First version by David Gobbi: Dec 19, 2002
Last update was on Feb 12, 2016
This document provides a detailed description of how VTK objects are accessed and modified through Python.
Nearly all the power of VTK objects are available through Python (with a few exceptions as noted below). The C++ semantics are translated as directly as possible to Python semantics. Currently, full support is provided for Python 2.6, 2.7, and 3.2 through 3.5.
If VTK has been properly built and installed with the python wrappers, then VTK can be accessed by importing the 'vtk' module:
import vtk
or
from vtk import *
For the most part, using VTK from Python is very similar to using VTK from C++ except for changes in syntax, e.g.
vtkObject *o = vtkObject::New()
becomes
o = vtkObject()
and
o->Method()
becomes
o.Method()
Some other important differences are that you can pass a Python tuple, list or array to a method that requires a C++ array e.g.:
>>> a = vtkActor()
>>> p = (100.0, 200.0, 100.0)
>>> a.SetPosition(p)
If the C++ array parameter is used to return information, you must pass a Python list or array that has the correct number of slots to accept the returned values:
>>> z = [0.0, 0.0, 0.0]
>>> vtkMath.Cross((1,0,0),(0,1,0),z)
>>> print z
[0.0, 0.0, 1.0]
For multi-dimensional arrays, it is your choice whether to use a nested list, or whether to use a numpy array with the correct size and number of dimensions.
If the C++ method returns a pointer to an array, then that method is only wrapped if there is a hint (usually in VTK/Wrapping/hints) that gives the size of the array. Hinted pointers are returned as tuples:
>>> a = vtkActor()
>>> print a.GetPosition()
(0.0, 0.0, 0.0)
Finally, the python 'None' is treated the same as C++ 'NULL':
>>> a = vtkActor()
>>> a.SetMapper(None)
>>> print a.GetMapper()
None
And perhaps one of the most pleasant features of Python is that all type-checking is performed at run time, so the type casts that are often necessary in VTK-C++ are never needed in VTK-Python.
The mapping of Python string types to C++ string types is different in Python 3 as compared to Python 2. In Python 2, the basic 'str()' type was for 8-bit strings, and a separate 'unicode()' type was used for unicode strings.
For Python 3, the basic 'str()' type is unicode, and when you pass a str() as a VTK 'std::string' or 'const char *' parameter, VTK will receive the string in utf-8 encoding. To use a different encoding, you must encode the string yourself and pass it to VTK as a bytes() object, e.g. writer.SetFileName('myfile'.encode('latin1')).
When VTK returns a 'const char *' or 'std::string' in Python 3, the wrappers will test to see of the string is utf-8 (or ascii), and if so they will pass the string to python as a unicode str() object. If the VTK string is not valid utf-8, then the wrappers will pass the string to python as a bytes() object.
This means that using encodings other than utf-8 with VTK is risky. In rare cases, these other encodings might produce 8-bit data that the wrappers will detect as utf-8, causing them to produce a string with incorrect characters.
VTK provides conversion between 'std::vector' and Python sequences such as 'tuple' and 'list'. If the C++ method returns a vector, the Python method will return a tuple:
C++: const std::vector<std::string>& GetPaths()
C++: std::vector<std::string> GetPaths()
Python: GetPaths() -> Tuple[str]
If the C++ method accepts a vector, then the Python method can be passed any sequence with compatible values:
C++: void SetPaths(const std::vector<std::string>& paths)
C++: void SetPaths(std::vector<std::string> paths)
Python: SetPaths(paths: Sequence[str]) -> None
Furthermore, if the C++ method accepts a non-const vector reference, then the Python method can be passed a mutable sequence (e.g. list):
C++: void GetPaths(std::vector<std::string>& paths)
Python: GetPaths(paths: MutableSequence[str]) -> None
The value type of the std::vector must be std::string or a fundamental numeric type such as 'double' or 'int' (including 'signed char' and 'unsigned char' but excluding 'char').
Most VTK constants are available in Python, usually in the 'vtk' module but sometimes as class attributes:
>>> vtk.VTK_DOUBLE_MAX
1.0000000000000001e+299
>>> vtk.vtkCommand.ErrorEvent
39
Each named enum type is wrapped as a new Python type, and members of the enum are instances of that type. This allows type checking for enum types:
>>> # works if given a constant of the correct enum type
>>> o.SetIntegrationMode(o.Continuous)
>>> # does not work, because 'int' is not of the correct type
>>> o.SetIntegrationMode(10)
TypeError: SetIntegrationMode arg 1: expected enum EnumType, got int
Note that members of anonymous enums do not have a special type, and are simply wrapped as python ints.
Namespaces are currently wrapped in a very limited manner: the only namespace members that are wrapped are constants and enum types. There is no wrapping of namespaced classes or functions, or of nested namespaces. This is likely to be expanded upon when (or if) VTK begins to make greater use of namespaces.
A method is not wrapped if:
- its parameter list contains a pointer to anything other than a vtkObjectBase-derived object or a fundamental C++ type (void, char, int, unsigned short, double, etc.)
- it returns a pointer to anything other than a vtkObjectBase-derived object, unless the method returns a pointer to a fundamental C++ type and has an entry in the wrapping hints file, or the method is a vtkDataArray Get() method, or the returned type is 'char *' or 'void *'
- it is an operator method (though many exceptions exist)
Some classes are meant to be used only by other VTK classes and are not wrapped. These are labelled as WRAP_EXCLUDE_PYTHON in the CMakeLists.txt files.
Printing a vtk object will provide the same information as provided by the vtkObject::Print() method (i.e. the values of all instance variables) The same information is provided by calling str(obj). A more compact representation of the object is available by calling repr(obj)
repr(obj) -> '(vtkFloatArray)0x100c8d48'
All of the documentation that is available in the VTK header files and in the html man pages is also available through python.
If you want to see what methods are available for a class, use e.g.
>>> dir(vtk.vtkActor)
or, equivalently,
>>> a = vtk.vtkActor()
>>> dir(a)
You can also retrieve documentation about VTK classes and methods from the built-in 'docstrings':
>>> help(vtk.vtkActor)
>>> help(vtk.vtkActor.SetUserTransform)
[ lots of info printed, try it yourself ]
For the method documentation, all the different 'signatures' for the method are given in Python format and the original C++ format:
>>> help(vtkActor.SetPosition)
SetPosition(...)
V.SetPosition(float, float, float)
C++: virtual void SetPosition(double _arg1, double _arg2, double _arg3)
V.SetPosition([float, float, float])
C++: virtual void SetPosition(double _arg[3])
Set/Get/Add the position of the Prop3D in world coordinates.
There is no direct equivalent of VTK's Delete() since Python provides a mechanism for automatic garbage collection. The object will be deleted once there are no remaining references to it either from inside Python or from other VTK objects. It is possible to get rid of the local reference to the object by using the python 'del' command, i.e. 'del o', and this will result in a call to Delete() if the local reference to the object was the last remaining reference to the object from within Python.
Templated classes are rare in VTK. Where they occur, they can be instantiated much like they can be in C++, except that [ ] brackets are used for the template arguments instead of < > brackets:
>>> v = vtkVector['float64',3]([1.0, 2.0, 3.0])
>>> a = vtkDenseArray[str]()
Only a limited range of template args can be used, usually dictated by by which args are used by typedefs and by other classes in the C++ code. A list of the allowed argument combinations available for a particular template can be found by calling help() on the template:
>>> help(vtkVector)
The types are usually given as strings, in the form 'int32', 'uint16', 'float32', 'float64', 'bool', 'char', 'str', 'vtkVariant'. Python type objects are acceptable, too, if the name of the type is the same as one of the accepted type strings:
>>> a = vtkDenseArray[int]()
Note that python 'int' is the same size as a C++ 'long', and python 'float' is the same size as C++ 'double'. For compatibility with the python array module, single-character typecodes are allowed, taken from this list: '?', 'c', 'b', 'B', 'h', 'H', 'i', 'I', 'l', 'L', 'q', 'Q', 'f', 'd'. The python array documentation explains what these mean.
Some useful operators are wrapped in python: the [ ] operator is wrapped for indexing and item assignment, but because it relies on hints to guess which indices are out-of-bounds, it is only wrapped for vtkVector and a few other classes.
The comparison operators '<' '<=' '==' '>=' '>' are wrapped for all classes that have these operators in C++.
The '<<' operator for printing is wrapped and is used by the python 'print()' and 'str()' commands.
Pass-by-reference of values that are mutable in C++ but not in Python (such as string, int, and float) is only possible by using vtk.reference(), which is in the vtkCommonCore Python module:
>>> plane = vtk.vtkPlane()
>>> t = vtk.reference(0.0)
>>> x = [0.0, 0.0, 0.0]
>>> plane.InsersectWithLine([0, 0, -1], [0, 0, 1], t, x)
>>> print t
0.5
Simple callback
Similarly to what can be done in C++, a python function can be called each time a VTK event is invoked on a given object:
>>> def onObjectModified(object, event):
>>> print('object: %s - event: %s' % (object.GetClassName(), event))
>>>
>>> o = vtkObject()
>>> o.AddObserver(vtkCommand.ModifiedEvent, onObjectModified)
1
>>> o.Modified()
object: vtkObject - event: ModifiedEvent
Callback with CallData
In case there is a 'CallData' value associated with an event, in C++, you have to cast it from void* to the expected type using reinterpret_cast. For example, see http://www.vtk.org/Wiki/VTK/Examples/Cxx/Interaction/CallData
The equivalent in python is to set a CallDataType attribute on the associated python callback. The supported CallDataType are vtk.VTK_STRING, vtk.VTK_OBJECT, vtk.VTK_INT, vtk.VTK_LONG, vtk.VTK_DOUBLE, vtk.VTK_FLOAT
For example:
>>> def onError(object, event, calldata):
>>> print('object: %s - event: %s - msg: %s' % (object.GetClassName(),
event, calldata))
>>>
>>> onError.CallDataType = vtk.VTK_INT
>>>
>>> lt = vtkLookupTable()
>>> lt.AddObserver(vtkCommand.ErrorEvent, onError)
1
>>> lt.SetTableRange(2,1)
object: vtkLookupTable - event: ErrorEvent - msg: ERROR:
In /home/jchris/Projects/VTK6/Common/Core/vtkLookupTable.cxx, line 122
vtkLookupTable (0x6b40b30): Bad table range: [2, 1]
For convenience, the CallDataType can also be specified where the function is first declared with the help of the 'calldata_type' decorator:
>>> @calldata_type(vtk.VTK_INT)
>>> def onError(object, event, calldata):
>>> print('object: %s - event: %s - msg: %s' % (object.GetClassName(),
event, calldata))
It is possible to subclass a VTK class from within Python, but it is NOT possible to properly override the virtual methods of the class. The python-level code will be invisible to the VTK C++ code, so when the virtual method is called from C++, the method that you defined from within Python will not be called. The method will only be executed if you call it from within Python.
It is therefore not reasonable, for instance, to subclass the vtkInteractorStyle to provide custom python interaction. Instead, you have to do this by adding Observers to the vtkInteractor object.
In C++, if you want to call a method from a superclass you can do the following:
vtkActor *a = vtkActor::New();
a->vtkProp3D::SetPosition(10,20,50);
The equivalent in python is
>>> a = vtkActor()
>>> vtkProp3D.SetPosition(a,10,20,50)
As a special feature, a C++ method that requires a 'void *' can be passed any python object that supports the 'buffer' protocol, which include string objects, numpy arrays and even VTK arrays. Extreme caution should be applied when using this feature.
Methods that return a 'void *' in C++ will, in Python, return a string with a hexadecimal number that gives the memory address.
If you have a large block of data in Python (for example a Numeric array) that you want to access from VTK, then you can do so using the vtkDataArray.SetVoidArray() method.
When you instantiate a class, you can provide a hexadecimal string containing the address of an existing vtk object, e.g.
t = vtkTransform('_1010e068_vtkTransform_p')
The string follows SWIG mangling conventions. If a wrapper for the specified object already exists, then that wrapper will be used rather than a new wrapper being created. If you want to use this feature of vtkpython, please think twice.
SafeDownCast(): Unnecessary, Python already knows the real type
IsA(): Python provides a built-in isinstance() method.
IsTypeOf(): Python provides a built-in issubclass() method.
GetClassName(): This info is given by o.__class__.__name__
In addition to VTK objects that are derived from vtkObjectBase, there are many lightweight types in VTK such as vtkTimeStamp or vtkVariant. These can usually be distinguished from vtkObjects because they do not have a C++ '::New()' method for construction.
These types are wrapped in a slightly different way from vtkObject-derived classes. The details of memory management are different because Python actually keeps a copy of the object within its 'wrapper', whereas for vtkObjects it just keeps a pointer.
An incomplete list of these types is as follows: vtkVariant, vtkTimeStamp, vtkArrayCoordinates, vtkArrayExtents, vtkArrayExtentsList, vtkArrayRange
These special types can have several constructors, and the constructors can be used for automatic type conversion for VTK methods. For example, vtkVariantArray has a method InsertNextItem(vtkVariant v), and vtkVariant has a constructor vtkVariant(int x). So, you can do this:
>>> variantArray.InsertNextItem(1)
The wrappers will automatically construct a vtkVariant from '1', and will then pass it as a parameter to InsertNextItem.
Some special types can be sorted by value, and some can be used as dict keys. Sorting requires the existence of comparison operators such as '<' '<=' '==' '>=' '>' and these are not automatically wrapped. The use of an object as a dict key requires the computation of a hash. Comparison and hashing are supported by vtkVariant and vtkTimeStamp, and will be supported by other types on a case-by-case basis.
The reason that all vtkObjects can be easily hashed, while vtk special types are hard to hash, is that vtkObjects are hashed by memory address. This cannot be done for special types, since they must be hashed by value, not by address. I.e. vtkVariant(1) must hash equal to every other vtkVariant(1), even though the various instances will lie and different memory addresses.
o.__class__ the class that this object is an instance of
o.__doc__ a description of the class (obtained from C++ header file)
o.__this__ a string containing the address of the VTK object
m.__doc__ a description of the method (obtained from C++ header file)
c.__bases__ a tuple of base classes for this class (empty for vtkObject)
c.__doc__ a description of the class (obtained from C++ header file)
c.__name__ the name of the class, same as returned by GetClassName()