scipy.fft.

ifht#

scipy.fft.ifht(A, dln, mu, offset=0.0, bias=0.0)[source]#

Compute the inverse fast Hankel transform.

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

Parameters:
Aarray_like (…, n)

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

dlnfloat

Uniform logarithmic spacing of the input array.

mufloat

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

offsetfloat, optional

Offset of the uniform logarithmic spacing of the output array.

biasfloat, optional

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

Returns:
aarray_like (…, n)

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

fht

Definition of the fast Hankel transform.

fhtoffset

Return an optimal offset for ifht.

Notes

This function computes a discrete version of the Hankel transform

$a(r) = \int_{0}^{\infty} \! A(k) \, J_\mu(kr) \, r \, dk \;,$

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

See fht for further details.