.
-                        // technically we fetch a bunch of regions we don't need, but this operation is not too expensive.
-
-                        let mut binmap: HashMap<u32, Bin> = HashMap::new();
-                        let mut lastanchor: u32 = bodystart;
-
-                        for ix in 0..((truebodylength / scaledbinsize) + 1) {
-                            let (bin, anchor) = refpoint_exonwalker(
-                                &exons,
-                                lastanchor,
-                                scaledbinsize,
-                                chromend,
-                                scale_regions.nan_after_end,
-                                true,
-                            );
-                            lastanchor = anchor;
-                            match bin {
-                                Bin::Conbin(start, end) => {
-                                    if end > bodyend {
-                                        binmap.insert(ix, Bin::Conbin(start, bodyend));
-                                    } else {
-                                        binmap.insert(ix, Bin::Conbin(start, end));
-                                    }
-                                }
-                                Bin::Catbin(bins) => {
-                                    if bins.last().unwrap().1 > bodyend {
-                                        let mut newbins: Vec<(u32, u32)> = Vec::new();
-                                        for (s, e) in bins.iter() {
-                                            if *e > bodyend {
-                                                newbins.push((*s, bodyend));
-                                            } else {
-                                                newbins.push((*s, *e));
-                                            }
-                                        }
-                                        binmap.insert(ix, Bin::Catbin(newbins));
-                                    } else {
-                                        binmap.insert(ix, Bin::Catbin(bins));
-                                    }
-                                }
-                            }
-                        }
+                        let truebodylength: u32 = body_exons.iter().map(|(s, e)| e - s).sum();
 
-                        let innerbins = Array1::linspace(
-                            0 as f32,
-                            ((truebodylength) / scaledbinsize) as f32,
-                            neededbins,
-                        )
-                        .mapv(|x| x.floor() as u32)
-                        .map(|x| binmap.get(&x).unwrap().clone())
-                        .into_iter()
-                        .collect::<Vec<Bin>>();
+                        let step = truebodylength as f64 / neededbins as f64;
+                        let mut edges: Vec<u32> = (0..neededbins)
+                            .map(|i| (i as f64 * step).floor() as u32)
+                            .collect();
+                        edges.push(truebodylength);
+
+                        let innerbins: Vec<Bin> = (0..neededbins)
+                            .map(|i| {
+                                let rel_start = edges[i];
+                                let rel_end = std::cmp::max(edges[i + 1], rel_start + 1);
+                                exon_relative_bin(&body_exons, rel_start, rel_end)
+                            })
+                            .collect();
 
                         // Combine the vectors and return
                         let mut combined_bins = Vec::new();
@@ -1221,28 +1258,21 @@ impl Region {
                         let bodystart = *start + scale_regions.unscaled3prime;
                         let bodyend = *end - scale_regions.unscaled5prime;
 
-                        // Get the bins over the body length. These need to be scaled, so similar to deeptools < 4, linspace is used.
                         let neededbins =
                             (scale_regions.regionbodylength / scale_regions.binsize) as usize;
-                        // There's multiple options here:
-                        // transcriptlength >= regionbodylength -> linspace
-                        // regionbodylength / binsize > transcriptlength <= regionbodylength -> 1 >= binsize > binsize.
-                        // transcriptlength <= regionbodylength / binsize -> index repetitions with binsize of one.
-                        let scaledbinsize = min(
-                            max((bodyend - bodystart) / neededbins as u32, 1),
-                            scale_regions.binsize,
-                        );
-                        innerbins.extend(
-                            Array1::linspace(
-                                bodystart as f32,
-                                (bodyend - scaledbinsize) as f32,
-                                neededbins,
-                            )
-                            .mapv(|x| x.floor() as u32)
-                            .map(|x| Bin::Conbin(*x, *x + scaledbinsize))
-                            .into_iter()
-                            .collect::<Vec<_>>(),
-                        );
+                        let bodylength = (bodyend - bodystart) as f64;
+                        let step = bodylength / neededbins as f64;
+
+                        let mut edges: Vec<u32> = (0..neededbins)
+                            .map(|i| (bodystart as f64 + i as f64 * step).floor() as u32)
+                            .collect();
+                        edges.push(bodyend);
+
+                        for i in 0..neededbins {
+                            let s = edges[i];
+                            let e = std::cmp::max(edges[i + 1], s + 1);
+                            innerbins.push(Bin::Conbin(s, e));
+                        }
                         // Combine the vectors and return
                         let mut combined_bins = Vec::new();
                         if scale_regions.unscaled3prime > 0 {
@@ -1262,10 +1292,10 @@ impl Region {
                             .collect();
                         let mut un5bins: Vec<Bin> = Vec::new();
                         let mut un3bins: Vec<Bin> = Vec::new();
+
                         if scale_regions.unscaled5prime > 0 {
                             let mut walked_bps: u32 = 0;
                             let mut lastanchor: u32 = *end.last().unwrap();
-
                             while walked_bps < scale_regions.unscaled5prime {
                                 let (bin, retanch) = refpoint_exonwalker(
                                     &exons,
@@ -1284,7 +1314,6 @@ impl Region {
                         if scale_regions.unscaled3prime > 0 {
                             let mut walked_bps: u32 = 0;
                             let mut lastanchor: u32 = start[0];
-
                             while walked_bps < scale_regions.unscaled3prime {
                                 let (bin, retanch) = refpoint_exonwalker(
                                     &exons,
@@ -1300,79 +1329,28 @@ impl Region {
                             }
                         }
 
-                        let bodystart: u32;
-                        let bodyend: u32;
-                        if scale_regions.unscaled5prime > 0 {
-                            bodyend = un5bins.first().unwrap().get_start();
-                        } else {
-                            bodyend = *start.first().unwrap();
-                        }
-                        if scale_regions.unscaled3prime > 0 {
-                            bodystart = un3bins.last().unwrap().get_end() - 1;
-                        } else {
-                            bodystart = *end.last().unwrap();
-                        }
-                        let truebodylength = self.regionlength
-                            - scale_regions.unscaled5prime
-                            - scale_regions.unscaled3prime;
                         let neededbins =
                             (scale_regions.regionbodylength / scale_regions.binsize) as usize;
-                        let scaledbinsize = min(
-                            max(truebodylength / neededbins as u32, 1),
-                            scale_regions.binsize,
+                        let body_exons = chop_exons(
+                            &exons,
+                            scale_regions.unscaled3prime,
+                            scale_regions.unscaled5prime,
                         );
-                        // Things are a bit tricky now, as we can do a linspace over the region, but we don't have a notion of the exons.
-                        // I think easiest is to just pull a hashmap over the entire region, get linspace from hashmap to vec, and be done with it.
-                        // technically we fetch a bunch of regions we don't need, but this operation is not too expensive.
-
-                        let mut binmap: HashMap<u32, Bin> = HashMap::new();
-                        let mut lastanchor: u32 = bodystart;
-
-                        for ix in 0..((truebodylength / scaledbinsize) + 1) {
-                            let (bin, anchor) = refpoint_exonwalker(
-                                &exons,
-                                lastanchor,
-                                scaledbinsize,
-                                chromend,
-                                scale_regions.nan_after_end,
-                                true,
-                            );
-                            lastanchor = anchor;
-                            match bin {
-                                Bin::Conbin(start, end) => {
-                                    if end > bodyend {
-                                        binmap.insert(ix, Bin::Conbin(start, bodyend));
-                                    } else {
-                                        binmap.insert(ix, Bin::Conbin(start, end));
-                                    }
-                                }
-                                Bin::Catbin(bins) => {
-                                    if bins.last().unwrap().1 > bodyend {
-                                        let mut newbins: Vec<(u32, u32)> = Vec::new();
-                                        for (s, e) in bins.iter() {
-                                            if *e > bodyend {
-                                                newbins.push((*s, bodyend));
-                                            } else {
-                                                newbins.push((*s, *e));
-                                            }
-                                        }
-                                        binmap.insert(ix, Bin::Catbin(newbins));
-                                    } else {
-                                        binmap.insert(ix, Bin::Catbin(bins));
-                                    }
-                                }
-                            }
-                        }
+                        let truebodylength: u32 = body_exons.iter().map(|(s, e)| e - s).sum();
 
-                        let innerbins = Array1::linspace(
-                            0 as f32,
-                            ((truebodylength) / scaledbinsize) as f32,
-                            neededbins,
-                        )
-                        .mapv(|x| x.floor() as u32)
-                        .map(|x| binmap.get(&x).unwrap().clone())
-                        .into_iter()
-                        .collect::<Vec<Bin>>();
+                        let step = truebodylength as f64 / neededbins as f64;
+                        let mut edges: Vec<u32> = (0..neededbins)
+                            .map(|i| (i as f64 * step).floor() as u32)
+                            .collect();
+                        edges.push(truebodylength);
+
+                        let innerbins: Vec<Bin> = (0..neededbins)
+                            .map(|i| {
+                                let rel_start = edges[i];
+                                let rel_end = std::cmp::max(edges[i + 1], rel_start + 1);
+                                exon_relative_bin(&body_exons, rel_start, rel_end)
+                            })
+                            .collect();
 
                         // Combine the vectors and return
                         let mut combined_bins = Vec::new();
@@ -1420,7 +1398,10 @@ fn refpoint_exonwalker(
             Some(i) => {
                 // anchor sits in an exon. Check if anchor + binsize is also in same exon.
                 if anchor + binsize > chromend {
-                    return (Bin::Conbin(0, 0), chromend);
+                    // Bin extends past chromosome end. Clamp to [anchor, chromend).
+                    let valid = chromend.saturating_sub(anchor);
+                    let pad = binsize - valid.min(binsize);
+                    return (Bin::PaddedConbin(anchor, chromend, pad), chromend);
                 }
                 if anchor + binsize <= exons[i].1 {
                     (Bin::Conbin(anchor, anchor + binsize), anchor + binsize)
@@ -1433,6 +1414,7 @@ fn refpoint_exonwalker(
                     let mut remainingbin: u32 = binsize - (exons[i].1 - anchor);
                     let mut lastix: usize = i;
                     let mut lastanchor: u32 = exons[i].1;
+                    let mut pad: u32 = 0;
 
                     while remainingbin != 0 {
                         if lastix + 1 < exons.len() {
@@ -1459,7 +1441,7 @@ fn refpoint_exonwalker(
                             // No next exon available. Remainder can just be genomic.
                             // The last entry here can be changed to include the last part.
                             if nan_after_end {
-                                start_end_vec.push((0, 0));
+                                pad += remainingbin;
                             } else {
                                 let last = start_end_vec.last_mut().unwrap();
                                 assert_eq!(
@@ -1468,6 +1450,7 @@ fn refpoint_exonwalker(
                                 );
                                 // Check we don't fall of the chromosome.
                                 if lastanchor + remainingbin > chromend {
+                                    pad += (lastanchor + remainingbin) - chromend;
                                     last.1 = chromend;
                                     lastanchor = chromend;
                                 } else {
@@ -1481,7 +1464,13 @@ fn refpoint_exonwalker(
                     // We now have a Vec of start - end, we can construct a CatBin.
                     // Note that CatBins are (absstart, absstop, ((intstart1, intstart2), ...))
                     // This seems weird, but makes sure we need to slice the bigwig file only once per bin.
-                    if start_end_vec.len() == 1 {
+                    if pad > 0 {
+                        if start_end_vec.len() == 1 {
+                            (Bin::PaddedConbin(anchor, lastanchor, pad), lastanchor)
+                        } else {
+                            (Bin::PaddedCatbin(start_end_vec, pad), lastanchor)
+                        }
+                    } else if start_end_vec.len() == 1 {
                         (Bin::Conbin(anchor, lastanchor), lastanchor)
                     } else {
                         (Bin::Catbin(start_end_vec), lastanchor)
@@ -1491,7 +1480,9 @@ fn refpoint_exonwalker(
             None => {
                 // our anchor doesn't sit in exons. We just return the anchor + binsize as Bin
                 if anchor + binsize > chromend {
-                    (Bin::Conbin(0, 0), chromend)
+                    let valid = chromend.saturating_sub(anchor);
+                    let pad = binsize - valid.min(binsize);
+                    (Bin::PaddedConbin(anchor, chromend, pad), chromend)
                 } else {
                     (Bin::Conbin(anchor, anchor + binsize), anchor + binsize)
                 }
@@ -1503,8 +1494,9 @@ fn refpoint_exonwalker(
             Some(i) => {
                 // Run a check to see if binsize > anchor.
                 if anchor < binsize {
-                    // We are at the start of the chromosome. We need to return a Conbin.
-                    return (Bin::Conbin(0, 0), 0);
+                    // We are at the start of the chromosome. Clamp upstream bin to [0, anchor).
+                    let pad = binsize - anchor.min(binsize);
+                    return (Bin::PaddedConbin(0, anchor, pad), 0);
                 }
                 // anchor sits in an exon. Check if anchor - binsize is also in same exon.
                 if anchor - binsize >= exons[i].0 {
@@ -1518,6 +1510,7 @@ fn refpoint_exonwalker(
                     let mut remainingbin: u32 = binsize - (anchor - exons[i].0);
                     let mut lastix: usize = i;
                     let mut lastanchor: u32 = exons[i].0;
+                    let mut pad: u32 = 0;
 
                     while remainingbin != 0 {
                         if lastix >= 1 {
@@ -1541,10 +1534,8 @@ fn refpoint_exonwalker(
                                 lastanchor = exons[lastix].0;
                             }
                         } else {
-                            // No previous exon available. Remainder can just be genomic.
-                            // The last entry here can be changed to include the last part.
                             if nan_after_end {
-                                start_end_vec.push((0, 0));
+                                pad += remainingbin;
                             } else {
                                 let last = start_end_vec.last_mut().unwrap();
                                 assert_eq!(
@@ -1553,6 +1544,7 @@ fn refpoint_exonwalker(
                                 );
                                 // Check we don't go in the negative.
                                 if lastanchor < remainingbin {
+                                    pad += remainingbin - lastanchor;
                                     last.0 = 0;
                                     lastanchor = 0;
                                 } else {
@@ -1566,7 +1558,14 @@ fn refpoint_exonwalker(
                     // We now have a Vec of start - end, we can construct a CatBin.
                     // Note that CatBins are (absstart, absstop, ((intstart1, intstart2), ...))
                     // This seems weird, but makes sure we need to slice the bigwig file only once per bin.
-                    if start_end_vec.len() == 1 {
+                    if pad > 0 {
+                        if start_end_vec.len() == 1 {
+                            (Bin::PaddedConbin(lastanchor, anchor, pad), lastanchor)
+                        } else {
+                            start_end_vec.reverse();
+                            (Bin::PaddedCatbin(start_end_vec, pad), lastanchor)
+                        }
+                    } else if start_end_vec.len() == 1 {
                         (Bin::Conbin(lastanchor, anchor), lastanchor)
                     } else {
                         start_end_vec.reverse();
@@ -1577,7 +1576,8 @@ fn refpoint_exonwalker(
             None => {
                 // our anchor doesn't sit in exons. We just return the anchor - binsize as Bin
                 if anchor < binsize {
-                    (Bin::Conbin(0, 0), 0)
+                    let pad = binsize - anchor.min(binsize);
+                    (Bin::PaddedConbin(0, anchor, pad), 0)
                 } else {
                     (Bin::Conbin(anchor - binsize, anchor), anchor - binsize)
                 }
@@ -1619,6 +1619,64 @@ pub fn region_divider(regs: &Vec<Region>) -> Vec<Vec<Region>> {
     blocks
 }
 
+fn chop_exons(exons: &Vec<(u32, u32)>, mut left: u32, mut right: u32) -> Vec<(u32, u32)> {
+    let mut ex: Vec<(u32, u32)> = exons.clone();
+
+    while !ex.is_empty() && left > 0 {
+        let (s, e) = ex[0];
+        let width = e - s;
+        if width <= left {
+            ex.remove(0);
+            left -= width;
+        } else {
+            ex[0] = (s + left, e);
+            left = 0;
+        }
+    }
+
+    while !ex.is_empty() && right > 0 {
+        let (s, e) = *ex.last().unwrap();
+        let width = e - s;
+        if width <= right {
+            ex.pop();
+            right -= width;
+        } else {
+            let n = ex.len();
+            ex[n - 1] = (s, e - right);
+            right = 0;
+        }
+    }
+
+    ex
+}
+
+fn exon_relative_bin(body_exons: &Vec<(u32, u32)>, rel_start: u32, rel_end: u32) -> Bin {
+    let mut segs: Vec<(u32, u32)> = Vec::new();
+    let mut cum: u32 = 0;
+
+    for &(es, ee) in body_exons.iter() {
+        let exon_len = ee - es;
+        let next_cum = cum + exon_len;
+
+        let seg_rel_start = rel_start.max(cum);
+        let seg_rel_end = rel_end.min(next_cum);
+        if seg_rel_start < seg_rel_end {
+            segs.push((es + (seg_rel_start - cum), es + (seg_rel_end - cum)));
+        }
+
+        cum = next_cum;
+        if cum >= rel_end {
+            break;
+        }
+    }
+
+    if segs.len() == 1 {
+        Bin::Conbin(segs[0].0, segs[0].1)
+    } else {
+        Bin::Catbin(segs)
+    }
+}
+
 #[derive(Debug)]
 #[allow(dead_code)]
 pub struct Scalingregions {
@@ -1720,19 +1778,26 @@ impl fmt::Display for Revalue {
 pub enum Bin {
     Conbin(u32, u32),
     Catbin(Vec<(u32, u32)>),
+    PaddedConbin(u32, u32, u32),
+    PaddedCatbin(Vec<(u32, u32)>, u32),
 }
 
+#[allow(dead_code)]
 impl Bin {
     pub fn get_start(&self) -> u32 {
         match self {
             Bin::Conbin(start, _) => *start,
+            Bin::PaddedConbin(start, _, _) => *start,
             Bin::Catbin(starts) => starts.first().unwrap().0,
+            Bin::PaddedCatbin(starts, _) => starts.first().unwrap().0,
         }
     }
     pub fn get_end(&self) -> u32 {
         match self {
             Bin::Conbin(_, end) => *end,
+            Bin::PaddedConbin(_, end, _) => *end,
             Bin::Catbin(ends) => ends.last().unwrap().1,
+            Bin::PaddedCatbin(ends, _) => ends.last().unwrap().1,
         }
     }
 }
diff --git a/src/filehandler.rs b/src/filehandler.rs
index 027201cc1d..113fee9a1b 100644
--- a/src/filehandler.rs
+++ b/src/filehandler.rs
@@ -92,6 +92,8 @@ pub fn read_gtffile(
         let mut txn_hash: HashMap<String, Vec<(u32, u32)>> = HashMap::new();
         let mut txn_strand: HashMap<String, String> = HashMap::new();
         let mut txn_chrom: HashMap<String, String> = HashMap::new();
+        // Store transcript-level coordinates as fallback when no exon entries exist.
+        let mut txn_transcript: HashMap<String, (u32, u32)> = HashMap::new();
 
         for line in gtffile.lines() {
             let line = line.unwrap();
@@ -100,42 +102,78 @@ pub fn read_gtffile(
                 continue;
             }
             let fields: Vec<&str> = line.split('\t').collect();
-            if fields[2].to_string() == gtfparse.exonid {
-                let start: u32 = fields[3].parse().unwrap();
-                let end: u32 = fields[4].parse().unwrap();
-                let txnid = fields[8]
-                    .split(';')
-                    .find(|x| x.trim().starts_with(gtfparse.txniddesignator.as_str()))
-                    .and_then(|x| x.split('"').nth(1))
-                    .map(|s| s.to_string())
-                    .unwrap();
-                if !txnids.contains(&txnid) {
-                    txnids.push(txnid.clone());
+            let feature = fields[2].to_string();
+            let mut start: u32 = fields[3].parse().unwrap();
+            if start >= 1 {
+                start -= 1;
+            }
+            let end: u32 = fields[4].parse().unwrap();
+            let txnid: Option<String> = fields[8]
+                .split(';')
+                .find(|x| x.trim().starts_with(gtfparse.txniddesignator.as_str()))
+                .and_then(|x| x.split('"').nth(1))
+                .map(|s| s.to_string());
+
+            if feature == gtfparse.exonid {
+                let tid = txnid.unwrap();
+                if !txnids.contains(&tid) {
+                    txnids.push(tid.clone());
                 }
 
-                let txnentry = txn_hash.entry(txnid.clone()).or_insert(Vec::new());
-                // Just to verify all exons are on the same strand.
-                if txn_strand.contains_key(&txnid) {
-                    assert_eq!(txn_strand.get(&txnid).unwrap(), fields[6]);
+                let txnentry = txn_hash.entry(tid.clone()).or_insert(Vec::new());
+                if txn_strand.contains_key(&tid) {
+                    assert_eq!(txn_strand.get(&tid).unwrap(), fields[6]);
                 } else {
-                    txn_strand.insert(txnid.clone(), fields[6].to_string());
+                    txn_strand.insert(tid.clone(), fields[6].to_string());
                 }
-                // Same for chromosome
-                if txn_chrom.contains_key(&txnid) {
-                    assert_eq!(txn_chrom.get(&txnid).unwrap(), fields[0]);
+                if txn_chrom.contains_key(&tid) {
+                    assert_eq!(txn_chrom.get(&tid).unwrap(), fields[0]);
                 } else {
-                    txn_chrom.insert(txnid, fields[0].to_string());
+                    txn_chrom.insert(tid.clone(), fields[0].to_string());
                 }
                 txnentry.push((start, end));
+            } else if feature == gtfparse.txnid {
+                // Store transcript-level coordinates as fallback.
+                if let Some(tid) = txnid {
+                    if !txn_strand.contains_key(&tid) {
+                        txn_strand.insert(tid.clone(), fields[6].to_string());
+                    }
+                    if !txn_chrom.contains_key(&tid) {
+                        txn_chrom.insert(tid.clone(), fields[0].to_string());
+                    }
+                    txn_transcript.insert(tid, (start, end));
+                }
+            }
+        }
+
+        // Also pull in transcript IDs that have no exon entries.
+        for tid in txn_transcript.keys() {
+            if !txnids.contains(tid) {
+                txnids.push(tid.clone());
             }
         }
 
         for txnid in txnids.into_iter() {
-            let txnentry = txn_hash.get_mut(&txnid).unwrap();
-            let length: u32 = txnentry.iter().map(|(s, e)| e - s).sum();
-            txnentry.sort_by(|a, b| a.0.cmp(&b.0));
-            let (starts, ends): (Vec<u32>, Vec<u32>) =
-                txnentry.iter().map(|(s, e)| (*s, *e)).unzip();
+            let has_exons = txn_hash.contains_key(&txnid);
+            let has_transcript = txn_transcript.contains_key(&txnid);
+
+            // Only keep entries that have a 'transcript' feature line.
+            // This mirrors Python behavior: the transcript must exist in the
+            // interval tree for exons to be returned by findOverlaps().
+            if has_exons && !has_transcript {
+                continue;
+            }
+
+            let (starts, ends) = if has_exons {
+                let txnentry = txn_hash.get_mut(&txnid).unwrap();
+                txnentry.sort_by(|a, b| a.0.cmp(&b.0));
+                txnentry.iter().map(|(s, e)| (*s, *e)).unzip()
+            } else {
+                // No exons, fall back to transcript-level coordinates.
+                let (s, e) = txn_transcript.get(&txnid).unwrap();
+                (vec![*s], vec![*e])
+            };
+            let length: u32 = starts.iter().zip(ends.iter()).map(|(s, e)| e - s).sum();
             let chrom = txn_chrom.get(&txnid).unwrap().to_string();
 
             if !chroms.contains(&&chrom.to_string()) {
@@ -145,13 +183,13 @@ pub fn read_gtffile(
                 );
             } else {
                 regions.push(Region {
-                    chrom: txn_chrom.get(&txnid).unwrap().to_string(), //chrom
-                    start: Revalue::V(starts),                         //start
-                    end: Revalue::V(ends),                             //end
-                    score: ".".to_string(),                            //score
-                    strand: txn_strand.get(&txnid).unwrap().to_string(), // strand
+                    chrom,
+                    start: Revalue::V(starts),
+                    end: Revalue::V(ends),
+                    score: ".".to_string(),
+                    strand: txn_strand.get(&txnid).unwrap().to_string(),
                     name: txnid.to_string(),
-                    regionlength: length, // regionlength
+                    regionlength: length,
                 });
                 entries += 1;
             }
@@ -167,7 +205,10 @@ pub fn read_gtffile(
 
             let fields: Vec<&str> = line.split('\t').collect();
             if fields[2].to_string() == gtfparse.txnid {
-                let start: u32 = fields[3].parse().unwrap();
+                let mut start: u32 = fields[3].parse().unwrap();
+                if start >= 1 {
+                    start -= 1;
+                }
                 let end: u32 = fields[4].parse().unwrap();
                 let mut entryname = fields[8]
                     .split(';')
@@ -215,7 +256,7 @@ pub fn read_gtffile(
 pub fn read_bedfile(
     bed_file: &String,
     metagene: bool,
-    chroms: Vec<&String>,
+    chroms: &HashMap<String, u32>,
 ) -> (Vec<Region>, (String, u32)) {
     // read a provided bed_file into a vec of Region
     // Additional return is the filename and the number of entries (for sorting later on if needed).
@@ -241,13 +282,26 @@ pub fn read_bedfile(
                 let mut entryname = format!("{}:{}-{}", fields[0], fields[1], fields[2]);
                 // Only check for valid chroms, if chroms vec is not empty.
 
-                if !chroms.contains(&&chrom.to_string()) {
+                let chromlen = match chroms.get(chrom) {
+                    Some(len) => *len,
+                    None => {
+                        println!(
+                            "Warning, region {} not found in at least one of the bigwig/bam files. Skipping {}.",
+                            chrom, entryname
+                        );
+                        continue;
+                    }
+                };
+                let start: u32 = fields[1].parse().unwrap();
+                let mut end: u32 = fields[2].parse().unwrap();
+                if start >= chromlen {
                     println!(
-                        "Warning, region {} not found in at least one of the bigwig/bam files. Skipping {}.",
-                        chrom, entryname
+                        "Warning, region {} lies entirely beyond the end of {} ({}bp). Skipping.",
+                        entryname, chrom, chromlen
                     );
                     continue;
                 }
+                end = end.min(chromlen);
                 if names.contains_key(&entryname) {
                     let count = names.get_mut(&entryname).unwrap();
                     *count += 1;
@@ -255,8 +309,6 @@ pub fn read_bedfile(
                 } else {
                     names.insert(entryname.clone(), 0);
                 }
-                let start = fields[1].parse().unwrap();
-                let end = fields[2].parse().unwrap();
                 regions.push(Region {
                     chrom: fields[0].to_string(), //chrom
                     start: Revalue::U(start),     //start
@@ -274,15 +326,26 @@ pub fn read_bedfile(
                 }
                 let chrom = fields[0];
                 let mut entryname = fields[3].to_string();
-                if !chroms.contains(&&chrom.to_string()) {
+                let chromlen = match chroms.get(chrom) {
+                    Some(len) => *len,
+                    None => {
+                        println!(
+                            "Warning, region {} not found in at least one of the bigwig/bam files. Skipping {}.",
+                            chrom, entryname
+                        );
+                        continue;
+                    }
+                };
+                let start: u32 = fields[1].parse().unwrap();
+                let mut end: u32 = fields[2].parse().unwrap();
+                if start >= chromlen {
                     println!(
-                        "Warning, region {} not found in at least one of the bigwig/bam files. Skipping {}.",
-                        chrom, entryname
+                        "Warning, region {} lies entirely beyond the end of {} ({}bp). Skipping.",
+                        entryname, chrom, chromlen
                     );
                     continue;
                 }
-                let start = fields[1].parse().unwrap();
-                let end = fields[2].parse().unwrap();
+                end = end.min(chromlen);
                 if names.contains_key(&entryname) {
                     let count = names.get_mut(&entryname).unwrap();
                     *count += 1;
@@ -304,10 +367,21 @@ pub fn read_bedfile(
             12 => {
                 let chrom = fields[0];
                 let mut entryname = fields[3].to_string();
-                if !chroms.contains(&&chrom.to_string()) {
+                let chromlen = match chroms.get(chrom) {
+                    Some(len) => *len,
+                    None => {
+                        println!(
+                            "Warning, region {} not found in at least one of the bigwig/bam files. Skipping {}.",
+                            chrom, entryname
+                        );
+                        continue;
+                    }
+                };
+                let feat_start: u32 = fields[1].parse().unwrap();
+                if feat_start >= chromlen {
                     println!(
-                        "Warning, region {} not found in at least one of the bigwig/bam files. Skipping {}.",
-                        chrom, entryname
+                        "Warning, region {} lies entirely beyond the end of {} ({}bp). Skipping.",
+                        entryname, chrom, chromlen
                     );
                     continue;
                 }
@@ -319,25 +393,33 @@ pub fn read_bedfile(
                     names.insert(entryname.clone(), 0);
                 }
                 if metagene {
-                    let start: u32 = fields[1].parse().unwrap();
+                    let start: u32 = feat_start;
                     let blocksizes: Vec<u32> = fields[10]
                         .split(',')
                         .filter(|x| !x.is_empty())
                         .map(|x| x.parse().unwrap())
                         .collect();
-                    let length: u32 = blocksizes.iter().sum();
                     let blockstarts: Vec<u32> = fields[11]
                         .split(',')
                         .filter(|x| !x.is_empty())
                         .map(|x| x.parse::<u32>().unwrap() + start)
                         .collect();
 
-                    let (starts, ends) = blocksizes
+                    let (starts, ends): (Vec<u32>, Vec<u32>) = blocksizes
                         .into_iter()
                         .zip(blockstarts.into_iter())
                         .map(|(s, start)| (start, start + s))
                         .into_iter()
                         .unzip();
+                    // Clip exons to the chromosome length: drop any exon that starts
+                    // beyond it, and truncate one that only partially overflows.
+                    let (starts, ends): (Vec<u32>, Vec<u32>) = starts
+                        .into_iter()
+                        .zip(ends.into_iter())
+                        .filter(|&(s, _)| s < chromlen)
+                        .map(|(s, e)| (s, e.min(chromlen)))
+                        .unzip();
+                    let length: u32 = starts.iter().zip(ends.iter()).map(|(s, e)| e - s).sum();
                     regions.push(Region {
                         chrom: fields[0].to_string(),  //chrom
                         start: Revalue::V(starts),     //start
@@ -349,8 +431,8 @@ pub fn read_bedfile(
                     });
                     entries += 1;
                 } else {
-                    let start = fields[1].parse().unwrap();
-                    let end = fields[2].parse().unwrap();
+                    let start = feat_start;
+                    let end: u32 = fields[2].parse::<u32>().unwrap().min(chromlen);
                     regions.push(Region {
                         chrom: fields[0].to_string(),  //chrom
                         start: Revalue::U(start),      //start
@@ -424,17 +506,24 @@ pub fn chrombounds_from_bam(bamfiles: Vec<&str>) -> HashMap<String, u32> {
             );
         }
     }
-    let bam = IndexedReader::from_path(bamfiles[0]).unwrap();
-    let header = bam.header().clone();
-    let mut chromsizes = HashMap::new();
-    for tid in 0..header.target_count() {
-        let chromname = String::from_utf8(header.tid2name(tid).to_vec())
-            .expect("Invalid UTF-8 in chromosome name");
-        let chromlen = header
-            .target_len(tid)
-            .expect("Error retrieving length for chromosome");
-        if validchroms.contains(&chromname) {
-            chromsizes.insert(chromname, chromlen as u32);
+
+    let mut chromsizes: HashMap<String, u32> = HashMap::new();
+    for bamfile in bamfiles.iter() {
+        let bam = IndexedReader::from_path(bamfile).unwrap();
+        let header = bam.header().clone();
+        for tid in 0..header.target_count() {
+            let chromname = String::from_utf8(header.tid2name(tid).to_vec())
+                .expect("Invalid UTF-8 in chromosome name");
+            if !validchroms.contains(&chromname) {
+                continue;
+            }
+            let chromlen = header
+                .target_len(tid)
+                .expect("Error retrieving length for chromosome") as u32;
+            chromsizes
+                .entry(chromname)
+                .and_modify(|len| *len = (*len).min(chromlen))
+                .or_insert(chromlen);
         }
     }
     chromsizes
@@ -445,6 +534,7 @@ pub fn bwintervals(
     regions: &Vec<Region>,
     slopregions: &Vec<Vec<Bin>>,
     scale_regions: &Scalingregions,
+    blacklist_index: Option<&crate::filtering::BlacklistIndex>,
 ) -> Vec<Vec<f32>> {
     // For a given bw file, a vector of slopregions (Bin enum))
     // return a vector with for every region a vector of f64.
@@ -470,10 +560,15 @@ pub fn bwintervals(
             .iter()
             .flat_map(|bin| match bin {
                 Bin::Conbin(a, b) => vec![*a, *b],
+                Bin::PaddedConbin(a, b, _) => vec![*a, *b],
                 Bin::Catbin(pairs) => pairs
                     .iter()
                     .flat_map(|(x, y)| vec![*x, *y])
                     .collect::<Vec<u32>>(),
+                Bin::PaddedCatbin(pairs, _) => pairs
+                    .iter()
+                    .flat_map(|(x, y)| vec![*x, *y])
+                    .collect::<Vec<u32>>(),
             })
             .fold((u32::MAX, u32::MIN), |(min, max), x| {
                 (min.min(x), max.max(x))
@@ -490,6 +585,23 @@ pub fn bwintervals(
             let val = interval.value as f32;
             bwhash.extend((start..end).map(|bp| (bp, val)));
         }
+        let gather_vals = |a: u32, b: u32, vals: &mut Vec<f32>| {
+            for bp in a..b {
+                if blacklist_index.is_some() && blacklist_index.unwrap().contains(&region.chrom, bp)
+                {
+                    continue;
+                }
+                match bwhash.get(&bp) {
+                    Some(v) => vals.push(*v),
+                    None => {
+                        if scale_regions.missingdata_as_zero {
+                            vals.push(0.0);
+                        }
+                    }
+                }
+            }
+        };
+
         // Now we can iterate over the slopped regions, and get the values from the hashmap.
         for bin in sls {
             match bin {
@@ -501,48 +613,118 @@ pub fn bwintervals(
                             bwval.push(std::f32::NAN);
                         }
                     } else {
-                        // Get values from the hashmap
-                        let vals: Vec<&f32> = (*a..*b).filter_map(|bp| bwhash.get(&bp)).collect();
-
+                        let mut vals: Vec<f32> = Vec::new();
+                        gather_vals(*a, *b, &mut vals);
+                        if vals.is_empty() {
+                            if scale_regions.missingdata_as_zero {
+                                bwval.push(0.0);
+                            } else {
+                                bwval.push(std::f32::NAN);
+                            }
+                        } else {
+                            let valrefs: Vec<&f32> = vals.iter().collect();
+                            let val = match scale_regions.avgtype.as_str() {
+                                "mean" => mean_float(&valrefs),
+                                "median" => median_float(&valrefs),
+                                "min" => min_float(&valrefs),
+                                "max" => max_float(&valrefs),
+                                "std" => std_float(&valrefs),
+                                "sum" => sum_float(&valrefs),
+                                _ => panic!("Unknown avgtype."),
+                            };
+                            bwval.push(val);
+                        }
+                    }
+                }
+                Bin::PaddedConbin(a, b, pad) => {
+                    let mut vals: Vec<f32> = Vec::new();
+                    gather_vals(*a, *b, &mut vals);
+                    if scale_regions.missingdata_as_zero && *pad > 0 {
+                        vals.extend(std::iter::repeat(0.0f32).take(*pad as usize));
+                    }
+                    if vals.is_empty() {
+                        if scale_regions.missingdata_as_zero {
+                            bwval.push(0.0);
+                        } else {
+                            bwval.push(std::f32::NAN);
+                        }
+                    } else {
+                        let valrefs: Vec<&f32> = vals.iter().collect();
                         let val = match scale_regions.avgtype.as_str() {
-                            "mean" => mean_float(&vals),
-                            "median" => median_float(&vals),
-                            "min" => min_float(&vals),
-                            "max" => max_float(&vals),
-                            "std" => std_float(&vals),
-                            "sum" => sum_float(&vals),
+                            "mean" => mean_float(&valrefs),
+                            "median" => median_float(&valrefs),
+                            "min" => min_float(&valrefs),
+                            "max" => max_float(&valrefs),
+                            "std" => std_float(&valrefs),
+                            "sum" => sum_float(&valrefs),
                             _ => panic!("Unknown avgtype."),
                         };
                         bwval.push(val);
                     }
                 }
                 Bin::Catbin(pairs) => {
-                    let mut vals: Vec<&f32> = Vec::new();
+                    let mut vals: Vec<f32> = Vec::new();
 
                     for (start, end) in pairs {
                         if start == end && *end == 0 {
-                            if scale_regions.missingdata_as_zero {
-                                vals.push(&0.0);
-                            } else {
-                                vals.push(&std::f32::NAN);
-                            }
+                            continue;
+                        }
+                        gather_vals(*start, *end, &mut vals);
+                    }
+
+                    // Handle case where no valid values exist
+                    if vals.is_empty() {
+                        if scale_regions.missingdata_as_zero {
+                            bwval.push(0.0);
                         } else {
-                            (*start..*end)
-                                .filter_map(|bp| bwhash.get(&bp))
-                                .for_each(|v| vals.push(v));
+                            bwval.push(std::f32::NAN);
+                        }
+                    } else {
+                        let valrefs: Vec<&f32> = vals.iter().collect();
+                        let val = match scale_regions.avgtype.as_str() {
+                            "mean" => mean_float(&valrefs),
+                            "median" => median_float(&valrefs),
+                            "min" => min_float(&valrefs),
+                            "max" => max_float(&valrefs),
+                            "std" => std_float(&valrefs),
+                            "sum" => sum_float(&valrefs),
+                            _ => panic!("Unknown avgtype."),
+                        };
+                        bwval.push(val);
+                    }
+                }
+                Bin::PaddedCatbin(pairs, pad) => {
+                    let mut vals: Vec<f32> = Vec::new();
+
+                    for (start, end) in pairs {
+                        if start == end && *end == 0 {
+                            continue;
                         }
+                        gather_vals(*start, *end, &mut vals);
+                    }
+                    if scale_regions.missingdata_as_zero && *pad > 0 {
+                        vals.extend(std::iter::repeat(0.0f32).take(*pad as usize));
                     }
 
-                    let val = match scale_regions.avgtype.as_str() {
-                        "mean" => mean_float(&vals),
-                        "median" => median_float(&vals),
-                        "min" => min_float(&vals),
-                        "max" => max_float(&vals),
-                        "std" => std_float(&vals),
-                        "sum" => sum_float(&vals),
-                        _ => panic!("Unknown avgtype."),
-                    };
-                    bwval.push(val);
+                    if vals.is_empty() {
+                        if scale_regions.missingdata_as_zero {
+                            bwval.push(0.0);
+                        } else {
+                            bwval.push(std::f32::NAN);
+                        }
+                    } else {
+                        let valrefs: Vec<&f32> = vals.iter().collect();
+                        let val = match scale_regions.avgtype.as_str() {
+                            "mean" => mean_float(&valrefs),
+                            "median" => median_float(&valrefs),
+                            "min" => min_float(&valrefs),
+                            "max" => max_float(&valrefs),
+                            "std" => std_float(&valrefs),
+                            "sum" => sum_float(&valrefs),
+                            _ => panic!("Unknown avgtype."),
+                        };
+                        bwval.push(val);
+                    }
                 }
             }
         }
@@ -600,16 +782,15 @@ pub fn header_matrix(
     // ref point can be empty (for scale_regions, for example).
     // To keep compatibility with deepTools 3 it should be written as null
     let refpointstring = (0..scale_regions.bwfiles)
-        .map(|_| scale_regions.referencepoint.clone())
-        .collect::<Vec<_>>()
-        .into_iter()
-        .join("\",\"");
-
-    if refpointstring.is_empty() {
-        headstr.push_str(&format!("\"ref point\":[null],"));
-    } else {
-        headstr.push_str(&format!("\"ref point\":[\"{}\"],", refpointstring));
-    }
+        .map(|_| {
+            if scale_regions.referencepoint.is_empty() {
+                "null".to_string()
+            } else {
+                format!("\"{}\"", scale_regions.referencepoint)
+            }
+        })
+        .join(",");
+    headstr.push_str(&format!("\"ref point\":[{}],", refpointstring));
 
     headstr.push_str(&format!("\"verbose\":{},", scale_regions.verbose));
     headstr.push_str(&format!("\"bin avg type\":\"{}\",", scale_regions.avgtype));
@@ -711,41 +892,17 @@ pub fn header_matrix(
 
 pub fn write_matrix(
     header: String,
-    mat: Vec<Vec<f32>>,
+    mat: &[Vec<f32>],
     ofile: &str,
-    regions: Vec<Region>,
+    regions: &[Region],
     scale_regions: &Scalingregions,
 ) {
     // Write out the matrix to a compressed file.
     let omat = File::create(ofile).unwrap();
     let mut encoder = GzEncoder::new(omat, Compression::default());
     encoder.write_all(header.as_bytes()).unwrap();
-    // Final check to make sure our regions and mat iter are of equal length.
     assert_eq!(regions.len(), mat.len());
-    for (region, row) in regions.into_iter().zip(mat.into_iter()) {
-        // Skipping rules.
-        // skip_zeros
-        if scale_regions.skipzero && row.iter().all(|&x| x == 0.0) {
-            continue;
-        }
-        // min threshold (Python: coverage.min() <= minThreshold → skip)
-        // Python: if any element is NaN, coverage.min() returns NaN, NaN <= threshold is False → row passes
-        // Rust: NaN <= threshold is False, so NaN is ignored in .any(). To match Python, skip threshold
-        // check entirely if the row contains any NaN values.
-        if scale_regions.minthresh != 0.0
-            && !row.iter().any(|&x| x.is_nan())
-            && row.iter().any(|&x| x <= scale_regions.minthresh)
-        {
-            continue;
-        }
-        // max threshold (Python: if max(coverage) >= maxThreshold → skip)
-        // NaN matching: Python's np.min()/np.max() propagate NaN, so NaN comparisons are False. If row contains NaN, skip filtering.
-        if scale_regions.maxthresh != 0.0
-            && !row.iter().any(|&x| x.is_nan())
-            && row.iter().any(|&x| x >= scale_regions.maxthresh)
-        {
-            continue;
-        }
+    for (region, row) in regions.iter().zip(mat.iter()) {
         let mut writerow = format!(
             "{}\t{}\t{}\t{}\t{}\t{}\t",
             region.chrom,            // Chromosome
@@ -762,7 +919,7 @@ pub fn write_matrix(
                         // as deepTools 3 encoded nan in matrix.
                         "nan".to_string()
                     } else {
-                        ((scale_regions.scale * x * 100.0).round() / 100.0).to_string()
+                        format!("{:.6}", scale_regions.scale * x)
                     }
                 })
                 .collect::<Vec<String>>()
@@ -782,7 +939,7 @@ pub fn write_matrix_values(
     use std::io::Write;
     let mut fh = File::create(file_name).unwrap();
 
-    // Header line 1: group labels with region counts (this was already correct)
+    // Header line 1: group labels with region counts
     let info: Vec<String> = scale_regions
         .regionlabels
         .iter()
@@ -791,7 +948,7 @@ pub fn write_matrix_values(
     fh.write_all(format!("#{}\n", info.join("\t")).as_bytes())
         .unwrap();
 
-    // Header line 2: region dimension parameters (this was already correct)
+    // Header line 2: region dimension parameters
     let header2 = format!(
         "#downstream:{}\tupstream:{}\tbody:{}\tbin size:{}\tunscaled 5 prime:{}\tunscaled 3 prime:{}\n",
         scale_regions.downstream,
@@ -803,7 +960,7 @@ pub fn write_matrix_values(
     );
     fh.write_all(header2.as_bytes()).unwrap();
 
-    // Header line 3: sample labels repeated per column (this was already correct)
+    // Header line 3: sample labels repeated per column
     let cols_per_sample = scale_regions.cols_expected / scale_regions.bwfiles;
     let sample_info: Vec<String> = scale_regions
         .bwlabels
@@ -814,7 +971,7 @@ pub fn write_matrix_values(
         .unwrap();
     fh.flush().unwrap();
 
-    // Reopen in append mode and write matrix data (matches Python np.savetxt fmt="%.4g")
+    // Reopen in append mode and write matrix data
     let mut fh = std::fs::OpenOptions::new()
         .create(false)
         .append(true)
@@ -827,7 +984,7 @@ pub fn write_matrix_values(
                 if x.is_nan() {
                     "nan".to_string()
                 } else {
-                    format!("{}", *x)
+                    format!("{:.6}", scale_regions.scale * x)
                 }
             })
             .collect::<Vec<_>>()
diff --git a/src/filtering.rs b/src/filtering.rs
index acda45d290..004fe18118 100644
--- a/src/filtering.rs
+++ b/src/filtering.rs
@@ -12,7 +12,7 @@ pub struct BlacklistIndex {
 }
 
 impl BlacklistIndex {
-    fn from_regions(regions: &[Region]) -> Self {
+    pub fn from_regions(regions: &[Region]) -> Self {
         let mut chroms: HashMap<String, Vec<(u32, u32)>> = HashMap::new();
         for r in regions {
             chroms
@@ -26,7 +26,7 @@ impl BlacklistIndex {
         Self { chroms }
     }
 
-    fn contains(&self, chrom: &str, pos: u32) -> bool {
+    pub fn contains(&self, chrom: &str, pos: u32) -> bool {
         let list = match self.chroms.get(chrom) {
             Some(l) => l,
             None => return false,
@@ -44,6 +44,29 @@ impl BlacklistIndex {
             }
         }
     }
+
+    // pub fn overlaps(&self, chrom: &str, start: u32, end: u32) -> bool {
+    //     // Returns true if any position in [start, end) falls within a blacklisted region.
+    //     let list = match self.chroms.get(chrom) {
+    //         Some(l) => l,
+    //         None => return false,
+    //     };
+    //     // Find the first blacklist entry with start >= start (or the one just before it)
+    //     match list.binary_search_by_key(&start, |&(s, _)| s) {
+    //         Ok(ix) => list[ix].1 > start,
+    //         Err(ix) => {
+    //             // Check the entry just before ix (its start < `start`), see if it extends past `start`
+    //             if ix > 0 && list[ix - 1].1 > start {
+    //                 return true;
+    //             }
+    //             // Check entries starting from ix onward, as long as their start < end
+    //             if ix < list.len() && list[ix].0 < end {
+    //                 return true;
+    //             }
+    //             false
+    //         }
+    //     }
+    // }
 }
 
 #[derive(Clone)]
@@ -60,6 +83,7 @@ pub struct Alignmentfilters {
     pub filterrnastrand: String,
     pub extendreads: bool,
     pub extendreadslen: u32,
+    pub extendreads_auto: bool,
     pub centerreads: bool,
     pub filter: bool,
     pub manipulate: bool,
@@ -93,6 +117,7 @@ impl Alignmentfilters {
         let _frs = filterrnastrand.unwrap_or(String::from("None"));
         let _extend = extendreads.unwrap_or(false);
         let _extendreadslen = extendreadslen.unwrap_or(0);
+        let _extend_auto = _extend && _extendreadslen == 0;
         let _center = centerreads.unwrap_or(false);
 
         // Set the manipulate bool for a quick escape in case manipulation is not needed.
@@ -131,6 +156,7 @@ impl Alignmentfilters {
             filterrnastrand: _frs,
             extendreads: _extend,
             extendreadslen: _extendreadslen,
+            extendreads_auto: _extend_auto,
             centerreads: _center,
             filter: filter,
             manipulate: manipulate,
@@ -271,13 +297,7 @@ impl Alignmentfilters {
             return None;
         }
         if self.offset != (0, 0) {
-            let mut blockvec: Vec<u32> = if self.extendreads {
-                self.rec_extension(rec)
-            } else {
-                rec.aligned_blocks()
-                    .flat_map(|x| x[0] as u32..x[1] as u32)
-                    .collect()
-            };
+            let mut blockvec: Vec<u32> = self.rec_blocks_for_offset(rec);
 
             let blocklen = blockvec.len() as i32;
 
@@ -314,8 +334,7 @@ impl Alignmentfilters {
                     self.offset.1
                 };
 
-                // if the range falls outside the vec, return none (retain deeptools 3 behavior)
-                if start < 0 || end < 0 || start >= blocklen || end >= blocklen || start >= end {
+                if start < 0 || end < 0 || start >= blocklen || end > blocklen || start >= end {
                     return None;
                 }
                 if rec.is_reverse() {
@@ -337,71 +356,131 @@ impl Alignmentfilters {
         return None;
     }
 
-    pub fn rec_extension(&self, rec: &Record) -> Vec<u32> {
-        // extend the reads. if the read is a proper pair, we get the fragment length from there.
-        // If not (or if se), then extendreadslen is used.
-        // Note that extendsreadslen is already populated at this stage, either by CLI (se) or calculated (pe).
-        let mut blockvec: Vec<u32> = Vec::new();
-        let mut blocklen: u32 = 0;
+    fn is_proper_pair_precise(&self, rec: &Record, max_paired_fragment_length: i64) -> bool {
+        if !rec.is_proper_pair() {
+            return false;
+        }
+        if rec.tid() != rec.mtid() {
+            return false;
+        }
+        if rec.insert_size().abs() > max_paired_fragment_length {
+            return false;
+        }
+        if rec.is_reverse() == rec.is_mate_reverse() {
+            return false;
+        }
+        if rec.is_reverse() {
+            rec.pos() >= rec.mpos()
+        } else {
+            rec.pos() <= rec.mpos()
+        }
+    }
 
-        rec.aligned_blocks().for_each(|x| {
-            let _s = x[0] as u32;
-            let _e = x[1] as u32;
-            blockvec.extend(_s.._e);
-            blocklen += _e - _s;
-        });
+    pub fn rec_blocks_for_offset(&self, rec: &Record) -> Vec<u32> {
+        let mut blocks: Vec<(i64, i64)> = rec
+            .aligned_blocks()
+            .map(|x| (x[0] as i64, x[1] as i64))
+            .collect();
 
-        if rec.is_proper_pair() {
-            // Proper pairs
-            if rec.is_reverse() {
-                let ns = rec.mpos() as u32;
-                let ne = rec.reference_start() as u32;
-                if ns < ne {
-                    // blockvec.splice(0..0,ns..ne);
-                    let mut new_blockvec = Vec::with_capacity((ne - ns) as usize + blockvec.len());
-                    new_blockvec.extend(ns..ne);
-                    new_blockvec.extend(blockvec);
-                    blockvec = new_blockvec;
-                }
+        if self.extendreads {
+            let query_len: i64 = rec.seq_len_from_cigar(false) as i64;
+            let max_paired_fragment_length: i64 = if self.maxfraglen > 0 {
+                self.maxfraglen as i64
             } else {
-                let ns = rec.reference_end() as u32;
-                let ne: u32 =
-                    ns + rec.insert_size().abs() as u32 - rec.seq_len_from_cigar(false) as u32;
-                if ns < ne {
-                    blockvec.extend(ns..ne);
-                }
-            }
-        } else {
-            // non proper pairs -> 'se mode'
-            if rec.is_reverse() {
-                let ns: u32;
-                let _rem = self.extendreadslen - rec.seq_len_from_cigar(false) as u32;
-                if _rem > rec.reference_start() as u32 {
-                    ns = 0;
+                4 * self.extendreadslen as i64
+            };
+            let max_paired_fragment_length = if max_paired_fragment_length <= 0 {
+                1000
+            } else {
+                max_paired_fragment_length
+            };
+
+            if self.is_proper_pair_precise(rec, max_paired_fragment_length) {
+                if rec.is_reverse() {
+                    let foo = (rec.mpos(), rec.reference_start());
+                    if foo.0 < foo.1 {
+                        blocks.insert(0, foo);
+                    }
                 } else {
-                    ns = rec.reference_start() as u32 - _rem;
-                }
-                let ne = rec.reference_start() as u32;
-                if ns < ne {
-                    //blockvec.splice(0..0,ns..ne);
-                    let mut new_blockvec = Vec::with_capacity((ne - ns) as usize + blockvec.len());
-                    new_blockvec.extend(ns..ne);
-                    new_blockvec.extend(blockvec);
-                    blockvec = new_blockvec;
+                    let foo = (
+                        rec.reference_end(),
+                        rec.reference_end() + rec.insert_size().abs() - query_len,
+                    );
+                    if foo.0 < foo.1 {
+                        blocks.push(foo);
+                    }
                 }
             } else {
-                let ns = rec.reference_end() as u32;
-                let ne: u32 = ns + self.extendreadslen - rec.seq_len_from_cigar(false) as u32;
-                if ns < ne {
-                    blockvec.extend(ns..ne);
+                if rec.is_reverse() {
+                    let mut start = rec.reference_start() - self.extendreadslen as i64 + query_len;
+                    if start < 0 {
+                        start = 0;
+                    }
+                    let foo = (start, rec.reference_start());
+                    if foo.0 < foo.1 {
+                        blocks.insert(0, foo);
+                    }
+                } else {
+                    let foo = (
+                        rec.reference_end(),
+                        rec.reference_end() + self.extendreadslen as i64 - query_len,
+                    );
+                    if foo.0 < foo.1 {
+                        blocks.push(foo);
+                    }
                 }
             }
         }
-        if self.centerreads {
-            let centerpoint = (blockvec.len() as u32 - blocklen) / 2;
-            return blockvec[centerpoint as usize..(centerpoint + blocklen) as usize].to_vec();
+
+        let mut stretch: Vec<u32> = Vec::new();
+        for (s, e) in blocks {
+            stretch.extend((s.max(0) as u32)..(e.max(0) as u32));
+        }
+
+        stretch
+    }
+
+    pub fn rec_extension(&self, rec: &Record) -> Vec<u32> {
+        let read_len: i64 = rec.seq_len_from_cigar(false) as i64;
+        let is_pe = rec.is_proper_pair();
+
+        if !self.extendreads_auto && (self.extendreadslen as i64) <= read_len {
+            let mut blockvec: Vec<u32> = Vec::new();
+            rec.aligned_blocks().for_each(|x| {
+                blockvec.extend(x[0] as u32..x[1] as u32);
+            });
+            return blockvec;
+        }
+
+        let (mut fragment_start, mut fragment_end): (i64, i64) = if is_pe {
+            if rec.is_reverse() {
+                (rec.mpos(), rec.reference_end())
+            } else {
+                (
+                    rec.reference_start(),
+                    rec.reference_start() + rec.insert_size().abs(),
+                )
+            }
+        } else if rec.is_reverse() {
+            (
+                rec.reference_end() - self.extendreadslen as i64,
+                rec.reference_end(),
+            )
+        } else {
+            (
+                rec.reference_start(),
+                rec.reference_start() + self.extendreadslen as i64,
+            )
+        };
+
+        if self.centerreads && fragment_end > fragment_start {
+            let fragment_center =
+                fragment_end as f64 - (fragment_end - fragment_start) as f64 / 2.0;
+            fragment_start = (fragment_center - read_len as f64 / 2.0).trunc() as i64;
+            fragment_end = fragment_start + read_len;
         }
-        return blockvec;
+
+        (fragment_start.max(0) as u32..fragment_end.max(0) as u32).collect()
     }
 
     pub fn rec_in_blacklist(&self, rec: &Record, chrom: &str) -> bool {
diff --git a/src/multibamsummary.rs b/src/multibamsummary.rs
index 2d34af8124..730c369c53 100644
--- a/src/multibamsummary.rs
+++ b/src/multibamsummary.rs
@@ -1,6 +1,8 @@
 use crate::calc::deseq_scalefactors;
-use crate::covcalc::{bam_pileup, parse_regions, region_divider, TempZip};
 use crate::covcalc::{Gtfparse, Region};
+use crate::covcalc::{
+    TempZip, bam_pileup, filter_regions_by_supregion, parse_regions, region_divider,
+};
 use crate::filehandler::{
     bam_ispaired, chrombounds_from_bam, is_bed_or_gtf, read_bedfile, read_gtffile,
 };
@@ -10,8 +12,8 @@ use ndarray::Array2;
 use ndarray_npy::NpzWriter;
 use pyo3::prelude::*;
 use pyo3::types::PyList;
-use rayon::prelude::*;
 use rayon::ThreadPoolBuilder;
+use rayon::prelude::*;
 use std::collections::HashMap;
 use std::fs::File;
 use std::io::prelude::*;
@@ -81,9 +83,6 @@ pub fn r_mbams(
         if verbose {
             println!("BED file mode. with files: {:?}", bedfiles);
         }
-        if supregion != "None" {
-            println!("Region supplied in BED-file mode. The region will be ignored.");
-        }
         let gtfparse = Gtfparse {
             metagene: metagene,
             txnid: txnid.to_string(),
@@ -103,7 +102,7 @@ pub fn r_mbams(
 
                 match ftype.as_str() {
                     "gtf" => read_gtffile(r, &gtfparse, chromsizes.keys().collect()),
-                    "bed" => read_bedfile(r, metagene, chromsizes.keys().collect()),
+                    "bed" => read_bedfile(r, metagene, &chromsizes),
                     _ => panic!("Only .bed and .gtf files are allowed (as determined by the number of columns). File = {}", ftype),
                 }
             })
@@ -111,6 +110,19 @@ pub fn r_mbams(
                 regions.extend(reg);
                 regionsizes.insert(regsize.0, regsize.1);
             });
+        // Restrict to the user-supplied --region window, if any.
+        if supregion != "None" {
+            let nbefore = regions.len();
+            regions = filter_regions_by_supregion(regions, supregion);
+            if verbose {
+                println!(
+                    "Region {} supplied: {} of {} regions overlap it.",
+                    supregion,
+                    regions.len(),
+                    nbefore
+                );
+            }
+        }
         gene_mode = true;
 
         // If there is a blacklist, read it.
@@ -120,8 +132,7 @@ pub fn r_mbams(
             match isbed.as_str() {
                 "gtf" => panic!("Error: Please provide a bed file for the blacklist."),
                 "bed" => {
-                    let (bls, _) =
-                        read_bedfile(&blacklist.to_string(), false, chromsizes.keys().collect());
+                    let (bls, _) = read_bedfile(&blacklist.to_string(), false, &chromsizes);
                     blacklistregions = Some(bls);
                 }
                 _ => panic!("Error: Cannot determine filetype of blacklist file."),
@@ -144,8 +155,7 @@ pub fn r_mbams(
             match isbed.as_str() {
                 "gtf" => panic!("Error: Please provide a bed file for the blacklist."),
                 "bed" => {
-                    let (bls, _) =
-                        read_bedfile(&blacklist.to_string(), false, chromsizes.keys().collect());
+                    let (bls, _) = read_bedfile(&blacklist.to_string(), false, &chromsizes);
                     blacklistregions = Some(bls);
                 }
                 _ => panic!("Error: Cannot determine filetype of blacklist file."),
@@ -153,6 +163,13 @@ pub fn r_mbams(
         }
     }
 
+    regions.sort_by(|a, b| {
+        a.chrom
+            .cmp(&b.chrom)
+            .then_with(|| a.start.start_key().cmp(&b.start.start_key()))
+            .then_with(|| a.end.end_key().cmp(&b.end.end_key()))
+    });
+
     let filters = Alignmentfilters::new(
         blacklistregions,
         Some(minmappingquality),
@@ -191,6 +208,8 @@ pub fn r_mbams(
     // Divide up the regions into regionBlocks
     let regionblocks = region_divider(&regions);
 
+    let binstep = binsize + distance_between_bins;
+
     assert!(regionblocks.len() > 0, "No regions to process. Exiting.");
     if verbose {
         println!(
@@ -208,8 +227,8 @@ pub fn r_mbams(
                     .par_iter()
                     .map(|i| {
                         bam_pileup(
-                            bamfile, &i, &binsize, &ispe, &ignorechr, filter, false, gene_mode,
-                            false, 0,
+                            bamfile, &i, &binsize, &binstep, &ispe, &ignorechr, filter, false,
+                            gene_mode, false, 0,
                         )
                     })
                     .reduce(
@@ -240,7 +259,6 @@ pub fn r_mbams(
         println!("Start iterating through temp coverage files and create output npy.");
     }
     let zips_vec: Vec<_> = zips.collect();
-    println!(" Length of ziperators = {}", zips_vec.len());
 
     let matvec: Vec<_> = pool.install(|| {
         let _m: Vec<_> = zips_vec
@@ -333,7 +351,7 @@ pub fn r_mbams(
         let sf = deseq_scalefactors(&matarr);
         // save scalefactors to file
         let mut sf_file = File::create(scaling_factors).unwrap();
-        writeln!(sf_file, "Sample\tscalingFactor").unwrap();
+        writeln!(sf_file, "sample\tscalingFactor").unwrap();
         for (sf, label) in sf.iter().zip(bamlabels.iter()) {
             writeln!(sf_file, "{}\t{}", label, sf).unwrap();
         }