def loadmodel(basedir, ptcode, ctcode, cropname, modelname='modelavgreg'):
""" Load stent model. An ssdf struct is returned.
"""
# Load
fname = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, modelname)
try:
s = ssdf.load(os.path.join(basedir, ptcode, fname))
except FileNotFoundError:
s = ssdf.load(os.path.join(basedir, fname))
# Turn into graph model
from stentseg.stentdirect import stentgraph
for key in dir(s):
if key.startswith('model'):
model = stentgraph.StentGraph()
model.unpack(s[key])
s[key] = model
# also unpack seeds if exist
#-mind that also seeds need to be packed before save is possible again-
elif key.startswith('seeds'):
seeds = stentgraph.StentGraph()
seeds.unpack(s[key])
s[key] = seeds
elif key.startswith('landmark'): # landmark validation
landmarks = stentgraph.StentGraph()
landmarks.unpack(s[key])
s[key] = landmarks
return s
def loadvol(basedir,
ptcode=None,
ctcode=None,
cropname=None,
what='phases',
fname=None):
""" Load volume data. An ssdf struct is returned. The volumes
are made into Aarray's with their sampling and origin set.
"""
if fname is None:
fname = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, what)
try:
s = ssdf.load(os.path.join(basedir, ptcode, fname))
except FileNotFoundError:
s = ssdf.load(os.path.join(basedir, fname))
for key in dir(s):
if key.startswith('vol'):
s[key] = vv.Aarray(s[key], s.sampling, s.origin)
elif key.startswith('deform'):
fields = s[key]
s[key] = [
vv.Aarray(field, s.sampling, s.origin) for field in fields
] # origin of volume is added as meta-data
#[vv.Aarray(field, s.sampling, [0,0,0]) for field in fields] would use wrong deform-data when deforming
return s
def __init__(self):
# load font data
path = getResourceDir()
self.s = ssdf.load(os.path.join(path, 'fonts.ssdf'))
# list of fonts
self.fonts = {}
def __init__(self):
# load font data
path = getResourceDir()
self.s = ssdf.load(os.path.join(path, 'fonts.ssdf'))
# list of fonts
self.fonts = {}
def __init__(self, fname=None):
# Store filename
self._fname = fname
# Load
if fname and os.path.exists(fname):
self._db = ssdf.load(fname)
else:
self._db = ssdf.new()
# Key of last added entry
self._lastkey = ''
def load_volume(patnr):
"""
Gives back volume (pixels) and volume properties (sampling and origin)
"""
# tmp = r'C:\Users\Michel\Documents\BMT\Bacheloropdracht\data\croppedAvg7_pat%02i.ssdf'
tmp = r'C:\almar\data\dicom\cropped\croppedReg_pat%02i_gravity.bsdf'
s = ssdf.load(tmp % patnr)
vol = Aarray(s.vol.astype(np.float32), s.sampling, s.origin)
#Save sampling
sampling = s.sampling
origin = s.origin
return vol, sampling, origin
def test_pack1(self):
# Custom stent
g = StentGraph(summary='dit is een stent!', lala=3)
g.add_node((10, 20), foo=3)
g.add_node((30, 40), foo=5)
g.add_edge((1, 1), (2, 2), bar=10)
g.add_edge((10, 20), (1, 1), bar=20)
fname = '/home/almar/test.ssdf'
ssdf.save(fname, g.pack())
g2 = StentGraph()
g2.unpack(ssdf.load(fname))
#print(nx.is_isomorphic(g, g2))
assert nx.is_isomorphic(g, g2)
def makeLandmarkModelDynamic(basedir,
ptcode,
ctcode,
cropname,
what='landmarksavgreg',
savedir=None):
""" Make model dynamic with deforms from registration
(and store/overwrite to disk)
"""
#todo: change in default and merge with branch landmarks?
import pirt
from stentseg.motion.dynamic import (incorporate_motion_nodes,
incorporate_motion_edges)
from visvis import ssdf
import os
if savedir is None:
savedir = basedir
# Load deforms
s = loadvol(basedir, ptcode, ctcode, cropname, 'deforms')
deformkeys = []
for key in dir(s):
if key.startswith('deform'):
deformkeys.append(key)
deforms = [s[key] for key in deformkeys]
deforms = [pirt.DeformationFieldBackward(*fields) for fields in deforms]
paramsreg = s.params
# Load model where landmarks were stored
# s2 = loadmodel(savedir, ptcode, ctcode, cropname, what)
fname = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, what)
s2 = ssdf.load(os.path.join(savedir, fname))
# Turn into graph model
model = stentgraph.StentGraph()
model.unpack(s2[what])
# Combine ...
incorporate_motion_nodes(model, deforms, s2.origin)
incorporate_motion_edges(model, deforms, s2.origin)
# Save back
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, what)
s2.model = model.pack()
s2.paramsreg = paramsreg
ssdf.save(os.path.join(savedir, filename), s2)
print('saved to disk to {}.'.format(os.path.join(savedir, filename)))
def test_pack2(self):
# Auto generate
import random
n = 500
p = dict(
(i, (random.gauss(0, 2), random.gauss(0, 2))) for i in range(n))
g_ = nx.random_geometric_graph(n, 0.1, dim=3, pos=p)
g = StentGraph(summary='dit is een stent!', lala=3)
g.add_nodes_from(g_.nodes_iter())
g.add_edges_from(g_.edges_iter())
fname = '/home/almar/test.ssdf'
ssdf.save(fname, g.pack())
g2 = StentGraph()
g2.unpack(ssdf.load(fname))
#print(nx.is_isomorphic(g, g2))
assert nx.is_isomorphic(g, g2)
def __init__(self):
# Define settings file name
self._fname = os.path.join(appdata_dir('visvis'), 'config.ssdf')
# Init settings
self._s = ssdf.new()
# Load settings if we can
if os.path.exists(self._fname):
try:
self._s = ssdf.load(self._fname)
except Exception:
pass
# Update any missing settings to their defaults
for key in dir(self):
if key.startswith('_'):
continue
self._s[key] = getattr(self, key)
# Save now so the config file contains all settings
self._Save()
def __init__(self):
# Define settings file name
self._fname = os.path.join(appdata_dir('visvis'), 'config.ssdf')
# Init settings
self._s = ssdf.new()
# Load settings if we can
if os.path.exists(self._fname):
try:
self._s = ssdf.load(self._fname)
except Exception:
pass
# Update any missing settings to their defaults
for key in dir(self):
if key.startswith('_'):
continue
self._s[key] = getattr(self, key)
# Save now so the config file contains all settings
self._Save()
def saveaveraged(basedir, ptcode, ctcode, cropname, phases):
""" Step C: Save average of a number of volumes (phases in cardiac cycle)
Load ssdf containing all phases and save averaged volume as new ssdf
"""
filename = '%s_%s_%s_phases.ssdf' % (ptcode, ctcode, cropname)
file_in = os.path.join(basedir, ptcode, filename)
if not os.path.exists(file_in):
raise RuntimeError('Could not find ssdf for given input %s' % ptcode,
ctcode, cropname)
s = ssdf.load(file_in)
s_avg = ssdf.new()
averaged = np.zeros(s.vol0.shape, np.float64)
if phases[1] < phases[0]:
phaserange = list(range(0, 100, 10))
for i in range(phases[1] + 10, phases[0], 10):
phaserange.remove(i)
else:
phaserange = range(phases[0], phases[1] + 10, 10)
for phase in phaserange:
averaged += s['vol%i' % phase]
s_avg['meta%i' % phase] = s['meta%i' % phase]
averaged *= 1.0 / len(phaserange)
averaged = averaged.astype('float32')
s_avg.vol = averaged
s_avg.sampling = s.sampling # z, y, x voxel size in mm
s_avg.origin = s.origin
s_avg.stenttype = s.stenttype
s_avg.croprange = s.croprange
s_avg.ctcode = s.ctcode
s_avg.ptcode = s.ptcode
avg = 'avg' + str(phases[0]) + str(phases[1])
filename = '%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, avg)
file_out = os.path.join(basedir, ptcode, filename)
ssdf.save(file_out, s_avg)
# Visvis is distributed under the terms of the (new) BSD License.
# The full license can be found in 'license.txt'.
import numpy as np
import visvis as vv
import sys
import zlib
import base64
# todo: parameterize; allow custum Gaussian blobs at specified positions.
if False:
# Get data (exported from Matlab)
from visvis import ssdf
db = ssdf.load('d:/almar/projects/peaks.ssdf')
data = db.z.astype(np.float32)
# Dump
data = data.tostring()
data = zlib.compress(data)
text = base64.encodebytes(data)
print(text)
def peaks():
""" peaks()
Returs a 2D map of z-values that represent an example landscape with
Gaussian blobs.
# Copyright (C) 2012, Almar Klein
#
# Visvis is distributed under the terms of the (new) BSD License.
# The full license can be found in 'license.txt'.
import numpy as np
import visvis as vv
import zlib, base64
# todo: parameterize; allow custum Gaussian blobs at specified positions.
if False:
# Get data (exported from Matlab)
from visvis import ssdf
db = ssdf.load('d:/almar/projects/peaks.ssdf')
data = db.z.astype(np.float32)
# Dump
data = data.tostring()
data = zlib.compress(data)
text = base64.encodestring(data)
print(text)
def peaks():
""" peaks()
Returs a 2D map of z-values that represent an example landscape with
Gaussian blobs.
"""
# Create volume (smooth a bit)
if True:
vol0 = vv.aVolume()
vol = vol0.copy() * 0.5
vol[1:, :, :] += 0.3 * vol0[:-1, :, :]
vol[:-1, :, :] += 0.3 * vol0[1:, :, :]
vol[:, 1:, :] += 0.3 * vol0[:, :-1, :]
vol[:, :-1, :] += 0.3 * vol0[:, 1:, :]
vol[:, :, 1:] += 0.3 * vol0[:, :, :-1]
vol[:, :, :-1] += 0.3 * vol0[:, :, 1:]
else:
# My personal test
from visvis import ssdf
s = ssdf.load(
'/home/almar/data/dicom/cropped/croppedReg_pat01_gravity.bsdf')
vol = s.vol
##
# Create figure and make subplots with different renderers
vv.figure(1)
vv.clf()
RS = ['mip', 'iso', 'edgeray', 'ray', 'litray']
a0 = None
tt = []
for i in range(5):
a = vv.subplot(3, 2, i + 2)
t = vv.volshow(vol)
vv.title('Renderstyle ' + RS[i])
t.colormap = vv.CM_HOT #vv.CM_CT1
clim0 = (0,2500)
isoTh = 250
targetdir2 = os.path.join(targetdir1, ptcode)
s = loadvol(basedir2, ptcode, ctcode, cropname, what)
nrs = [1,2,4,5,7,8,10,11,13,14,16,17,19,20,22,23,25,26]
FIG1 = False
## Load all rings of the limb
for i in nrs:
ring = 'ringR%s' %(i)
filename = '%s_%s_%s_%s_%s.ssdf' % (ptcode, ctcode, cropname, 'model'+what,ring)
s["ringR" + str(i)] = ssdf.load(os.path.join(basedir1, filename))
## Visualize centerlines rings
s2 = loadmodel(targetdir2, ptcode, ctcode, cropname, modelname='stentseedsavgreg')
pmodel = points_from_nodes_in_graph(s2.model)
if FIG1 == True:
f = vv.figure(1); vv.clf()
f.position = 709.00, 30.00, 1203.00, 1008.00
a1 = vv.subplot(121)
show_ctvolume(s.vol, None, showVol=showVol, clim=clim0, isoTh=isoTh, removeStent=False)
label = pick3d(vv.gca(), s.vol)
a1.axis.visible = showAxis
a1.daspect = 1,1,-1
a2 = vv.subplot(122)
# Create volume (smooth a bit)
if True:
vol0 = vv.aVolume()
vol = vol0.copy()*0.5
vol[1:,:,:] += 0.3 * vol0[:-1,:,:]
vol[:-1,:,:] += 0.3 * vol0[1:,:,:]
vol[:,1:,:] += 0.3 * vol0[:,:-1,:]
vol[:,:-1,:] += 0.3 * vol0[:,1:,:]
vol[:,:,1:] += 0.3 * vol0[:,:,:-1]
vol[:,:,:-1] += 0.3 * vol0[:,:,1:]
else:
# My personal test
from visvis import ssdf
s = ssdf.load('/home/almar/data/dicom/cropped/croppedReg_pat01_gravity.bsdf')
vol = s.vol
##
# Create figure and make subplots with different renderers
vv.figure(1); vv.clf()
RS = ['mip', 'iso', 'edgeray', 'ray', 'litray']
a0 = None
tt = []
for i in range(5):
a = vv.subplot(3,2,i+2)
t = vv.volshow(vol)
vv.title('Renderstyle ' + RS[i])
t.colormap = vv.CM_HOT #vv.CM_CT1
t.renderStyle = RS[i]