check also for closure test data in read_replica_pseudodata

validphys2/src/validphys/pseudodata.py

@@ -80,25 +80,40 @@ def read_replica_pseudodata(fit, context_index, replica):
     log.debug(f"Reading pseudodata & training/validation splits from {fit.name}.")
     replica_path = fit.path / "nnfit" / f"replica_{replica}"
 
-    training_path = replica_path / (FILE_PREFIX + "training_pseudodata.csv")
-    validation_path = replica_path / (FILE_PREFIX + "validation_pseudodata.csv")
-
     try:
+        # The paths where sampled experimental data is stored
+        training_path = replica_path / "datacuts_theory_fitting_training_pseudodata.csv"
+        validation_path = replica_path / "datacuts_theory_fitting_validation_pseudodata.csv"
         tr = pd.read_csv(training_path, index_col=[0, 1, 2], sep="\t", header=0)
         val = pd.read_csv(validation_path, index_col=[0, 1, 2], sep="\t", header=0)
     except FileNotFoundError:
-        # Old 3.1 style fits had pseudodata called training.dat and validation.dat
-        training_path = replica_path / "training.dat"
-        validation_path = replica_path / "validation.dat"
-        tr = pd.read_csv(training_path, index_col=[0, 1, 2], sep="\t", names=[f"replica {replica}"])
-        val = pd.read_csv(
-            validation_path, index_col=[0, 1, 2], sep="\t", names=[f"replica {replica}"]
-        )
-    except FileNotFoundError as e:
-        raise FileNotFoundError(
-            "Could not find saved training and validation data files. "
-            f"Please ensure {fit} was generated with the savepseudodata flag set to true"
-        ) from e
+        try:
+            # Pseudodata generated in a closure test
+            training_path = (
+                replica_path / "datacuts_theory_closuretest_fitting_training_pseudodata.csv"
+            )
+            validation_path = (
+                replica_path / "datacuts_theory_closuretest_fitting_validation_pseudodata.csv"
+            )
+            tr = pd.read_csv(training_path, index_col=[0, 1, 2], sep="\t", header=0)
+            val = pd.read_csv(validation_path, index_col=[0, 1, 2], sep="\t", header=0)
+        except FileNotFoundError:
+            try:
+                # Old 3.1 style fits had pseudodata called training.dat and validation.dat
+                training_path = replica_path / "training.dat"
+                validation_path = replica_path / "validation.dat"
+                tr = pd.read_csv(
+                    training_path, index_col=[0, 1, 2], sep="\t", names=[f"replica {replica}"]
+                )
+                val = pd.read_csv(
+                    validation_path, index_col=[0, 1, 2], sep="\t", names=[f"replica {replica}"]
+                )
+            except FileNotFoundError as e:
+                raise FileNotFoundError(
+                    "Could not find saved training and validation data files. "
+                    f"Please ensure {fit} was generated with the savepseudodata flag set to true"
+                ) from e
+
     tr["type"], val["type"] = "training", "validation"
 
     pseudodata = pd.concat((tr, val))