iq_readout.pdfs

Module containing the probability density functions used in the classifiers.

The probability density functions have been implemented keeping in mind that they will be used for fitting using scipy.optimize.curve_fit, thus all its arguments are split into scalars while the input points have been grouped into a single multidimensional variable.

Functions

decay_amplitude_1d_pdf(x, mu_0, mu_1, sigma, ...)	Probability density function observed when considering amplitude decay during the measurement.
decay_amplitude_2d_pdf(z, mu_0_x, mu_0_y, ...)	Probability density function corresponding to a decay_amplitude_1d_pdf in the (parallel) projected axis along mu_0 and mu_1 and a simple_1d_gaussian in the perpendicular dimension
pdf_from_hist1d(x, bins, pdf_values)	Returns the PDF value from the 1D histogram bins closest to x.
pdf_from_hist2d(z, bins_x, bins_y, pdf_values)	Returns the PDF value from the 2D histogram bins closest to x.
simple_1d_gaussian(x, mu, sigma)	Probability density function of a 1D Gaussian.
simple_1d_gaussian_double_mixture(x, mu_0, ...)	Probability density function corresponding to the sum of two 1D Gaussians with the same standard deviation.
simple_2d_gaussian(z, mu_x, mu_y, sigma)	Probability density function of a 2D Gaussian.
simple_2d_gaussian_double_mixture(z, mu_0_x, ...)	Probability density function corresponding to the sum of two 2D Gaussians.
simple_2d_gaussian_triple_mixture(z, mu_0_x, ...)	Probability density function corresponding to the sum of three 2D Gaussians.