happy weekend

ephys_analysis.py

@@ -1,4 +1,3 @@
-import os
 import numpy as np
 import matplotlib.pyplot as plt
 import nixio as nix
@@ -6,62 +5,87 @@ import glob
 import os
 from IPython import embed
 
+
+def stimulus_collector(filename):
+    try:
+        stims = []
+        f = nix.File.open(filename, nix.FileMode.ReadOnly)
+        b = f.blocks[0]
+        for g in b.groups:
+            # embed()
+            # exit()
+            stims.append(g.multi_tags[0].name)
+    except KeyError:
+        embed()
+        exit()
+    return stims
+
+
 def analyze_sams(filename):
-    # print(filename)
+    print(filename)
     f = nix.File.open(filename, nix.FileMode.ReadOnly)
     b = f.blocks[0]
     b.metadata.pprint(max_depth=-1) # max_depth=-1: alles rausschreiben
-    # print(b.groups)
     for g in b.groups:
-        if 'sam' in g.name.lower(): # go through loop, until 'sam' is found
-            break
-        rtag_data = g.tags[0]
-        rtag_data.metadata.pprint(max_depth=-1)
-        # print(40*'*')
-        stim_tag = g.multi_tags[0]
-        stim_pos = stim_tag.positions[:] # beginnings of stimulations
-        stim_extent = stim_tag.extents[:] # duration of stimulations
-        # embed()
-        # exit()
-        for r in rtag_data.references:
-            print(r.name, r.type)
-        # embed()
-        # exit()
-        voltage_trace = rtag_data.references['V-1']
 
-        spike_data = []
+        embed()
+        exit()
+        for stim in stims:
+            print(stim)
+            if stim in g.name.lower():
+                # embed()
+                # exit()
+                # if 'sam' in g.name.lower(): # go through loop, until 'sam' is found
+                #     break
+                rtag_data = g.tags[0]
+                # rtag_data.metadata.pprint(max_depth=-1)
+                #
+                # print(40*'*')
+
+                stim_tag = g.multi_tags[0]
+                stim_type = g.multi_tags[0].name
+                stim_pos = stim_tag.positions[:] # beginnings of stimulations
+                stim_extent = stim_tag.extents[:] # duration of stimulations
+
+                # for r in rtag_data.references:
+                #     print(r.name, r.type)
+
+                voltage_trace = rtag_data.references['V-1']
+
+                spike_data = []
 
-        for idx in range(len(stim_pos)):
-            spike_data.append(stim_tag.retrieve_data(idx, 'Spikes-1')[:])
+                for idx in range(len(stim_pos)):
+                    spike_data.append(stim_tag.retrieve_data(idx, 'Spikes-1')[:])
 
-        # embed()
-        # exit()
-        dims = voltage_trace.dimensions[0].axis(len(voltage_trace))
+                dims = voltage_trace.dimensions[0].axis(len(voltage_trace))
+                plt.plot(dims[:-1], voltage_trace[:-1])
+                for i in range(len(stim_pos)):
+                    stim_y = [np.max(voltage_trace)+10, np.max(voltage_trace)+10]
+                    plt.plot([stim_pos[i], stim_pos[i] + stim_extent[i]], stim_y, 'k')
 
-        # # f.close()
-        # embed()
-    # exit()
-    return stim_pos, stim_extent, spike_data, voltage_trace, dims
+                for j in range(len(spike_data)):
+                    for k in range(len(spike_data[j])):
+                        plt.plot(spike_data[j][k], np.max(voltage_trace)+5, 'o', color='k')
+                plt.xlim([stim_pos[0]-1, stim_extent[-1]+1])
+                plt.title(filename + ': ' + stim_type)
+                # plt.show()
+                print('saving...')
+                os.chdir('/home/lisa/Dropbox/Masterarbeit/')
+                plt.savefig(filename[-22:-19] + ': ' + stim + '.png')
+                plt.close()
+                # f.close()
+                # embed()
+                # exit()
+        return
 
 
 if __name__ == '__main__':
-    data_dir = '/home/lisa/data'
+    data_dir = '/home/lisa/data/'
     os.chdir(data_dir)
-    data_set = glob.glob('2019-*')
-    stim_pos, stim_extent, spike_data, voltage_trace, dims = analyze_sams(os.path.join(data_dir, data_set,
-                                                                                       data_set + '.nix'))
-    print(len(spike_data))
-    stims = []
-    for i in range(len(stim_pos)):
-        stim_y = [-38, -38]
-        plt.plot([stim_pos[i], stim_pos[i] + stim_extent[i]], stim_y, 'k')
-    plt.plot(dims[:-1], voltage_trace[:-1])
-    spike_y = np.ones(len(spike_data))*80
+    # data_set = glob.glob('2019-*')
+    # for i in range(len(data_set)):
+    data_set = '2019-08-22-aa-invivo-1'
+    # print(data_dir + data_set[i] + '/' + data_set[i])
+    # stims = stimulus_collector(data_dir + data_set[i] + '/' + data_set[i] + '.nix')
+    analyze_sams(data_dir + data_set + '/' + data_set + '.nix')
 
-    for j in range(len(spike_data)):
-        print('length of current spike train: ', len(spike_data))
-        for k in range(len(spike_data[j])):
-            print('current spike time is: ', spike_data[j][k])
-            plt.plot(spike_data[j][k], -40, 'o', color='k')
-    # plt.ylim([-45, 0])
-    plt.show()

stimuli_figures.py

@@ -1,6 +1,6 @@
 import glob
 import matplotlib.pyplot as plt
-
+# figures for phase_ and amplitude_sweep should be made with artificial data
 filenames = glob.glob('*.dat')
 
 for i in range(len(filenames)):