Merge pull request #131 from washingtonpost/error-handling

Error handling

src/elexmodel/handlers/data/VersionedData.py

@@ -127,6 +127,8 @@ def compute_estimated_margin(df):
                         "percent_expected_vote": np.arange(101),
                         "nearest_observed_vote": np.nan * np.ones(101),
                         "est_margin": np.nan * np.ones(101),
+                        "est_correction": np.nan * np.ones(101),
+                        "error_type": "non-monotone percent expected vote",
                     }
                 )
 
@@ -152,6 +154,8 @@ def compute_estimated_margin(df):
                         "percent_expected_vote": np.arange(101),
                         "nearest_observed_vote": np.nan * np.ones(101),
                         "est_margin": np.nan * np.ones(101),
+                        "est_correction": np.nan * np.ones(101),
+                        "error_type": "batch_margin",
                     }
                 )
 
@@ -196,10 +200,17 @@ def compute_estimated_margin(df):
                     "nearest_observed_vote": percent_vote[np.clip(obs_indices + 1, 0, len(percent_vote) - 1)],
                     "est_margin": est_margins,
                     "est_correction": norm_margin[-1] - est_margins,
+                    "error_type": "none",
                 }
             )
 
         results = results.groupby("geographic_unit_fips").apply(compute_estimated_margin).reset_index()
+
+        for error_type in sorted(set(results["error_type"])):
+            if error_type == "none":
+                continue
+            category_error_type = results[results["error_type"] == error_type].geographic_unit_fips.unique()
+            LOG.info(f"# of versioned units with {error_type} error: {len(category_error_type)}")
         return results
 
     def get_versioned_predictions(self, filepath=None):