def add_cb_to_electrode_probs():
fol = '/homes/5/npeled/space1/mmvt/mg117/figures'
fu.combine_brain_with_color_bar(op.join(fol, 'cortical.png'),
cb_max=1,
cb_min=0,
cb_cm='YlOrRd',
ticks=(0, 1))
def post_script(args):
from src.utils import figures_utils as fu
from src.utils import utils
from src.mmvt_addon import clusters_utils as cu
subject_fol = op.join(su.get_mmvt_dir(), args.subject)
figures_fol = op.join(subject_fol, 'figures')
clusters_file_names, _, _ = cu.get_clusters_files('fmri', subject_fol)
clusters_names = [
f for f in clusters_file_names if args.clusters_type in f
]
print('clusters_names: {}'.format(clusters_names))
fmri_files_minmax_fname = op.join(subject_fol, 'fmri',
'fmri_files_minmax_cm.pkl')
data_min, data_max, colors_map_name = utils.load(fmri_files_minmax_fname)
for clusters_name, inflated, background_color in product(
clusters_names, args.inflated, args.background_color):
print('Combing figures for {}, inflated: {}, background color: {}'.
format(clusters_name, inflated, background_color))
perspectives_image_fname = fu.combine_four_brain_perspectives(
figures_fol, inflated, args.dpi, background_color, clusters_name,
args.inflated_ratio, True, args.overwrite)
fu.combine_brain_with_color_bar(
data_max, data_min, perspectives_image_fname, colors_map_name,
args.overwrite, args.dpi, args.x_left_crop, args.x_right_crop,
args.y_top_crop, args.y_buttom_crop, args.w_fac, args.h_fac,
background_color)
def example1():
figures_fol = '/cluster/neuromind/npeled/mmvt/fsaverage5c/figures/final2'
colors_map = 'YlOrRd'
data_max, data_min = 0.2, 0.3
for fig_name in glob.glob(op.join(figures_fol, '*.png')):
fu.combine_brain_with_color_bar(
data_max, data_min, fig_name, colors_map, dpi=100,
x_left_crop=350, x_right_crop=200)
def example5():
figures_fol = '/home/npeled/mmvt/nmr00698/figures/'
colors_map = 'BuPu_YlOrRd'
data_max, data_min = 1, -1
for fig_name in glob.glob(op.join(figures_fol, '*.png')):
fu.combine_brain_with_color_bar(data_max,
data_min,
fig_name,
colors_map,
dpi=100)
def example4(subject='colin27', map_name='s32_spmT', figure_name='splitted_lateral_medial_pial_white.png'):
data_min, data_max = utils.load(
op.join(MMVT_DIR, subject, 'fmri', 'fmri_activity_map_minmax_{}.pkl'.format(map_name)))
data_min = utils.ceil_floor(data_min)
data_max = utils.ceil_floor(data_max)
figure_fname = op.join(MMVT_DIR, subject, 'figures', figure_name)
colors_map = 'BuPu_YlOrRd'
background = 'white' if 'white' in figure_name else 'black'
fu.combine_brain_with_color_bar(
data_max, data_min, figure_fname, colors_map,
x_left_crop=300, x_right_crop=300, y_top_crop=0, y_buttom_crop=0,
w_fac=1.5, h_fac=1, facecolor=background)
def example1():
figures_fol = '/cluster/neuromind/npeled/mmvt/fsaverage5c/figures/final2'
colors_map = 'YlOrRd'
data_max, data_min = 0.2, 0.3
for fig_name in glob.glob(op.join(figures_fol, '*.png')):
fu.combine_brain_with_color_bar(data_max,
data_min,
fig_name,
colors_map,
dpi=100,
x_left_crop=350,
x_right_crop=200)
def example7():
images_names = glob.glob('/home/npeled/mmvt/nmr01216/figures/back/*.png')
for fig_name in images_names:
fu.combine_brain_with_color_bar(data_max,
data_min,
fig_name,
args.cb_cm,
dpi=100,
overwrite=True,
ticks=ticks,
w_fac=1.2,
h_fac=1.2,
ddh=0.7,
dy=0.13)
def example6():
figures_fol = '/home/npeled/mmvt/nmr01216/figures'
colors_map = 'RdOrYl'
data_max, data_min = 2, 6
background = '#393939'
files = glob.glob(op.join(figures_fol, '*.png'))
images_hemi_inv_list = set([
utils.namebase(fname)[3:] for fname in files
if utils.namebase(fname)[:2] in ['rh', 'lh']
])
files = [[
fname for fname in files if utils.namebase(fname)[3:] == img_hemi_inv
] for img_hemi_inv in images_hemi_inv_list]
for files_coup in files:
hemi = 'rh' if utils.namebase(files_coup[0]).startswith('rh') else 'lh'
coup_template = files_coup[0].replace(hemi, '{hemi}')
coup = {}
for hemi in utils.HEMIS:
coup[hemi] = coup_template.format(hemi=hemi)
new_image_fname = op.join(utils.get_fname_folder(files_coup[0]),
utils.namebase_with_ext(files_coup[0])[3:])
fu.crop_image(coup['lh'], coup['lh'], dx=150, dy=0, dw=150, dh=0)
fu.crop_image(coup['rh'], coup['rh'], dx=150, dy=0, dw=0, dh=0)
fu.combine_two_images(coup['lh'],
coup['rh'],
new_image_fname,
facecolor=background)
fu.combine_brain_with_color_bar(data_max,
data_min,
new_image_fname,
colors_map,
dpi=200,
overwrite=True,
w_fac=1.2,
h_fac=1.2,
ddh=0.7,
dy=0.13,
ddw=0.4,
dx=-0.08)
for hemi in utils.HEMIS:
utils.remove_file(coup[hemi])
def example4(subject='colin27',
map_name='s32_spmT',
figure_name='splitted_lateral_medial_pial_white.png'):
data_min, data_max = utils.load(
op.join(MMVT_DIR, subject, 'fmri',
'fmri_activity_map_minmax_{}.pkl'.format(map_name)))
data_min = utils.ceil_floor(data_min)
data_max = utils.ceil_floor(data_max)
figure_fname = op.join(MMVT_DIR, subject, 'figures', figure_name)
colors_map = 'BuPu_YlOrRd'
background = 'white' if 'white' in figure_name else 'black'
fu.combine_brain_with_color_bar(data_max,
data_min,
figure_fname,
colors_map,
x_left_crop=300,
x_right_crop=300,
y_top_crop=0,
y_buttom_crop=0,
w_fac=1.5,
h_fac=1,
facecolor=background)
def post_script(args):
from src.utils import figures_utils as fu
from src.mmvt_addon import fMRI_panel as fmri
from src.utils import utils
subject_fol = op.join(su.get_mmvt_dir(), args.subject)
figures_fol = op.join(subject_fol, 'figures')
clusters_file_names, _ = fmri.get_clusters_files(subject_fol)
clusters_names = [f for f in clusters_file_names if args.clusters_type in f]
print('clusters_names: {}'.format(clusters_names))
fmri_files_minmax_fname = op.join(subject_fol, 'fmri', 'fmri_files_minmax_cm.pkl')
data_min, data_max, colors_map_name = utils.load(fmri_files_minmax_fname)
for clusters_name, inflated, background_color in product(clusters_names, args.inflated, args.background_color):
print('Combing figures for {}, inflated: {}, background color: {}'.format(
clusters_name, inflated, background_color))
perspectives_image_fname = fu.combine_four_brain_perspectives(
figures_fol, inflated, args.dpi, background_color,
clusters_name, args.inflated_ratio, True, args.overwrite)
fu.combine_brain_with_color_bar(
data_max, data_min, perspectives_image_fname, colors_map_name, args.overwrite, args.dpi,
args.x_left_crop, args.x_right_crop, args.y_top_crop, args.y_buttom_crop,
args.w_fac, args.h_fac, background_color)
def post_blender_call(args):
if not args.add_cb and not args.join_hemis:
return
from src.utils import figures_utils as fu
from src.utils import utils
from PIL import Image
if args.call_mmvt_calls:
su.waits_for_file(args.log_fname)
with open(args.images_log_fname, 'r') as text_file:
images_names = text_file.readlines()
images_names = [l.strip() for l in images_names]
data_max, data_min = list(map(float, args.cb_vals))
ticks = list(map(float,
args.cb_ticks)) if args.cb_ticks is not None else None
background = args.background_color # '#393939'
if args.join_hemis:
images_hemi_inv_list = set([
utils.namebase(fname)[3:] for fname in images_names
if utils.namebase(fname)[:2] in ['rh', 'lh']
])
files = [[
fname for fname in images_names
if utils.namebase(fname)[3:] == img_hemi_inv
] for img_hemi_inv in images_hemi_inv_list]
fol = utils.get_fname_folder(files[0][0])
cb_fname = op.join(fol, '{}_colorbar.jpg'.format(args.cb_cm))
# if not op.isfile(cb_fname):
fu.plot_color_bar(data_max,
data_min,
args.cb_cm,
do_save=True,
ticks=ticks,
fol=fol,
background_color=background,
cb_ticks_font_size=args.cb_ticks_font_size)
cb_img = Image.open(cb_fname)
for files_coup in files:
hemi = 'rh' if utils.namebase(
files_coup[0]).startswith('rh') else 'lh'
coup_template = files_coup[0].replace(hemi, '{hemi}')
coup = {
hemi: coup_template.format(hemi=hemi)
for hemi in utils.HEMIS
}
new_image_fname = op.join(
fol,
utils.namebase_with_ext(files_coup[0])[3:])
if args.add_cb:
if args.crop_figures:
fu.crop_image(coup['lh'],
coup['lh'],
dx=150,
dy=0,
dw=50,
dh=70)
fu.crop_image(coup['rh'],
coup['rh'],
dx=150 + 50,
dy=0,
dw=0,
dh=70)
fu.combine_two_images(coup['lh'],
coup['rh'],
new_image_fname,
facecolor=background,
dpi=200,
w_fac=1,
h_fac=1)
fu.combine_brain_with_color_bar(new_image_fname,
cb_img,
overwrite=True)
else:
if args.crop_figures:
fu.crop_image(coup['lh'],
coup['lh'],
dx=150,
dy=0,
dw=150,
dh=0)
fu.crop_image(coup['rh'],
coup['rh'],
dx=150,
dy=0,
dw=150,
dh=0)
fu.combine_two_images(coup['lh'],
coup['rh'],
new_image_fname,
facecolor=background)
if args.remove_temp_figures:
for hemi in utils.HEMIS:
utils.remove_file(coup[hemi])
elif args.add_cb and not args.join_hemis:
fol = utils.get_fname_folder(images_names[0])
cb_fname = op.join(fol, '{}_colorbar.jpg'.format(args.cb_cm))
if not op.isfile(cb_fname):
fu.plot_color_bar(data_max,
data_min,
args.cb_cm,
do_save=True,
ticks=ticks,
fol=fol,
background_color=background)
cb_img = Image.open(cb_fname)
for fig_name in images_names:
fu.combine_brain_with_color_bar(fig_name, cb_img, overwrite=True)
