What is Pints?
Pints (Probabilistic Inference on Noisy Time-Series) is a framework for optimisation and bayesian inference problems with ODE models of noisy time-series, such as arise in electrochemistry and cardiac electrophysiology.
To use a model with Pints, you need to make sure it extends the ForwardModel interface, which has just two methods:
n_parameters() --> Returns the dimension of the parameter space. simulate(parameters, times) --> Returns a vector of model evaluations at the given times, using the given parameters
If you use PINTS in any scientific work, please credit our work with a citation.
Examples and documentation
You'll need the following requirements:
- Python 2.7 or Python 3.4+
- Python libraries:
These can easily be installed using
pip. To do this, first make sure you have the latest version of pip installed:
$ pip install --upgrade pip
Then navigate to the path where you downloaded Pints to, and install both Pints and its dependencies by typing:
$ pip install .
Or, if you want to install Pints as a developer, use
$ pip install -e .[dev,docs]
To uninstall again, type
$ pip uninstall pints
Contributing to Pints
If you'd like to help us develop Pints by adding new methods, writing documentation, or fixing embarassing bugs, please have a look at these guidelines first.
Pints is fully open source. For more information about its license, see LICENSE.