edges_analysis.averaging.averaging

Methods for averaging arrays.

There are multiple methods in this module, due to the need for careful averages/binning done in different ways. There are ultimately three axes over which we might bin spectra: nights, LST/GHA and frequency. Each of these in fact requires slightly different methods for averaging, in order to make the average unbiased (given flags).

Functions

bin_array_biased_regular(data[, weights, ...])	Bin arbitrary-dimension data carefully along an axis.
bin_array_unbiased_irregular(data[, ...])	Bin arbitrary-dimension data carefully along an axis.
bin_data(data[, residuals, weights, bins, axis])	Bin data, in an un-biased way if possible.
bin_freq_unbiased_irregular(spectrum[, ...])	Average a spectrum, with weights, in frequency.
bin_freq_unbiased_regular(model, params, ...)	Bin an array along the frequency axis into regular bins.
bin_gha_unbiased_regular(params, resids, ...)	Bin data in an unbiased way using a model fit.
bin_spectrum_unbiased_regular(params, ...[, ...])	Bin a spectrum in GHA and frequency in an unbiased and regular manner.
get_bin_edges(coords[, bins, start, stop])	Get bin edges given input coordinates and a simple description of the binning.
get_binned_weights(x, bins[, weights])	Get the total weight in each bin for a given vector.
weighted_mean(data[, weights, axis])	A careful weighted mean where zero-weights don't error.
weighted_sorted_metric(data[, weights, metric])	Semi-weighted integrator of data.
weighted_standard_deviation(av, data, std[, ...])	Calcualte a careful weighted standard deviation.
weighted_sum(data[, weights, normalize, axis])	A careful weighted sum.