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Implementation of a grammar of model analysis (grama). See the documentation for more info.


Grama is a grammar of model analysis---a Python package that supports building and analyzing models with quantified uncertainties. This language is heavily inspired by the Tidyverse. Grama provides convenient syntax for building a model (with functions and distributions), generating data, and visualizing results. The purpose of this language is to support scientists and engineers learning to handle uncertainty, and to improve documentation + reproducibility of results.

Uncertainty Quantification (UQ) is the science of analyzing uncertainty in scientific problems and using those results to inform decisions. UQ has important applications to building safety-critical engineering systems, and to making high-consequence choices based on scientific models. However, UQ is generally not taught at the undergraduate level: Many engineers leave their undergraduate training with a purely deterministic view of their discipline, which can lead to probabilistic design errors that negatively impact safety. To that end, Grama is designed to facilitate rapid model analysis, communication of results, and the teaching of concepts, all with quantified uncertainties. Intended users of Grama are scientists and engineers at the undergraduate level and upward, seeking to analyze computationally-lightweight models.


Quick install:

$ pip install py-grama

For a manual install clone this repo, change directories and run the following to install dependencies. (Note: I recommend Anaconda as a Python distribution; it takes care of most of the dependencies.)

$ git clone
$ cd py_grama/
$ pip install -r requirements.txt
$ pip install .

Run the following to check your install:

$ python
> import grama

Quick Tour

py_grama has tools for both building and analyzing models. For a quick look at functionality, see the following notebooks:


The tutorials page has educational materials for learning to work with py_grama.

Support and Contributing

If you are seeking support or want to contribute, please see Contributing.

Cite As

If you find Grama useful in your work, we'd appreciate that you cite it as:

del Rosario, Z., (2020). Grama: A Grammar of Model Analysis. Journal of Open Source Software, 5(51), 2462,

Bibtex code:

@article{del Rosario2020,
  doi = {10.21105/joss.02462},
  url = {},
  year = {2020},
  publisher = {The Open Journal},
  volume = {5},
  number = {51},
  pages = {2462},
  author = {Zachary del Rosario},
  title = {Grama: A Grammar of Model Analysis},
  journal = {Journal of Open Source Software}