def apply(self, space, orig_arr):
arr = orig_arr.implementation
ofs, subdtype = arr.dtype.fields[self.name]
# strides backstrides are identical, ofs only changes start
return W_NDimArray.new_slice(space, arr.start + ofs, arr.get_strides(),
arr.get_backstrides(), arr.shape, arr,
orig_arr, subdtype)
def new_view(space, w_arr, chunks):
arr = w_arr.implementation
dim = -1
for i, c in enumerate(chunks):
if isinstance(c, BooleanChunk):
dim = i
break
if dim >= 0:
# filter by axis dim
filtr = chunks[dim]
assert isinstance(filtr, BooleanChunk)
# XXX this creates a new array, and fails in setitem
w_arr = w_arr.getitem_filter(space, filtr.w_idx, axis=dim)
arr = w_arr.implementation
chunks[dim] = SliceChunk(
space.newslice(space.wrap(0), space.w_None, space.w_None))
r = calculate_slice_strides(space, arr.shape, arr.start,
arr.get_strides(), arr.get_backstrides(),
chunks)
else:
r = calculate_slice_strides(space, arr.shape, arr.start,
arr.get_strides(), arr.get_backstrides(),
chunks)
shape, start, strides, backstrides = r
return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
shape[:], arr, w_arr)
def apply(self, space, orig_arr):
arr = orig_arr.implementation
ofs, subdtype = arr.dtype.fields[self.name]
# strides backstrides are identical, ofs only changes start
return W_NDimArray.new_slice(space, arr.start + ofs, arr.get_strides(),
arr.get_backstrides(),
arr.shape, arr, orig_arr, subdtype)
def new_view(space, w_arr, chunks):
arr = w_arr.implementation
r = calculate_slice_strides(space, arr.shape, arr.start, arr.get_strides(),
arr.get_backstrides(), chunks)
shape, start, strides, backstrides = r
return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
shape[:], arr, w_arr)
def apply(self, space, orig_arr):
arr = orig_arr.implementation
shape = self.extend_shape(arr.shape)
r = calculate_slice_strides(arr.shape, arr.start, arr.get_strides(),
arr.get_backstrides(), self.l)
_, start, strides, backstrides = r
return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
shape[:], arr, orig_arr)
def apply(self, space, orig_arr):
arr = orig_arr.implementation
shape = self.extend_shape(arr.shape)
r = calculate_slice_strides(arr.shape, arr.start, arr.get_strides(),
arr.get_backstrides(), self.l)
_, start, strides, backstrides = r
return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
shape[:], arr, orig_arr)
def swapaxes(self, space, orig_arr, axis1, axis2):
shape = self.get_shape()[:]
strides = self.get_strides()[:]
backstrides = self.get_backstrides()[:]
shape[axis1], shape[axis2] = shape[axis2], shape[axis1]
strides[axis1], strides[axis2] = strides[axis2], strides[axis1]
backstrides[axis1], backstrides[axis2] = backstrides[axis2], backstrides[axis1]
return W_NDimArray.new_slice(space, self.start, strides,
backstrides, shape, self, orig_arr)
def swapaxes(self, space, orig_arr, axis1, axis2):
shape = self.get_shape()[:]
strides = self.get_strides()[:]
backstrides = self.get_backstrides()[:]
shape[axis1], shape[axis2] = shape[axis2], shape[axis1]
strides[axis1], strides[axis2] = strides[axis2], strides[axis1]
backstrides[axis1], backstrides[axis2] = backstrides[axis2], backstrides[axis1]
return W_NDimArray.new_slice(space, self.start, strides,
backstrides, shape, self, orig_arr)
def apply(self, space, orig_arr):
arr = orig_arr.implementation
ofs, subdtype = arr.dtype.fields[self.name]
# ofs only changes start
# create a view of the original array by extending
# the shape, strides, backstrides of the array
strides, backstrides = calc_strides(subdtype.shape,
subdtype.subdtype, arr.order)
final_shape = arr.shape + subdtype.shape
final_strides = arr.get_strides() + strides
final_backstrides = arr.get_backstrides() + backstrides
final_dtype = subdtype
if subdtype.subdtype:
final_dtype = subdtype.subdtype
return W_NDimArray.new_slice(space, arr.start + ofs, final_strides,
final_backstrides,
final_shape, arr, orig_arr, final_dtype)
def apply(self, space, orig_arr):
arr = orig_arr.implementation
ofs, subdtype = arr.dtype.fields[self.name]
# ofs only changes start
# create a view of the original array by extending
# the shape, strides, backstrides of the array
strides, backstrides = calc_strides(subdtype.shape, subdtype.subdtype,
arr.order)
final_shape = arr.shape + subdtype.shape
final_strides = arr.get_strides() + strides
final_backstrides = arr.get_backstrides() + backstrides
final_dtype = subdtype
if subdtype.subdtype:
final_dtype = subdtype.subdtype
return W_NDimArray.new_slice(space, arr.start + ofs, final_strides,
final_backstrides, final_shape, arr,
orig_arr, final_dtype)
def new_view(space, w_arr, chunks):
arr = w_arr.implementation
dim = -1
for i, c in enumerate(chunks):
if isinstance(c, BooleanChunk):
dim = i
break
if dim >= 0:
# filter by axis dim
filtr = chunks[dim]
assert isinstance(filtr, BooleanChunk)
# XXX this creates a new array, and fails in setitem
w_arr = w_arr.getitem_filter(space, filtr.w_idx, axis=dim)
arr = w_arr.implementation
chunks[dim] = SliceChunk(space.newslice(space.wrap(0),
space.w_None, space.w_None))
r = calculate_slice_strides(space, arr.shape, arr.start,
arr.get_strides(), arr.get_backstrides(), chunks)
else:
r = calculate_slice_strides(space, arr.shape, arr.start,
arr.get_strides(), arr.get_backstrides(), chunks)
shape, start, strides, backstrides = r
return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
shape[:], arr, w_arr)
