fft¶
- fft(x: array, /, *, n: int | None = None, axis: int = -1, norm: Literal['backward', 'ortho', 'forward'] = 'backward') array ¶
Computes the one-dimensional discrete Fourier transform.
Note
Applying the one-dimensional inverse discrete Fourier transform to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e.,
ifft(fft(x)) == x
), provided that the transform and inverse transform are performed with the same arguments (number of elements, axis, and normalization mode).- Parameters:
x (array) – input array. Should have a complex floating-point data type.
n (Optional[int]) –
number of elements over which to compute the transform along the axis (dimension) specified by
axis
. LetM
be the size of the input array along the axis specified byaxis
. Whenn
isNone
, the function must setn
equal toM
.If
n
is greater thanM
, the axis specified byaxis
must be zero-padded to sizen
.If
n
is less thanM
, the axis specified byaxis
must be trimmed to sizen
.If
n
equalsM
, all elements along the axis specified byaxis
must be used when computing the transform.
Default:
None
.axis (int) – axis (dimension) of the input array over which to compute the transform. A valid
axis
must be an integer on the interval[-N, N)
, whereN
is the rank (number of dimensions) ofx
. If anaxis
is specified as a negative integer, the function must determine the axis along which to compute the transform by counting backward from the last dimension (where-1
refers to the last dimension). Default:-1
.norm (Literal['backward', 'ortho', 'forward']) –
normalization mode. Should be one of the following modes:
'backward'
: no normalization.'ortho'
: normalize by1/sqrt(n)
(i.e., make the FFT orthonormal).'forward'
: normalize by1/n
.
Default:
'backward'
.
- Returns:
out (array) – an array transformed along the axis (dimension) specified by
axis
. The returned array must have the same data type asx
and must have the same shape asx
, except for the axis specified byaxis
which must have sizen
.
Notes
New in version 2022.12.
Changed in version 2023.12: Required the input array have a complex floating-point data type and required that the output array have the same data type as the input array.