BUG/ENH: Fix zipf changes missed in NumPy

Fix zipf changes missed in NumPy
Enable 0 as valid input for hypergeometric

Author: bashtage

numpy/random/generator.pyx

@@ -3639,7 +3639,7 @@ cdef class RandomGenerator:
         x.shape = tuple(final_shape)
         return x
 
-    def multinomial(self, np.npy_intp n, object pvals, size=None):
+    def multinomial(self, object n, object pvals, size=None):
         """
         multinomial(n, pvals, size=None)
 

numpy/random/src/distributions/distributions.c

@@ -1048,25 +1048,31 @@ int64_t random_geometric(brng_t *brng_state, double p) {
 }
 
 int64_t random_zipf(brng_t *brng_state, double a) {
-  double T, U, V;
-  int64_t X;
   double am1, b;
 
   am1 = a - 1.0;
   b = pow(2.0, am1);
-  do {
-    U = 1.0 - next_double(brng_state);
-    V = next_double(brng_state);
-    X = (int64_t)floor(pow(U, -1.0 / am1));
-    /* The real result may be above what can be represented in a int64.
-     * It will get casted to -sys.maxint-1. Since this is
-     * a straightforward rejection algorithm, we can just reject this value
-     * in the rejection condition below. This function then models a Zipf
+  while (1) {
+    double T, U, V, X;
+
+    U = 1.0 - random_double(brng_state);
+    V = random_double(brng_state);
+    X = floor(pow(U, -1.0 / am1));
+    /*
+     * The real result may be above what can be represented in a signed
+     * long. Since this is a straightforward rejection algorithm, we can
+     * just reject this value. This function then models a Zipf
      * distribution truncated to sys.maxint.
      */
+    if (X > LONG_MAX || X < 1.0) {
+      continue;
+    }
+
     T = pow(1.0 + 1.0 / X, am1);
-  } while (((V * X * (T - 1.0) / (b - 1.0)) > (T / b)) || X < 1);
-  return X;
+    if (V * X * (T - 1.0) / (b - 1.0) <= T / b) {
+      return (long)X;
+    }
+  }
 }
 
 double random_triangular(brng_t *brng_state, double left, double mode,

numpy/random/tests/test_generator_mt19937.py

@@ -804,8 +804,7 @@ def test_geometric_exceptions(self):
         assert_raises(ValueError, random.geometric, [1.1] * 10)
         assert_raises(ValueError, random.geometric, -0.1)
         assert_raises(ValueError, random.geometric, [-0.1] * 10)
-        with suppress_warnings() as sup:
-            sup.record(RuntimeWarning)
+        with np.errstate(invalid='ignore'):
             assert_raises(ValueError, random.geometric, np.nan)
             assert_raises(ValueError, random.geometric, [np.nan] * 10)
 
@@ -888,8 +887,7 @@ def test_logseries(self):
         assert_array_equal(actual, desired)
 
     def test_logseries_exceptions(self):
-        with suppress_warnings() as sup:
-            sup.record(RuntimeWarning)
+        with np.errstate(invalid='ignore'):
             assert_raises(ValueError, random.logseries, np.nan)
             assert_raises(ValueError, random.logseries, [np.nan] * 10)
 
@@ -964,8 +962,7 @@ def test_negative_binomial(self):
         assert_array_equal(actual, desired)
 
     def test_negative_binomial_exceptions(self):
-        with suppress_warnings() as sup:
-            sup.record(RuntimeWarning)
+        with np.errstate(invalid='ignore'):
             assert_raises(ValueError, random.negative_binomial, 100, np.nan)
             assert_raises(ValueError, random.negative_binomial, 100,
                           [np.nan] * 10)
@@ -1046,8 +1043,7 @@ def test_poisson_exceptions(self):
         assert_raises(ValueError, random.poisson, [lamneg] * 10)
         assert_raises(ValueError, random.poisson, lambig)
         assert_raises(ValueError, random.poisson, [lambig] * 10)
-        with suppress_warnings() as sup:
-            sup.record(RuntimeWarning)
+        with np.errstate(invalid='ignore'):
             assert_raises(ValueError, random.poisson, np.nan)
             assert_raises(ValueError, random.poisson, [np.nan] * 10)