ztv 0.2.3.post4
Simple python image viewer, largely intended for astronomical applications
License: MIT License
Keywords: astronomy image viewer fits

*ztv* - astronomical image viewer
=================================

*ztv* is an astronomical image viewer designed to be used from a python
command line for display and analysis.

*ztv* is useful as-is for display and simple analysis of images already
loaded in to `numpy arrays <http://www.numpy.org>`__, as well as `FITS
files <http://fits.gsfc.nasa.gov/fits_primer.html>`__. It can display
the most recently acquired image by watching a directory for new FITS
files to appear or watching a single FITS file for when it changes. It
can also receive new images via an `ActiveMQ message
stream <http://activemq.apache.org>`__.

*ztv* is intended for real-time display and analysis. *ztv* is not
intended to produce publication quality figures.

*ztv* comes with a number of built-in control panels, for: - selecting
input source (FITS file, auto-reload from FITS file, etc) - selecting a
frame to subtract (e.g. sky or dark) and a flat field frame to divide by
- setting colormap, stretch, and lower/upper limits - doing basic slice
plots, statistics, and aperture photometry. Additional panels can be
written and added, for e.g. controlling a camera. (One example add-on
panel is included that generates faked images in the FITS format.)

If proper FITS header keywords are available, *ztv* will display the
ra/dec of the cursor point.

Examples of usage
=================

To launch:

::

    import ztv
    z = ztv.ZTV()

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/default.png
   :alt: 

To load an image in a numpy array:

::

    import numpy as np
    im = np.random.normal(size=[10, 256, 256])  # create a 3-d image stack
    z.load(im)

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/random_noise1.png
   :alt: 

You can now look at your data, manipulate display parameters, etc all
using the gui elements. All of these elements are accessible through the
tabbed control panels. You can also switch amongst the control panel
tabs by ``cmd-alt-#`` where *#* is the number of the panel, starting
from 1. Or, by ``cmd-[`` and ``cmd-]`` to move left/right amongst the
tabs. You can even switch tabs from the command line api, e.g.:

::

    z.control_panel('Color')

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/random_noise2.png
   :alt: 

To change cursor mode, press ``cmd-#`` where *#* is the number shown in
the pop-up menu that's available by right-clicking in the primary image
area:

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/popup_menu.png
   :alt: 

To manipulate display parameters:

::

    z.cmap('gist_heat')
    z.minmax(0., 4.)
    z.scaling('Sqrt')
    z.xy_center(100, 100)
    z.zoom(5.)

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/random_noise3.png
   :alt: 

To set up a statistics box and see the GUI output (note that output is
also returned to your command line as a dict):

::

    z.stats_box(xrange=[80, 100], yrange=[100,120], show_overplot=True)
    z.control_panel('Stats')

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/random_noise4.png
   :alt: 

There's a lot more you can do from the command line if you play with
*ztv*, especially in an exploration-friendly environment like
`ipython <http://ipython.org/>`__. And, anything you can do from the
command line can be done from the GUI.

Download an iconic FITS image from the web and display it:

::

    from urllib import urlopen
    from zipfile import ZipFile
    from StringIO import StringIO
    remote_url = 'http://www.spacetelescope.org/static/projects/fits_liberator/datasets/eagle/656nmos.zip'
    local_filename = '/tmp/hst-eagle-nebula-656nmos.fits'
    zip = ZipFile(StringIO(urlopen(remote_url).read()))
    zip_filename = zip.filelist[0].filename
    open(local_filename, 'w').write(zip.open(zip_filename).read())
    z.load(local_filename)
    z.scaling('Log')
    z.minmax(0, 500)

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/eagle1.png
   :alt: 

We can even do a little aperture photometry while we're here:

::

    z.cmap('gray')
    z.xy_center(624, 524)
    z.zoom(4)
    z.minmax(0, 1000)
    z.scaling('Asinh')
    z.control_panel('phot')
    z.aperture_phot(xclick=614, yclick=516, show_overplot=True)

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/eagle2.png
   :alt: 

And, of course, you can adjust the window size to suit your needs,
either smaller:

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/eagle-small.png
   :alt: 

or larger:

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/eagle-large.png
   :alt: 

Example of an Add-on Control Panel
----------------------------------

One of the motivating use cases for *ztv* was real-time quick-look of
incoming images and the ability to extend the basic installation,
including instrumentat control. An example of this is that *ztv* will be
used to both control and inspect the images from a slit viewing camera
on a spectrograph of mine. To demonstrate this extensibility, there's a
simple example in ``ztv_examples/fits_faker_panel/``:

::

    from ztv_examples.fits_faker_panel.launch_ztv import launch_ztv
    z = launch_ztv()
    z.start_fits_faker()

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/faker1.png
   :alt: 

Our fake example data looks a lot better when we subtract the sky and
divide the flat field (someone needs to blow the dust off that fake
dewar window...):

::

    z.control_panel('Source')
    z.sky_frame(True)
    z.flat_frame(True)

.. figure:: https://raw.githubusercontent.com/henryroe/ztv/master/screenshots/faker2.png
   :alt: 

Installation and Dependencies
=============================

*ztv* uses several packages, including
`wxPython <http://wxpython.org>`__,
`astropy <http://www.astropy.org>`__. These should be automatically
installed if you install *ztv* from
`pypi <https://pypi.python.org/pypi/ztv>`__ with:

::

    pip install ztv

You can also grab source code from
`github <https://github.com/henryroe/ztv>`__.

Note that *ztv* was developed and tested on OS X.

Example of installation using Mac OS X's included Python
--------------------------------------------------------

The following steps worked on a fresh install of OS X Yosemite 10.10.5
on 2015-09-06:

-  Install Xcode from the App Store
-  Launch Xcode one time to accept licenses
-  Install pip and other necessary python packages

Run following command lines in a terminal:

::

    curl -o ~/Downloads/get-pip.py https://bootstrap.pypa.io/get-pip.py
    sudo -H python ~/Downloads/get-pip.py
    sudo -H pip install matplotlib
    sudo -H pip install astropy
    sudo -H pip install astropy-helpers

-  Install wxPython version 3

   -  Download `OS X cocoa version of wxPython version 3 from
      here <http://wxpython.org/download.php#osx>`__ (was
      *wxPython3.0-osx-docs-demos-3.0.2.0-cocoa-py2.7.dmg* at time of
      writing)
   -  Open disk image and install with the following command line
      command:

(This is necessary because package isn't properly signed & is an
old-style package, see
`here <http://stackoverflow.com/questions/21223717/install-wxpython-on-mac-os-mavericks>`__.
Obviously may need to update exact file path to the pkg.)

::

    sudo installer -pkg /Volumes/wxPython3.0-osx-3.0.2.0-cocoa-py2.7/wxPython3.0-osx-cocoa-py2.7.pkg -target /

Finally, install *ztv*:

::

    sudo -H pip install ztv

Example of installation into anaconda python distribution
---------------------------------------------------------

The following was tested on a fresh install of OS X 10.10.5 on
2015-09-08.

Install Xcode from the App Store and launch Xcode one time to accept its
licenses.

Download
`Anaconda-2.3.0-MacOSX-x86\_64.sh <http://continuum.io/downloads>`__
from here.

::

    bash Anaconda-2.3.0-MacOSX-x86_64.sh
    source ~/.bash_profile
    conda create --name ztv-test wxpython matplotlib
    source activate ztv-test
    pip install ztv

Example of installation into a Homebrew python distribution
-----------------------------------------------------------

The following was tested on a fresh install of OS X 10.10.5 on
2015-09-07.

Install Xcode from the App Store and launch Xcode one time to accept its
licenses.

Install `Homebrew <http://brew.sh/>`__ with the one-line ruby command on
`Homebrew's home page <http://brew.sh/>`__

Install python & other necessary bits with the following commands.

::

    brew install python
    brew install wxpython
    pip install numpy
    pip install ztv

Note that ``numpy`` is explicitly installed first using
``pip install numpy`` before ``ztv`` is installed. During testing on OS
X 10.10.5 on 2015-09-07 allowing the numpy dependency to be
automatically filled by ``pip install ztv`` resulted in an installation
error that does not occur if you follow the above sequence.

Linux/Ubuntu
------------

I tested briefly on Ubuntu 14.04. *ztv* basically works, although the
pulldown colormap menus will not have bitmaps of the colormaps. Also,
(at least on my testing virtual machine) the performance of *ztv* was
much laggier than on my main OS X laptop. For the colormaps you could
try looking at `this
link <http://askubuntu.com/questions/464146/how-to-enable-icons-in-menus-in-ubuntu-14-04>`__,
but it didn't work on my test system.

Background
==========

In graduate school in the late 1990's I learned
`IDL <http://en.wikipedia.org/wiki/IDL_(programming_language)>`__ and
used `Aaron Barth's ATV <http://www.physics.uci.edu/~barth/atv/>`__
extensively. I even contributed a little to a now-outdated version of
`ATV <http://www.physics.uci.edu/~barth/atv/>`__, adding 3-d image stack
capability. `ATV <http://www.physics.uci.edu/~barth/atv/>`__ was and is
incredibly useful for quick-looks at image data, analysis, and all the
things you want when working with typical astronomical image data.

After graduate school I began migrating toward python and away from IDL.
I've written about this choice elsewhere, but some of the basic reasons
were to avoid IDL licensing issues and being beholden to one company.
(To be fair, how much I pay every year to keep my IDL license current
has always been reasonable. It helps that my license has some obscure
history to it that makes the maintenance fees moderate. But, at any time
they could raise the prices on me massively. And, I wanted to use a
language that could effectively be on every machine I touch, from my
main laptop to an embedded server.)

In python there are already a multitude of possible image viewers. Many
of which are great and can do much of what I needed. (See next section
for some links.) But, inevitably as I've played with them I've found
they each doesn't scratch my itch in some way. I wanted something that
worked exactly the way I wanted, with the right (for me) mix of
complexity and simplicity. I need day-to-day image quicklook from the
python command-line, e.g. while I'm developing some new image processing
algorithm or to check on last night's data. But, I also need to be able
to easily adapt my viewer to other situations, including real-time use
on a slit-viewing camera, quick-reduction of incoming data, etc.. So, I
wrote *ztv*.

The name *ztv* is an obvious play off of
`ATV <http://www.physics.uci.edu/~barth/atv/>`__. And, "z" is my
daughter's middle initial.

Other Image Viewers You Should Check Out
========================================

-  If you're using IDL, check out
   `ATV <http://www.physics.uci.edu/~barth/atv/>`__ of course!
-  `SAOImage DS9 <http://ds9.si.edu/site/Home.html>`__
-  `Aladin Desktop Sky Atlas <http://aladin.u-strasbg.fr>`__ (not
   primarily an image viewer, but can open FITS files and overlay
   catalogs and other images nicely)
-  `ginga <http://ejeschke.github.io/ginga/>`__
-  `Toyz <http://fred3m.github.io/toyz/>`__

(If your favorite isn't on this list, please email hroe@hroe.me to get
it added.)

Acknowledgements
================

Thank you to Aaron Barth for his original
`ATV <http://www.physics.uci.edu/~barth/atv/>`__. Thank you to all the
numerous people who have put so much effort in to all the packages that
make my work not only easier but possible. I especially thank the
developers of `astropy <http://www.astropy.org>`__ and its associated
packages. e.g. It's an amazing thing to do correct FITS coordinate
conversions in one line of code.

Author
======

Henry Roe (hroe@hroe.me)

License
=======

*ztv* is licensed under the MIT License, see ``LICENSE.txt``. Basically,
feel free to use any or all of this code in any way. But, no warranties,
guarantees, etc etc..