finished plot in chasing
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@ -110,7 +110,7 @@ def PlotStyle() -> None:
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plt.setp(bp["boxes"], color=color)
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plt.setp(bp["whiskers"], color=white)
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plt.setp(bp["caps"], color=white)
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plt.setp(bp["medians"], color=white)
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plt.setp(bp["medians"], color=black)
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@classmethod
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@ -255,10 +255,10 @@ def PlotStyle() -> None:
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plt.rcParams["boxplot.boxprops.color"] = gray
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plt.rcParams["boxplot.whiskerprops.color"] = gray
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plt.rcParams["boxplot.capprops.color"] = gray
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plt.rcParams["boxplot.medianprops.color"] = gray
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plt.rcParams["boxplot.medianprops.color"] = black
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plt.rcParams["text.color"] = white
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plt.rcParams["axes.facecolor"] = black # axes background color
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plt.rcParams["axes.edgecolor"] = gray # axes edge color
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plt.rcParams["axes.edgecolor"] = white # axes edge color
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# plt.rcParams["axes.grid"] = True # display grid or not
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# plt.rcParams["axes.grid.axis"] = "y" # which axis the grid is applied to
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plt.rcParams["axes.labelcolor"] = white
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@ -284,9 +284,9 @@ def PlotStyle() -> None:
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"#f5c2e7",
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],
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)
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plt.rcParams["xtick.color"] = gray # color of the ticks
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plt.rcParams["ytick.color"] = gray # color of the ticks
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plt.rcParams["grid.color"] = dark_gray # grid color
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plt.rcParams["xtick.color"] = white # color of the ticks
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plt.rcParams["ytick.color"] = white # color of the ticks
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plt.rcParams["grid.color"] = white # grid color
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plt.rcParams["figure.facecolor"] = black # figure face color
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plt.rcParams["figure.edgecolor"] = black # figure edge color
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plt.rcParams["savefig.facecolor"] = black # figure face color when saving
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@ -252,9 +252,9 @@ def main(datapath: str):
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size_loser_pearsonr = pearsonr(size_diffs_loser, size_chirps_loser)
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fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(
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21*ps.cm, 10*ps.cm), width_ratios=[1, 0.8, 0.8], sharey=True)
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plt.subplots_adjust(left=0.11, right=0.948, top=0.905,
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wspace=0.343, bottom=0.145)
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21*ps.cm, 8*ps.cm), width_ratios=[1, 0.8, 0.8], sharey=True)
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plt.subplots_adjust(left=0.11, right=0.948, top=0.86,
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wspace=0.343, bottom=0.18)
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scatterwinner = 1.15
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scatterloser = 1.85
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chirps_winner = np.asarray(chirps_winner)[~np.isnan(chirps_winner)]
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@ -262,47 +262,51 @@ def main(datapath: str):
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stat = wilcoxon(chirps_winner, chirps_loser)
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print(stat)
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winner_color = ps.lavender
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loser_color = ps.purple
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bplot1 = ax1.boxplot(chirps_winner, positions=[
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0.9], showfliers=False, patch_artist=True)
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bplot2 = ax1.boxplot(chirps_loser, positions=[
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2.1], showfliers=False, patch_artist=True)
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ax1.scatter(np.ones(len(chirps_winner)) *
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scatterwinner, chirps_winner, color=ps.red)
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scatterwinner, chirps_winner, color=winner_color)
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ax1.scatter(np.ones(len(chirps_loser)) *
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scatterloser, chirps_loser, color=ps.orange)
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ax1.set_xticklabels(['winner', 'loser'])
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scatterloser, chirps_loser, color=loser_color)
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ax1.set_xticklabels(['Winner', 'Loser'])
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ax1.text(0.1, 0.95, f'n={len(chirps_winner)}', transform=ax1.transAxes, color=ps.white)
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ax1.text(0.1, 0.95, f'n={len(chirps_winner)}',
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transform=ax1.transAxes, color=ps.white)
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for w, l in zip(chirps_winner, chirps_loser):
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ax1.plot([scatterwinner, scatterloser], [w, l],
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color=ps.white, alpha=1, linewidth=0.5)
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ax1.set_ylabel('chirpcounts', color=ps.white)
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ax1.set_xlabel('outcome', color=ps.white)
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color=ps.white, alpha=0.6, linewidth=1, zorder=-1)
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ax1.set_ylabel('Chirp counts', color=ps.white)
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ax1.set_xlabel('Competition outcome', color=ps.white)
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colors1 = ps.red
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ps.set_boxplot_color(bplot1, colors1)
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colors1 = ps.orange
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ps.set_boxplot_color(bplot2, colors1)
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ps.set_boxplot_color(bplot1, winner_color)
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ps.set_boxplot_color(bplot2, loser_color)
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ax2.scatter(size_diffs_winner, size_chirps_winner,
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color=ps.red, label=f'winner')
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color=winner_color, label=f'Winner')
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ax2.scatter(size_diffs_loser, size_chirps_loser,
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color=ps.orange, label='loser')
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color=loser_color, label='Loser')
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ax2.text(0.05, 0.95, f'n={len(size_chirps_winner)}', transform=ax2.transAxes, color=ps.white)
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ax2.text(0.05, 0.95, f'n={len(size_chirps_winner)}',
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transform=ax2.transAxes, color=ps.white)
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ax2.set_xlabel('size difference [cm]')
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ax2.set_xlabel('Size difference [cm]')
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# ax2.set_xticks(np.arange(-10, 10.1, 2))
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ax3.scatter(freq_diffs_higher, freq_chirps_winner, color=ps.red)
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ax3.scatter(freq_diffs_lower, freq_chirps_loser, color=ps.orange)
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ax3.scatter(freq_diffs_higher, freq_chirps_winner, color=winner_color)
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ax3.scatter(freq_diffs_lower, freq_chirps_loser, color=loser_color)
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ax3.text(0.1, 0.95, f'n={len(freq_chirps_loser)}', transform=ax3.transAxes, color=ps.white)
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ax3.text(0.1, 0.95, f'n={len(freq_chirps_loser)}',
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transform=ax3.transAxes, color=ps.white)
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ax3.set_xlabel('absolute frequency [Hz]')
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ax3.set_xlabel('EODf [Hz]')
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handles, labels = ax2.get_legend_handles_labels()
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fig.legend(handles, labels, loc='upper center', ncol=2)
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# pearson r
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@ -45,33 +45,46 @@ def main(datapath: str):
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chirps_in_chasings = []
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for onset, offset in zip(chasing_onset, chasing_offset):
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chirps_in_chasing = [c for c in bh.chirps if (c > onset) & (c < offset)]
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chirps_in_chasing = [
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c for c in bh.chirps if (c > onset) & (c < offset)]
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chirps_in_chasings.append(chirps_in_chasing)
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try:
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time_chasing = np.sum(chasing_offset[chasing_offset<3*60*60] - chasing_onset[chasing_onset<3*60*60])
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time_chasing = np.sum(
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chasing_offset[chasing_offset < 3*60*60] - chasing_onset[chasing_onset < 3*60*60])
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except:
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time_chasing = np.sum(chasing_offset[chasing_offset<3*60*60] - chasing_onset[chasing_onset<3*60*60][:-1])
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time_chasing = np.sum(
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chasing_offset[chasing_offset < 3*60*60] - chasing_onset[chasing_onset < 3*60*60][:-1])
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time_chasing_percent = (time_chasing/(3*60*60))*100
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chirps_chasing = np.asarray(flatten(chirps_in_chasings))
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chirps_chasing_new = chirps_chasing[chirps_chasing<3*60*60]
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chirps_percent = (len(chirps_chasing_new)/len(bh.chirps[bh.chirps<3*60*60]))*100
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chirps_chasing_new = chirps_chasing[chirps_chasing < 3*60*60]
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chirps_percent = (len(chirps_chasing_new) /
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len(bh.chirps[bh.chirps < 3*60*60]))*100
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time_precents.append(time_chasing_percent)
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chirps_percents.append(chirps_percent)
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fig, ax = plt.subplots(1, 1, figsize=(14*ps.cm, 10*ps.cm))
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ax.boxplot([time_precents, chirps_percents])
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ax.set_xticklabels(['Time Chasing', 'Chirps in Chasing'])
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fig, ax = plt.subplots(1, 1, figsize=(7*ps.cm, 7*ps.cm))
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scatter_time = 1.20
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scatter_chirps = 1.80
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size = 10
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bplot1 = ax.boxplot([time_precents, chirps_percents],
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showfliers=False, patch_artist=True)
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ps.set_boxplot_color(bplot1, ps.gray)
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ax.set_xticklabels(['Time \nChasing', 'Chirps \nin Chasing'])
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ax.set_ylabel('Percent')
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ax.scatter(np.ones(len(time_precents))*1.25, time_precents, color=ps.white)
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ax.scatter(np.ones(len(chirps_percents))*1.75, chirps_percents, color=ps.white)
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ax.scatter(np.ones(len(time_precents))*scatter_time, time_precents,
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facecolor=ps.white, s=size)
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ax.scatter(np.ones(len(chirps_percents))*scatter_chirps, chirps_percents,
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facecolor=ps.white, s=size)
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for i in range(len(time_precents)):
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ax.plot([1.25, 1.75], [time_precents[i], chirps_percents[i]], color=ps.white)
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ax.text(0.99, 0.99, f'{len(time_precents)} fish', transform=ax.transAxes)
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ax.plot([scatter_time, scatter_chirps], [time_precents[i],
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chirps_percents[i]], alpha=0.6, linewidth=1, color=ps.white)
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ax.text(0.1, 0.9, f'n={len(time_precents)}', transform=ax.transAxes)
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plt.subplots_adjust(left=0.221, bottom=0.186, right=0.97, top=0.967)
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plt.savefig('../poster/figs/chirps_in_chasing.pdf')
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plt.show()
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@ -80,5 +93,3 @@ if __name__ == '__main__':
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# Path to the data
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datapath = '../data/mount_data/'
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main(datapath)
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@ -79,7 +79,6 @@ def main(datapath: str):
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ax[0].set_xticks([])
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ax[0].set_yticks([])
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ps.hide_ax(ax[0])
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ax[0].yaxis.set_label_coords(-0.1, 0.5)
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ax[1].grid(False)
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ax[1].set_frame_on(False)
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@ -99,19 +98,23 @@ def main(datapath: str):
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labelpad = 30
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fsize = 12
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ax[0].set_ylabel('contact', rotation=0,
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ax[0].set_ylabel('Contact', rotation=0,
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labelpad=labelpad, fontsize=fsize)
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ax[1].set_ylabel('chasing', rotation=0,
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ax[0].yaxis.set_label_coords(-0.062, -0.08)
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ax[1].set_ylabel('Chasing', rotation=0,
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labelpad=labelpad, fontsize=fsize)
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ax[2].set_ylabel('chirps', rotation=0,
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ax[1].yaxis.set_label_coords(-0.06, -0.08)
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ax[2].set_ylabel('Chirps', rotation=0,
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labelpad=labelpad, fontsize=fsize)
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ax[2].yaxis.set_label_coords(-0.07, -0.08)
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ax[4].set_ylabel('EODf')
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ax[4].set_xlabel('time [h]')
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ax[4].set_xlabel('Time [h]')
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# ax[0].set_title(foldername.split('/')[-2])
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# 2020-03-31-9_59
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plt.subplots_adjust(left=0.158, right=0.987, top=0.918)
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# plt.savefig('../poster/figs/timeline.pdf')
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plt.subplots_adjust(left=0.158, right=0.987, top=0.918, bottom=0.136)
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plt.savefig('../poster/figs/timeline.pdf')
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plt.show()
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# plot chirps
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poster/main.pdf
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poster/main.pdf
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@ -22,20 +22,20 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
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weakly electric fish impossible. This profoundly limits our current
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understanding of chirps to experiments
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with single - or physically separated - individuals.
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% \begin{tikzfigure}[]
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% \label{griddrawing}
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% \includegraphics[width=0.8\linewidth]{figs/introplot}
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% \end{tikzfigure}
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\begin{tikzfigure}[]
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\label{griddrawing}
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\includegraphics[width=0.6\linewidth]{figs/introplot}
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\end{tikzfigure}
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}
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\myblock[TranspBlock]{Chirp detection}{
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\begin{tikzfigure}[]
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\label{fig:alg1}
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\includegraphics[width=0.9\linewidth]{figs/algorithm1}
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\includegraphics[width=0.6\linewidth]{figs/algorithm1}
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\end{tikzfigure}
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\vspace{2cm}
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\begin{tikzfigure}[]
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\label{fig:alg2}
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\includegraphics[width=1\linewidth]{figs/algorithm}
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\includegraphics[width=0.9\linewidth]{figs/algorithm}
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\end{tikzfigure}
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\vspace{0cm}
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}
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@ -63,8 +63,8 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
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\begin{itemize}
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\setlength\itemsep{0.5em}
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\item Fish who won the competition chirped more often than the fish who lost.
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\item
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\item Fish who lost the competition chirped more often than the fish who lost.
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\item Size has an effect on the Competition outcome, and the chirp count.
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\end{itemize}
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}
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