Added functions to ensure minimum/maximum columns exist

Functions added it utils/io.py and applied in csv.py. Function safe_parameters_fillna for loading and safe_parameters_replace for saving parameters. Now it will be checked if columns exist before replacing inf/-inf and empty strings.

glotaran/builtin/io/pandas/csv.py

@@ -8,6 +8,8 @@
 from glotaran.io import ProjectIoInterface
 from glotaran.io import register_project_io
 from glotaran.parameter import ParameterGroup
+from glotaran.utils.io import safe_parameters_fillna
+from glotaran.utils.io import safe_parameters_replace
 
 
 @register_project_io(["csv"])
@@ -27,8 +29,8 @@ def load_parameters(self, file_name: str) -> ParameterGroup:
             :class:`ParameterGroup
         """
         df = pd.read_csv(file_name, skipinitialspace=True, na_values=["None", "none"])
-        df["minimum"].fillna(-np.inf, inplace=True)
-        df["maximum"].fillna(np.inf, inplace=True)
+        safe_parameters_fillna(df, "minimum", -np.inf)
+        safe_parameters_fillna(df, "maximum", np.inf)
         return ParameterGroup.from_dataframe(df, source=file_name)
 
     def save_parameters(self, parameters: ParameterGroup, file_name: str, *, sep: str = ","):
@@ -44,6 +46,6 @@ def save_parameters(self, parameters: ParameterGroup, file_name: str, *, sep: st
             Other separators can be used optionally.
         """
         df = parameters.to_dataframe()
-        df["minimum"].replace([-np.inf], "", inplace=True)
-        df["maximum"].replace([np.inf], "", inplace=True)
+        safe_parameters_replace(df, "minimum", -np.inf, "")
+        safe_parameters_replace(df, "maximum", np.inf, "")
         df.to_csv(file_name, na_rep="None", index=False, sep=sep)

glotaran/utils/io.py

@@ -180,3 +180,41 @@ def relative_posix_path(source_path: StrOrPath, base_path: StrOrPath | None = No
     if base_path is not None and os.path.isabs(source_path):
         source_path = os.path.relpath(source_path, Path(base_path).as_posix())
     return Path(source_path).as_posix()
+
+
+def safe_parameters_fillna(df, column_name, fill_value):
+    """Ensure that columns exist in order to replace empty strings with +/-np.inf values.
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        DataFrame from which specific column values will be replaced
+    column_name : str
+        Name of column from DataFrame
+    fill_value : str
+        Values to be replaced in column
+    """
+    if column_name in df.columns:
+        df[column_name].fillna(fill_value, inplace=True)
+
+
+def safe_parameters_replace(df, column_name, to_be_replaced_values, replace_value):
+    """Ensure that columns exist in order to replace  +/-np.inf values with empty strings.
+
+    If value is not list or tuple format, convert into list with same value as element.
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        DataFrame from which specific column values will be replaced
+    column_name : str
+        Name of column from DataFrame
+    to_be_replaced_values : float
+        Values to be replaced
+    replace_value : str
+        Replace values
+    """
+    if not isinstance(to_be_replaced_values, (list, tuple)):
+        to_be_replaced_values = [to_be_replaced_values]
+    if column_name in df.columns:
+        df[column_name].replace(to_be_replaced_values, replace_value, inplace=True)