Repository: climate Updated Branches: refs/heads/master bb61395ce -> 43b04e4f0
CLIMATE-849 - Adding joint histogram calculation to the metrics module - calc_histogram_overlap and calc_joint_histogram have been added to ocw.metrics. Project: http://git-wip-us.apache.org/repos/asf/climate/repo Commit: http://git-wip-us.apache.org/repos/asf/climate/commit/61fd42ef Tree: http://git-wip-us.apache.org/repos/asf/climate/tree/61fd42ef Diff: http://git-wip-us.apache.org/repos/asf/climate/diff/61fd42ef Branch: refs/heads/master Commit: 61fd42efa79e6df4d83c24a6e36534fb6a43b9e5 Parents: 05519e1 Author: huikyole <huiky...@argo.jpl.nasa.gov> Authored: Mon Aug 15 16:04:55 2016 -0700 Committer: huikyole <huiky...@argo.jpl.nasa.gov> Committed: Mon Aug 15 16:04:55 2016 -0700 ---------------------------------------------------------------------- ocw/metrics.py | 42 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 42 insertions(+) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/climate/blob/61fd42ef/ocw/metrics.py ---------------------------------------------------------------------- diff --git a/ocw/metrics.py b/ocw/metrics.py index 62f4e3d..0d79928 100644 --- a/ocw/metrics.py +++ b/ocw/metrics.py @@ -346,3 +346,45 @@ def calc_rmse(target_array, reference_array): ''' return (ma.mean((calc_bias(target_array, reference_array))**2))**0.5 + +def calc_histogram_overlap(hist1, hist2): + ''' from Lee et al. (2014) + :param hist1: a histogram array + :type hist1: :class:'numpy.ndarray' + :param hist2: a histogram array with the same size as hist1 + :type hist2: :class:'numpy.ndarray' + ''' + + hist1_flat = hist1.flatten() + hist2_flat = hist2.flatten() + + if len(hist1_flat) != len(hist2_flat): + err = "The two histograms have different sizes" + raise ValueError(err) + overlap = 0. + for ii in len(hist1_flat): + overlap = overlap + numpy.min(hist1_flat[ii], hist2_flat[ii]) + return overlap + +def calc_joint_histogram(data_array1, data_array2, bins_for_data1, bins_for_data2): + ''' Calculate a joint histogram of two variables in data_array1 and data_array2 + :param data_array1: the first variable + :type data_array1: :class:'numpy.ma.core.MaskedArray' + :param data_array2: the second variable + :type data_array2: :class:'numpy.ma.core.MaskedArray' + :param bins_for_data1: histogram bin edges for data_array1 + :type bins_for_data1: :class:'numpy.ndarray' + :param bins_for_data2: histogram bin edges for data_array2 + :type bins_for_data2: :class:'numpy.ndarray' + ''' + if ma.count_masked(data_array1)!=0 or ma.count_masked(data_array2)!=0: + index = numpy.where((data_array1.mask == False) & (data_array2.mask==False)) + new_array1 = data_array1[index] + new_array2 = data_array2[index] + else: + new_array1 = data_array1.flatten() + new_array2 = data_array2.flatten() + + histo2d, xedge, yedge = numpy.histogram2d(new_array1, new_array2, bins=[bins_for_data1, bins_for_data2]) + return histo2d +
