pyrad.util.quantiles_weighted#

pyrad.util.quantiles_weighted(values, weight_vector=None, quantiles=array([0.5]), weight_threshold=None, data_is_log=False, nvalid_min=3)[source]#

Given a set of values and weights, compute the weighted quantile(s) and average.

Parameters:

  • values (array of floats) – Array containing the values. Can be 2-dimensional

  • weight_vector (array of floats or None) – array containing the weights to apply. If None it will be an array of ones (uniform weight). If values is a 2D array it will be repeated for the second dimension

  • quantiles (array of floats) – The quantiles to be computed

  • weight_threshold (float or None) – If weight_threshold is set quantiles will be computed only if the total weight (sum of the weights of valid data) exceeds this threshold

  • data_is_log (Bool) – If true the values will be considered to be in logarithmic scale and transformed into linear scale before computing the quantiles and average

  • nvalid_min (int) – Minimum number of valid points to consider the computation valid

Returns:

  • avg (float) – the weighted average

  • quants (array of floats) – an array containing the weighted quantiles in the same order as the quantiles vector

  • nvalid (int) – Number of valid points in the computation of the statistics