MAINT: Simplify return types

Standardize returns types for Windows and 32-bit platforms on int64
in choice and randint (default).
Refactor tomaxint to call randint

Author: bashtage

numpy/random/generator.pyx

@@ -368,26 +368,11 @@ cdef class RandomGenerator:
                 [ True,  True]]])
 
         """
-        cdef np.npy_intp n
-        cdef np.ndarray randoms
-        cdef int64_t *randoms_data
-
-        if size is None:
-            with self.lock:
-                return random_positive_int(self._brng)
-
-        randoms = <np.ndarray>np.empty(size, dtype=np.int64)
-        randoms_data = <int64_t*>np.PyArray_DATA(randoms)
-        n = np.PyArray_SIZE(randoms)
-
-        for i in range(n):
-            with self.lock, nogil:
-                randoms_data[i] = random_positive_int(self._brng)
-        return randoms
+        return self.randint(0, np.iinfo(np.int).max + 1, dtype=np.int, size=size)
 
-    def randint(self, low, high=None, size=None, dtype=int, use_masked=True):
+    def randint(self, low, high=None, size=None, dtype=np.int64, use_masked=True):
         """
-        randint(low, high=None, size=None, dtype='l', use_masked=True)
+        randint(low, high=None, size=None, dtype='int64', use_masked=True)
 
         Return random integers from `low` (inclusive) to `high` (exclusive).
 
@@ -661,9 +646,9 @@ cdef class RandomGenerator:
                 cdf /= cdf[-1]
                 uniform_samples = self.random_sample(shape)
                 idx = cdf.searchsorted(uniform_samples, side='right')
-                idx = np.array(idx, copy=False)  # searchsorted returns a scalar
+                idx = np.array(idx, copy=False, dtype=np.int64)  # searchsorted returns a scalar
             else:
-                idx = self.randint(0, pop_size, size=shape)
+                idx = self.randint(0, pop_size, size=shape, dtype=np.int64)
         else:
             if size > pop_size:
                 raise ValueError("Cannot take a larger sample than "
@@ -692,7 +677,7 @@ cdef class RandomGenerator:
                     n_uniq += new.size
                 idx = found
             else:
-                idx = self.permutation(pop_size)[:size]
+                idx = (self.permutation(pop_size)[:size]).astype(np.int64)
                 if shape is not None:
                     idx.shape = shape
 

numpy/random/tests/test_against_numpy.py

@@ -183,6 +183,7 @@ def test_standard_exponential(self):
                         self.rs.standard_exponential)
         self._is_state_common_legacy()
 
+    @pytest.mark.xfail(reason='Stream broken for simplicity')
     def test_tomaxint(self):
         self._set_common_state()
         self._is_state_common()

numpy/random/tests/test_generator_mt19937.py

@@ -639,6 +639,18 @@ def test_choice_nan_probabilities(self):
         p = [None, None, None]
         assert_raises(ValueError, random.choice, a, p=p)
 
+    def test_choice_return_type(self):
+        # gh 9867
+        p = np.ones(4) / 4.
+        actual = random.choice(4, 2)
+        assert actual.dtype == np.int64
+        actual = random.choice(4, 2, replace=False)
+        assert actual.dtype == np.int64
+        actual = random.choice(4, 2, p=p)
+        assert actual.dtype == np.int64
+        actual = random.choice(4, 2, p=p, replace=False)
+        assert actual.dtype == np.int64
+
     def test_bytes(self):
         random.brng.seed(self.seed)
         actual = random.bytes(10)