scipy.fftpack.irfft¶
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scipy.fftpack.irfft(x, n=None, axis=-1, overwrite_x=False)[source]¶
- Return inverse discrete Fourier transform of real sequence x. - The contents of x are interpreted as the output of the - rfftfunction.- Parameters: - x : array_like
- Transformed data to invert. 
- n : int, optional
- Length of the inverse Fourier transform. If n < x.shape[axis], x is truncated. If n > x.shape[axis], x is zero-padded. The default results in n = x.shape[axis]. 
- axis : int, optional
- Axis along which the ifft’s are computed; the default is over the last axis (i.e., axis=-1). 
- overwrite_x : bool, optional
- If True, the contents of x can be destroyed; the default is False. 
 - Returns: - irfft : ndarray of floats
- The inverse discrete Fourier transform. 
 - See also - Notes - The returned real array contains: - [y(0),y(1),...,y(n-1)] - where for n is even: - y(j) = 1/n (sum[k=1..n/2-1] (x[2*k-1]+sqrt(-1)*x[2*k]) * exp(sqrt(-1)*j*k* 2*pi/n) + c.c. + x[0] + (-1)**(j) x[n-1]) - and for n is odd: - y(j) = 1/n (sum[k=1..(n-1)/2] (x[2*k-1]+sqrt(-1)*x[2*k]) * exp(sqrt(-1)*j*k* 2*pi/n) + c.c. + x[0]) - c.c. denotes complex conjugate of preceding expression. - For details on input parameters, see - rfft.- To process (conjugate-symmetric) frequency-domain data with a complex datatype, consider using the related function - numpy.fft.irfft.
