Merge pull request #66 from yasinthanvickneswaran/master

Test Witvliet

.github/workflows/non_omv.yml

@@ -1,4 +1,4 @@
-name: Non OMV tests
+name: Non-OMV-tests
 
 on:
   push:

c302/VarshneyDataReader.py

@@ -0,0 +1,109 @@
+from c302.NeuroMLUtilities import ConnectionInfo
+from c302.NeuroMLUtilities import analyse_connections
+
+from xlrd import open_workbook
+import os
+
+spreadsheet_location = os.path.dirname(os.path.abspath(__file__))+"/data/"
+
+from c302 import print_
+
+READER_DESCRIPTION = """Data extracted from NeuronConnectFormatted.xls for neuronal connectivity"""
+
+def read_data(include_nonconnected_cells=False, neuron_connect=True):
+
+
+
+# reading the NeuronConnectFormatted.xls file if neuron_connect = True
+    if neuron_connect:
+        conns = []
+        cells = []
+        filename = "%sNeuronConnectFormatted.xls"%spreadsheet_location
+        rb = open_workbook(filename)
+        print_("Opened the Excel file: " + filename)
+
+        for row in range(1,rb.sheet_by_index(0).nrows):
+            pre = str(rb.sheet_by_index(0).cell(row,0).value)
+            post = str(rb.sheet_by_index(0).cell(row,1).value)
+            syntype = rb.sheet_by_index(0).cell(row,2).value
+            num = int(rb.sheet_by_index(0).cell(row,3).value)
+            synclass = 'Generic_GJ' if 'EJ' 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 = "%sCElegansNeuronTables.xls"%spreadsheet_location
+        rb = open_workbook(filename)
+
+        print_("Opened Excel file: " + filename)
+
+        known_nonconnected_cells = ['CANL', 'CANR', 'VC6']
+
+
+        for row in range(1,rb.sheet_by_index(0).nrows):
+            pre = str(rb.sheet_by_index(0).cell(row,0).value)
+            post = str(rb.sheet_by_index(0).cell(row,1).value)
+            syntype = rb.sheet_by_index(0).cell(row,2).value
+            num = int(rb.sheet_by_index(0).cell(row,3).value)
+            synclass = rb.sheet_by_index(0).cell(row,4).value
+
+            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 = "%sNeuronConnectFormatted.xls"%spreadsheet_location
+    rb = open_workbook(filename)
+
+    print_("Opened Excel file: "+ filename)
+
+    sheet = rb.sheet_by_index(0)
+
+    for row in range(1,sheet.nrows):
+        pre = str(sheet.cell(row,0).value)
+        post = str(sheet.cell(row,1).value)
+        num = int(sheet.cell(row,3).value)
+        syntype = 'Send'
+        synclass = sheet.cell(row,2).value.replace(',', 'plus').replace(' ', '_')
+
+        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/W_SpreadsheetDataReader.py

@@ -0,0 +1,205 @@
+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_
+
+
+class WitvlietDataReader1:   
+
+    def read_data(include_nonconnected_cells=False, neuron_connect=False):
+
+        if neuron_connect:
+            conns = []
+            cells = []
+            filename = "%switvliet_2020_7.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.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.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 main1():
+
+    cells, neuron_conns = WitvlietDataReader1.read_data(include_nonconnected_cells=True)
+    neurons2muscles, muscles, muscle_conns = WitvlietDataReader1.read_muscle_data()
+
+    analyse_connections(cells, neuron_conns, neurons2muscles, muscles, muscle_conns)
+
+
+class WitvlietDataReader2:   
+    def read_data(include_nonconnected_cells=False, neuron_connect=False):
+
+        if neuron_connect:
+            conns = []
+            cells = []
+            filename = "%switvliet_2020_8.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_8.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_8.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 main2():
+
+    cells, neuron_conns = WitvlietDataReader2.read_data(include_nonconnected_cells=True)
+    neurons2muscles, muscles, muscle_conns = WitvlietDataReader2.read_muscle_data()
+
+    analyse_connections(cells, neuron_conns, neurons2muscles, muscles, muscle_conns)
+
+if __name__ == '__main__':
+    main1()
+    main2()