<commit_before>*******************************
Image reprojection (resampling)
*******************************

Introduction
============

The *reproject* package implements image reprojection (resampling) methods
for astronomical images and more generally n-dimensional data. These assume
that the WCS information contained in the data are correct. This package does
**not** do image registration, which is the process of aligning images where
one or more images may have incorrect or missing WCS.

Requirements
============

This package has the following hard dependencies:

* `Numpy <http://www.numpy.org/>`__ 1.7 or later

* `Astropy <http://www.astropy.org/>`__ 1.0 or later

* `Scipy <http://www.scipy.org/>`__ 0.9 or later

and the following optional dependencies:

* `healpy <https://healpy.readthedocs.io>`_ 1.8 or later for HEALPIX image reprojection

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

To install the *reproject* package, simply do::

    pip install reproject

.. _quickstart:

Quick start
===========

A common use case is that you have two FITS images, and want to reproject one
to the same header as the other. This can easily be done with the *reproject*
package, and we demonstrate this in the following example. We start off by
downloading two example images from `http://data.astropy.org <http://data.astropy.org>`_,
namely a 2MASS K-band image and an MSX band E image of the Galactic center::

    from astropy.io import fits
    from astropy.utils.data import get_pkg_data_filename
    hdu1 = fits.open(get_pkg_data_filename('galactic_center/gc_2mass_k.fits'))[0]
    hdu2 = fits.open(get_pkg_data_filename('galactic_center/gc_msx_e.fits'))[0]<commit_msg>Adding the build and test dependencies and also conda as a way to install<commit_after>*******************************
Image reprojection (resampling)
*******************************

Introduction
============

The *reproject* package implements image reprojection (resampling) methods
for astronomical images and more generally n-dimensional data. These assume
that the WCS information contained in the data are correct. This package does
**not** do image registration, which is the process of aligning images where
one or more images may have incorrect or missing WCS.

Requirements
============

This package has the following hard run time dependencies:

* `Numpy <http://www.numpy.org/>`__ 1.7 or later

* `Astropy <http://www.astropy.org/>`__ 1.0 or later

* `Scipy <http://www.scipy.org/>`__ 0.9 or later

and the following optional dependencies:

* `healpy <https://healpy.readthedocs.io>`_ 1.8 or later for HEALPIX image reprojection

If you build the package from the source, the following additional packages
are required:

* `Cython <http://cython.org>`__

and to run the tests:

* `Matplotlib <http://matplotlib.org/>`__

* `pytest-arraydiff <https://github.com/astrofrog/pytest-fits>`__


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

Using pip
---------

To install *reproject* with `pip <http://www.pip-installer.org/en/latest/>`_,
simply run:

    pip install reproject

Using conda
-----------

To install *reproject* with `anaconda <https://continuum.io/>`_, simply run::

    conda install -c astropy reproject

.. _quickstart:

Quick start
===========

A common use case is that you have two FITS images, and want to reproject one
to the same header as the other. This can easily be done with the *reproject*
package, and we demonstrate this in the following example. We start off by
downloading two example images from `http://data.astropy.org <http://data.astropy.org>`_,
namely a 2MASS K-band image and an MSX band E image of the Galactic center::

    from astropy.io import fits
    from astropy.utils.data import get_pkg_data_filename
    hdu1 = fits.open(get_pkg_data_filename('galactic_center/gc_2mass_k.fits'))[0]
    hdu2 = fits.open(get_pkg_data_filename('galactic_center/gc_msx_e.fits'))[0]
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