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_compute_virtual_index(n, quantiles, alpha: float, beta: float)

alpha and beta values depend on the chosen method (see quantile documentation)

Reference: Hyndman&Fan paper "Sample Quantiles in Statistical Packages", DOI: 10.1080/00031305.1996.10473566

Compute the floating point indexes of an array for the linear interpolation of quantiles. n : array_like The sample sizes. quantiles : array_like The quantiles values. alpha : float A constant used to correct the index computed. beta : float A constant used to correct the index computed.

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


GitHub : /numpy/lib/function_base.py#4425
type: <class 'function'>
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