neu

code/func_chirp.py

@@ -0,0 +1,41 @@
+from read_baseline_data import *
+from read_chirp_data import *
+from utility import *
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def chirp_eod_plot(df_map, eod, times):
+	#die äußere Schleife geht für alle Keys durch und somit durch alle dfs
+	#die innnere Schleife bildet die 16 Wiederholungen einer Frequenz ab
+
+	for i in df_map.keys():
+	freq = list(df_map[i]) 
+	fig,axs = plt.subplots(2, 2, sharex = True, sharey = True)
+
+	for idx, k in enumerate(freq):
+		ct = times[k]
+		e1 = eod[k]
+		zeit = e1[0]
+		eods = e1[1]
+	
+		if idx <= 3:
+			axs[0, 0].plot(zeit, eods, color= 'blue', linewidth = 0.25)
+			axs[0, 0].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
+		elif 4<= idx <= 7:
+			axs[0, 1].plot(zeit, eods, color= 'blue', linewidth = 0.25)
+			axs[0, 1].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
+		elif 8<= idx <= 11:
+			axs[1, 0].plot(zeit, eods, color= 'blue', linewidth = 0.25)
+			axs[1, 0].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
+		else: 
+			axs[1, 1].plot(zeit, eods, color= 'blue', linewidth = 0.25)
+			axs[1, 1].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
+
+fig.suptitle('EOD for chirps', fontsize = 16)
+axs[0,0].set_ylabel('Amplitude [mV]') 
+axs[0,1].set_xlabel('Amplitude [mV]')
+axs[1,0].set_xlabel('Time [ms]')
+axs[1,1].set_xlabel('Time [ms]')
+plt.show()
+

code/func_spike.py

@@ -0,0 +1,7 @@
+from read_baseline_data import *
+from read_chirp_data import *
+from utility import *
+import matplotlib.pyplot as plt
+import numpy as np
+
+