_compute_absolute_step(rel_step, x0, f0, method)

Notes

h will always be np.float64. However, if :None:None:`x0` or :None:None:`f0` are smaller floating point dtypes (e.g. np.float32), then the absolute step size will be calculated from the smallest floating point size.

Parameters

rel_step: None or array-like :

Relative step for the finite difference calculation

x0 : np.ndarray

Parameter vector

f0 : np.ndarray or scalar

method : {'2-point', '3-point', 'cs'}

Returns

h : float

The absolute step size

Computes an absolute step from a relative step for finite difference calculation.

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/optimize/_numdiff.py#144
type: <class 'function'>
Commit: