As a result, the full name of each coordinate variable should be coord/x, coord/y and coord/z. For the mentioned example in this document, the mesh should be defined as:Īs the above definition shows, the group name is coord and 3 different variables, namely x, y and z are defined inside it. Each mesh in Damaris configuration file includes a name, its type, its dimensions and the list of variables associated to each dimension. Ghosts are not implemented in the current version of Damaris (1.5.0) yet.Ī mesh (or grid) defines how data elements in a variable should be distributed in a 2D or 3D space.
In this case, the type is defined as double.
The type of the layout determines the type of each data element.To do so, we can define the following parameters in the xml file:
To make the xml configuration file more flexible, it is better to define every important data item as an parameter. To do so, doing the following steps is necessary: 1. The decomposition will happen over the Z axis, as a result, each process will work on a 3D array with the dimensions of (100, 100, 100/size). Suppose that you are going to decompose a 3D array with 100x100x100 dimensions over some processes (let’s say the number of processes is size). Please note that in the current version of ParaView backend for Damaris (version 1.3.0), only rectilinear and curvilinear meshes are supported. We will describe them once more in this tutorial with an example. Description of meshes, fields and variablesĭefinition of meshes, fields and variables is as same as the ones that were described for VisIt connector here. /path/to/the/first/script1.py /path/to/the/first/script2.py To do that, it is necessary to create a tag in the xml configuration file and mention the Python script files like this: The Python scripts should be introduced in the same file as well. In the context of Damaris, ParaView should be enabled in the xml configuration files. Afterwards, the dedicated core(s) load the Python scripts and use the steps inside each script to process data. In this context, simulation processes pass the datasets to the dedicated core(s) using shared memory. The mentioned Python scripts are used in the same way within Damaris too. These scripts, include necessary steps to produce images, generate plots, and also extract derived information such as polygonal data in support of in situ processing and visualization. During the simulation execution, any analysis and visualization output is generated in synchronous fashion (i.e., while the simulation is running). When using ParaView Catalyst in support of in situ data analysis and visualization without Damaris, the instrumented simulation starts loading a set of Python scripts.
PARAVIEW SCRIPTING CODE
It has an accompanying Catalyst script code ( image.py) and Damaris configuration file ( image.xml). Example codeĪ working example that closely matches the following description is available in the /examples/paraview directory, of either the git repository or installed if Damaris was configured with -DENABLE_EXAMPLES=ON and is named image.cpp. As a result, it is recommended to check the in situ visualization with VisIt documentation before working through this tutorial. Note 2: In situ visualization with VisIt and ParaView in Damaris are quite similar. Damaris v1.3.1+ has been tested with 5.5.0 and 5.8.0 of Paraview. Note 1: The first version of ParaView backend for Damaris (Damaris 1.3.0), has been developed and tested with ParaView 5.5.0. Also, please ensure that the version of Paraview that Damaris is compiled against matches the Paraview being used for visualization of the simulation exactly.
PARAVIEW SCRIPTING INSTALL
Please note that if you are going to have your simulation and visualization in two different nodes, it is recommended not to install ParaView GUI on simulation nodes. You may use this link to install ParaView in your machine. In order to benefit from ParaView connector that has been implemented in Damaris, it is necessary to build Damaris on a machine that ParaView Catalyst is already installed.
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