From af088f5726e8fa28a2f84017152edf37543c0f07 Mon Sep 17 00:00:00 2001 From: wendtalexander Date: Wed, 25 Jan 2023 10:16:28 +0100 Subject: [PATCH] trying different stuff --- code/plot_chirp_bodylegth.py | 152 +++++++++++++++++------------------ 1 file changed, 76 insertions(+), 76 deletions(-) diff --git a/code/plot_chirp_bodylegth.py b/code/plot_chirp_bodylegth.py index 3c34953..4c1b771 100644 --- a/code/plot_chirp_bodylegth.py +++ b/code/plot_chirp_bodylegth.py @@ -105,7 +105,7 @@ def get_chirp_freq(folder_name, Behavior, order_meta_df): freq_diff = chirp_freq_fish2 - chirp_freq_fish1 winner_fish_id = folder_row['rec_id2'].values[0] loser_fish_id = folder_row['rec_id1'].values[0] - + chirp_diff = len(Behavior.chirps[Behavior.chirps_ids == winner_fish_id]) - len( Behavior.chirps[Behavior.chirps_ids == loser_fish_id]) @@ -144,80 +144,80 @@ def main(datapath: str): # Get rid of tracking faults (two onsets or two offsets after another) category, timestamps = correct_chasing_events(category, timestamps) - winner_chirp, loser_chirp = get_chirp_winner_loser( - foldername, bh, order_meta_df) - chirps_winner.append(winner_chirp) - chirps_loser.append(loser_chirp) - size_diff, chirp_diff = get_chirp_size( - foldername, bh, order_meta_df, id_meta_df) - size_diffs.append(size_diff) - size_chirps_diffs.append(chirp_diff) - - freq_diff, freq_chirps_diff = get_chirp_freq( - foldername, bh, order_meta_df) - freq_diffs.append(freq_diff) - freq_chirps_diffs.append(freq_chirps_diff) - - # folder_name = foldername.split('/')[-2] - # winner_row = order_meta_df[order_meta_df['recording'] == folder_name] - # winner = winner_row['winner'].values[0].astype(int) - # winner_fish1 = winner_row['fish1'].values[0].astype(int) - # winner_fish2 = winner_row['fish2'].values[0].astype(int) - - # groub = winner_row['group'].values[0].astype(int) - # size_rows = id_meta_df[id_meta_df['group'] == groub] - - # if winner == winner_fish1: - # winner_fish_id = winner_row['rec_id1'].values[0] - # loser_fish_id = winner_row['rec_id2'].values[0] - - # size_winners = [] - # for l in ['l1', 'l2', 'l3']: - # size_winner = size_rows[size_rows['fish']== winner_fish1][l].values[0] - # size_winners.append(size_winner) - # mean_size_winner = np.nanmean(size_winners) - - # size_losers = [] - # for l in ['l1', 'l2', 'l3']: - # size_loser = size_rows[size_rows['fish']== winner_fish2][l].values[0] - # size_losers.append(size_loser) - # mean_size_loser = np.nanmean(size_losers) - - # size_diffs.append(mean_size_winner - mean_size_loser) - - # elif winner == winner_fish2: - # winner_fish_id = winner_row['rec_id2'].values[0] - # loser_fish_id = winner_row['rec_id1'].values[0] - - # size_winners = [] - # for l in ['l1', 'l2', 'l3']: - # size_winner = size_rows[size_rows['fish']== winner_fish2][l].values[0] - # size_winners.append(size_winner) - # mean_size_winner = np.nanmean(size_winners) - - # size_losers = [] - # for l in ['l1', 'l2', 'l3']: - # size_loser = size_rows[size_rows['fish']== winner_fish1][l].values[0] - # size_losers.append(size_loser) - # mean_size_loser = np.nanmean(size_losers) - - # size_diffs.append(mean_size_winner - mean_size_loser) - # else: - # pass - - # print(foldername) - # all_fish_ids = np.unique(bh.chirps_ids) - # chirp_winner = len(bh.chirps[bh.chirps_ids == winner_fish_id]) - # chirp_loser = len(bh.chirps[bh.chirps_ids == loser_fish_id]) - - # freq_winner = np.nanmedian(bh.freq[bh.ident==winner_fish_id]) - # freq_loser = np.nanmedian(bh.freq[bh.ident==loser_fish_id]) - - # chirps_winner.append(chirp_winner) - # chirps_loser.append(chirp_loser) - - # chirps_diffs.append(chirp_winner - chirp_loser) - # freq_diffs.append(freq_winner - freq_loser) + # winner_chirp, loser_chirp = get_chirp_winner_loser( + # foldername, bh, order_meta_df) + # chirps_winner.append(winner_chirp) + # chirps_loser.append(loser_chirp) + # size_diff, chirp_diff = get_chirp_size( + # foldername, bh, order_meta_df, id_meta_df) + # size_diffs.append(size_diff) + # size_chirps_diffs.append(chirp_diff) + + # freq_diff, freq_chirps_diff = get_chirp_freq( + # foldername, bh, order_meta_df) + # freq_diffs.append(freq_diff) + # freq_chirps_diffs.append(freq_chirps_diff) + + folder_name = foldername.split('/')[-2] + winner_row = order_meta_df[order_meta_df['recording'] == folder_name] + winner = winner_row['winner'].values[0].astype(int) + winner_fish1 = winner_row['fish1'].values[0].astype(int) + winner_fish2 = winner_row['fish2'].values[0].astype(int) + + groub = winner_row['group'].values[0].astype(int) + size_rows = id_meta_df[id_meta_df['group'] == groub] + + if winner == winner_fish1: + winner_fish_id = winner_row['rec_id1'].values[0] + loser_fish_id = winner_row['rec_id2'].values[0] + + size_winners = [] + for l in ['l1', 'l2', 'l3']: + size_winner = size_rows[size_rows['fish']== winner_fish1][l].values[0] + size_winners.append(size_winner) + mean_size_winner = np.nanmean(size_winners) + + size_losers = [] + for l in ['l1', 'l2', 'l3']: + size_loser = size_rows[size_rows['fish']== winner_fish2][l].values[0] + size_losers.append(size_loser) + mean_size_loser = np.nanmean(size_losers) + + size_diffs.append(mean_size_winner - mean_size_loser) + + elif winner == winner_fish2: + winner_fish_id = winner_row['rec_id2'].values[0] + loser_fish_id = winner_row['rec_id1'].values[0] + + size_winners = [] + for l in ['l1', 'l2', 'l3']: + size_winner = size_rows[size_rows['fish']== winner_fish2][l].values[0] + size_winners.append(size_winner) + mean_size_winner = np.nanmean(size_winners) + + size_losers = [] + for l in ['l1', 'l2', 'l3']: + size_loser = size_rows[size_rows['fish']== winner_fish1][l].values[0] + size_losers.append(size_loser) + mean_size_loser = np.nanmean(size_losers) + + size_diffs.append(mean_size_winner - mean_size_loser) + else: + continue + + print(foldername) + all_fish_ids = np.unique(bh.chirps_ids) + chirp_winner = len(bh.chirps[bh.chirps_ids == winner_fish_id]) + chirp_loser = len(bh.chirps[bh.chirps_ids == loser_fish_id]) + + freq_winner = np.nanmedian(bh.freq[bh.ident==winner_fish_id]) + freq_loser = np.nanmedian(bh.freq[bh.ident==loser_fish_id]) + + chirps_winner.append(chirp_winner) + chirps_loser.append(chirp_loser) + + size_chirps_diffs.append(chirp_winner - chirp_loser) + freq_diffs.append(freq_winner - freq_loser) fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10, 5)) scatterwinner = 1.15 @@ -246,7 +246,7 @@ def main(datapath: str): colors1 = ps.orange ps.set_boxplot_color(bplot2, colors1) ax1.set_ylabel('Chirpscounts [n]') - + embed() ax2.scatter(size_diffs, size_chirps_diffs, color='r') ax2.set_xlabel('Size difference [mm]') ax2.set_ylabel('Chirps difference [n]')