Fit supernova + galaxy model on a Nearby Supernova Factory spectral data cube.

To install a release version:

pip install http://github.com/snfactory/cubefit/archive/v0.2.0.tar.gz

Release versions are listed here. CubeFit has the following dependencies:

• Python 2.7 or 3.3+
• numpy
• scipy (for optimization)
• fitsio (for FITS file I/O)
• pyfftw (for fast FFTs)

Fit the model, write output to given file:

cubefit config.json output.fits

Producing subtracted data cubes is a separate step:

cubefit-subtract config.json output.fits

This reads the input and output filenames listed in the configuration file, and the results of the fit saved in output.fits.

With either command, you can run with -h or --help options to see all the optional arguments: cubefit --help.

CubeFit requires the following keys in the input JSON file. Keys are case-sensitive. Additional keys are simply ignored.

Parameter only used in cubefit-subtract:

NOTE: the meaning of xcenters and ycenters is different than in DDT config files!

CubeFit outputs a FITS file with two extensions.

• HDU 1: (image) Full galaxy model. E.g., a 32 x 32 x 779 array.

• HDU 2: (binary table) Per-epoch results. Columns:

  • yctr Fitted y position of data in model frame
  • xctr fitted x position of data in model frame
  • sn (1-d array) fitted SN spectrum in this epoch
  • sky (1-d array) fitted sky spectrum in this epoch
  • galeval (3-d array) Galaxy model evaluated on this epoch (e.g., 15 x 15 x 779)
  • sneval (3-d array) SN model evaluated on this epoch (e.g., 15 x 15 x 779)

• The HDU 1 header contains the wavelength solution in the "CRPIX3", "CRVAL3", "CDELT3" keywords. These are simply propagated from input data cubes.

• The HDU 2 header contains the fitted SN position in the model frame in the "SNX" and "SNY" kewords.

Here is an example demonstrating how to reproduce the full model of the scene for the first epoch:

>>> import fitsio
>>> f = fitsio.FITS("PTF09fox_B.fits")
>>> f[1]

  file: PTF09fox_B.fits
  extension: 1
  type: BINARY_TBL
  extname: epochs
  rows: 17
  column info:
    yctr                f8  
    xctr                f8  
    sn                  f4  array[779]
    sky                 f4  array[779]
    galeval             f4  array[15,15,779]
    sneval              f4  array[15,15,779]

>>> epochs = f[1].read()
>>> i = 0
>>> scene = epochs["sky"][i, :, None, None] + epochs["galeval"][i] + epochs["sneval"][i]

The data

The data are N 3-d cubes, where N are observations at different times (typically N ~ 10-30). Each cube has two spatial directions and one wavelength direction (typical dimensions 15 x 15 x 800). Each cube has both a data array and a corresponding weight (error) array.

The model

The model parameters consist of:

• 3-d galaxy model ("unconvolved"). Default size is approximately 32 x 32 x 800, where the pixel size of the model matches that of the data (both spatially and in wavelength) but the model extends past the data spatially.
• N 1-d sky spectra
• N 1-d supernova spectra
• position of each of the N data cubes relative to a "master final ref": 2 x (N-1) parameters
• position of the SN in the "master final ref" frame of reference: 2 parameters

Additionally there are inputs that describe "atmospheric conditions". These are necessary for propagating the model to the data. They are derived externally and are not varied in the fit:

• Amount and direction of atmospheric differential refraction in each observation.
• wavelength-dependent PSF model for each observation.

Finally, there are two regularization parameters that determine the penalty on the galaxy model for being "rougher" (having a high pixel-to-pixel variation).

The Procedure

These steps are carried out in cubefit.main (which is called from the command-line script).

1. Initialization

   • Read in datacubes
   • Read in parameters that determine the PSF and ADR and initialize the "atmospheric model" that contains these for each epoch.
   • Initialize all model parameters to zero, except sky. For the sky, we make an initial heuristic guess based on only the data and a sigma-clipping process.
   • Initialize the regularization, based on the input regularization parameters and a rough guess at the average galaxy spectrum.

2. Fit the galaxy model to just the master final ref

   The model is defined in the frame of the master final ref, so there is no position fit here. Also, the sky of the master final ref is fixed to the initial guess (as the galaxy model and sky level are degenerate).

3. Fit the position and sky of the remaining final refs

4. Re-fit galaxy model using all final refs

5. Fit position, sky and SN position of all the non-final refs

Data structure and I/O

ADR and PSF model

Additionally, the ADR class from the SNfactory Toolbox package is used.

Fitting

Utilities

Running Tests:

If you've clone the repository (rather than using pip to install), you can run tests with ./test.py. Requires the pytest package (available via pip or conda).

CubeFit is released under the MIT license. See LICENSE.md.