Author: mattip
Branch: numpypy-out
Changeset: r52072:620d218f4ddf
Date: 2012-02-03 15:45 +0200
http://bitbucket.org/pypy/pypy/changeset/620d218f4ddf/
Log: branch to handle "out" arg, first stab at tests and implementation
for reduce functions
diff --git a/pypy/module/micronumpy/interp_numarray.py
b/pypy/module/micronumpy/interp_numarray.py
--- a/pypy/module/micronumpy/interp_numarray.py
+++ b/pypy/module/micronumpy/interp_numarray.py
@@ -131,13 +131,20 @@
descr_rmod = _binop_right_impl("mod")
def _reduce_ufunc_impl(ufunc_name, promote_to_largest=False):
- def impl(self, space, w_axis=None):
+ def impl(self, space, w_axis=None, w_out=None):
if space.is_w(w_axis, space.w_None):
axis = -1
else:
axis = space.int_w(w_axis)
+ if space.is_w(w_out, space.w_None):
+ out = None
+ elif not isinstance(w_out, W_NDimArray):
+ raise OperationError(space.w_TypeError, space.wrap(
+ 'output must be an array'))
+ else:
+ out = w_out
return getattr(interp_ufuncs.get(space), ufunc_name).reduce(space,
- self, True, promote_to_largest, axis)
+ self, True, promote_to_largest, axis,
False, out)
return func_with_new_name(impl, "reduce_%s_impl" % ufunc_name)
descr_sum = _reduce_ufunc_impl("add")
@@ -484,14 +491,14 @@
)
return w_result
- def descr_mean(self, space, w_axis=None):
+ def descr_mean(self, space, w_axis=None, w_out=None):
if space.is_w(w_axis, space.w_None):
w_axis = space.wrap(-1)
w_denom = space.wrap(self.size)
else:
dim = space.int_w(w_axis)
w_denom = space.wrap(self.shape[dim])
- return space.div(self.descr_sum_promote(space, w_axis), w_denom)
+ return space.div(self.descr_sum_promote(space, w_axis, w_out), w_denom)
def descr_var(self, space, w_axis=None):
return get_appbridge_cache(space).call_method(space, '_var', self,
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
@@ -105,28 +105,32 @@
array([[ 1, 5],
[ 9, 13]])
"""
- if not space.is_w(w_out, space.w_None):
- raise OperationError(space.w_NotImplementedError, space.wrap(
- "out not supported"))
if w_axis is None:
axis = 0
elif space.is_w(w_axis, space.w_None):
axis = -1
else:
axis = space.int_w(w_axis)
- return self.reduce(space, w_obj, False, False, axis, keepdims)
+ if space.is_w(w_out, space.w_None):
+ out = None
+ elif not isinstance(w_out, W_NDimArray):
+ raise OperationError(space.w_TypeError, space.wrap(
+ 'output must be an array'))
+ else:
+ out = w_out
+ return self.reduce(space, w_obj, False, False, axis, keepdims, out)
- def reduce(self, space, w_obj, multidim, promote_to_largest, dim,
- keepdims=False):
+ def reduce(self, space, w_obj, multidim, promote_to_largest, axis,
+ keepdims=False, out=None):
from pypy.module.micronumpy.interp_numarray import convert_to_array, \
- Scalar, ReduceArray
+ Scalar, ReduceArray, W_NDimArray
if self.argcount != 2:
raise OperationError(space.w_ValueError, space.wrap("reduce only "
"supported for binary functions"))
assert isinstance(self, W_Ufunc2)
obj = convert_to_array(space, w_obj)
- if dim >= len(obj.shape):
- raise OperationError(space.w_ValueError, space.wrap("axis(=%d) out
of bounds" % dim))
+ if axis >= len(obj.shape):
+ raise OperationError(space.w_ValueError, space.wrap("axis(=%d) out
of bounds" % axis))
if isinstance(obj, Scalar):
raise OperationError(space.w_TypeError, space.wrap("cannot reduce "
"on a scalar"))
@@ -144,21 +148,32 @@
if self.identity is None and size == 0:
raise operationerrfmt(space.w_ValueError, "zero-size array to "
"%s.reduce without identity", self.name)
- if shapelen > 1 and dim >= 0:
- return self.do_axis_reduce(obj, dtype, dim, keepdims)
+ if shapelen > 1 and axis >= 0:
+ if keepdims:
+ shape = obj.shape[:axis] + [1] + obj.shape[axis + 1:]
+ else:
+ shape = obj.shape[:axis] + obj.shape[axis + 1:]
+ if out:
+ #Test for shape agreement
+ return self.do_axis_reduce(obj, 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)
- return loop.compute(arr)
+ 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.setitem(0, out.dtype.coerce(space, val))
+ return out
+ return val
- def do_axis_reduce(self, obj, dtype, dim, keepdims):
- from pypy.module.micronumpy.interp_numarray import AxisReduce,\
- W_NDimArray
- if keepdims:
- shape = obj.shape[:dim] + [1] + obj.shape[dim + 1:]
- else:
- shape = obj.shape[:dim] + obj.shape[dim + 1:]
- result = W_NDimArray(support.product(shape), shape, dtype)
+ def do_axis_reduce(self, obj, dtype, axis, result):
+ from pypy.module.micronumpy.interp_numarray import AxisReduce
arr = AxisReduce(self.func, self.name, self.identity, obj.shape, dtype,
- result, obj, dim)
+ result, obj, axis)
loop.compute(arr)
return arr.left
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
@@ -785,7 +785,7 @@
assert (arange(10).reshape(5, 2).mean(axis=1) == [0.5, 2.5, 4.5, 6.5,
8.5]).all()
def test_sum(self):
- from _numpypy import array
+ from _numpypy import array,zeros
a = array(range(5))
assert a.sum() == 10
assert a[:4].sum() == 6
@@ -794,6 +794,10 @@
assert a.sum() == 5
raises(TypeError, 'a.sum(2, 3)')
+ skip('fails since Scalar is not a subclass of W_NDimArray')
+ d = zeros(())
+ b = a.sum(out=d)
+ assert b == d
def test_reduce_nd(self):
from numpypy import arange, array, multiply
@@ -821,6 +825,14 @@
assert (array([[1,2],[3,4]]).prod(0) == [3, 8]).all()
assert (array([[1,2],[3,4]]).prod(1) == [2, 12]).all()
+ def test_reduce_out(self):
+ from numpypy import arange, array, multiply
+ a = arange(15).reshape(5, 3)
+ b = arange(3)
+ c = a.sum(0, out=b)
+ assert (c == [30, 35, 40]).all()
+ assert (c == b).all()
+
def test_identity(self):
from _numpypy import identity, array
from _numpypy import int32, float64, dtype
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