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vector strength

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Ramona 2018-11-15 15:48:34 +01:00
parent 466a46c966
commit cf4d63966a
2 changed files with 16 additions and 5 deletions
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11
code/analysis_rs.py
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@ -3,6 +3,7 @@ import matplotlib.pyplot as plt
from read_baseline_data import * from read_baseline_data import *
from IPython import embed from IPython import embed
from NixFrame import * from NixFrame import *
from utility import *
inch_factor = 2.54 inch_factor = 2.54
data_dir = '../data' data_dir = '../data'
@ -53,6 +54,7 @@ max_cut = int(np.max(np.diff(eod_idx)))
eod_cuts = np.zeros([len(eod_idx)-1, max_cut]) eod_cuts = np.zeros([len(eod_idx)-1, max_cut])
# eods 15 + 16 are to short # eods 15 + 16 are to short
relative_times = [] relative_times = []
eod_durations = []
for i, idx in enumerate(eod_idx[:-1]): for i, idx in enumerate(eod_idx[:-1]):
eod_cut = eod[int(idx):int(eod_idx[i+1])] eod_cut = eod[int(idx):int(eod_idx[i+1])]
@ -63,14 +65,20 @@ for i, idx in enumerate(eod_idx[:-1]):
relative_time = spike_cut - time_cut[0] relative_time = spike_cut - time_cut[0]
if len(relative_time) > 0: if len(relative_time) > 0:
relative_times.append(relative_time[:][0]*1000) relative_times.append(relative_time[:][0]*1000)
eod_durations.append(len(eod_cut))
mu_eod = np.nanmean(eod_cuts, axis=0) mu_eod = np.nanmean(eod_cuts, axis=0)
std_eod = np.nanstd(eod_cuts, axis=0)*3 std_eod = np.nanstd(eod_cuts, axis=0)*3
time_axis = np.arange(max_cut)/sampling_rate*1000 vs = vector_strength(relative_times, eod_durations)
embed()
exit()
#time_axis = np.arange(max_cut)/sampling_rate*1000
#fig = plt.figure(figsize=(12/inch_factor, 8/inch_factor)) #fig = plt.figure(figsize=(12/inch_factor, 8/inch_factor))
'''
fig, ax1 = plt.subplots(figsize=(12/inch_factor, 8/inch_factor)) fig, ax1 = plt.subplots(figsize=(12/inch_factor, 8/inch_factor))
ax1.hist(relative_times, color='crimson') ax1.hist(relative_times, color='crimson')
ax1.set_xlabel('time [ms]', fontsize=12) ax1.set_xlabel('time [ms]', fontsize=12)
@ -90,4 +98,5 @@ plt.xticks(fontsize = 8)
plt.yticks(fontsize = 8) plt.yticks(fontsize = 8)
fig.tight_layout() fig.tight_layout()
plt.show() plt.show()
'''

10
code/utility.py
View File

@ -11,8 +11,10 @@ def zero_crossing(eod,time):
def vector_strength(spike_times, eod_durations): def vector_strength(spike_times, eod_durations):
alphas = spike_times/ eod_durations n = len(spike_times)
cs = (1/len(spike_times))*np.sum(np.cos(alphas))^2 phase_times = np.zeros(n)
sn = (1/len(spike_times))*np.sum(np.sin(alphas))^2 for i, idx in enumerate(spike_times):
vs = np.sqrt(cs+sn) phase_times[i]= spike_times[i]/eod_durations[i]
vs = np.sqrt((1/n*sum(np.cos(phase_times)))**2 + (1/n*sum(np.sin(phase_times)))**2)
return vs return vs