moved _cleanup_data_columns() function to "columns" module

by moving this function it can be easily reused in the upcoming "xml_parser" module

src/sensospot_parser/columns.py

@@ -1,5 +1,7 @@
 """ Column name definitions """
 
+import pandas
+
 # original, unmodified column names
 POS_X = "Pos.X"
 POS_Y = "Pos.Y"
@@ -121,3 +123,19 @@ INDEX_COLUMNS_POS = (
     WELL_ROW,
     POS_ID,
 )
+
+
+def _cleanup_data_columns(data_frame: pandas.DataFrame) -> pandas.DataFrame:
+    """renames some data columns for consistency and drops unused columns
+
+    Args:
+        data_frame: pandas DataFrame with parsed measurement data
+
+    Returns:
+        pandas DataFrame, column names cleaned up
+    """
+    renamed = data_frame.rename(columns=CSV_RENAME_MAP)
+    surplus_columns = set(renamed.columns) - PARSED_DATA_COLUMN_SET
+    x = renamed.drop(columns=surplus_columns)
+    print(PARSED_DATA_COLUMN_SET - set(x.columns))
+    return x

src/sensospot_parser/csv_parser.py

@@ -1,6 +1,6 @@
 """ Sensospot Data Parser
 
-Parsing the numerical output from Sensovations Sensospot image analysis.
+Parsing the csv result files from Sensovations Sensospot image analysis.
 """
 
 import re
@@ -84,20 +84,6 @@ def _extract_measurement_info(data_file: PathLike) -> FileInfo:
     return FileInfo(row, column, exposure)
 
 
-def _cleanup_data_columns(data_frame: pandas.DataFrame) -> pandas.DataFrame:
-    """renames some data columns for consistency and drops unused columns
-
-    Args:
-        data_frame: pandas DataFrame with parsed measurement data
-
-    Returns:
-        pandas DataFrame, column names cleaned up
-    """
-    renamed = data_frame.rename(columns=columns.CSV_RENAME_MAP)
-    surplus_columns = set(renamed.columns) - columns.PARSED_DATA_COLUMN_SET
-    return renamed.drop(columns=surplus_columns)
-
-
 def parse_file(data_file: PathLike) -> pandas.DataFrame:
     """parses one data file and adds metadata to result
 
@@ -124,7 +110,7 @@ def parse_file(data_file: PathLike) -> pandas.DataFrame:
     data_frame[columns.EXPOSURE_ID] = measurement_info.exposure
     data_frame[columns.ANALYSIS_NAME] = data_path.parent.name
     data_frame[columns.ANALYSIS_IMAGE] = data_path.with_suffix(".tif").name
-    return _cleanup_data_columns(data_frame)
+    return columns._cleanup_data_columns(data_frame)
 
 
 def _parse_file_silenced(data_file: PathLike) -> Optional[pandas.DataFrame]:

tests/test_columns.py

@@ -0,0 +1,15 @@
+def test_cleanup_data_columns():
+    from pandas import DataFrame
+
+    from sensospot_parser.columns import _cleanup_data_columns
+
+    columns = ["Rect.", "Contour", " ID ", "Found", "Dia."]
+    data = {col: [i] for i, col in enumerate(columns)}
+    data_frame = DataFrame(data=data)
+
+    result = _cleanup_data_columns(data_frame)
+
+    assert set(result.columns) == {"Pos.Id", "Spot.Found", "Spot.Diameter"}
+    assert result["Pos.Id"][0] == 2
+    assert result["Spot.Found"][0] == 3
+    assert result["Spot.Diameter"][0] == 4

tests/test_csv_parser.py

@@ -127,23 +127,6 @@ def test_extract_measurement_info_raises_error(filename):
         _extract_measurement_info(filename)
 
 
-def test_cleanup_data_columns():
-    from pandas import DataFrame
-
-    from sensospot_parser.csv_parser import _cleanup_data_columns
-
-    columns = ["Rect.", "Contour", " ID ", "Found", "Dia."]
-    data = {col: [i] for i, col in enumerate(columns)}
-    data_frame = DataFrame(data=data)
-
-    result = _cleanup_data_columns(data_frame)
-
-    assert set(result.columns) == {"Pos.Id", "Spot.Found", "Spot.Diameter"}
-    assert result["Pos.Id"][0] == 2
-    assert result["Spot.Found"][0] == 3
-    assert result["Spot.Diameter"][0] == 4
-
-
 def test_parse_file(example_file):
     from sensospot_parser.csv_parser import parse_file