<commit_before>.. holoviews documentation master file

Introduction
____________

**Composable, declarative data structures for building even complex visualizations easily.**


..
   # Code used to generate mandelbrot.npy, for reference
   from numpy import *
   import pylab

   def mandelbrot( h,w, maxit=200 ):
           y,x = ogrid[ -1.4:1.4:h*1j, -2:0.8:w*1j ]
           c = x+y*1j
           z = c
           divtime = maxit + zeros(z.shape, dtype=int)
           for i in xrange(maxit):
                   z  = z**2 + c
                   diverge = z*conj(z) > 2**2
                   div_now = diverge & (divtime==maxit)
                   divtime[div_now] = i
                   z[diverge] = 2
           return divtime
   # Wait a long while..then normalize
   arr = mandelbrot(4000,4000, maxit=2000)[400:800, 2500:2900]


..
  # Code needed to run the index.ipynb tutorial (add as two new cells at the top)
  
  cd ..

  import holoviews
  %load_ext holoviews.ipython
  %view holomap='widgets'
  import numpy as np


.. notebook:: holoviews index.ipynb


Installation
____________

HoloViews is compatible with Python `2.7, 3.3, and 3.4 <https://travis-ci.org/ioam/holoviews>`_.

HoloViews requires `Param <http://ioam.github.com/param/>`_ and
`Numpy <http://numpy.org>`_, neither of which has any required dependencies,
and so it should be very easy to integrate HoloViews into your
workflow or as part of another project.

For plotting, HoloViews uses `Matplotlib <http://http://matplotlib.org/>`_,
which most scientists and engineers using Python will already have
installed.  HoloViews is designed to work well with `IPython Notebook
<http://ipython.org/notebook/>`_ 2 and 3, although it can also be used
separately. 

Param, Matplotlib, and IPython Notebook can be installed using your
operating system's package manager, or by using pip::

  pip install matplotlib 'ipython[notebook]'
  pip install --user https://github.com/ioam/param/archive/master.zip

You can then obtain the latest version of HoloViews by cloning the git
repository::

  git clone git://github.com/ioam/holoviews.git<commit_msg>Updated installation instructions on the homepage<commit_after>.. holoviews documentation master file

Introduction
____________

**Composable, declarative data structures for building even complex visualizations easily.**


..
   # Code used to generate mandelbrot.npy, for reference
   from numpy import *
   import pylab

   def mandelbrot( h,w, maxit=200 ):
           y,x = ogrid[ -1.4:1.4:h*1j, -2:0.8:w*1j ]
           c = x+y*1j
           z = c
           divtime = maxit + zeros(z.shape, dtype=int)
           for i in xrange(maxit):
                   z  = z**2 + c
                   diverge = z*conj(z) > 2**2
                   div_now = diverge & (divtime==maxit)
                   divtime[div_now] = i
                   z[diverge] = 2
           return divtime
   # Wait a long while..then normalize
   arr = mandelbrot(4000,4000, maxit=2000)[400:800, 2500:2900]


..
  # Code needed to run the index.ipynb tutorial (add as two new cells at the top)
  
  cd ..

  import holoviews
  %load_ext holoviews.ipython
  %view holomap='widgets'
  import numpy as np


.. notebook:: holoviews index.ipynb


Installation
____________

HoloViews is compatible with Python `2.7, 3.3, and 3.4 <https://travis-ci.org/ioam/holoviews>`_.

HoloViews requires `Param <http://ioam.github.com/param/>`_ and
`Numpy <http://numpy.org>`_, neither of which has any required dependencies,
and so it should be very easy to integrate HoloViews into your
workflow or as part of another project.

For plotting, HoloViews uses `Matplotlib <http://http://matplotlib.org/>`_,
which most scientists and engineers using Python will already have
installed.  HoloViews is designed to work well with `IPython Notebook
<http://ipython.org/notebook/>`_ 2 and 3, although it can also be used
separately. 

Param, Matplotlib, and IPython Notebook can be installed using your
operating system's package manager, or by using pip::

  pip install matplotlib 'ipython[notebook]'
  pip install https://github.com/ioam/param/archive/master.zip

You can then obtain the latest version of HoloViews by cloning the git
repository::

  git clone git://github.com/ioam/holoviews.git

Alternatively, you may install the development version using pip::

  pip install https://github.com/ioam/holoviews/archive/master.zip

We plan to have a full PyPI release of HoloViews within the next week.


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