def testdistancemap():
c = np.asarray((25, 25, 25))
a = make_test_array(c)
x = krebs.distancemap(a)
print "range: %f %f" % (x.min(), x.max())
grad = krebs.field_gradient(x, spacing=1.)
for i, g in enumerate(grad):
print "grad range %i: %f %f" % (i, g.min(), g.max())
gnorm = np.sum(g * g for g in grad)
for i in [c[2]]: #xrange(x.shape[2]):
plt.subplot(221)
p = plt.imshow(x[:, :, i],
vmin=x.min(),
vmax=6,
interpolation='nearest')
plt.colorbar(p)
plt.subplot(222)
p = plt.imshow(a[:, :, i], interpolation='nearest')
plt.colorbar(p)
plt.subplot(223)
p = plt.imshow(grad[0][:, :, i], interpolation='nearest')
plt.colorbar(p)
plt.subplot(224)
p = plt.imshow(gnorm[:, :, i], interpolation='nearest')
plt.colorbar(p)
plt.show()
def calc_distmap(tumorgroup):
ld = get_tumld(tumorgroup)
distmap = np.asarray(tumorgroup['ls']) > 0
distmap = krebsutils.flood_fill(distmap, (0, 0, 0))
distmap = np.logical_not(distmap)
distmap = krebsutils.distancemap(distmap) * ld.scale
return distmap
def addBulkTissueTumor(epv, tumorgroup, trafo, options):
ld = krebsutils.read_lattice_data_from_hdf_by_filename(
str(tumorgroup.file.filename),
str(tumorgroup['conc'].attrs['LATTICE_PATH']))
ld = transform_ld(trafo, ld)
ds_necro = np.asarray(tumorgroup['necro'])
data = np.clip(np.asarray(tumorgroup['conc']), 0.,
1.) # - np.asanyarray(tumorgroup['necro']), 0., 1.)
ds_levelset = -np.minimum(np.asarray(tumorgroup['ls']), 0.4 - ds_necro)
ds_levelset = krebsutils.distancemap(ds_levelset) * ld.scale
# import matplotlib
# matplotlib.use('Qt4Agg')
# import matplotlib.pyplot as pyplot
# pyplot.imshow(ds_levelset[:,:,8])
# pyplot.contour(ds_levelset[:,:,8],[0.])
# pyplot.show()
if 'tumor_clip' in options:
clip = clipFactory(options.tumor_clip)
else:
clip = clipFactory('None')
voldata_ls = epv.declareVolumeData(ds_levelset, ld.GetWorldBox())
voldata_cells = epv.declareVolumeData(data, ld.GetWorldBox())
value_bounds = voldata_cells.value_bounds
style = """
texture {
pigment {
function { %f + %f*%s(x,y,z) }
color_map {
[0.0 color <0.3,0,0>]
[0.5 color <1,0.8, 0.3>]
[0.8 color <1,1,0.1>]
}
}
finish {
specular 0.3
}
}""" % (value_bounds[0],
(value_bounds[1] - value_bounds[0]), voldata_cells.name)
#style = " texture { pigment { color rgb<1,0.8,0.3> } finish { specular 0.3 }}"
epv.addIsosurface(voldata_ls, 0., lambda: style, clip, style)
def calc_distmap(ds, ld, level): distmap = np.asarray(ds) > level distmap = krebsutils.flood_fill(distmap, (0,0,0)) distmap = np.logical_not(distmap) distmap = krebsutils.distancemap(distmap)*ld.scale return distmap