Author: Ronan Lamy <[email protected]>
Branch: fix-result-types
Changeset: r77458:76dd9c09a0e8
Date: 2015-05-21 20:01 +0100
http://bitbucket.org/pypy/pypy/changeset/76dd9c09a0e8/
Log: Implement numpy's complicated scalar handling rules in result_type()
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
@@ -63,8 +63,7 @@
kind = 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
- use_min_scalar = False
+ use_min_scalar = bool(arrays_w) and not all_scalars and max_array_kind >=
max_scalar_kind
if not use_min_scalar:
for w_array in arrays_w:
if result is None:
@@ -76,6 +75,31 @@
result = dtype
else:
result = _promote_types(space, result, dtype)
+ else:
+ small_unsigned = False
+ alt_result = None
+ for w_array in arrays_w:
+ dtype = w_array.get_dtype()
+ small_unsigned_scalar = False
+ if w_array.is_scalar() and dtype.is_number():
+ num, alt_num = w_array.get_scalar_value().min_dtype()
+ small_unsigned_scalar = (num != alt_num)
+ dtype = num2dtype(space, num)
+ if result is None:
+ result = dtype
+ small_unsigned = small_unsigned_scalar
+ else:
+ result, small_unsigned = _promote_types_su(
+ space, result, dtype,
+ small_unsigned, small_unsigned_scalar)
+ for dtype in dtypes_w:
+ if result is None:
+ result = dtype
+ small_unsigned = False
+ else:
+ result, small_unsigned = _promote_types_su(
+ space, result, dtype,
+ small_unsigned, False)
return result
@@ -215,6 +239,27 @@
return dt1
raise oefmt(space.w_TypeError, "invalid type promotion")
+def _promote_types_su(space, dt1, dt2, su1, su2):
+ """Like _promote_types(), but handles the small_unsigned flag as well"""
+ if su1:
+ if dt2.is_bool() or dt2.is_unsigned():
+ dt1 = dt1.as_unsigned(space)
+ else:
+ dt1 = dt1.as_signed(space)
+ elif su2:
+ if dt1.is_bool() or dt1.is_unsigned():
+ dt2 = dt2.as_unsigned(space)
+ else:
+ dt2 = dt2.as_signed(space)
+ if dt1.elsize < dt2.elsize:
+ su = su2 and (su1 or not dt1.is_signed())
+ elif dt1.elsize == dt2.elsize:
+ su = su1 and su2
+ else:
+ su = su1 and (su2 or not dt2.is_signed())
+ return _promote_types(space, dt1, dt2), su
+
+
def find_dtype_for_scalar(space, w_obj, current_guess=None):
from .boxes import W_GenericBox
diff --git a/pypy/module/micronumpy/descriptor.py
b/pypy/module/micronumpy/descriptor.py
--- a/pypy/module/micronumpy/descriptor.py
+++ b/pypy/module/micronumpy/descriptor.py
@@ -164,6 +164,20 @@
def is_native(self):
return self.byteorder in (NPY.NATIVE, NPY.NATBYTE)
+ def as_signed(self, space):
+ """Convert from an unsigned integer dtype to its signed partner"""
+ if self.is_unsigned():
+ return num2dtype(space, self.num - 1)
+ else:
+ return self
+
+ def as_unsigned(self, space):
+ """Convert from a signed integer dtype to its unsigned partner"""
+ if self.is_signed():
+ return num2dtype(space, self.num + 1)
+ else:
+ return self
+
def get_float_dtype(self, space):
assert self.is_complex()
dtype = get_dtype_cache(space).component_dtypes[self.num]
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
@@ -1,7 +1,8 @@
from pypy.module.micronumpy.test.test_base import BaseNumpyAppTest
-from pypy.module.micronumpy.descriptor import get_dtype_cache
+from pypy.module.micronumpy.descriptor import get_dtype_cache, num2dtype
from pypy.module.micronumpy.casting import (
- find_binop_result_dtype, can_cast_type)
+ find_binop_result_dtype, can_cast_type, _promote_types_su)
+import pypy.module.micronumpy.constants as NPY
class AppTestNumSupport(BaseNumpyAppTest):
@@ -140,6 +141,20 @@
assert can_cast_type(space, dt_bool, dt_bool, 'same_kind')
assert can_cast_type(space, dt_bool, dt_bool, 'unsafe')
+def test_promote_types_su(space):
+ dt_int8 = num2dtype(space, NPY.BYTE)
+ dt_uint8 = num2dtype(space, NPY.UBYTE)
+ dt_int16 = num2dtype(space, NPY.SHORT)
+ dt_uint16 = num2dtype(space, NPY.USHORT)
+ # The results must be signed
+ assert _promote_types_su(space, dt_int8, dt_int16, False, False) ==
(dt_int16, False)
+ assert _promote_types_su(space, dt_int8, dt_int16, True, False) ==
(dt_int16, False)
+ assert _promote_types_su(space, dt_int8, dt_int16, False, True) ==
(dt_int16, False)
+
+ # The results may be unsigned
+ assert _promote_types_su(space, dt_int8, dt_int16, True, True) ==
(dt_int16, True)
+ assert _promote_types_su(space, dt_uint8, dt_int16, False, True) ==
(dt_uint16, True)
+
class TestCoercion(object):
def test_binops(self, space):
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