def AddStatsPage(self, pdfwriter):
text = GenerateGlobalMeasurementOutputStrings(self.dataman,
self.po2group,
self.cachelocation)
text += ['-----------------------']
text += GenerateParameterOutputStrings(self.dataman, self.group,
self.cachelocation)
fig, _ = mpl_utils.MakeTextPage(text,
figsize=(mpl_utils.a4size[0] * 0.5,
mpl_utils.a4size[1] * 0.75))
pdfwriter.savefig(fig, postfix='_data')
def DoIt(filenames, pattern, with_o2):
fn_measure = basename(commonprefix(filenames))
fn_measure = myutils.strip_from_end(fn_measure, '.h5')
fn_measure = myutils.strip_from_end(fn_measure, '-type')
def cachelocation(g):
path = posixpath.join(
'FileCS_' + myutils.checksum(basename(g.file.filename)),
g.name.strip(posixpath.sep))
return (f_measure, path)
if with_o2:
fn_measure = myutils.strip_from_end(fn_measure, '_detailedpo2')
files = [h5files.open(fn, 'a') for fn in filenames]
f_measure = h5files.open('plotVessels_chache.h5', 'a', search=False)
groups = list(
itertools.chain.from_iterable(
myutils.walkh5(f, pattern, return_h5objects=True) for f in files))
if len(groups) <= 0:
print 'no matching groups in hdf file(s)'
sys.exit(0)
if with_o2:
name = posixpath.commonprefix(map(lambda g: g.name, groups))
name = myutils.strip_from_start(name, '/po2/vessels').replace('/', '-')
fn_measure += name
with mpl_utils.PdfWriter(fn_measure + '.pdf') as pdfpages:
rc = matplotlib.rc
rc('font', size=8.)
rc('axes', titlesize=10., labelsize=8.)
if with_o2:
import detailedo2Analysis as o2analysis
import detailedo2Analysis.plotsForPaper
import detailedo2
dataman = myutils.DataManager(20, [
o2analysis.DataDetailedPO2(),
analyzeGeneral.DataTumorTissueSingle(),
analyzeGeneral.DataDistanceFromCenter(),
analyzeGeneral.DataBasicVessel(),
analyzeGeneral.DataVesselSamples(),
analyzeBloodFlow.DataTumorBloodFlow(),
analyzeGeneral.DataVesselRadial(),
analyzeGeneral.DataVesselGlobal()
])
vesselgroups = list(
detailedo2.OpenVesselAndTumorGroups(g)[0] for g in groups)
#original_vesselgroups = list(h5files.openLink(g, 'SOURCE') for g in vesselgroups)
if 1:
PrintGlobalDataWithOxygen(pdfpages, groups, vesselgroups,
f_measure, dataman)
'''FormatParameters makes the network creation parameters
that does not work, if we have an o2 file'''
#text = FormatParameters(original_vesselgroups[0].file)
text = [' ']
text += detailedo2Analysis.plotsForPaper.FormatParameters(
groups[0])
fig, _ = mpl_utils.MakeTextPage(text,
figsize=(mpl_utils.a4size[0],
mpl_utils.a4size[0]))
pdfpages.savefig(fig, postfix='_vesselsparams')
if 1:
res = getMultiScatter(300. * len(filenames), vesselgroups)
plotMultiScatterBeauty(res, pdfpages)
else:
dataman = myutils.DataManager(20, [
analyzeGeneral.DataTumorTissueSingle(),
analyzeGeneral.DataVesselRadial(),
analyzeGeneral.DataDistanceFromCenter(),
analyzeBloodFlow.DataTumorBloodFlow(),
analyzeGeneral.DataBasicVessel(),
analyzeGeneral.DataVesselSamples(),
analyzeGeneral.DataVesselGlobal()
])
#dataman = myutils.DataManager(20, [ analyzeGeneral.DataBasicVessel(), analyzeGeneral.DataVesselSamples(), analyzeGeneral.DataVesselGlobal()])
vesselgroups = groups
if 0:
res = getMultiScatter(300. * len(filenames), vesselgroups)
plotMultiScatterBeauty(res, pdfpages)
if 0:
PlotRadiusHistogram2(dataman, vesselgroups, pdfpages)
if 0 and all(map(lambda g: 'data' in g.parent, vesselgroups)):
data = VesselData()
for g in vesselgroups:
data.add(g.parent['data'])
plot_topological_stats_avg(data, pdfpages)
if 0: #reproduce swine
plot_geometric_stuff_on_RC(dataman, f_measure, filenames,
options, pdfpages)
if 1:
PrintGlobalData(pdfpages, vesselgroups, f_measure, dataman)
def PrintGlobalData(pdfpages, vesselgroups, f_measure, dataman):
from analyzeBloodVolumeSimple import cylinderCollectionVolumeDensity
import detailedo2Analysis.plotsForPaper
import detailedo2
sample_length = detailedo2Analysis.plotsForPaper.sample_length
def cachelocation(g):
path = posixpath.join(
'FileCS_' + myutils.checksum(basename(g.file.filename)),
g.name.strip(posixpath.sep))
return (f_measure, path)
f2l = myutils.f2l
bbox_vessels = list()
data_by_name = collections.defaultdict(list)
#prop_list = ['mvd', 'mvd_a', 'mvd_v', 'mvd_c', 'rBV', 'rBV_a', 'rBV_v', 'rBV_c', 'venous_rBV_fraction', 'rBF', 'meanCapillaryDistance', 'mean_r']
#prop_list = ['rBV', 'rBF', ]
#prop_list = 'phi_a phi_v phi_c mvd_a mvd_v mvd_c mean_r'.split()
prop_list2 = [
'radius', 'shearforce', 'velocity', 'flow', 'avg_cap_dist',
'mvd_linedensity', 'mvd_sphere_sampling', 'mvd', 'mvd_a', 'mvd_v',
'mvd_c', 'phi_vessels', 'phi_a', 'phi_v', 'phi_c', 'total_perfusion'
]
#prop_list2 = ['radius','shearforce','velocity','flow','avg_cap_dist','mvd_linedensity','phi_vessels']
prop_data_vessel_global = ['mvd']
try:
os.remove('initialvesseldata.h5')
except OSError:
pass
with h5py.File('initialvesseldata.h5', 'w-') as f:
for k, v in data_by_name.iteritems():
f.create_dataset(k, data=v)
result_string = []
for name in prop_list2:
data = []
for gvessels in vesselgroups:
data.append(
dataman.obtain_data('basic_vessel_global', name, gvessels,
cachelocation(gvessels)))
ld_vessels = krebsutils.read_lattice_data_from_hdf(
gvessels['lattice'])
bbox_vessels.append(ld_vessels.worldBox)
result_string.append(r'$<%s>$ = $%s$%s' %
(Prettyfier.get_sym(name), Format(
name, data), Prettyfier.get_munit(name)))
ld = krebsutils.read_lattice_data_from_hdf(vesselgroups[0]['lattice'])
bbox_vessels.append(ld.worldBox)
bbox_vessels = np.average(bbox_vessels, axis=0).reshape(3, 2).transpose()
result_string += ['Vessel System Bounding Box'] + list(fmt_(bbox_vessels))
fig, _ = mpl_utils.MakeTextPage(result_string,
figsize=(mpl_utils.a4size[0],
mpl_utils.a4size[0]))
pdfpages.savefig(fig, postfix='_vesselsglobal')
def PrintGlobalDataWithOxygen(pdfpages, po2groups, vesselgroups, f_measure,
dataman):
from analyzeBloodVolumeSimple import cylinderCollectionVolumeDensity
import detailedo2Analysis.plotsForPaper
import detailedo2
sample_length = detailedo2Analysis.plotsForPaper.sample_length
def cachelocation(g):
path = posixpath.join(
'FileCS_' + myutils.checksum(basename(g.file.filename)),
g.name.strip(posixpath.sep))
return (f_measure, path)
f2l = myutils.f2l
bbox_vessels = list()
bbox_field = list()
data_by_name = collections.defaultdict(list)
O2_prop_list = [
'po2', 'sat', 'sat_via_hb_ratio', 'gtv', 'jtv', 'mro2', 'po2_tissue',
'chb', 'chb_oxy', 'chb_deoxy', 'oef', 'e1', 'e3', 'Jin_root',
'Jout_root', 'Jout_tv', 'Jout_cons', 'sat_vein', 'sat_art', 'sat_capi'
]
prop_list = [
'mvd', 'mvd_a', 'mvd_v', 'mvd_c', 'rBV', 'rBV_a', 'rBV_v', 'rBV_c',
'venous_rBV_fraction', 'rBF', 'meanCapillaryDistance', 'mean_r'
]
#prop_list2 = ['shearforce', 'velocity']
#prop_list2 = ['velocity']
for po2group in po2groups:
for prop in O2_prop_list:
data = dataman.obtain_data('detailedPO2_global', prop, po2group,
sample_length, cachelocation(po2group))
data_by_name[prop].append(data)
ld = krebsutils.read_lattice_data_from_hdf(po2group['field_ld'])
bbox_field.append(ld.worldBox)
gvessels, _ = detailedo2.OpenVesselAndTumorGroups(po2group)
# for prop in prop_list2:
# data = dataman.obtain_data('basic_vessel_global', prop, gvessels, cachelocation(gvessels))
# data_by_name[prop].append(data)
ld = krebsutils.read_lattice_data_from_hdf(gvessels['lattice'])
bbox_vessels.append(ld.worldBox)
rbv, a, v, c = cylinderCollectionVolumeDensity(gvessels)
sa, sv, sc = data_by_name['sat_art'][-1], data_by_name['sat_vein'][
-1], data_by_name['sat_capi'][-1]
data_by_name['sat_estimated_by_acv'].append(
(sa * a + sv * v + sc * c) / rbv)
O2_prop_list.append('sat_estimated_by_acv')
try:
os.remove('initialvesseldata.h5')
except OSError:
pass
with h5py.File('initialvesseldata.h5', 'w-') as f:
for k, v in data_by_name.iteritems():
f.create_dataset(k, data=v)
# def fmt_(v, exponent=None, multi=1.):
# avg, std = np.average(v, axis=0), np.std(v, axis=0)
# if exponent is not None:
# exponent_str = ('\,10^{%i}' % exponent) if exponent<>0 else ''
# f = math.pow(10., exponent)
# s = r'%s \pm %s%s' % (f2l(avg/f*multi, exponential=False), f2l(std/f*multi, exponential=False), exponent_str)
# else:
# s = r'%s \pm %s\,' % (f2l(avg*multi), f2l(std*multi))
# return s
result_string = []
for name, v in myutils.iterate_items(data_by_name, O2_prop_list):
result_string.append(r'$<%s>$ = $%s$%s' %
(Prettyfier.get_sym(name), Format(
name, v), Prettyfier.get_munit(name)))
# text = FormatGeometricAndPerfusionData()
prop_list2 = ['avg_cap_dist', 'mvd_linedensity']
#bbox_vessels = list()
#bbox_field = list()
for name in prop_list2:
data = []
for gvessels in vesselgroups:
data.append(
dataman.obtain_data('basic_vessel_global', name, gvessels,
cachelocation(gvessels)))
#ld = krebsutils.read_lattice_data_from_hdf(vesselgroups[0]['lattice'])
#bbox_vessels.append(ld.worldBox)
result_string.append(r'$<%s>$ = $%s$%s' %
(Prettyfier.get_sym(name), Format(
name, data), Prettyfier.get_munit(name)))
#""" some problems still exists here
#need field_ld which in not consistently stored"""
# mvd_exp=[]
# for (gvessels,po2group) in zip(vesselgroups,po2groups):
# ld = krebsutils.read_lattice_data_from_hdf(po2group['field_ld'])
# mvd_sampling_results, mvd_bins = dataman.obtain_data('sphere_vessel_density', gvessels, None, suggest_bins_from_world(ld), 'radial', ld, cachelocation(gvessels))
# mvd_exp.append(np.mean(np.asarray(mvd_sampling_results)*1e6))
#
# result_string.append(r'$<%s>$ = $%s$%s' %
# (Prettyfier.get_sym('mvd_exp'), Format('mvd_exp', mvd_exp), Prettyfier.get_munit('mvd_exp')))
bbox_vessels = np.average(bbox_vessels, axis=0).reshape(3, 2).transpose()
bbox_field = np.average(bbox_field, axis=0).reshape(3, 2).transpose()
result_string += ['Vessel System Bounding Box'] + list(
fmt_(bbox_vessels)) + ['FD-Grid Bounding Box'] + list(fmt_(bbox_field))
fig, _ = mpl_utils.MakeTextPage(result_string,
figsize=(mpl_utils.a4size[0],
mpl_utils.a4size[0]))
pdfpages.savefig(fig, postfix='_vesselsglobal')
fig = matplotlib.figure.Figure(figsize=(mpl_utils.a4size[0] * 0.5,
mpl_utils.a4size[0] * 0.5))
ax = fig.add_axes([0.1, 0.2, 0.8, 0.75])
for po2group in po2groups:
iterations = detailedo2Analysis.plotsForPaper.GetConvergenceData(
po2group)
x = iterations['iteration']
y = iterations['delta_vessM'] + iterations['delta_fieldM']
ax.plot(x, y)
ax.set(yscale='log',
xlabel='iterations',
ylabel=r'$|p(new) - p(old)|_\infty$')
pdfpages.savefig(fig, postfix='_convergence')
def DoIt(filenames, options):
fn_measure = basename(commonprefix(filenames))
fn_measure = myutils.strip_from_end(fn_measure, '.h5')
fn_measure = myutils.strip_from_end(fn_measure, '-type')
f_measure = h5files.open('adaption_common.h5', 'a', search = False)
files = [h5files.open(fn, 'r') for fn in filenames]
groups_with_adaption = [f['/vessels_after_adaption'] for f in files]
#this data is stored with the adaption
files_without_adaption = []
for afile in files:
completeFilename=str(afile['/vessels_after_adaption/parameters'].attrs['cwd'])+'/'+str(afile['/vessels_after_adaption/parameters'].attrs['vesselFileName'])
files_without_adaption.append(
h5files.open(completeFilename))
groups_without_adaption = [f['vessels'] for f in files_without_adaption]
with mpl_utils.PdfWriter('adaption_' + fn_measure+'.pdf') as pdfpages:
import analyzeGeneral
dataman = myutils.DataManager(20, [ analyzeGeneral.DataBasicVessel(), analyzeGeneral.DataVesselSamples(), analyzeGeneral.DataVesselGlobal()])
# vesselgroups_without = groups_without_adaption
# vesselgroups_with = groups_with_adaption
geometric_data_before = getGeometricData(groups_without_adaption)
perfusion_data_before = getTotalPerfusion(groups_without_adaption)*60
geometric_data_after = getGeometricData(groups_with_adaption)
perfusion_data_after = getTotalPerfusion(groups_with_adaption)*60
if 1:
res_without = getMultiScatter(300. * len(filenames), groups_without_adaption)
plotMultiScatterBeauty(res_without, pdfpages)
res_with = getMultiScatter(300. * len(filenames), groups_with_adaption)
plotMultiScatterBeauty(res_with, pdfpages, withRadiusPressureRelation=False)
# if 0:
# PlotRadiusHistogram2(dataman, groups_without_adaption, pdfpages)
# PlotRadiusHistogram2(dataman, groups_with_adaption, pdfpages)
#
if 0:
#printBarPlot_rBV(filenames, pdfpages) -->alt
printBarPlot_rBV(dataman, f_measure, filenames, options, pdfpages) #-->mw enginered
if 0:
printBarPlot_rBF(dataman, f_measure, filenames, options, pdfpages)
if 0:
PlotRadiusHistogram_with_cache_by_RC(dataman, f_measure, filenames, options, pdfpages)
#PlotRadiusHistogram_with_cache(dataman, f_measure, filenames, options, pdfpages)
if 0:
printBarPlot_vesseltype_on_root_node_configuration(filenames, pdfpages)
## is it worth to update this ???
if 1:
#importing the murray thing
#DoGetMurray(filenames, pdfpages)
printMurray(dataman, f_measure, filenames, options, pdfpages)
if 1:
printMurray_alphas_effective(dataman, f_measure, filenames, options, pdfpages)
if 1:
text = ["Before adaption"]
text2 = FormatGeometricAndPerfusionData(geometric_data_before, perfusion_data_before)
text = text+text2
def cachelocation(g):
path = posixpath.join('FileCS_'+myutils.checksum(basename(g.file.filename)), g.name.strip(posixpath.sep))
return (f_measure, path)
prop_list2 = ['shearforce', 'velocity']
for name in prop_list2:
data = []
for gvessels in groups_without_adaption:
data.append(dataman.obtain_data('basic_vessel_global', name, gvessels, cachelocation(gvessels)))
text.append(r'$<%s>$ = $%s$%s' %
(Prettyfier.get_sym(name), Format(name, data), Prettyfier.get_munit(name)))
fig, _ = mpl_utils.MakeTextPage(text,figsize = (mpl_utils.a4size[0]*0.8, mpl_utils.a4size[0]*0.8))
pdfpages.savefig(fig, postfix='_vesselsglobal')
text = FormatParameters(groups_without_adaption[0].file)
fig, _ = mpl_utils.MakeTextPage(text,figsize = (mpl_utils.a4size[0]*0.8, mpl_utils.a4size[0]*0.8))
pdfpages.savefig(fig, postfix='_vesselsparams')
text = ["After adaption"]
text2 = FormatGeometricAndPerfusionData(geometric_data_after, perfusion_data_after)
text = text+text2
def cachelocation(g):
path = posixpath.join('FileCS_'+myutils.checksum(basename(g.file.filename)), g.name.strip(posixpath.sep))
return (f_measure, path)
prop_list2 = ['shearforce', 'velocity']
for name in prop_list2:
data = []
for gvessels in groups_with_adaption:
data.append(dataman.obtain_data('basic_vessel_global', name, gvessels, cachelocation(gvessels)))
text.append(r'$<%s>$ = $%s$%s' %
(Prettyfier.get_sym(name), Format(name, data), Prettyfier.get_munit(name)))
fig, _ = mpl_utils.MakeTextPage(text,figsize = (mpl_utils.a4size[0]*0.8, mpl_utils.a4size[0]*0.8))
pdfpages.savefig(fig, postfix='_vesselsglobal')
text = FormatParameters(groups_without_adaption[0].file)
fig, _ = mpl_utils.MakeTextPage(text,figsize = (mpl_utils.a4size[0]*0.8, mpl_utils.a4size[0]*0.8))
pdfpages.savefig(fig, postfix='_vesselsparams')
if 0 and all(map(lambda g: 'data' in g.parent, groups_without_adaption)):
data = VesselData()
for g in groups_without_adaption:
data.add(g.parent['data'])
plot_topological_stats_avg(data, pdfpages)
if 1:
#PlotQdevs_unnormalized(filenames, pdfpages)
PlotQdevs_normalized(filenames, options, pdfpages)
