Used python formatter to format code

Signed-off-by: Stephen Suffian <[email protected]>

eemeter/cli.py

@@ -65,7 +65,6 @@ def cli():
 def _get_data(
     sample, meter_file, temperature_file, heating_balance_points, cooling_balance_points
 ):
-
     if sample is not None:
         with resource_stream("eemeter.samples", "metadata.json") as f:
             metadata = json.loads(f.read().decode("utf-8"))

eemeter/derivatives.py

@@ -37,7 +37,7 @@ def _compute_ols_error(
 ):
     ols_model_agg_error = (
         (t_stat * rmse_base_residuals * post_obs)
-        / (base_obs ** 0.5)
+        / (base_obs**0.5)
         * (1.0 + ((base_avg - post_avg) ** 2.0 / base_var)) ** 0.5
     )
 
@@ -46,7 +46,7 @@ def _compute_ols_error(
     )
 
     ols_total_agg_error = (
-        ols_model_agg_error ** 2.0 + ols_noise_agg_error ** 2.0
+        ols_model_agg_error**2.0 + ols_noise_agg_error**2.0
     ) ** 0.5
 
     return ols_total_agg_error, ols_model_agg_error, ols_noise_agg_error
@@ -75,7 +75,7 @@ def _compute_fsu_error(
 
     fsu_error_band = total_base_energy * (
         t_stat
-        * (a_coeff * months_reporting ** 2.0 + b_coeff * months_reporting + c_coeff)
+        * (a_coeff * months_reporting**2.0 + b_coeff * months_reporting + c_coeff)
         * (rmse_base_residuals / base_avg)
         * ((base_obs / nprime) * (1.0 + (2.0 / nprime)) * (1.0 / post_obs)) ** 0.5
     )
@@ -372,7 +372,7 @@ def _compute_error_bands_modeled_savings(
         "FSU Error Band: Baseline": fsu_error_band_baseline,
         "FSU Error Band: Reporting": fsu_error_band_reporting,
         "FSU Error Band": (
-            fsu_error_band_baseline ** 2.0 + fsu_error_band_reporting ** 2.0
+            fsu_error_band_baseline**2.0 + fsu_error_band_reporting**2.0
         )
         ** 0.5,
     }

eemeter/features.py

@@ -233,7 +233,6 @@ def _compute_columns(temps):
         def _compute_columns(temps):
             count = temps.shape[0]
             if count > 24:
-
                 day_groups = np.floor(np.arange(count) / 24)
                 daily_temps = temps.groupby(day_groups).agg(["mean", "count"])
                 n_limit_period = percent_hourly_coverage_per_billing_period * count
@@ -267,7 +266,6 @@ def _compute_columns(temps):
                     for bp in heating_balance_points
                 }
             else:  # faster route for daily case, should have same effect.
-
                 if count > n_limit_daily:
                     count_cols = {"n_days_kept": 1, "n_days_dropped": 0}
                     # CalTRACK 2.2.2.3
@@ -833,7 +831,6 @@ def compute_temperature_bin_features(temperatures, bin_endpoints):
     bins = {}
 
     for i, (left_bin, right_bin) in enumerate(zip(bin_endpoints, bin_endpoints[1:])):
-
         bin_name = "bin_{}".format(i)
 
         in_bin = (temperatures > left_bin) & (temperatures <= right_bin)

eemeter/metrics.py

@@ -384,12 +384,10 @@ def __init__(
             or self.degrees_of_freedom < 1
             or self.observed_length < self.num_parameters
         ):
-
             self.cvrmse_auto_corr_correction = None
             self.approx_factor_auto_corr_correction = None
             self.fsu_base_term = None
         else:
-
             # factor to correct cvrmse_adj for autocorrelation of inputs
             # i.e., divide by (n' - n_param) instead of by (n - n_param)
             self.cvrmse_auto_corr_correction = (
@@ -411,15 +409,18 @@ def __init__(
             )
 
     def __repr__(self):
-        return "ModelMetrics(merged_length={}, r_squared_adj={}, cvrmse_adj={}, " "mape_no_zeros={}, nmae={}, nmbe={}, autocorr_resid={}, confidence_level={})".format(
-            self.merged_length,
-            round(self.r_squared_adj, 3),
-            round(self.cvrmse_adj, 3),
-            round(self.mape_no_zeros, 3),
-            round(self.nmae, 3),
-            round(self.nmbe, 3),
-            round(self.autocorr_resid, 3),
-            round(self.confidence_level, 3),
+        return (
+            "ModelMetrics(merged_length={}, r_squared_adj={}, cvrmse_adj={}, "
+            "mape_no_zeros={}, nmae={}, nmbe={}, autocorr_resid={}, confidence_level={})".format(
+                self.merged_length,
+                round(self.r_squared_adj, 3),
+                round(self.cvrmse_adj, 3),
+                round(self.mape_no_zeros, 3),
+                round(self.nmae, 3),
+                round(self.nmbe, 3),
+                round(self.autocorr_resid, 3),
+                round(self.confidence_level, 3),
+            )
         )
 
     def json(self):

tests/test_caltrack_usage_per_day.py

@@ -674,7 +674,7 @@ def cdd_hdd_h54_c67_billing_monthly_totals(il_electricity_cdd_hdd_billing_monthl
 
 
 def test_caltrack_predict_design_matrix_input_avg_false_output_avg_true(
-    cdd_hdd_h54_c67_billing_monthly_totals
+    cdd_hdd_h54_c67_billing_monthly_totals,
 ):
     data = cdd_hdd_h54_c67_billing_monthly_totals
     prediction = _caltrack_predict_design_matrix(
@@ -694,7 +694,7 @@ def test_caltrack_predict_design_matrix_input_avg_false_output_avg_true(
 
 
 def test_caltrack_predict_design_matrix_input_avg_false_output_avg_false(
-    cdd_hdd_h54_c67_billing_monthly_totals
+    cdd_hdd_h54_c67_billing_monthly_totals,
 ):
     data = cdd_hdd_h54_c67_billing_monthly_totals
     prediction = _caltrack_predict_design_matrix(
@@ -730,7 +730,7 @@ def cdd_hdd_h54_c67_billing_monthly_avgs(il_electricity_cdd_hdd_billing_monthly)
 
 
 def test_caltrack_predict_design_matrix_input_avg_true_output_avg_false(
-    cdd_hdd_h54_c67_billing_monthly_avgs
+    cdd_hdd_h54_c67_billing_monthly_avgs,
 ):
     data = cdd_hdd_h54_c67_billing_monthly_avgs
     prediction = _caltrack_predict_design_matrix(
@@ -750,7 +750,7 @@ def test_caltrack_predict_design_matrix_input_avg_true_output_avg_false(
 
 
 def test_caltrack_predict_design_matrix_input_avg_true_output_avg_true(
-    cdd_hdd_h54_c67_billing_monthly_avgs
+    cdd_hdd_h54_c67_billing_monthly_avgs,
 ):
     data = cdd_hdd_h54_c67_billing_monthly_avgs
     prediction = _caltrack_predict_design_matrix(
@@ -792,7 +792,7 @@ def test_caltrack_predict_design_matrix_n_days(cdd_hdd_h54_c67_billing_monthly_t
 
 
 def test_caltrack_predict_design_matrix_no_days_fails(
-    cdd_hdd_h54_c67_billing_monthly_totals
+    cdd_hdd_h54_c67_billing_monthly_totals,
 ):
     # This makes sure that the method fails if neither n_days nor
     # a DatetimeIndex is available.
@@ -1443,7 +1443,9 @@ def test_select_best_candidate_ok(
     assert best_candidate.r_squared_adj == 1
 
 
-def test_select_best_candidate_none(candidate_model_disqualified,):
+def test_select_best_candidate_none(
+    candidate_model_disqualified,
+):
     candidates = [candidate_model_disqualified]
 
     best_candidate, warnings = select_best_candidate(candidates)

tests/test_derivatives.py

@@ -91,7 +91,6 @@ def reporting_temperature_data():
 def test_metered_savings_cdd_hdd_daily(
     baseline_model_daily, reporting_meter_data_daily, reporting_temperature_data
 ):
-
     results, error_bands = metered_savings(
         baseline_model_daily, reporting_meter_data_daily, reporting_temperature_data
     )
@@ -153,7 +152,6 @@ def reporting_meter_data_billing():
 def test_metered_savings_cdd_hdd_billing(
     baseline_model_billing, reporting_meter_data_billing, reporting_temperature_data
 ):
-
     results, error_bands = metered_savings(
         baseline_model_billing, reporting_meter_data_billing, reporting_temperature_data
     )
@@ -174,7 +172,6 @@ def test_metered_savings_cdd_hdd_billing(
 def test_metered_savings_cdd_hdd_billing_no_reporting_data(
     baseline_model_billing, reporting_meter_data_billing, reporting_temperature_data
 ):
-
     results, error_bands = metered_savings(
         baseline_model_billing,
         reporting_meter_data_billing[:0],
@@ -192,7 +189,6 @@ def test_metered_savings_cdd_hdd_billing_no_reporting_data(
 def test_metered_savings_cdd_hdd_billing_single_record_reporting_data(
     baseline_model_billing, reporting_meter_data_billing, reporting_temperature_data
 ):
-
     results, error_bands = metered_savings(
         baseline_model_billing,
         reporting_meter_data_billing[:1],
@@ -232,7 +228,6 @@ def test_metered_savings_cdd_hdd_billing_single_record_baseline_data(
     reporting_meter_data_billing,
     reporting_temperature_data,
 ):
-
     results, error_bands = metered_savings(
         baseline_model_billing_single_record_baseline_data,
         reporting_meter_data_billing,
@@ -265,7 +260,6 @@ def test_metered_savings_cdd_hdd_billing_reporting_data_wrong_timestamp(
     reporting_meter_data_billing_wrong_timestamp,
     reporting_temperature_data,
 ):
-
     results, error_bands = metered_savings(
         baseline_model_billing,
         reporting_meter_data_billing_wrong_timestamp,
@@ -283,7 +277,6 @@ def test_metered_savings_cdd_hdd_billing_reporting_data_wrong_timestamp(
 def test_metered_savings_cdd_hdd_daily_hourly_degree_days(
     baseline_model_daily, reporting_meter_data_daily, reporting_temperature_data
 ):
-
     results, error_bands = metered_savings(
         baseline_model_daily, reporting_meter_data_daily, reporting_temperature_data
     )
@@ -309,7 +302,6 @@ def test_metered_savings_cdd_hdd_no_params(
 def test_metered_savings_cdd_hdd_daily_with_disaggregated(
     baseline_model_daily, reporting_meter_data_daily, reporting_temperature_data
 ):
-
     results, error_bands = metered_savings(
         baseline_model_daily,
         reporting_meter_data_daily,
@@ -547,7 +539,6 @@ def reporting_meter_data_hourly():
 def test_metered_savings_cdd_hdd_hourly(
     baseline_model_hourly, reporting_meter_data_hourly, reporting_temperature_data
 ):
-
     results, error_bands = metered_savings(
         baseline_model_hourly, reporting_meter_data_hourly, reporting_temperature_data
     )
@@ -592,7 +583,6 @@ def normal_year_temperature_data():
 def test_modeled_savings_cdd_hdd_billing(
     baseline_model_billing, reporting_model_billing, normal_year_temperature_data
 ):
-
     results, error_bands = modeled_savings(
         baseline_model_billing,
         reporting_model_billing,
@@ -624,7 +614,6 @@ def test_metered_savings_not_aligned_reporting_data(
     reporting_meter_data_billing_not_aligned,
     reporting_temperature_data,
 ):
-
     results, error_bands = metered_savings(
         baseline_model_billing,
         reporting_meter_data_billing_not_aligned,
@@ -658,7 +647,6 @@ def test_metered_savings_model_single_record(
     reporting_meter_data_billing,
     reporting_temperature_data,
 ):
-
     assert pd.isnull(baseline_model_billing_single_record.totals_metrics.autocorr_resid)
 
     # simulating deserialization

tests/test_json_serialization.py

@@ -85,8 +85,10 @@ def test_json_hourly():
     )
 
     # create a design matrix for occupancy and segmentation
-    preliminary_design_matrix = eemeter.create_caltrack_hourly_preliminary_design_matrix(
-        baseline_meter_data, temperature_data
+    preliminary_design_matrix = (
+        eemeter.create_caltrack_hourly_preliminary_design_matrix(
+            baseline_meter_data, temperature_data
+        )
     )
 
     # build 12 monthly models - each step from now on operates on each segment
@@ -110,12 +112,14 @@ def test_json_hourly():
     )
 
     # build a design matrix for each monthly segment
-    segmented_design_matrices = eemeter.create_caltrack_hourly_segmented_design_matrices(
-        preliminary_design_matrix,
-        segmentation,
-        occupancy_lookup,
-        occupied_temperature_bins,
-        unoccupied_temperature_bins,
+    segmented_design_matrices = (
+        eemeter.create_caltrack_hourly_segmented_design_matrices(
+            preliminary_design_matrix,
+            segmentation,
+            occupancy_lookup,
+            occupied_temperature_bins,
+            unoccupied_temperature_bins,
+        )
     )
 
     # build a CalTRACK hourly model

tests/test_transform.py

@@ -308,7 +308,7 @@ def test_get_baseline_data_with_ignored_gap(il_electricity_cdd_hdd_billing_month
 
 
 def test_get_baseline_data_with_overshoot_and_ignored_gap(
-    il_electricity_cdd_hdd_billing_monthly
+    il_electricity_cdd_hdd_billing_monthly,
 ):
     meter_data = il_electricity_cdd_hdd_billing_monthly["meter_data"]
     baseline_data, warnings = get_baseline_data(
@@ -335,7 +335,7 @@ def test_get_baseline_data_with_overshoot_and_ignored_gap(
 
 
 def test_get_baseline_data_n_days_billing_period_overshoot(
-    il_electricity_cdd_hdd_billing_monthly
+    il_electricity_cdd_hdd_billing_monthly,
 ):
     meter_data = il_electricity_cdd_hdd_billing_monthly["meter_data"]
     baseline_data, warnings = get_baseline_data(
@@ -548,7 +548,7 @@ def test_get_reporting_data_with_ignored_gap(il_electricity_cdd_hdd_billing_mont
 
 
 def test_get_reporting_data_with_overshoot_and_ignored_gap(
-    il_electricity_cdd_hdd_billing_monthly
+    il_electricity_cdd_hdd_billing_monthly,
 ):
     meter_data = il_electricity_cdd_hdd_billing_monthly["meter_data"]
     reporting_data, warnings = get_reporting_data(
@@ -792,7 +792,7 @@ def test_as_freq_hourly_to_daily_include_coverage(il_electricity_cdd_hdd_hourly)
 
 
 def test_clean_caltrack_billing_daily_data_billing(
-    il_electricity_cdd_hdd_billing_monthly
+    il_electricity_cdd_hdd_billing_monthly,
 ):
     meter_data = il_electricity_cdd_hdd_billing_monthly["meter_data"]
     cleaned_data = clean_caltrack_billing_daily_data(meter_data, "billing_monthly")
@@ -848,7 +848,7 @@ def test_clean_caltrack_billing_data_estimated(il_electricity_cdd_hdd_billing_mo
 
 
 def test_clean_caltrack_billing_data_uneven_datetimes(
-    il_electricity_cdd_hdd_billing_monthly
+    il_electricity_cdd_hdd_billing_monthly,
 ):
     meter_data = il_electricity_cdd_hdd_billing_monthly["meter_data"]
     too_short_meter_data = pd.concat(