teda 2.1.0

TeDa FITS Viewer

TeDa FITS Viewer

Observatory optimized FITS Images viewer

Key Features

• Flexible windows and widgets layout
• WCS support
• Radial Profile with gaussoide fit (try r-key)
• Scan mode: observes directory for changes and automatically opens new FITS
• Integrated ipython console with direct access to data and application

Installation

   pip install teda
   teda_viewer 

Optional dependencies

To use ipython console the qtconsole package is needed, additionally:

    pip install qtconsole

For directory scanning functionality, the watchdog package should be installed, e.g.

    pip install watchdog

Run

The installation scripts should install the command:

    teda_viewer

Try

    teda_viewer --help

for list of command line parameters.

Dynamic Scale and Color

The dynamic scale of the image, and color mapping can be adjusted form the Dynamic Scale panel. From menu: View/Dynamic Scale

Fits Header Cards Pinning

On the FITS Header panel, selected keys can be pinned to appear on the top ot the list. This can be done via context (right-click) menu.

The set of pinned keys is saved and preserved between sessions.

Radial Profile

The Radial Profile button turns on the mode of selecting targets for the radial profile analysis. Make sure the radial profile panel is visible (View/Radial Profile). The shortcut for displaying radial profile of the star under cursor is the R-key.

The centroid of the star is corrected within small (be precise!) radius using the bivariate gaussoide fit.

Together with the pixels values, the radial profile presents 1D fit of "gaussian(r) + sky". This fit provides information of presented fwhm and sky level.

Integrated Python Console

In order to use integrated python console the qtconsole module, and it's dependencies (jupyter related) have to be installed. This is not done by default pip installation to keep number of dependencies reasonably small. Install qtconsole by:

    pip install qtconsole

The console is available form menu View/Python Console

Predefined variables

The console has a number of predefined variables set:

• ax: WCSAxesSubplot main plotting axes.
• window: MainWindow main window
• data: numpy.ndarray current HDU data
• header: astropy.fits.Header current HDU header
• wcs: astropy.wcs.WCS the WCS transformer

Plotting

To plot directly on the console, run the following magic command %matplotlib inline.

When plotting on the main canvas, the result will appear after redrawing main figure by ax.figure.canvas.draw().

The example below, draws linear profile on the console and corresponding line on the main FITS display:

%matplotlib inline
import matplotlib.pyplot as plt
ax.plot([10,30], [10,10])
ax.figure.canvas.draw()
plt.plot(data[10,10:30])

Directory Scan

The Scan Toolbar (hidden by default) provides controls for the directory scanning mode.

This mode is intended to observe newly created FITS files in observatory.

After pressing Scan button, and choosing directory, TeDa Fits Viewer will load most recent FITS file from that directory, and keep watching the directory for changes. When new FITS file is added to directory, it will be loaded automatically.

User can pause scanning using Pause button. There is also auto pause feature, when active, any mouse movement in the main area pauses scanning for 5 seconds, avoiding FITS reload when working.

After un-pausing (manually or after idle 5 seconds when auto-pause) the newest FITS will be loaded if any new files appeared during the pause.

Directory scanning needs the watchdog component to be installed manually (optional dependence).

Directory Panel

The Directory Panel can be shown using menu command View-Directory view.

The Directory Panel is convenient files navigator. The panel has two views:

• Directory Tree
• Files List

User can collapse any of them using divider handle and use only remaining one. If the tree view is the only visible, it shows directories and files as well.

Development version install

    git clone https://github.com/majkelx/teda.git
    cd teda
    python -m venv venv
    source ./venv/bin/activate
    pip install -r requirements.txt
    pip install -e .

Bugs, remarks, greetings and contribution

Please use GitHub issues tracker and pull requests.

@2020 AkondLab for the Araucaria Project.