Syntax edits

metcalcpy/agg_eclv.py

@@ -209,7 +209,7 @@ def _get_bootstrapped_stats(self, series_data, thresholds):
                         save_data=False,
                         block_length=block_length,
                         eclv=True
-                    )
+                        )
                     logger.info(f"Bootstrapped statistics calculated for threshold {thresh}.")
                 except KeyError as err:
                     logger.error(f"Failed to calculate bootstrapped statistics due to missing key: {err}", exc_info=True)

metcalcpy/agg_stat.py

@@ -1075,7 +1075,8 @@ def _get_bootstrapped_stats_for_derived(self, series, distributions, axis="1"):
                     alpha=self.params['alpha'],
                     save_data=False,
                     save_distributions=(derived_curve_component.derived_operation == 'DIFF_SIG'),
-                    block_length=block_length)
+                    block_length=block_length
+                    )
             except KeyError as err:
                 logger.error(f"Error during bootstrapping: {err}", exc_info=True)
                 return BootstrapResults(None, None, None)

metcalcpy/calc_difficulty_index.py

@@ -43,7 +43,7 @@ def safe_log(logger, log_method, message):
     if logger:
         log_method(message)
 
-def _input_check(sigmaij, muij, threshold, fieldijn, sigma_over_mu_ref, under_factor, logger):
+def _input_check(logger, sigmaij, muij, threshold, fieldijn, sigma_over_mu_ref, under_factor):
     """
     Check for valid input to _difficulty_index.
 
@@ -93,7 +93,7 @@ def _input_check(sigmaij, muij, threshold, fieldijn, sigma_over_mu_ref, under_fa
     assert 0.0 <= under_factor <= 1.0
     safe_log(logger, logger.debug, "under_factor is valid and within range.")
 
-def _difficulty_index(sigmaij, muij, threshold, fieldijn, Aplin, sigma_over_mu_ref=EPS, under_factor=0.5, logger):
+def _difficulty_index(logger, sigmaij, muij, threshold, fieldijn, Aplin, sigma_over_mu_ref=EPS, under_factor=0.5):
     """
     Calculates version 6.1 of forecast difficulty index.
     The threshold terms all penalize equal (or slightly unequal) spread.
@@ -160,8 +160,8 @@ def _difficulty_index(sigmaij, muij, threshold, fieldijn, Aplin, sigma_over_mu_r
     return dij
 
 
-def forecast_difficulty(sigmaij, muij, threshold, fieldijn,
-                        Aplin, sigma_over_mu_ref=EPS, logger):
+def forecast_difficulty(logger, sigmaij, muij, threshold, fieldijn,
+                        Aplin, sigma_over_mu_ref=EPS):
     """
     Calls private function _difficulty_index, 
     to calculate version (v6.1) of forecast difficulty index.

test/test_calc_difficulty_index.py

@@ -46,12 +46,12 @@ def test_forecast_difficulty():
     thresh_eps = 2.0
     kwargs = {'thresh_eps': thresh_eps, 'threshold_type': 'proximity'}
 
-    assert 0.9095608641027515 == forecast_difficulty(sigmaij, muij, threshold, fieldijn,
-            Aplin=None, sigma_over_mu_ref=EPS, None)[0][0]
-    assert 0.8191620255148825 == forecast_difficulty(sigmaij, muij, threshold, fieldijn,
-            Aplin=None, sigma_over_mu_ref=EPS, None)[8][17]
-    assert 1.227707670365556 == forecast_difficulty(sigmaij, muij, threshold, fieldijn,
-            Aplin=None, sigma_over_mu_ref=EPS, None)[4][9]
+    assert 0.9095608641027515 == forecast_difficulty(None, sigmaij, muij, threshold, fieldijn,
+            Aplin=None, sigma_over_mu_ref=EPS)[0][0]
+    assert 0.8191620255148825 == forecast_difficulty(None, sigmaij, muij, threshold, fieldijn,
+            Aplin=None, sigma_over_mu_ref=EPS)[8][17]
+    assert 1.227707670365556 == forecast_difficulty(None, sigmaij, muij, threshold, fieldijn,
+            Aplin=None, sigma_over_mu_ref=EPS)[4][9]
 
 
 if __name__ == "__main__":

test/test_scorecard.py

@@ -84,7 +84,7 @@ def settings():
                        'NoahMPv3.5.1_d01']},
               'stat_flag': 'NCAR',
               'sum_stat_input': f'{cwd}/data/scorecard.data',
-              'sum_stat_output': f'{cwd}/data/scorecard_output.data'
+              'sum_stat_output': f'{cwd}/data/scorecard_output.data',
               'log_dir': f'{cwd}/logs/',
               'log_filename': 'log_scorecard.txt',
               'log_level': 'WARNING'