import numpy as np import itertools import pandas as pd import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec from IPython import embed colors = ['#BA2D22', '#53379B', '#F47F17', '#3673A4', '#AAB71B', '#DC143C', '#1E90FF'] female_color, male_color = '#e74c3c', '#3498db' Wc, Lc = 'darkgreen', '#3673A4' def plot_rise_vs_chirp_count(trial_summary): fig = plt.figure(figsize=(20/2.54, 20/2.54)) gs = gridspec.GridSpec(2, 2, left=0.1, bottom=0.1, right=0.95, top=0.95, height_ratios=[1, 3], width_ratios=[3, 1]) ax = fig.add_subplot(gs[1, 0]) ax.plot(trial_summary['rises_win'], trial_summary['chirps_win'], 'o', color=Wc, label='winner') ax.plot(trial_summary['rises_lose'], trial_summary['chirps_lose'], 'o', color=Lc, label='loster') ax.set_xlabel('rises [n]', fontsize=12) ax.set_ylabel('chirps [n]', fontsize=12) ax.tick_params(labelsize=10) ax_chirps = fig.add_subplot(gs[1, 1], sharey=ax) ax_chirps.boxplot([trial_summary['chirps_win'], trial_summary['chirps_lose']], widths = .5, positions = [1, 2]) ax_chirps.set_xticks([1, 2]) ax_chirps.set_xticklabels(['Win', 'Lose']) plt.setp(ax_chirps.get_yticklabels(), visible=False) ax_rises = fig.add_subplot(gs[0, 0], sharex=ax) ax_rises.boxplot([trial_summary['rises_win'], trial_summary['rises_lose']], widths = .5, positions = [1, 2], vert=False) ax_rises.set_yticks([1, 2]) ax_rises.set_yticklabels(['Win', 'Lose']) plt.setp(ax_rises.get_xticklabels(), visible=False) def plot_beh_count_per_pairing(trial_summary, beh_key_win=None, beh_key_lose=None, ylabel='y'): mek = ['k', 'None', 'None', 'k'] markersize = 12 win_colors = [male_color, male_color, female_color, female_color] lose_colors = [male_color, female_color, male_color, female_color] win_count = [] lose_count = [] for win_sex, lose_sex in itertools.product(['m', 'f'], repeat=2): win_count.append(trial_summary[beh_key_win][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy()) lose_count.append(trial_summary[beh_key_lose][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy()) fig = plt.figure(figsize=(20/2.54, 12/2.54)) gs = gridspec.GridSpec(1, 1, left=0.1, bottom=0.1, right=0.95, top=0.95) ax = fig.add_subplot(gs[0, 0]) ax.boxplot(win_count, positions=np.arange(len(win_count))-0.15, widths= .2, sym='') ax.boxplot(lose_count, positions=np.arange(len(lose_count))+0.15, widths= .2, sym='') ax.set_xticks(np.arange(len(win_count))) ax.set_xticklabels([u'\u2642\u2642', u'\u2642\u2640', u'\u2640\u2642', u'\u2640\u2640']) # ax.set_xticklabels(['mm', 'mf', 'fm', 'ff']) y0, y1 = ax.get_ylim() for i in range(len(win_count)): ax.text(i, y1, f'n={len(win_count[i]):.0f}', fontsize=10, ha='center', va='bottom') ax.set_ylim(top = y1*1.1) ax.set_ylabel(ylabel, fontsize=12) plt.tick_params(labelsize=10) def plot_beh_count_vs_meta(trial_summary, beh_key_win=None, beh_key_lose=None, meta_key_win=None, meta_key_lose=None, xlabel='x'): mek = ['k', 'None', 'None', 'k'] markersize = 12 win_colors = [male_color, male_color, female_color, female_color] lose_colors = [male_color, female_color, male_color, female_color] win_count = [] lose_count = [] win_meta = [] lose_meta = [] for win_sex, lose_sex in itertools.product(['m', 'f'], repeat=2): win_count.append(trial_summary[beh_key_win][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy()) lose_count.append(trial_summary[beh_key_lose][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy()) win_meta.append(trial_summary[meta_key_win][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy()) lose_meta.append(trial_summary[meta_key_lose][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy()) fig = plt.figure(figsize=(20/2.54, 20/2.54)) gs = gridspec.GridSpec(2, 2, left=0.1, bottom=0.1, right=0.95, top=0.95, hspace=0.1, wspace=0.1) ax = [] ax.append(fig.add_subplot(gs[0, 0])) ax.append(fig.add_subplot(gs[1, 0], sharex=ax[0])) ax.append(fig.add_subplot(gs[0, 1], sharey=ax[0])) ax.append(fig.add_subplot(gs[1, 1], sharex=ax[2], sharey=ax[1])) for i in range(len(win_count)): ax[0].plot(win_meta[i]-lose_meta[i], win_count[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2) ax[1].plot(win_meta[i]-lose_meta[i], lose_count[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2) ax[2].plot((win_meta[i]-lose_meta[i])*-1, win_count[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2) ax[3].plot((win_meta[i]-lose_meta[i])*-1, lose_count[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2 ) ax[0].set_ylabel(f'{beh_key_win} [n]', fontsize=12) ax[1].set_ylabel(f'{beh_key_lose} [n]', fontsize=12) ax[1].set_xlabel(f'{xlabel}', fontsize=12) ax[3].set_xlabel(f'{xlabel}', fontsize=12) plt.setp(ax[0].get_xticklabels(), visible=False) plt.setp(ax[2].get_xticklabels(), visible=False) plt.setp(ax[2].get_yticklabels(), visible=False) plt.setp(ax[3].get_yticklabels(), visible=False) plt.tick_params(labelsize=10) def plot_beh_conut_vs_experience(trial_summary, beh_key_win='chirps_win', beh_key_lose='chirps_lose', ylabel='chirps [n]'): mek = ['k', 'None', 'None', 'k'] markersize = 10 win_colors = [male_color, male_color, female_color, female_color] lose_colors = [male_color, female_color, male_color, female_color] lose_beh_per_exp = [] win_beh_per_exp = [] for i in np.unique(trial_summary['exp_lose']): lose_beh_per_exp.append(trial_summary[beh_key_lose][(trial_summary['exp_lose'] == i) & (trial_summary["draw"] == 0)].to_numpy()) win_beh_per_exp.append(trial_summary[beh_key_win][(trial_summary['exp_lose'] == i) & (trial_summary["draw"] == 0)].to_numpy()) fig = plt.figure(figsize=(20 / 2.54, 12 / 2.54)) gs = gridspec.GridSpec(1, 1, left=0.1, bottom=0.15, right=0.95, top=0.95, hspace=0.1, wspace=0.1) ax = fig.add_subplot(gs[0, 0]) ax.boxplot(lose_beh_per_exp, positions = np.unique(trial_summary['exp_lose'])-0.15, widths=0.2) ax.boxplot(win_beh_per_exp, positions = np.unique(trial_summary['exp_lose'])+0.15, widths=0.2) for enu, (win_sex, lose_sex) in enumerate(itertools.product(['m', 'f'], repeat=2)): lose_beh_count = trial_summary[beh_key_lose][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy() win_beh_count = trial_summary[beh_key_win][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy() lose_exp = trial_summary['exp_lose'][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy() win_exp = trial_summary['exp_win'][(trial_summary["sex_win"] == win_sex) & (trial_summary["sex_lose"] == lose_sex) & (trial_summary["draw"] == 0)].to_numpy() ax.plot(lose_exp-0.15, lose_beh_count, 'o', color=lose_colors[enu], markeredgecolor=mek[enu], markersize=markersize, markeredgewidth=2) ax.plot(win_exp+0.15, win_beh_count, 'p', color=win_colors[enu], markeredgecolor=mek[enu], markersize=markersize, markeredgewidth=2) ax.set_xticks(np.unique(trial_summary['exp_lose'])) ax.set_xticklabels(np.unique(trial_summary['exp_lose'])) ax.set_xlabel('experience [trials]', fontsize=12) ax.set_ylabel(ylabel, fontsize=12) ax.tick_params(labelsize=10) def main(): trial_summary = pd.read_csv('trial_summary.csv', index_col=0) chirp_notes = pd.read_csv('chirp_notes.csv', index_col=0) trial_summary = trial_summary[chirp_notes['good'] == 1] plot_rise_vs_chirp_count(trial_summary) plot_beh_count_per_pairing(trial_summary, beh_key_win='chirps_win', beh_key_lose='chirps_lose', ylabel='chirps [n]') plot_beh_count_per_pairing(trial_summary, beh_key_win='rises_win', beh_key_lose='rises_lose', ylabel='rises [n]') plot_beh_count_vs_meta(trial_summary, beh_key_win='chirps_win', beh_key_lose='chirps_lose', meta_key_win="size_win", meta_key_lose='size_lose', xlabel=u'$\Delta$size [cm]') plot_beh_count_vs_meta(trial_summary, beh_key_win='rises_win', beh_key_lose='rises_lose', meta_key_win="size_win", meta_key_lose='size_lose', xlabel=u'$\Delta$size [cm]') plot_beh_count_vs_meta(trial_summary, beh_key_win='chirps_win', beh_key_lose='chirps_lose', meta_key_win="EODf_win", meta_key_lose='EODf_lose', xlabel=u'$\Delta$EODf [Hz]') plot_beh_count_vs_meta(trial_summary, beh_key_win='rises_win', beh_key_lose='rises_lose', meta_key_win="EODf_win", meta_key_lose='EODf_lose', xlabel=u'$\Delta$EODf [Hz]') plot_beh_conut_vs_experience(trial_summary, beh_key_win='chirps_win', beh_key_lose='chirps_lose', ylabel='chirps [n]') plot_beh_conut_vs_experience(trial_summary, beh_key_win='rises_win', beh_key_lose='rises_lose', ylabel='rises [n]') plt.show() if __name__ == '__main__': main()