Author: Ronan Lamy <[email protected]>
Branch: fix-result-types
Changeset: r77459:5c9551b5f9f3
Date: 2015-05-21 20:27 +0100
http://bitbucket.org/pypy/pypy/changeset/5c9551b5f9f3/
Log: test np.result_type(); fix
diff --git a/pypy/module/micronumpy/casting.py
b/pypy/module/micronumpy/casting.py
--- a/pypy/module/micronumpy/casting.py
+++ b/pypy/module/micronumpy/casting.py
@@ -37,6 +37,12 @@
dtypes_w.append(dtype)
return find_result_type(space, arrays_w, dtypes_w)
+simple_kind_ordering = {
+ Bool.kind: 0, ULong.kind: 1, Long.kind: 1,
+ Float64.kind: 2, Complex64.kind: 2,
+ NPY.STRINGLTR: 3, NPY.STRINGLTR2: 3,
+ UnicodeType.kind: 3, VoidType.kind: 3, ObjectType.kind: 3}
+
def find_result_type(space, arrays_w, dtypes_w):
# equivalent to PyArray_ResultType
@@ -50,17 +56,18 @@
max_array_kind = 0
for w_array in arrays_w:
if w_array.is_scalar():
- kind = kind_ordering[w_array.get_dtype().kind]
+ kind = simple_kind_ordering[w_array.get_dtype().kind]
if kind > max_scalar_kind:
max_scalar_kind = kind
else:
all_scalars = False
- kind = kind_ordering[w_array.get_dtype().kind]
+ kind = simple_kind_ordering[w_array.get_dtype().kind]
if kind > max_array_kind:
max_array_kind = kind
if arrays_w:
for dtype in dtypes_w:
- kind = kind_ordering[dtype.kind]
+ all_scalars = False
+ kind = simple_kind_ordering[dtype.kind]
if kind > max_array_kind:
max_array_kind = kind
use_min_scalar = bool(arrays_w) and not all_scalars and max_array_kind >=
max_scalar_kind
diff --git a/pypy/module/micronumpy/test/test_casting.py
b/pypy/module/micronumpy/test/test_casting.py
--- a/pypy/module/micronumpy/test/test_casting.py
+++ b/pypy/module/micronumpy/test/test_casting.py
@@ -133,6 +133,13 @@
assert np.promote_types('i4', 'S8') == np.dtype('S11')
assert np.promote_types('f4', 'S8') == np.dtype('S32')
+ def test_result_type(self):
+ import numpy as np
+ assert np.result_type(np.uint8, np.int8) == np.int16
+ assert np.result_type(np.uint16(1), np.int8(0)) == np.int32
+ assert np.result_type(np.uint16(1), np.int8(0), np.uint8) == np.uint8
+ assert np.result_type(-1, np.uint8, 1) == np.int16
+
def test_can_cast_same_type(space):
dt_bool = get_dtype_cache(space).w_booldtype
assert can_cast_type(space, dt_bool, dt_bool, 'no')
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