pymosaic-fits 0.4.5

# pymosaics

[](https://badge.fury.io/py/pymosaic-fits) [](https://travis-ci.org/volodymyrss/pymosaics) [](https://codecov.io/gh/volodymyrss/pymosaics) [](https://lgtm.com/projects/g/volodymyrss/pymosaics/alerts/) [](https://lgtm.com/projects/g/volodymyrss/pymosaics/context:python)

__CAUTION__: this is a simple functional project, although it should work as generally expected, do make sanity checks and make sure you understand what the mosaic does - as usual. In particular, the re-pixelization approach (mapping/interpolation) is suitable for maps with flux density, as long as the pixels are smaller than PSF

Merge FITS file mosaic

• maps all images in the same pixels (taken from one of the images, or healpix)

• sums with a flexible algorithm

• output mosaics format is compatible with input - allowing map-reduce operations

  note that pixelization used for mosaic and for the output is not necessarily the same, i.e. for healpix it’s useful to have “regular” projection output.

  clearly, healpix pixels are useful primarily for all-sky.

## Installation

`bash $ pip install pymosaic-fits `

## Example:

`bash $ mosaic tests/data/isgri_sky_ima_{1,2}.fits.gz out.fits # just a normal mosaic, pixels/output from first image $ mosaic tests/data/isgri_sky_ima_{1,2}.fits.gz out.fits --mock # mock, to show assembly $ mosaic tests/data/isgri_sky_ima_{1,2}.fits.gz out.fits --pixels healpix # healpix pixels, projected output `

`python import mosaic mosaic.mosaic_fn_list(["tests/data/isgri_sky_ima_1.fits.gz", "tests/data/isgri_sky_ima_2.fits.gz"], "out.fits") `

## Additional mosaic analysis

Using https://github.com/astromatic/sextractor/ we provide some analysis, suitable for example for INTEGRAL ISGRI and JEMX mosaics: