8000 BUG: Backport #7254 by ahaldane · Pull Request #7271 · numpy/numpy · GitHub
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BUG: Backport #7254 #7271

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Merged
merged 1 commit into from
Feb 19, 2016
Merged

BUG: Backport #7254 #7271

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4 changes: 2 additions & 2 deletions numpy/core/tests/test_mem_overlap.py
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Original file line number Diff line number Diff line change
Expand Up @@ -116,9 +116,9 @@ def test_diophantine_fuzz():
A_max = min(max_int, A_max)
U_max = min(max_int-1, U_max)

A = tuple(rng.randint(1, A_max+1, dtype=np.intp)
A = tuple(int(rng.randint(1, A_max+1, dtype=np.intp))
for j in range(ndim))
U = tuple(rng.randint(0, U_max+2, dtype=np.intp)
U = tuple(int(rng.randint(0, U_max+2, dtype=np.intp))
for j in range(ndim))

b_ub = min(max_int-2, sum(a*ub for a, ub in zip(A, U)))
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18 changes: 9 additions & 9 deletions numpy/random/mtrand/mtrand.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -612,7 +612,7 @@ def _rand_bool(low, high, size, rngstate):
off = <npy_bool>(low)
if size is None:
rk_random_bool(off, rng, 1, &buf, state)
return buf
return np.bool_(<npy_bool>buf)
else:
array = <ndarray>np.empty(size, np.bool_)
cnt = PyArray_SIZE(array)
Expand All @@ -639,7 +639,7 @@ def _rand_int8(low, high, size, rngstate):
off = <npy_uint8>(<npy_int8>low)
if size is None:
rk_random_uint8(off, rng, 1, &buf, state)
return <npy_int8>buf
return np.int8(<npy_int8>buf)
else:
array = <ndarray>np.empty(size, np.int8)
cnt = PyArray_SIZE(array)
Expand All @@ -666,7 +666,7 @@ def _rand_int16(low, high, size, rngstate):
off = <npy_uint16>(<npy_int16>low)
if size is None:
rk_random_uint16(off, rng, 1, &buf, state)
return <npy_int16>buf
return np.int16(<npy_int16>buf)
else:
array = <ndarray>np.empty(size, np.int16)
cnt = PyArray_SIZE(array)
Expand Down Expand Up @@ -717,7 +717,7 @@ def _rand_int32(low, high, size, rngstate):
off = <npy_uint32>(<npy_int32>low)
if size is None:
rk_random_uint32(off, rng, 1, &buf, state)
return <npy_int32>buf
return np.int32(<npy_int32>buf)
else:
array = <ndarray>np.empty(size, np.int32)
cnt = PyArray_SIZE(array)
Expand All @@ -744,7 +744,7 @@ def _rand_int64(low, high, size, rngstate):
off = <npy_uint64>(<npy_int64>low)
if size is None:
rk_random_uint64(off, rng, 1, &buf, state)
return <npy_int64>buf
return np.int64(<npy_int64>buf)
else:
array = <ndarray>np.empty(size, np.int64)
cnt = PyArray_SIZE(array)
Expand All @@ -770,7 +770,7 @@ def _rand_uint8(low, high, size, rngstate):
off = <npy_uint8>(low)
if size is None:
rk_random_uint8(off, rng, 1, &buf, state)
return buf
return np.uint8(<npy_uint8>buf)
else:
array = <ndarray>np.empty(size, np.uint8)
cnt = PyArray_SIZE(array)
Expand All @@ -797,7 +797,7 @@ def _rand_uint16(low, high, size, rngstate):
off = <npy_uint16>(low)
if size is None:
rk_random_uint16(off, rng, 1, &buf, state)
return buf
return np.uint16(<npy_uint16>buf)
else:
array = <ndarray>np.empty(size, np.uint16)
cnt = PyArray_SIZE(array)
Expand All @@ -824,7 +824,7 @@ def _rand_uint32(low, high, size, rngstate):
off = <npy_uint32>(low)
if size is None:
rk_random_uint32(off, rng, 1, &buf, state)
return <npy_uint32>buf
return np.uint32(<npy_uint32>buf)
else:
array = <ndarray>np.empty(size, np.uint32)
cnt = PyArray_SIZE(array)
Expand All @@ -851,7 +851,7 @@ def _rand_uint64(low, high, size, rngstate):
off = <npy_uint64>(low)
if size is None:
rk_random_uint64(off, rng, 1, &buf, state)
return <npy_uint64>buf
return np.uint64(<npy_uint64>buf)
else:
array = <ndarray>np.empty(size, np.uint64)
cnt = PyArray_SIZE(array)
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9 changes: 9 additions & 0 deletions numpy/random/tests/test_random.py
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Expand Up @@ -209,6 +209,15 @@ def test_repeatability(self):
res = hashlib.md5(val).hexdigest()
assert_(tgt[np.dtype(np.bool).name] == res)

def test_respect_dtype_singleton(self):
# See gh-7203
for dt in self.itype:
lbnd = 0 if dt is np.bool else np.iinfo(dt).min
ubnd = 2 if dt is np.bool else np.iinfo(dt).max + 1

sample = self.rfunc(lbnd, ubnd, dtype=dt)
self.assertEqual(sample.dtype, np.dtype(dt))


class TestRandomDist(TestCase):
# Make sure the random distribution returns the correct value for a
Expand Down
0