sys.path.append('/auto/users/hellerc/code/projects/PTD/') import ptd_utils as pu import pandas as pd sites = [ 'TAR010c', 'BRT026c', 'BRT033b', 'BRT034f', 'BRT036b', 'BRT037b', 'BRT039c', 'bbl102d', 'AMT018a', 'AMT020a', 'AMT022c', 'AMT026a' ] fs = 20 batch = 307 results = pd.DataFrame( index=sites, columns=['DI', 'dprime', 'targets', 'all_DI', 'all_dprime']) for site in sites: rawid = tuple(pu.which_rawids(site)) manager = BAPHYExperiment(batch=batch, siteid=site, rawid=rawid) options = { 'rasterfs': fs, 'batch': batch, 'siteid': site, 'keep_following_incorrect_trial': False, 'keep_early_trials': False } correct_trials = manager.get_behavior_performance(**options) options = { 'rasterfs': fs, 'batch': batch,
import ptd_utils as pu import charlieTools.preprocessing as preproc import charlieTools.discrimination_tools as di import charlieTools.plotting as cplt import charlieTools.simulate_data as sim import matplotlib as mp mp.rcParams.update({'svg.fonttype': 'none'}) fn = '/auto/users/hellerc/code/projects/Cosyne2020_poster/svgs/dec_cv_example.svg' site = 'TAR010c' nPCs = 4 batch = 307 fs = 20 rawid = pu.which_rawids(site) ops = { 'batch': batch, 'pupil': 1, 'rasterfs': fs, 'siteid': site, 'stim': 0, 'rawid': rawid } uri = nb.baphy_load_recording_uri(**ops) rec = Recording.load(uri) rec['resp'] = rec['resp'].rasterize() rec = rec.and_mask(['HIT_TRIAL', 'MISS_TRIAL', 'PASSIVE_EXPERIMENT']) rec = rec.and_mask(['PreStimSilence', 'PostStimSilence'], invert=True) rec = rec.apply_mask(reset_epochs=True)
sites = ['TAR010c', 'BRT026c', 'BRT033b', 'BRT034f', 'BRT036b', 'BRT037b', 'BRT039c', 'bbl102d', 'AMT018a', 'AMT020a', 'AMT022c', 'AMT026a'] batch = 307 cells = [c for c in nd.get_batch_cells(batch).cellid if c[:7] in sites] fs = 1000 save_fn = '/auto/users/hellerc/results/Cosyne2020_poster/single_cell_analyses/strfs/{}_cache.pickle' df = pd.DataFrame(index=cells, columns=['BF', 'SNR', 'STRF', 'StimParms']) dfa = pd.DataFrame(index=cells, columns=['BF', 'SNR', 'STRF', 'StimParms']) dfp = pd.DataFrame(index=cells, columns=['BF', 'SNR', 'STRF', 'StimParms']) dfpb = pd.DataFrame(index=cells, columns=['BF', 'SNR', 'STRF', 'StimParms']) dfps = pd.DataFrame(index=cells, columns=['BF','SNR', 'STRF', 'StimParms']) for s in sites: rawid = pu.which_rawids(s) ops = {'batch': batch, 'pupil': 1, 'rasterfs': fs, 'siteid': s, 'stim': 0, 'rawid': rawid} uri = nb.baphy_load_recording_uri(**ops) rec = Recording.load(uri) rec = preproc.create_ptd_masks(rec) ra = rec.copy() ra['mask'] = ra['a_mask'] ra = ra.apply_mask(reset_epochs=True) rp = rec.copy() rp['mask'] = rp['p_mask'] rp = rp.apply_mask(reset_epochs=True)