Python Brain.save_image方法代码示例

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def drawROI():
	for hemi in ["lh"]:
		# load data
		roivol = io.project_volume_data(roifile,
						             hemi,
						             subject_id=surfsubj,
						             smooth_fwhm=4.0,
						             projmeth="dist",
						             projsum="avg",
						             projarg=[0,6,0.1],
						             surf="white")
		# create label
		roivol = abs(roivol)
		roivol[roivol < 0.33] = 0
		#if max(roivol) < 1:
		#	brain.close()
		#	continue
		#else:
		write_label(np.asarray(np.nonzero(roivol)),"/gablab/p/bps/zqi_ytang/scripts/roi/surf-IFG.label")

		# load brain
		my_fig = mlab.figure(figure="new_fig1", size=(800,800))
		brain = Brain("fsaverage",hemi,"inflated",curv=True,size=[800,800],background="white",cortex=(("gist_yarg",-1.5,3.5,False)),figure=my_fig)
		set_mylights(my_fig,lights[hemi])

		#add label
		brain.add_label("/gablab/p/bps/zqi_ytang/scripts/roi/surf-IFG.label",borders=False,color="#ffff00",alpha=1)
		brain.add_label("/gablab/p/bps/zqi_ytang/scripts/roi/surf-IFG.label",borders=1,color="black",alpha=0.5)

		brain.show_view('lat')
		brain.save_image("/gablab/p/bps/zqi_ytang/scripts/roi/surf-IFG.tiff")
		brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def curvature_normalization(data_dir, subj, close=True):
    """Normalize the curvature map and plot contour over fsaverage."""
    surf_dir = op.join(data_dir, subj, "surf")
    snap_dir = op.join(data_dir, subj, "snapshots")
    for hemi in ["lh", "rh"]:

        cmd = ["mri_surf2surf",
               "--srcsubject", subj,
               "--trgsubject", "fsaverage",
               "--hemi", hemi,
               "--sval", op.join(surf_dir, "%s.curv" % hemi),
               "--tval", op.join(surf_dir, "%s.curv.fsaverage.mgz" % hemi)]

        sub.check_output(cmd)

        b = Brain("fsaverage", hemi, "inflated",
                  config_opts=dict(background="white",
                                   width=700, height=500))
        curv = nib.load(op.join(surf_dir, "%s.curv.fsaverage.mgz" % hemi))
        curv = (curv.get_data() > 0).squeeze()
        b.add_contour_overlay(curv, min=0, max=1.5, n_contours=2, line_width=4)
        b.contour["colorbar"].visible = False
        for view in ["lat", "med"]:
            b.show_view(view)
            mlab.view(distance=330)
            png = op.join(snap_dir, "%s.surf_warp_%s.png" % (hemi, view))
            b.save_image(png)

        if close:
            b.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def test_image():
    """Test image saving
    """
    mlab.options.backend = 'auto'
    brain = Brain(*std_args, config_opts=small_brain)
    tmp_name = mktemp() + '.png'
    brain.save_image(tmp_name)
    brain.save_imageset(tmp_name, ['med', 'lat'], 'jpg')
    brain.save_montage(tmp_name, ['l', 'v', 'm'], orientation='v')
    brain.screenshot()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def pysurfer_plot_perm_ttest_results(vertices, vertives_values, max_vals, fol):
    T = max(vertices.keys())
    for t in range(T+1):
        print(t)
        brain = Brain('fsaverage', 'split', 'pial', curv=False, offscreen=False, views=['lat', 'med'], title='{} ms'.format(t))
        for hemi in ['rh', 'lh']:
            if t in vertices:
                brain.add_data(np.array(vertives_values[t][hemi]), hemi=hemi, min=1, max=max_vals, remove_existing=True,
                         colormap="YlOrRd", alpha=1, vertices=np.array(vertices[t][hemi]))
        brain.save_image(os.path.join(fol, '{}.jpg'.format(t)))
        brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def inflated_surfaces(out_dir, subj, close=True):
    """Native inflated surfaces with cortical label."""
    for hemi in ["lh", "rh"]:
        b = Brain(subj, hemi, "inflated", curv=False,
                  config_opts=dict(background="white",
                                   width=800, height=500))
        b.add_label("cortex", color="#6B6B6B")

        for view in ["lat", "med"]:
            b.show_view(view)
            mlab.view(distance=400)
            png = op.join(out_dir, "%s.surface_%s.png" % (hemi, view))
            b.save_image(png)
        if close:
            b.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def make_pysurfer_images(folder,suffix='cope1',threshold=0.9499,coords=(),surface='inflated',fwhm=0,filename='',saveFolder=[]):
    from surfer import Brain, io
    TFCEposImg,posImg,TFCEnegImg,negImg=getFileNamesfromFolder(folder,suffix)

    pos=image.math_img("np.multiply(img1,img2)",
                         img1=image.threshold_img(TFCEposImg,threshold=threshold),img2=posImg)
    neg=image.math_img("np.multiply(img1,img2)",
                         img1=image.threshold_img(TFCEnegImg,threshold=threshold),img2=negImg)
    fw=image.math_img("img1-img2",img1=pos,img2=neg)

    if fwhm==0:
        smin=np.min(np.abs(fw.get_data()[fw.get_data()!=0]))
    else:
        smin=2

    mri_file = "%s/thresholded_posneg.nii.gz" % folder
    fw.to_filename(mri_file)

    """Bring up the visualization"""
    brain = Brain("fsaverage", "split", surface ,views=['lat', 'med'], offscreen=True , background="white")

    """Project the volume file and return as an array"""

    reg_file = os.path.join("/opt/freesurfer","average/mni152.register.dat")
    surf_data_lh = io.project_volume_data(mri_file, "lh", reg_file,smooth_fwhm=fwhm)
    surf_data_rh = io.project_volume_data(mri_file, "rh", reg_file,smooth_fwhm=fwhm)


    """
    You can pass this array to the add_overlay method for a typical activation
    overlay (with thresholding, etc.).
    """
    brain.add_overlay(surf_data_lh, min=smin, max=5, name="ang_corr_lh", hemi='lh')
    brain.add_overlay(surf_data_rh, min=smin, max=5, name="ang_corr_rh", hemi='rh')

    if len(coords)>0:
        if coords[0]>0:
            hemi='rh'
        else:
            hemi='lh'
        brain.add_foci(coords, map_surface="pial", color="gold",hemi=hemi)

    if len(saveFolder)>0:
        folder=saveFolder
        brain.save_image('%s/%s.png' % (folder,filename))
    else:
        brain.save_image('%s/surfaceplot.jpg' % folder)
    brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def plot_data_surf_bh(in_file, colormap='jet', thr_list=[(None, None, None)],roi_coords=(), fwhm=0):
    '''
    allows more flexible visualization than plot_rs_surf_bh
    thr_list = [(min, max, thresh)]
    colormap: matplotlib colormap (http://matplotlib.org/examples/color/colormaps_reference.html)
    '''

    # in_file .nii to be projected on surface


    import os
    from surfer import Brain, io

    out_file_list = []
    in_file_name = os.path.basename(in_file)

    reg_file = os.path.join(os.environ["FREESURFER_HOME"],"average/mni152.register.dat")
    for thr in thr_list:
        min_thr = thr[0]
        max_thr = thr[1]
        thr_thr = thr[2]


        brain = Brain("fsaverage", "split", "inflated", views=['lat', 'med'], config_opts=dict(background="white"))

        surf_data_lh = io.project_volume_data(in_file, "lh", reg_file, smooth_fwhm=fwhm)
        surf_data_rh = io.project_volume_data(in_file, "rh", reg_file, smooth_fwhm=fwhm)

        brain.add_data(surf_data_lh, min=min_thr, max=max_thr, thresh=thr_thr, colormap=colormap, hemi='lh')
        brain.add_data(surf_data_rh, min=min_thr, max=max_thr, thresh=thr_thr, colormap=colormap, hemi='rh')

        roi_str = ''
        if not(roi_coords == ()):
            if roi_coords[0] <0: #lh
                hemi_str = 'lh'
            else:
                hemi_str = 'rh'
            roi_str = '_roi_%s.%s.%s' % roi_coords

            brain.add_foci(roi_coords, map_surface="white", hemi=hemi_str, color='red', scale_factor=2)


        out_filename = os.path.join(os.getcwd(), in_file_name + roi_str + '_thr_%s' % min_thr + '.png')
        out_file_list += [out_filename]
        brain.save_image(out_filename)
        brain.close()
    return out_file_list

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def plot_rs_surf(in_file, thr_list=[(.2,1)],roi_coords=(), fwhm=0):
    # in_file .nii to be projected on surface
    # list of tuples defining min and max thr_list=[(.2,1)]
    import os
    import subprocess
    from surfer import Brain, io

    arch = subprocess.check_output('arch')
    if arch.startswith('x86_'): # set offscrene rendering to avoid intereference on linux
        from mayavi import mlab
        mlab.options.offscreen = True

    out_file_list = []
    in_file_name = os.path.basename(in_file)

    reg_file = os.path.join(os.environ["FREESURFER_HOME"],"average/mni152.register.dat")
    for thr in thr_list:
        min_thr = thr[0]
        max_thr = thr[1]
        print(min_thr)
        print(max_thr)

        for hemi in ['lh', 'rh']:
            brain = Brain("fsaverage", hemi, "inflated", views=['lat', 'med'], config_opts=dict(background="white"))

            surf_data = io.project_volume_data(in_file, hemi, reg_file, smooth_fwhm=fwhm)

            brain.add_overlay(surf_data, min=min_thr, max=max_thr, name="ang_corr", hemi=hemi)

            roi_str = ''
            if not(roi_coords == ()):
                if roi_coords[0] <0: #lh
                    hemi_str = 'lh'
                else:
                    hemi_str = 'rh'
                roi_str = '_roi_%s.%s.%s' % roi_coords

                if hemi_str == hemi:
                    brain.add_foci(roi_coords, map_surface="white", hemi=hemi_str, color='red', scale_factor=2)


            out_filename = os.path.join(os.getcwd(), in_file_name + roi_str + '_thr_%s' % min_thr + '_' + hemi + '.png')
            out_file_list += [out_filename]
            brain.save_image(out_filename)
            brain.close()
    return out_file_list

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def test_image():
    """Test image saving
    """
    tmp_name = mktemp() + '.png'

    mlab.options.backend = 'auto'
    subject_id, _, surf = std_args
    brain = Brain(subject_id, 'both', surf=surf, size=100)
    brain.add_overlay(overlay_fname, hemi='lh', min=5, max=20, sign="pos")
    brain.save_imageset(tmp_name, ['med', 'lat'], 'jpg')

    brain = Brain(*std_args, size=100)
    brain.save_image(tmp_name)
    brain.save_montage(tmp_name, ['l', 'v', 'm'], orientation='v')
    brain.save_montage(tmp_name, ['l', 'v', 'm'], orientation='h')
    brain.save_montage(tmp_name, [['l', 'v'], ['m', 'f']])
    brain.screenshot()
    brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def plot_rs_surf_bh(in_file, thr_list=[(.2,1)],roi_coords=(), fwhm=0):
    # in_file .nii to be projected on surface
    # list of tuples defining min and max thr_list=[(.2,1)]
    import os
    from surfer import Brain, io

    out_file_list = []
    in_file_name = os.path.basename(in_file)

    reg_file = os.path.join(os.environ["FREESURFER_HOME"],"average/mni152.register.dat")
    for thr in thr_list:
        min_thr = thr[0]
        max_thr = thr[1]
        print(min_thr)
        print(max_thr)

        brain = Brain("fsaverage", "split", "inflated", views=['lat', 'med'], config_opts=dict(background="white"))

        surf_data_lh = io.project_volume_data(in_file, "lh", reg_file, smooth_fwhm=fwhm)
        surf_data_rh = io.project_volume_data(in_file, "rh", reg_file, smooth_fwhm=fwhm)

        brain.add_overlay(surf_data_lh, min=min_thr, max=max_thr, name="ang_corr_lh", hemi='lh')
        brain.add_overlay(surf_data_rh, min=min_thr, max=max_thr, name="ang_corr_rh", hemi='rh')

        roi_str = ''
        if not(roi_coords == ()):
            if roi_coords[0] <0: #lh
                hemi_str = 'lh'
            else:
                hemi_str = 'rh'
            roi_str = '_roi_%s.%s.%s' % roi_coords

            brain.add_foci(roi_coords, map_surface="white", hemi=hemi_str, color='red', scale_factor=2)


        out_filename = os.path.join(os.getcwd(), in_file_name + roi_str + '_thr_%s' % min_thr + '.png')
        out_file_list += [out_filename]
        brain.save_image(out_filename)
        brain.close()
    return out_file_list

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def test_image(tmpdir):
    """Test image saving."""
    tmp_name = tmpdir.join('temp.png')
    tmp_name = str(tmp_name)  # coerce to str to avoid PIL error

    _set_backend()
    subject_id, _, surf = std_args
    brain = Brain(subject_id, 'both', surf=surf, size=100)
    brain.add_overlay(overlay_fname, hemi='lh', min=5, max=20, sign="pos")
    brain.save_imageset(tmp_name, ['med', 'lat'], 'jpg')
    brain.close()

    brain = Brain(*std_args, size=100)
    brain.save_image(tmp_name)
    brain.save_image(tmp_name, 'rgba', True)
    brain.screenshot()
    if os.getenv('TRAVIS', '') != 'true':
        # for some reason these fail on Travis sometimes
        brain.save_montage(tmp_name, ['l', 'v', 'm'], orientation='v')
        brain.save_montage(tmp_name, ['l', 'v', 'm'], orientation='h')
        brain.save_montage(tmp_name, [['l', 'v'], ['m', 'f']])
    brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
from surfer import Brain

DST = '../images/brain_%s.png'
subjects_dir = '/Volumes/Seagate/refpred/mri'
surfaces = ('inflated',
            'inflated_avg',
            'inflated_pre',
            # 'orig',
            # 'pial',
            'smoothwm',
            'sphere',
            'white')


for surf in surfaces:
    brain = Brain('fsaverage', 'lh', surf, size=400, background='white',
                  subjects_dir=subjects_dir)
    brain.save_image(DST % surf, 'rgba', True)

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
        label_fname = os.path.join(root, f) 
        label = mne.read_label(label_fname)
        #label.values.fill(1.0)
        #label_morph = label.morph(subject_from='fsaverage', subject_to=subject, smooth=5, 
         #                        n_jobs=1, copy=True)
        if label.hemi == 'lh':
           brain.add_label(label, color=random.choice(color))
        elif label.hemi == 'rh':
           brain.add_label(label, color=random.choice(color))
#brain.add_foci(vertno_max, coords_as_verts=True, hemi='lh', color='blue', scale_factor=0.6)
# If the label lives in the normal place in the subjects directory,
# you can plot it by just using the name
#ref_ROI_fname = '/home/qdong/freesurfer/subjects/fsaverage/label/lh.Auditory_82.label'
#ref_label = mne.read_label(ref_ROI_fname)
#brain.add_label(ref_label, color="blue")
#brain.add_label("ROI1", color="blue")
#brain.add_label("ROI2", color="red")
#brain.add_label("ROI3", color="green")
#brain.add_label("ROI4", color="blue")
#brain.add_label("ROI5", color="blue")
#brain.add_label("ROI6", color="blue")
#brain.add_label("ROI7", color="blue")
#brain.add_label("ROI8", color="blue")
#brain.add_label("ROI9", color="blue")
#brain.add_label("ROI10", color="blue")
#brain.add_label("ROI11", color="blue")
#brain.add_label("RefROI1", color="yellow")
#
brain.show_view("lateral")
brain.save_image('/home/qdong/freesurfer/subjects/101611/lh_ROI2.tiff')

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
def drawContrast(infile,outname):
	for hemi in ["rh"]:
		# load data
		volpos = io.project_volume_data(infile,
						             hemi,
						             subject_id=surfsubj,
						             smooth_fwhm=4.0,
						             projmeth="dist",
						             projsum="max",
						             projarg=[-6,6,0.1],
						             surf="pial")
		"""
		volneg = io.project_volume_data(rsfcfile_neg,
						             hemi,
						             subject_id=surfsubj,
						             smooth_fwhm=4.0,
						             projmeth="dist",
						             projsum="max",
						             projarg=[-6,6,0.1],
						             surf="white")
		volneg=volneg*-1
		ccvol=volpos+volneg
		"""

		# load brain
		my_fig = mlab.figure(figure="new_fig1", size=(800,800))
		brain = Brain("fsaverage",hemi,"inflated",curv=True,size=[800,800],background="white",cortex=(("gist_yarg",-1.5,3.5,False)),figure=my_fig)
		set_mylights(my_fig,lights[hemi])

		if outname == "fig6b":
			# create label
			labIFG = volpos
			labIFG[labIFG < 2.0739] = 0
			write_label(np.asarray(np.nonzero(labIFG)),"fig6prep/roi_IFG.label")
			#brain.add_label("fig6prep/roi_IFG.label",borders=False,color="red",alpha=0.125)			
			brain.add_label("fig6prep/roi_IFG.label",borders=2,color="#e7298a",alpha=1)		

		if outname == "fig6d":
			# create label
			labAG = io.project_volume_data("/gablab/p/CASL/Results/Imaging/resting/zqi/conn_CASL_pre_post_training13o/results/secondlevel/ANALYSIS_01/3mohsk_all(0).3mohsk(1)/pre-training(-1).post-training(1)/anat_func_lifg_1_1/roi_AG.nii.gz",
								         hemi,
								         subject_id=surfsubj,
								         smooth_fwhm=4.0,
								         projmeth="dist",
								         projsum="max",
								         projarg=[-6,6,0.1],
								         surf="pial")
			labAG[labAG < 0.33] = 0
			write_label(np.asarray(np.nonzero(labAG)),"fig6prep/roi_AG.label")
			labSTGMTG = io.project_volume_data("/gablab/p/CASL/Results/Imaging/resting/zqi/conn_CASL_pre_post_training13o/results/secondlevel/ANALYSIS_01/3mohsk_all(0).3mohsk(1)/pre-training(-1).post-training(1)/anat_func_lifg_1_1/roi_STGMTG.nii.gz",
								         hemi,
								         subject_id=surfsubj,
								         smooth_fwhm=4.0,
								         projmeth="dist",
								         projsum="max",
								         projarg=[-6,6,0.1],
								         surf="pial")
			labSTGMTG[labSTGMTG < 0.66] = 0
			write_label(np.asarray(np.nonzero(labSTGMTG)),"fig6prep/roi_STGMTG.label")
			#brain.add_label("fig6prep/roi_AG.label",borders=False,color="black",alpha=0.125)
			brain.add_label("fig6prep/roi_AG.label",borders=2,color="#1b9e77",alpha=1)
			#brain.add_label("fig6prep/roi_STGMTG.label",borders=False,color="blue",alpha=0.125)
			brain.add_label("fig6prep/roi_STGMTG.label",borders=2,color="#7570b3",alpha=1)


		brain.add_overlay(volpos,
							min=2.0739, #p = 0.025 2-tailed
							max=5.0216, #p = 0.000025, 2-tailed
							sign="abs",
							name=outname,
							hemi=hemi)

		brain.show_view('lat')
		brain.save_image("fig6prep/%s.tiff"%(outname))
		brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_image [as 别名]
rh_aparc_file = os.path.join(label_dir, right_label_file)
lh_labels, lh_ctab, lh_names = nb.freesurfer.read_annot(lh_aparc_file)
rh_labels, rh_ctab, rh_names = nb.freesurfer.read_annot(rh_aparc_file)
left_df = left_df.set_index('col').loc[lh_names].reset_index().fillna(0)
right_df = right_df.set_index('col').loc[rh_names].reset_index().fillna(0)
vtx_lh = left_df.val.values[lh_labels]
vtx_lh[lh_labels == -1] = 0
vtx_rh = right_df.val.values[rh_labels]
vtx_rh[rh_labels == -1] = 0

brain.add_data(vtx_lh,
               0,
               400,
               colormap="Reds",
               alpha=.8,
               hemi='lh')

brain.add_annotation(lh_aparc_file, hemi='lh')

brain.add_data(vtx_rh,
               0,
               400,
               colormap="Reds",
               alpha=.8,
               hemi='rh')

brain.add_annotation(rh_aparc_file, hemi='rh', remove_existing=False)
save_name = "../images/{}_brain.png".format(save_name)
brain.save_image(save_name)