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)