def test_information():
filename = 'test_file.vti'
path = os.path.join(helpers.get_dir(), filename)
info1 = VTKInformation(path)
info2 = VTKInformation(path=path)
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(path)
reader.Update()
info3 = VTKInformation(reader=reader)
assert info1 == info2
assert info1 == info3
with pytest.raises(IOError):
VTKInformation('bad_path')
with pytest.raises(ValueError):
reader = vtk.vtkXMLImageDataReader()
VTKInformation(reader=reader) # No path
with pytest.raises(ValueError):
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName('bad_path')
VTKInformation(reader=reader)
assert info1.dtype == np.int32
assert info1.datatype == vtk.VTK_INT
def loadVisualisations(self):
for tuple in self.d_tuples:
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(tuple[0])
reader.Update()
self.d_window.open_vtk_data(reader.GetOutput())
self.d_window.load_mm(tuple[1])
def main(argv):
#Just get something working for testing...
try:
opts, args = getopt.getopt(argv, "hi:", ["ifile="])
except getopt.GetoptError as err:
print 'tviewer.py -i <inputfile.vtk>'
print(str(err))
for opt, arg in opts:
if opt == '-h':
print 'tviewer.py -i <inputfile.vtk>'
sys.exit()
elif opt in ("-i", "--ifile"):
inputfile = arg
print("Going to load and generate png from ", inputfile)
#Read data
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(inputfile)
reader.Update()
image = reader.GetOutput()
#image.SetSpacing(1,1,1)
#image.GetPointData().SetScalars(image.GetPointData().GetVectors())
#Compute Q Criterion for texture mapping
#Now put this in a png file
castFilter = vtk.vtkImageCast()
castFilter.SetInputData(image)
castFilter.Update()
w = vtk.vtkPNGWriter()
w.SetInputData(castFilter.GetOutput())
w.SetFileName("xyslice.png")
w.Write()
def read_rect_vtu(name):
""" Opens a vtp and returns the vtkUnstructuredGrid class """
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(name)
reader.Update()
ug = reader.GetOutput()
return ug
def ConvertVTItoMatlab(work_dir):
import vtk
import vtk.util.numpy_support as vtkNumPy
import numpy
import scipy.io as scipyio
import os
# echo vtk version info
print "using vtk version", vtk.vtkVersion.GetVTKVersion()
directoryList = os.listdir(work_dir)
files = filter(lambda x:os.path.isfile("%s/%s" % (work_dir,x) ),directoryList)
vtiFiles = filter(lambda x: x.split(".").pop() == "vti" ,files)
filenames = filter(lambda x: x.split(".").pop(0) == "updatefemROI5" ,vtiFiles)
for idlist, fileID in enumerate( filenames):
print "reading %s/%s" % (work_dir,fileID)
vtkReader = vtk.vtkXMLImageDataReader()
vtkReader.SetFileName( "%s/%s" % (work_dir,fileID) )
vtkReader.Update()
imageDataVTK = vtkReader.GetOutput()
dimensions = imageDataVTK.GetDimensions()
spacing = imageDataVTK.GetSpacing()
origin = imageDataVTK.GetOrigin()
print spacing, origin, dimensions
#fem.SetImagingDimensions( dimensions ,origin,spacing)
image_point_data = imageDataVTK.GetPointData()
image_data = vtkNumPy.vtk_to_numpy( image_point_data.GetArray(0) )
# write numpy to disk in matlab
scipyio.savemat("%s/%s.mat" % (work_dir,fileID), {'spacing':spacing, 'origin':origin,'image':image_data})
print "wrote %d of %d" % (idlist, len( filenames))
def __init__(self,offset,get=1,file='data',type='vtu',mirrorPlane=None,silent=0):
self.offset=offset
self.filenameout = file
self.type = type
self.isLoaded = False
self.mirrorPlane=mirrorPlane
self.silent = silent
if type == 'vtu':
self.filename=''.join([self.filenameout,repr(offset).zfill(4),'.vtu'])
self.datareader = v.vtkXMLUnstructuredGridReader()
elif type == 'pvtu':
self.filename=''.join([self.filenameout,repr(offset).zfill(4),'.pvtu'])
self.datareader = v.vtkXMLPUnstructuredGridReader()
elif type == 'vti':
self.filename=''.join([self.filenameout,repr(offset).zfill(4),'.vti'])
self.datareader = v.vtkXMLImageDataReader()
else:
print 'Unknown filetype'
if (self.silent == 0): print '========================================'
if (self.silent == 0): print 'loading file %s' % (self.filename)
if get != None:
self.getAll()
def vti2mat(fileIn, fileOut):
"""Convert voxel-array from VTI to MAT (MATLAB(R)) format.
Parameters
----------
fileIn : str
Path for input VTI file.
fileOut : str
Path for output MAT file.
"""
import numpy as np
import vtk
import scipy.io as sio
from vtk.util import numpy_support as nps
from math_utils import lcmm
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(fileIn)
reader.Update()
vtkImageData = reader.GetOutput()
dim = vtkImageData.GetDimensions()
flatV = nps.vtk_to_numpy(vtkImageData.GetPointData().GetScalars())
V = flatV.reshape(dim[::-1])
spacing = np.array(vtkImageData.GetSpacing())[::-1]
estimatedFactors = lcmm(*spacing) / spacing
estimatedVoxelSize = 1. / estimatedFactors
sio.savemat(fileOut, {'volume':V, 'spacing': spacing, 'estimated_voxel_size': estimatedVoxelSize})
def import_space(filename):
if (not os.path.isfile(filename)):
print("Can't find file: " + filename)
else:
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
reader.GetNumberOfCells()
data = reader.GetOutput()
dim = np.asarray(data.GetDimensions())
x = np.zeros(data.GetNumberOfPoints())
y = x.copy()
z = x.copy()
for i in range(data.GetNumberOfPoints()):
x[i], y[i], z[i] = data.GetPoint(i)
x = x.reshape(dim, order='F')
x = 0.5 * (x[1:, 0, 0] + x[:-1, 0, 0])
y = y.reshape(dim, order='F')
y = 0.5 * (y[0, 1:, 0] + y[0, :-1, 0])
z = z.reshape(dim, order='F')
z = 0.5 * (z[0, 0, 1:] + z[0, 0, :-1])
return x, y, z
def vti_to_numpy(filename, fieldName='density'):
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
# get vtkImageData
imageData = reader.GetOutput()
sr = imageData.GetScalarRange()
print("scalar range {}".format(sr))
# get dimensions tuple
dims = imageData.GetDimensions()
print("dims {}".format(dims))
# get vtk data
vtk_data = imageData.GetPointData().GetArray(fieldName)
# convert to numpy array
numpy_data = numpy_support.vtk_to_numpy(vtk_data)
#numpy_data = numpy_data.reshape(dims[0], dims[1], dims[2])
numpy_data = numpy_data.reshape(dims[1], dims[0])
print("shape in reader {}".format(numpy_data.shape))
#numpy_data = numpy_data.transpose(2,1,0)
return numpy_data
def main():
path = "yC31/"
# the variable name of data array which we used to analyze
daryName = "tev"
files = os.listdir(path)
# declare empty list first, and for every timestep statistics inside.
#for i in range(0, 10):
#for i in range(0, len(files)):
for i in range(74, 75):
filename = path + files[i]
print(filename)
# data reader
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
# specify the data array in the file to process
reader.GetOutput().GetPointData().SetActiveAttribute(daryName, 0)
# convert the data array to numpy array and get the min and maximum value
dary = VN.vtk_to_numpy(
reader.GetOutput().GetPointData().GetScalars(daryName))
dMax = np.amax(dary)
dMin = np.amin(dary)
dstd = np.std(dary)
dsize = np.size(dary)
dRange = dMax - dMin
dMean = np.mean(dary)
dMedian = np.median(dary)
print("Data array median: ", dMedian)
print("Data array mean: ", dMean)
print("Data array std: ", dstd)
print("Data array size: ", dsize)
print("Data array max: ", dMax)
print("Data array min: ", dMin)
print("Data array range: ", dRange)
def __init__(self, vtifname, parallel=False, dtype=np.float64):
if not os.path.isfile(vtifname):
raise FileNotFoundError(vtifname)
if parallel:
self.reader = vtk.vtkXMLPImageDataReader()
else:
self.reader = vtk.vtkXMLImageDataReader()
self.reader.SetFileName(vtifname)
self.reader.Update()
self.data = self.reader.GetOutput()
self.dim = self.data.GetDimensions()
self.trim_0 = [0, 0, 0]
self.trim_1 = [x - 1 for x in self.dim]
self.s_vec = [self.dim[2] - 1, self.dim[1] - 1, self.dim[0] - 1]
if self.dim[2] > 2:
self.subspace = np.meshgrid(
*[range(self.trim_0[i], self.trim_1[i]) for i in range(3)])
self.s_scal = [self.dim[2] - 1, self.dim[1] - 1, self.dim[0] - 1]
else:
self.s_scal = [self.dim[1] - 1, self.dim[0] - 1]
self.subspace = np.meshgrid(
*[range(self.trim_0[i], self.trim_1[i]) for i in range(2)])
self.dtype = dtype
def read(path, name=None):
"""
Read a vti image.
:param path:
Path to file
:param name:
Name or index of array.
If 'name' is None then array at index 0 is returned
:return:
VTKImage instance
"""
if not os.path.exists(path):
raise IOError("No such file or directory: '{}'".format(path))
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(path)
reader.Update()
output = reader.GetOutput()
obj = VTKImage.from_image_data(output, name)
obj.info.path = path
del output
del reader
return obj
def generate(self, input_path, output_directory, part_name):
input_path = work_dir + "/vtk_image/itk_tile_0_2_6.vti"
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(input_path)
reader.Update()
pad_filter = vtk.vtkImageConstantPad()
pad_filter.SetInputConnection(reader.GetOutputPort())
pad_filter.SetConstant(0)
pad_filter.SetOutputWholeExtent(reader.GetOutput().GetExtent()[0]-5,
reader.GetOutput().GetExtent()[1]+5,
reader.GetOutput().GetExtent()[2]-5,
reader.GetOutput().GetExtent()[3]+5,
reader.GetOutput().GetExtent()[4]-5,
reader.GetOutput().GetExtent()[5]+5)
pad_filter.Update()
writer = vtk.vtkXMLImageDataWriter()
writer.SetFileName(work_dir + "/surface/itk_tile_0_2_6_pad.vti")
writer.SetInputConnection(pad_filter.GetOutputPort())
writer.Update()
myArguments = 'vmtklevelsetsegmentation -ifile ' + work_dir + "/surface/itk_tile_0_2_6_pad.vti" + ' -ofile ' + output_path+"/itk_tile_0_2_6_ls.vti"
myPype = pypes.PypeRun(myArguments)
myArguments = 'vmtkmarchingcubes -ifile ' + output_path+"/itk_tile_0_2_6_ls.vti" + ' -ofile ' + output_path+"/itk_tile_0_2_6_model.vtp"
myPype = pypes.PypeRun(myArguments)
def _load_slice(self, q, index, desc):
if not self._volume:
import vtk
dirname = os.path.dirname(self.__dbfilename)
vol_file = os.path.join(dirname, "cinema.vti")
vr = vtk.vtkXMLImageDataReader()
vr.SetFileName(vol_file)
vr.Update()
volume = vr.GetOutput()
self._volume = volume
self._vol_file = vol_file
else:
volume = self._volume
ext = volume.GetExtent()
width = ext[1] - ext[0]
height = ext[3] - ext[2]
from vtk.numpy_interface import dataset_adapter as dsa
image = dsa.WrapDataObject(volume)
oid = volume.ComputePointId([0, 0, index])
nparray = image.PointData[0]
imageslice = np.reshape(nparray[oid:oid + width * height],
(width, height, 3))
doc = store.Document(desc, imageslice)
doc.attributes = None
return doc
def load(file):
datareader = v.vtkXMLImageDataReader()
datareader.SetFileName(file)
datareader.Update()
data = datareader.GetOutput()
return data
def __init__(self, module_manager):
SimpleVTKClassModuleBase.__init__(
self, module_manager,
vtk.vtkXMLImageDataReader(), 'Reading vtkXMLImageData.',
(), ('vtkXMLImageData',),
replaceDoc=True,
inputFunctions=None, outputFunctions=None)
def convert_vtk_file(vtk_file, plt_file, strand=None, solution_time=None):
reader = None
if vtk_file.endswith(".vtu"):
reader = vtk.vtkXMLUnstructuredGridReader()
elif vtk_file.endswith(".vtp"):
reader = vtk.vtkXMLPolyDataReader()
elif vtk_file.endswith(".vts"):
reader = vtk.vtkXMLStructuredGridReader()
elif vtk_file.endswith(".vti"):
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(vtk_file)
reader.Update()
vtk_dataset = reader.GetOutput()
tp.new_layout()
tecplot_dataset = tp.active_frame().dataset
add_vtk_dataset(vtk_dataset, tecplot_dataset)
if tecplot_dataset.num_zones == 0:
print("No zones created.")
return
for z in tecplot_dataset.zones():
z.name = os.path.basename(vtk_file)
if strand and solution_time:
z.strand = strand
z.solution_time = solution_time
tp.data.save_tecplot_plt(plt_file, dataset=tecplot_dataset)
def VTK_import_space(filename):
if(os.path.isfile(filename)):
print('Space',filename)
else:
print('Space',filename + ' not found')
return
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
reader.GetNumberOfCells()
data = reader.GetOutput()
''' Import space '''
dim = np.asarray(data.GetDimensions())
c = np.asarray(data.GetOrigin())
d = np.asarray(data.GetSpacing())
x = np.arange(dim[0])*d[0]+c[0]
y = np.arange(dim[1])*d[1]+c[1]
z = np.arange(dim[2])*d[2]+c[2]
x = 0.5*(x[1:]+x[:-1])
y = 0.5*(y[1:]+y[:-1])
z = 0.5*(z[1:]+z[:-1])
return x,y,z
def VTK_import_array(filename,varname):
if(os.path.isfile(filename)):
print('File',filename,varname)
else:
print('File',filename + ' not found')
return
#varname = filename[:4] + varname
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
reader.GetNumberOfCells()
data = reader.GetOutput()
dim = data.GetDimensions()
cdata = data.GetCellData()
N_comps = cdata.GetNumberOfComponents()
v = vtk_to_numpy(data.GetCellData().GetArray(varname))
vec = [int(i-1) for i in dim]
if(N_comps>1):
vec.append(N_comps)
v = v.reshape(vec,order='F')
return v
def __init__(self,
data_file_name,
scalar_field_name='Scalars_',
max_zoom=2.5,
begin_alpha=0.1,
end_alpha=0.9):
volume_reader = vtk.vtkXMLImageDataReader()
volume_reader.SetFileName(data_file_name)
volume_reader.Update()
volume_data = volume_reader.GetOutput()
volume_data.GetPointData().SetActiveAttribute(scalar_field_name, 0)
self.data_range = volume_data.GetPointData().GetScalars().GetRange()
# default options
self.name = ""
self.min_scalar_value = self.data_range[0]
self.max_scalar_value = self.data_range[1]
self.num_cps = 5
self.num_colors = 5
self.scalar_step = (self.max_scalar_value -
self.min_scalar_value) / (self.num_cps - 1)
self.min_elevation = 5
self.max_elevation = 165
self.max_modes = 5
self.max_zoom = max_zoom
self.tf_res = 256
self.begin_alpha = begin_alpha
self.end_alpha = end_alpha
def processVTI(obj_name):
filename = './' + obj_name + '.vti'
r = vtk.vtkXMLImageDataReader()
r.SetFileName(filename)
r.Update()
data = r.GetOutput()
dim = numpy.asarray(data.GetDimensions())
dim = [dim[0] / 1000.0, dim[1] / 1000.0, dim[2] / 1000.0]
spacing = data.GetSpacing()
spacing = [spacing[0] / 1000.0, spacing[1] / 1000.0, spacing[2] / 1000.0]
#x = numpy.zeros(data.GetNumberOfPoints())
#y = x.copy()
#z = x.copy()
#Can do data.SetOrigin(data.GetOrigin() blah blah blah)
bounds = data.GetBounds()
bounds = numpy.array(bounds) / 1000
extent = data.GetExtent()
pd = data.GetPointData()
a = pd.GetArray(0)
xshape = numpy.array((extent[1], extent[3], extent[5])) - numpy.array(
(extent[0], extent[2], extent[4])) + 1
xshape_rev = xshape[-1::-1]
x = numpy.zeros(xshape_rev, numpy.float32)
for zi in range(xshape[2]):
for yi in range(xshape[1]):
for xi in range(xshape[0]):
idx = zi * xshape[0] * xshape[1] + yi * xshape[0] + xi
x[zi, yi, xi] = a.GetValue(idx) / 1000.0
return x, bounds, extent, spacing
def loadImageData(filename, spacing=()):
"""Read and return a ``vtkImageData`` object from file.
Use ``load`` instead.
E.g. `img = load('myfile.tif').imagedata()`
"""
if ".tif" in filename.lower():
reader = vtk.vtkTIFFReader()
elif ".slc" in filename.lower():
reader = vtk.vtkSLCReader()
if not reader.CanReadFile(filename):
colors.printc("~prohibited Sorry bad slc file " + filename, c=1)
return None
elif ".vti" in filename.lower():
reader = vtk.vtkXMLImageDataReader()
elif ".mhd" in filename.lower():
reader = vtk.vtkMetaImageReader()
elif ".dem" in filename.lower():
reader = vtk.vtkDEMReader()
elif ".nii" in filename.lower():
reader = vtk.vtkNIFTIImageReader()
elif ".nrrd" in filename.lower():
reader = vtk.vtkNrrdReader()
if not reader.CanReadFile(filename):
colors.printc("~prohibited Sorry bad nrrd file " + filename, c=1)
return None
reader.SetFileName(filename)
reader.Update()
image = reader.GetOutput()
if len(spacing) == 3:
image.SetSpacing(spacing[0], spacing[1], spacing[2])
return image
def getReader(self):
reader = None;
if self.srcFormat == "vti":
reader = vtk.vtkXMLImageDataReader();
reader.SetFileName(self.src);
reader.Update();
return reader;
def readDataset(filePath):
# load dataset
# reader = vtk.vtkDatasetReader()
# reader.SetFileName(filePath)
# reader.Update()
## print reader.GetOutput()
# if reader.GetOutput() == None:
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filePath)
reader.Update()
reader.GetOutput().GetPointData().RemoveArray("ProcessId")
reader.GetOutput().GetPointData().RemoveArray("vtkValidPointMask")
reader.GetOutput().GetPointData().RemoveArray("vtkGhostType")
# print reader.GetOutput().GetPointData()
# print reader.GetOutput().GetBounds()
bounds = numpy.zeros(6)
reader.GetOutput().GetBounds(bounds)
# print( 'bounds={0}'.format( bounds ))
dimension = 3
if abs(bounds[5] - bounds[4]) < 1e-5:
dimension = 2
if reader.GetOutput().GetSpacing()[2] == 0:
reader.GetOutput().SetSpacing(reader.GetOutput().GetSpacing()[0],
reader.GetOutput().GetSpacing()[1],
1)
return (reader.GetOutput(), bounds, dimension)
def ConvertVTKMatlab(input_filename,output_filename):
import vtk.util.numpy_support as vtkNumPy
import numpy
import scipy.io as scipyio
extension = input_filename.split('.').pop()
vtkReader = None
if extension == 'vtk':
vtkReader = vtk.vtkDataSetReader()
elif extension == 'vti':
vtkReader = vtk.vtkXMLImageDataReader()
else:
raise RuntimeError('unknown file type %s ' % input_filename)
vtkReader.SetFileName( "%s" % (input_filename) )
vtkReader.Update()
imageDataVTK = vtkReader.GetOutput()
dimensions = imageDataVTK.GetDimensions()
spacing = imageDataVTK.GetSpacing()
origin = imageDataVTK.GetOrigin()
print spacing, origin, dimensions
#fem.SetImagingDimensions( dimensions ,origin,spacing)
image_point_data = imageDataVTK.GetPointData()
image_data = vtkNumPy.vtk_to_numpy( image_point_data.GetArray(0) )
# write numpy to disk in matlab
# indexing is painful.... reshape to dimensions and transpose 2d dimensions only
scipyio.savemat( output_filename, {'spacing':spacing, 'origin':origin,'image':image_data.reshape(dimensions,order='F').transpose(1,0,2)})
def load(file):
datareader = v.vtkXMLImageDataReader()
datareader.SetFileName(file)
datareader.Update()
data = datareader.GetOutput()
return data
def main():
path = "yC31/"
# the variable name of data array which we used to analyze
daryName = "v03"
files = os.listdir(path)
#for i in range(0, 10):
for i in range(0, len(files)):
filename = path + files[i]
print(filename)
# data reader
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
# specify the data array in the file to process
reader.GetOutput().GetPointData().SetActiveAttribute(daryName, 0)
# convert the data array to numpy array and get the min and maximum value
dary = VN.vtk_to_numpy(
reader.GetOutput().GetPointData().GetScalars(daryName))
plt.hist(dary, color="blue", bins=20)
titlename = "Histogram of v03 timestep " + files[i][22:27]
plt.title(titlename)
savefilename = "plots/hists/v03_t_" + files[i][22:27] + ".png"
plt.savefig(savefilename)
'''
def test_XDMF_shape(self, tmp_path, single_phase):
os.chdir(tmp_path)
single_phase.export_XDMF()
fname = os.path.splitext(os.path.basename(
single_phase.fname))[0] + '.xdmf'
reader_xdmf = vtk.vtkXdmfReader()
reader_xdmf.SetFileName(fname)
reader_xdmf.Update()
dim_xdmf = reader_xdmf.GetOutput().GetDimensions()
bounds_xdmf = reader_xdmf.GetOutput().GetBounds()
single_phase.view('increments', 0).export_VTK()
fname = os.path.splitext(os.path.basename(
single_phase.fname))[0] + '_inc00.vti'
for i in range(10): # waiting for parallel IO
reader_vti = vtk.vtkXMLImageDataReader()
reader_vti.SetFileName(fname)
reader_vti.Update()
dim_vti = reader_vti.GetOutput().GetDimensions()
bounds_vti = reader_vti.GetOutput().GetBounds()
if dim_vti == dim_xdmf and bounds_vti == bounds_xdmf:
return
time.sleep(.5)
assert False
def main(argv):
#Just get something working for testing...
try:
opts, args = getopt.getopt(argv,"hi:", ["ifile="])
except getopt.GetoptError as err:
print 'tviewer.py -i <inputfile.vtk>'
print (str(err))
for opt, arg in opts:
if opt == '-h':
print 'tviewer.py -i <inputfile.vtk>'
sys.exit()
elif opt in ("-i", "--ifile"):
inputfile = arg
print("Going to load and generate png from ", inputfile)
#Read data
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(inputfile)
reader.Update()
image = reader.GetOutput()
#image.SetSpacing(1,1,1)
#image.GetPointData().SetScalars(image.GetPointData().GetVectors())
#Compute Q Criterion for texture mapping
#Now put this in a png file
castFilter = vtk.vtkImageCast()
castFilter.SetInputData(image)
castFilter.Update()
w = vtk.vtkPNGWriter()
w.SetInputData(castFilter.GetOutput())
w.SetFileName("xyslice.png")
w.Write()
def main():
colors = vtk.vtkNamedColors()
file_name = get_program_parameters()
# Read the source file.
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(file_name)
# Create the mapper that creates graphics elements
mapper = vtk.vtkDataSetMapper()
mapper.SetInputConnection(reader.GetOutputPort())
# Create the Actor
actor = vtk.vtkActor()
actor.SetMapper(mapper)
# show the edges of the image grid
actor.GetProperty().SetRepresentationToWireframe()
actor.GetProperty().SetColor(colors.GetColor3d("DarkSalmon"))
# Create the Renderer
renderer = vtk.vtkRenderer()
renderer.AddActor(actor)
renderer.ResetCamera()
renderer.SetBackground(colors.GetColor3d("Silver"))
# Create the RendererWindow
renderer_window = vtk.vtkRenderWindow()
renderer_window.AddRenderer(renderer)
# Create the RendererWindowInteractor and display the vti file
interactor = vtk.vtkRenderWindowInteractor()
interactor.SetRenderWindow(renderer_window)
interactor.Initialize()
interactor.Start()
def loadVisualisations(self):
for tuple in self.d_tuples:
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(tuple[0])
reader.Update()
self.d_window.open_vtk_data(reader.GetOutput())
self.d_window.load_mm(tuple[1])
def main(args):
IMAGE_FILENAME = args.image_data
THRESHOLD = args.t
DATA_FILENAME = args.data
if not os.path.exists('./TEST_DATA'):
os.mkdir('TEST_DATA')
#Read vti file
ref = vtk.vtkXMLImageDataReader()
ref.SetFileName(IMAGE_FILENAME)
ref.Update()
#Read your data into another polydata variable for reading
image = vtk.vtkPolyData()
image = ref.GetOutput()
global vprint
if args.v:
def vprint(*args):
# Print each argument separately so caller doesn't need to
# stuff everything to be printed into a single string
for arg in args:
print(arg),
else:
vprint = lambda *a: None
heart = read_polydata(args.heart)
#determinePerfusionVolumesMask(image,heart,args.t)
#centerlines = ['LAD_CAR_004_centerlines.vtp','LCX_CAR_004_centerlines.vtp','RCA_CAR_004_centerlines.vtp']
#centerline_dict = {'LAD_CAR_004_centerlines':0,'LCX_CAR_004_centerlines':1,'RCA_CAR_004_centerlines':2}
#centerlines = ['RCA_CAR_004_centerlines.vtp']
centerline_dir = 'TEST_DATA'
centerlines = [
'LCA_adult_mouse_centerlines.vtp', 'RSA_adult_mouse_centerlines.vtp',
'RCA_adult_mouse_centerlines.vtp'
]
centerline_dict = {
'LCA_adult_mouse_centerlines': 0,
'RCA_adult_mouse_centerlines': 1,
'RSA_adult_mouse_centerlines': 2
}
vtk_centerline_data = dict()
for i in centerlines:
if not os.path.isfile('./' + 'heart_' + i.split('.')[0] + '.vtu'):
cap_center_coordinates = calculateCapCenters(caps)
centerline = intializeVTP(os.path.join(centerline_dir, i), vprint)
coords = getCoords(centerline)
weights = getWeights(centerline, option=0)
volumes = determineCenterlinePerfusionVolumes(
coords, weights, heart, 'heart_' + i.split('.')[0] + '.vtu')
centerline_heart = intializeVTU('heart_' + i.split('.')[0] + '.vtu',
vprint)
vtk_centerline_data[i.split(
'.')[0]] = centerline_heart.GetPointData().GetArray('distance_map')
if len(vtk_centerline_data) == len(centerlines):
markTerritories(heart, vtk_centerline_data, centerline_dict)
write_polydata(heart, args.vtu_data)
def test():
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName("C:/Users/Asus/Dropbox/2017-18/ScientificCompAndVisualization/Semana2/SS_2017-master/SS_2017-master/data/wind_image.vti")
volume = vtk.vtkVolume()
#mapper = vtk.vtkFixedPointVolumeRayCastMapper()
mapper = vtk.vtkGPUVolumeRayCastMapper()
mapper.SetBlendModeToMinimumIntensity();
mapper.SetSampleDistance(0.1)
mapper.SetAutoAdjustSampleDistances(0)
ren = vtk.vtkRenderer()
renWin = vtk.vtkRenderWindow()
iRen = vtk.vtkRenderWindowInteractor()
# Set connections
mapper.SetInputConnection(reader.GetOutputPort());
volume.SetMapper(mapper)
ren.AddViewProp(volume)
renWin.AddRenderer(ren)
iRen.SetRenderWindow(renWin)
# Define opacity transfer function and color functions
opacityTransferFunction = vtk.vtkPiecewiseFunction()
opacityTransferFunction.AddPoint(0.1, 1.0)
opacityTransferFunction.AddPoint(14, 0.5)
# Create transfer mapping scalar value to color
colorTransferFunction = vtk.vtkColorTransferFunction()
colorTransferFunction.AddRGBPoint(1.5, 1.0, 1.0, 0.0)
colorTransferFunction.AddRGBPoint(0.5, 1.0, 0.0, 0.0)
colorTransferFunction.AddRGBPoint(3.0, 0.0, 1.0, 0.0)
colorTransferFunction.AddRGBPoint(6.0, 0.0, 1.0, 1.0)
colorTransferFunction.AddRGBPoint(14.0, 0.0, 0.0, 1.0)
# Now set the opacity and the color
volumeProperty = vtk.vtkVolumeProperty()
volumeProperty.SetColor(colorTransferFunction)
volumeProperty.SetScalarOpacity(opacityTransferFunction)
volumeProperty.ShadeOff()
volumeProperty.SetInterpolationTypeToLinear()
volume.SetProperty(volumeProperty)
renderer = vtk.vtkRenderer()
renderer.SetBackground(0.5, 0.5, 0.5)
renderer.AddVolume(volume)
renderer.ResetCamera()
renderWindow = vtk.vtkRenderWindow()
renderWindow.AddRenderer(renderer)
renderWindow.SetSize(500, 500)
renderWindow.Render()
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(renderWindow)
iren.Start()
def _load_slice(self, q, index, desc):
if not self._volume:
import vtk
dirname = os.path.dirname(self.__dbfilename)
vol_file = os.path.join(dirname, "cinema.vti")
vr = vtk.vtkXMLImageDataReader()
vr.SetFileName(vol_file)
vr.Update()
volume = vr.GetOutput()
self._volume = volume
self._vol_file = vol_file
else:
volume = self._volume
ext = volume.GetExtent()
width = ext[1]-ext[0]
height = ext[3]-ext[2]
from vtk.numpy_interface import dataset_adapter as dsa
image = dsa.WrapDataObject(volume)
oid = volume.ComputePointId([0, 0, index])
nparray = image.PointData[0]
imageslice = np.reshape(nparray[oid:oid+width*height], (width,height,3))
doc = Document(desc, imageslice)
doc.attributes = None
return doc
def vti_to_numpy(filename, fieldName='density'):
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
# get vtkImageData
imageData = reader.GetOutput()
sr = imageData.GetScalarRange()
print("scalar range {}".format(sr))
# get dimensions tuple
dims = imageData.GetDimensions()
print("dims {}".format(dims))
# get vtk data
vtk_data = imageData.GetPointData().GetArray(fieldName)
# convert to numpy array
numpy_data = numpy_support.vtk_to_numpy(vtk_data)
#numpy_data = numpy_data.reshape(dims[0], dims[1], dims[2])
numpy_data = numpy_data.reshape(dims[1], dims[0])
print("shape in reader {}".format(numpy_data.shape))
#numpy_data = numpy_data.transpose(2,1,0)
return numpy_data
def ConvertVTKMatlab(input_filename, output_filename):
import vtk.util.numpy_support as vtkNumPy
import numpy
import scipy.io as scipyio
extension = input_filename.split('.').pop()
vtkReader = None
if extension == 'vtk':
vtkReader = vtk.vtkDataSetReader()
elif extension == 'vti':
vtkReader = vtk.vtkXMLImageDataReader()
else:
raise RuntimeError('unknown file type %s ' % input_filename)
vtkReader.SetFileName("%s" % (input_filename))
vtkReader.Update()
imageDataVTK = vtkReader.GetOutput()
dimensions = imageDataVTK.GetDimensions()
spacing = imageDataVTK.GetSpacing()
origin = imageDataVTK.GetOrigin()
print spacing, origin, dimensions
#fem.SetImagingDimensions( dimensions ,origin,spacing)
image_point_data = imageDataVTK.GetPointData()
image_data = vtkNumPy.vtk_to_numpy(image_point_data.GetArray(0))
# write numpy to disk in matlab
# indexing is painful.... reshape to dimensions and transpose 2d dimensions only
scipyio.savemat(
output_filename, {
'spacing': spacing,
'origin': origin,
'image': image_data.reshape(dimensions, order='F').transpose(
1, 0, 2)
})
def test_image_data(field_data, compression_fixture, format_fixture,
ordering_fixture):
coords, r, e_r, field, order = field_data
dim = r.ndim
f = io.StringIO()
compress = compression_fixture.param
format = format_fixture.param
with ImageData(f, [(min(x), max(x)) for x in coords],
[x.size for x in coords],
compression=compress,
byte_order=order) as fh:
fh.addPointData(DataArray(r, range(dim), 'point',
ordering_fixture.param),
vtk_format=format).addCellData(
DataArray(e_r, range(dim), 'cell',
ordering_fixture.param),
vtk_format=format).addFieldData(DataArray(
field, [0], 'field', ordering_fixture.param),
vtk_format=format)
reader = vtkXMLImageDataReader()
vtk_r, vtk_e_r, vtk_f = get_vtk_data(reader, f)
vtk_r = vtk_r.reshape(r.shape, order='F')
vtk_e_r = vtk_e_r.reshape(e_r.shape, order='F') \
.transpose(ordering_fixture.transp(dim))
assert all(vtk_r == r)
assert all(vtk_e_r == e_r)
assert all(vtk_f == field)
def load_image_to_nifty(fn):
"""
This function imports image file as vtk image.
Args:
fn: filename of the image data
Return:
label: label map as a vtk image
"""
import SimpleITK as sitk
ext = fn.split(os.extsep)[-1]
if ext == 'vti':
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(fn)
reader.Update()
label_vtk = reader.GetOutput()
size = label_vtk.GetDimensions()
py_arr = np.reshape(vtk_to_numpy(
label_vtk.GetPointData().GetScalars()),
tuple(size),
order='F')
label = sitk.GetImageFromArray(py_arr.transpose(2, 1, 0))
label.SetOrigin(label_vtk.GetOrigin())
label.SetSpacing(label_vtk.GetSpacing())
label.SetDirection(np.eye(3).ravel())
elif ext == 'nii' or ext == 'nii.gz':
label = sitk.ReadImage(fn)
else:
raise IOError("File extension is not recognized: ", ext)
return label
def vti2mat(fileIn, fileOut):
"""Convert voxel-array from VTI to MAT (MATLAB(R)) format.
Parameters
----------
fileIn : str
Path for input VTI file.
fileOut : str
Path for output MAT file.
"""
import numpy as np
import vtk
import scipy.io as sio
from vtk.util import numpy_support as nps
from math_utils import lcmm
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(fileIn)
reader.Update()
vtkImageData = reader.GetOutput()
dim = vtkImageData.GetDimensions()
flatV = nps.vtk_to_numpy(vtkImageData.GetPointData().GetScalars())
V = flatV.reshape(dim[::-1])
spacing = np.array(vtkImageData.GetSpacing())[::-1]
estimatedFactors = lcmm(*spacing) / spacing
estimatedVoxelSize = 1. / estimatedFactors
sio.savemat(
fileOut, {
'volume': V,
'spacing': spacing,
'estimated_voxel_size': estimatedVoxelSize
})
def from_vti(cls, fname, idx=0):
"""
Get data and metadata from a VTK file.
Assumes gprMax 'material' array has index 0.
"""
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(fname)
reader.Update()
output = reader.GetOutput()
dx_dy_dz = reader.GetOutput().GetSpacing()
arr = cls._get_vti_array(output, 0)
pml = (cls._get_vti_array(output, 1) == 1).astype(int)
npml = np.where(pml[:, pml.shape[1]//2] == 0)[0][0]
# Squeeze out the last dim if it's really a 2D model.
if arr.shape[-1] == 1:
arr = arr.squeeze()
dx, dz, dy = dx_dy_dz # Careful! gprMax y is vertical (depth).
params = {'dx_dy_dz': (dx, dy, dz),
'dx': dx,
'dz': dz,
'npml': npml,
'domain': 'depth',
}
return cls(arr, params)
def ReadVTKXMLImageFile(self):
if (self.InputFileName == ''):
self.PrintError('Error: no InputFileName.')
self.PrintLog('Reading VTK XML image file.')
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(self.InputFileName)
reader.Update()
self.Image = reader.GetOutput()
def __init__(self, vtifname, parallel=False):
self.reader = vtk.vtkXMLImageDataReader()
self.reader.SetFileName(vtifname)
self.reader.Update()
self.data = self.reader.GetOutput()
self.dim = self.data.GetDimensions()
self.s_scal = [self.dim[1]-1, self.dim[0]-1]
self.s_vec = [self.dim[1]-1, self.dim[0]-1,3]
def Import(filename):
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
# TODO: Check if the code bellow is necessary
reader.WholeSlicesOn()
reader.Update()
return reader.GetOutput()
def GetImageDataForBaseAndExtension(self, fileName, extension):
"""
:type fileName: basestring
:type extension: basestring
:rtype: vtkImageData
"""
if extension == DataReader.TypeMHA or extension == DataReader.TypeMHD:
# Use a vktMetaImageReader
imageReader = vtkMetaImageReader()
imageReader.SetFileName(fileName)
imageReader.Update()
return imageReader.GetOutput()
elif extension == DataReader.TypeDICOM:
# Use a dicom reader
dirName = os.path.dirname(fileName)
return self.GetImageDataFromDirectory(dirName)
elif extension == DataReader.TypeDAT:
raise Exception("Support for .dat files is not implemented.")
# Read in the .dat file byte by byte
imageData = None
import numpy as np
with open(fileName, "rb") as f:
dimensions = np.fromfile(f, np.int16, count=3)
imageData = vtkImageData()
imageData.SetDimensions(int(dimensions[0]), int(dimensions[1]), int(dimensions[2]))
imageData.SetScalarTypeToFloat()
imageData.SetNumberOfScalarComponents(1)
imageData.AllocateScalars()
imageData.Update()
imageData.PrepareForNewData()
fileData = np.fromfile(f, np.int16)
dataIndex = 0
for z in range(int(dimensions[2])):
for y in range(int(dimensions[1])):
for x in range(int(dimensions[0])):
imageData.SetScalarComponentFromFloat(x, y, z, 0, float(fileData[dataIndex]))
dataIndex += 1
return imageData
elif extension == DataReader.TypeVTI:
# Use a XMLImageReader
imageReader = vtkXMLImageDataReader()
imageReader.SetFileName(fileName)
imageReader.Update()
return imageReader.GetOutput()
elif extension == DataReader.TypeNRRD:
# Use a NrrdReader
imageReader = vtkNrrdReader()
imageReader.SetFileName(fileName)
imageReader.Update()
return imageReader.GetOutput()
else:
assert False
def load_image_data(handle):
"""
Load vtkImageData from XML file.
:param handle: file name
:type handle: str
"""
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(handle)
return reader.GetOutput()
def multi_con_h2(filename):
# Creating contour for h2 fileld
data = vtk.vtkXMLImageDataReader()
data.SetFileName(filename)#"/Users/y1275963/Documents/homework/multifield.0060.vti")
data.Update()
#Getting highest value
[low,high] = data.GetOutput().GetPointData().GetArray("H2").GetRange()
data_h2 = vtk.vtkAssignAttribute()
data_h2.SetInputConnection(data.GetOutputPort())
data_h2.Assign('H2','SCALARS','POINT_DATA')
# Create a filter to extract an isosurface from
# the dataset. Connect the input of this
# filter to the output of the reader. Set the
# value for the (one) isosurface that we want
# to extract, and tell the filter to compute
# normal vectors for each triangle on the
# output isosurface.
iso = vtk.vtkContourFilter()
iso.SetInputConnection(data_h2.GetOutputPort())
iso.ComputeNormalsOn()
iso.SetNumberOfContours(10)
for i in range(10):
iso.SetValue(i, (1.0-0.1*i)*high) #Chnge here to change the isovalue
# Create a mapper to traverse the polydata and
# generate graphics commands for drawing the
# polygons onto the output device.
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputConnection(iso.GetOutputPort())
mapper.ScalarVisibilityOff()
# Output primitives (i.e. the triangles making
# up the isosurface) are managed as an actor;
# we specify that all outputs are coloured
# red.
actor = vtk.vtkActor()
actor.SetMapper(mapper)
actor.GetProperty().SetColor(0, 0, 1)
actor.GetProperty().SetOpacity(0.3)
# Create a renderer which will output the
# graphics commands onto a drawing surface within
# a window. By default the renderer will fill
# all of the window. We set the background
# colour of the window to white.
return actor
def vtkKWHeaderAnnotationEditorEntryPoint(parent, win):
app = parent.GetApplication()
# -----------------------------------------------------------------------
# Create a render widget
# Set the header annotation visibility and set some text
hae_renderwidget = vtkKWRenderWidget()
hae_renderwidget.SetParent(parent)
hae_renderwidget.Create()
hae_renderwidget.HeaderAnnotationVisibilityOn()
hae_renderwidget.SetHeaderAnnotationText("Hello, World!")
app.Script("pack %s -side right -fill both -expand y -padx 0 -pady 0",
hae_renderwidget.GetWidgetName())
# -----------------------------------------------------------------------
# Create a volume reader
hae_reader = vtkXMLImageDataReader()
hae_reader.SetFileName(os.path.join(
os.path.dirname(os.path.abspath(__file__)),
"..", "..", "..", "..", "Data", "head100x100x47.vti"))
# Create an image viewer
# Use the render window and renderer of the renderwidget
hae_viewer = vtkImageViewer2()
hae_viewer.SetRenderWindow(hae_renderwidget.GetRenderWindow())
hae_viewer.SetRenderer(hae_renderwidget.GetRenderer())
hae_viewer.SetInput(hae_reader.GetOutput())
hae_viewer.SetupInteractor(
hae_renderwidget.GetRenderWindow().GetInteractor())
hae_renderwidget.ResetCamera()
# -----------------------------------------------------------------------
# Create a header annotation editor
# Connect it to the render widget
hae_anno_editor = vtkKWHeaderAnnotationEditor()
hae_anno_editor.SetParent(parent)
hae_anno_editor.Create()
hae_anno_editor.SetRenderWidget(hae_renderwidget)
app.Script("pack %s -side left -anchor nw -expand n -padx 2 -pady 2",
hae_anno_editor.GetWidgetName())
return "TypeVTK"
def GetNumPyData(filename): print filename vtiReader = vtk.vtkXMLImageDataReader() vtiReader.SetFileName(filename) vtiReader.Update() vtiData = vtk.vtkImageCast() vtiData.SetOutputScalarTypeToDouble() vtiData.SetInput( vtiReader.GetOutput() ) vtiData.Update( ) vti_image = vtiData.GetOutput().GetPointData() vti_array = vtkNumPy.vtk_to_numpy(vti_image.GetArray(0)) return vti_array
def vti_to_nparray(fname):
r = vtk.vtkXMLImageDataReader()
r.SetFileName(fname)
r.Update()
o = r.GetOutput()
x, y, z = o.GetDimensions()
m = numpy_support.vtk_to_numpy(o.GetPointData().GetScalars())
m.shape = (z, y, x)
m[:] = (m > 127) * 1
return m, o.GetSpacing()
def _load_data_from_file(self, file_path):
"""Loads scanvolume data from file. Also sets the volume as input for the sliceviewers
"""
#self.frame.SetStatusText("Opening file: %s..." % (file_path))
filename = os.path.split(file_path)[1]
fileBaseName = os.path.splitext(filename)[0]
self.frame._set_filename(filename)
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(file_path)
reader.Update()
self.set_input(0, reader.GetOutput())
def __init__(self,offset,get=1,file='data',mirrorPlane=None,silent=0):
self.offset=offset
self.filenameout = file
self.isLoaded = False
self.mirrorPlane=mirrorPlane
self.silent = silent
self.filename=''.join([self.filenameout,repr(offset).zfill(4),'.vti'])
self.datareader = v.vtkXMLImageDataReader()
if (self.silent == 0): print '========================================'
if (self.silent == 0): print 'loading file %s' % (self.filename)
if get != None:
self.getAll()
def test_vtk_exceptions(self):
"""Test if VTK has been patched with our VTK error to Python exception
patch.
"""
import vtk
a = vtk.vtkXMLImageDataReader()
a.SetFileName('blata22 hello')
b = vtk.vtkMarchingCubes()
b.SetInput(a.GetOutput())
try:
b.Update()
except RuntimeError, e:
self.failUnless(str(e).startswith('ERROR'))
def reader_vti(filename):
logging.debug("In data.reader_vti()")
append = vtk.vtkImageAppend()
append.ReleaseDataFlagOn()
append.SetAppendAxis(2)
reader = vtk.vtkXMLImageDataReader()
reader.ReleaseDataFlagOn()
if os.path.exists(filename):
reader.SetFileName(filename)
# reader.GetOutput().Register(reader)
reader.Update()
return vtk.vtkImageData.SafeDownCast(reader.GetOutput())
else:
i = 0
paths = []
while True:
partName = filename.replace(".vti", "{0}.vti".format(i))
# print partName
if os.path.exists(partName):
paths.append(partName)
else:
break
i = i + 1
# paths.reverse()
for i, partName in enumerate(paths):
reader = vtk.vtkXMLImageDataReader()
reader.ReleaseDataFlagOn()
reader.SetFileName(partName)
# reader.GetOutput().Register(reader)
reader.Update()
append.SetInput(i, reader.GetOutput())
append.Update()
output = append.GetOutput()
for i in range(append.GetNumberOfInputs()):
append.GetInput(i).ReleaseData()
return output
def __init__(self, vtifname, parallel=False, dtype=np.float64):
if parallel:
self.reader = vtk.vtkXMLPImageDataReader()
else:
self.reader = vtk.vtkXMLImageDataReader()
self.reader.SetFileName(vtifname)
self.reader.Update()
self.data = self.reader.GetOutput()
self.dim = self.data.GetDimensions()
self.s_scal = [self.dim[2]-1, self.dim[1]-1, self.dim[0]-1]
self.s_vec = [self.dim[2]-1, self.dim[1]-1, self.dim[0]-1,3]
self.trim_0 = [0,0,0]
self.trim_1 = [x-1 for x in self.dim]
self.dtype = dtype
def loadVti(self, filename):
"""
Loads the specified DataSet from disk and returns
it as vtkImageData
@param filename The file where Dataset is loaded from
"""
if not self.reader or self.filename != filename:
self.filename = filename
self.reader = vtk.vtkXMLImageDataReader()
self.reader.AddObserver("ProgressEvent", lib.messenger.send)
lib.messenger.connect(self.reader, 'ProgressEvent', self.updateProgress)
filepath = os.path.join(self.path, filename)
if not self.reader.CanReadFile(filepath):
Logging.error("Cannot read file",
"Cannot read XML Image Data File %s"%filename)
self.reader.SetFileName(filepath)
self.updateProgress(None, None)
data = self.reader.GetOutput()
return data
def to_h5(fname, outname):
r = vtk.vtkXMLImageDataReader()
r.SetFileName(fname)
r.Update()
o = r.GetOutput()
x, y, z = o.GetDimensions()
m = numpy_support.vtk_to_numpy(o.GetPointData().GetScalars())
m.shape = (z, y, x)
# m[m>0] = 1
print m.dtype, m.shape
mh5 = h5py.File(outname, 'w')
mh5.create_dataset('spacing', data=o.GetSpacing());
mh5.create_dataset('data', shape=m.shape, dtype=m.dtype)
d = mh5['data']
d[:] = m
mh5.flush()
mh5.close()
def vti2arr(fileIn):
"""Convert voxel-array from VTI to Numpy 3D image array.
Parameters
----------
fileIn : str
Path for input VTI file.
fileOut : str
Path for output MAT file.
Returns
-------
V : np.ndarray
Lx x Ly x Lz 3D array, representing the voxel-array.
metadata : dict
Dict containing metadata about voxel array:
- 'spacing': array of voxel dimensions (pixel/mm)
"""
import numpy as np
import vtk
from vtk.util import numpy_support as nps
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(fileIn)
reader.Update()
vtkImageData = reader.GetOutput()
dim = vtkImageData.GetDimensions()
flatV = nps.vtk_to_numpy(vtkImageData.GetPointData().GetScalars())
V = flatV.reshape(dim[::-1])
#V = flatV.reshape(dim)
metadata = {}
spacing = np.array(vtkImageData.GetSpacing())[::-1]
#spacing = np.array(vtkImageData.GetSpacing())
metadata['spacing'] = spacing
return V, metadata
def readImage(
filename,
verbose=1):
myVTK.myPrint(verbose, "*** readImage: " + filename + " ***")
if ('vtk' in filename):
image_reader = vtk.vtkImageDataReader()
elif ('vti' in filename):
image_reader = vtk.vtkXMLImageDataReader()
else:
assert 0, "File must be .vtk or .vti. Aborting."
image_reader.SetFileName(filename)
image_reader.Update()
image = image_reader.GetOutput()
if (verbose):
print "n_points = " + str(image.GetNumberOfPoints())
return image
def readImage(
filename,
verbose=0):
myVTK.myPrint(verbose, "*** readImage: "+filename+" ***")
assert (os.path.isfile(filename)), "Wrong filename (\""+filename+"\"). Aborting."
if ('vtk' in filename):
image_reader = vtk.vtkImageDataReader()
elif ('vti' in filename):
image_reader = vtk.vtkXMLImageDataReader()
else:
assert 0, "File must be .vtk or .vti. Aborting."
image_reader.SetFileName(filename)
image_reader.Update()
image = image_reader.GetOutput()
myVTK.myPrint(verbose-1, "n_points = "+str(image.GetNumberOfPoints()))
return image
