Author: Ronan Lamy <[email protected]>
Branch: fix-result-types
Changeset: r77418:c9ba53952909
Date: 2015-05-20 03:56 +0100
http://bitbucket.org/pypy/pypy/changeset/c9ba53952909/
Log: fix promote_types(<numeric>, <string>)
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
@@ -10,7 +10,9 @@
from .types import (
Bool, ULong, Long, Float64, Complex64, UnicodeType, VoidType, ObjectType,
promotion_table)
-from .descriptor import get_dtype_cache, as_dtype, is_scalar_w, variable_dtype
+from .descriptor import (
+ get_dtype_cache, as_dtype, is_scalar_w, variable_dtype, new_string_dtype,
+ new_unicode_dtype)
@jit.unroll_safe
def result_type(space, __args__):
@@ -151,39 +153,41 @@
if dt1.num > dt2.num:
dt1, dt2 = dt2, dt1
- # for now this means mixing signed and unsigned
- if dt2.kind == NPY.SIGNEDLTR:
- # if dt2 has a greater number of bytes, then just go with it
- if dt1.itemtype.get_element_size() < dt2.itemtype.get_element_size():
- return dt2
- # we need to promote both dtypes
- dtypenum = dt2.num + 2
- elif dt2.num == NPY.ULONGLONG or (LONG_BIT == 64 and dt2.num == NPY.ULONG):
- # UInt64 + signed = Float64
- dtypenum = NPY.DOUBLE
- elif dt2.is_flexible():
- # For those operations that get here (concatenate, stack),
- # flexible types take precedence over numeric type
- if dt2.is_record():
- return dt2
- if dt1.is_str_or_unicode():
- if dt2.elsize >= dt1.elsize:
+ if dt2.is_str():
+ if dt1.is_str():
+ if dt1.elsize > dt2.elsize:
+ return dt1
+ else:
return dt2
+ else: # dt1 is numeric
+ dt1_size = dt1.itemtype.strlen
+ if dt1_size > dt2.elsize:
+ return new_string_dtype(space, dt1_size)
+ else:
+ return dt2
+ elif dt2.is_unicode():
+ if dt1.is_unicode():
+ if dt1.elsize > dt2.elsize:
+ return dt1
+ else:
+ return dt2
+ elif dt1.is_str():
+ if dt2.elsize >= 4 * dt1.elsize:
+ return dt2
+ else:
+ return new_unicode_dtype(space, 4 * dt1.elsize)
+ else: # dt1 is numeric
+ dt1_size = 4 * dt1.itemtype.strlen
+ if dt1_size > dt2.elsize:
+ return new_unicode_dtype(space, dt1_size)
+ else:
+ return dt2
+ else:
+ assert dt2.num == NPY.VOID
+ if can_cast_type(space, dt1, dt2, casting='equiv'):
return dt1
- return dt2
- else:
- # increase to the next signed type
- dtypenum = dt2.num + 1
- newdtype = get_dtype_cache(space).dtypes_by_num[dtypenum]
+ raise oefmt(space.w_TypeError, "invalid type promotion")
- if (newdtype.itemtype.get_element_size() > dt2.itemtype.get_element_size()
or
- newdtype.kind == NPY.FLOATINGLTR):
- return newdtype
- else:
- # we only promoted to long on 32-bit or to longlong on 64-bit
- # this is really for dealing with the Long and Ulong dtypes
- dtypenum += 2
- return get_dtype_cache(space).dtypes_by_num[dtypenum]
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
@@ -146,6 +146,9 @@
def is_str(self):
return self.num == NPY.STRING
+ def is_unicode(self):
+ return self.num == NPY.UNICODE
+
def is_object(self):
return self.num == NPY.OBJECT
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
@@ -130,6 +130,7 @@
assert np.promote_types('i8', 'f4') == np.dtype('float64')
assert np.promote_types('>i8', '<c8') == np.dtype('complex128')
assert np.promote_types('i4', 'S8') == np.dtype('S11')
+ assert np.promote_types('f4', 'S8') == np.dtype('S32')
def test_can_cast_same_type(space):
dt_bool = get_dtype_cache(space).w_booldtype
diff --git a/pypy/module/micronumpy/types.py b/pypy/module/micronumpy/types.py
--- a/pypy/module/micronumpy/types.py
+++ b/pypy/module/micronumpy/types.py
@@ -721,6 +721,7 @@
class Float(Primitive):
_mixin_ = True
+ strlen = 32
def _coerce(self, space, w_item):
if w_item is None:
@@ -1047,7 +1048,7 @@
else:
return x
-class Float16(BaseType, Float):
+class Float16(Float, BaseType):
_STORAGE_T = rffi.USHORT
T = rffi.SHORT
num = NPY.HALF
@@ -1092,7 +1093,7 @@
hbits = byteswap(hbits)
raw_storage_setitem_unaligned(storage, i + offset, hbits)
-class Float32(BaseType, Float):
+class Float32(Float, BaseType):
T = rffi.FLOAT
num = NPY.FLOAT
kind = NPY.FLOATINGLTR
@@ -1101,7 +1102,7 @@
format_code = "f"
max_value = 3.4e38
-class Float64(BaseType, Float):
+class Float64(Float, BaseType):
T = rffi.DOUBLE
num = NPY.DOUBLE
kind = NPY.FLOATINGLTR
@@ -1112,6 +1113,7 @@
class ComplexFloating(object):
_mixin_ = True
+ strlen = 64
def _coerce(self, space, w_item):
if w_item is None:
@@ -1721,7 +1723,7 @@
ComponentType = Float64
if boxes.long_double_size == 8:
- class FloatLong(BaseType, Float):
+ class FloatLong(Float, BaseType):
T = rffi.DOUBLE
num = NPY.LONGDOUBLE
kind = NPY.FLOATINGLTR
@@ -1739,7 +1741,7 @@
ComponentType = FloatLong
elif boxes.long_double_size in (12, 16):
- class FloatLong(BaseType, Float):
+ class FloatLong(Float, BaseType):
T = rffi.LONGDOUBLE
num = NPY.LONGDOUBLE
kind = NPY.FLOATINGLTR
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