def __init__(self, obj=None):
vtk.vtkImageActor.__init__(self)
Base3DProp.__init__(self)
if utils.isSequence(obj) and len(obj):
iac = vtk.vtkImageAppendComponents()
nchan = obj.shape[
2] # get number of channels in inputimage (L/LA/RGB/RGBA)
for i in range(nchan):
#arr = np.flip(np.flip(array[:,:,i], 0), 0).ravel()
arr = np.flip(obj[:, :, i], 0).ravel()
varb = numpy_to_vtk(arr,
deep=True,
array_type=vtk.VTK_UNSIGNED_CHAR)
imgb = vtk.vtkImageData()
imgb.SetDimensions(obj.shape[1], obj.shape[0], 1)
imgb.GetPointData().SetScalars(varb)
iac.AddInputData(0, imgb)
iac.Update()
img = iac.GetOutput()
self.SetInputData(img)
elif isinstance(obj, vtk.vtkImageData):
self.SetInputData(obj)
img = obj
elif isinstance(obj, str):
if "https://" in obj:
import vedo.io as io
obj = io.download(obj, verbose=False)
if ".png" in obj:
picr = vtk.vtkPNGReader()
elif ".jpg" in obj or ".jpeg" in obj:
picr = vtk.vtkJPEGReader()
elif ".bmp" in obj:
picr = vtk.vtkBMPReader()
elif ".tif" in obj:
picr = vtk.vtkTIFFReader()
else:
colors.printc("Cannot understand picture format", obj, c='r')
return
picr.SetFileName(obj)
self.filename = obj
picr.Update()
img = picr.GetOutput()
self.SetInputData(img)
else:
img = vtk.vtkImageData()
self.SetInputData(img)
self._data = img
sx, sy, _ = img.GetDimensions()
self.shape = np.array([sx, sy])
self._mapper = self.GetMapper()
def __init__(
self,
inputobj=None,
c=('r', 'y', 'lg', 'lb', 'b'), #('b','lb','lg','y','r')
alpha=(0.5, 1),
alphaUnit=1,
mapper='tetra',
):
BaseGrid.__init__(self)
self.useArray = 0
inputtype = str(type(inputobj))
#printc('TetMesh inputtype', inputtype)
###################
if inputobj is None:
self._data = vtk.vtkUnstructuredGrid()
elif isinstance(inputobj, vtk.vtkUnstructuredGrid):
self._data = inputobj
elif isinstance(inputobj, vtk.vtkRectilinearGrid):
r2t = vtk.vtkRectilinearGridToTetrahedra()
r2t.SetInputData(inputobj)
r2t.RememberVoxelIdOn()
r2t.SetTetraPerCellTo6()
r2t.Update()
self._data = r2t.GetOutput()
elif isinstance(inputobj, vtk.vtkDataSet):
r2t = vtk.vtkDataSetTriangleFilter()
r2t.SetInputData(inputobj)
#r2t.TetrahedraOnlyOn()
r2t.Update()
self._data = r2t.GetOutput()
elif isinstance(inputobj, str):
from vedo.io import download, loadUnStructuredGrid
if "https://" in inputobj:
inputobj = download(inputobj, verbose=False)
ug = loadUnStructuredGrid(inputobj)
tt = vtk.vtkDataSetTriangleFilter()
tt.SetInputData(ug)
tt.SetTetrahedraOnly(True)
tt.Update()
self._data = tt.GetOutput()
elif utils.isSequence(inputobj):
# if "ndarray" not in inputtype:
# inputobj = np.array(inputobj)
self._data = self._buildtetugrid(inputobj[0], inputobj[1])
###################
if 'tetra' in mapper:
self._mapper = vtk.vtkProjectedTetrahedraMapper()
elif 'ray' in mapper:
self._mapper = vtk.vtkUnstructuredGridVolumeRayCastMapper()
elif 'zs' in mapper:
self._mapper = vtk.vtkUnstructuredGridVolumeZSweepMapper()
elif isinstance(mapper, vtk.vtkMapper):
self._mapper = mapper
else:
printc('Unknown mapper type', [mapper], c='r')
raise RuntimeError()
self._mapper.SetInputData(self._data)
self.SetMapper(self._mapper)
self.color(c).alpha(alpha)
if alphaUnit:
self.GetProperty().SetScalarOpacityUnitDistance(alphaUnit)
# remember stuff:
self._color = c
self._alpha = alpha
self._alphaUnit = alphaUnit
def __init__(
self,
inputobj=None,
c='RdBu_r',
alpha=(0.0, 0.0, 0.2, 0.4, 0.8, 1.0),
alphaGradient=None,
alphaUnit=1,
mode=0,
shade=False,
spacing=None,
dims=None,
origin=None,
mapper='smart',
):
vtk.vtkVolume.__init__(self)
BaseGrid.__init__(self)
###################
if isinstance(inputobj, str):
if "https://" in inputobj:
from vedo.io import download
inputobj = download(inputobj, verbose=False) # fpath
elif os.path.isfile(inputobj):
pass
else:
inputobj = sorted(glob.glob(inputobj))
###################
if 'gpu' in mapper:
self._mapper = vtk.vtkGPUVolumeRayCastMapper()
elif 'opengl_gpu' in mapper:
self._mapper = vtk.vtkOpenGLGPUVolumeRayCastMapper()
elif 'smart' in mapper:
self._mapper = vtk.vtkSmartVolumeMapper()
elif 'fixed' in mapper:
self._mapper = vtk.vtkFixedPointVolumeRayCastMapper()
elif isinstance(mapper, vtk.vtkMapper):
self._mapper = mapper
else:
print("Error unknown mapper type", [mapper])
raise RuntimeError()
self.SetMapper(self._mapper)
###################
inputtype = str(type(inputobj))
#colors.printc('Volume inputtype', inputtype)
if inputobj is None:
img = vtk.vtkImageData()
elif utils.isSequence(inputobj):
if isinstance(inputobj[0], str): # scan sequence of BMP files
ima = vtk.vtkImageAppend()
ima.SetAppendAxis(2)
pb = utils.ProgressBar(0, len(inputobj))
for i in pb.range():
f = inputobj[i]
picr = vtk.vtkBMPReader()
picr.SetFileName(f)
picr.Update()
mgf = vtk.vtkImageMagnitude()
mgf.SetInputData(picr.GetOutput())
mgf.Update()
ima.AddInputData(mgf.GetOutput())
pb.print('loading...')
ima.Update()
img = ima.GetOutput()
else:
if "ndarray" not in inputtype:
inputobj = np.array(inputobj)
if len(inputobj.shape) == 1:
varr = numpy_to_vtk(inputobj,
deep=True,
array_type=vtk.VTK_FLOAT)
else:
if len(inputobj.shape) > 2:
inputobj = np.transpose(inputobj, axes=[2, 1, 0])
varr = numpy_to_vtk(inputobj.ravel(order='F'),
deep=True,
array_type=vtk.VTK_FLOAT)
varr.SetName('input_scalars')
img = vtk.vtkImageData()
if dims is not None:
img.SetDimensions(dims)
else:
if len(inputobj.shape) == 1:
colors.printc(
"Error: must set dimensions (dims keyword) in Volume.",
c='r')
raise RuntimeError()
img.SetDimensions(inputobj.shape)
img.GetPointData().SetScalars(varr)
#to convert rgb to numpy
# img_scalar = data.GetPointData().GetScalars()
# dims = data.GetDimensions()
# n_comp = img_scalar.GetNumberOfComponents()
# temp = numpy_support.vtk_to_numpy(img_scalar)
# numpy_data = temp.reshape(dims[1],dims[0],n_comp)
# numpy_data = numpy_data.transpose(0,1,2)
# numpy_data = np.flipud(numpy_data)
elif "ImageData" in inputtype:
img = inputobj
elif isinstance(inputobj, Volume):
img = inputobj.inputdata()
elif "UniformGrid" in inputtype:
img = inputobj
elif hasattr(
inputobj,
"GetOutput"): # passing vtk object, try extract imagdedata
if hasattr(inputobj, "Update"):
inputobj.Update()
img = inputobj.GetOutput()
elif isinstance(inputobj, str):
from vedo.io import loadImageData, download
if "https://" in inputobj:
inputobj = download(inputobj, verbose=False)
img = loadImageData(inputobj)
else:
colors.printc("Volume(): cannot understand input type:\n",
inputtype,
c='r')
return
if dims is not None:
img.SetDimensions(dims)
if origin is not None:
img.SetOrigin(origin) ### DIFFERENT from volume.origin()!
if spacing is not None:
img.SetSpacing(spacing)
self._data = img
self._mapper.SetInputData(img)
self.mode(mode).color(c).alpha(alpha).alphaGradient(alphaGradient)
self.GetProperty().SetShade(True)
self.GetProperty().SetInterpolationType(1)
self.GetProperty().SetScalarOpacityUnitDistance(alphaUnit)
# remember stuff:
self._mode = mode
self._color = c
self._alpha = alpha
self._alphaGrad = alphaGradient
self._alphaUnit = alphaUnit
def __init__(
self,
inputobj=None,
):
vtk.vtkActor.__init__(self)
BaseGrid.__init__(self)
inputtype = str(type(inputobj))
self._data = None
self._polydata = None
###################
if inputobj is None:
self._data = vtk.vtkUnstructuredGrid()
# elif utils.isSequence(inputobj):pass # TODO
elif "UnstructuredGrid" in inputtype:
self._data = inputobj
elif isinstance(inputobj, str):
from vedo.io import download, loadUnStructuredGrid
if "https://" in inputobj:
inputobj = download(inputobj)
self._data = loadUnStructuredGrid(inputobj)
else:
colors.printc("UGrid(): cannot understand input type:\n",
inputtype,
c=1)
return
self._mapper = vtk.vtkPolyDataMapper()
self._mapper.SetInterpolateScalarsBeforeMapping(
settings.interpolateScalarsBeforeMapping)
if settings.usePolygonOffset:
self._mapper.SetResolveCoincidentTopologyToPolygonOffset()
pof, pou = settings.polygonOffsetFactor, settings.polygonOffsetUnits
self._mapper.SetResolveCoincidentTopologyPolygonOffsetParameters(
pof, pou)
self.GetProperty().SetInterpolationToFlat()
if not self._data:
return
sf = vtk.vtkShrinkFilter()
sf.SetInputData(self._data)
sf.SetShrinkFactor(1.0)
sf.Update()
gf = vtk.vtkGeometryFilter()
gf.SetInputData(sf.GetOutput())
gf.Update()
self._polydata = gf.GetOutput()
self._mapper.SetInputData(self._polydata)
sc = None
if self.useCells:
sc = self._polydata.GetCellData().GetScalars()
else:
sc = self._polydata.GetPointData().GetScalars()
if sc:
self._mapper.SetScalarRange(sc.GetRange())
self.SetMapper(self._mapper)
def __init__(self, inputobj=None):
vtk.vtkActor.__init__(self)
BaseGrid.__init__(self)
inputtype = str(type(inputobj))
self._data = None
self._polydata = None
self.name = "UGrid"
###################
if inputobj is None:
self._data = vtk.vtkUnstructuredGrid()
elif utils.isSequence(inputobj):
pts, cells, celltypes = inputobj
self._data = vtk.vtkUnstructuredGrid()
if not utils.isSequence(cells[0]):
tets = []
nf = cells[0] + 1
for i, cl in enumerate(cells):
if i == nf or i == 0:
k = i + 1
nf = cl + k
cell = [cells[j + k] for j in range(cl)]
tets.append(cell)
cells = tets
# This would fill the points and use those to define orientation
vpts = utils.numpy2vtk(pts, dtype=float)
points = vtk.vtkPoints()
points.SetData(vpts)
self._data.SetPoints(points)
# This fill the points and use cells to define orientation
# points = vtk.vtkPoints()
# for c in cells:
# for pid in c:
# points.InsertNextPoint(pts[pid])
# self._data.SetPoints(points)
# Fill cells
# https://vtk.org/doc/nightly/html/vtkCellType_8h_source.html
for i, ct in enumerate(celltypes):
cell_conn = cells[i]
if ct == vtk.VTK_HEXAHEDRON:
cell = vtk.vtkHexahedron()
elif ct == vtk.VTK_TETRA:
cell = vtk.vtkTetra()
elif ct == vtk.VTK_VOXEL:
cell = vtk.vtkVoxel()
elif ct == vtk.VTK_WEDGE:
cell = vtk.vtkWedge()
elif ct == vtk.VTK_PYRAMID:
cell = vtk.vtkPyramid()
elif ct == vtk.VTK_HEXAGONAL_PRISM:
cell = vtk.vtkHexagonalPrism()
elif ct == vtk.VTK_PENTAGONAL_PRISM:
cell = vtk.vtkPentagonalPrism()
else:
print("UGrid: cell type", ct, "not implemented. Skip.")
continue
cpids = cell.GetPointIds()
for j, pid in enumerate(cell_conn):
cpids.SetId(j, pid)
self._data.InsertNextCell(ct, cpids)
elif "UnstructuredGrid" in inputtype:
self._data = inputobj
elif isinstance(inputobj, str):
from vedo.io import download, loadUnStructuredGrid
if "https://" in inputobj:
inputobj = download(inputobj, verbose=False)
self._data = loadUnStructuredGrid(inputobj)
self.filename = inputobj
else:
colors.printc("UGrid(): cannot understand input type:\n",
inputtype,
c='r')
return
# self._mapper = vtk.vtkDataSetMapper()
self._mapper = vtk.vtkPolyDataMapper()
self._mapper.SetInterpolateScalarsBeforeMapping(
settings.interpolateScalarsBeforeMapping)
if settings.usePolygonOffset:
self._mapper.SetResolveCoincidentTopologyToPolygonOffset()
pof, pou = settings.polygonOffsetFactor, settings.polygonOffsetUnits
self._mapper.SetResolveCoincidentTopologyPolygonOffsetParameters(
pof, pou)
self.GetProperty().SetInterpolationToFlat()
if not self._data:
return
# now fill the representation of the vtk unstr grid
sf = vtk.vtkShrinkFilter()
sf.SetInputData(self._data)
sf.SetShrinkFactor(1.0)
sf.Update()
gf = vtk.vtkGeometryFilter()
gf.SetInputData(sf.GetOutput())
gf.Update()
self._polydata = gf.GetOutput()
self._mapper.SetInputData(self._polydata)
sc = None
if self.useCells:
sc = self._polydata.GetCellData().GetScalars()
else:
sc = self._polydata.GetPointData().GetScalars()
if sc:
self._mapper.SetScalarRange(sc.GetRange())
self.SetMapper(self._mapper)
self.property = self.GetProperty()
def __init__(self, inputobj=None):
vtk.vtkImageSlice.__init__(self)
Base3DProp.__init__(self)
BaseVolume.__init__(self)
self._mapper = vtk.vtkImageResliceMapper()
self._mapper.SliceFacesCameraOn()
self._mapper.SliceAtFocalPointOn()
self._mapper.SetAutoAdjustImageQuality(False)
self._mapper.BorderOff()
self.lut = None
self.property = vtk.vtkImageProperty()
self.property.SetInterpolationTypeToLinear()
self.SetProperty(self.property)
###################
if isinstance(inputobj, str):
if "https://" in inputobj:
from vedo.io import download
inputobj = download(inputobj, verbose=False) # fpath
elif os.path.isfile(inputobj):
pass
else:
inputobj = sorted(glob.glob(inputobj))
###################
inputtype = str(type(inputobj))
if inputobj is None:
img = vtk.vtkImageData()
if isinstance(inputobj, Volume):
img = inputobj.imagedata()
self.lut = utils.ctf2lut(inputobj)
elif utils.isSequence(inputobj):
if isinstance(inputobj[0], str): # scan sequence of BMP files
ima = vtk.vtkImageAppend()
ima.SetAppendAxis(2)
pb = utils.ProgressBar(0, len(inputobj))
for i in pb.range():
f = inputobj[i]
picr = vtk.vtkBMPReader()
picr.SetFileName(f)
picr.Update()
mgf = vtk.vtkImageMagnitude()
mgf.SetInputData(picr.GetOutput())
mgf.Update()
ima.AddInputData(mgf.GetOutput())
pb.print('loading...')
ima.Update()
img = ima.GetOutput()
else:
if "ndarray" not in inputtype:
inputobj = np.array(inputobj)
if len(inputobj.shape) == 1:
varr = utils.numpy2vtk(inputobj, dtype=float)
else:
if len(inputobj.shape) > 2:
inputobj = np.transpose(inputobj, axes=[2, 1, 0])
varr = utils.numpy2vtk(inputobj.ravel(order='F'),
dtype=float)
varr.SetName('input_scalars')
img = vtk.vtkImageData()
img.SetDimensions(inputobj.shape)
img.GetPointData().AddArray(varr)
img.GetPointData().SetActiveScalars(varr.GetName())
elif "ImageData" in inputtype:
img = inputobj
elif isinstance(inputobj, Volume):
img = inputobj.inputdata()
elif "UniformGrid" in inputtype:
img = inputobj
elif hasattr(
inputobj,
"GetOutput"): # passing vtk object, try extract imagdedata
if hasattr(inputobj, "Update"):
inputobj.Update()
img = inputobj.GetOutput()
elif isinstance(inputobj, str):
from vedo.io import loadImageData, download
if "https://" in inputobj:
inputobj = download(inputobj, verbose=False)
img = loadImageData(inputobj)
else:
colors.printc("VolumeSlice: cannot understand input type:\n",
inputtype,
c='r')
return
self._data = img
self._mapper.SetInputData(img)
self.SetMapper(self._mapper)
