ParaView/Python Scripting

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Note: This document if based on ParaView 3.6 or higher. If you are using 3.4, go to the history page and select the version from May 13, 2009.

ParaView and Python

ParaView offers rich scripting support through Python. This support is available as part of the ParaView client (paraview), an MPI-enabled batch application (pvbatch), the ParaView python client (pvpython), or any other Python-enabled application. Using Python, users and developers can gain access to the ParaView engine called Server Manager.

Note: Server Manager is a library that is designed to make it easy to build distributed client-server applications.

This document is a short introduction to ParaView's Python interface. You may also visit the Python recipes page for some examples.

Quick Start - a Tutorial

Getting Started

To start interacting with the Server Manager, you have to load the "simple" module. This module can be loaded from any python interpreter as long as the necessary files are in PYTHONPATH. These files are the shared libraries located in the paraview binary directory and python modules in the paraview directory: paraview/, paraview/ etc. You can also use either pvpython (for stand-alone or client/server execution), pvbatch (for non-interactive, distributed batch processing) or the python shell invoked from Tools|Python Shell using the ParaView client to execute Python scripts. You do not have to set PYTHONPATH when using these.

This tutorial will be using the python integrated development environment IDLE. PYTHONPATH is set to the following:


Note that depending on your build configuration, your *.libs files may not be under "lib" but under one of its sub-folders, like "lib/Release" or "lib/Debug". In those cases add the correct folder where the *.libs reside:


Note: For older versions of ParaView this was /Users/berk/work/paraview3-build/bin:/Users/berk/work/paraview3-build/Utilities/VTKPythonWrapping/site-packages --Andy.bauer 24 January 2013, or /Users/berk/work/paraview3-build/bin:/Users/berk/work/paraview3-build/Utilities/VTKPythonWrapping --Andy.bauer 23 July 2010.

You may also need to set your path variable for searching for shared libraries (i.e. PATH on Windows and LD_LIBRARY_PATH on Unix/Linux/Mac). The corresponding LD_LIBRARY_PATH would be:

 /Users/berk/work/paraview3-build/lib (/Users/berk/work/paraview3-build/bin for versions before 3.98)

(Under WindowsXP for a debug build of paraview, set both PATH and PYTHONPATH environment variables to include ${BUILD}/lib/Debug and ${BUILD}/lib/site-packages to make it work.)

When using a Mac to use the build tree in IDLE, start by loading the servermanager module:

<source lang="python"> >>> from paraview.simple import * </source>

Note: Importing the paraview module directly is deprecated, although still possible for backwards compatibility. This document refers to the simple module alone.

In this example, we will use ParaView in the stand-alone mode. Connecting to a ParaView server running on a cluster is covered later in this document.


The Python shell in the ParaView Qt client provides auto-completion. One can also use IDLE, for example to enable auto-completion. To use auto-completion in pvpython, one can use the tips provided at [1].

In summary, you need to create a variable PYTHONSTARTUP as (in bash):

 export PYTHONSTARTUP = /home/<username>/.pythonrc

where .pythonrc is: <source lang="python">

   # ~/.pythonrc
   # enable syntax completion
       import readline
   except ImportError:
       print "Module readline not available."
       import rlcompleter
       readline.parse_and_bind("tab: complete")


That is it. Tab completion works just as in any other shell.

Creating a Pipeline

The simple module contains many functions to instantiate sources, filters, and other related objects. You can get a list of objects this module can create from ParaView's online help (from help menu or here:

Start by creating a Cone object:

<source lang="python"> >>> cone = Cone() </source>

You can get some documentation about the cone object using help().

<source lang="python"> >>> help(cone) Help on Cone in module paraview.servermanager object:

class Cone(SourceProxy)

|  The Cone source can be used to add a polygonal cone to the 3D scene. The output of the 
Cone source is polygonal data.
|  Method resolution order:
|      Cone
|      SourceProxy
|      Proxy
|      __builtin__.object
|  Methods defined here:
|  Initialize = aInitialize(self, connection=None)
|  ----------------------------------------------------------------------
|  Data descriptors defined here:
|  Capping
|      If this property is set to 1, the base of the cone will be capped with a filled polygon. 
Otherwise, the base of the cone will be open.
|  Center
|      This property specifies the center of the cone.
|  Direction
|      Set the orientation vector of the cone.  The vector does not have to be normalized.  The cone 
will point in the direction specified.
|  Height
|      This property specifies the height of the cone.
|  Radius
|      This property specifies the radius of the base of the cone.
|  Resolution
|      This property indicates the number of divisions around the cone. The higher this number, the 
closer the polygonal approximation will come to representing a cone, and the more polygons it will 


This gives you a full list of properties. Check what the resolution property is set to:

<source lang="python"> >>> cone.Resolution 6 </source>

You can increase the resolution as shown below:

<source lang="python"> >>> cone.Resolution = 32 </source>

Alternatively, we could have specified a value for resolution when creating the object:

<source lang="python"> >>> cone = Cone(Resolution=32) </source>

You can assign values to any number of properties during construction using keyword arguments: You can also change the center.

<source lang="python"> >>> cone.Center [0.0, 0.0, 0.0] >>> cone.Center = [1, 2, 3] </source>

Vector properties such as this one support setting and retrieval of individual elements, as well as slices (ranges of elements):

<source lang="python"> >>> cone.Center[0:2] = [2, 4] >>> cone.Center [2.0, 4.0, 3.0] </source>

Next, apply a shrink filter to the cone:

<source lang="python"> >>> shrinkFilter = Shrink(cone) >>> shrinkFilter.Input <paraview.servermanager.Cone object at 0xaf701f0> </source>

At this point, if you are interested in getting some information about the output of the shrink filter, you can force it to update (which will also cause the execution of the cone source). For details about VTK's demand-driven pipeline model used by ParaView, see one of the VTK books.

<source lang="python"> >>> shrinkFilter.UpdatePipeline() >>> shrinkFilter.GetDataInformation().GetNumberOfCells() 33L >>> shrinkFilter.GetDataInformation().GetNumberOfPoints() 128L </source>

We will cover the DataInformation class in more detail later.


Now that you've created a small pipeline, render the result. You will need two objects to render the output of an algorithm in a scene: a representation and a view. A representation is responsible for taking a data object and rendering it in a view. A view is responsible for managing a render context and a collection of representations. Simple creates a view by default. The representation object is created automatically with Show().

<source lang="python"> >>> Show(shrinkFilter) >>> Render() </source>

Et voila:

Figure 14.1 Server manager snapshot

In example Figure 14.1, the value returned by Cone() and Shrink() was assigned to Python variables and used to build the pipeline. ParaView keeps track of the last pipeline object created by the user. This allows you to accomplish everything you did above using the following code:

<source lang="python"> >>> from paraview.simple import *

  1. Create a cone and assign it as the active object

>>> Cone() <paraview.servermanager.Cone object at 0x2910f0>

  1. Set a property of the active object

>>> SetProperties(Resolution=32)

  1. Apply the shrink filter to the active object
  2. Shrink is now active

>>> Shrink() <paraview.servermanager.Shrink object at 0xaf64050>

  1. Show shrink

>>> Show() <paraview.servermanager.UnstructuredGridRepresentation object at 0xaf57f90>

  1. Render the active view

>>> Render() <paraview.servermanager.RenderView object at 0xaf57ff0> </source>

This was a quick introduction to the paraview.simple module. In the following sections, we will discuss the Python interface in more detail and introduce more advanced concepts.

paraview.simple Module

The simple module is a ParaView component written using Python on top of the Server Manager C++ library. Its purpose is to make it easier to create ParaView data analysis and visualization pipelines using Python. The simple module can be loaded from Python interpreters running in several applications.

  • pvpython: The pvpython application, distributed with the ParaView application suite, is a Python client to the ParaView servers. It supports interactive execution as well as batch execution.
  • pvbatch: The pvbatch application, also distributed with the ParaView application suite, is a Python application designed to run batch scripts on distributed servers. When ParaView is compiled with MPI, pvbatch can be launched as an MPI program. In this mode, the first node will load a Python script specified as a command-line argument and execute it using a special built-in connection on all nodes. This application does not support interactive execution.
  • paraview: Python scripts can be run from the paraview client using the Python shell that is invoked from Tools|Python Shell. The Python shell supports interactive mode as well as loading of scripts from file.
  • External Python interpreter: Any Python-capable application can load the paraview.simple module if the right environment is configured. For this to work, you either have to install the paraview Python modules (including the right shared libraries) somewhere in sys.path or you have to set PYTHONPATH to point to the right locations.


The paraview.simple module contains several Python classes designed to be Python-friendly, as well as all classes wrapped from the C++ Server Manager library. The following sections cover the usage of this module and occasionally the paraview.servermanager module, which is lower level.

Connecting to a Server

ParaView can run in two modes: stand-alone and client/server where the server is usually a visualization cluster. In this section, we discuss how to establish a connection to a server when using ParaView in the client/server mode. If you are using the ParaView graphical interface, you should use Connect from the File menu to connect to a server. If you are using ParaView from a Python shell (not the Python console that is part of the graphical interface), you need to use servermanager.Connect() to connect a server. Note: you cannot connect to the ParaView application from a stand-alone Python shell. You can only connect to a server. This method takes four arguments, all of which have default values.

<source lang="python"> def Connect(ds_host=None, ds_port=11111, rs_host=None, rs_port=11111) </source>

When connecting to a server (pvserver), specify only the first two arguments. These are the server name (or IP address) and port number.

When connecting to a data-server/render-server pair, you have to specify all four arguments. The first two are the host name (or IP address) and port number of the data server, the last two those of the render server. Here are some examples:

<source lang="python">

  1. Connect to pvserver running on amber1 (first node of our test cluster)
  2. using the default port 11111

>>> Connect(‘amber1’)

  1. Connect to pvdataserver running on the amber cluster, pvrenderserver
  2. running on Berk’s desktop

>>> Connect(‘amber1’, 12000, ‘kamino’, 11111) </source>

Note: Connect() will return None on failure. To be safe, you should check the return value of Connect().

Getting Help

You can access the documentation of all Proxy types by using Python's built-in help.

<source lang="python"> >>> help(paraview.simple.Cone) Help on function CreateObject in module paraview.simple:

CreateObject(*input, **params)

   The Cone source can be used to add a polygonal cone to the 3D scene. The output of the 
   Cone source is polygonal data.


To get the full documentation, you have to create an instance.

<source lang="python"> >>> c = Cone() >>> help(c) </source>

This documentation is automatically generated from the Server Manager configuration files. It is identical to the class documentation found under the ParaView Help menu, as well as here: Beyond this document and the online help, there are a few useful documentation sources:

If you are interested in learning more about the Visualization Toolkit that is at the foundation of ParaView, visit

Proxies and Properties


The VTK Server Manager design uses the Proxy design pattern (See Design Patterns: Elements of Reusable Object-Oriented Software by Erich Gamma, Richard Helm, Ralph Johnson and John Vlissides for details). Quoting from Wikipedia: “A proxy, in its most general form, is a class functioning as an interface to another thing. The other thing could be anything: a network connection, a large object in memory, a file, or some other resource that is expensive or impossible to duplicate”. In the case of Server Manager, a Proxy object acts as a proxy to one-or-more VTK objects. Most of the time, these are server-side objects and are distributed to the server nodes. Proxy objects allow you to interact with these objects as if you directly have access to them, manipulate them, and obtain information about them. When creating visualization pipelines, you create proxies instead of VTK objects.

<source lang="python"> >>> sphereSource = vtk.vtkSphereSource() # VTK-Python script

>>> sphereSourceP = Sphere() # ParaView script </source>

A proxy also provides an interface to modify the properties of the objects it maintains. For example, instead of:

<source lang="python"> >>> sphereSource.SetCenter(1.0, 1.0, 0.0) </source>

you can write the following:

<source lang="python"> >>> sphere.Center = [1.0, 1.0, 0.0] </source>

When a pipeline object proxy is created, it is set as the active object. You can also set an object as the active one. This is equivalent to clicking-on an object in the pipeline browser.

<source lang="python"> >>> c = Cone() <paraview.servermanager.Cone object at 0xaf73090> >>> GetActiveSource() <paraview.servermanager.Cone object at 0xaf73090> >>> Shrink() <paraview.servermanager.Shrink object at 0xb4f8610>

  1. Make the cone active

>>> SetActiveSource(c) </source>

When dealing with objects created through the graphical interface or by loading a state, it is useful to be able to search through existing pipeline objects. To accomplish this, you can use GetSources() and FindSource(). GetSources() returns a dictionary of (name, id) object pairs. Since multiple objects can have the same name, the (name,id) pair identifies objects uniquely. FindSource() returns an object given its name. If there are more than one objects with the same name, the first one is returned.

<source lang="python"> >>> Cone() <paraview.servermanager.Cone object at 0xaf73090> >>> GetActiveSource() <paraview.servermanager.Cone object at 0xaf73090> >>> Shrink() <paraview.servermanager.Shrink object at 0xb4f8610> >>> SetActiveSource(c) </source>

To delete pipeline objects, you need to use the Delete() function. Simply letting a Python variable go out of scope is not enough to delete the object. Following the example above:

<source lang="python">

  1. Delete the cone source

>>> Delete(c)

  1. To fully remove the cone from memory, get rid of the
  2. variable too

>>> del c </source>

If you do not use a Python variable to hold the value returned by the pipeline object proxy constructor, the following is needed to delete the object: <source lang="python"> Cone() # not: c = Cone()

  1. to delete this object:
  2. First, delete its entry in the ParaView's pipeline GUI or call Delete(FindSource("Cone1"))
  3. Then, this is needed:

import gc gc.collect() </source>

Please note that for destructors to be called, calls such as c = FindSource("name"), respecively FindSource("name") will also require the call to del(c), respectively gc.collect() afterward.


Property objects are used to read and modify the properties of pipeline objects. Each proxy has a list of properties defined in the Server Manager configuration files. The property interface of the Server Manager C++ library is somewhat cumbersome. Here is how you can set the radius property of a sphere source:

<source lang="python"> >>> rp = sphere.GetProperty("Radius") >>> rp.SetElement(0, 2) 1 >>> sphere.UpdateProperty("Radius") </source>

The servermanager module makes property access much easier by defining Python property accessors for property objects:

<source lang="python"> >>> sphere.Radius = 3 </source>

Here, Radius is a Python property which, when a value is assigned to it, calls sphere.SetPropertyWithName("Radius",3). Properties can also passed to the function creating the object:

<source lang="python"> >>> cone = Cone(Radius=0.5, Center=[1, 0.5, 0]) <paraview.servermanager.Cone object at 0xaf73090> </source>

You can also use the SetProperties() function to set property values.

<source lang="python"> >>> SetProperties(cone, Radius=0.2, Center=[2, 0.5, 0]) </source>

If the first argument is not specified, the active object is used. You also use SetDisplayProperties() and SetViewProperties() to set display (representation) and view properties respectively.

All Property classes define the following methods:

  • __len__()
  • __getitem__()
  • __setitem__()
  • __getslice__()
  • __setslice__()
  • GetData()
  • SetData().

Therefore, all of the following are supported:

<source lang="python"> >>> sphere.Center [0.0, 0.0, 0.0] >>> sphere.Center[0] = 1 >>> sphere.Center[0:3] = [1,2,3] >>> sphere.Center[0:3] [1.0, 2.0, 3.0] >>> len(sphere.Center) 3 </source>

ProxyProperty and InputProperty also define

  • append()
  • __delitem__()
  • __delslice__()

to support del() and append(), similar to Python list objects.

VectorProperty is used for scalars, vectors and lists of integer and floating point numbers as well as strings. Most properties of this type are simple. Examples include Sphere.Radius (double scalar), Sphere.Center (vector of doubles), a2DGlyph.Filled (boolean), a2DGlyph.GlyphType (enumeration), a3DText.Text (string), and Contour.Isosurfaces (list of doubles). Some properties may be more complicated because they map to C++ methods with mixed argument types. Two good examples of this case are Glyph.Scalars and ExodusIIReader.PointVariables.

<source lang="python"> >>> reader = ExodusIIReader(FileName='.../can.ex2')

  1. These variables are currently selected

>>> reader.PointVariables ['DISPL', 'VEL', 'ACCL']

  1. These are available in the file

>>> reader.PointVariables.Available ['DISPL', 'VEL', 'ACCL']

  1. Enable the DISPL array only

>>> reader.PointVariables = ['DISPL']

  1. Force read

>>> reader.UpdatePipeline()

  1. Now check the output. Note: GlobalNodeId is generated automatically by the reader.

>>> reader.PointData[:] [Array: GlobalNodeId, Array: PedigreeNodeId, Array: DISPL] </source>

This example demonstrates the use of ExodusIIReader.PointVariables. This is a VectorProperty that represents a list of array names. The underlying C++ function has a signature of SetPointResultArrayStatus(const char* name, int flag). This method is usually called once per array to enable or disable it (i.e. to set whether the reader will read a particular array).

Glyph.Scalars is a bit more complicated. This property allows the developer to select the scalar array with which to scale the glyphs.

<source lang="python"> >>> sph = Sphere() >>> elev=Elevation(sph)

  1. Glyph the points of the sphere with spheres

>>> glyph=Glyph(elev, GlyphType='Sphere')

  1. Scale the glyph with the Elevation array

>>> glyph.Scalars = 'Elevation' >>> glyph.Scalars ['POINTS', 'Elevation']

  1. The above shows the association of the array as well as its name.
  2. In this case, the array is associated with POINTS as it has to be
  3. since Glyph cannot scale by cell arrays. We could have done:

>>> glyph.Scalars = ['POINTS', 'Elevation']

  1. Enable scaling by scalars

>>> glyph.ScaleMode = 'scalar' </source>

Here the property Scalars maps to SetInputArrayToProcess(int idx, int port, int connection, int fieldAssociation, const char *name), which has four integer arguments (some of which are enumeration) and one string argument (see vtkAlgorithm documentation for details).

Properties are either regular (push) or information (pull) properties. Information properties do not have a VTK method associated with them and are responsible for getting information from the server. A good example of an information property is TimestepValues, which returns all time steps available in a file (if the reader supports time).

<source lang="python"> >>> reader = ExodusIIReader(FileName='.../can.ex2') >>> reader.TimestepValues [0.0, 0.00010007373930420727, 0.00019990510190837085, 0.00029996439116075635, 0.00040008654468692839,

0.00049991923151537776, 0.00059993512695655227, 0.00070004, ...]


You can obtain a list of properties a proxy supports by using help(). However, this does not allow introspection programmatically. If you need to obtain information about a proxy’s properties programmatically, you can use a property iterator:

<source lang="python"> >>> for prop in glyph: print type(prop), prop.GetXMLLabel()

<class 'paraview.servermanager.InputProperty'> Input <class 'paraview.servermanager.VectorProperty'> Maximum Number of Points <class 'paraview.servermanager.VectorProperty'> Random Mode <class 'paraview.servermanager.ArraySelectionProperty'> Scalars <class 'paraview.servermanager.ArraySelectionProperty'> Vectors <class 'paraview.servermanager.VectorProperty'> Orient <class 'paraview.servermanager.VectorProperty'> Set Scale Factor <class 'paraview.servermanager.EnumerationProperty'> Scale Mode <class 'paraview.servermanager.InputProperty'> Glyph Type <class 'paraview.servermanager.VectorProperty'> Mask Points </source>

The XMLLabel is the text display by the graphical user-interface. Note that there is a direct mapping from the XMLLabel to the property name. If you remove all spaces from the label, you get the property name. You can use the PropertyIterator object directly.

<source lang="python"> >>> it = iter(s) >>> for i in it: print it.GetKey(), it.GetProperty() </source>


The Server Manager provides information about values that are valid for properties. The main use of this information is for the user-interface to provide good ranges and choices in enumeration. However, some of this information is also very useful for introspection. For example, enumeration properties look like simple integer properties unless a (value, name) pair is associated with them. The Server Manager uses Domain objects to store this information. The contents of domains may be loaded from xml configuration files or computed automatically. For example:

<source lang="python"> >>> s = Sphere() >>> Show(s) >>> dp = GetDisplayProperties(s) >>> dp.Representation 'Surface'

  1. The current representation type is Surface. What other types
  2. are available?

>>> dp.GetProperty("Representation").Available ['Outline', 'Points', 'Wireframe', 'Surface', 'Surface With Edges']

  1. Choose outline

>>> dp.Representation = 'Outline' </source>

Source Proxies

Source proxies are proxies that represent pipeline objects (For more information about VTK pipelines, see the VTK books: They have special properties to connect them as well as special method to query the meta-data of their output. To connect a source proxy to another, use one of its input properties.

<source lang="python">

  1. Either

>>> glyph = Glyph(elev)

  1. or

>>> glyph.Input = elev </source>

The SourceProxy class provides several additional properties and methods that are specific to pipelines (See vtkSMSourceProxy documentation for a full list).

  • UpdatePipelineInformation(): This method calls UpdateInformation() on the VTK algorithm. It also calls UpdatePropertyInformation() to update any information properties.
  • UpdatePipeline(): This method calls Update() on the VTK algorithm causing a pipeline execution if the pipeline changed. Another way of causing pipeline updates is to render. The render view updates all connected pipelines.
  • GetDataInformation(): This method is used to obtain meta-data about one output. It is discussed further below.
  • PointData and CellData properties discussed below.

There are two common ways of getting meta-data information from a proxy: information properties and DataInformation. Information properties are updated automatically every time UpdatePropertyInformation() and UpdatePipelineInformation() are called. All you have to do is read the data from the property as usual. To get a DataInformation object from a source proxy use GetDataInformation(port=0). By default, this method returns data information for the first output. You can pass an optional port number to get information for another output. You can get detailed documentation on DataInformation by using help() and by reading online documentation for vtkPVDataInformation ( Here are the use of some common methods:

<source lang="python"> >>> di = glyph.GetDataInformation(0) >>> di <paraview.servermanager.DataInformation object at 0x2d0920d0> >>> glyph.UpdatePipeline()

  1. Get the data type.

>>> di.GetDataClassName() 'vtkPolyData'

  1. Get information about point data.

>>> pdi = glyph.PointData

  1. We are now directly accessing the wrapper for a VTK class

>>> len(pdi) 2

  1. Get information for a point array

>>> ai = pdi[0] >>> ai.GetRange(0) (0.0, 0.5) </source>

When meta-data is not enough and you need access to the raw data, you can use Fetch() to bring it to the client side. Note that this function is provided by the servermanager module. Fetch() has three modes:

  • Append all of the data together and bring it to the client (only available for polygonal and unstructured datasets). Note: Do not do this if data is large otherwise the client will run out of memory.
  • Bring data from a given process to the client.
  • Use a reduction algorithm and bring its output to the client. For example, find the minimum value of an attribute.

Here is a demonstration:

<source lang="python"> >>> from paraview.simple import * >>> Connect("kamino") Connection (kamino:11111) >>> s = Sphere()

  1. Get the whole sphere. DO NOT DO THIS IF THE DATA IS LARGE otherwise
  2. the client will run out of memory.

>>> allsphere = servermanager.Fetch(s) getting appended use append poly data filter >>> allsphere.GetNumberOfPolys() 96

  1. Get the piece of the sphere on process 0.

>>> onesphere = servermanager.Fetch(s, 0) getting node 0 >>> onesphere.GetNumberOfPolys() 48

  1. Apply the elevation filter so that we have a useful scalar array.

>>> elev = Elevation(s)

  1. We will use the MinMax algorithm to compute the minimum value of
  2. elevation. MinMax will be first applied on each processor. The results
  3. will then be gathered to the first node. MinMax will be then applied
  4. to the gathered results.
  5. We first create MinMax without an input.

>>> mm = MinMax(None)

  1. Set it to compute min

>>> mm.Operation = "MIN"

  1. Get the minimum

>>> mindata = servermanager.Fetch(elev, mm, mm) applying operation

  1. The result is a vtkPolyData with one point

>>> mindata.GetPointData().GetNumberOfArrays() 2 >>> a0 = mindata.GetPointData().GetArray(1) >>> a0.GetName() 'Elevation' >>> a0.GetTuple1(0) 0.0 </source>

Representations and Views

Once a pipeline is created, it can be rendered using representations and views. A view is essentially a “window” in which multiple representations can be displayed. When the view is a VTK view (such as RenderView), this corresponds to a collection of objects including vtkRenderers and a vtkRenderWindow. However, there is no requirement for a view to be a VTK view or to render anything. A representation is a collection of objects, usually a pipeline, that takes a data object, converts it to something that can be rendered, and renders it. When the view is a VTK view, this corresponds to a collection of objects including geometry filters, level-of-detail algorithms, vtkMappers and vtkActors. The simple module automatically creates a view after connecting to a server (including the built-in connection when using the stand-alone mode). Furthermore, the simple module creates a representation the first time a pipeline object is displayed with Show(). It is easy to create new views.

<source lang="python"> >>> view = CreateRenderView() </source>

CreateRenderView() is a special method that creates the render view appropriate for the ActiveConnection (or for another connection specified as an argument). It returns a sub-class of Proxy. Like the constructor of Proxy, it can take an arbitrary number of keyword arguments to set initial values for properties. Note that ParaView makes the view that was created last the active view. When using Show() without a view argument, the pipeline is shown in the active view. You can get a list of views as well as the active view as follows:

<source lang="python"> >>> GetRenderViews() [<paraview.servermanager.RenderView object at 0xaf64ef0>, <paraview.servermanager.RenderView object at 0xaf64b70>] >>> GetActiveView() <paraview.servermanager.RenderView object at 0xaf64b70> </source>

You can also change the active view using SetActiveView().

Once you have a render view, you can use pass it to Show in order to select in which view a pipeline object is displayed. You can also pass it to Render() to select which view is rendered.

<source lang="python"> >>> Show(elev, GetRenderViews()[1]) <paraview.servermanager.GeometryRepresentation object at 0xaf64e30> >>> Render(GetRenderViews()[1]) </source>

Notice that Show() returns a representation object (aka DisplayProperties in the simple module). This object can be used to manipulate how the pipeline object is displayed in the view. You can also access the display properties of an object using GetDisplayProperties().

<source lang="python"> >>> dp = GetDisplayProperties(elev) >>> dp <paraview.servermanager.GeometryRepresentation object at 0xaf649d0> </source>

Display properties and views have a large number of properties some of which are poorly documented. We will cover some them here.

<source lang="python"> >>> from paraview.simple import *

  1. Create a simple pipeline

>>> sph = Sphere() >>> elev = Elevation(sph) >>> Show(elev) >>> Render()

  1. Set the representation type of elev

>>> dp = GetDisplayProperties(elev) >>> dp.Representation = 'Points'

  1. Here is how you get the list of representation types

>>> dp.GetProperty("Representation").Available ['Outline', 'Points', 'Wireframe', 'Surface', 'Surface With Edges'] >>> Render()

  1. Change the representation to wireframe

>>> dp.Representation = 'Wireframe' >>> Render()

  1. Let’s get some information about the output of the elevation
  2. filter. We want to color the representation by one of it’s
  3. arrays.
  4. Second array = Elevation. Interesting. Let’s use this one.

>>> ai = elev.PointData[1] >>> ai.GetName() 'Elevation'

  1. What is its range?

>>> ai.GetRange() (0.0, 0.5)

  1. To color the representation by an array, we need to first create
  2. a lookup table. We use the range of the Elevation array

>>> dp.LookupTable = MakeBlueToRedLT(0, 0.5) >>> dp.ColorAttributeType = 'POINT_DATA' >>> dp.ColorArrayName = 'Elevation' # color by Elevation >>> Render() </source>

Here is the result:

Figure 14.2 Object displayed in a view

Once you create a scene, you will probably want to interact with the camera and ResetCamera() is likely to be insufficient. In this case, you can directly get the camera from the view and manipulate it. GetActiveCamera() returns a VTK object (not a proxy) with which you can interact.

<source lang="python"> >>> camera = GetActiveCamera() >>> camera <libvtkCommonPython.vtkCamera vtkobject at 0xe290> >>> camera.Elevation(45) >>> Render() </source>

Another common thing to do is to save the view as an image. For this purpose, you can use the WriteImage() method provided by the view:

<source lang="python"> >> WriteImage("/Users/berk/image.png") </source>

The resulting image.png looks like this. See the documentation for WriteImage() for details on choosing file type, as well as a magnification factor to save images larger than the view size.

Figure 14.3 Saving a view as an image

Advanced Concepts

Dealing with lookup tables

In v4.1 LUT manipulation was simplified so that the LUTs found in the GUI may be assigned to arrays by name. See Lookup tables recipe for more information.

As shown earlier, you can use MakeBlueToRedLt(min, max) to create a lookup table. However, this simply creates a new lookup table that the GUI won't be aware of. In the ParaView Qt application, we have special lookup table management that ensures that the same lookup table is used for all arrays with same name and number of components. To reproduce the same behavior in Python, use GetLookupTableForArray().

<source lang="python"> def GetLookupTableForArray(arrayname, num_components, **params):

   """Used to get an existing lookuptable for a array or to create one if none
   exists. Keyword arguments can be passed in to initialize the LUT if a new
   one is created. Returns the lookup table."""


This will create a new lookup table and associate it with that array, if none already exists. Any default arguments to be passed to the lookup table if a new one is created, can be specified as additional parameters. You can always change the properties on the lookup table returned by this function.

<source lang="python">

  1. To color the representation by an array, we need to first create
  2. a lookup table. We use the range of the Elevation array

>>> dp.LookupTable = GetLookupTableForArray("Elevation", 1,

                      RGBPoints = [min, 0, 0, 1, max, 1, 0, 0],
                      ColorSpace = "HSV")

>>> dp.ColorAttributeType = 'POINT_DATA' >>> dp.ColorArrayName = 'Elevation' # color by Elevation >>> Render() </source>

Loading State and Manipulating It

Let’s say you created a complicated visualization using the paraview application and now you want to make slight changes to it and run it in a loop as a batch script. What do you do? The best way of dealing with this is to save your visualization state and then load it from Python. Let’s say you have a state file saved as myteststate.pvsm:

<source lang="python"> >>> from paraview.simple import *

  1. Load the state

>>> servermanager.LoadState("/Users/berk/myteststate.pvsm")

  1. Make sure that the view in the state is the active one

>>> SetActiveView(GetRenderView())

  1. Now render

>>> Render()

  1. Get the list of sources

>>> GetSources() {('Sphere1', '5'): <paraview.servermanager.Sphere object at 0xaf80e30>, ('Shrink1', '11'): <paraview.servermanager.Shrink object at 0xaf80df0>, ('Cone1', '8'): <paraview.servermanager.Cone object at 0xaf80cf0>}

  1. Change the resolution of the cone and render again

>>> FindSource("Cone1").Resolution = 32 >>> Render() </source>

You can also save state.

<source lang="python"> >>> from paraview.simple import * >>> sph = Sphere() >>> Render() >>> servermanager.SaveState("/Users/berk/pythonstate.pvsm") </source>

Dealing with Time

If a reader or a filter supports time, it is easy to request a certain time step from Python. All time requests are set on views that then propagate them to the representations which then propagate them to the visualization pipeline. Here is an example demonstrating how a time request can be made:

<source lang="python"> >>> Show(ExodusIIReader(FileName=".../can.ex2")) >>> Render()

  1. Get a nice view angle

>>> cam = GetActiveCamera() >>> cam.Elevation(45) >>> Render()

  1. Check the current view time

>>> view = GetActiveView() >>> view.ViewTime 0.0 >>> reader = GetActiveSource() >>> reader.TimestepValues [0.0, 0.00010007373930420727, 0.00019990510190837085, 0.00029996439116075635, 0.00040008654468692839, ...] >>> tsteps = reader.TimestepValues

  1. Let’s be fancy and use a time annotation filter. This will show the
  2. current time value of the reader as text in the corner of the view.

>>> annTime = AnnotateTimeFilter(reader)

  1. Show the filter

>>> Show(annTime)

  1. Look at a few time steps. Note that the time value is requested not
  2. the time step index.

>>> view.ViewTime = tsteps[2] >>> Render() >>> view.ViewTime = tsteps[4] >>> Render() </source>


Server Manager has a complicated animation engine based on keyframes and scenes. This section will introduce a few simple ways of animating your visualization. If you have a time-aware reader, you can animate it with AnimateReader().

<source lang="python"> >>> reader = ExodusIIReader(FileName=“.../can.ex2”) >>> Show(reader) >>> Render() >>> c = GetActiveCamera() >>> c.Elevation(95)

  1. Animate over all time steps. Note that we are not passing the optional
  2. 3rd argument here. If you pass a filename as the 3rd argument,
  3. AnimateReader will create a movie.

>>> AnimateReader(reader)

  1. Save the animation to an avi file

>>> AnimateReader(reader, filename=".../movie.avi") </source>

To animate properties other than time, you can use regular keyframes.

ParaView 3.8.0 and earlier

Although the following script will work with 3.8.1 and later, it's not the recommended way since the changes done so will not be reflected in the GUI. Refer to the following sub-section for the recommended style for 3.8.1 and later versions.

<source lang="python"> >>> Sphere() >>> Show() >>> Render()

  1. Create an animation scene

>>> scene = servermanager.animation.AnimationScene()

  1. Add one view

>>> scene.ViewModules = [GetActiveView()]

  1. Create a cue to animate the StartTheta property

>>> cue = servermanager.animation.KeyFrameAnimationCue() >>> cue.AnimatedProxy = GetActiveSource() >>> cue.AnimatedPropertyName = "StartTheta"

  1. Add it to the scene's cues

>>> scene.Cues = [cue]

  1. Create 2 keyframes for the StartTheta track

>>> keyf0 = servermanager.animation.CompositeKeyFrame() >>> keyf0.Interpolation = 'Ramp'

  1. At time = 0, value = 0

>>> keyf0.KeyTime = 0 >>> keyf0.KeyValues= [0]

>>> keyf1 = servermanager.animation.CompositeKeyFrame()

  1. At time = 1.0, value = 200

>>> keyf1.KeyTime = 1.0 >>> keyf1.KeyValues= [200]

  1. Add keyframes.

>>> cue.KeyFrames = [keyf0, keyf1]

>>> scene.Play()

  1. Some properties you can change
  2. Number of frames used in Sequence mode
  3. scene.NumberOfFrames = 100
  4. Or you can use real time mode
  5. scene.PlayMode = 'Real Time'
  6. scene.Duration = 20


ParaView 3.8.1 onwards

The following script will only work with ParaView versions 3.8.1 and later. It is now the recommended way for accessing animation scenes and tracks since the updates are reflected in the GUI when running through the Python shell from the ParaView application.

<source lang="python"> >>> Sphere() >>> Show() >>> Render()

  1. Get the application-wide animation scene

>>> scene = GetAnimationScene()

  1. Get the animation track for animating "StartTheta" on the active source.
  2. GetAnimationTrack() creates a new track if none exists.

>>> cue = GetAnimationTrack("StartTheta")

  1. Create 2 keyframes for the StartTheta track

>>> keyf0 = CompositeKeyFrame() >>> keyf0.Interpolation = 'Ramp'

  1. At time = 0, value = 0

>>> keyf0.KeyTime = 0 >>> keyf0.KeyValues= [0]

>>> keyf1 = CompositeKeyFrame()

  1. At time = 1.0, value = 200

>>> keyf1.KeyTime = 1.0 >>> keyf1.KeyValues= [200]

  1. Add keyframes.

>>> cue.KeyFrames = [keyf0, keyf1]

>>> scene.Play()

  1. Some properties you can change
  2. Number of frames used in Sequence mode
  3. scene.NumberOfFrames = 100
  4. Or you can use real time mode
  5. scene.PlayMode = 'Real Time'
  6. scene.Duration = 20


GetAnimationTrack Usages

<source lang="python">

  1. Typical usage

>>> track = GetAnimationTrack("Center", 0, sphere) or >>> track = GetAnimationTrack(sphere.GetProperty("Radius")) or

  1. this returns the track to animate visibility of the active source in
  2. all views.

>>> track = GetAnimationTrack("Visibility")

  1. For animating properties on implicit planes etc., use the following
  2. signatures:

>>> track = GetAnimationTrack(slice.SliceType.GetProperty("Origin"), 0) or >>> track = GetAnimationTrack("Origin", 0, slice.SliceType)


Loading Data Files

As seen throughout this document, you can always load a data file by explicitly creating the reader that can read the data file as follows:

<source lang="python"> >>> reader = ExodusIIReader(FileName=“.../can.ex2”) </source>

Alternatively, starting with ParaView 3.8, you can use OpenDataFile() function to let ParaView pick a reader using the extension of the file.

<source lang="python"> >>> reader = OpenDataFile(“.../can.ex2”) </source>

Writing Data Files (ParaView 3.9 or later)

To create a writer to write the output from a source, one can use the following:

<source lang="python"> from paraview.simple import *

  1. Specifying the source explicitly

>>> writer= CreateWriter("/.../filename.vtk", source)

  1. Using the active source

>>> writer= CreateWriter("/.../filename.vtk")

  1. Writing data from a particular output port

>>> writer= CreateWriter("/.../filename.vtk", servermanager.OutputPort(source, 1))

  1. Now one change change the ivars on the writer
  1. To do the actual writing, use:

>>> writer.UpdatePipeline()


Exporting CSV Data

To export a csv from the cell or point data associated with a source, one can use the following:

<source lang="python"> >>> writer = CreateWriter(".../foo.csv", source) >>> writer.FieldAssociation = "Points" # or "Cells" >>> writer.UpdatePipeline() >>> del writer </source>

Updating View Layout

Starting with ParaView 3.14, Python scripts can be used to update view layout.

Every tab in the central frame of the ParaView application is represented by layout proxy. To obtain a map of layout proxies present, use the GetLayouts().

<source lang="python"> >>> GetLayouts() {('ViewLayout1', '264'): <paraview.servermanager.ViewLayout object at 0x2e5b7d0>} </source>

To get the layout corresponding to the active view (or a particular view), use the GetLayout() function.

<source lang="python"> >>> GetLayout() <paraview.servermanager.ViewLayout object at 0x2e5b7d0> >>> >>> GetLayout(GetActiveView()) <paraview.servermanager.ViewLayout object at 0x2e5b7d0> </source>

To split the cell containing a particular view, either horizontally or vertically, use:

<source lang="python">

>>> layout.SplitViewVertical(view = GetActiveView())

>>> layout.SplitViewHorizontal(view = GetActiveView(), fraction = 0.7)


To resize a cell containing a particular view:

<source lang="python">

>>> location = layout.GetViewLocation(view) >>> layout.SetSplitFraction(location, 0.3)


To maximize a particular view <source lang="python">

>>> location = layout.GetViewLocation(view) >>> layout.MaximizeCell(location)


There are a host of other methods that are available that can help with layout of the views. Refer to the API exposed by vtkSMViewLayoutProxy. The API is fully accessible through Python.

To create a new tab, one can use the following piece of code:

<source lang="python">

 new_layout = servermanager.misc.ViewLayout(registrationGroup="layouts")


Multiple Renders

When working in an interactive python session, the Render() command will open a new graphical window. If this window is closed before a subsequent Render() call, the new Render() call will cause the interactive python session to exit with an error like:

<source lang="bash">

XIO: fatal IO error 11 (Resource temporarily unavailable) on X server ":0"


Take away: leave the graphical window open for the duration of your python/paraview session in order for multiple Render() calls to work.

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