Witvliet_DataReaders

c302/W7_SpreadsheetDataReader.py

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+from c302.NeuroMLUtilities import ConnectionInfo
+from c302.NeuroMLUtilities import analyse_connections
+
+from openpyxl import load_workbook
+import os
+
+spreadsheet_location = os.path.dirname(os.path.abspath(__file__))+"/data/"
+
+
+from c302 import print_
+
+def read_data(include_nonconnected_cells=False, neuron_connect=False):
+
+    if neuron_connect:
+        conns = []
+        cells = []
+        filename = "%switvliet_2020_7_adult.xlsx"%spreadsheet_location
+        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):  # Assuming data starts from the second row
+            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)
+
+        return cells, conns
+
+    else:
+        conns = []
+        cells = []
+        filename = "%switvliet_2020_7_adult.xlsx"%spreadsheet_location
+        wb = load_workbook(filename)
+        sheet = wb.worksheets[0]
+
+        print_("Opened Excel file..: " + filename)
+
+        known_nonconnected_cells = ['CANL', 'CANR', 'VC6']
+
+
+        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:
+            for c in known_nonconnected_cells: cells.append(c)
+
+        return cells, conns
+
+
+def read_muscle_data():
+
+    conns = []
+    neurons = []
+    muscles = []
+
+    filename = "%switvliet_2020_7_adult.xlsx"%spreadsheet_location
+    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():
+
+    cells, neuron_conns = read_data(include_nonconnected_cells=True)
+    neurons2muscles, muscles, muscle_conns = read_muscle_data()
+
+    analyse_connections(cells, neuron_conns, neurons2muscles, muscles, muscle_conns)
+
+if __name__ == '__main__':
+
+    main()
+

c302/WL1_SpreadsheetDataReader1.py

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+from c302.NeuroMLUtilities import ConnectionInfo
+from c302.NeuroMLUtilities import analyse_connections
+
+from openpyxl import load_workbook
+import os
+
+spreadsheet_location = os.path.dirname(os.path.abspath(__file__))+"/data/"
+
+
+from c302 import print_
+
+def read_data(include_nonconnected_cells=False, neuron_connect=False):
+
+    if neuron_connect:
+        conns = []
+        cells = []
+        filename = "%switvliet_2020_1_L1.xlsx"%spreadsheet_location
+        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):  # Assuming data starts from the second row
+            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)
+
+        return cells, conns
+
+    else:
+        conns = []
+        cells = []
+        filename = "%switvliet_2020_1_L1.xlsx"%spreadsheet_location
+        wb = load_workbook(filename)
+        sheet = wb.worksheets[0]
+
+        print_("Opened Excel file..: " + filename)
+
+        known_nonconnected_cells = ['CANL', 'CANR', 'VC6']
+
+
+        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:
+            for c in known_nonconnected_cells: cells.append(c)
+
+        return cells, conns
+
+
+def read_muscle_data():
+
+    conns = []
+    neurons = []
+    muscles = []
+
+    filename = "%switvliet_2020_1_L1.xlsx"%spreadsheet_location
+    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():
+
+    cells, neuron_conns = read_data(include_nonconnected_cells=True)
+    neurons2muscles, muscles, muscle_conns = read_muscle_data()
+
+    analyse_connections(cells, neuron_conns, neurons2muscles, muscles, muscle_conns)
+
+if __name__ == '__main__':
+
+    main()

c302/WL1_SpreadsheetDataReader2.py

@@ -0,0 +1,109 @@
+from c302.NeuroMLUtilities import ConnectionInfo
+from c302.NeuroMLUtilities import analyse_connections
+
+from openpyxl import load_workbook
+import os
+
+spreadsheet_location = os.path.dirname(os.path.abspath(__file__))+"/data/"
+
+
+from c302 import print_
+
+def read_data(include_nonconnected_cells=False, neuron_connect=False):
+
+    if neuron_connect:
+        conns = []
+        cells = []
+        filename = "%switvliet_2020_2_L1.xlsx"%spreadsheet_location
+        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):  # Assuming data starts from the second row
+            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)
+
+        return cells, conns
+
+    else:
+        conns = []
+        cells = []
+        filename = "%switvliet_2020_2_L1.xlsx"%spreadsheet_location
+        wb = load_workbook(filename)
+        sheet = wb.worksheets[0]
+
+        print_("Opened Excel file..: " + filename)
+
+        known_nonconnected_cells = ['CANL', 'CANR', 'VC6']
+
+
+        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:
+            for c in known_nonconnected_cells: cells.append(c)
+
+        return cells, conns
+
+
+def read_muscle_data():
+
+    conns = []
+    neurons = []
+    muscles = []
+
+    filename = "%switvliet_2020_2_L1.xlsx"%spreadsheet_location
+    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():
+
+    cells, neuron_conns = read_data(include_nonconnected_cells=True)
+    neurons2muscles, muscles, muscle_conns = read_muscle_data()
+
+    analyse_connections(cells, neuron_conns, neurons2muscles, muscles, muscle_conns)
+
+if __name__ == '__main__':
+
+    main()