Code for the Manifold Boundary Approximation Method
Project description
MBAM
Code for the Manifold Boundary Approximation Method
Install
Using pip
pip install mbam
From source
git clone https://github.com/mktranstrum/MBAM.git
pip install ./MBAM
Example
See examples.
-
Start by looking at
exp_example.py
. This script defines a simple model which is the sum of two exponentials sampled at 3 points. It defines a function to evaluate the model as well as its first and second derivatives with respect to the parameters. It then imports functions for solving the geodesic equation. It solves the geodesic equation and then plots the parameter values along the geodesic. The output of this script should be similar toexp_example.png
-
Next, consider the
MMR.py
which defines a model (a Michaelis-Menten reaction) by solving a nonlinear ordinary differential equation. This script defines a model by sampling by evaluating this model at three time points. It also defines functions for calculating first and second derivatives. Note that evaluating these derivatives involves solving the so-called sensitivity equations. Alternatively, they can be estimated using finite differences.
The scriptMMR_Plots.py
solves the geodesic equation for the MMR model and creates several plots to visualize the parameter space, parameter values along the geodesic, and the model manifold.
Attribution
Please cite Transtrum, Machta, and Sethna (2011) and Transtrum and Qiu (2014) if you find this code useful in your research.
License
mbam is free software distributed under the MIT License; see the LICENSE file for details.
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