def choose(space, w_arr, w_choices, w_out, w_mode):
arr = convert_to_array(space, w_arr)
choices = [convert_to_array(space, w_item) for w_item in space.listview(w_choices)]
if not choices:
raise oefmt(space.w_ValueError, "choices list cannot be empty")
if space.is_none(w_out):
w_out = None
elif not isinstance(w_out, W_NDimArray):
raise OperationError(space.w_TypeError, space.wrap("return arrays must be of ArrayType"))
shape = shape_agreement_multiple(space, choices + [w_out])
out = descriptor.dtype_agreement(space, choices, shape, w_out)
dtype = out.get_dtype()
mode = clipmode_converter(space, w_mode)
loop.choose(space, arr, choices, shape, dtype, out, mode)
return out
def put(space, w_arr, w_indices, w_values, w_mode):
arr = convert_to_array(space, w_arr)
mode = clipmode_converter(space, w_mode)
if not w_indices:
raise oefmt(space.w_ValueError, "indices list cannot be empty")
if not w_values:
raise oefmt(space.w_ValueError, "value list cannot be empty")
dtype = arr.get_dtype()
if space.isinstance_w(w_indices, space.w_list):
indices = space.listview(w_indices)
else:
indices = [w_indices]
if space.isinstance_w(w_values, space.w_list):
values = space.listview(w_values)
else:
values = [w_values]
v_idx = 0
for idx in indices:
index = support.index_w(space, idx)
if index < 0 or index >= arr.get_size():
if mode == NPY.RAISE:
raise oefmt(
space.w_IndexError,
"index %d is out of bounds for axis 0 with size %d", index,
arr.get_size())
elif mode == NPY.WRAP:
index = index % arr.get_size()
elif mode == NPY.CLIP:
if index < 0:
index = 0
else:
index = arr.get_size() - 1
else:
assert False
value = values[v_idx]
if v_idx + 1 < len(values):
v_idx += 1
arr.setitem(space, [index], dtype.coerce(space, value))
def put(space, w_arr, w_indices, w_values, w_mode):
arr = convert_to_array(space, w_arr)
mode = clipmode_converter(space, w_mode)
if not w_indices:
raise oefmt(space.w_ValueError, "indices list cannot be empty")
if not w_values:
raise oefmt(space.w_ValueError, "value list cannot be empty")
dtype = arr.get_dtype()
if space.isinstance_w(w_indices, space.w_list):
indices = space.listview(w_indices)
else:
indices = [w_indices]
if space.isinstance_w(w_values, space.w_list):
values = space.listview(w_values)
else:
values = [w_values]
v_idx = 0
for idx in indices:
index = support.index_w(space, idx)
if index < 0 or index >= arr.get_size():
if mode == NPY.RAISE:
raise oefmt(space.w_IndexError,
"index %d is out of bounds for axis 0 with size %d",
index, arr.get_size())
elif mode == NPY.WRAP:
index = index % arr.get_size()
elif mode == NPY.CLIP:
if index < 0:
index = 0
else:
index = arr.get_size() - 1
else:
assert False
value = values[v_idx]
if v_idx + 1 < len(values):
v_idx += 1
arr.setitem(space, [index], dtype.coerce(space, value))
def choose(space, w_arr, w_choices, w_out, w_mode):
arr = convert_to_array(space, w_arr)
choices = [convert_to_array(space, w_item) for w_item
in space.listview(w_choices)]
if not choices:
raise oefmt(space.w_ValueError, "choices list cannot be empty")
if space.is_none(w_out):
w_out = None
elif not isinstance(w_out, W_NDimArray):
raise OperationError(space.w_TypeError, space.wrap(
"return arrays must be of ArrayType"))
shape = shape_agreement_multiple(space, choices + [w_out])
out = descriptor.dtype_agreement(space, choices, shape, w_out)
dtype = out.get_dtype()
mode = clipmode_converter(space, w_mode)
loop.choose(space, arr, choices, shape, dtype, out, mode)
return out
