fix: remove numpy warnings

Author: sbrugman

histogrammar/primitives/centrallybin.py

@@ -703,8 +703,8 @@ def _numpy(self, data, weights, shape):
                 v.fill(None, float(hi))
 
         else:
-            selection = numpy.empty(q.shape, dtype=numpy.bool)
-            selection2 = numpy.empty(q.shape, dtype=numpy.bool)
+            selection = numpy.empty(q.shape, dtype=bool)
+            selection2 = numpy.empty(q.shape, dtype=bool)
 
             for index in xrange(len(self.bins)):
                 if index == 0:

histogrammar/primitives/irregularlybin.py

@@ -648,8 +648,8 @@ def _numpy(self, data, weights, shape):
 
         # FIXME: the case of all Counts could be optimized with numpy.histogram (see CentrallyBin for an example)
 
-        selection = numpy.empty(q.shape, dtype=numpy.bool)
-        selection2 = numpy.empty(q.shape, dtype=numpy.bool)
+        selection = numpy.empty(q.shape, dtype=bool)
+        selection2 = numpy.empty(q.shape, dtype=bool)
         subweights = weights.copy()
         for (low, sub), (high, _) in zip(self.bins, self.bins[1:] + ((float("nan"), None),)):
             numpy.greater_equal(q, low, selection)

histogrammar/primitives/stack.py

@@ -527,7 +527,7 @@ def _numpy(self, data, weights, shape):
         weights = weights.copy()
         weights[selection] = 0.0
 
-        selection = numpy.empty(q.shape, dtype=numpy.bool)
+        selection = numpy.empty(q.shape, dtype=bool)
         for threshold, sub in self.bins:
             numpy.less(q, threshold, selection)
             subweights[:] = weights