pygsti.extras.drift.signal.dft

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pygsti.extras.drift.signal.dft#

dft(x, null_hypothesis=None, counts=1)#

Returns the discrete Fourier transform of y, with a unitary normalization, where y is an array with elements related to the x array by

y = (x - counts * null_hypothesis) / sqrt(counts * null_hypothesis * (1-null_hypothesis)),

where the arithmetic is element-wise, and null_hypothesis is a vector in (0,1). If null_hypothesis is None it is set to the mean of x. If that mean is 0 or 1 then the vector of all ones, except for the first element which is set to zero, is returned.

Parameters:

  • x (array) – Data string, on which the normalization and discrete cosine transformation is performed. If counts is not specified, this must be a bit string.

  • null_hypothesis (array, optional) – If not None, an array to use in the normalization before the dct. If None, it is taken to be an array in which every element is the mean of x.

  • counts (int, optional) – A factor in the normalization, that should correspond to the counts-per-timestep (so for full time resolution this is 1).

Returns:

The DFT modes described above.

Return type:

array

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