v1.0

load_data.py

@@ -0,0 +1,104 @@
+"""
+Load a nix data file from the data set of Henke et al. and make a basic
+plot of its contents.
+
+The nix files contain the spike times of a cell recorded in a recording session, stimulus
+onset and durations, reproduction onset times and durations, reward information,
+feedback range widths, and distance covered by the animal throughout the session.
+
+Use with Python 3.
+"""
+__author__ = ("Kay Thurley")
+__version__ = "1.0, November 2021"
+
+
+import sys
+import nixio
+import numpy as np
+
+
+###################################################### commandline parameters
+
+file_name = sys.argv[1]				# second argument should be the name of the file to load
+
+###################################################### load data
+
+file = nixio.File.open(file_name, nixio.FileMode.ReadOnly)
+session = file.blocks[0]
+metadata = file.sections[0]
+for key, m in metadata.items():
+    print(key+':', metadata[key])
+
+
+###################################################### plotting initialization
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+
+fontsize = 12.0
+markersize = 6
+
+mpl.rcParams['lines.linewidth'] = 2
+mpl.rcParams['lines.markersize'] = markersize
+mpl.rcParams['font.size'] = fontsize
+mpl.rcParams['xtick.direction'] = 'out'
+mpl.rcParams['ytick.direction'] = 'out'
+
+
+###################################################### plotting
+
+x_axis = session.data_arrays['spike times'].dimensions[0]
+spikes = session.data_arrays['spike times'].data[:]
+
+fig = plt.figure(figsize=(11, 3))
+ax = fig.add_axes([0.075, 0.25, 0.85, 0.625])
+
+# -- plot spikes
+ax.eventplot(spikes, colors=[[0, 0, 0]], lineoffsets=1, linelengths=.25, linewidth=.5, alpha=.5)
+
+
+# -- mark stimuli / measurement phase
+stimuli = session.multi_tags['stimuli']
+stimulus_onsets = stimuli.positions[:]
+stimulus_durations = stimuli.extents[:]
+for i, onset in enumerate(stimulus_onsets):
+    ax.axvspan(onset, onset+stimulus_durations[i],
+                          color='silver', alpha=0.5, zorder=0, label="measurement phase")
+    ax.text(onset, 1.2, stimuli.features[0].data[i][0], color="slategray", fontsize=8)
+
+
+# -- mark reproduction phase
+reproductions = session.multi_tags['reproductions']
+reproduction_onsets = reproductions.positions[:]
+reproduction_durations = reproductions.extents[:]
+rewards = session.data_arrays['rewards'].data[:]
+for i, onset in enumerate(reproduction_onsets):
+    # green color for reward, red for no reward
+    if rewards[i]:
+        col = 'green'
+    else:
+        col = 'red'
+    ax.axvspan(onset, onset + reproduction_durations[i],
+               color=col, alpha=0.5, zorder=0, label="reproduction phase")
+
+
+# -- add speed information
+ax2 = ax.twinx()
+distances = session.data_arrays['distance covered']
+x_axis = distances.dimensions[0]
+x = x_axis.axis(distances.data.shape[0])
+speed = np.diff(distances.data[:])/np.diff(x)
+line_speed, = ax2.plot(x[:-1], speed, '.-', linewidth=1, alpha=0.5, color=np.ones(3)*.5,
+                  markersize=1)
+
+
+# -- annotate plot
+ax.set_yticks([])
+ax.set_xlabel(x_axis.label.capitalize() + " (" + x_axis.unit + ")")
+ax2.set_ylabel('Speed (' + distances.unit + '/' + x_axis.unit + ')')
+
+
+###################################################### finishing
+
+file.close()
+plt.show()