witvliet

c302/W00_SpreadsheetDataReader.py

@@ -0,0 +1,94 @@
+from c302.NeuroMLUtilities import ConnectionInfo, analyse_connections
+from openpyxl import load_workbook
+import os
+from c302 import print_
+
+class Witvliet:
+    def __init__(self, file_prefix, num_files=8):
+        self.file_prefix = file_prefix
+        self.num_files = num_files
+        self.spreadsheet_location = os.path.dirname(os.path.abspath(__file__)) + "/data/"
+
+    def read_data(self, include_nonconnected_cells=False, neuron_connect=False):
+        all_cells = []
+        all_conns = []
+
+        for i in range(1, self.num_files + 1):
+            cells = []
+            conns = []
+            filename = f"{self.spreadsheet_location}{self.file_prefix}_{i}.xlsx"
+            wb = load_workbook(filename)
+            sheet = wb.worksheets[0]
+            print_("Opened the Excel file: " + filename)
+
+            for row in sheet.iter_rows(min_row=2, values_only=True):
+                pre = str(row[0])
+                post = str(row[1])
+                syntype = str(row[2])
+                num = int(row[3])
+                synclass = 'Generic_GJ' if 'electrical' in syntype else 'Chemical_Synapse'
+
+                conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
+                if pre not in cells:
+                    cells.append(pre)
+                if post not in cells:
+                    cells.append(post)
+
+            if include_nonconnected_cells:
+                known_nonconnected_cells = ['CANL', 'CANR', 'VC6']
+                for c in known_nonconnected_cells:
+                    cells.append(c)
+
+            all_cells.append(cells)
+            all_conns.append(conns)
+
+        return all_cells, all_conns
+
+    def read_muscle_data(self):
+        all_neurons = []
+        all_muscles = []
+        all_conns = []
+
+        for i in range(1, self.num_files + 1):
+            neurons = []
+            muscles = []
+            conns = []
+
+            filename = f"{self.spreadsheet_location}{self.file_prefix}_{i}.xlsx"
+            wb = load_workbook(filename)
+            sheet = wb.worksheets[0]
+            print_("Opened Excel file: " + filename)
+
+            for row in sheet.iter_rows(min_row=2, values_only=True):
+                pre = str(row[0])
+                post = str(row[1])
+                syntype = str(row[2])
+                num = int(row[3])
+                synclass = 'Generic_GJ' if 'electrical' in syntype else 'Chemical_Synapse'
+
+                conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
+                if pre not in neurons:
+                    neurons.append(pre)
+                if post not in muscles:
+                    muscles.append(post)
+
+            all_neurons.append(neurons)
+            all_muscles.append(muscles)
+            all_conns.append(conns)
+
+        return all_neurons, all_muscles, all_conns
+
+    def main(self):
+        all_cells, all_neuron_conns = self.read_data(include_nonconnected_cells=True)
+        all_neurons2muscles, all_muscles, all_muscle_conns = self.read_muscle_data()
+
+        for cells, neuron_conns in zip(all_cells, all_neuron_conns):
+            analyse_connections(cells, neuron_conns, [], [], [])  # Adjust the parameters accordingly
+
+        for neurons, muscles, muscle_conns in zip(all_neurons2muscles, all_muscles, all_muscle_conns):
+            analyse_connections([], [], neurons, muscles, muscle_conns)  # Adjust the parameters accordingly
+
+
+if __name__ == '__main__':
+    excel_reader = Witvliet(file_prefix='witvliet_2020', num_files=8)
+    excel_reader.main()

c302/W0_SpreadsheetDataReader.py

@@ -0,0 +1,76 @@
+from c302.NeuroMLUtilities import ConnectionInfo, analyse_connections
+from openpyxl import load_workbook
+import os
+from c302 import print_
+
+class ExcelDataReader:
+    def __init__(self, file_prefix, num_files=8):
+        self.file_prefix = file_prefix
+        self.num_files = num_files
+        self.spreadsheet_location = os.path.dirname(os.path.abspath(__file__)) + "/data/"
+
+    def read_data(self, include_nonconnected_cells=False, neuron_connect=False):
+        cells = []
+        conns = []
+
+        for i in range(1, self.num_files + 1):
+            filename = f"{self.spreadsheet_location}{self.file_prefix}_{i}.xlsx"
+            wb = load_workbook(filename)
+            sheet = wb.worksheets[0]
+            print_("Opened the Excel file: " + filename)
+
+            for row in sheet.iter_rows(min_row=2, values_only=True):
+                pre = str(row[0])
+                post = str(row[1])
+                syntype = str(row[2])
+                num = int(row[3])
+                synclass = 'Generic_GJ' if 'electrical' in syntype else 'Chemical_Synapse'
+
+                conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
+                if pre not in cells:
+                    cells.append(pre)
+                if post not in cells:
+                    cells.append(post)
+
+        if include_nonconnected_cells:
+            known_nonconnected_cells = ['CANL', 'CANR', 'VC6']
+            for c in known_nonconnected_cells:
+                cells.append(c)
+
+        return cells, conns
+
+    def read_muscle_data(self):
+        neurons = []
+        muscles = []
+        conns = []
+
+        for i in range(1, self.num_files + 1):
+            filename = f"{self.spreadsheet_location}{self.file_prefix}_{i}.xlsx"
+            wb = load_workbook(filename)
+            sheet = wb.worksheets[0]
+            print_("Opened Excel file: " + filename)
+
+            for row in sheet.iter_rows(min_row=2, values_only=True):
+                pre = str(row[0])
+                post = str(row[1])
+                syntype = str(row[2])
+                num = int(row[3])
+                synclass = 'Generic_GJ' if 'electrical' in syntype else 'Chemical_Synapse'
+
+                conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
+                if pre not in neurons:
+                    neurons.append(pre)
+                if post not in muscles:
+                    muscles.append(post)
+
+        return neurons, muscles, conns
+
+    def main(self):
+        cells, neuron_conns = self.read_data(include_nonconnected_cells=True)
+        neurons2muscles, muscles, muscle_conns = self.read_muscle_data()
+        analyse_connections(cells, neuron_conns, neurons2muscles, muscles, muscle_conns)
+
+
+if __name__ == '__main__':
+    excel_reader = ExcelDataReader(file_prefix='witvliet_2020', num_files=8)
+    excel_reader.main()

c302/W_SpreadsheetDataReader.py

@@ -14,7 +14,7 @@ def read_data(include_nonconnected_cells=False, neuron_connect=False):
     if neuron_connect:
         conns = []
         cells = []
-        filename = "%switvliet_2020_8_adult.xlsx"%spreadsheet_location
+        filename = "%switvliet_2020_8.xlsx"%spreadsheet_location
         wb = load_workbook(filename)
         sheet = wb.worksheets[0]
         print_("Opened the Excel file: " + filename)
@@ -38,7 +38,7 @@ def read_data(include_nonconnected_cells=False, neuron_connect=False):
     else:
         conns = []
         cells = []
-        filename = "%switvliet_2020_8_adult.xlsx"%spreadsheet_location
+        filename = "%switvliet_2020_8.xlsx"%spreadsheet_location
         wb = load_workbook(filename)
         sheet = wb.worksheets[0]
 
@@ -73,7 +73,7 @@ def read_muscle_data():
     neurons = []
     muscles = []
 
-    filename = "%switvliet_2020_8_adult.xlsx"%spreadsheet_location
+    filename = "%switvliet_2020_8.xlsx"%spreadsheet_location
     wb = load_workbook(filename)
     sheet = wb.worksheets[0]
 
@@ -107,4 +107,3 @@ def main():
 if __name__ == '__main__':
 
     main()
-