From 1daf5c244ed736f8113df00a20e8be9550393060 Mon Sep 17 00:00:00 2001 From: Ramona Date: Tue, 20 Nov 2018 17:40:37 +0100 Subject: [PATCH] data is ready for plotting --- code/spikes_analysis.py | 42 +++++++++++++++++++++++++---------------- 1 file changed, 26 insertions(+), 16 deletions(-) diff --git a/code/spikes_analysis.py b/code/spikes_analysis.py index 2d72447..a665a80 100644 --- a/code/spikes_analysis.py +++ b/code/spikes_analysis.py @@ -4,6 +4,7 @@ from read_chirp_data import * from utility import * from IPython import embed +sampling_rate = 40 #kHz data_dir = "../data" dataset = "2018-11-09-ad-invivo-1" @@ -21,37 +22,46 @@ for k in spikes.keys(): # make phases together, 12 phases phase_vec = np.arange(0, 1+1/12, 1/12) -phase_mat_df = {} +cut_range = np.arange(-50*sampling_rate, 50*sampling_rate, 1) + +df_phase_time = {} +df_phase_binary = {} for deltaf in df_map.keys(): - phase_df = {} + df_phase_time[deltaf] = {} + df_phase_binary[deltaf] = {} for rep in df_map[deltaf]: for phase in spikes[rep]: #print(phase) for idx in range(len(phase_vec)-1): if phase[1] > phase_vec[idx] and phase[1] < phase_vec[idx+1]: - if phase_vec[idx] in phase_df.keys(): - phase_df[phase_vec[idx]].append(phase) - else: - phase_df[phase_vec[idx]] = [phase] - - #spikes_one_chirp = spikes[rep][phase] + spikes_to_cut = np.asarray(spikes[rep][phase]) + spikes_cut = spikes_to_cut[(spikes_to_cut > -50) & (spikes_to_cut < 50)] + spikes_idx = np.round(spikes_cut*sampling_rate) + binary_spikes = np.isin(cut_range, spikes_idx)*1 - phase_mat_df[deltaf] = phase_df + if phase_vec[idx] in df_phase_time[deltaf].keys(): + df_phase_time[deltaf][phase_vec[idx]].append(spikes[rep][phase]) + df_phase_binary[deltaf][phase_vec[idx]] = np.vstack((df_phase_binary[deltaf][phase_vec[idx]], binary_spikes)) + else: + df_phase_time[deltaf][phase_vec[idx]] = [spikes[rep][phase]] + df_phase_binary[deltaf][phase_vec[idx]] = binary_spikes -#df_spikes = spikes[df_map['-50Hz'][0]] -#phase_spikes = df_spikes[phase_mat_df['-50Hz'][0.0][0]] -trial_spikes = np.asarray(spikes[(0, '-50Hz', '20%', '100Hz')][(0, 0.789)]) -plot_spikes = trial_spikes[(trial_spikes < 50.0) & (trial_spikes > -50.0)] +plot_trials = df_phase_binary['-50Hz'][0.0] +#hist_data = plt.hist(plot_trials) +#ax.plot(hist_data[1][:-1], hist_data[0]) -hist_data = plt.hist(plot_spikes, color='w') fig, ax = plt.subplots() -ax.scatter(plot_spikes, np.ones(len(plot_spikes))*10, marker='|', color='k') -ax.plot(hist_data[1][:-1], hist_data[0]) +for i, trial in enumerate(plot_trials): + embed() + exit() + trial[trial == 0] = np.nan + ax.scatter(np.ones(len(trial)), trial, marker='|', color='k', size=12) plt.show() + #mu = 1 #sigma = 1 #time_gauss = np.arange(-4, 4, 1)