from matplotlib.patches import Patch
import matplotlib.colors
from scipy.spatial.distance import pdist
from seriate import seriate
from scfc import bridge, anatomical_connectivity, functional_connectivity, plotting
import matplotlib
from matplotlib import rcParams
rcParams.update({'font.size': 12})
rcParams.update({'axes.spines.right': False})
rcParams.update({'axes.spines.top': False})
rcParams['svg.fonttype'] = 'none' # let illustrator handle the font type
data_dir = bridge.getUserConfiguration()['data_dir']
analysis_dir = bridge.getUserConfiguration()['analysis_dir']
plot_colors = plt.get_cmap('tab10')(np.arange(8)/8)
save_dpi = 400
# %% Eg region traces and cross corrs
pull_regions = ['AL_R', 'CAN_R', 'LH_R', 'SPS_R']
include_inds_ito, name_list_ito = bridge.getItoNames()
display_names = [x.replace('_R', '(R)').replace('_L', '(L)').replace('_', '') for x in name_list_ito]
pull_inds = [np.where(np.array(name_list_ito) == x)[0][0] for x in pull_regions]
resp_fp = os.path.join(data_dir, 'ito_responses', 'ito_2018-11-03_5.pkl')
import os
import glob
import nibabel as nib
import numpy as np
import pandas as pd
import time
import sys
from scfc import functional_connectivity, bridge
atlas_id = sys.argv[1] # name of atlas to use: ito or branson
t_total_0 = time.time()
data_dir = bridge.getUserConfiguration()['data_dir']
brain_filepaths = glob.glob(os.path.join(data_dir, 'brain_files', 'func_volreg') + '*')
for brain_fp in brain_filepaths:
t0 = time.time()
suffix = brain_fp.split('func_volreg_')[-1]
if atlas_id == 'ito':
atlas_fp = os.path.join(data_dir, 'ito_68_atlas', 'vfb_68_' + suffix)
elif atlas_id == 'branson':
atlas_fp = os.path.join(data_dir, 'branson_999_atlas', 'vfb_999_' + suffix)
else:
print('Unrecognized atlas ID')
mask_brain = np.asarray(np.squeeze(nib.load(atlas_fp).get_fdata()), 'uint16')
functional_brain = np.asanyarray(nib.load(brain_fp).dataobj).astype('uint16')