def do_axis_reduce(self, obj, dtype, dim):
from pypy.module.micronumpy.interp_numarray import AxisReduce,\
W_NDimArray
shape = obj.shape[0:dim] + obj.shape[dim + 1:len(obj.shape)]
size = 1
for s in shape:
size *= s
result = W_NDimArray(size, shape, dtype)
rightsig = obj.create_sig()
# note - this is just a wrapper so signature can fetch
# both left and right, nothing more, especially
# this is not a true virtual array, because shapes
# don't quite match
arr = AxisReduce(self.func, self.name, obj.shape, dtype, result, obj,
dim)
scalarsig = ScalarSignature(dtype)
sig = find_sig(
AxisReduceSignature(self.func, self.name, dtype, scalarsig,
rightsig), arr)
assert isinstance(sig, AxisReduceSignature)
frame = sig.create_frame(arr)
shapelen = len(obj.shape)
if self.identity is not None:
identity = self.identity.convert_to(dtype)
else:
identity = None
self.reduce_axis_loop(frame, sig, shapelen, arr, identity)
return result
def do_axis_reduce(self, obj, dtype, dim):
from pypy.module.micronumpy.interp_numarray import AxisReduce,\
W_NDimArray
shape = obj.shape[0:dim] + obj.shape[dim + 1:len(obj.shape)]
size = 1
for s in shape:
size *= s
result = W_NDimArray(size, shape, dtype)
rightsig = obj.create_sig()
# note - this is just a wrapper so signature can fetch
# both left and right, nothing more, especially
# this is not a true virtual array, because shapes
# don't quite match
arr = AxisReduce(self.func, self.name, obj.shape, dtype,
result, obj, dim)
scalarsig = ScalarSignature(dtype)
sig = find_sig(AxisReduceSignature(self.func, self.name, dtype,
scalarsig, rightsig), arr)
assert isinstance(sig, AxisReduceSignature)
frame = sig.create_frame(arr)
shapelen = len(obj.shape)
if self.identity is not None:
identity = self.identity.convert_to(dtype)
else:
identity = None
self.reduce_axis_loop(frame, sig, shapelen, arr, identity)
return result
def reduce(self, space, w_obj, multidim, promote_to_largest, w_dim):
from pypy.module.micronumpy.interp_numarray import convert_to_array, \
Scalar
if self.argcount != 2:
raise OperationError(
space.w_ValueError,
space.wrap("reduce only "
"supported for binary functions"))
dim = space.int_w(w_dim)
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 isinstance(obj, Scalar):
raise OperationError(space.w_TypeError,
space.wrap("cannot reduce "
"on a scalar"))
size = obj.size
dtype = find_unaryop_result_dtype(
space,
obj.find_dtype(),
promote_to_float=self.promote_to_float,
promote_to_largest=promote_to_largest,
promote_bools=True)
shapelen = len(obj.shape)
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:
res = self.do_axis_reduce(obj, dtype, dim)
return space.wrap(res)
scalarsig = ScalarSignature(dtype)
sig = find_sig(
ReduceSignature(self.func, self.name, dtype, scalarsig,
obj.create_sig()), obj)
frame = sig.create_frame(obj)
if self.identity is None:
value = sig.eval(frame, obj).convert_to(dtype)
frame.next(shapelen)
else:
value = self.identity.convert_to(dtype)
return self.reduce_loop(shapelen, sig, frame, value, obj, dtype)
def reduce(self, space, w_obj, multidim, promote_to_largest, w_dim):
from pypy.module.micronumpy.interp_numarray import convert_to_array, \
Scalar
if self.argcount != 2:
raise OperationError(space.w_ValueError, space.wrap("reduce only "
"supported for binary functions"))
dim = space.int_w(w_dim)
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 isinstance(obj, Scalar):
raise OperationError(space.w_TypeError, space.wrap("cannot reduce "
"on a scalar"))
size = obj.size
dtype = find_unaryop_result_dtype(
space, obj.find_dtype(),
promote_to_float=self.promote_to_float,
promote_to_largest=promote_to_largest,
promote_bools=True
)
shapelen = len(obj.shape)
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:
res = self.do_axis_reduce(obj, dtype, dim)
return space.wrap(res)
scalarsig = ScalarSignature(dtype)
sig = find_sig(ReduceSignature(self.func, self.name, dtype,
scalarsig,
obj.create_sig()), obj)
frame = sig.create_frame(obj)
if self.identity is None:
value = sig.eval(frame, obj).convert_to(dtype)
frame.next(shapelen)
else:
value = self.identity.convert_to(dtype)
return self.reduce_loop(shapelen, sig, frame, value, obj, dtype)
def find_sig(self, res_shape=None, arr=None):
""" find a correct signature for the array
"""
res_shape = res_shape or self.shape
arr = arr or self
return signature.find_sig(self.create_sig(), arr)
def find_sig(self, res_shape=None, arr=None):
""" find a correct signature for the array
"""
res_shape = res_shape or self.shape
arr = arr or self
return signature.find_sig(self.create_sig(), arr)