wradlib Documentation - Bitbucket

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wradlib Documentation, Release 0.1.1 wradlib.verify.ErrorMetrics.spearman ErrorMetrics.spearman() Spearman rank correlation coefficient wradlib.verify.ErrorMetrics.sse ErrorMetrics.sse() Sum of Squared Errors all() corr() mas() meanerr() mse() nash() plot([ax, unit, maxval]) pprint() r2() ratio() report([metrics, ax, unit, maxval]) rmse() spearman() sse() Returns a dictionary of all error metrics Correlation coefficient Mean Absolute Error Mean Error Mean Squared Error Nash-Sutcliffe Efficiency Scatter plot of estimates vs observations Pretty prints a summary of error metrics Coefficient of determination Mean ratio between observed and estimated Pretty prints selected error metrics over a scatter plot Root Mean Squared Error Spearman rank correlation coefficient Sum of Squared Errors wradlib.verify.ErrorMetrics.all ErrorMetrics.all() Returns a dictionary of all error metrics wradlib.verify.ErrorMetrics.corr ErrorMetrics.corr() Correlation coefficient wradlib.verify.ErrorMetrics.mas ErrorMetrics.mas() Mean Absolute Error wradlib.verify.ErrorMetrics.meanerr ErrorMetrics.meanerr() Mean Error wradlib.verify.ErrorMetrics.mse ErrorMetrics.mse() Mean Squared Error 82 Chapter 3. Library Reference
wradlib Documentation, Release 0.1.1 wradlib.verify.ErrorMetrics.nash ErrorMetrics.nash() Nash-Sutcliffe Efficiency wradlib.verify.ErrorMetrics.plot ErrorMetrics.plot(ax=None, unit=’‘, maxval=None) Scatter plot of estimates vs observations Parameters ax : a matplotlib axes object to plot on if None, a new axes object will be created unit : string measurement unit of the observations / estimates wradlib.verify.ErrorMetrics.pprint ErrorMetrics.pprint() Pretty prints a summary of error metrics wradlib.verify.ErrorMetrics.r2 ErrorMetrics.r2() Coefficient of determination wradlib.verify.ErrorMetrics.ratio ErrorMetrics.ratio() Mean ratio between observed and estimated wradlib.verify.ErrorMetrics.report ErrorMetrics.report(metrics=[’rmse’, ‘nash’, ‘meanerr’], ax=None, unit=’‘, maxval=None) Pretty prints selected error metrics over a scatter plot Parameters metrics : sequence of strings names of the metrics which should be included in the report defaults to [”rmse”,”r2”,”meanerr”] ax : a matplotlib axes object to plot on if None, a new axes object will be created unit : string measurement unit of the observations / estimates wradlib.verify.ErrorMetrics.rmse ErrorMetrics.rmse() Root Mean Squared Error 3.14. Verification 83
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