res[prefix][thres] = quality_mx
pickle.dump(res, open(os.path.join(save_path, 'thres_res.pckl'), 'w'))
# plotting
for prefix in res.keys():
fig = plt.figure()
fig.suptitle(prefix)
gs = gridspec.GridSpec(len(range(2, 7)), 1)
gs.update(hspace=0.7)
thresholds = sorted(res[prefix].keys())
for n in range(2, 7):
p = fig.add_subplot(gs[n - 2, 0])
channels = np.zeros(len(thresholds))
for i, thres in enumerate(thresholds):
quality_mx = res[prefix][thres]
best = utils.select_n_channels(quality_mx, n)
channels[i] = sum((np.sum(quality_mx[best, :], 0) == n).astype('int'))
p.grid()
p.plot(thresholds, channels.T)
p.set_title('# of animals: %d' % int(n))
p.set_xticklabels([])
p.set_yticks(range(0, np.size(quality_mx, 1), 5))
p.set_xlabel('threshold')
p.set_xticklabels(thresholds)
fig.savefig(os.path.join(save_path, 'groupsize_' + prefix + '.png'))
answer = raw_input('output folder already exists, overwrite results? (y/n): ')
if not answer == 'y':
print 'abort run, output folder contains files'
sys.exit()
print 'results are written to : %s' % save_base_path
total_resp = []
for prefix in config['prefixes']:
filelist = glob.glob(os.path.join(config['data_path'], prefix) + '*.json')
colorlist = {}
# use only the n_best animals --> most stable odors in common
if config['n_best']:
res = pickle.load(open(os.path.join(config['data_path'], config['load_path'], 'thres_res.pckl')))
best = utils.select_n_channels(res[prefix][config['choose_threshold']], config['n_best'])
filelist = [filelist[i] for i in best]
#create lists to collect results
all_sel_modes, all_sel_modes_condensed, all_raw = [], [], []
baselines, all_stimulifilter = [], []
filelist = filelist[0:2]
for file_ind, filename in enumerate(filelist):
print prefix, filename
meas_path = os.path.splitext(filename)[0]
fname = os.path.basename(meas_path)
plot_name_base = os.path.join(plots_folder, fname)
#assign each file a color:
tmp_filelist = []
for filename in filelist:
info = json.load(open(filename))
print "checking file: ", filename
if 'bad_data' in info:
print 'skip this file: bad_data flag found'
continue
else:
tmp_filelist.append(filename)
filelist = tmp_filelist
colorlist, allodors = {}, []
# use only the n_best animals --> most stable odors in common
res = pickle.load(open(os.path.join(data_path, loadfolder, 'thres_res.pckl')))
best = utils.select_n_channels(res[prefix][selection_thres], n_best)
filelist = [filelist[i] for i in best]
for i in range(-1, len(filelist)):
if i == -1:
filelist_fold = filelist
save_name = prefix + '_all'
else:
filelist_fold = [filelist[j] for j in range(len(filelist)) if j != i]
name_list = [os.path.splitext(os.path.basename(f))[0] for f in filelist_fold]
name_list = [f.split('_')[1] for f in name_list]
save_name = prefix + "_" + "_".join(sorted(name_list))
save_name = save_name + "-" + os.path.splitext(os.path.basename(filelist[i]))[0]
print save_name
