updated write_json_files to fix model card issues

src/sasctl/pzmm/write_json_files.py

@@ -965,6 +965,7 @@ def format_max_differences(
         maxdiff_df = maxdiff_df.rename(
             columns={"Value": "maxdiff", "Base": "BASE", "Compare": "COMPARE"}
         )
+        maxdiff_df["maxdiff"] = maxdiff_df["maxdiff"].apply(str)
 
         maxdiff_df["VLABEL"] = ""
         maxdiff_df["_DATAROLE_"] = datarole
@@ -2257,6 +2258,7 @@ def generate_model_card(
         interval_vars: Optional[list] = [],
         class_vars: Optional[list] = [],
         selection_statistic: str = None,
+        training_table_name: str = None,
         server: str = "cas-shared-default",
         caslib: str = "Public",
     ):
@@ -2336,7 +2338,7 @@ def generate_model_card(
 
         # Upload training table to CAS. The location of the training table is returned.
         training_table = cls.upload_training_data(
-            conn, model_prefix, train_data, server, caslib
+            conn, model_prefix, train_data, training_table_name, server, caslib
         )
 
         # Generates the event percentage for Classification targets, and the event average
@@ -2378,6 +2380,7 @@ def upload_training_data(
         conn,
         model_prefix: str,
         train_data: pd.DataFrame,
+        train_data_name: str,
         server: str = "cas-shared-default",
         caslib: str = "Public",
     ):
@@ -2404,15 +2407,18 @@ def upload_training_data(
         Returns a string that represents the location of the training table within CAS.
         """
         # Upload raw training data to caslib so that data can be analyzed
-        train_data_name = model_prefix + "_train_data"
+        if not train_data_name:
+            train_data_name = model_prefix + "_train_data"
         upload_train_data = conn.upload(
             train_data, casout={"name": train_data_name, "caslib": caslib}, promote=True
         )
 
         if upload_train_data.status is not None:
-            raise RuntimeError(
-                f"A table with the name {train_data_name} already exists in the specified caslib. Please "
-                "either delete/rename the old table or give a new name to the current table."
+            # raise RuntimeError(
+            warnings.warn(
+                f"A table with the name {train_data_name} already exists in the specified caslib. If this "
+                f"is not intentional, please either rename the training data file or remove the duplicate from "
+                f"the caslib."
             )
 
         return server + "/" + caslib + "/" + train_data_name.upper()
@@ -2762,6 +2768,9 @@ def generate_misc(cls, model_files: Union[str, Path, dict]):
                 roc_table = json.load(roc_file)
         correct_text = ["CORRECT", "INCORRECT", "CORRECT", "INCORRECT"]
         outcome_values = ["1", "0", "0", "1"]
+        target_texts = ["Event", "Event", "NEvent", "NEvent"]
+        target_values = ["1", "1", "0", "0"]
+
         misc_data = list()
         # Iterates through ROC table to get TRAIN, TEST, and VALIDATE data with a cutoff of .5
         for i in range(50, 300, 100):
@@ -2772,8 +2781,8 @@ def generate_misc(cls, model_files: Union[str, Path, dict]):
                 roc_data["_TN_"],
                 roc_data["_FN_"],
             ]
-            for c_text, c_val, o_val in zip(
-                correct_text, correctness_values, outcome_values
+            for c_text, c_val, o_val, t_txt, t_val in zip(
+                correct_text, correctness_values, outcome_values, target_texts, target_values
             ):
                 misc_data.append(
                     {
@@ -2784,6 +2793,8 @@ def generate_misc(cls, model_files: Union[str, Path, dict]):
                             "_DataRole_": roc_data["_DataRole_"],
                             "_cutoffSource_": "Default",
                             "_cutoff_": "0.5",
+                            "TargetText": t_txt,
+                            "Target": t_val
                         },
                         "rowNumber": len(misc_data) + 1,
                     }