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continued meta analysis

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Till Raab 2023-05-22 15:15:16 +02:00
parent 42640c17d9
commit 5af9a25dfd
2 changed files with 145 additions and 42 deletions
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54
complete_analysis.py
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@ -168,8 +168,10 @@ def main(data_folder=None):
if not os.path.exists(os.path.join(os.path.split(__file__)[0], 'figures')): if not os.path.exists(os.path.join(os.path.split(__file__)[0], 'figures')):
os.makedirs(os.path.join(os.path.split(__file__)[0], 'figures')) os.makedirs(os.path.join(os.path.split(__file__)[0], 'figures'))
trials_meta = pd.read_csv('order_meta.csv') # trials_meta = pd.read_csv('order_meta.csv')
fish_meta = pd.read_csv('id_meta.csv') trials_meta = pd.read_csv(os.path.join(data_folder, 'order_meta.csv'))
# fish_meta = pd.read_csv('id_meta.csv')
fish_meta = pd.read_csv(os.path.join(data_folder, 'id_meta.csv'))
fish_meta['mean_w'] = np.nanmean(fish_meta.loc[:, ['w1', 'w2', 'w3']], axis=1) fish_meta['mean_w'] = np.nanmean(fish_meta.loc[:, ['w1', 'w2', 'w3']], axis=1)
fish_meta['mean_l'] = np.nanmean(fish_meta.loc[:, ['l1', 'l2', 'l3']], axis=1) fish_meta['mean_l'] = np.nanmean(fish_meta.loc[:, ['l1', 'l2', 'l3']], axis=1)
@ -354,29 +356,29 @@ def main(data_folder=None):
plt.savefig(os.path.join(os.path.join(os.path.split(__file__)[0], 'figures', f'{recording}.png')), dpi=300) plt.savefig(os.path.join(os.path.join(os.path.split(__file__)[0], 'figures', f'{recording}.png')), dpi=300)
plt.close() plt.close()
fig = plt.figure(figsize=(20/2.54, 20/2.54)) # 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]) # 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 = 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_win'], trial_summary['chirps_win'], 'o', color=Wc, label='winner')
ax.plot(trial_summary['rise_lose'], trial_summary['chirps_lose'], 'o', color=Lc, label='loster') # ax.plot(trial_summary['rise_lose'], trial_summary['chirps_lose'], 'o', color=Lc, label='loster')
ax.set_xlabel('rises [n]', fontsize=12) # ax.set_xlabel('rises [n]', fontsize=12)
ax.set_ylabel('chirps [n]', fontsize=12) # ax.set_ylabel('chirps [n]', fontsize=12)
ax.tick_params(labelsize=10) # ax.tick_params(labelsize=10)
#
ax_chirps = fig.add_subplot(gs[1, 1], sharey=ax) # 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.boxplot([trial_summary['chirps_win'], trial_summary['chirps_lose']], widths = .5, positions = [1, 2])
ax_chirps.set_xticks([1, 2]) # ax_chirps.set_xticks([1, 2])
ax_chirps.set_xticklabels(['Win', 'Lose']) # ax_chirps.set_xticklabels(['Win', 'Lose'])
plt.setp(ax_chirps.get_yticklabels(), visible=False) # plt.setp(ax_chirps.get_yticklabels(), visible=False)
#
ax_rises = fig.add_subplot(gs[0, 0], sharex=ax) # ax_rises = fig.add_subplot(gs[0, 0], sharex=ax)
ax_rises.boxplot([trial_summary['rises_win'], trial_summary['rise_lose']], widths = .5, positions = [1, 2], vert=False) # ax_rises.boxplot([trial_summary['rises_win'], trial_summary['rise_lose']], widths = .5, positions = [1, 2], vert=False)
ax_rises.set_yticks([1, 2]) # ax_rises.set_yticks([1, 2])
ax_rises.set_yticklabels(['Win', 'Lose']) # ax_rises.set_yticklabels(['Win', 'Lose'])
plt.setp(ax_rises.get_xticklabels(), visible=False) # plt.setp(ax_rises.get_xticklabels(), visible=False)
#
plt.show() # plt.show()
for g in pd.unique(trial_summary['group']): for g in pd.unique(trial_summary['group']):
@ -385,7 +387,7 @@ def main(data_folder=None):
for f in fish_no: for f in fish_no:
fish_EODf25 = np.concatenate((trial_summary['EODf_lose'][(trial_summary['group'] == g) & (trial_summary['lose_fish'] == f)], fish_EODf25 = np.concatenate((trial_summary['EODf_lose'][(trial_summary['group'] == g) & (trial_summary['lose_fish'] == f)],
trial_summary['EODf_win'][(trial_summary['group'] == g) & (trial_summary['win_fish'] == f)])) trial_summary['EODf_win'][(trial_summary['group'] == g) & (trial_summary['win_fish'] == f)]))
if np.median(fish_EODf25) < 740: if np.nanmedian(fish_EODf25) < 740:
sex = 'f' sex = 'f'
else: else:
sex = 'm' sex = 'm'

133
trial_summary_eval.py
View File

@ -10,6 +10,30 @@ female_color, male_color = '#e74c3c', '#3498db'
Wc, Lc = 'darkgreen', '#3673A4' 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['rise_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['rise_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_chirp_rise_count_per_pairing(trial_summary): def plot_chirp_rise_count_per_pairing(trial_summary):
win_chirps = [] win_chirps = []
lose_chirps = [] lose_chirps = []
@ -39,8 +63,8 @@ def plot_chirp_rise_count_per_pairing(trial_summary):
ax.boxplot(lose_chirps, positions=np.arange(len(lose_chirps))+0.15, widths= .2, sym='') ax.boxplot(lose_chirps, positions=np.arange(len(lose_chirps))+0.15, widths= .2, sym='')
ax.set_xticks(np.arange(len(win_chirps))) ax.set_xticks(np.arange(len(win_chirps)))
# ax.set_xticklabels([u'\u2642\u2642', u'\u2642\u2640', u'\u2640\u2642', u'\u2640\u2640']) ax.set_xticklabels([u'\u2642\u2642', u'\u2642\u2640', u'\u2640\u2642', u'\u2640\u2640'])
ax.set_xticklabels(['mm', 'mf', 'fm', 'ff']) # ax.set_xticklabels(['mm', 'mf', 'fm', 'ff'])
y0, y1 = ax.get_ylim() y0, y1 = ax.get_ylim()
for i in range(len(win_chirps)): for i in range(len(win_chirps)):
ax.text(i, y1, f'n={len(win_chirps[i]):.0f}', fontsize=10, ha='center', va='bottom') ax.text(i, y1, f'n={len(win_chirps[i]):.0f}', fontsize=10, ha='center', va='bottom')
@ -55,17 +79,18 @@ def plot_chirp_rise_count_per_pairing(trial_summary):
ax.boxplot(lose_rises, positions=np.arange(len(lose_rises))+0.15, widths= .2, sym='') ax.boxplot(lose_rises, positions=np.arange(len(lose_rises))+0.15, widths= .2, sym='')
ax.set_xticks(np.arange(len(win_rises))) ax.set_xticks(np.arange(len(win_rises)))
# ax.set_xticklabels([u'\u2642\u2642', u'\u2642\u2640', u'\u2640\u2642', u'\u2640\u2640']) ax.set_xticklabels([u'\u2642\u2642', u'\u2642\u2640', u'\u2640\u2642', u'\u2640\u2640'])
ax.set_xticklabels(['mm', 'mf', 'fm', 'ff']) # ax.set_xticklabels(['mm', 'mf', 'fm', 'ff'])
y0, y1 = ax.get_ylim() y0, y1 = ax.get_ylim()
for i in range(len(win_rises)): for i in range(len(win_rises)):
ax.text(i, y1, f'n={len(win_rises[i]):.0f}', fontsize=10, ha='center', va='bottom') ax.text(i, y1, f'n={len(win_rises[i]):.0f}', fontsize=10, ha='center', va='bottom')
ax.set_ylim(top = y1*1.1) ax.set_ylim(top = y1*1.1)
ax.set_ylabel('rises [n]', fontsize=12) ax.set_ylabel('rises [n]', fontsize=12)
plt.tick_params(labelsize=10) plt.tick_params(labelsize=10)
plt.show() # plt.show()
def plot_chirp_rise_count_per_vs_size_diff(trial_summary):
def plot_chirp_rise_count_vs_size_diff(trial_summary):
win_chirps = [] win_chirps = []
lose_chirps = [] lose_chirps = []
@ -73,6 +98,7 @@ def plot_chirp_rise_count_per_vs_size_diff(trial_summary):
lose_rises = [] lose_rises = []
d_size = [] d_size = []
d_EODf = []
for win_sex, lose_sex in itertools.product(['m', 'f'], repeat=2): for win_sex, lose_sex in itertools.product(['m', 'f'], repeat=2):
win_chirps.append(trial_summary['chirps_win'][(trial_summary["sex_win"] == win_sex) & win_chirps.append(trial_summary['chirps_win'][(trial_summary["sex_win"] == win_sex) &
@ -95,32 +121,107 @@ def plot_chirp_rise_count_per_vs_size_diff(trial_summary):
(trial_summary["sex_lose"] == lose_sex) & (trial_summary["sex_lose"] == lose_sex) &
(trial_summary["draw"] == 0)].to_numpy() (trial_summary["draw"] == 0)].to_numpy()
w_EODf = trial_summary['EODf_win'][(trial_summary["sex_win"] == win_sex) &
(trial_summary["sex_lose"] == lose_sex) &
(trial_summary["draw"] == 0)].to_numpy()
l_EODf = trial_summary['EODf_lose'][(trial_summary["sex_win"] == win_sex) &
(trial_summary["sex_lose"] == lose_sex) &
(trial_summary["draw"] == 0)].to_numpy()
d_size.append(w_size-l_size) d_size.append(w_size-l_size)
embed() d_EODf.append(w_EODf-l_EODf)
quit()
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])
mek = ['k', 'None', 'None', 'k'] 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]
### SIZE
##################################################################################################################
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)
ax = fig.add_subplot(gs[0, 0])
c = [male_color, male_color, female_color, female_color]
for i in range(len(lose_rises)): for i in range(len(lose_rises)):
ax.plot(d_size[i]*-1, lose_rises[i], 'p', color=c[i], markeredgecolor=mek[i], markersize=8) ax.plot(d_size[i], lose_rises[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize)
# ax.plot(d_size[i]*-1, lose_rises[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize)
ax.set_ylabel('rises [n]', fontsize=12) ax.set_ylabel('lose rises [n]', fontsize=12)
ax.set_xlabel(u'$\Delta$size [cm]', fontsize=12)
plt.tick_params(labelsize=10) plt.tick_params(labelsize=10)
##################################################################################################################
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(lose_chirps)):
ax[0].plot(d_size[i], win_chirps[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2)
ax[1].plot(d_size[i], lose_chirps[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2)
ax[2].plot(d_size[i], win_chirps[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2)
ax[3].plot(d_size[i], lose_chirps[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2 )
ax[0].set_ylabel('win chirps [n]', fontsize=12)
ax[1].set_ylabel('lose chirps [n]', fontsize=12)
ax[1].set_xlabel(u'$\Delta$size [cm]', fontsize=12)
ax[3].set_xlabel(u'$\Delta$size [cm]', 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)
### EODf
##################################################################################################################
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)
ax = fig.add_subplot(gs[0, 0])
for i in range(len(lose_rises)):
ax.plot(d_EODf[i], lose_rises[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize)
# ax.plot(d_EODf[i]*-1, lose_rises[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize)
ax.set_ylabel('lose rises [n]', fontsize=12)
ax.set_xlabel(u'$\Delta$EODf [Hz]', fontsize=12)
plt.tick_params(labelsize=10)
##################################################################################################################
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)
ax = fig.add_subplot(gs[0, 0])
for i in range(len(lose_chirps)):
ax.plot(d_EODf[i], lose_chirps[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize)
# ax.plot(d_EODf[i]*-1, lose_chirps[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize)
ax.set_ylabel('lose chirps [n]', fontsize=12)
ax.set_xlabel(u'$\Delta$EODf [Hz]', fontsize=12)
plt.tick_params(labelsize=10)
def main(): def main():
trial_summary = pd.read_csv('trial_summary.csv', index_col=0) 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_chirp_rise_count_per_pairing(trial_summary) plot_chirp_rise_count_per_pairing(trial_summary)
plot_chirp_rise_count_per_vs_size_diff(trial_summary) plot_chirp_rise_count_vs_size_diff(trial_summary)
pass plt.show()
embed()
quit()
if __name__ == '__main__': if __name__ == '__main__':
main() main()