idd_frm(n, w, x)

In contrast to idd_sfrm , this routine works best when the length of the transformed vector is the power-of-two integer output by idd_frmi , or when the length is not specified but instead determined a posteriori from the output. The returned transformed vector is randomly permuted.

paramn

Greatest power-of-two integer satisfying :None:None:`n <= x.size` as obtained from idd_frmi ; :None:None:`n` is also the length of the output vector.

typen

int

paramw

Initialization array constructed by idd_frmi .

typew

numpy.ndarray

paramx

Vector to be transformed.

typex

numpy.ndarray

return

Transformed vector.

rtype

numpy.ndarray

Transform real vector via a composition of Rokhlin's random transform, random subselection, and an FFT.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /scipy/linalg/_interpolative_backend.py#96
type: <class 'function'>
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