Merge pull request #285 from cseptesting/284-issue-with-scipy-update

Removed scipy.repeats due to function deprecation

Author: pabloitu

csep/core/poisson_evaluations.py

@@ -555,7 +555,9 @@ def _w_test_ndarray(x, m=0):
     mn = count * (count + 1.) * 0.25
     se = count * (count + 1.) * (2. * count + 1.)
 
-    replist, repnum = scipy.stats.find_repeats(r)
+    _, repnum = numpy.unique(r, return_counts=True)
+    repnum = repnum[repnum > 1]
+
     if repnum.size != 0:
         # Correction for repeated elements.
         se -= 0.5 * (repnum * (repnum * repnum - 1)).sum()

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pycsep"
-dynamic = ["version"]              # <— version comes from SCM
+dynamic = ["version"]
 description = "Python tools from the Collaboratory for the Study of Earthquake Predictability"
 readme = "README.md"
 requires-python = ">=3.9"

tests/test_csep1_evaluations.py

@@ -109,6 +109,25 @@ def test_w_test(self):
         print('W Test: Running Unit Test')
         self.assertEqual(_w_test_ndarray(x, median), expected_output, 'Failed W Test')
 
+        out_rev = _w_test_ndarray(x[::-1], median)
+        self.assertAlmostEqual(out_rev['z_statistic'], expected_output['z_statistic'], places=15)
+        self.assertAlmostEqual(out_rev['probability'], expected_output['probability'], places=15)
+
+        x_with_zeros = numpy.concatenate([x, numpy.array([median, median, median])])
+        out_with_zeros = _w_test_ndarray(x_with_zeros, median)
+        self.assertAlmostEqual(out_with_zeros['z_statistic'], expected_output['z_statistic'], places=15)
+        self.assertAlmostEqual(out_with_zeros['probability'], expected_output['probability'], places=15)
+
+        x_ties = numpy.array([median + 1, median - 1,
+                              median + 2, median - 2,
+                              median + 2, median - 2,
+                              median + 5, median - 5,
+                              median + 10, median - 10], dtype=float)
+        out_ties = _w_test_ndarray(x_ties, median)
+        self.assertTrue(numpy.isfinite(out_ties['z_statistic']))
+        self.assertTrue(0.0 <= out_ties['probability'] <= 1.0)
+
+
     def test_t_test(self):
         pass
         """