def DoGetMurrayForSingleFile(fn, pattern):
vesselgrp_before = fn['adaption/recomputed']
result = ku.get_Murray(ku.find_lattice_group_(vesselgrp_before),
vesselgrp_before)
vesselgrp_after = fn['adaption/vessels_after_adaption']
result_after = ku.get_Murray(ku.find_lattice_group_(vesselgrp_after),
vesselgrp_after)
#print result
max_before = np.max(result[0, :])
max_after = np.max(result_after[0, :])
xmax = np.ceil(np.fmax(max_before, max_after))
x = np.arange(0, xmax, 0.1)
y = x
fig1, (ax1, ax2) = plt.subplots(2, 1, sharex=True, sharey=True)
#fig1.suptitle('this is the figure title', fontsize=12)
ax1.set_title('Murray for \n%s\n%i points considered' %
(os.path.basename(afile.filename), result.shape[1]))
#plt.subplot(2,1,1)
ax1.scatter(result[0, :], np.sqrt(result[1, :]**2 + result[2, :]**2))
ax1.set_xlabel('radius mother/ daughter vessel')
ax1.set_ylabel(r"$\sqrt{r_a^2+r_b^2}$")
#plt.title('Murray for \n%s\n%i points considered' % (os.path.basename(afile.filename),result.shape[1]))
ax1.plot(x, y, 'k')
ax1.grid()
ax1.legend(['murray', 'before_data'], loc=4)
# plt.subplot(2,1,2)
ax2.scatter(result_after[0, :],
np.sqrt(result_after[1, :]**2 + result_after[2, :]**2))
#ax2.set_xlabel('radius mother/ daughter vessel')
ax2.set_ylabel(r"$\sqrt{r_a^2+r_b^2}$")
#plt.title('Murray for \n%s\n%i points considered' % (os.path.basename(afile.filename),result.shape[1]))
ax2.plot(x, y, 'k')
ax2.legend(['murray', 'after_data'], loc=4)
ax2.grid()
plt.savefig('murray_%s.png' % os.path.basename(afile.filename))
def DoGetMurrayForSingleFileGENERAL(fn, pattern, pdfpages):
afile = h5files.open(fn, 'r')
vesselgrp = afile[pattern]
print(vesselgrp)
result_venous, result_a = ku.get_Murray(vesselgrp)
#result = ku.get_Murray(vesselgrp, alpha)
result_venous = removeZeros(result_venous)
result_a = removeZeros(result_a)
#x=np.arange(0,max_,0.1)
#y=x
#fig1, (ax1, ax2) = plt.subplots(2,1,sharex=True, sharey=True)
fig1, (ax1, ax2) = plt.subplots(2, 1)
### plot murrays law with exponent
alphas = np.arange(2, 6, 0.5)
alphas = [3]
max_ = np.max(result_venous[2, :])
min_ = np.min(result_venous[0, :])
x = np.arange(min_, max_, 0.1)
font = {
'family': 'serif',
'color': 'black',
'weight': 'normal',
'size': 4,
'rotation': 30,
'verticalalignment': 'bottom',
'horizontalalignment': 'left',
}
for alpha in alphas:
ax1.text(x[-1], x[-1], r'$\alpha = %0.1f $' % alpha, fontdict=font)
ax1.plot(x, x, c='k', linewidth=0.1)
### plot data
ax1.set_title('%i venous points, %i arterial points' %
(result_venous.shape[1], result_a.shape[1]),
size=6)
# ax1.set_title('Murray for file:\n%s\n%i venous points, %i arterial points' % (os.path.basename(afile.filename),result_venous.shape[1], result_a.shape[1]), size=6)
pointsize = 0.1
venous = ax1.scatter(np.power(
result_venous[0, :]**3 + result_venous[1, :]**3, 1 / float(3)),
result_venous[2, :],
c='b',
s=pointsize,
label='bldk')
arterial = ax1.scatter(np.power(result_a[0, :]**3 + result_a[1, :]**3,
1 / float(3)),
result_a[2, :],
c='r',
s=pointsize)
ax1.set_xlabel(r'$\sqrt[3]{r_{daughter_1}^3 + r_{daughter_2}^3}$')
ax1.set_ylabel(r'$r_{mother}$')
ax1.legend((venous, arterial), ('Venous', 'Arterial'), loc='lower right')
ax1.grid()
### histogramm deviation of daughters
hist, bin_edges = np.histogram(
result_a[1, :] - result_a[0, :],
bins=50) #note. they are sorted in on c++ side
width = 0.7 * (bin_edges[1] - bin_edges[0])
centers = (bin_edges[:-1] + bin_edges[1:]) / 2
ax2.bar(centers,
hist / float(len(result_a[0, :])),
align='center',
width=width,
color='red')
ax2.set_xlabel(r'$\|r_{daughter 1}- r_{daughter 2}\|$')
ax2.set_ylabel(r'$p$')
fig1.tight_layout()
pdfpages.savefig(fig1)
def DoGetMurray(filenames, pdfpages):
alpha = 3
filenames = adaption.get_files_with_successful_adaption(filenames)
files = [h5files.open(fn, 'r') for fn in filenames]
for afile in files:
print("consider file: %s " % afile.filename)
if ('adaption/recomputed' in afile):
vesselgrp_before = afile['adaption/recomputed']
if ('vessels/recomputed_flow' in afile):
vesselgrp_before = afile['vessels/recomputed_flow']
if (not 'vesselgrp_before' in locals()):
print("bad")
if ('results' in locals()):
results = np.hstack(
(results, ku.get_Murray(vesselgrp_before, alpha)))
else:
results = ku.get_Murray(vesselgrp_before, alpha)
vesselgrp_after = afile['adaption/vessels_after_adaption']
if ('results_after' in locals()):
results_after = np.hstack(
(results_after, ku.get_Murray(vesselgrp_after, alpha)))
else:
results_after = ku.get_Murray(vesselgrp_after, alpha)
results = removeZeros(results)
results_after = removeZeros(results_after)
#print result
max_before = np.amax(results)
max_after = np.amax(results_after)
xmax = np.ceil(np.fmax(max_before, max_after))
x = np.arange(0, xmax, 0.1)
y = x
fig1, (ax1, ax2) = plt.subplots(2, 1, sharex=True, sharey=True)
fig2, (ax3, ax4) = plt.subplots(2, 1, sharex=True, sharey=True)
#fig2 = plt.hist(results[0,:]-results[1,:],20)
#fig1.suptitle('this is the figure title', fontsize=12)
ax1.set_title('Murray for \n%s\n%i points considered' %
(os.path.basename(afile.filename), results.shape[1]))
#plt.subplot(2,1,1)
ax1.scatter(results[0, :], results[1, :])
#ax1.set_xlabel('daughter vessel')
ax1.set_ylabel('mother')
#plt.title('Murray for \n%s\n%i points considered' % (os.path.basename(afile.filename),result.shape[1]))
ax1.plot(x, y, 'k')
ax1.grid()
ax1.legend(['murray', 'before_data'], loc=4)
# plt.subplot(2,1,2)
ax2.scatter(results_after[0, :], results_after[1, :])
ax2.set_xlabel(r"daughter $\sqrt{\sum_ir_i^2}$")
#ax2.set_ylabel(r"$\sqrt{r_a^2+r_b^2}$")
#plt.title('Murray for \n%s\n%i points considered' % (os.path.basename(afile.filename),result.shape[1]))
ax2.plot(x, y, 'k')
ax2.legend(['murray', 'after_data'], loc=4)
ax2.grid()
pdfpages.savefig(fig1)
#fig1.savefig('murray_%s.png' % os.path.basename(afile.filename))
hist, bin_edges = np.histogram(results[0, :] - results[1, :], bins=50)
width = 0.7 * (bin_edges[1] - bin_edges[0])
centers = (bin_edges[:-1] + bin_edges[1:]) / 2
ax3.bar(centers, hist, align='center', width=width)
hist_after, bin_edges = np.histogram(
results_after[0, :] - results_after[1, :], bin_edges)
ax4.bar(centers, hist_after, align='center', width=width)
#fig2.savefig('dens_murray_%s.png' % os.path.basename(afile.filename))
pdfpages.savefig(fig2)