MRI Contours 2D plotΒΆ

../../_images/mri_contours1.png

Similar to the MRI Regions example, 3D surface and contours are viewed normal to the xy-plane. The surface colormap and contour colormap are compliments to each other for contrast. The colormaps are shown below.

../../_images/cmap_mri_contours.png
import gzip
import copy
import numpy as np
from matplotlib import pyplot as plt
import s3dlib.surface as s3d
import s3dlib.cmap_utilities as cmu

#.. MRI contours 2D plot

# 1. Define function to examine .....................................

with gzip.open('data/s1045.ima.gz') as datafile:    
    s = datafile.read()
Z = np.frombuffer(s, np.uint16).astype(float).reshape((256, 256))
Z = np.flip(Z,0)

# 2. Setup and map surfaces .........................................
rez=6
cmu.hsv_cmap_gradient( [0.666,1,.25], [0.166,1,1], 'HSV_b-y' )
cmu.hsv_cmap_gradient( [1.166,1,1], [0.666,1,.25], 'HSV_y-b' )

surf = s3d.PlanarSurface(rez, basetype='oct1', name='MRI')
surf.map_geom_from_datagrid( Z, scale=.3 )
cont = surf.contourLineSet(6)
cont.set_linewidth(.5)

kwsurf,kwcont = copy.copy(surf),  copy.copy(cont)

kwsurf.map_cmap_from_datagrid( Z,'binary_r', cname='cmap: binary' )
kwcont.map_cmap_from_op( lambda c: c[2], 'binary' )
surf.map_cmap_from_datagrid( Z,'HSV_b-y',    cname='cmap: HSV' )
cont.map_cmap_from_op( lambda c: c[2], 'HSV_y-b' )

surfaces = [kwsurf, surf]
contour  = [kwcont, cont]

# 3. Construct figure, add surface, plot ............................
info = str(surf) +'\n'+ str(cont)

minmax = (-.7,.7)
fig = plt.figure(figsize=plt.figaspect(0.5))
fig.text(0.01,0.01,info, ha='left', va='bottom', fontsize='smaller')
for i,surface in enumerate(surfaces) :
    ax = fig.add_subplot(121+i, projection='3d')
    ax.set_proj_type('ortho')
    ax.set(xlim=minmax, ylim=minmax, zlim=minmax )
    ax.set_axis_off()
    ax.view_init(90,-90)
    ax.set_title(surface.cname, fontsize='xx-large')

    ax.add_collection3d( surface )
    ax.add_collection3d(contour[i].transform(translate=[0,0,1]))

fig.tight_layout(pad=0)
plt.show()