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i0(x)

Usually denoted $I_0$ .

Notes

The scipy implementation is recommended over this function: it is a proper ufunc written in C, and more than an order of magnitude faster.

We use the algorithm published by Clenshaw and referenced by Abramowitz and Stegun , for which the function domain is partitioned into the two intervals [0,8] and (8,inf), and Chebyshev polynomial expansions are employed in each interval. Relative error on the domain [0,30] using IEEE arithmetic is documented as having a peak of 5.8e-16 with an rms of 1.4e-16 (n = 30000).

Parameters

x : array_like of float

Argument of the Bessel function.

Returns

out : ndarray, shape = x.shape, dtype = float

The modified Bessel function evaluated at each of the elements of x.

Modified Bessel function of the first kind, order 0.

See Also

scipy.special.i0
scipy.special.iv
scipy.special.ive

Examples

>>> np.i0(0.)
array(1.0)
>>> np.i0([0, 1, 2, 3])
array([1.        , 1.26606588, 2.2795853 , 4.88079259])
See :

Local connectivity graph

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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#3343
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