import numpy as np import os import numpy as np import matplotlib.pyplot as plt from thunderfish.powerspectrum import decibel from IPython import embed from pandas import read_csv from modules.logger import makeLogger from modules.plotstyle import PlotStyle from modules.behaviour_handling import Behavior, correct_chasing_events from extract_chirps import get_valid_datasets ps = PlotStyle() logger = makeLogger(__name__) def main(datapath: str): foldernames = [ datapath + x + "/" for x in os.listdir(datapath) if os.path.isdir(datapath + x) ] foldernames, _ = get_valid_datasets(datapath) for foldername in foldernames[3:4]: print(foldername) # foldername = foldernames[0] if foldername == "../data/mount_data/2020-05-12-10_00/": continue # behabvior is pandas dataframe with all the data bh = Behavior(foldername) # 2020-06-11-10 category = bh.behavior timestamps = bh.start_s # Correct for doubles in chasing on- and offsets to get the right on-/offset pairs # Get rid of tracking faults (two onsets or two offsets after another) category, timestamps = correct_chasing_events(category, timestamps) # split categories chasing_onset = (timestamps[category == 0] / 60) / 60 chasing_offset = (timestamps[category == 1] / 60) / 60 physical_contact = (timestamps[category == 2] / 60) / 60 all_fish_ids = np.unique(bh.chirps_ids) fish1_id = all_fish_ids[0] fish2_id = all_fish_ids[1] # Associate chirps to inidividual fish fish1 = (bh.chirps[bh.chirps_ids == fish1_id] / 60) / 60 fish2 = (bh.chirps[bh.chirps_ids == fish2_id] / 60) / 60 embed() exit() fish1_color = ps.gblue2 fish2_color = ps.gblue1 fig, ax = plt.subplots( 5, 1, figsize=(21 * ps.cm, 10 * ps.cm), height_ratios=[0.5, 0.5, 0.5, 0.2, 6], sharex=True, ) # marker size s = 80 ax[0].scatter( physical_contact, np.ones(len(physical_contact)), color=ps.gray, marker="|", s=s, ) ax[1].scatter( chasing_onset, np.ones(len(chasing_onset)), color=ps.gray, marker="|", s=s, ) ax[2].scatter( fish1, np.ones(len(fish1)) - 0.25, color=fish1_color, marker="|", s=s, ) ax[2].scatter( fish2, np.zeros(len(fish2)) + 0.25, color=fish2_color, marker="|", s=s, ) freq_temp = bh.freq[bh.ident == fish1_id] time_temp = bh.time[bh.idx[bh.ident == fish1_id]] ax[4].plot((time_temp / 60) / 60, freq_temp, color=fish1_color) freq_temp = bh.freq[bh.ident == fish2_id] time_temp = bh.time[bh.idx[bh.ident == fish2_id]] ax[4].plot((time_temp / 60) / 60, freq_temp, color=fish2_color) # ax[3].imshow(decibel(bh.spec), extent=[bh.time[0]/60/60, bh.time[-1]/60/60, 0, 2000], aspect='auto', origin='lower') # Hide grid lines ax[0].grid(False) ax[0].set_frame_on(False) ax[0].set_xticks([]) ax[0].set_yticks([]) ps.hide_ax(ax[0]) ax[1].grid(False) ax[1].set_frame_on(False) ax[1].set_xticks([]) ax[1].set_yticks([]) ps.hide_ax(ax[1]) ax[2].grid(False) ax[2].set_frame_on(False) ax[2].set_yticks([]) ax[2].set_xticks([]) ps.hide_ax(ax[2]) ax[4].axvspan(0, 3, 0, 5, facecolor="grey", alpha=0.5) ax[4].set_xticks(np.arange(0, 6.1, 0.5)) ps.hide_ax(ax[3]) labelpad = 30 fsize = 12 ax[0].set_ylabel( "Contact", rotation=0, labelpad=labelpad, fontsize=fsize ) ax[0].yaxis.set_label_coords(-0.062, -0.08) ax[1].set_ylabel( "Chasing", rotation=0, labelpad=labelpad, fontsize=fsize ) ax[1].yaxis.set_label_coords(-0.06, -0.08) ax[2].set_ylabel( "Chirps", rotation=0, labelpad=labelpad, fontsize=fsize ) ax[2].yaxis.set_label_coords(-0.07, -0.08) ax[4].set_ylabel("EODf") ax[4].set_xlabel("Time [h]") # ax[0].set_title(foldername.split('/')[-2]) # 2020-03-31-9_59 plt.subplots_adjust(left=0.158, right=0.987, top=0.918, bottom=0.136) plt.savefig("../poster/figs/timeline.svg") plt.show() # plot chirps if __name__ == "__main__": # Path to the data datapath = "../data/mount_data/" main(datapath)