"""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() elif self.Association == ArrayAssociation.ROW \ and self.DataSet.GetNumberOfColumns() > 0: arrLength = self.DataSet.GetNumberOfRows() 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, ArrayAssociation.ROW]: if this.HasAttributes(assoc) and that.HasAttributes(assoc): 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 HasAttributes(self, type): "Returns if current object support this attributes type" return type == ArrayAssociation.FIELD 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 vtkTable 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) def HasAttributes(self, type): "Returns if current object support this attributes type" return type == ArrayAssociation.ROW or DataObject.HasAttributes(self, type) RowData = property(GetRowData, None, None, "This property returns the row data of the table.") class HyperTreeGrid(DataObject): """A wrapper for vtkHyperTreeGrid that makes it easier to access CellData arrays as VTKArrays. """ def GetCellData(self): "Returns the cell data as DataSetAttributes instance." return self.GetAttributes(ArrayAssociation.CELL) def HasAttributes(self, type): "Returns if current object support this attributes type" return type == ArrayAssociation.CELL or DataObject.HasAttributes(self, type) CellData = property(GetCellData, None, None, "This property returns the cell data of the hypertree grid.") 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 HasAttributes(self, type): "Returns true if every leaves of current composite object support this attributes type" for dataset in self: if not dataset.HasAttributes(type): return False return True 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) def HasAttributes(self, type): "Returns if current object support this attributes type" return type == ArrayAssociation.POINT or type == ArrayAssociation.CELL or DataObject.HasAttributes(self, type) 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("vtkHyperTreeGrid"): return HyperTreeGrid(ds) elif ds.IsA("vtkDataObject"): return DataObject(ds)