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cleaned code

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Till Raab 2023-05-23 11:01:59 +02:00
parent 5af9a25dfd
commit 8c1f85f89e
3 changed files with 268 additions and 141 deletions
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7
complete_analysis.py
View File

@ -181,7 +181,7 @@ def main(data_folder=None):
trial_summary = pd.DataFrame(columns=['recording', 'group', 'win_fish', 'lose_fish', 'sex_win', 'sex_lose',
'size_win', 'size_lose', 'EODf_win', 'EODf_lose', 'exp_win', 'exp_lose',
'chirps_win', 'chirps_lose', 'rises_win', 'rise_lose', 'draw'])
'chirps_win', 'chirps_lose', 'rises_win', 'rises_lose', 'draw'])
trial_summary_row = {f'{s}':None for s in trial_summary.keys()}
for trial_idx in tqdm(np.arange(len(trials_meta)), desc='Trials'):
@ -299,7 +299,7 @@ def main(data_folder=None):
'chirps_win': len(chirp_times[0]),
'chirps_lose': len(chirp_times[1]),
'rises_win': len(rise_idx_int[0]),
'rise_lose': len(rise_idx_int[1]),
'rises_lose': len(rise_idx_int[1]),
'draw': 1 if trials_meta['winner'][trial_idx] == -1 else 0
}
# embed()
@ -393,8 +393,7 @@ def main(data_folder=None):
sex = 'm'
trial_summary['sex_win'][(trial_summary['group'] == g) & (trial_summary['win_fish'] == f)] = sex
trial_summary['sex_lose'][(trial_summary['group'] == g) & (trial_summary['lose_fish'] == f)] = sex
embed()
quit()
trial_summary.to_csv('trial_summary.csv')
pass
if __name__ == '__main__':

10
trial_summary.csv
View File

@ -1,4 +1,4 @@
,recording,group,win_fish,lose_fish,sex_win,sex_lose,size_win,size_lose,EODf_win,EODf_lose,exp_win,exp_lose,chirps_win,chirps_lose,rises_win,rise_lose,draw
,recording,group,win_fish,lose_fish,sex_win,sex_lose,size_win,size_lose,EODf_win,EODf_lose,exp_win,exp_lose,chirps_win,chirps_lose,rises_win,rises_lose,draw
0,2019-11-25-09_59,3,1,2,f,f,13.2,12.0,713.0544113886845,762.0273047058653,1,1,36,2657,22,165,0
1,2019-11-26-10_00,3,4,3,m,m,15.5,17.5,883.141322780704,918.0584506431281,1,1,472,1322,17,481,0
2,2019-11-27-10_00,3,5,6,f,f,14.4,12.65,728.1663791991439,650.6079943890219,1,1,16,2041,14,311,0
@ -13,14 +13,14 @@
11,2019-12-11-10_00,3,4,1,m,f,15.5,13.2,909.5564241038855,704.759181051688,4,5,44,260,48,165,0
12,2019-12-12-10_00,3,2,6,f,f,12.0,12.65,708.2029632781753,649.3215729301896,5,5,55,1489,26,152,0
13,2019-12-16-10_00,3,4,5,m,f,15.5,14.4,911.4475182245616,734.3463774893517,5,5,52,963,39,123,0
14,2020-03-13-10_00,4,5,4,m,f,12.5,12.266666666666666,726.3470010966499,705.1654694195288,2,2,54,941,70,177,0
14,2020-03-13-10_00,4,5,4,f,f,12.5,12.266666666666666,726.3470010966499,705.1654694195288,2,2,54,941,70,177,0
15,2020-03-16-10_00,4,3,1,m,f,11.933333333333332,11.299999999999999,852.2318545355058,642.0347177867645,3,3,1304,724,57,154,0
16,2020-03-18-10_34,4,5,3,m,m,12.5,11.933333333333332,725.8257351336636,863.6524533012707,3,4,16557,2089,339,43,1
16,2020-03-18-10_34,4,5,3,f,m,12.5,11.933333333333332,725.8257351336636,863.6524533012707,3,4,16557,2089,339,43,1
17,2020-03-19-10_00,4,1,4,f,f,11.299999999999999,12.266666666666666,659.5490944255365,697.5034008357667,4,4,52,1583,36,197,0
18,2020-03-20-10_00,4,5,2,m,f,12.5,12.266666666666666,,,4,4,45,665,75,76,0
18,2020-03-20-10_00,4,5,2,f,f,12.5,12.266666666666666,,,4,4,45,665,75,76,0
19,2020-03-23-09_58,4,2,1,f,f,12.266666666666666,11.299999999999999,699.4914052830558,654.7533296886725,5,5,84,1158,17,67,1
20,2020-03-24-10_00,4,4,3,f,m,12.266666666666666,11.933333333333332,684.578069899078,854.0458114588357,5,5,883,2,184,86,1
21,2020-03-25-10_00,4,5,1,m,f,12.5,11.299999999999999,733.5001619575638,647.9874053272127,5,6,819,1831,48,70,1
21,2020-03-25-10_00,4,5,1,f,f,12.5,11.299999999999999,733.5001619575638,647.9874053272127,5,6,819,1831,48,70,1
22,2020-03-31-09_59,4,3,2,m,f,11.933333333333332,12.266666666666666,860.5459022492297,692.2978867242133,6,6,10,225,26,50,1
23,2020-05-11-10_00,5,1,2,m,f,12.333333333333334,13.166666666666666,834.369973908149,667.9762847453638,1,1,4,631,25,230,0
24,2020-05-12-10_00,5,5,3,f,m,19.0,10.666666666666666,697.6088902440882,818.2108387976053,1,1,1,117,8,429,0

1 recording group win_fish lose_fish sex_win sex_lose size_win size_lose EODf_win EODf_lose exp_win exp_lose chirps_win chirps_lose rises_win rise_lose rises_lose draw
2 0 2019-11-25-09_59 3 1 2 f f 13.2 12.0 713.0544113886845 762.0273047058653 1 1 36 2657 22 165 0
3 1 2019-11-26-10_00 3 4 3 m m 15.5 17.5 883.141322780704 918.0584506431281 1 1 472 1322 17 481 0
4 2 2019-11-27-10_00 3 5 6 f f 14.4 12.65 728.1663791991439 650.6079943890219 1 1 16 2041 14 311 0
13 11 2019-12-11-10_00 3 4 1 m f 15.5 13.2 909.5564241038855 704.759181051688 4 5 44 260 48 165 0
14 12 2019-12-12-10_00 3 2 6 f f 12.0 12.65 708.2029632781753 649.3215729301896 5 5 55 1489 26 152 0
15 13 2019-12-16-10_00 3 4 5 m f 15.5 14.4 911.4475182245616 734.3463774893517 5 5 52 963 39 123 0
16 14 2020-03-13-10_00 4 5 4 m f f 12.5 12.266666666666666 726.3470010966499 705.1654694195288 2 2 54 941 70 177 0
17 15 2020-03-16-10_00 4 3 1 m f 11.933333333333332 11.299999999999999 852.2318545355058 642.0347177867645 3 3 1304 724 57 154 0
18 16 2020-03-18-10_34 4 5 3 m f m 12.5 11.933333333333332 725.8257351336636 863.6524533012707 3 4 16557 2089 339 43 1
19 17 2020-03-19-10_00 4 1 4 f f 11.299999999999999 12.266666666666666 659.5490944255365 697.5034008357667 4 4 52 1583 36 197 0
20 18 2020-03-20-10_00 4 5 2 m f f 12.5 12.266666666666666 4 4 45 665 75 76 0
21 19 2020-03-23-09_58 4 2 1 f f 12.266666666666666 11.299999999999999 699.4914052830558 654.7533296886725 5 5 84 1158 17 67 1
22 20 2020-03-24-10_00 4 4 3 f m 12.266666666666666 11.933333333333332 684.578069899078 854.0458114588357 5 5 883 2 184 86 1
23 21 2020-03-25-10_00 4 5 1 m f f 12.5 11.299999999999999 733.5001619575638 647.9874053272127 5 6 819 1831 48 70 1
24 22 2020-03-31-09_59 4 3 2 m f 11.933333333333332 12.266666666666666 860.5459022492297 692.2978867242133 6 6 10 225 26 50 1
25 23 2020-05-11-10_00 5 1 2 m f 12.333333333333334 13.166666666666666 834.369973908149 667.9762847453638 1 1 4 631 25 230 0
26 24 2020-05-12-10_00 5 5 3 f m 19.0 10.666666666666666 697.6088902440882 818.2108387976053 1 1 1 117 8 429 0

390
trial_summary_eval.py
View File

@ -16,7 +16,7 @@ def plot_rise_vs_chirp_count(trial_summary):
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.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)
@ -28,130 +28,134 @@ def plot_rise_vs_chirp_count(trial_summary):
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.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_chirp_rise_count_per_pairing(trial_summary):
win_chirps = []
lose_chirps = []
def plot_chirp_rise_count_per_pairing(trial_summary,
beh_key_win=None, beh_key_lose=None,
ylabel='y'):
win_rises = []
lose_rises = []
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_chirps.append(trial_summary['chirps_win'][(trial_summary["sex_win"] == win_sex) &
(trial_summary["sex_lose"] == lose_sex) &
(trial_summary["draw"] == 0)].to_numpy())
lose_chirps.append(trial_summary['chirps_lose'][(trial_summary["sex_win"] == win_sex) &
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())
win_rises.append(trial_summary['rises_win'][(trial_summary["sex_win"] == win_sex) &
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())
lose_rises.append(trial_summary['rise_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_chirps, positions=np.arange(len(win_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_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_chirps)):
ax.text(i, y1, f'n={len(win_chirps[i]):.0f}', fontsize=10, ha='center', va='bottom')
ax.set_ylim(top = y1*1.1)
ax.set_ylabel('chirps [n]', 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=0.1, right=0.95, top=0.95)
ax = fig.add_subplot(gs[0, 0])
ax.boxplot(win_rises, positions=np.arange(len(win_rises))-0.15, widths= .2, sym='')
ax.boxplot(lose_rises, positions=np.arange(len(lose_rises))+0.15, widths= .2, sym='')
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_rises)))
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_rises)):
ax.text(i, y1, f'n={len(win_rises[i]):.0f}', fontsize=10, ha='center', va='bottom')
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('rises [n]', fontsize=12)
ax.set_ylabel(ylabel, fontsize=12)
plt.tick_params(labelsize=10)
# plt.show()
# win_chirps = []
# lose_chirps = []
#
# win_rises = []
# lose_rises = []
#
# 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) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy())
# lose_chirps.append(trial_summary['chirps_lose'][(trial_summary["sex_win"] == win_sex) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy())
# win_rises.append(trial_summary['rises_win'][(trial_summary["sex_win"] == win_sex) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy())
# lose_rises.append(trial_summary['rises_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_chirps, positions=np.arange(len(win_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_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_chirps)):
# ax.text(i, y1, f'n={len(win_chirps[i]):.0f}', fontsize=10, ha='center', va='bottom')
# ax.set_ylim(top = y1*1.1)
# ax.set_ylabel('chirps [n]', 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=0.1, right=0.95, top=0.95)
# ax = fig.add_subplot(gs[0, 0])
# ax.boxplot(win_rises, positions=np.arange(len(win_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_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_rises)):
# 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_ylabel('rises [n]', fontsize=12)
# plt.tick_params(labelsize=10)
# # plt.show()
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]
def plot_chirp_rise_count_vs_size_diff(trial_summary):
win_chirps = []
lose_chirps = []
win_rises = []
lose_rises = []
win_count = []
lose_count = []
d_size = []
d_EODf = []
win_meta = []
lose_meta = []
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_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_chirps.append(trial_summary['chirps_lose'][(trial_summary["sex_win"] == win_sex) &
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_rises.append(trial_summary['rises_win'][(trial_summary["sex_win"] == win_sex) &
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_rises.append(trial_summary['rise_lose'][(trial_summary["sex_win"] == win_sex) &
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())
w_size = trial_summary['size_win'][(trial_summary["sex_win"] == win_sex) &
(trial_summary["sex_lose"] == lose_sex) &
(trial_summary["draw"] == 0)].to_numpy()
l_size = trial_summary['size_lose'][(trial_summary["sex_win"] == win_sex) &
(trial_summary["sex_lose"] == lose_sex) &
(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_EODf.append(w_EODf-l_EODf)
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])
for i in range(len(lose_rises)):
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('lose rises [n]', fontsize=12)
ax.set_xlabel(u'$\Delta$size [cm]', fontsize=12)
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 = []
@ -160,17 +164,17 @@ def plot_chirp_rise_count_vs_size_diff(trial_summary):
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)
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(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[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('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)
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)
@ -179,49 +183,173 @@ def plot_chirp_rise_count_vs_size_diff(trial_summary):
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)
###############################################################################################################
# win_chirps = []
# lose_chirps = []
#
# win_rises = []
# lose_rises = []
#
# d_size = []
# d_EODf = []
#
# 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) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy())
# lose_chirps.append(trial_summary['chirps_lose'][(trial_summary["sex_win"] == win_sex) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy())
# win_rises.append(trial_summary['rises_win'][(trial_summary["sex_win"] == win_sex) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy())
# lose_rises.append(trial_summary['rises_lose'][(trial_summary["sex_win"] == win_sex) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy())
#
# w_size = trial_summary['size_win'][(trial_summary["sex_win"] == win_sex) &
# (trial_summary["sex_lose"] == lose_sex) &
# (trial_summary["draw"] == 0)].to_numpy()
# l_size = trial_summary['size_lose'][(trial_summary["sex_win"] == win_sex) &
# (trial_summary["sex_lose"] == lose_sex) &
# (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_EODf.append(w_EODf-l_EODf)
#
#
# 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, 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_rises[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2)
# ax[1].plot(d_size[i], lose_rises[i], 'p', color=win_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2)
#
# ax[2].plot(d_size[i], win_rises[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2)
# ax[3].plot(d_size[i], lose_rises[i], 'o', color=lose_colors[i], markeredgecolor=mek[i], markersize=markersize, markeredgewidth=2 )
#
# ax[0].set_ylabel('win rises [n]', fontsize=12)
# ax[1].set_ylabel('lose rises [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)
#
# ##################################################################################################################
# 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():
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]
# 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_vs_size_diff(trial_summary)
plot_chirp_rise_count_per_pairing(trial_summary,
beh_key_win='chirps_win', beh_key_lose='chirps_lose',
ylabel='chirps [n]')
plot_chirp_rise_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]')
plt.show()
embed()
quit()
if __name__ == '__main__':
main()