Introduction to VisIt¶
VisIt is a distributed, parallel, visualization tool for visualizing data defined on two and three-dimensional structured and unstructured meshes. VisIt’s distributed architecture allows it to leverage both the compute power of a large parallel computer and the graphics acceleration hardware of a local workstation. Another benefit of the distributed architecture is that VisIt can visualize the data where it is generated, eliminating the need to move data. VisIt can be controlled by a Graphical User Interface (GUI) or through the Python scripting language. More information about VisIt’s Graphical User Interface can be found in the VisIt User’s Manual.
This manual is broken down into the following chapters:
|Chapter title||Chapter description|
|Introduction to VisIt||This chapter.|
|Python||Describes the basic features of the|
|Python programming language.|
|Quick Recipes||Describes common patterns for scripting|
|using the VisIt Python Interface.|
|Functions||Describes functions in the VisIt Python|
|Attributes References||Describes attributes for setting common|
|operations, as well as for VisIt’s plugins|
|CLI Events||Describes possible events for callbacks.|
Understanding how VisIt works¶
VisIt visualizes data by creating one or more plots in a visualization window, also known as a vis window. Examples of plots include Mesh plots, Contour plots and Pseudocolor plots. Plots take as input one or more mesh, material, scalar, or tensor variables. It is possible to modify the variables by applying one or more operators to the variables before passing them to a plot. Examples of operators include arithmetic operations or taking slices through the mesh. It is also possible to restrict the visualization of the data to subsets of the mesh. VisIt provides Python bindings to all of its plots and operators so they may be controlled through scripting. Each plot or operator plugin provides a function, which is added to the VisIt namespace, to create the right type of plot or operator attributes. The attribute object can then be modified by setting its fields and then it can be passed to a general-purpose function to set the plot or operator attributes. To display a complete list of functions in the VisIt Python Interface, you can type dir() at the Python prompt. Similarly, to inspect the contents of any object, you can type its name at the Python prompt. VisIt supports up to 16 visualization windows, also called vis windows. Each vis window is independent of the other vis windows and VisIt Python functions generally apply only to the currently active vis window. This manual explains how to use the VisIt Python Interface which is a Python extension module that controls VisIt’s viewer. In that way, the VisIt Python Interface fulfills the same role as VisIt’s GUI. The difference is that the viewer is totally controlled through Python scripting, which makes it easy to write scripts to create visualizations and even movies. Since the VisIt module controls VisIt’s viewer, the Python interpreter currently has no direct mechanism for passing data to the compute engine (see Figure 13). If you want to write a script that generates simulation data and have that script pass data to the compute engine, you must pass the data through a file on disk. The VisIt Python Interface comes packaged in two varieties: the extension module and the Command Line Interface (CLI). The extension module version of the VisIt Python Interface is imported into a standard Python interpreter using the import directive. VisIt’s command line interface (CLI) is essentially a Python interpreter where the VisIt Python Interface is built-in. The CLI is provided to simplify the process of running VisIt Python scripts.
You can invoke VisIt’s command line interface from the command line by typing:
VisIt provides a separate Python module if you instead wish to include VisIt functions in an existing Python script. In that case, you must first import the VisIt module into Python and then call the Launch() function to make VisIt launch and dynamically load the rest of the VisIt functions into the Python namespace. VisIt adopts this somewhat unusual approach to module loading since the lightweight “visit” front-end module can be installed as one of your Python’s site packages yet still dynamically load the real control functions from different versions of VisIt selected by the user.
If you do not install the visit.so module as a Python site package, you can tell the Python interpreter where it is located by appending a new path to the sys.path variable. Be sure to substitute the correct path to visit.so on your system.
import sys sys.path.append("/path/to/visit/<version>/<architecture>/lib/site-packages")
Here is how to import all functions into the global Python namespace:
from visit import * Launch()
Here is how to import all functions into a “visit” module namespace:
import visit visit.Launch()
Python 3 vs Python 2¶
Python 2 has reached end of life and Python 3 is now preferred. VisIt was ported to use Python 3 as part of VisIt’s 3.2 release. Some Python 2 syntax and common patterns no longer work in Python 3.
For example, this is no longer valid in Python 3:
print "Hello from VisIt"
In Python 3 you must call
print("Hello from VisIt")
Since many VisIt scripts in the wild are written for Python 2 we provide
limited on-the-fly support to convert Python 2 style scripts to valid
Python 3 and execute them. The CLI command line option
this automatic conversion logic.
-py2to3 is used, VisIt will attempt to convert the input script
-s and any scripts run using
For example, if you create script called
that includes the Python 2 style print above and run it as follows:
visit -nowin -cli -py2to3 -s hello_visit.py
On-the-fly conversion and execution will succeed and you will see:
Running: cli -dv -nowin -py2to3 -s hello_visit.py VisIt CLI: Automatic Python 2to3 Conversion Enabled Running: viewer -dv -nowin -noint -host 127.0.0.1 -port 5600 Hello from VisIt
You can also toggle this support in VisIt’s CLI using:
visit_utils.builtin.SetAutoPy2to3(True) # or False
You can check the current value using:
We want to emphasize the limited aspect of the automatic support. The best long term path is to port your Python 2 style scripts to Python 3.
Python 3 installs provide a utility called
2to3 that you can use to
help automate porting, see https://docs.python.org/3/library/2to3.htm
for more details.
If you need help porting your trusty (or favorite) VisIt script, please reach out to the VisIt team.
VisIt is a tool for visualizing 2D and 3D scientific databases. The first thing to do when running VisIt is select databases to visualize. To select a database, you must first open the database using the OpenDatabase function. After a window has an open database, any number of plots and operators can be added. To create a plot, use the AddPlot function. After adding a plot, call the DrawPlots function to make sure that all of the new plots are drawn.
OpenDatabase("/usr/local/visit/data/multi_curv3d.silo") AddPlot("Pseudocolor", "u") DrawPlots()
To see a list of the available plots and operators when you use the VisIt Python Interface, use the Operator Plugins and Plot Plugins functions. Each of those functions returns a tuple of strings that contain the names of the currently loaded plot or operator plugins. Each plot and operator plugin provides a function for creating an attributes object to set the plot or operator attributes. The name of the function is the name of the plugin in the tuple returned by the OperatorPlugins or PlotPlugins functions plus the word “Attributes”. For example, the “Pseudocolor” plot provides a function called PseudocolorAttributes. To set the plot attributes or the operator attributes, first use the attributes creation function to create an attributes object. Assign the newly created object to a variable name and set the fields in the object. Each object has its own set of fields. To see the available fields in an object, print the name of the variable at the Python prompt and press the Enter key. This will print the contents of the object so you can see the fields contained by the object. After setting the appropriate fields, pass the object to either the SetPlotOptions function or the SetOperatorAttributes function.
OpenDatabase("/usr/local/visit/data/globe.silo") AddPlot("Pseudocolor", "u") AddOperator("Slice") p = PseudocolorAttributes() p.colorTableName = "rainbow" p.opacity = 0.5 SetPlotOptions(p) a = SliceAttributes() a.originType = a.Point a.normal, a.upAxis = (1,1,1), (-1,1,-1) SetOperatorOptions(a) DrawPlots()
That’s all there is to creating a plot using VisIt’s Python Interface. For more information on creating plots and performing specific actions in VisIt, refer to the documentation for each function later in this manual.