bundles / numpy 2.4.3 / numpy / lib / stride_tricks / as_strided
function
numpy.lib.stride_tricks:as_strided
Signature
def as_strided ( x , shape = None , strides = None , subok = False , writeable = True ) Summary
Create a view into the array with the given shape and strides.
Extended Summary
Parameters
x: ndarrayArray to create a new.
shape: sequence of int, optionalThe shape of the new array. Defaults to
x.shape.strides: sequence of int, optionalThe strides of the new array. Defaults to
x.strides.subok: bool, optionalIf True, subclasses are preserved.
writeable: bool, optionalIf set to False, the returned array will always be readonly. Otherwise it will be writable if the original array was. It is advisable to set this to False if possible (see Notes).
Returns
view: ndarray
Notes
as_strided creates a view into the array given the exact strides and shape. This means it manipulates the internal data structure of ndarray and, if done incorrectly, the array elements can point to invalid memory and can corrupt results or crash your program. It is advisable to always use the original x.strides when calculating new strides to avoid reliance on a contiguous memory layout.
Furthermore, arrays created with this function often contain self overlapping memory, so that two elements are identical. Vectorized write operations on such arrays will typically be unpredictable. They may even give different results for small, large, or transposed arrays.
Since writing to these arrays has to be tested and done with great care, you may want to use writeable=False to avoid accidental write operations.
For these reasons it is advisable to avoid as_strided when possible.
See also
- broadcast_to
broadcast an array to a given shape.
- lib.stride_tricks.sliding_window_view
userfriendly and safe function for a creation of sliding window views.
- reshape
reshape an array.
Aliases
-
numpy.lib._stride_tricks_impl.as_strided