<commit_before>pvlib-python
============

[![TravisCI](https://travis-ci.org/pvlib/pvlib-python.svg?branch=master)](https://travis-ci.org/pvlib/pvlib-python)
[![Coverage Status](https://img.shields.io/coveralls/pvlib/pvlib-python.svg)](https://coveralls.io/r/pvlib/pvlib-python)
[![Documentation Status](https://readthedocs.org/projects/pvlib-python/badge/?version=latest)](http://pvlib-python.readthedocs.org/en/latest/)


pvlib-python provides a set of documented functions for simulating the performance of photovoltaic energy systems. The toolbox was originally developed in MATLAB at Sandia National Laboratories and it implements many of the models and methods developed at the Labs. More information on Sandia Labs PV performance modelling programs can be found at https://pvpmc.sandia.gov/. 

Documentation
=============

Full documentation can be found at [readthedocs](http://pvlib-python.readthedocs.org/en/latest/)

Quick Start
===========

Installation
------------
Hopefully you're using [virtualenv](http://virtualenv.readthedocs.org/en/latest/) and [virtualenvwrapper](http://virtualenvwrapper.readthedocs.org). To install, run

```
pip install git+https://github.com/pvlib/pvlib-python.git
```

Alternatively, ``git clone`` this repository, ``cd`` into it, and run

```
pip install .
```

Add ``-e`` to install in [develop mode](http://pip.readthedocs.org/en/latest/reference/pip_install.html#editable-installs).

``pvlib-python`` comes with Python bindings for NREL's solar position C code,
however you must manually download the C code directly from [NREL](http://www.nrel.gov/midc/spa/).
To use the NREL SPA algorithm,

1. Download the SPA files from [NREL](http://www.nrel.gov/midc/spa/)
2. Copy the SPA files into ``pvlib/spa_c_files``
3. From this ``pvlib-python`` directory, run ``pip install .``

Usage Example
-------------
```
# built-in imports
import sys
import datetime

# add-on imports
import pandas as pd

# pvlib imports
from pvlib.location import Location
import pvlib.solarposition
import pvlib.clearsky

# make a location
tus = Location(32.2, -111, 'MST', 700)
<commit_msg>fix install instruction<commit_after>pvlib-python
============

[![TravisCI](https://travis-ci.org/pvlib/pvlib-python.svg?branch=master)](https://travis-ci.org/pvlib/pvlib-python)
[![Coverage Status](https://img.shields.io/coveralls/pvlib/pvlib-python.svg)](https://coveralls.io/r/pvlib/pvlib-python)
[![Documentation Status](https://readthedocs.org/projects/pvlib-python/badge/?version=latest)](http://pvlib-python.readthedocs.org/en/latest/)


pvlib-python provides a set of documented functions for simulating the performance of photovoltaic energy systems. The toolbox was originally developed in MATLAB at Sandia National Laboratories and it implements many of the models and methods developed at the Labs. More information on Sandia Labs PV performance modelling programs can be found at https://pvpmc.sandia.gov/. 

Documentation
=============

Full documentation can be found at [readthedocs](http://pvlib-python.readthedocs.org/en/latest/)

Quick Start
===========

Installation
------------
Hopefully you're using [virtualenv](http://virtualenv.readthedocs.org/en/latest/) and [virtualenvwrapper](http://virtualenvwrapper.readthedocs.org). To install, run

```
pip install git+https://github.com/pvlib/pvlib-python.git
```

Alternatively, ``git clone`` this repository, ``cd`` into it, and run

```
pip install .
```

Add ``-e`` to install in [develop mode](http://pip.readthedocs.org/en/latest/reference/pip_install.html#editable-installs).

``pvlib-python`` comes with Python bindings for NREL's solar position C code,
however you must manually download the C code directly from [NREL](http://www.nrel.gov/midc/spa/).
To use the NREL SPA algorithm,

1. Download the SPA files from [NREL](http://www.nrel.gov/midc/spa/)
2. Copy the SPA files into ``pvlib/spa_c_files``
3. From this ``pvlib-python`` directory, run ``pip install . -I --no-deps``

Usage Example
-------------
```
# built-in imports
import sys
import datetime

# add-on imports
import pandas as pd

# pvlib imports
from pvlib.location import Location
import pvlib.solarposition
import pvlib.clearsky

# make a location
tus = Location(32.2, -111, 'MST', 700)

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