# Bumps 0.7.6 documentation

## Simple functions

Bumps allows fits with varying levels of complexity. Simple fits accept a function \(f(x;p)\) and data \(x,y,\sigma_y\), where vector \(y\) is the value measured in conditions \(x\), and \(\sigma_y\) is the \(1-\sigma\) uncertainty in the measurement. Bumps also provides a simple wrapper for poisson data taken from counting statistics, with function \(f(x;p)\) and data \(x,y\). sim.py is a simulation of data from a poisson process, showing maximum likelihood, expected value and variance.