sampling from univariate distributions

## Project description

==============
samplepy 1.0.10
==============

**samplepy** implements three sampling methods for univariate distributions. The package includes:

- Importance sampling: **samplepy.Importance**
- Rejection sampling: **samplepy.Rejection**
- Metropolis-Hastings sampling: **samplepy.MH**

Examples:
=========

.. code:: python

from samplepy import Rejection
import matplotlib.pyplot as plt
import numpy as np

"""
Rejection sampling example from 2 different functions
"""
# define a unimodal function to sample under
f = lambda x: 2.0*np.exp(-2.0*x)
rej = Rejection(f, [0.01, 3.0]) # instantiate Rejection sampling with f and interval
sample = rej.sample(10000, 1) # create a sample of 10K points

x = np.arange(0.01, 3.0, (3.0-0.01)/10000)
fx = f(x)

figure, axis = plt.subplots()
axis.hist(sample, normed=1, bins=40)
axis2 = axis.twinx()
axis2.plot(x, fx, 'g', label="f(x)=2.0*exp(-2*x)")
plt.legend(loc=1)
plt.show()

More examples and package documentation can be found at <https://github.com/elena-sharova/samplepy/blob/master/README.rst>

Installation
===============

::

pip install samplepy

## Project details

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