racecar 0.0.3

A lightweight Bayesian sampling package

A Python package collecting awesome sampling algorithms.
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Table of Contents

• Features
• Examples
• Installation
• License
• Contact

Examples

Simple example

We will sample points from the distribution using racecar and plot the results.

# Import racecar and numpy
import racecar as rc
import numpy as np

# Define the log likelihood function
def llh(x):
  return {
  'llh' : -( np.cos(2*x) + x**2/12 )
  }

# Create the sampler object and use Random Walk Metropolis
initial_condition = [0]
learning_rate = 0.5
S = rc.sampler(initial_condition, learning_rate, llh, algo="RWMetropolis")

# Sample some points, outputting arrays of position and log likelihood
Pos_traj, LLH_traj = S.sample(100000, output=['pos','llh'])

# Plot the results using matplotlib

More examples

Some more detailed examples are given in detailed Jupyter notebooks below

• Example 1
• Example 2
• Example 3

Installation

You can install the package from source by cloning this repo and using setup.py, the only dependencies are on numpy and scipy. Otherwise it is available on pip via

pip install racecar

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Made by Charles Matthews - www.cmatthe.ws - [e-mail]

Project Link: https://github.com/c-matthews/racecar