astro_reduce -- A Simple CCD Images Reducer for the Paris Observatory.

What does astro_reduce do?

astro_reduce reduces raw astronomical CCD images read in FITS format with dark and flat field images. Optionally, it can interpolate missing dark fields from the ones available, and can also convert the intermediate and reduced images to PNG format for easy inspection.

To operate, astro_reduce is to be launched from a directory containing three folders:

• A DARK folder, containing all the dark field images,
• A FLAT folder, containing all flat field images,
• A ORIGINAL folder, containing all the images of objects.

All files must be in FITS format, with correct filter, exposure time and object header keywords wherever relevant.

When launched, astro_reduce will copy all data files to working folders (thereby backing up the original data), and apply the standard astronomical CCD image reduction process. On the way, intermediate images such as master dark fields or non-realigned object fields are safe-kept in the tmp/ folder.

After running, the final reduced images can be found in the reduced/ folder. The reduction process and the nomenclature for the naming of the files in the tmp/ and reduced/ folders are given in the Reduction method paragraph below.

Note: It is highly recommended to inspect the intermediate images produced by astro_reduce before considering the final reduced images. Also, we highly recommend you inspect your raw images and eliminate any bad ones before launching the reduction.

Installing

The astro_reduce program can be installed from the PyPI under the name astro-reduce. This package provides the command with all options.

Alternatively, use the setup.py file in the project directory with python3 setup.py install --user to install the program locally. You should then include ~/.local/bin (or ~/Library/Python/3.7/bin for Mac users) to your path in order to invoke astro_reduce from the console.

Dependencies

astro_reduce is written in Python 3.

astro_reduce depends on the click, astropy, numpy, scipy, packaging and matplotlib Python packages, which are all available through the PyPI. The matplotlib package in only necessary when using the --tmppng and redpng options; see the Options paragraph below for more details.

Usage

When used for the first time in a directory, or when the data has been modified since the last use of astro_reduce, the program should be invoked with the --setup option:

astro_reduce --setup [OPTIONS]

This will setup the reduction by copying all the raw data to astro_reduce's working folders whilst changing the file names to standardized formats. Also, during this phase, a configuration file in the JSON format will be written. It summarizes the objects, filters and exposures times present in the original data and is used by astro_reduce in the reduction process. This file should be left in the directory for further reference or for later rerunning of the program.

Note: This first setup step is effectively a back-up of your data, as the data left in the DARK, FLAT and ORIGINAL folders are no longer touched during the subsequent reduction process.

If the setup has already been done in the directory by prior use of the --setup option, astro_reduce should be used without this option:

astro_reduce [OPTIONS]

astro_reduce has been tested on Linux and Mac platforms, and has yet to be tested on Windows.

Options

• -s, --setup Sets up the directory for reduction. Use this option only the first time astro_reduce is run in the directory.
• -i, --interpolate Interpolate existing dark fields if some are missing.
• -v, --verbose Enables verbose mode (recommended).
• -t, --tmppng Write PNG format of intermediary images after reduction.
• -r, --redpng Write PNG format of reduced images after reduction.
• --help Show this message and exit.

Reduction method

Master dark images

For a given exposure time, the master dark is calculated as the pixel-wise median of all the dark fields of that exposure. This allows to eliminate cosmic ray traces.

Dark field interpolation

In the case where some dark fields are missing, astro_reduce can interpolate from the available master darks to obtain master darks for all the exposures necessary to reduce the object or flat images. This is done by specifying the --interpolate option.

The interpolation is least-square linear, i.e., two images A and B are determined from the available master dark images such as to minimize the square error on the linear interpolation (master dark) = (exposure time) x A + B.

Using these A and B, the missing master darks are calculated according to this equation.

The FITS files for all the master dark images (deduced from dark fields or interpolated) can be found after reduction in the tmp directory under the names mdark_[exposure].fits.

Master transmission images

The master transmission image for a given filter is an image which encompasses the relative transmission of each pixel in the optical setup (telescope optics through filter to CCD matrix). It is calculated for every filter as the median over all flat field images, after subtraction of corresponding master dark images and normalization.

The FITS files for all the master transmission images can be found after reduction in the tmp/ directory under the names mtrans_[filter].fits.

Individual image reduction

An object image of given exposure and filter is reduced by subtracting the corresponding exposure master dark image, and dividing by the corresponding filter master transmission image.

The FITS files for object obj, with filter filt and exposure time exp are found in the tmp/ folder after reduction, under the name [obj]_[filt]_[exp]_*_aux.fits (for auxiliary).

Realignment and reduction

Finally, for each series of same exposure and filter for each object, the auxiliary files are realigned through optimization of their mutual cross-correlations, and then their pixel-wise median image is calculated. Using the median rather than the mean allows to efficiently remove hot pixels. This will be all the more effective as dithering has been used in acquiring the images of a series.

These are the final reduced images and can be found in the reduced/ folder after reduction, with the same names as in the preceding step.

Some things to know

• As mentioned earlier, the original files in the DARK, FLAT and ORIGINAL folders are not used during the reduction process. Only their copies in the ar_* working folders are used.
• In copying the original files during the setup process, astro_reduce in effect backs up your data.
• astro_reduce will deduce the object captured in a given field from the OBJECT keyword entry in the file's header. In the reduction, all files of a same object, filter and exposure time are reduced and realigned together. Therefore, in order to keep different series of images of a same object separate, it is recommended to append a tag to the object name in acquiring the images of the series. For example NGC4993-1, NGC4993-2, etc.
• During the reduction, the headers of synthetic images are filled in with the correct OBJECT, FILTER, EXPOSURE, EXPTIME and IMAGETYP keyword values. The other keyword values (such as the time of acquisition) are inherited from the parent images (raw darks and flats for master dark and master transmission images; raw object images for final reduced object fields).
• fit and other derivatives can be used as extensions for the FITS files.
• Remaining hot pixels in the reduced images can be the result of insufficient dithering.