This book includes the following chapters:

- Chapter
*Introduction*gives a general overview of the DANA computing framework - Chapter
*Installation*explains how to install DANA on your machine. - Chapter
*Quick tour*gives a rapid overview of main concepts related to DANA. - Chapter
*From numpy array to dana group*explains conceptual differences between array and group. - Chapter
*Model and equations*explains what are model and equations and how to use them. - Chapter
*Connections*gives details on group connections - Chapter
*Learning*gives main concepts related to learning - Chapter
*Life and Death*explains what are dead units and dead connections - Chapter
*Time*details time management and timers - Chapter
*Advanced concepts*introduces advanced dana concepts - Chapter
*Examples*comments on examples from various scientific domain. - Chapter
*Application Programming Interface*Application Programming Interface - Chapter
*Frequently asked questions*gives answers to frequently asked questions - Chapter
*Glossary*explains terms used in this book - Chapter
*GNU Free Documentation License*explains what you can and cannot do with this book.

You should read this book if you intent to develop models using the DANA computing framework and especially if your models belong to the computational neuroscience domain. DANA is a python library and depends heavily on external library such as numpy and scipy. However, this book does not provide a tutorial to the python language neither an introduction to the numpy/scipy libraries. If you’re unfamiliar with both of them, you’encouraged to document yourself first by considering external resources for both python, numpy and scipy.

If you’re unfamiliar with python, have a look first at the very nice tutorial by Mark Pilgrim (which is also available as a book). Numpy user guide should gives you the main concepts related to vectorized computation while scipy tutorial may be considered optional but worth reading anyway.

**Python**

- Python website : http://www.python.org
- Python tutorial: http://diveintopython.org

**Numpy**

- Numpy website: http://numpy.scipy.org
- Numpy tutorial: http://docs.scipy.org/doc/numpy/user/
- Numpy manual: http://docs.scipy.org/doc/numpy/reference/

**Scipy**

- SciPy website: http://www.scipy.org
- SciPy tutorial: http://docs.scipy.org/doc/scipy/reference/tutorial/index.html
- SciPy manual: http://docs.scipy.org/doc/scipy/reference

A lot of examples are given throughout the book and the may be related to either a regular shell, a python shell or an ipython shell. You can easily distinguish them by the prompt they use:

**System shell**:

`$`

**Python/IPython shell**:

```
>>>
```

Furthemore, since numpy, scipy and matplotlib libraries are extensively used
throughout the whole book, they will respectively referred as `np`, `sp`,
and `plt` and are supposed to have been imported as:

```
>>> import numpy as np
>>> import scipy as sp
>>> import matplotlib.pyplot as plt
```

This book has been written using Sphinx and was last generated on February 14, 2012.