This repository is an updated version of an earlier blog post (http://www.mathcancer.org/blog/paraview-for-physicell-part-1/)
In this tutorial, we discuss the topic of visualizing data that is generated by PhysiCell. Specifically, we discuss the visualization of cells. In a later post, we’ll discuss options for visualizing the microenvironment. For 2-D models, PhysiCell generates Scalable Vector Graphics (SVG) files that depict cells’ positions, sizes (volumes), and colors (virtual pathology). Obviously, visualizing cells from 3-D models is more challenging. (Note: SVG files are also generated for 3-D models; however, they capture only the cells that intersect the Z=0 plane). Until now, we have only discussed a couple of applications for visualizing 3-D data from PhysiCell: MATLAB (or Octave) and POV-Ray. In this post, we describe ParaView: an open source, data analysis and visualization application from Kitware. ParaView can be used to visualize a wide variety of scientific data, as depicted on their gallery page (https://www.paraview.org/gallery).
Before we get started, just a reminder – if you have any problems or questions, please post a ticket to https://sourceforge.net/projects/physicell/. In preparation for using the customized PhysiCell data reader in ParaView, you will need to have a specific Python module, scipy, installed. Python will be a useful language for other PhysiCell data analysis and visualization tasks too, so having it installed on your computer will come in handy later, beyond using ParaView. The confusion of installing/using Python (and the scipy module) for ParaView is due to multiple factors:
- you may or may not have Administrator permission on your computer,
- there are different versions of Python, including the major version confusion – 2 vs. 3,
- there are different distributions of Python, and
- ParaView comes with its own built-in Python (version 2), but it isn’t easily extensible.
Before we get operating system specific, we just want to point out that it is possible to have multiple versions and/or distributions of Python on your computer. Unfortunately, there is no guarantee that you can mix modules of one with another. This is especially true for one popular Python distribution, Anaconda, and any other distribution.
We now provide some detailed instructions for the primary operating systems. In the sections that follow, we assume you have Admin permission on your computer. If you do not and you need to install Python + scipy as a standard user, see Appendix A at the end.