From eae57b5f3b596bd55dfaf9b42c2f3259c129bc85 Mon Sep 17 00:00:00 2001 From: Romain Hugonnet Date: Fri, 3 Nov 2023 15:40:37 -0700 Subject: [PATCH] Remove changes from kurtosis --- examples/advanced/plot_standardization.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/examples/advanced/plot_standardization.py b/examples/advanced/plot_standardization.py index 49958ef5..61c89a5f 100644 --- a/examples/advanced/plot_standardization.py +++ b/examples/advanced/plot_standardization.py @@ -45,7 +45,7 @@ maxc_arr = np.maximum(np.abs(planc_arr), np.abs(profc_arr)) # Remove large outliers -dh_arr[np.abs(dh_arr) > 7 * xdem.spatialstats.nmad(dh_arr)] = np.nan +dh_arr[np.abs(dh_arr) > 4 * xdem.spatialstats.nmad(dh_arr)] = np.nan # Define bins for 2D binning custom_bin_slope = np.unique( @@ -97,11 +97,6 @@ z_dh.data[mask_glacier.data] = np.nan z_dh.data[np.abs(z_dh.data) > 4] = np.nan -from scipy.stats import kurtosis -kbef = kurtosis(dh_arr, nan_policy="omit") -kaft = kurtosis(z_dh.flatten(), nan_policy="omit") -print("Excess kurtosis before standardization: {}".format(kbef)) -print("Excess kurtosis after standardization: {}".format(kaft)) # %% # We perform a scale-correction for the standardization, to ensure that the spread of the data is exactly 1.