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tested and corrected sam_data function

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mbergmann 2024-10-22 15:12:28 +02:00
parent c7436ad6b6
commit c995ed7a3b
1 changed files with 46 additions and 43 deletions
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code/test.py
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@ -5,6 +5,7 @@ import matplotlib.pyplot as plt
import rlxnix as rlx
from IPython import embed
from scipy.signal import welch
import useful_functions as f
def binary_spikes(spike_times, duration, dt):
"""
@ -68,10 +69,10 @@ def extract_stim_data(stimulus):
'''
# extract metadata
# the stim.name adjusts the first key as it changes with every stimulus
amplitude = stim.metadata[stim.name]['Contrast'][0][0]
df = stim.metadata[stim.name]['DeltaF'][0][0]
eodf = round(stim.metadata[stim.name]['EODf'][0][0])
stim_freq = round(stim.metadata[stim.name]['Frequency'][0][0])
amplitude = stimulus.metadata[stimulus.name]['Contrast'][0][0]
df = stimulus.metadata[stimulus.name]['DeltaF'][0][0]
eodf = round(stimulus.metadata[stimulus.name]['EODf'][0][0])
stim_freq = round(stimulus.metadata[stimulus.name]['Frequency'][0][0])
# calculates the amplitude modulation
amp_mod, ny_freq = AM(eodf, stim_freq)
return amplitude, df, eodf, stim_freq, amp_mod, ny_freq
@ -187,7 +188,7 @@ def sam_data(sam):
#find example data
datafolder = "../../data"
example_file = datafolder + "/" + "2024-10-16-ah-invivo-1.nix"
example_file = datafolder + "/" + "2024-10-16-ad-invivo-1.nix"
data_files = glob.glob("../../data/*.nix")
@ -209,41 +210,43 @@ ax.scatter(spike_times[spike_times < 0.1],
np.ones_like(spike_times[spike_times < 0.1]) * np.max(potential)) #plot teh spike times on top
plt.show()
plt.close()
# get all the stimuli
stims = sam.stimuli
# empty list for the spike times
spikes = []
#spikes2 = np.array(range(len(stims)))
# loop over the stimuli
for stim in stims:
# get the spike times
spike, _ = stim.trace_data('Spikes-1')
# append the first 100ms to spikes
spikes.append(spike[spike < 0.1])
# get stimulus duration
duration = stim.duration
ti = stim.trace_info("V-1")
dt = ti.sampling_interval # get the stimulus interval
bin_spikes = binary_spikes(spike, duration, dt) #binarize the spike_times
print(len(bin_spikes))
pot,tim= stim.trace_data("V-1") #membrane potential
rate = firing_rate(bin_spikes, dt = dt)
print(np.mean(rate))
fig, [ax1, ax2] = plt.subplots(1, 2,layout = 'constrained')
ax1.plot(tim,rate)
ax1.set_ylim(0,600)
ax1.set_xlim(0, 0.04)
freq, power = power_spectrum(rate, dt)
ax2.plot(freq,power)
ax2.set_xlim(0,1000)
plt.close()
if stim == stims[-1]:
amplitude, df, eodf, stim_freq = extract_stim_data(stim)
print(amplitude, df, eodf, stim_freq)
# make an eventplot
fig = plt.figure(figsize = (5, 3), layout = 'constrained')
ax = fig.add_subplot()
ax.eventplot(spikes, linelength = 0.8)
ax.set_xlabel('time [ms]')
ax.set_ylabel('loop no.')
sam_amp, sam_am,sam_df, sam_eodf, sam_nyquist, sam_stim = f.sam_data(sam)
# # get all the stimuli
# stims = sam.stimuli
# # empty list for the spike times
# spikes = []
# #spikes2 = np.array(range(len(stims)))
# # loop over the stimuli
# for stim in stims:
# # get the spike times
# spike, _ = stim.trace_data('Spikes-1')
# # append the first 100ms to spikes
# spikes.append(spike[spike < 0.1])
# # get stimulus duration
# duration = stim.duration
# ti = stim.trace_info("V-1")
# dt = ti.sampling_interval # get the stimulus interval
# bin_spikes = binary_spikes(spike, duration, dt) #binarize the spike_times
# print(len(bin_spikes))
# pot,tim= stim.trace_data("V-1") #membrane potential
# rate = firing_rate(bin_spikes, dt = dt)
# print(np.mean(rate))
# fig, [ax1, ax2] = plt.subplots(1, 2,layout = 'constrained')
# ax1.plot(tim,rate)
# ax1.set_ylim(0,600)
# ax1.set_xlim(0, 0.04)
# freq, power = power_spectrum(rate, dt)
# ax2.plot(freq,power)
# ax2.set_xlim(0,1000)
# plt.close()
# if stim == stims[-1]:
# amplitude, df, eodf, stim_freq = extract_stim_data(stim)
# print(amplitude, df, eodf, stim_freq)
# # make an eventplot
# fig = plt.figure(figsize = (5, 3), layout = 'constrained')
# ax = fig.add_subplot()
# ax.eventplot(spikes, linelength = 0.8)
# ax.set_xlabel('time [ms]')
# ax.set_ylabel('loop no.')