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bundles / scipy latest / scipy / fft / _fftlog / ifht

_Function

scipy.fft._fftlog:ifht

source: /scipy/fft/_fftlog.py :179

Signature

def   ifht ( A ,  dln ,  mu ,  offset = 0.0 ,  bias = 0.0 )

Summary

Compute the inverse fast Hankel transform.

Extended Summary

Computes the discrete inverse Hankel transform of a logarithmically spaced periodic sequence. This is the inverse operation to fht.

Parameters

A : array_like (..., n)

Real periodic input array, uniformly logarithmically spaced. For multidimensional input, the transform is performed over the last axis.

dln : float

Uniform logarithmic spacing of the input array.

mu : float

Order of the Hankel transform, any positive or negative real number.

offset : float, optional

Offset of the uniform logarithmic spacing of the output array.

bias : float, optional

Exponent of power law bias, any positive or negative real number.

Returns

a : array_like (..., n)

The transformed output array, which is real, periodic, uniformly logarithmically spaced, and of the same shape as the input array.

Notes

This function computes a discrete version of the Hankel transform

where is the Bessel function of order . The index may be any real number, positive or negative. Note that the numerical inverse Hankel transform uses an integrand of , while the mathematical inverse Hankel transform is commonly defined using .

See fht for further details.

Array API Standard Support

ifht has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ✅                   
PyTorch               ✅                     ✅                   
JAX                   ✅                     ✅                   
Dask                  ⚠️ computes graph     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

See also

fht

Definition of the fast Hankel transform.

fhtoffset

Return an optimal offset for ifht.

Aliases

  • scipy.fft.ifht

Referenced by

This package