Author: mattip
Branch: numpypy-out
Changeset: r52403:4dad485d2e24
Date: 2012-02-12 23:20 +0200
http://bitbucket.org/pypy/pypy/changeset/4dad485d2e24/
Log: never create intermediates, add tests to verify
diff --git a/pypy/module/micronumpy/interp_ufuncs.py
b/pypy/module/micronumpy/interp_ufuncs.py
--- a/pypy/module/micronumpy/interp_ufuncs.py
+++ b/pypy/module/micronumpy/interp_ufuncs.py
@@ -168,22 +168,23 @@
'output parameter shape mismatch, expecting %s' +
' , got %s', str(shape), str(out.shape))
#Test for dtype agreement, perhaps create an itermediate
- if out.dtype != dtype
- raise OperationError(space.w_TypeError, space.wrap(
- "mismatched dtypes"))
- return self.do_axis_reduce(obj, dtype, axis, out)
+ #if out.dtype != dtype:
+ # raise OperationError(space.w_TypeError, space.wrap(
+ # "mismatched dtypes"))
+ return self.do_axis_reduce(obj, out.find_dtype(), axis, out)
else:
result = W_NDimArray(support.product(shape), shape, dtype)
return self.do_axis_reduce(obj, dtype, axis, result)
- arr = ReduceArray(self.func, self.name, self.identity, obj, dtype)
- val = loop.compute(arr)
if out:
if len(out.shape)>0:
raise operationerrfmt(space.w_ValueError, "output parameter "
"for reduction operation %s has too many"
" dimensions",self.name)
- out.value = out.dtype.coerce(space, val)
- return out
+ arr = ReduceArray(self.func, self.name, self.identity, obj,
+ out.find_dtype())
+ else:
+ arr = ReduceArray(self.func, self.name, self.identity, obj, dtype)
+ val = loop.compute(arr)
return val
def do_axis_reduce(self, obj, dtype, axis, result):
diff --git a/pypy/module/micronumpy/signature.py
b/pypy/module/micronumpy/signature.py
--- a/pypy/module/micronumpy/signature.py
+++ b/pypy/module/micronumpy/signature.py
@@ -441,6 +441,5 @@
cur = arr.left.getitem(iterator.offset)
value = self.binfunc(self.calc_dtype, cur, v)
arr.left.setitem(iterator.offset, value)
-
def debug_repr(self):
return 'AxisReduceSig(%s, %s)' % (self.name, self.right.debug_repr())
diff --git a/pypy/module/micronumpy/test/test_numarray.py
b/pypy/module/micronumpy/test/test_numarray.py
--- a/pypy/module/micronumpy/test/test_numarray.py
+++ b/pypy/module/micronumpy/test/test_numarray.py
@@ -896,7 +896,7 @@
assert (array([[1,2],[3,4]]).prod(1) == [2, 12]).all()
def test_reduce_out(self):
- from numpypy import arange, array
+ from numpypy import arange, zeros, array
a = arange(15).reshape(5, 3)
b = arange(12).reshape(4,3)
c = a.sum(0, out=b[1])
@@ -906,6 +906,16 @@
a=arange(12).reshape(3,2,2)
raises(ValueError, 'a.sum(0, out=arange(12).reshape(3,2,2))')
raises(ValueError, 'a.sum(0, out=arange(3))')
+ c = array([-1, 0, 1]).sum(out=zeros([], dtype=bool))
+ #You could argue that this should product False, but
+ # that would require an itermediate result. Cpython numpy
+ # gives True.
+ assert c == True
+ a = array([[-1, 0, 1], [1, 0, -1]])
+ c = a.sum(0, out=zeros((3,), dtype=bool))
+ assert (c == [True, False, True]).all()
+ c = a.sum(1, out=zeros((2,), dtype=bool))
+ assert (c == [True, True]).all()
def test_reduce_intermediary(self):
from numpypy import arange, array
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