Python Brain.save_imageset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_imageset [as 别名]
 def vizify(self):
     for hemi in self.hemis:
         print "visualize %s" % hemi
         
         # Bring up the beauty (the underlay)
         brain = Brain(self.subject_id, hemi, self.surf, \
                       config_opts=self.config_opts, \
                       subjects_dir=self.subjects_dir)
         
         surf_data = io.read_scalar_data(self.overlay_surf[hemi])
         if (sum(abs(surf_data)) > 0):
             # Overlay another hopeful beauty (functional overlay)
             brain.add_overlay(self.overlay_surf[hemi], name=self.overlay_name, 
                               min=self.min, max=self.max, sign=self.sign)
         
             # Update colorbar
             #brain.overlays[self.overlay_name].pos_bar.lut_mode = self.colorbar
             tmp = brain.overlays[self.overlay_name]
             lut = tmp.pos_bar.lut.table.to_array()
             lut[:,0:3] = self.colorbar
             tmp.pos_bar.lut.table = lut
         
             # Refresh
             brain.show_view("lat")
             brain.hide_colorbar()
         
         # Save the beauts
         brain.save_imageset("%s_%s" % (self.outprefix, hemi), self.views, 
                             'jpg', colorbar=None)
         
         # End a great journey, till another life
         brain.close()
     return

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
def plot_surface(vtx_data, subject_id, subjects_dir, hemi, surface, output_dir, prefix, l, u, cmap, center, thresh):
    # Open up a brain in pysurfer
    brain = Brain(
        subject_id,
        hemi,
        surface,
        subjects_dir=subjects_dir,
        config_opts=dict(background="white", height=665, width=800),
    )

    if center:
        # Make sure the colorbar is centered
        if l ** 2 < u ** 2:
            l = u * -1
        else:
            u = l * -1

    # Create an empty brain if the values are all below threshold
    if np.max(vtx_data) < thresh:
        # Add your data to the brain
        brain.add_data(vtx_data * 0, l, u, thresh=thresh, colormap=cmap, alpha=0.0)

    # Otherwise, add the data appropriately!
    else:
        # Add your data to the brain
        brain.add_data(vtx_data, l, u, thresh=thresh, colormap=cmap, alpha=0.8)

    # Save the images for medial and lateral
    # putting a color bar on all of them
    brain.save_imageset(prefix=os.path.join(output_dir, prefix), views=views_list, colorbar=range(len(views_list)))

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
def plot_parcel(num_nodes=600,numbers=[1],hemi='lh'):
    from surfer import Brain, io
    for n in numbers:
        brain = Brain("fsaverage", "%s" %(hemi), "pial",config_opts=dict(background="white"))
        image = io.project_volume_data('/home/despo/mb3152/random_nodes/%s/parcel_%s.nii'%(num_nodes,n),hemi, subject_id="fsaverage", projsum = 'max', smooth_fwhm = 0)
        brain.add_data(image,thresh=1,colormap = "spectral")
        brain.save_imageset('/home/despo/mb3152/random_nodes/%s/parcel_%s' %(num_nodes,n),['med','lat'],'jpg',colorbar= None)
        brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [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_imageset [as 别名]
def save_groups_labels_figures():
    labels, groups = get_groups()
    for group in groups:
        print(group)
        if len(get_group_labels(group)) < 4:
            group_label = [l for l in labels if group in l]
            colors = get_spaced_colors(len(group_label))
        brain = Brain(subject, hemi, surf, offscreen=False)
        for label_id, label in enumerate(group_label):
            print(label)
            brain.add_label(label, color=colors[label_id])
        fol = os.path.join(subjects_dir, subject, 'label', '{}_figures'.format(aparc_name))
        if not os.path.isdir(fol):
            os.mkdir(fol)
        brain.save_imageset(os.path.join(fol, group), get_views(), 'jpg')
        brain.remove_labels()
        brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
def corr_image(resting_image,fwhm):
    """This function makes correlation image on brain surface"""
    import numpy as np
    import nibabel as nb
    import matplotlib.pyplot as plt
    from surfer import Brain, Surface
    import os

    img = nb.load(resting_image)
    corrmat = np.corrcoef(np.squeeze(img.get_data()))
    corrmat[np.isnan(corrmat)] = 0
    corrmat_npz = os.path.abspath('corrmat.npz')
    np.savez(corrmat_npz,corrmat=corrmat)

    br = Brain('fsaverage5', 'lh', 'smoothwm')

    #br.add_overlay(corrmat[0,:], min=0.2, name=0, visible=True)
    lh_aparc_annot_file = os.path.join(os.environ["FREESURFER_HOME"],'/subjects/label/lh.aparc.annot')
    values = nb.freesurfer.read_annot(lh_aparc_annot_file)

    #br.add_overlay(np.mean(corrmat[values[0]==5,:], axis=0), min=0.8, name='mean', visible=True)


    data = img.get_data()

    data = np.squeeze(img.get_data())

    #
    precuneus_signal = np.mean(data[values[0]==np.nonzero(np.array(values[2])=='precuneus')[0][0],:], axis=0)
    precuneus = np.corrcoef(precuneus_signal, data)
    #precuneus.shape

    #br.add_overlay(precuneus[0,1:], min=0.3, sign='pos', name='mean', visible=True)

    br.add_overlay(precuneus[0,1:], min=0.2, name='mean')#, visible=True)
    #br.add_overlay(precuneus[0,1:], min=0.2, name='mean')#, visible=True)
    plt.hist(precuneus[0,1:], 128)
    plt.savefig(os.path.abspath("histogram.png"))
    plt.close()

    corr_image = os.path.abspath("corr_image%s.png"%fwhm)
    br.save_montage(corr_image)
    ims = br.save_imageset(prefix=os.path.abspath('fwhm_%s'%str(fwhm)),views=['medial','lateral','caudal','rostral','dorsal','ventral'])
    br.close()
    print ims
    #precuneus[np.isnan(precuneus)] = 0
    #plt.hist(precuneus[0,1:])

    roitable = [['Region','Mean Correlation']]
    for i, roi in enumerate(np.unique(values[2])):
        roitable.append([roi,np.mean(precuneus[values[0]==np.nonzero(np.array(values[2])==roi)[0][0]])])

        #images = [corr_fimage]+ims+[os.path.abspath("histogram.png"), roitable]
    roitable=[roitable]
    histogram = os.path.abspath("histogram.png")

    return corr_image, ims, roitable, histogram, corrmat_npz

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [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_imageset [as 别名]
def plot_group(hub,num_nodes,hemi='lh'):
    from surfer import Brain, io
    brain = Brain("fsaverage", "%s" %(hemi), "pial",config_opts=dict(background="white"))
    if hub == 'pc' or hub =='wmd':
        image = io.project_volume_data('/home/despo/mb3152/random_nodes/%s/final_group_%s.nii'%(num_nodes,hub),hemi, subject_id="fsaverage", projsum = 'max', smooth_fwhm = 20)
        brain.add_data(image,thresh = np.nanmin(image[image>0]),colormap = "jet", colorbar= True)
        brain.save_imageset('/home/despo/mb3152/random_nodes/%s/final_%s' %(num_nodes,hub),['med','lat'],'jpg',colorbar= None)
    else:
        pc_image = io.project_volume_data('/home/despo/mb3152/random_nodes/%s/final_group_pc.nii'%(num_nodes),hemi, subject_id="fsaverage", projsum = 'max', smooth_fwhm = 20)
        wmd_image = io.project_volume_data('/home/despo/mb3152/random_nodes/%s/final_group_wmd.nii'%(num_nodes),hemi, subject_id="fsaverage", projsum = 'max', smooth_fwhm = 20) 
        wmd_thresh = np.nanmean(wmd_image[wmd_image>0])
        pc_thresh = np.nanmean(pc_image[pc_image >0])
        #find connetor hub activity
        connector_hub_image = pc_image.copy()
        connector_hub_image[pc_image < pc_thresh] = 0.
        connector_hub_image[wmd_image < wmd_thresh] = 0.
        #find sattelite connector activty
        satellite_image = pc_image.copy()
        satellite_image[pc_image < pc_thresh] = 0.
        satellite_image[wmd_image > wmd_thresh] = 0.
        # find provincial hub activity
        provincial_hub_image = wmd_image.copy()
        provincial_hub_image[pc_image > pc_thresh] = 0.
        provincial_hub_image[wmd_image < wmd_thresh] = 0.

        node_image = pc_image.copy()
        node_image[provincial_hub_image > 0] = 0
        node_image[connector_hub_image > 0] = 0
        node_image[satellite_image > 0] = 0
        node_image[node_image > 0] = 1

        # brain.add_data(node_image,thresh= 0, max = max(wmd_image), colormap = 'Blues',alpha= .65,hemi=hemi,smoothing_steps = 0)
        # brain.add_data(connector_hub_image,thresh=pc_thresh,max=np.nanmax(pc_image), colormap = 'Purples',alpha= .65,hemi=hemi,smoothing_steps = 0)
        # brain.add_data(satellite_image,thresh= pc_thresh,max=np.nanmax(pc_image),colormap = 'Reds',alpha= .65,hemi=hemi,smoothing_steps = 0)
        # brain.add_data(provincial_hub_image,thresh=wmd_thresh,max=np.nanmax(wmd_image),colormap = 'Blues',alpha= .65,hemi=hemi,smoothing_steps = 0)

        brain.add_data(node_image,thresh= 0, max = max(wmd_image), colormap = 'Blues',hemi=hemi,smoothing_steps = 0)
        brain.add_data(connector_hub_image,thresh=pc_thresh,max=np.nanmax(pc_image), colormap = 'Purples',hemi=hemi,smoothing_steps = 0)
        brain.add_data(satellite_image,thresh= pc_thresh,max=np.nanmax(pc_image),colormap = 'Reds',hemi=hemi,smoothing_steps = 0)
        brain.add_data(provincial_hub_image,thresh=wmd_thresh,max=np.nanmax(wmd_image),colormap = 'Blues',hemi=hemi,smoothing_steps = 0)
        brain.save_imageset('/home/despo/mb3152/random_nodes/%s/final_combined' %(num_nodes),['med','lat'],'jpg',colorbar= None)

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [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_imageset [as 别名]
                      config_opts=dict(background="white"), 
                      subjects_dir="/home2/data/PublicProgram/freesurfer")
    
        """Get the volume => surface file"""
        cwas_file = path.join(mdmr_dir, "surf_lh_fdr_logp_%s.nii.gz" % factor)

        """
        You can pass this array to the add_overlay method for
        a typical activation overlay (with thresholding, etc.)
        """
        brain.add_overlay(cwas_file, min=2, max=max_zvals[i], name="%s_lh" % factor)

        ## get overlay and color bar
        tmp1 = brain.overlays["%s_lh" % factor]
        lut = tmp1.pos_bar.lut.table.to_array()

        ## update color scheme
        lut[:,0:3] = cols
        tmp1.pos_bar.lut.table = lut

        ## refresh view
        brain.show_view("lat")
        brain.hide_colorbar()

        """Save Pictures"""
        brain.save_imageset(path.join(odir, "zpics_%s_%s_surface_lh" % (sample, factor)), 
                            ['med', 'lat', 'ros', 'caud'], 'jpg')

        brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
## update color scheme
single = [251, 154, 143]
overlap = [227, 26, 28]
lut[0:85,0:3] = single
lut[85:170,0:3] = single
lut[170:256,0:3] = overlap
tmp1.pos_bar.lut.table = lut

## refresh view
brain.show_view("lat")
brain.hide_colorbar()

"""Save Pictures"""
odir = "/home/data/Projects/CWAS/age+gender/03_robustness/viz_cwas/pysurfer"
brain.save_imageset(path.join(odir, "zpics_overlap_age_surface_rh"), 
                    ['med', 'lat', 'ros', 'caud'], 'jpg')

brain.close()


## SEX

"""Bring up the visualization"""
brain = Brain("fsaverage_copy", "rh", "iter8_inflated",
              config_opts=dict(background="white"), 
              subjects_dir="/home2/data/PublicProgram/freesurfer")

"""Project the volume file and return as an array"""
cwas_file = path.join(overlap_dir, "surf_rh_fdr_logp_sex_thr2.nii.gz")

"""

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
                                          projmeth=projmeth,
                                          projsum=projsum, 
                                          projarg=projarg,
                                          smooth_fwhm = smooth_fwhm,
                                          subject_id='fsaverage')


        # nothing to do, if all points in the projection are nul                              
        if surf_data.max()!=0:
            name_overlay = '{name_roi}_{hemi}'.format(name_roi=name_roi, hemi=hemi)
            brain.add_overlay(surf_data, name=name_overlay, hemi=hemi)
            overlay_roi = brain.overlays[name_overlay]
            lut = overlay_roi.pos_bar.lut.table.to_array()
            lut[0:255, 0:3] = color_list[cpt_color]
            overlay_roi.pos_bar.lut.table = lut
            
            # Save in png   
            #brain.save_imageset(save_png, ['lat'], 'png', colorbar=None)  
            
            # Color cpt
            cpt_color += 1
            
            # If you just want one roi by one  
            # Remove for the next roi
            # for overlay in brain.overlays_dict[name_overlay]:
            #    overlay.remove() 
    
    #   Save in png  
    save_png = os.path.join(datadir, "all_rois")  
    brain.save_imageset(save_png, ['lat'], 'png', colorbar=None) 
    brain.close()

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
tmp1 = brain.overlays["%s_rh" % factor]
lut = tmp1.pos_bar.lut.table.to_array()

## update color scheme
lut[:,0:3] = cols
tmp1.pos_bar.lut.table = lut

## refresh view
brain.show_view("lat")
brain.hide_colorbar()

"""
Save some images
"""
odir = "/home/data/Projects/CWAS/development+motion/viz"
brain.save_imageset(path.join(odir, "zpics_surface_%s_rh" % "only_age"), 
                    ['med', 'lat', 'ros', 'caud'], 'jpg')

brain.close()


## Age with motion as covariate

print "age with motion"

mdmr_dir = "/home2/data/Projects/CWAS/development+motion/cwas/rois_random_k3200/age+motion_sex+tr.mdmr"
factor = "age"

"""Bring up the visualization"""
brain = Brain("fsaverage_copy", "rh", "iter8_inflated",
              config_opts=dict(background="white"), 
              subjects_dir="/home2/data/PublicProgram/freesurfer")

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
            l = u*-1
    else:
        cmap = "jet"
        
    """
    Make a vector containing the data point at each vertex.
    """
    vtx_data = roi_data[labels]
    
    """
    Display these values on the brain.
    """
    ### MEAN
    brain = Brain(subject_id, hemi, surface,
                  subjects_dir = subjects_dir,
                  config_opts=dict(background="white"))

    
    brain.add_data(vtx_data,
                    l, 
                    u,
                    thresh = -98,
                    colormap=cmap,
                    alpha=.8)
    
    views_list = [ 'medial', 'lateral' ]
    prefix = '_'.join([data_file.strip('.csv'), surface, hemi])
    brain.save_imageset(prefix = os.path.join(fs_rois_dir, prefix),
                        views = views_list, 
                        colorbar = range(len(views_list)) )
                        

# 需要导入模块: from surfer import Brain [as 别名]
# 或者: from surfer.Brain import save_imageset [as 别名]
            data_min = 0
        else:
            data_min = data[data.nonzero()].min()

        """
        You can pass this array to the add_overlay method for
        a typical activation overlay (with thresholding, etc.)
        """
        brain.add_overlay(cwas_file, min=data_min, max=data_max, name="%s_rh" % factor)

        ## get overlay and color bar
        tmp1 = brain.overlays["%s_rh" % factor]
        lut = tmp1.pos_bar.lut.table.to_array()

        ## update color scheme
        lut[:,0:3] = cols
        tmp1.pos_bar.lut.table = lut

        ## refresh view
        brain.show_view("lat")
        brain.hide_colorbar()

        """
        Save some images
        """
        odir = "/home/data/Projects/CWAS/%s/viz" % study
        brain.save_imageset(path.join(odir, "zpics_surface_%s_rh" % onames[i][j]), 
                            ['med', 'lat', 'ros', 'caud'], 'jpg')

        brain.close()