def _scalar_data_changed(self, data):
img_data = self.image_data
if data is None:
img_data.point_data.scalars = None
self.data_changed = True
return
dims = list(data.shape)
if len(dims) == 2:
dims.append(1)
img_data.origin = tuple(self.origin)
img_data.dimensions = tuple(dims)
img_data.extent = 0, dims[0]-1, 0, dims[1]-1, 0, dims[2]-1
img_data.update_extent = 0, dims[0]-1, 0, dims[1]-1, 0, dims[2]-1
if self.transpose_input_array:
img_data.point_data.scalars = numpy.ravel(numpy.transpose(data))
else:
img_data.point_data.scalars = numpy.ravel(data)
img_data.point_data.scalars.name = self.scalar_name
# This is very important and if not done can lead to a segfault!
typecode = data.dtype
img_data.scalar_type = array_handler.get_vtk_array_type(typecode)
img_data.update() # This sets up the extents correctly.
img_data.update_traits()
self.change_information_filter.update()
# Now flush the mayavi pipeline.
self.data_changed = True
def _scalar_data_changed(self, data):
img_data = self.image_data
if data is None:
img_data.point_data.scalars = None
self.data_changed = True
return
dims = list(data.shape)
if len(dims) == 2:
dims.append(1)
img_data.origin = tuple(self.origin)
img_data.dimensions = tuple(dims)
img_data.extent = 0, dims[0]-1, 0, dims[1]-1, 0, dims[2]-1
img_data.update_extent = 0, dims[0]-1, 0, dims[1]-1, 0, dims[2]-1
if self.transpose_input_array:
img_data.point_data.scalars = numpy.ravel(numpy.transpose(data))
else:
img_data.point_data.scalars = numpy.ravel(data)
img_data.point_data.scalars.name = self.scalar_name
# This is very important and if not done can lead to a segfault!
typecode = data.dtype
img_data.scalar_type = array_handler.get_vtk_array_type(typecode)
img_data.update() # This sets up the extents correctly.
img_data.update_traits()
# Now flush the mayavi pipeline.
self.data_changed = True
def _change_primary_scalars(self, arr, name):
"""
Parameters
----------
arr: ndarray, shape (Nx, Ny, Nz, 4)
If this is going in as primary scalars, it is definitely an RGBA
vector array provided by a BlendedImages. Therefore is needs to
be reshaped to C-order (Nz, Ny, Nx, 4)
name: str
array label
"""
pd = self.data.point_data
if pd.scalars is not None \
and pd.scalars.size != arr.size:
#self.flush_arrays(update=False)
self.safe_remove_arrays()
rgba = quick_convert_rgba_to_vtk(arr)
xyz_shape = rgba.shape[:3]
flat_shape = (np.prod(xyz_shape), 4)
dataset = self.data
# set the ImageData metadata
dataset.origin = self.blender.img_origin
dataset.spacing = self.blender.img_spacing
dataset.dimensions = xyz_shape[::-1]
dataset.extent = 0, xyz_shape[2]-1, 0, xyz_shape[1]-1, 0, xyz_shape[0]-1
dataset.update_extent = dataset.extent
dataset.number_of_scalar_components = 4
dataset.scalar_type = get_vtk_array_type(arr.dtype)
# set the scalars and name
self.set_new_array(rgba, name, update=False)
## pd.scalars = rgba.reshape(flat_shape)
## pd.scalars.name = name
dataset.update()
dataset.update_traits()
self._check_aa()
self._update_data()
self._push_changes()
self.point_scalars_name = name
def _scalar_data_changed(self, data):
img_data = self.image_data
if data is None:
img_data.point_data.scalars = None
self.data_changed = True
return
is_rgba_bytes = (data.dtype.char=='B' and data.shape[-1]==4)
dims = list(data.shape[:-1]) if is_rgba_bytes else list(data.shape)
if len(dims) == 2:
dims.append(1)
img_data.origin = tuple(self.origin)
flat_shape = ( np.prod(dims), )
if is_rgba_bytes:
flat_shape += (4,)
if self.transpose_input_array:
if is_rgba_bytes:
# keep the color components in the last dimension
d = data.transpose(2,1,0,3).copy()
d.shape = flat_shape
img_data.point_data.scalars = d
else:
img_data.point_data.scalars = np.ravel(np.transpose(data))
img_data.dimensions = tuple(dims)
img_data.extent = 0, dims[0]-1, 0, dims[1]-1, 0, dims[2]-1
img_data.update_extent = 0, dims[0]-1, 0, dims[1]-1, 0, dims[2]-1
else:
img_data.point_data.scalars = data.reshape(flat_shape)
img_data.dimensions = tuple(dims[::-1])
img_data.extent = 0, dims[2]-1, 0, dims[1]-1, 0, dims[0]-1
img_data.update_extent = 0, dims[2]-1, 0, dims[1]-1, 0, dims[0]-1
img_data.number_of_scalar_components = 4 if is_rgba_bytes else 1
img_data.point_data.scalars.name = self.scalar_name
# This is very important and if not done can lead to a segfault!
typecode = data.dtype
img_data.scalar_type = get_vtk_array_type(typecode)
img_data.update() # This sets up the extents correctly.
img_data.update_traits()
self.change_information_filter.update()
# Now flush the mayavi pipeline.
self.data_changed = True
# Make the tvtk dataset.
spoints = tvtk.StructuredPoints(origin=origin,
spacing=spacing,
dimensions=dims)
# The copy makes the data contiguous and the transpose makes it
# suitable for display via tvtk. Note that it is not necessary to
# make the data contiguous since in that case the array is copied
# internally.
s = scalars.transpose().copy()
spoints.point_data.scalars = ravel(s)
spoints.point_data.scalars.name = 'scalars'
# This is needed in slightly older versions of VTK (like the 5.0.2
# release) to prevent a segfault. VTK does not detect the correct
# data type.
spoints.scalar_type = get_vtk_array_type(s.dtype)
# Uncomment the next two lines to save the dataset to a VTK XML file.
#w = tvtk.XMLImageDataWriter(input=spoints, file_name='spoints3d.vti')
#w.write()
# Now view the data.
@mayavi2.standalone
def view():
from enthought.mayavi.sources.vtk_data_source import VTKDataSource
from enthought.mayavi.modules.outline import Outline
from enthought.mayavi.modules.image_plane_widget import ImagePlaneWidget
mayavi2.new_scene()
src = VTKDataSource(data=spoints)
# Make the tvtk dataset.
spoints = tvtk.StructuredPoints(origin=origin, spacing=spacing,
dimensions=dims)
# The copy makes the data contiguous and the transpose makes it
# suitable for display via tvtk. Note that it is not necessary to
# make the data contiguous since in that case the array is copied
# internally.
s = scalars.transpose().copy()
spoints.point_data.scalars = ravel(s)
spoints.point_data.scalars.name = 'scalars'
# This is needed in slightly older versions of VTK (like the 5.0.2
# release) to prevent a segfault. VTK does not detect the correct
# data type.
spoints.scalar_type = get_vtk_array_type(s.dtype)
# Uncomment the next two lines to save the dataset to a VTK XML file.
#w = tvtk.XMLImageDataWriter(input=spoints, file_name='spoints3d.vti')
#w.write()
# Now view the data.
@mayavi2.standalone
def view():
from enthought.mayavi.sources.vtk_data_source import VTKDataSource
from enthought.mayavi.modules.outline import Outline
from enthought.mayavi.modules.image_plane_widget import ImagePlaneWidget
mayavi.new_scene()
src = VTKDataSource(data = spoints)
mayavi.add_source(src)
