def plotShapeMetrics(resultfile, pdfpages):
ld = resultfile.obtain_data('ld')
# get data as time series
data = collections.defaultdict(list)
for groupname in resultfile.groupnames:
metrics = resultfile.obtain_data('shape_metrics', groupname)
for k, v in metrics.iteritems():
data[k].append(v)
data['time'].append(resultfile.obtain_data('time', groupname))
# plot it
for groupname in resultfile.groupnames[-1:]:
metrics = resultfile.obtain_data('shape_metrics', groupname)
curv, curv_weights = resultfile.obtain_data('curvature_samples',
groupname)
#pprint.pprint(metrics)
fig, axes = pyplot.subplots(2, 2, figsize=(8, 6))
text = []
text += [
'time : {}'.format(f2s(resultfile.obtain_data('time', groupname)))
]
text += [
'surface tension : {}'.format(
f2s(
float(resultfile.f['parameters/tumor'].
attrs['surface_tension'])))
]
text += ['sphericity : {}'.format(f2s(metrics['sphericity']))]
text += ['approx. radius : {}'.format(f2s(metrics['radius']))]
text = '\n'.join(text)
axes[0, 0].text(0.1, 0.1, text, fontsize=14)
mpl_utils.remove_frame(axes[0, 0])
h, bins = np.histogram(curv,
bins=10,
weights=curv_weights,
normed=True)
bins = 0.5 * (bins[1:] + bins[:-1])
axes[0, 1].bar(bins, h, width=bins[1] - bins[0])
axes[0, 1].set(title=ur'$\kappa$', xlabel=ur'[1/\u03BCm]', ylabel='N')
axes[1, 0].plot(data['time'], data['radius'], marker='x')
axes[1, 0].set(xlabel='$t$', ylabel=r'$r_{tum}$')
v, y0 = linearFit(data['time'], data['radius'])
x = np.asarray([0., data['time'][-1] * 1.1])
y = y0 + v * x
axes[1, 0].plot(x, y, label=ur'v = %s [\u03BCm/h]' % f2s(v))
axes[1, 0].legend()
axes[1, 1].set_visible(False)
fig.subplots_adjust(left=0.10,
right=0.95,
top=0.95,
bottom=0.10,
wspace=0.2,
hspace=0.2)
pdfpages.savefig(fig)
def plot3dRendering(resultfile, pdfpages, showVessels=False, showTumor=True):
arr = resultfile.obtain_data('3drendering', resultfile.groupnames[-1],
showVessels, showTumor)
fig, ax = pyplot.subplots(1, 1, figsize=(8, 7))
fig.subplots_adjust(left=0.1,
right=0.9,
top=0.9,
bottom=0.1,
wspace=0.,
hspace=0.)
ax.imshow(arr, interpolation='none')
mpl_utils.remove_frame(ax)
pdfpages.savefig(fig)
origin='lower',
interpolation='nearest',
vmin=0.,
vmax=maxMVD)
plt1 = ax1.imshow(grad,
extent=extents,
origin='lower',
interpolation='nearest',
vmin=0.,
vmax=maxGrad)
ax0.contour(mask,
levels=[0.],
extent=extents,
linewidths=0.25,
colors='w')
ax1.contour(mask,
levels=[0.],
extent=extents,
linewidths=0.25,
colors='w')
mpl_utils.remove_frame(ax0, ax1)
ax0.set(title='MVD (' + filename + ')')
ax1.set(title='Grad')
divider = mpl_utils.make_axes_locatable(ax0)
cax = divider.append_axes("right", size="5%", pad=0.05)
fig.colorbar(plt0, cax=cax)
divider = mpl_utils.make_axes_locatable(ax1)
cax = divider.append_axes("right", size="5%", pad=0.05)
fig.colorbar(plt1, cax=cax)
#pyplot.tight_layout()
pdfwriter.savefig(fig)