Merge pull request #165 from LSSTDESC/tqz/fix_oldevaluator

remove column that are not computed by the scipy functions
LSSTDESC · Dec 2, 2024 · 820e3ea · 820e3ea
2 parents 83f0930 + 7017240
commit 820e3ea
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Showing 2 changed files with 12 additions and 7 deletions.
diff --git a/src/rail/estimation/estimator.py b/src/rail/estimation/estimator.py
@@ -102,7 +102,9 @@ def estimate(self, input_data):
         self.set_data("input", input_data)
         self.run()
         self.finalize()
-        return self.get_handle("output")
+        results = self.get_handle("output")
+        results.read(force = True)
+        return results
 
     def run(self):
         self.open_model(**self.config)

diff --git a/src/rail/evaluation/evaluator.py b/src/rail/evaluation/evaluator.py
@@ -481,19 +481,22 @@ def run(self):
         out_table = {}
         for pit_metric in pit_metrics:
             value = PIT_METRICS[pit_metric]()
-
             # The result objects of some meta-metrics are bespoke scipy objects with inconsistent fields.
             # Here we do our best to store the relevant fields in `out_table`.
             if isinstance(value, list):  # pragma: no cover
                 out_table[f"PIT_{pit_metric}"] = value
+            elif pit_metric== 'OutRate':
+                out_table[f"PIT_{pit_metric}_stat"] = [value]
             else:
                 out_table[f"PIT_{pit_metric}_stat"] = [
                     getattr(value, "statistic", None)
                 ]
-                out_table[f"PIT_{pit_metric}_pval"] = [getattr(value, "p_value", None)]
-                out_table[f"PIT_{pit_metric}_significance_level"] = [
-                    getattr(value, "significance_level", None)
-                ]
+                if getattr(value, "pvalue", None) is not None:
+                    out_table[f"PIT_{pit_metric}_pval"] = [getattr(value, "p_value", None)]
+                if getattr(value, "significance_level", None) is not None:
+                    out_table[f"PIT_{pit_metric}_significance_level"] = [
+                        getattr(value, "significance_level", None)
+                    ]
 
         POINT_METRICS = dict(
             SimgaIQR=PointSigmaIQR,
@@ -516,7 +519,7 @@ def run(self):
         if self.config.do_cde:
             value = CDELoss(pz_data, zgrid, z_true).evaluate()
             out_table["CDE_stat"] = [value.statistic]
-            out_table["CDE_pval"] = [value.p_value]
+            # out_table["CDE_pval"] = [value.p_value]
 
         # Converting any possible None to NaN to write it
         out_table_to_write = {