changes to reflect numpy and pandas deprecation for geneprofile

cgat-developers · Apr 1, 2024 · e39589a · e39589a
1 parent 1ec3733
commit e39589a
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Showing 2 changed files with 8 additions and 8 deletions.
diff --git a/cgat/BamTools/geneprofile.pyx b/cgat/BamTools/geneprofile.pyx
@@ -562,7 +562,7 @@ class IntervalsCounter:
         if self.normalization in ("max", "sum", "total-max", "total-sum"):
             self.dtype = numpy.float
         else:
-            self.dtype = numpy.int
+            self.dtype = numpy.int64
         self.aggregate_counts.append(numpy.zeros(length, dtype=self.dtype))
 
     def setOutputProfiles(self, outfile_profiles):
@@ -587,7 +587,7 @@ class IntervalsCounter:
             self.dtype = numpy.float
             self.format = "%6.4f"
         else:
-            self.dtype = numpy.int
+            self.dtype = numpy.int64
             self.format = "%i"
 
         for x,c in enumerate(self.aggregate_counts):

diff --git a/cgat/Stats.py b/cgat/Stats.py
@@ -502,7 +502,7 @@ def doFDRPython(pvalues,
         vlambda = numpy.arange(0, 0.95, 0.05)
 
     m = len(pvalues)
-    pvalues = numpy.array(pvalues, dtype=numpy.float)
+    pvalues = numpy.array(pvalues, dtype=numpy.float64)
 
     if pi0 is None:
         if type(vlambda) == float:
@@ -525,7 +525,7 @@ def doFDRPython(pvalues,
             pi0 = min(pi0, 1.0)
         else:
 
-            pi0 = numpy.zeros(len(vlambda), numpy.float)
+            pi0 = numpy.zeros(len(vlambda), numpy.float64)
 
             for i in range(len(vlambda)):
                 pi0[i] = numpy.mean([x >= vlambda[i]
@@ -558,8 +558,8 @@ def doFDRPython(pvalues,
 
                 minpi0 = min(pi0)
 
-                mse = numpy.zeros(len(vlambda), numpy.float)
-                pi0_boot = numpy.zeros(len(vlambda), numpy.float)
+                mse = numpy.zeros(len(vlambda), numpy.float64)
+                pi0_boot = numpy.zeros(len(vlambda), numpy.float64)
 
                 for i in range(100):
                     # sample pvalues
@@ -674,7 +674,7 @@ def getHeaders(cls):
 
 
 def filterMasked(xvals, yvals, missing=("na", "Nan", None, ""),
-                 dtype=numpy.float):
+                 dtype=numpy.float64):
     """convert xvals and yvals to numpy array skipping pairs with
     one or more missing values."""
     xmask = [i in missing for i in xvals]
@@ -1041,7 +1041,7 @@ def adjustPValues(pvalues, method='fdr', n=None):
         method = "BH"
 
     # optional, remove NA values
-    p = numpy.array(pvalues, dtype=numpy.float)
+    p = numpy.array(pvalues, dtype=numpy.float64)
     lp = len(p)
 
     assert n <= lp