update ignore

.gitignore

@@ -175,3 +175,4 @@ cython_debug/
 .pypirc
 
 /individual_images
+*.xlsx

main.py

@@ -550,10 +550,10 @@ class UpdateOptodesWindow(QWidget):
         self.btn_browse_a = QPushButton("Browse .snirf")
         self.btn_browse_a.clicked.connect(self.browse_file_a)
 
-        self.label_file_b = QLabel("TXT file:")
+        self.label_file_b = QLabel("Text file:")
         self.line_edit_file_b = QLineEdit()
         self.line_edit_file_b.setReadOnly(True)
-        self.btn_browse_b = QPushButton("Browse .txt")
+        self.btn_browse_b = QPushButton("Browse .txt/.xlsx")
         self.btn_browse_b.clicked.connect(self.browse_file_b)
 
         self.label_suffix = QLabel("Suffix to append to filename:")
@@ -574,9 +574,10 @@ class UpdateOptodesWindow(QWidget):
             
         self.description.setText("Some software when creating snirf files will insert a template of optode positions as the correct position of the optodes for the participant.<br>"
         "This is rarely correct as each head differs slightly in shape or size, and a lot of calculations require the optodes to be in the correct location.<br>"
-        "Using a .txt file, we can update the positions in the snirf file to match those of a digitization system such as one from Polhemus or elsewhere.<br>"
+        "Using a .txt or .xlsx file, we can update the positions in the snirf file to match those of a digitization system such as one from Polhemus or elsewhere.<br>"
         "The .txt file should have the fiducials, detectors, and sources clearly labeled, followed by the x, y, and z coordinates seperated by a space.<br>"
-        "An example format of what a digitization text file should look like can be found <a href='custom_link'>by clicking here</a>.")
+        "An example format of what a digitization text file should look like can be found <a href='custom_link'>by clicking here</a>. Currently only .xlsx files directly exported from a<br>"
+        "Polhemus system are supported.")
 
         self.description.linkActivated.connect(self.handle_link_click)
         layout.addWidget(self.description)
@@ -605,8 +606,7 @@ class UpdateOptodesWindow(QWidget):
         file_a_layout.addWidget(file_a_container)
         layout.addLayout(file_a_layout)
 
-
+        help_text_b = "Provide a .txt file with labeled optodes (e.g., nz, rpa, lpa, d1, s1) and their x, y, z coordinates, or a .xlsx file from a Polhemius system."
-        help_text_b = "Provide a .txt file with labeled optodes (e.g., nz, rpa, lpa, d1, s1) and their x, y, z coordinates."
 
         file_b_layout = QHBoxLayout()
 
@@ -689,7 +689,7 @@ class UpdateOptodesWindow(QWidget):
             self.line_edit_file_a.setText(file_path)
 
     def browse_file_b(self):
-        file_path, _ = QFileDialog.getOpenFileName(self, "Select TXT File", "", "Text Files (*.txt)")
+        file_path, _ = QFileDialog.getOpenFileName(self, "Select File", "", "Text Files (*.txt), Excel Files (*.xlsx)")
         if file_path:
             self.line_edit_file_b.setText(file_path)
 
@@ -743,21 +743,67 @@ class UpdateOptodesWindow(QWidget):
         fiducials = {}
         ch_positions = {}
 
+        extension = Path(file_b).suffix
+
         # Read the lines from the optode file
-        with open(file_b, 'r') as f:
+        if extension == '.txt':
-            for line in f:
+            with open(file_b, 'r') as f:
-                if line.strip():
+                for line in f:
-                    # Split by the semicolon and convert to meters
+                    if line.strip():
-                    ch_name, coords_str = line.split(":")
+                        # Split by the semicolon and convert to meters
-                    coords = np.array(list(map(float, coords_str.strip().split()))) * 0.001
+                        ch_name, coords_str = line.split(":")
+                        coords = np.array(list(map(float, coords_str.strip().split()))) * 0.001
 
-                    # The key we have is a fiducial
+                        # The key we have is a fiducial
-                    if ch_name.lower() in ['lpa', 'nz', 'rpa']:
+                        if ch_name.lower() in ['lpa', 'nz', 'rpa']:
-                        fiducials[ch_name.lower()] = coords
+                            fiducials[ch_name.lower()] = coords
 
-                    # The key we have is a source or detector
+                        # The key we have is a source or detector
-                    else:
+                        else:
-                        ch_positions[ch_name.upper()] = coords
+                            ch_positions[ch_name.upper()] = coords
+
+        elif extension == '.xlsx':
+
+            df = pd.read_excel(file_b, sheet_name='Sheet1')
+
+            def _get_block_data(df, block_id, row_mapping, scale=0.001):
+                """Isolates a block, cleans numeric data, and returns a scaled dictionary."""
+                # 1. Isolate and clean
+                block = df[df['block_id'] == block_id].iloc[:, [1, 2, 3]].copy()
+                block = block.apply(pd.to_numeric, errors='coerce')
+                
+                # 2. Extract into dictionary based on mapping
+                result = {}
+                
+                # If row_mapping is a dict (like {0: 'nz'}), use it directly
+                if isinstance(row_mapping, dict):
+                    for row_idx, key in row_mapping.items():
+                        if row_idx < len(block):
+                            result[key] = block.iloc[row_idx].to_numpy(dtype=float) * scale
+                
+                # If row_mapping is a string prefix (like 'D' or 'S'), auto-generate keys
+                elif isinstance(row_mapping, str):
+                    for i in range(len(block)):
+                        result[f"{row_mapping}{i+1}"] = block.iloc[i].to_numpy(dtype=float) * scale
+                        
+                return result
+
+                    
+            # Identify blocks
+            is_empty = df.isnull().all(axis=1)
+            df['block_id'] = is_empty.cumsum()
+            clean_df = df[~is_empty].copy()
+
+            # Process Block 2: Landmarks
+            fiducials = _get_block_data(clean_df, 2, {0: 'nz', 2: 'rpa', 3: 'lpa'})
+
+            # Process Block 3: D-Points
+            d_points = _get_block_data(clean_df, 3, 'D')
+
+            # Process Block 4: S-Points
+            s_points = _get_block_data(clean_df, 4, 'S')
+
+            ch_positions = {**d_points, **s_points}
 
         # Create montage with updated coords in head space
         initial_montage = make_dig_montage(ch_pos=ch_positions, nasion=fiducials.get('nz'), lpa=fiducials.get('lpa'), rpa=fiducials.get('rpa'), coord_frame='head') # type: ignore