eemeter-3.1.0/tests/test_metrics.py

57     assert round(model_metrics.observed_skew, 3) == 0.524
58     assert round(model_metrics.predicted_skew, 3) == 0.512
59     assert round(model_metrics.observed_kurtosis, 3) == -0.963
60     assert round(model_metrics.predicted_kurtosis, 3) == -0.612
61     assert round(model_metrics.observed_cvstd, 3) == 0.707
62     assert round(model_metrics.predicted_cvstd, 3) == 0.299
63     assert round(model_metrics.r_squared, 3) == 0.972
64     assert round(model_metrics.r_squared_adj, 3) == 0.944
65     assert round(model_metrics.cvrmse, 3) == 0.394
66     assert round(model_metrics.cvrmse_adj, 3) == 0.509
67     assert round(model_metrics.mape, 3) == 0.517
68     assert round(model_metrics.mape_no_zeros, 3) == 0.517
70     assert round(model_metrics.nmae, 3) == 0.333
71     assert round(model_metrics.nmbe, 3) == -0.067
72     assert round(model_metrics.autocorr_resid, 3) == -0.674
73     assert round(model_metrics.n_prime, 3) == 25.694
74     assert round(model_metrics.single_tailed_confidence_level, 3) == 0.95
75     assert round(model_metrics.degrees_of_freedom, 3) == 24
76     assert round(model_metrics.t_stat, 3) == 1.711
77     assert round(model_metrics.cvrmse_auto_corr_correction, 3) == 0.356
78     assert round(model_metrics.approx_factor_auto_corr_correction, 3) == 1.038
255     assert round(_compute_r_squared(combined), 3) == 0.972
260     assert round(_compute_r_squared_adj(_compute_r_squared(combined), 5, 2), 3) == 0.944
266     assert round(_compute_cvrmse(_compute_rmse(combined), observed_mean), 3) == 0.394
275     assert round(_compute_cvrmse_adj(rmse_adj, observed_mean), 3) == 0.509
280     assert round(_compute_mape(combined), 3) == 0.517
285     assert round(_compute_nmae(combined), 3) == 0.333
290     assert round(_compute_nmbe(combined), 3) == -0.067
295     assert round(_compute_autocorr_resid(combined, 1), 3) == -0.674
327     assert round(totals_metrics["observed_length"], 3) == 3.000
328     assert round(totals_metrics["predicted_length"], 3) == 3.000
329     assert round(totals_metrics["merged_length"], 3) == 3.000
330     assert round(totals_metrics["num_parameters"], 3) == 0
331     assert round(totals_metrics["observed_mean"], 3) == 2.667
332     assert round(totals_metrics["predicted_mean"], 3) == 3.5
333     assert round(totals_metrics["observed_variance"], 3) == 5.556
334     assert round(totals_metrics["predicted_variance"], 3) == 0
335     assert round(totals_metrics["observed_skew"], 3) == 1.732
336     assert round(totals_metrics["predicted_skew"], 3) == 0
337     assert round(totals_metrics["observed_cvstd"], 3) == 1.083
338     assert round(totals_metrics["predicted_cvstd"], 3) == 0
339     assert round(totals_metrics["rmse"], 3) == 2.5
340     assert round(totals_metrics["rmse_adj"], 3) == 2.5
341     assert round(totals_metrics["cvrmse"], 3) == 0.938
342     assert round(totals_metrics["cvrmse_adj"], 3) == 0.938
343     assert round(totals_metrics["mape"], 3) == 1.806
344     assert round(totals_metrics["mape_no_zeros"], 3) == 1.806
345     assert round(totals_metrics["num_meter_zeros"], 3) == 0
346     assert round(totals_metrics["nmae"], 3) == 0.938
347     assert round(totals_metrics["nmbe"], 3) == 0.312
348     assert round(totals_metrics["confidence_level"], 3) == 0.9
349     assert round(totals_metrics["single_tailed_confidence_level"], 3) == 0.95
365     assert round(avgs_metrics["observed_length"], 3) == 4.000
366     assert round(avgs_metrics["predicted_length"], 3) == 4.000
367     assert round(avgs_metrics["merged_length"], 3) == 4.000
368     assert round(avgs_metrics["num_parameters"], 3) == 0
369     assert round(avgs_metrics["observed_mean"], 3) == 3.5
370     assert round(avgs_metrics["predicted_mean"], 3) == 3.5
371     assert round(avgs_metrics["observed_variance"], 3) == 6.25
372     assert round(avgs_metrics["predicted_variance"], 3) == 0
373     assert round(avgs_metrics["observed_skew"], 3) == 0
374     assert round(avgs_metrics["predicted_skew"], 3) == 0
375     assert round(avgs_metrics["observed_cvstd"], 3) == 0.825
376     assert round(avgs_metrics["predicted_cvstd"], 3) == 0
377     assert round(avgs_metrics["observed_kurtosis"], 3) == -6.0
378     assert round(avgs_metrics["predicted_kurtosis"], 3) == 0
380     assert round(avgs_metrics["rmse"], 3) == 2.5
381     assert round(avgs_metrics["rmse_adj"], 3) == 2.5
382     assert round(avgs_metrics["cvrmse"], 3) == 0.714
383     assert round(avgs_metrics["cvrmse_adj"], 3) == 0.714
384     assert round(avgs_metrics["mape"], 3) == 1.458
385     assert round(avgs_metrics["mape_no_zeros"], 3) == 1.458
386     assert round(avgs_metrics["num_meter_zeros"], 3) == 0
387     assert round(avgs_metrics["nmae"], 3) == 0.714
388     assert round(avgs_metrics["nmbe"], 3) == 0
389     assert round(avgs_metrics["confidence_level"], 3) == 0.9
390     assert round(avgs_metrics["n_prime"], 3) == 12.0
391     assert round(avgs_metrics["single_tailed_confidence_level"], 3) == 0.95
392     assert round(avgs_metrics["autocorr_resid"], 3) == -0.5
393     assert round(avgs_metrics["degrees_of_freedom"], 3) == 12.0
394     assert round(avgs_metrics["t_stat"], 3) == 1.782
395     assert round(avgs_metrics["cvrmse_auto_corr_correction"], 3) == 0.577
396     assert round(avgs_metrics["approx_factor_auto_corr_correction"], 3) == 1.08
397     assert round(avgs_metrics["fsu_base_term"], 3) == 0.794