def visualize_colorbar(savedir, min=0.75, max=1.0):
    gl.resetdefaults()
    gl.minmax(0, min, max)
    gl.colorname(0, colorname)
    gl.opacity(0, 0)
    gl.colorbarposition(1)
    gl.savebmp(os.path.join(savedir, 'colorbar.png'))
def visualize_axial(niidir, savedir, min=0.75, max=1.0):
    gl.viewaxial(1)
    for method in ['grad', 'cam']:
        for network in ['Vis', 'SomMot', 'DorsAttn', 'SalVentAttn', 'Limbic', 'Cont', 'Default']:
            for gender in ['female', 'male']:
                gl.overlayload(os.path.join(niidir, 'network', 'saliency_{}_{}_top20_{}_lh'.format(method, gender, network)))
                gl.overlayload(os.path.join(niidir, 'network', 'saliency_{}_{}_top20_{}_rh'.format(method, gender, network)))
                gl.minmax(1, min, max)
                gl.minmax(2, min, max)
                gl.colorname(1, colorname)
                gl.colorname(2, colorname)

                gl.savebmp(os.path.join(savedir, '{}_{}_{}_axial.png'.format(method, network, gender)))
                gl.overlaycloseall()
def visualize_sagittal(niidir, savedir, min=0.75, max=1.0):
    for hemisphere in ['lh', 'rh']:
        if hemisphere =='lh': gl.clipazimuthelevation(0.49, 90, 0)
        elif hemisphere =='rh': gl.clipazimuthelevation(0.49, 270, 0)
        for network in ['Vis', 'SomMot', 'DorsAttn', 'SalVentAttn', 'Limbic', 'Cont', 'Default']:
            for gender in ['female', 'male']:
                gl.overlayload(os.path.join(niidir, 'network', 'saliency_{}_top20_{}_{}'.format(method, gender, network, hemisphere)))
                gl.minmax(1, min, max)
                gl.colorname(1, colorname)

                gl.viewsagittal(1)
                gl.savebmp(os.path.join(savedir, '{}_{}_sagittal_{}_lt.png'.format(network, gender, hemisphere)))
                gl.viewsagittal(0)
                gl.savebmp(os.path.join(savedir, '{}_{}_sagittal_{}_rt.png'.format(network, gender, hemisphere)))
                gl.overlaycloseall()
networks_names=['DMN','SMOTOR','VISUAL','AUDIT','ECN_L','ECN_R']
netfile_sufx= ['_Group1X','_Group2L','_Group3R','_Group4N']

for net in networks_names:
    savefolder=FILESPATH + '\\' + net + '\\'
    for i in netfile_sufx:
    
        FILENAME=net+i
        SEEDFILENAME=net+"_seed"
    
        gl.overlaycloseall()
        gl.overlayload(FILENAME)
        gl.overlayload(SEEDFILENAME)
        gl.colorname (2,"3blue")
        
        #gl.opacity(1,50)
        
        # changing view ----------------------
        gl.azimuthelevation(140,20)
        ktime= 1
        ksteps= 72
        for x in range(0, ksteps):
            gl.azimuthelevation(140+(x*5),20)
            gl.wait(ktime)
    
            if x < 10:
                gl.savebmp(savefolder + FILENAME + '_0' + str(x)+'.png')
            else:
                gl.savebmp(savefolder + FILENAME + '_' + str(x)+'.png')

# %% General----------------------

gl.backcolor(255, 255, 255)

# %% background image ----------------------
gl.loadimage('mni152')

# %% overlay ----------------------
FILESPATH = 'D:\\GD_UNICAMP\\IC_NeuroFisica\\Projetos\\fMRI_TLE_2020\\Seed_based_analysis'
os.chdir(FILESPATH)

#networks_names=['DMN','SMOTOR','VISUAL','AUDIT','DAN']
networks_names = ['DAN_R', 'DAN_L']
netfile_sufx = ['_Group1X', '_Group2L', '_Group3R', '_Group4N']

for net in networks_names:
    SEEDFILENAME = net + '_seed'
    for sufx in netfile_sufx:

        FILENAME = net + sufx

        gl.overlaycloseall()
        gl.overlayload(FILENAME)
        gl.overlayload(SEEDFILENAME)
        gl.colorname(2, "3blue")

        gl.azimuthelevation(0, 90)

        gl.savebmp(FILESPATH + '\\' + FILENAME)
예제 #6
0
    '//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/oldadult/spmT_0001.nii'
]
#OA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/oldadult/spmT_0002.nii']
#OA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/oldadult/spmT_0003.nii']
#OA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/oldadult/spmT_0004.nii']
#OA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/oldadult/spmT_0005.nii']

gl.overlayload(OA_filename[0])
gl.minmax(1, 1, 5)
gl.colorname(1, "8redyell")
gl.opacity(1, 80)
#gl.mosaic('l+ h -0.3 v -0.1 a 55 s x r 0')
gl.mosaic('a 55')
gl.colorbarposition(0)
#gl.linewidth(5)
gl.savebmp(OA_filename[0])

gl.loadimage(
    '//cifs.rc.ufl.edu/ufrc/rachaelseidler/tfettrow/Crunch_Code/MR_Templates/MNI_2mm.nii'
)
YA_filename = [
    '//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/youngadult/spmT_0001.nii'
]
#YA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/youngadult/spmT_0002.nii']
#YA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/youngadult/spmT_0003.nii']
#YA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/youngadult/spmT_0004.nii']
#YA_filename = ['//cifs.rc.ufl.edu/ufrc/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/Level2_Results/MRI_files/05_MotorImagery/youngadult/spmT_0005.nii']

gl.overlayload(YA_filename[0])
gl.minmax(1, 1, 5)
gl.colorname(1, "8redyell")
예제 #7
0
rois_to_plot = ['neurosynth_acc_gmMasked', 'neurosynth_dlpfc_left_gmMasked', 'neurosynth_dlpfc_right_gmMasked']
# rois_to_plot = ['neurosynth_acc_mask', 'neurosynth_dlpfc_left_mask', 'neurosynth_dlpfc_right_mask']
# rois_to_plot = ['left_dlpfc', 'right_dlpfc', 'left_acc', 'right_acc']
######################################

gl.loadimage('//exasmb.rc.ufl.edu/blue/rachaelseidler/tfettrow/Crunch_Code/MR_Templates/MNI_2mm.nii')

gl.opacity(1,1)
######################################
# rois_plotted=1;
# this_index=0;
for this_roi in rois_to_plot:
    # gl.loadimage('//exasmb.rc.ufl.edu/blue/rachaelseidler/tfettrow/Crunch_Code/MR_Templates/MNI_2mm.nii')
    # gl.opacity(1,10)
    
    # gl.mosaic('a -36 -32 -28 -24 -20 -16 -10 -6 -2; 2 6 10 14 18 22 26 30 34; 38 42 46 50 54 58 62 66 70')
    # gl.mosaic("A R 0 C R 0 S R 0; A R -0 C R -0 S R -0");
    gl.mosaic("A R 0");
  
    gl.overlayload("//exasmb.rc.ufl.edu/blue/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/ROIs/"+this_roi)
    #gl.minmax(0,.01,.01)
    gl.colorbarposition(0)

    gl.colornode(1,2,255,0,0,255,255) # blue
    gl.colornode(2,2,255,255,0,0,255) # red
    gl.colornode(3,2,255,0,255,0,255) # green
    # gl.colornode(4,2,255,0,88,0,255) #darkgreen
    gl.backcolor(255,255,255)

    gl.savebmp("//exasmb.rc.ufl.edu/blue/rachaelseidler/share/FromExternal/Research_Projects_UF/CRUNCH/MiM_Data/ROIs/"+this_roi)
gl.minmax(1, 0, 3)
gl.minmax(2, 0, 3)
gl.colorname(1, '1red')
gl.colorname(2, '3blue')
output_dir_path = os.path.join(analysis_path, 'imageSequenceFolders',
                               'pVal_inv_sig_InDe')
if not os.path.exists(output_dir_path):
    os.mkdir(output_dir_path)

y_min = -13.15
y_max = 0
y_step = 0.05

y = y_min
count = 0
while y <= y_max:
    print(y)
    count = count + 1
    print(count)

    gl.orthoviewmm(0, y, -4)
    gl.view(2)
    gl.linewidth(0)
    gl.colorbarposition(0)

    filepath = os.path.join(output_dir_path, 'imagenew' + '_' +
                            str(round(count)).rjust(3, '0')) + '_' + str(y)
    gl.savebmp(filepath)

    y = y + y_step
예제 #9
0
OAi_filenames=['C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/OAi_Flat', \
 'C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/OAi_Low', \
'C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/OAi_Med', \
'C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/OAi_Hard' ]

for this_index in range(0, len(OAi_filenames)):
    gl.overlaycloseall()
    gl.overlayload(OAi_filenames[this_index])
    gl.minmax(1, 0, 5)
    gl.colorname(1, "8redyell")
    gl.opacity(1, 80)
    #gl.mosaic('l+ h -0.3 v -0.1 a 55 s x r 0')
    gl.mosaic('a 55')
    gl.colorbarposition(0)
    #gl.linewidth(5)
    gl.savebmp(OAi_filenames[this_index])

# YA_filenames=['C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/YA_Flat', \
#  'C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/YA_Low', \
# 'C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/YA_Med', \
# 'C:/Users/tfettrow/Dropbox (UFL)/CrunchReview/Tables_and_Figs/YA_Hard' ]

# for this_index in range(0,len(YA_filenames)):
# 	gl.overlaycloseall()
# 	gl.overlayload(YA_filenames[this_index])
# 	gl.minmax(1, 0, 5)
# 	gl.colorname (1,"8redyell")
# 	gl.opacity(1,80)
# 	#gl.mosaic('l+ h -0.3 v -0.1 a 55 s x r 0')
# 	gl.mosaic('a 55')
# 	gl.colorbarposition(0)