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added trip metrics #31

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merged 2 commits into from
Jan 29, 2025
Merged

added trip metrics #31

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1e31216
added trip metrics
Jan 29, 2025
de13871
added trip metrics
Jan 29, 2025
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39 changes: 39 additions & 0 deletions nrel/routee/powertrain/validation/errors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,9 @@
"link_negative_log_likelihood": "Link NLL",
"link_continuous_ranked_probability_score": "Link CRPS",
"link_prediction_interval_coverage_probability": "Link PICP",
"trip_negative_log_likelihood": "Trip NLL",
"trip_continuous_ranked_probability_score": "Trip CRPS",
"trip_prediction_interval_coverage_probability": "Trip PICP",
}


Expand Down Expand Up @@ -107,6 +110,15 @@ def calculate_picp(target, lower_bound, upper_bound) -> float:
return picp


def calculate_combined_sd(target_std) -> float:
"""
Calculate the combined standard deviation of the target.
"""
combined_variance = (target_std**2).sum()
combined_sd = np.sqrt(combined_variance)
return combined_sd


def errors_to_html_lines(errors: Errors) -> List[str]:
html_lines = []
for error_name, error_value in errors.to_dict().items():
Expand Down Expand Up @@ -138,6 +150,10 @@ class Errors:
link_continuous_ranked_probability_score: Optional[float] = None
link_prediction_interval_coverage_probability: Optional[float] = None

trip_negative_log_likelihood: Optional[float] = None
trip_continuous_ranked_probability_score: Optional[float] = None
trip_prediction_interval_coverage_probability: Optional[float] = None

@classmethod
def from_dict(self, d: dict) -> Errors:
return Errors(**d)
Expand Down Expand Up @@ -344,6 +360,29 @@ def compute_errors(
calculate_picp(target, lower_bound, upper_bound), 2
)

if trip_column in test_df.columns:
test_df["energy_pred"] = target_pred
test_df["energy_pred_std"] = target_std
gb = test_df.groupby(trip_column).agg(
{
energy_name: "sum",
"energy_pred": "sum",
"energy_pred_std": calculate_combined_sd,
}
)
lower_bound = gb["energy_pred"] - z * gb["energy_pred_std"]
upper_bound = gb["energy_pred"] + z * gb["energy_pred_std"]

errors["trip_negative_log_likelihood"] = calculate_nll(
gb[energy_name], gb["energy_pred"], gb["energy_pred_std"]
)
errors["trip_continuous_ranked_probability_score"] = calculate_crps(
gb[energy_name], gb["energy_pred"], gb["energy_pred_std"]
)
errors["trip_prediction_interval_coverage_probability"] = round(
calculate_picp(gb[energy_name], lower_bound, upper_bound), 2
)

errors["net_error"] = net_energy_error(target, target_pred)

total_dist = test_df[distance.name].sum()
Expand Down