"""This module provides classes that allow Numpy-type access
to VTK datasets and arrays. This is best described with some examples.
To normalize a VTK array:
from vtkmodules.vtkImagingCore vtkRTAnalyticSource
import vtkmodules.numpy_interface.dataset_adapter as dsa
import vtkmodules.numpy_interface.algorithms as algs
rt = vtkRTAnalyticSource()
rt.Update()
image = dsa.WrapDataObject(rt.GetOutput())
rtdata = image.PointData['RTData']
rtmin = algs.min(rtdata)
rtmax = algs.max(rtdata)
rtnorm = (rtdata - rtmin) / (rtmax - rtmin)
image.PointData.append(rtnorm, 'RTData - normalized')
print image.GetPointData().GetArray('RTData - normalized').GetRange()
To calculate gradient:
grad= algs.gradient(rtnorm)
To access subsets:
>>> grad[0:10]
VTKArray([[ 0.10729134, 0.03763443, 0.03136338],
[ 0.02754352, 0.03886006, 0.032589 ],
[ 0.02248248, 0.04127144, 0.03500038],
[ 0.02678365, 0.04357527, 0.03730421],
[ 0.01765099, 0.04571581, 0.03944477],
[ 0.02344007, 0.04763837, 0.04136734],
[ 0.01089381, 0.04929155, 0.04302051],
[ 0.01769151, 0.05062952, 0.04435848],
[ 0.002764 , 0.05161414, 0.04534309],
[ 0.01010841, 0.05221677, 0.04594573]])
>>> grad[:, 0]
VTKArray([ 0.10729134, 0.02754352, 0.02248248, ..., -0.02748174,
-0.02410045, 0.05509736])
All of this functionality is also supported for composite datasets
even though their data arrays may be spread across multiple datasets.
We have implemented a VTKCompositeDataArray class that handles many
Numpy style operators and is supported by all algorithms in the
algorithms module.
This module also provides an API to access composite datasets.
For example:
from vtkmodules.vtkCommonDataModel import vtkMultiBlockDataSet
mb = vtkMultiBlockDataSet()
mb.SetBlock(0, image.VTKObject)
mb.SetBlock(1e, image.VTKObject)
cds = dsa.WrapDataObject(mb)
for block in cds:
print block
Note that this module implements only the wrappers for datasets
and arrays. The classes implement many useful operators. However,
to make best use of these classes, take a look at the algorithms
module.
"""
try:
import numpy
except ImportError:
raise RuntimeError("This module depends on the numpy module. Please make\
sure that it is installed properly.")
import itertools
import operator
import sys
from ..vtkCommonCore import buffer_shared
from ..util import numpy_support
from ..vtkCommonDataModel import vtkDataObject
from ..vtkCommonCore import vtkWeakReference
import weakref
if sys.hexversion < 0x03000000:
izip = itertools.izip
else:
izip = zip
def reshape_append_ones (a1, a2):
"""Returns a list with the two arguments, any of them may be
processed. If the arguments are numpy.ndarrays, append 1s to the
shape of the array with the smallest number of dimensions until
the arrays have the same number of dimensions. Does nothing if the
arguments are not ndarrays or the arrays have the same number of
dimensions.
"""
l = [a1, a2]
if (isinstance(a1, numpy.ndarray) and isinstance(a2, numpy.ndarray)):
len1 = len(a1.shape)
len2 = len(a2.shape)
if (len1 == len2 or len1 == 0 or len2 == 0 or
a1.shape[0] != a2.shape[0]):
return l;
elif (len1 < len2):
d = len1
maxLength = len2
i = 0
else:
d = len2
maxLength = len1
i = 1
while (d < maxLength):
l[i] = numpy.expand_dims(l[i], d)
d = d + 1
return l
class ArrayAssociation :
"""Easy access to vtkDataObject.AttributeTypes"""
POINT = vtkDataObject.POINT
CELL = vtkDataObject.CELL
FIELD = vtkDataObject.FIELD
ROW = vtkDataObject.ROW
class VTKObjectWrapper(object):
"""Superclass for classes that wrap VTK objects with Python objects.
This class holds a reference to the wrapped VTK object. It also
forwards unresolved methods to the underlying object by overloading
__get__attr."""
def __init__(self, vtkobject):
self.VTKObject = vtkobject
def __getattr__(self, name):
"Forwards unknown attribute requests to VTK object."
return getattr(self.VTKObject, name)
def vtkDataArrayToVTKArray(array, dataset=None):
"Given a vtkDataArray and a dataset owning it, returns a VTKArray."
narray = numpy_support.vtk_to_numpy(array)
# Make arrays of 9 components into matrices. Also transpose
# as VTK store matrices in Fortran order
shape = narray.shape
if len(shape) == 2 and shape[1] == 9:
narray = narray.reshape((shape[0], 3, 3)).transpose(0, 2, 1)
return VTKArray(narray, array=array, dataset=dataset)
def numpyTovtkDataArray(array, name="numpy_array", array_type=None):
"""Given a numpy array or a VTKArray and a name, returns a vtkDataArray.
The resulting vtkDataArray will store a reference to the numpy array:
the numpy array is released only when the vtkDataArray is destroyed."""
vtkarray = numpy_support.numpy_to_vtk(array, array_type=array_type)
vtkarray.SetName(name)
return vtkarray
def _make_tensor_array_contiguous(array):
if array is None:
return None
if array.flags.contiguous:
return array
array = numpy.asarray(array)
size = array.dtype.itemsize
strides = array.strides
if len(strides) == 3 and strides[1]/size == 1 and strides[2]/size == 3:
return array.transpose(0, 2, 1)
return array
def _metaclass(mcs):
"""For compatibility between python 2 and python 3."""
def decorator(cls):
body = vars(cls).copy()
body.pop('__dict__', None)
body.pop('__weakref__', None)
return mcs(cls.__name__, cls.__bases__, body)
return decorator
class VTKArrayMetaClass(type):
def __new__(mcs, name, parent, attr):
"""We overwrite numerical/comparison operators because we might need
to reshape one of the arrays to perform the operation without
broadcast errors. For instance:
An array G of shape (n,3) resulted from computing the
gradient on a scalar array S of shape (n,) cannot be added together without
reshaping.
G + expand_dims(S,1) works,
G + S gives an error:
ValueError: operands could not be broadcast together with shapes (n,3) (n,)
This metaclass overwrites operators such that it computes this
reshape operation automatically by appending 1s to the
dimensions of the array with fewer dimensions.
"""
def add_numeric_op(attr_name):
"""Create an attribute named attr_name that calls
_numeric_op(self, other, op)."""
def closure(self, other):
return VTKArray._numeric_op(self, other, attr_name)
closure.__name__ = attr_name
attr[attr_name] = closure
def add_default_numeric_op(op_name):
"""Adds '__[op_name]__' attribute that uses operator.[op_name]"""
add_numeric_op("__%s__"%op_name)
def add_reverse_numeric_op(attr_name):
"""Create an attribute named attr_name that calls
_reverse_numeric_op(self, other, op)."""
def closure(self, other):
return VTKArray._reverse_numeric_op(self, other, attr_name)
closure.__name__ = attr_name
attr[attr_name] = closure
def add_default_reverse_numeric_op(op_name):
"""Adds '__r[op_name]__' attribute that uses operator.[op_name]"""
add_reverse_numeric_op("__r%s__"%op_name)
def add_default_numeric_ops(op_name):
"""Call both add_default_numeric_op and add_default_reverse_numeric_op."""
add_default_numeric_op(op_name)
add_default_reverse_numeric_op(op_name)
add_default_numeric_ops("add")
add_default_numeric_ops("sub")
add_default_numeric_ops("mul")
if sys.hexversion < 0x03000000:
add_default_numeric_ops("div")
add_default_numeric_ops("truediv")
add_default_numeric_ops("floordiv")
add_default_numeric_ops("mod")
add_default_numeric_ops("pow")
add_default_numeric_ops("lshift")
add_default_numeric_ops("rshift")
add_numeric_op("and")
add_default_numeric_ops("xor")
add_numeric_op("or")
add_default_numeric_op("lt")
add_default_numeric_op("le")
add_default_numeric_op("eq")
add_default_numeric_op("ne")
add_default_numeric_op("ge")
add_default_numeric_op("gt")
return type.__new__(mcs, name, parent, attr)
@_metaclass(VTKArrayMetaClass)
class VTKArray(numpy.ndarray):
"""This is a sub-class of numpy ndarray that stores a
reference to a vtk array as well as the owning dataset.
The numpy array and vtk array should point to the same
memory location."""
def _numeric_op(self, other, attr_name):
"""Used to implement numpy-style numerical operations such as __add__,
__mul__, etc."""
l = reshape_append_ones(self, other)
return getattr(numpy.ndarray, attr_name)(l[0], l[1])
def _reverse_numeric_op(self, other, attr_name):
"""Used to implement numpy-style numerical operations such as __add__,
__mul__, etc."""
l = reshape_append_ones(self, other)
return getattr(numpy.ndarray, attr_name)(l[0], l[1])
def __new__(cls, input_array, array=None, dataset=None):
# Input array is an already formed ndarray instance
# We first cast to be our class type
obj = numpy.asarray(input_array).view(cls)
obj.Association = ArrayAssociation.FIELD
# add the new attributes to the created instance
obj.VTKObject = array
if dataset:
obj._dataset = vtkWeakReference()
obj._dataset.Set(dataset.VTKObject)
# Finally, we must return the newly created object:
return obj
def __array_finalize__(self,obj):
# Copy the VTK array only if the two share data
slf = _make_tensor_array_contiguous(self)
obj2 = _make_tensor_array_contiguous(obj)
self.VTKObject = None
try:
# This line tells us that they are referring to the same buffer.
# Much like two pointers referring to same memory location in C/C++.
if buffer_shared(slf, obj2):
self.VTKObject = getattr(obj, 'VTKObject', None)
except TypeError:
pass
self.Association = getattr(obj, 'Association', None)
self.DataSet = getattr(obj, 'DataSet', None)
def __getattr__(self, name):
"Forwards unknown attribute requests to VTK array."
try:
o = self.__dict__["VTKObject"]
except KeyError:
o = None
if o is None:
raise AttributeError("'%s' object has no attribute '%s'" %
(self.__class__.__name__, name))
return getattr(o, name)
def __array_wrap__(self, out_arr, context=None):
if out_arr.shape == ():
# Convert to scalar value
return out_arr[()]
else:
return numpy.ndarray.__array_wrap__(self, out_arr, context)
@property
def DataSet(self):
"""
Get the dataset this array is associated with. The reference to the
dataset is held through a vtkWeakReference to ensure it doesn't prevent
the dataset from being collected if necessary.
"""
if hasattr(self, '_dataset') and self._dataset and self._dataset.Get():
return WrapDataObject(self._dataset.Get())
return None
@DataSet.setter
def DataSet(self, dataset):
"""
Set the dataset this array is associated with. The reference is held
through a vtkWeakReference.
"""
# Do we have dataset to store
if dataset and dataset.VTKObject:
# Do we need to create a vtkWeakReference
if not hasattr(self, '_dataset') or self._dataset is None:
self._dataset = vtkWeakReference()
self._dataset.Set(dataset.VTKObject)
else:
self._dataset = None
class VTKNoneArrayMetaClass(type):
def __new__(mcs, name, parent, attr):
"""Simplify the implementation of the numeric/logical sequence API."""
def _add_op(attr_name, op):
"""Create an attribute named attr_name that calls
_numeric_op(self, other, op)."""
def closure(self, other):
return VTKNoneArray._op(self, other, op)
closure.__name__ = attr_name
attr[attr_name] = closure
def _add_default_reverse_op(op_name):
"""Adds '__r[op_name]__' attribute that uses operator.[op_name]"""
_add_op("__r%s__"%op_name, getattr(operator, op_name))
def _add_default_op(op_name):
"""Adds '__[op_name]__' attribute that uses operator.[op_name]"""
_add_op("__%s__"%op_name, getattr(operator, op_name))
def _add_default_ops(op_name):
"""Call both add_default_numeric_op and add_default_reverse_numeric_op."""
_add_default_op(op_name)
_add_default_reverse_op(op_name)
_add_default_ops("add")
_add_default_ops("sub")
_add_default_ops("mul")
if sys.hexversion < 0x03000000:
_add_default_ops("div")
_add_default_ops("truediv")
_add_default_ops("floordiv")
_add_default_ops("mod")
_add_default_ops("pow")
_add_default_ops("lshift")
_add_default_ops("rshift")
_add_op("__and__", operator.and_)
_add_op("__rand__", operator.and_)
_add_default_ops("xor")
_add_op("__or__", operator.or_)
_add_op("__ror__", operator.or_)
_add_default_op("lt")
_add_default_op("le")
_add_default_op("eq")
_add_default_op("ne")
_add_default_op("ge")
_add_default_op("gt")
return type.__new__(mcs, name, parent, attr)
@_metaclass(VTKNoneArrayMetaClass)
class VTKNoneArray(object):
"""VTKNoneArray is used to represent a "void" array. An instance
of this class (NoneArray) is returned instead of None when an
array that doesn't exist in a DataSetAttributes is requested.
All operations on the NoneArray return NoneArray. The main reason
for this is to support operations in parallel where one of the
processes may be working on an empty dataset. In such cases,
the process is still expected to evaluate a whole expression because
some of the functions may perform bulk MPI communication. None
cannot be used in these instances because it cannot properly override
operators such as __add__, __sub__ etc. This is the main raison
d'etre for VTKNoneArray."""
def __getitem__(self, index):
return NoneArray
def _op(self, other, op):
"""Used to implement numpy-style numerical operations such as __add__,
__mul__, etc."""
return NoneArray
def astype(self, dtype):
"""Implements numpy array's astype method."""
return NoneArray
NoneArray = VTKNoneArray()
class VTKCompositeDataArrayMetaClass(type):
def __new__(mcs, name, parent, attr):
"""Simplify the implementation of the numeric/logical sequence API."""
def add_numeric_op(attr_name, op):
"""Create an attribute named attr_name that calls
_numeric_op(self, other, op)."""
def closure(self, other):
return VTKCompositeDataArray._numeric_op(self, other, op)
closure.__name__ = attr_name
attr[attr_name] = closure
def add_reverse_numeric_op(attr_name, op):
"""Create an attribute named attr_name that calls
_reverse_numeric_op(self, other, op)."""
def closure(self, other):
return VTKCompositeDataArray._reverse_numeric_op(self, other, op)
closure.__name__ = attr_name
attr[attr_name] = closure
def add_default_reverse_numeric_op(op_name):
"""Adds '__r[op_name]__' attribute that uses operator.[op_name]"""
add_reverse_numeric_op("__r%s__"%op_name, getattr(operator, op_name))
def add_default_numeric_op(op_name):
"""Adds '__[op_name]__' attribute that uses operator.[op_name]"""
add_numeric_op("__%s__"%op_name, getattr(operator, op_name))
def add_default_numeric_ops(op_name):
"""Call both add_default_numeric_op and add_default_reverse_numeric_op."""
add_default_numeric_op(op_name)
add_default_reverse_numeric_op(op_name)
add_default_numeric_ops("add")
add_default_numeric_ops("sub")
add_default_numeric_ops("mul")
if sys.hexversion < 0x03000000:
add_default_numeric_ops("div")
add_default_numeric_ops("truediv")
add_default_numeric_ops("floordiv")
add_default_numeric_ops("mod")
add_default_numeric_ops("pow")
add_default_numeric_ops("lshift")
add_default_numeric_ops("rshift")
add_numeric_op("__and__", operator.and_)
add_reverse_numeric_op("__rand__", operator.and_)
add_default_numeric_ops("xor")
add_numeric_op("__or__", operator.or_)
add_reverse_numeric_op("__ror__", operator.or_)
add_default_numeric_op("lt")
add_default_numeric_op("le")
add_default_numeric_op("eq")
add_default_numeric_op("ne")
add_default_numeric_op("ge")
add_default_numeric_op("gt")
return type.__new__(mcs, name, parent, attr)
@_metaclass(VTKCompositeDataArrayMetaClass)
class VTKCompositeDataArray(object):
"""This class manages a set of arrays of the same name contained
within a composite dataset. Its main purpose is to provide a
Numpy-type interface to composite data arrays which are naturally
nothing but a collection of vtkDataArrays. A VTKCompositeDataArray
makes such a collection appear as a single Numpy array and support
all array operations that this module and the associated algorithm
module support. Note that this is not a subclass of a Numpy array
and as such cannot be passed to native Numpy functions. Instead
VTK modules should be used to process composite arrays.
"""
def __init__(self, arrays = [], dataset = None, name = None,
association = None):
"""Construct a composite array given a container of
arrays, a dataset, name and association. It is sufficient
to define a container of arrays to define a composite array.
It is also possible to initialize an array by defining
the dataset, name and array association. In that case,
the underlying arrays will be created lazily when they
are needed. It is recommended to use the latter method
when initializing from an existing composite dataset."""
self._Arrays = arrays
self.DataSet = dataset
self.Name = name
validAssociation = True
if association == None:
for array in self._Arrays:
if hasattr(array, "Association"):
if association == None:
association = array.Association
elif array.Association and association != array.Association:
validAssociation = False
break
if validAssociation:
self.Association = association
else:
self.Association = ArrayAssociation.FIELD
self.Initialized = False
def __init_from_composite(self):
if self.Initialized:
return
self.Initialized = True
if self.DataSet is None or self.Name is None:
return
self._Arrays = []
for ds in self.DataSet:
self._Arrays.append(ds.GetAttributes(self.Association)[self.Name])
def GetSize(self):
"Returns the number of elements in the array."
self.__init_from_composite()
size = numpy.int64(0)
for a in self._Arrays:
try:
size += a.size
except AttributeError:
pass
return size
size = property(GetSize)
def GetArrays(self):
"""Returns the internal container of VTKArrays. If necessary,
this will populate the array list from a composite dataset."""
self.__init_from_composite()
return self._Arrays
Arrays = property(GetArrays)
def __getitem__(self, index):
"""Overwritten to refer indexing to underlying VTKArrays.
For the most part, this will behave like Numpy. Note
that indexing is done per array - arrays are never treated
as forming a bigger array. If the index is another composite
array, a one-to-one mapping between arrays is assumed.
"""
self.__init_from_composite()
res = []
if type(index) == VTKCompositeDataArray:
for a, idx in izip(self._Arrays, index.Arrays):
if a is not NoneArray:
res.append(a.__getitem__(idx))
else:
res.append(NoneArray)
else:
for a in self._Arrays:
if a is not NoneArray:
res.append(a.__getitem__(index))
else:
res.append(NoneArray)
return VTKCompositeDataArray(res, dataset=self.DataSet)
def _numeric_op(self, other, op):
"""Used to implement numpy-style numerical operations such as __add__,
__mul__, etc."""
self.__init_from_composite()
res = []
if type(other) == VTKCompositeDataArray:
for a1, a2 in izip(self._Arrays, other.Arrays):
if a1 is not NoneArray and a2 is not NoneArray:
l = reshape_append_ones(a1, a2)
res.append(op(l[0],l[1]))
else:
res.append(NoneArray)
else:
for a in self._Arrays:
if a is not NoneArray:
l = reshape_append_ones(a, other)
res.append(op(l[0], l[1]))
else:
res.append(NoneArray)
return VTKCompositeDataArray(
res, dataset=self.DataSet, association=self.Association)
def _reverse_numeric_op(self, other, op):
"""Used to implement numpy-style numerical operations such as __add__,
__mul__, etc."""
self.__init_from_composite()
res = []
if type(other) == VTKCompositeDataArray:
for a1, a2 in izip(self._Arrays, other.Arrays):
if a1 is not NoneArray and a2 is notNoneArray:
l = reshape_append_ones(a2,a1)
res.append(op(l[0],l[1]))
else:
res.append(NoneArray)
else:
for a in self._Arrays:
if a is not NoneArray:
l = reshape_append_ones(other, a)
res.append(op(l[0], l[1]))
else:
res.append(NoneArray)
return VTKCompositeDataArray(
res, dataset=self.DataSet, association = self.Association)
def __str__(self):
return self.Arrays.__str__()
def astype(self, dtype):
"""Implements numpy array's as array method."""
res = []
if self is not NoneArray:
for a in self.Arrays:
if a is NoneArray:
res.append(NoneArray)
else:
res.append(a.astype(dtype))
return VTKCompositeDataArray(
res, dataset = self.DataSet, association = self.Association)
class DataSetAttributes(VTKObjectWrapper):
"""This is a python friendly wrapper of vtkDataSetAttributes. It
returns VTKArrays. It also provides the dictionary interface."""
def __init__(self, vtkobject, dataset, association):
super(DataSetAttributes, self).__init__(vtkobject)
# import weakref
# self.DataSet = weakref.ref(dataset)
self.DataSet = dataset
self.Association = association
def __getitem__(self, idx):
"""Implements the [] operator. Accepts an array name or index."""
return self.GetArray(idx)
def GetArray(self, idx):
"Given an index or name, returns a VTKArray."
if isinstance(idx, int) and idx >= self.VTKObject.GetNumberOfArrays():
raise IndexError("array index out of range")
vtkarray = self.VTKObject.GetArray(idx)
if not vtkarray:
vtkarray = self.VTKObject.GetAbstractArray(idx)
if vtkarray:
return vtkarray
return NoneArray
array = vtkDataArrayToVTKArray(vtkarray, self.DataSet)
array.Association = self.Association
return array
def keys(self):
"""Returns the names of the arrays as a list."""
kys = []
narrays = self.VTKObject.GetNumberOfArrays()
for i in range(narrays):
name = self.VTKObject.GetAbstractArray(i).GetName()
if name:
kys.append(name)
return kys
def values(self):
"""Returns the arrays as a list."""
vals = []
narrays = self.VTKObject.GetNumberOfArrays()
for i in range(narrays):
a = self.VTKObject.GetAbstractArray(i)
if a.GetName():
vals.append(a)
return vals
def PassData(self, other):
"A wrapper for vtkDataSet.PassData."
try:
self.VTKObject.PassData(other)
except TypeError:
self.VTKObject.PassData(other.VTKObject)
def append(self, narray, name):
"""Appends a new array to the dataset attributes."""
if narray is NoneArray:
# if NoneArray, nothing to do.
return
if self.Association == ArrayAssociation.POINT:
arrLength = self.DataSet.GetNumberOfPoints()
elif self.Association == ArrayAssociation.CELL:
arrLength = self.DataSet.GetNumberOfCells()
else:
if not isinstance(narray, numpy.ndarray):
arrLength = 1
else:
arrLength = narray.shape[0]
# Fixup input array length:
if not isinstance(narray, numpy.ndarray) or numpy.ndim(narray) == 0: # Scalar input
dtype = narray.dtype if isinstance(narray, numpy.ndarray) else type(narray)
tmparray = numpy.empty(arrLength, dtype=dtype)
tmparray.fill(narray)
narray = tmparray
elif narray.shape[0] != arrLength: # Vector input
components = 1
for l in narray.shape:
components *= l
tmparray = numpy.empty((arrLength, components), dtype=narray.dtype)
tmparray[:] = narray.flatten()
narray = tmparray
shape = narray.shape
if len(shape) == 3:
# Array of matrices. We need to make sure the order in memory is right.
# If column order (c order), transpose. VTK wants row order (fortran
# order). The deep copy later will make sure that the array is contiguous.
# If row order but not contiguous, transpose so that the deep copy below
# does not happen.
size = narray.dtype.itemsize
if (narray.strides[1]/size == 3 and narray.strides[2]/size == 1) or \
(narray.strides[1]/size == 1 and narray.strides[2]/size == 3 and \
not narray.flags.contiguous):
narray = narray.transpose(0, 2, 1)
# If array is not contiguous, make a deep copy that is contiguous
if not narray.flags.contiguous:
narray = numpy.ascontiguousarray(narray)
# Flatten array of matrices to array of vectors
if len(shape) == 3:
narray = narray.reshape(shape[0], shape[1]*shape[2])
# this handle the case when an input array is directly appended on the
# output. We want to make sure that the array added to the output is not
# referring to the input dataset.
copy = VTKArray(narray)
try:
copy.VTKObject = narray.VTKObject
except AttributeError: pass
arr = numpyTovtkDataArray(copy, name)
self.VTKObject.AddArray(arr)
class CompositeDataSetAttributes():
"""This is a python friendly wrapper for vtkDataSetAttributes for composite
datsets. Since composite datasets themselves don't have attribute data, but
the attribute data is associated with the leaf nodes in the composite
dataset, this class simulates a DataSetAttributes interface by taking a
union of DataSetAttributes associated with all leaf nodes."""
def __init__(self, dataset, association):
# import weakref
# self.DataSet = weakref.ref(dataset)
self.DataSet = dataset
self.Association = association
self.ArrayNames = []
self.Arrays = {}
# build the set of arrays available in the composite dataset. Since
# composite datasets can have partial arrays, we need to iterate over
# all non-null blocks in the dataset.
self.__determine_arraynames()
def __determine_arraynames(self):
array_set = set()
array_list = []
for dataset in self.DataSet:
dsa = dataset.GetAttributes(self.Association)
for array_name in dsa.keys():
if array_name not in array_set:
array_set.add(array_name)
array_list.append(array_name)
self.ArrayNames = array_list
def keys(self):
"""Returns the names of the arrays as a list."""
return self.ArrayNames
def __getitem__(self, idx):
"""Implements the [] operator. Accepts an array name."""
return self.GetArray(idx)
def append(self, narray, name):
"""Appends a new array to the composite dataset attributes."""
if narray is NoneArray:
# if NoneArray, nothing to do.
return
added = False
if not isinstance(narray, VTKCompositeDataArray): # Scalar input
for ds in self.DataSet:
ds.GetAttributes(self.Association).append(narray, name)
added = True
if added:
self.ArrayNames.append(name)
# don't add the narray since it's a scalar. GetArray() will create a
# VTKCompositeArray on-demand.
else:
for ds, array in izip(self.DataSet, narray.Arrays):
if array is not None:
ds.GetAttributes(self.Association).append(array, name)
added = True
if added:
self.ArrayNames.append(name)
self.Arrays[name] = weakref.ref(narray)
def GetArray(self, idx):
"""Given a name, returns a VTKCompositeArray."""
arrayname = idx
if arrayname not in self.ArrayNames:
return NoneArray
if arrayname not in self.Arrays or self.Arrays[arrayname]() is None:
array = VTKCompositeDataArray(
dataset = self.DataSet, name = arrayname, association = self.Association)
self.Arrays[arrayname] = weakref.ref(array)
else:
array = self.Arrays[arrayname]()
return array
def PassData(self, other):
"""Emulate PassData for composite datasets."""
for this,that in zip(self.DataSet, other.DataSet):
for assoc in [ArrayAssociation.POINT, ArrayAssociation.CELL]:
this.GetAttributes(assoc).PassData(that.GetAttributes(assoc))
class CompositeDataIterator(object):
"""Wrapper for a vtkCompositeDataIterator class to satisfy
the python iterator protocol. This iterator iterates
over non-empty leaf nodes. To iterate over empty or
non-leaf nodes, use the vtkCompositeDataIterator directly.
"""
def __init__(self, cds):
self.Iterator = cds.NewIterator()
if self.Iterator:
self.Iterator.UnRegister(None)
self.Iterator.GoToFirstItem()
def __iter__(self):
return self
def __next__(self):
if not self.Iterator:
raise StopIteration
if self.Iterator.IsDoneWithTraversal():
raise StopIteration
retVal = self.Iterator.GetCurrentDataObject()
self.Iterator.GoToNextItem()
return WrapDataObject(retVal)
def next(self):
return self.__next__()
def __getattr__(self, name):
"""Returns attributes from the vtkCompositeDataIterator."""
return getattr(self.Iterator, name)
class MultiCompositeDataIterator(CompositeDataIterator):
"""Iterator that can be used to iterate over multiple
composite datasets together. This iterator works only
with arrays that were copied from an original using
CopyStructured. The most common use case is to use
CopyStructure, then iterate over input and output together
while creating output datasets from corresponding input
datasets."""
def __init__(self, cds):
CompositeDataIterator.__init__(self, cds[0])
self.Datasets = cds
def __next__(self):
if not self.Iterator:
raise StopIteration
if self.Iterator.IsDoneWithTraversal():
raise StopIteration
retVal = []
retVal.append(WrapDataObject(self.Iterator.GetCurrentDataObject()))
if len(self.Datasets) > 1:
for cd in self.Datasets[1:]:
retVal.append(WrapDataObject(cd.GetDataSet(self.Iterator)))
self.Iterator.GoToNextItem()
return retVal
def next(self):
return self.__next__()
class DataObject(VTKObjectWrapper):
"""A wrapper for vtkDataObject that makes it easier to access FielData
arrays as VTKArrays
"""
def GetAttributes(self, type):
"""Returns the attributes specified by the type as a DataSetAttributes
instance."""
if type == ArrayAssociation.FIELD:
return DataSetAttributes(self.VTKObject.GetFieldData(), self, type)
return DataSetAttributes(self.VTKObject.GetAttributes(type), self, type)
def GetFieldData(self):
"Returns the field data as a DataSetAttributes instance."
return DataSetAttributes(self.VTKObject.GetFieldData(), self, ArrayAssociation.FIELD)
FieldData = property(GetFieldData, None, None, "This property returns the field data of a data object.")
class Table(DataObject):
"""A wrapper for vtkFielData that makes it easier to access RowData array as
VTKArrays
"""
def GetRowData(self):
"Returns the row data as a DataSetAttributes instance."
return self.GetAttributes(ArrayAssociation.ROW)
RowData = property(GetRowData, None, None, "This property returns the row data of the table.")
class CompositeDataSet(DataObject):
"""A wrapper for vtkCompositeData and subclasses that makes it easier
to access Point/Cell/Field data as VTKCompositeDataArrays. It also
provides a Python type iterator."""
def __init__(self, vtkobject):
DataObject.__init__(self, vtkobject)
self._PointData = None
self._CellData = None
self._FieldData = None
self._Points = None
def __iter__(self):
"Creates an iterator for the contained datasets."
return CompositeDataIterator(self)
def GetNumberOfElements(self, assoc):
"""Returns the total number of cells or points depending
on the value of assoc which can be ArrayAssociation.POINT or
ArrayAssociation.CELL."""
result = 0
for dataset in self:
result += dataset.GetNumberOfElements(assoc)
return int(result)
def GetNumberOfPoints(self):
"""Returns the total number of points of all datasets
in the composite dataset. Note that this traverses the
whole composite dataset every time and should not be
called repeatedly for large composite datasets."""
return self.GetNumberOfElements(ArrayAssociation.POINT)
def GetNumberOfCells(self):
"""Returns the total number of cells of all datasets
in the composite dataset. Note that this traverses the
whole composite dataset every time and should not be
called repeatedly for large composite datasets."""
return self.GetNumberOfElements(ArrayAssociation.CELL)
def GetAttributes(self, type):
"""Returns the attributes specified by the type as a
CompositeDataSetAttributes instance."""
return CompositeDataSetAttributes(self, type)
def GetPointData(self):
"Returns the point data as a DataSetAttributes instance."
if self._PointData is None or self._PointData() is None:
pdata = self.GetAttributes(ArrayAssociation.POINT)
self._PointData = weakref.ref(pdata)
return self._PointData()
def GetCellData(self):
"Returns the cell data as a DataSetAttributes instance."
if self._CellData is None or self._CellData() is None:
cdata = self.GetAttributes(ArrayAssociation.CELL)
self._CellData = weakref.ref(cdata)
return self._CellData()
def GetFieldData(self):
"Returns the field data as a DataSetAttributes instance."
if self._FieldData is None or self._FieldData() is None:
fdata = self.GetAttributes(ArrayAssociation.FIELD)
self._FieldData = weakref.ref(fdata)
return self._FieldData()
def GetPoints(self):
"Returns the points as a VTKCompositeDataArray instance."
if self._Points is None or self._Points() is None:
pts = []
for ds in self:
try:
_pts = ds.Points
except AttributeError:
_pts = None
if _pts is None:
pts.append(NoneArray)
else:
pts.append(_pts)
if len(pts) == 0 or all([a is NoneArray for a in pts]):
cpts = NoneArray
else:
cpts = VTKCompositeDataArray(pts, dataset=self)
self._Points = weakref.ref(cpts)
return self._Points()
PointData = property(GetPointData, None, None, "This property returns the point data of the dataset.")
CellData = property(GetCellData, None, None, "This property returns the cell data of a dataset.")
FieldData = property(GetFieldData, None, None, "This property returns the field data of a dataset.")
Points = property(GetPoints, None, None, "This property returns the points of the dataset.")
class DataSet(DataObject):
"""This is a python friendly wrapper of a vtkDataSet that defines
a few useful properties."""
def GetPointData(self):
"Returns the point data as a DataSetAttributes instance."
return self.GetAttributes(ArrayAssociation.POINT)
def GetCellData(self):
"Returns the cell data as a DataSetAttributes instance."
return self.GetAttributes(ArrayAssociation.CELL)
PointData = property(GetPointData, None, None, "This property returns the point data of the dataset.")
CellData = property(GetCellData, None, None, "This property returns the cell data of a dataset.")
class PointSet(DataSet):
"""This is a python friendly wrapper of a vtkPointSet that defines
a few useful properties."""
def GetPoints(self):
"""Returns the points as a VTKArray instance. Returns None if the
dataset has implicit points."""
if not self.VTKObject.GetPoints():
return None
array = vtkDataArrayToVTKArray(
self.VTKObject.GetPoints().GetData(), self)
array.Association = ArrayAssociation.POINT
return array
def SetPoints(self, pts):
"""Given a VTKArray instance, sets the points of the dataset."""
from ..vtkCommonCore import vtkPoints
if isinstance(pts, vtkPoints):
p = pts
else:
pts = numpyTovtkDataArray(pts)
p = vtkPoints()
p.SetData(pts)
self.VTKObject.SetPoints(p)
Points = property(GetPoints, SetPoints, None, "This property returns the point coordinates of dataset.")
class PolyData(PointSet):
"""This is a python friendly wrapper of a vtkPolyData that defines
a few useful properties."""
def GetPolygons(self):
"""Returns the polys as a VTKArray instance."""
if not self.VTKObject.GetPolys():
return None
return vtkDataArrayToVTKArray(
self.VTKObject.GetPolys().GetData(), self)
Polygons = property(GetPolygons, None, None, "This property returns the connectivity of polygons.")
class UnstructuredGrid(PointSet):
"""This is a python friendly wrapper of a vtkUnstructuredGrid that defines
a few useful properties."""
def GetCellTypes(self):
"""Returns the cell types as a VTKArray instance."""
if not self.VTKObject.GetCellTypesArray():
return None
return vtkDataArrayToVTKArray(
self.VTKObject.GetCellTypesArray(), self)
def GetCellLocations(self):
"""Returns the cell locations as a VTKArray instance."""
if not self.VTKObject.GetCellLocationsArray():
return None
return vtkDataArrayToVTKArray(
self.VTKObject.GetCellLocationsArray(), self)
def GetCells(self):
"""Returns the cells as a VTKArray instance."""
if not self.VTKObject.GetCells():
return None
return vtkDataArrayToVTKArray(
self.VTKObject.GetCells().GetData(), self)
def SetCells(self, cellTypes, cellLocations, cells):
"""Given cellTypes, cellLocations, cells as VTKArrays,
populates the unstructured grid data structures."""
from ..util.vtkConstants import VTK_ID_TYPE
from ..vtkCommonDataModel import vtkCellArray
cellTypes = numpyTovtkDataArray(cellTypes)
cellLocations = numpyTovtkDataArray(cellLocations, array_type=VTK_ID_TYPE)
cells = numpyTovtkDataArray(cells, array_type=VTK_ID_TYPE)
ca = vtkCellArray()
ca.SetCells(cellTypes.GetNumberOfTuples(), cells)
self.VTKObject.SetCells(cellTypes, cellLocations, ca)
CellTypes = property(GetCellTypes, None, None, "This property returns the types of cells.")
CellLocations = property(GetCellLocations, None, None, "This property returns the locations of cells.")
Cells = property(GetCells, None, None, "This property returns the connectivity of cells.")
class Graph(DataObject):
"""This is a python friendly wrapper of a vtkGraph that defines
a few useful properties."""
def GetVertexData(self):
"Returns the vertex data as a DataSetAttributes instance."
return self.GetAttributes(ArrayAssociation.VERTEX)
def GetEdgeData(self):
"Returns the edge data as a DataSetAttributes instance."
return self.GetAttributes(ArrayAssociation.EDGE)
VertexData = property(GetVertexData, None, None, "This property returns the vertex data of the graph.")
EdgeData = property(GetEdgeData, None, None, "This property returns the edge data of the graph.")
class Molecule(DataObject):
"""This is a python friendly wrapper of a vtkMolecule that defines
a few useful properties."""
def GetAtomData(self):
"Returns the atom data as a DataSetAttributes instance."
return self.GetVertexData()
def GetBondData(self):
"Returns the bond data as a DataSetAttributes instance."
return self.GetEdgeData()
AtomData = property(GetAtomData, None, None, "This property returns the atom data of the molecule.")
BondData = property(GetBondData, None, None, "This property returns the bond data of the molecule.")
def WrapDataObject(ds):
"""Returns a Numpy friendly wrapper of a vtkDataObject."""
if ds.IsA("vtkPolyData"):
return PolyData(ds)
elif ds.IsA("vtkUnstructuredGrid"):
return UnstructuredGrid(ds)
elif ds.IsA("vtkPointSet"):
return PointSet(ds)
elif ds.IsA("vtkDataSet"):
return DataSet(ds)
elif ds.IsA("vtkCompositeDataSet"):
return CompositeDataSet(ds)
elif ds.IsA("vtkTable"):
return Table(ds)
elif ds.IsA("vtkMolecule"):
return Molecule(ds)
elif ds.IsA("vtkGraph"):
return Table(ds)
elif ds.IsA("vtkDataObject"):
return DataObject(ds)