Merge pull request #451 from akmorrow13/python3

added compatibility for python3

mango-python/Makefile

@@ -44,7 +44,7 @@ help:
 
 # This Makefile uses bash features like printf and <()
 SHELL=bash
-python=python2.7
+python=python
 pip=pip
 tests=bdgenomics
 extras=
@@ -113,7 +113,7 @@ check_build_reqs:
 
 
 prepare:
-	$(pip) install pytest==2.8.3
+	$(pip) install pytest==3.9.1
 	# ipython version required for python 2.7
 	$(pip) install jupyter_contrib_nbextensions
 	$(pip) install -r requirements.txt

mango-python/bdgenomics/mango/distribution.py

@@ -70,7 +70,8 @@ def __init__(self):
         approximateCounts = lambda counts, sample: int(counts * 1.0/sample)
 
         # restructure each record so record structure is  (key: sampleId, value: (coverage, count))
-        x = map(lambda x: (x[0][0], (x[0][1], approximateCounts(x[1], self.sample))), collectedCounts)
+        x = list(map(lambda x: (x[0][0], (x[0][1], approximateCounts(x[1], self.sample))), collectedCounts))
+
         # create dictionary where keys are the sampleId
         self.collectedCounts = collections.defaultdict(set)
         for k, v in x:
@@ -99,14 +100,14 @@ def plotDistributions(self, normalize = True, cumulative = False, testMode = Fal
             f, ax = plt.subplots(figsize=figsize)
 
         # iterate through each sample
-        for label, data in self.collectedCounts.iteritems():
+        for label, data in self.collectedCounts.items():
 
             if data == set(): # Do not plot any empty sets of data
                 continue
 
             sData = sorted(data)
-            values = map(lambda p: p[0], sData)
-            counts   = map(lambda p: p[1], sData)
+            values = list(map(lambda p: p[0], sData))
+            counts   = list(map(lambda p: p[1], sData))
 
             if normalize:
                 # replace distribution counts with normalized values
@@ -118,7 +119,7 @@ def plotDistributions(self, normalize = True, cumulative = False, testMode = Fal
                 counts = np.cumsum(counts)
 
             # re-write manipulated data
-            countDistributions[label]=zip(values, counts)
+            countDistributions[label]=list(zip(values, counts))
 
             if (not testMode): # For testing: do not run plots if testMode
                 if (bar_plt):

mango-python/bdgenomics/mango/test/alignment_test.py

@@ -110,10 +110,11 @@ def test_coverage_distribution(self):
         _, cd = coverage.plotDistributions(testMode = True, cumulative = False, normalize=False)
 
         # first sample
-        items = cd.items()[0][1]
+        items = list(cd.popitem()[1])
         assert(len(items) == 1)
         x = items.pop()
         assert(x[0] == 1) # all positions have coverage of 1
+        assert(x[0] == 1) # all positions have coverage of 1
         assert(x[1] == 1500)
 
 
@@ -131,9 +132,8 @@ def test_fragment_distribution(self):
         _, cd = fragments.plotDistributions(testMode = True, cumulative = False, normalize=False)
 
         # first sample
-        items = cd.items()[0][1]
+        items = list(cd.popitem()[1])
         assert(len(items) == 1)
-        print(cd)
         x = items[0]
         assert(x[0] == 75)
         assert(x[1] == 20) # all 20 sequences have same length of 75
@@ -152,7 +152,7 @@ def test_mapq_distribution(self):
         _, md = mapq.plotDistributions(testMode = True, cumulative = False, normalize = False)
 
         # first sample
-        items = md.items()[0][1]
+        items = list(md.popitem()[1])
         assert(len(items) == 5) # mapq for 24, 28, 35, 40, 60
         x = items[0]
         assert(x[0] == 24) # 1 read with mapq 24

mango-python/bdgenomics/mango/test/coverage_test.py

@@ -44,10 +44,8 @@ def test_coverage_distribution(self):
         assert(len(cd) == 1)
 
         # all items for first sample
-        items = cd.items()[0][1]
+        items = list(cd.popitem()[1])
 
-        print("Coverage")
-        print(cd)
         assert(items[0][1] == 1500)
 
     def test_example_coverage(self):
@@ -60,28 +58,28 @@ def test_example_coverage(self):
 
         qc = CoverageDistribution(self.ss, coverage, bin_size = 1)
         # sum of all coverage
-        total = sum(map(lambda x: x[1], qc.collectedCounts.items()[0][1]))
 
         _, cd1 = qc.plotDistributions(testMode = True, cumulative = False, normalize=False)
+        total = sum(map(lambda x: x[1], list(qc.collectedCounts.items())[0][1]))
 
         # first sample
-        items = cd1.items()[0][1]
+        items = list(cd1.popitem()[1])
         x = items[0]
         assert(x[0] == 1) # 6 locations with read depth 1
         assert(x[1] == 6)
 
         _, cd2 = qc.plotDistributions(testMode = True, cumulative = False, normalize=True)
 
         # first sample
-        items = cd2.items()[0][1]
+        items = list(cd2.popitem()[1])
         x = items[0]
         assert(x[0] == 1)
         assert(x[1] == 6.0/total) # normalized value
 
         _, cd3 = qc.plotDistributions(testMode = True, cumulative = True, normalize = True)
 
         # first sample
-        items = cd3.items()[0][1]
+        items = list(cd3.popitem()[1])
         x = items[-1]
         assert(x[0] == 89)
         assert(x[1] > 0.999) # cumulative and normalized, so last value shound be about 1

mango-python/bdgenomics/mango/test/distribution_test.py

@@ -38,12 +38,12 @@ def test_normalized_count_distribution(self):
         qc = CoverageDistribution(self.ss, coverage)
 
         _, cd = qc.plotDistributions(testMode = True, normalize = True)
-        items = cd.items()[0][1]
+        items = list(cd.popitem()[1])
         assert(len(items) == 1)
         assert(items.pop()[1] == 1.0)
 
         _, cd = qc.plotDistributions(testMode = True, normalize = False)
-        items = cd.items()[0][1]
+        items = list(cd.popitem()[1])
         assert(len(items) == 1)
         assert(items.pop()[1] == 1500)
 
@@ -64,15 +64,14 @@ def test_cumulative_count_distribution(self):
         _, cd = qc.plotDistributions(testMode = True, cumulative = True, normalize = False)
 
         # first sample
-        items = cd.items()[0][1]
+        items = list(cd.popitem()[1])
         assert(len(items) == 1)
-        print(items)
         assert(items.pop()[1] == 1500)
 
         _, cd = qc.plotDistributions(testMode = True, cumulative = False, normalize = False)
 
         # first sample
-        items = cd.items()[0][1]
+        items = list(cd.popitem()[1])
         assert(len(items) == 1)
         assert(items.pop()[1] == 1500)
 
@@ -103,11 +102,10 @@ def test_sampling(self):
         coverage = reads.toCoverage()
 
         cd1 = CoverageDistribution(self.ss, coverage, sample = 0.9)
-        sum1 = sum(map(lambda x: x[1], cd1.collectedCounts.items()[0][1]))
+        sum1 = sum(map(lambda x: x[1], cd1.collectedCounts.popitem()[1]))
         cd2 = CoverageDistribution(self.ss, coverage, sample = 1.0)
-        sum2 = sum(map(lambda x: x[1], cd2.collectedCounts.items()[0][1]))
+        sum2 = sum(map(lambda x: x[1], cd2.collectedCounts.popitem()[1]))
 
         # estimated counts should be around real counts
         dev = 100
         assert(sum1 > sum2 - dev and sum1 < sum2 + dev)
-

mango-python/bdgenomics/mango/test/notebook_test.py

@@ -33,7 +33,7 @@ def test_example(self):
 
         # this file is converted from ipynb in make test
         testFile = self.exampleFile("notebooks/mango-viz.py")
-        execfile(testFile)
+        exec(open(testFile).read())
 
     def test_coverage_example(self):
         # these variables are read into mango-python.py
@@ -43,7 +43,7 @@ def test_coverage_example(self):
 
         # this file is converted from mango-python.coverage.ipynb in the Makefile
         testCoverageFile = self.exampleFile("notebooks/mango-python-coverage.py")
-        execfile(testCoverageFile)
+        exec(open(testCoverageFile).read())
 
     def test_alignment_example(self):
         # these variables are read into mango-python.py
@@ -53,5 +53,4 @@ def test_alignment_example(self):
 
         # this file is converted from mango-python-alignment.ipynb in the Makefile
         testAlignmentFile = self.exampleFile("notebooks/mango-python-alignment.py")
-        execfile(testAlignmentFile)
-
+        exec(open(testAlignmentFile).read())