analysis

code/analysis_rs.py

@@ -2,21 +2,22 @@ import numpy as np
 import matplotlib.pyplot as plt
 from read_baseline_data import *
 from IPython import embed
+from NixFrame import *
 
 inch_factor = 2.54
 data_dir = '../data'
 dataset = '2018-11-09-ad-invivo-1'
 time, eod = read_baseline_eod(os.path.join(data_dir, dataset))
 
-fig = plt.figure(figsize=(12/inch_factor, 8/inch_factor))
-ax = fig.add_subplot(111)
-ax.plot(time[:1000], eod[:1000])
-ax.set_xlabel('time [ms]', fontsize=12)
-ax.set_ylabel('voltage [mV]', fontsize=12)
-plt.xticks(fontsize = 8)
-plt.yticks(fontsize = 8)
-fig.tight_layout()
-plt.savefig('eod.pdf')
+#fig = plt.figure(figsize=(12/inch_factor, 8/inch_factor))
+#ax = fig.add_subplot(111)
+#ax.plot(time[:1000], eod[:1000])
+#ax.set_xlabel('time [ms]', fontsize=12)
+#ax.set_ylabel('voltage [mV]', fontsize=12)
+#plt.xticks(fontsize = 8)
+#plt.yticks(fontsize = 8)
+#fig.tight_layout()
+#plt.savefig('eod.pdf')
 
 #interspikeintervalhistogram, windowsize = 1 ms
 #plt.hist
@@ -26,14 +27,14 @@ plt.savefig('eod.pdf')
 
 spikes = read_baseline_spikes(os.path.join(data_dir, dataset))
 interspikeintervals = np.diff(spikes)
-fig = plt.figure()
-plt.hist(interspikeintervals, bins=np.arange(0, np.max(interspikeintervals), 0.0001))
-plt.show()
+#fig = plt.figure()
+#plt.hist(interspikeintervals, bins=np.arange(0, np.max(interspikeintervals), 0.0001))
+#plt.show()
 
 mu = np.mean(interspikeintervals)
 sigma = np.std(interspikeintervals)
 cv = sigma/mu
-print(cv)
+#print(cv)
 
 # calculate zero crossings of the eod
 # plot mean of eod circles
@@ -47,10 +48,15 @@ eod_times = time[(eod >= threshold) & (shift_eod < threshold)]
 sampling_rate = 40000.0
 eod_idx = eod_times*sampling_rate
 
-fig = plt.figure()
-for i, idx in enumerate(eod_idx):
-	#embed()
-	#exit()
-	plt.plot(time[int(idx):int(eod_idx[i+1])], eod[int(idx):int(eod_idx[i+1])])
-plt.show()
+#fig = plt.figure()
+eod_cuts = [];
+#for i, idx in enumerate(eod_idx)-1:
+	#eod_cuts.append(eod[int(idx):int(eod_idx[i+1])])
+	#time_cut = time[int(idx):int(eod_idx[i+1])]
+	#plt.plot(time[int(idx):int(eod_idx[i+1])], eod[int(idx):int(eod_idx[i+1])])
+#plt.show()
+data = NixToFrame(data_dir)
 
+
+embed()
+exit()