PSM.prysm
Classes that implement PRYSM sensor models
Description
The PSM.prysm package implements classes that run PRYSM sensor models. Each class implements a specific PRSYM sensor model - the names of the classes in DASH match the names of the corresponding PSM module in PRYSM. A list of supported PRYSM forward models is given below.
Downloading
The PRYSM forward models are all contained in the same package. Thus, if you use the “PSM.download” command to download a specific forward models, then you will also download all the other forward models in the PRYSM suite.
Setting Up Prysm
The PRYSM forward models are written in Python, and so require some extra setup to run in Matlab. You will need to complete the following to run the PRYSM forward models in DASH:
Install Python 3.7, 3.8, or 3.9 directly on your computer. DO NOT use conda to install python, as Matlab is unable to locate Python within a conda distribution. Instead, download the language from python.org and install it.
Use pip to install numpy, and scipy. Do this in a terminal (and not the Matlab console). For example: $ pip install numpy $ pip install scipy
Use pip to install the PRYSM package. Again, this should be in your computer’s terminal, and not the Matlab console: $ pip install git+https://github.com/sylvia-dee/PRYSM.git
Within the Matlab console, initialize your Matlab session’s Python environment using the version of Python that contains PRYSM. Do this using the “pyenv” command. For example, if you are using Python 3.7, do: >> pyenv(‘Version’, ‘3.7’) After completing this steps, the PRYSM forward models should be ready to run in DASH.
Abstract Superclass
The individual PRYSM forward model classes inherit from the abstract superclass PSM.prysm.package. The main purpose of this superclass is to hold the Github information for the PRYSM forward models, as all the PRYSM forward models are located in the same Github repository.