added col alt and tests

pyproject.toml

@@ -10,7 +10,7 @@ dependencies = [
     "fonttools==4.63.0",
     "flet==0.86.5",
     "flet-permission-handler==0.86.5",
-    "hyperkey-file-opener @ file:///D:/Masters%20of%20computing/Tech%20Launcher/hyperkey/hyperkey-file-opener",
+    "hyperkey-file-opener @ file://C:/Users/Samwi/OneDrive/Documents/Uni/Tech%20Launcher/hyperkey/hyperkey_file_opener",
     "greenlet==3.5.1",
     "kiwisolver==1.5.0",
     "Markdown==3.10.3",
@@ -33,4 +33,7 @@ dependencies = [
 module = "hyperkey"
 
 [tool.flet.android.permission]
-"android.permission.MANAGE_EXTERNAL_STORAGE" = true
+"android.permission.MANAGE_EXTERNAL_STORAGE" = true
+
+[tool.flet.android]
+extract_packages = ["matplotlib"]

scripts/visualise_heatmap.py

@@ -94,7 +94,8 @@ def calculate_square_grid(n_measurements):
 
 def validate_row_range_columns(csv_path):
     """
-    Check if CSV contains 'row' and 'range' columns (case-insensitive) and validate them.
+    Check if CSV contains 'row' and either 'range' or 'col' columns
+    (case-insensitive) and validate them.
     Returns (rows_list, ranges_list) if valid, (None, None) if columns don't exist.
     Raises ValueError if columns exist but contain non-integer values.
     """
@@ -105,27 +106,31 @@ def validate_row_range_columns(csv_path):
     cols_lower = {col.lower(): col for col in raw_df.columns}
 
     has_row = 'row' in cols_lower
-    has_range = 'range' in cols_lower
+    coordinate_col = cols_lower.get('range') or cols_lower.get('col')
+    has_coordinate = coordinate_col is not None
 
     # If neither exists, return None and use square grid
-    if not has_row and not has_range:
+    if not has_row and not has_coordinate:
         return None, None
 
     # If only one exists, that's an error
-    if has_row != has_range:
-        missing = 'range' if has_row else 'row'
-        raise ValueError(f"Found 'row' column but missing '{missing}' column. Both must exist together.")
+    if has_row != has_coordinate:
+        raise ValueError(
+            f"Found 'row' column but missing 'range' or 'col' column. "
+            "Both must exist together."
+        )
 
     # Both columns exist - validate them strictly
     row_col = cols_lower['row']
-    range_col = cols_lower['range']
 
     try:
         row_vals = pd.to_numeric(raw_df[row_col], errors='coerce')
-        range_vals = pd.to_numeric(raw_df[range_col], errors='coerce')
+        range_vals = pd.to_numeric(raw_df[coordinate_col], errors='coerce')
 
         if row_vals.isna().any() or range_vals.isna().any():
-            raise ValueError("Found non-numeric values in 'row' or 'range' columns")
+            raise ValueError(
+                f"Found non-numeric values in 'row' or '{coordinate_col}' columns"
+            )
 
         # Check if all values are integers
         if not (row_vals == row_vals.astype(int)).all() or not (range_vals == range_vals.astype(int)).all():
@@ -176,16 +181,19 @@ def load_location_mapping(location_path, measurement_names):
     """Load a location file and map each measurement name to a grid coordinate."""
     location_df = pd.read_csv(location_path, header=0)
     cols_lower = {col.lower(): col for col in location_df.columns}
+    coordinate_col = cols_lower.get('range') or cols_lower.get('col')
 
-    if 'row' in cols_lower and 'range' in cols_lower:
+    if 'row' in cols_lower and coordinate_col is not None:
         row_col = cols_lower['row']
-        range_col = cols_lower['range']
 
         row_vals = pd.to_numeric(location_df[row_col], errors='coerce')
-        range_vals = pd.to_numeric(location_df[range_col], errors='coerce')
+        range_vals = pd.to_numeric(location_df[coordinate_col], errors='coerce')
 
         if row_vals.isna().any() or range_vals.isna().any():
-            raise ValueError("Found non-numeric values in location file 'row' or 'range' columns")
+            raise ValueError(
+                f"Found non-numeric values in location file 'row' or "
+                f"'{coordinate_col}' columns"
+            )
 
         if not (row_vals == row_vals.astype(int)).all() or not (range_vals == range_vals.astype(int)).all():
             raise ValueError("All values in location file 'row' and 'range' columns must be integers")

tests/test_visualise_heatmap.py

@@ -0,0 +1,33 @@
+"""Tests for heatmap coordinate parsing."""
+
+import sys
+from pathlib import Path
+
+import pandas as pd
+import pytest
+
+sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
+
+from visualise_heatmap import validate_row_range_columns
+
+
+def test_validate_row_col_columns(tmp_path):
+    csv_path = tmp_path / "spectral.csv"
+    pd.DataFrame({"row": [1, 2], "col": [3, 4]}).to_csv(csv_path, index=False)
+
+    assert validate_row_range_columns(csv_path) == ([1, 2], [3, 4])
+
+
+def test_validate_row_range_columns_still_supported(tmp_path):
+    csv_path = tmp_path / "spectral.csv"
+    pd.DataFrame({"row": [1, 2], "range": [3, 4]}).to_csv(csv_path, index=False)
+
+    assert validate_row_range_columns(csv_path) == ([1, 2], [3, 4])
+
+
+def test_validate_row_without_coordinate_column_raises(tmp_path):
+    csv_path = tmp_path / "spectral.csv"
+    pd.DataFrame({"row": [1, 2], "value": [3, 4]}).to_csv(csv_path, index=False)
+
+    with pytest.raises(ValueError, match="range.*col"):
+        validate_row_range_columns(csv_path)