def test_animate(tmpdir): """Test animation.""" _set_backend('auto') brain = Brain(*std_args, size=100) brain.add_morphometry('curv') tmp_name = str(tmpdir.join('test.avi')) brain.animate(["m"] * 3, n_steps=2) brain.animate(['l', 'l'], n_steps=2, fname=tmp_name) # can't rotate in axial plane pytest.raises(ValueError, brain.animate, ['l', 'd']) brain.close()
def test_animate(): """Test animation.""" _set_backend('auto') brain = Brain(*std_args, size=100) brain.add_morphometry('curv') tmp_name = mktemp() + '.avi' brain.animate(["m"] * 3, n_steps=2) brain.animate(['l', 'l'], n_steps=2, fname=tmp_name) # can't rotate in axial plane assert_raises(ValueError, brain.animate, ['l', 'd']) brain.close()
def test_animate(): """Test animation """ mlab.options.backend = 'auto' brain = Brain(*std_args, config_opts=small_brain) brain.add_morphometry('curv') tmp_name = mktemp() + '.avi' brain.animate(["m"] * 3, n_steps=2) brain.animate(['l', 'l'], n_steps=2, fname=tmp_name) # can't rotate in axial plane assert_raises(ValueError, brain.animate, ['l', 'd']) brain.close()
def visMorph(pathToSurface, overlay, outputPath, hemi): ''' Display anything morphometric ''' # check the overlay if (not overlay == 'sulc' and not overlay == 'thickness' and not overlay == 'curv'): message = ('You specified %s as overlay, this doesn\'t make sense' % (overlay)) raise Exception(message) brain = Brain(pathToSurface, hemi, 'white') brain.add_morphometry(overlay) brain.save_montage(outputPath, ['l', 'm'], orientation='v') brain.close()
def test_morphometry(): """Test plotting of morphometry.""" mlab.options.backend = 'test' brain = Brain(*std_args) brain.add_morphometry("curv") brain.add_morphometry("sulc", grayscale=True) brain.add_morphometry("thickness") brain.close()
def test_morphometry(): """Test plotting of morphometry.""" _set_backend() brain = Brain(*std_args) brain.add_morphometry("curv") brain.add_morphometry("sulc", grayscale=True) brain.add_morphometry("thickness") brain.close()
def plot_brains(axes, palette): lat_ax, med_ax = axes lat_color, med_color = palette b = Brain("fsaverage", "lh", "pial", background="white", size=(1200, 1200)) b.add_morphometry("curv", grayscale=True, min=-.5, max=.5, colormap="Greys", colorbar=False) b.add_label("roi_labels/lh.ifs.label", alpha=.9, color="#feb308") b.add_label("roi_labels/lh.mfc.label", alpha=.9, color="#cf6275") mlab.view(160, 70) lat_ax.imshow(crop(b.screenshot()), rasterized=True) mlab.view(15, 90) med_ax.imshow(crop(b.screenshot()), rasterized=True) b.close() for ax in axes: ax.set_axis_off()
from surfer._commandline import parser args = parser.parse_args(sys.argv[1].split()) # Get a dict of config override options confkeys = ["size", "background", "cortex"] argdict = args.__dict__ config_opts = dict([(k, v) for k, v in argdict.items() if k in confkeys and v]) # Load up the figure and underlying brain object b = Brain(args.subject_id, args.hemi, args.surf, args.curv, args.title, config_opts=config_opts) # Maybe load some morphometry if args.morphometry is not None: b.add_morphometry(args.morphometry) # Maybe load an overlay if args.overlay is not None: if args.range is not None: args.min, args.max = args.range b.add_overlay(args.overlay, args.min, args.max, args.sign) # Maybe load an annot if args.annotation is not None: if not args.borders: args.borders = any([args.overlay, args.morphometry]) b.add_annotation(args.annotation, args.borders) # Maybe load a label
brain = Brain("fsaverage", "both", "pial", background="dimgray") if not brain.patch_mode: brain.show_view("frontal") """ Because the morphometry files generated by recon-all live in a predicatble location, all you need to call the add_morphometry method with is the name of the measure you want. Here, we'll look at cortical curvatuve values, and plot them for both hemispheres. """ brain.add_morphometry("curv") """ Each of the possible values is displayed in an appropriate full-color map, but you can also display in grayscale. Here we only plot the left hemisphere. """ brain.add_morphometry("sulc", hemi='lh', grayscale=True) """ You can also use a custom colormap and tweak its range. """ brain.add_morphometry("thickness", colormap="PuBuGn", min=1, max=4)
print __doc__ from surfer import Brain brain = Brain("fsaverage", "both", "pial", views="frontal", config_opts=dict(background="dimgray")) """ Because the morphometry files generated by recon-all live in a predicatble location, all you need to call the add_morphometry method with is the name of the measure you want. Here, we'll look at cortical curvatuve values, and plot them for both hemispheres. """ brain.add_morphometry("curv") """ Each of the possible values is displayed in an appropriate full-color map, but you can also display in grayscale. Here we only plot the left hemisphere. """ brain.add_morphometry("sulc", hemi='lh', grayscale=True) """ The Brain object can only hold one morphometry overlay at a time, so adding a new one removes any existing overlays. """ brain.add_morphometry("thickness")
from surfer import Brain print(__doc__) brain = Brain("fsaverage", "both", "pial", views="frontal", background="dimgray") """ Because the morphometry files generated by recon-all live in a predicatble location, all you need to call the add_morphometry method with is the name of the measure you want. Here, we'll look at cortical curvatuve values, and plot them for both hemispheres. """ brain.add_morphometry("curv") """ Each of the possible values is displayed in an appropriate full-color map, but you can also display in grayscale. Here we only plot the left hemisphere. """ brain.add_morphometry("sulc", hemi='lh', grayscale=True) """ You can also use a custom colormap and tweak its range. """ brain.add_morphometry("thickness", colormap="PuBuGn", min=1, max=4)
""" from os import environ from os.path import join import numpy as np from surfer import Brain from nibabel.freesurfer import read_label print(__doc__) brain = Brain("fsaverage", "lh", "inflated") """ Show the morphometry with a continuous grayscale colormap. """ brain.add_morphometry("curv", colormap="binary", min=-.8, max=.8, colorbar=False) """ The easiest way to label any vertex that could be in the region is with add_label. """ brain.add_label("BA1", color="#A6BDDB") """ You can also threshold based on the probability of that region being at each vertex. """ brain.add_label("BA1", color="#2B8CBE", scalar_thresh=.5) """ It's also possible to plot just the label boundary, in case you wanted to overlay the label on an activation plot to asses whether it falls within that
from surfer import Brain brain = Brain("fsaverage", "both", "pial", views="frontal", config_opts=dict(background="dimgray")) """ Because the morphometry files generated by recon-all live in a predicatble location, all you need to call the add_morphometry method with is the name of the measure you want. Here, we'll look at cortical curvatuve values, and plot them for both hemispheres. """ brain.add_morphometry("curv") """ Each of the possible values is displayed in an appropriate full-color map, but you can also display in grayscale. Here we only plot the left hemisphere. """ brain.add_morphometry("sulc", hemi='lh', grayscale=True) """ The Brain object can only hold one morphometry overlay at a time, so adding a new one removes any existing overlays. """ brain.add_morphometry("thickness")
from surfer import Brain print(__doc__) brain = Brain("fsaverage", "both", "inflated", views="lateral", background="white") """ You can also use a custom colormap and tweak its range. """ brain.add_morphometry("thickness", colormap="Blues", min=1, max=4, colorbar=False) brain.save_image('./figures/elements_fig_concept_anatomy.png')
""" from os import environ from os.path import join import numpy as np from surfer import Brain from nibabel.freesurfer import read_label print(__doc__) brain = Brain("fsaverage", "lh", "inflated") """ Show the morphometry with a continuous grayscale colormap. """ brain.add_morphometry("curv", colormap="binary", min=-.8, max=.8, colorbar=False) """ The easiest way to label any vertex that could be in the region is with add_label. """ brain.add_label("BA1_exvivo", color="#A6BDDB") """ You can also threshold based on the probability of that region being at each vertex. """ brain.add_label("BA1_exvivo", color="#2B8CBE", scalar_thresh=.5) """ It's also possible to plot just the label boundary, in case you wanted to