Add pytest for r_computematrix (salvage of #1369)

pydeeptools/deeptools/test/test_r_computeMatrix.py

@@ -0,0 +1,109 @@
+import pytest
+from deeptools.computeMatrix2 import r_computematrix  # Adjust the import to your actual module
+import os.path
+import gzip
+import hashlib
+
+root = os.path.dirname(os.path.abspath(__file__)) + "/test_data/"
+matrix = root + "computeMatrixOperations.mat.gz"
+bed = root + "computeMatrixOperations.bed"
+rbindMatrix1 = root + "somegenes.txt.gz"
+rbindMatrix2 = root + "othergenes.txt.gz"
+bigwig = root + "testA.bw"
+outnpz = root + "output.mat.npz.gz"
+
+def test_r_computematrix_referencePoint():
+    mode = "reference-point"
+    regionlis = [bed]
+    bwlis = [bigwig]
+    sampleslabel = ["sample1"]
+    upstream = 1000
+    downstream = 1000
+    unscaled5prime = 0
+    unscaled3prime = 0
+    regionbodylength = 0
+    binsize = 50
+    missingdatazero = False
+    metagene = False
+    txnid = ""
+    exonid = ""
+    txniddesignator = ""
+    scale = 1.0
+    nanafterend = False
+    skipzeros = False
+    minthresh = 0.0
+    maxthresh = 0.0
+    averagetypebins = "mean"
+    sortregions = "keep"
+    sortusing = "mean"
+    ortusingsamples = []
+    referencepoint = "TSS"
+    nproc = 1
+    verbose = False
+    ofile = outnpz
+
+    result = r_computematrix(
+        mode, regionlis, bwlis, sampleslabel, upstream, downstream, unscaled5prime, unscaled3prime,
+        regionbodylength, binsize, missingdatazero, metagene, txnid, exonid, txniddesignator, scale,
+        nanafterend, skipzeros, minthresh, maxthresh, averagetypebins, sortregions, sortusing,
+        ortusingsamples, referencepoint, nproc, verbose, ofile
+    )
+
+
+
+    with gzip.open(ofile, 'rb') as f:
+        file_content = f.read()
+        h = hashlib.md5(file_content).hexdigest()
+
+    expectedh = '4f1a2ce422d5b74fb6b75a81916929db'
+    assert h == expectedh
+
+    os.remove(ofile)
+
+def test_r_computematrix_scale():
+    mode = "scale-regions"
+    regionlis = [bed]
+    bwlis = [bigwig]
+    sampleslabel = ["sample1"]
+    upstream = 1000
+    downstream = 1000
+    unscaled5prime = 0
+    unscaled3prime = 0
+    regionbodylength = 0
+    binsize = 50
+    missingdatazero = False
+    metagene = False
+    txnid = ""
+    exonid = ""
+    txniddesignator = ""
+    scale = 1.0
+    nanafterend = False
+    skipzeros = False
+    minthresh = 0.0
+    maxthresh = 0.0
+    averagetypebins = "mean"
+    sortregions = "keep"
+    sortusing = "mean"
+    ortusingsamples = []
+    referencepoint = "TSS"
+    nproc = 1
+    verbose = False
+    ofile = outnpz
+
+    result = r_computematrix(
+        mode, regionlis, bwlis, sampleslabel, upstream, downstream, unscaled5prime, unscaled3prime,
+        regionbodylength, binsize, missingdatazero, metagene, txnid, exonid, txniddesignator, scale,
+        nanafterend, skipzeros, minthresh, maxthresh, averagetypebins, sortregions, sortusing,
+        ortusingsamples, referencepoint, nproc, verbose, ofile
+    )
+
+    with gzip.open(ofile, 'rb') as f:
+        file_content = f.read()
+        h = hashlib.md5(file_content).hexdigest()
+
+
+    expectedh = '4f1a2ce422d5b74fb6b75a81916929db'
+    assert h == expectedh
+
+    os.remove(ofile)
+