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numpy.fft.irfft
- fft.irfft(a, n=None, axis=- 1, norm=None)[source]
-
Computes the inverse of
rfft.This function computes the inverse of the one-dimensional n-point discrete Fourier Transform of real input computed by
rfft. In other words,irfft(rfft(a), len(a)) == ato within numerical accuracy. (See Notes below for whylen(a)is necessary here.)The input is expected to be in the form returned by
rfft, i.e. the real zero-frequency term followed by the complex positive frequency terms in order of increasing frequency. Since the discrete Fourier Transform of real input is Hermitian-symmetric, the negative frequency terms are taken to be the complex conjugates of the corresponding positive frequency terms.- Parameters
-
- aarray_like
-
The input array.
- nint, optional
-
Length of the transformed axis of the output. For
noutput points,n//2+1input points are necessary. If the input is longer than this, it is cropped. If it is shorter than this, it is padded with zeros. Ifnis not given, it is taken to be2*(m-1)wheremis the length of the input along the axis specified byaxis. - axisint, optional
-
Axis over which to compute the inverse FFT. If not given, the last axis is used.
- norm{“backward”, “ortho”, “forward”}, optional
-
New in version 1.10.0.
Normalization mode (see
numpy.fft). Default is “backward”. Indicates which direction of the forward/backward pair of transforms is scaled and with what normalization factor.New in version 1.20.0: The “backward”, “forward” values were added.
- Returns
-
- outndarray
-
The truncated or zero-padded input, transformed along the axis indicated by
axis, or the last one ifaxisis not specified. The length of the transformed axis isn, or, ifnis not given,2*(m-1)wheremis the length of the transformed axis of the input. To get an odd number of output points,nmust be specified.
- Raises
-
- IndexError
-
If
axisis not a valid axis ofa.
See also
Notes
Returns the real valued
n-point inverse discrete Fourier transform ofa, whereacontains the non-negative frequency terms of a Hermitian-symmetric sequence.nis the length of the result, not the input.If you specify an
nsuch thatamust be zero-padded or truncated, the extra/removed values will be added/removed at high frequencies. One can thus resample a series tompoints via Fourier interpolation by:a_resamp = irfft(rfft(a), m).The correct interpretation of the hermitian input depends on the length of the original data, as given by
n. This is because each input shape could correspond to either an odd or even length signal. By default,irfftassumes an even output length which puts the last entry at the Nyquist frequency; aliasing with its symmetric counterpart. By Hermitian symmetry, the value is thus treated as purely real. To avoid losing information, the correct length of the real input must be given.Examples
>>> np.fft.ifft([1, -1j, -1, 1j]) array([0.+0.j, 1.+0.j, 0.+0.j, 0.+0.j]) # may vary >>> np.fft.irfft([1, -1j, -1]) array([0., 1., 0., 0.])Notice how the last term in the input to the ordinary
ifftis the complex conjugate of the second term, and the output has zero imaginary part everywhere. When callingirfft, the negative frequencies are not specified, and the output array is purely real.
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https://numpy.org/doc/1.23/reference/generated/numpy.fft.irfft.html