wind_validation.ts.metrics.TimeSeriesMetrics.FUNC_MAPPER

TimeSeriesMetrics.FUNC_MAPPER = {'circular_median_absolute_error': <function circular_median_absolute_error>, 'cmae': <function cmae>, 'cme': <function cme>, 'crmse': <function crmse>, 'effective_sample_size': functools.partial(<function effective_sample_size>, skipna=True), 'mae': functools.partial(<function me>, abs=True), 'mape': functools.partial(<function me>, percent=True, abs=True), 'me': <function me>, 'median_absolute_error': functools.partial(<function median_absolute_error>, skipna=True), 'mpe': functools.partial(<function me>, percent=True), 'mse': functools.partial(<function mse>, skipna=True), 'pearson_r': functools.partial(<function pearson_r>, skipna=True), 'pearson_r_eff_p_value': functools.partial(<function pearson_r_eff_p_value>, skipna=True), 'pearson_r_p_value': functools.partial(<function pearson_r_p_value>, skipna=True), 'r2': functools.partial(<function r2>, skipna=True), 'rmse': functools.partial(<function rmse>, skipna=True), 'smape': functools.partial(<function smape>, skipna=True), 'spearman_r': functools.partial(<function spearman_r>, skipna=True), 'spearman_r_eff_p_value': functools.partial(<function spearman_r_eff_p_value>, skipna=True), 'spearman_r_p_value': functools.partial(<function spearman_r_p_value>, skipna=True)}