Commit f9c08834 by jansen31

### Merge remote-tracking branch 'origin/dornheim' into dornheim

parents cea9db3b 220d5637
 from math import sqrt, exp from numpy import zeros, angle, tile, mean, conj, reshape, repeat, newaxis, trace from numpy.fft import fft, ifft, fft2, ifft2 from numpy.fft import fft2, ifft2 from proxtoolbox.Utilities import fft, ifft from scipy.linalg import norm from .algorithms import Algorithm import numpy as np ... ...
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 ... ... @@ -29,3 +29,120 @@ def FFT(f): return np.fft.fftshift(F); def fft(a): """ fft(a) Compute the one-dimensional discrete Fourier transform of a the way Matlab does. When a is a vector, the Fourier transform of the vector is returned. When a is a matrix, each column vector of a is transformed individually, and a new matrix containing the transformed column vectors of a is returned. Parameters ---------- a : array_like 1-D or 2-D input array (can be complex) Returns ------- result : ndarray 1-D or 2-D array of similar shape and type containing the discrete fourier transform of a See Also -------- ifft Notes ----- Using the Numpy function fft on a matrix does not produce results similar to what Matlab does. This helper function uses the Numpy functions to produce a resut that agrees with what Matlab does. """ return transformVectors(a, np.fft.fft) def ifft(a): """ ifft(a) Compute the one-dimensional inverse discrete Fourier transform the way Matlab does. When a is a vector, the inverse Fourier transform of the vector is returned. When a is a matrix, each column vector of a is transformed individually, and a new matrix containing the transformed column vectors of a is returned. Parameters ---------- a : array_like 1-D or 2-D input array (can be complex) Returns ------- out : ndarray 1-D or 2-D array of similar shape and type containing the inverse discrete fourier transform of a See Also -------- fft Notes ----- Using the Numpy function ifft on a matrix does not produce results similar to what Matlab does. This helper function uses the Numpy functions to produce a resut that agrees with what Matlab does. """ return transformVectors(a, np.fft.ifft) def transformVectors(a, transform): """ transformVectors(a, transform) Transform a according to the given transform function. When a is a vector, it applies the transform function to a and returns the result. When a is a matrix, each column vector of a is transformed individually using the given transform function, and a new matrix containing the transformed column vectors of a is returned. Parameters ---------- a : array_like 1-D or 2-D input array transform : callable function This function takes a 1-D array as argument and returns a 1-D array of same size. This function is applied to a if it is a vector or to the column vectors of a if a is a matrix. Returns ------- out : ndarray 1-D or 2-D array of similar shape and type containing the transformed data See Also -------- fft, ifft Notes ----- This function is used by fft(a) and ifft(a). """ if a.ndim == 1: # a is a vector out = transform(a) else: # assume a is a matrix (2d array) shape = a.shape colCount = shape[1] #result = np.empty_like(a) out = np.zeros_like(a) # for each column vector in a for i in range(0, colCount): col = a[:,i] fft_col = transform(col) out[:,i] = fft_col return out
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