SourceXtractorPlusPlus Versions Save

Release 0.21 (Note: there is no version 0.20 on github as that was used for an internal release)

• Can now work without a detection image by supplying an assoc catalog
• Added check images for measurement images background (--check-image-measurement-background and --check-image-measurement-variance)

Important bug fixes:

• iterative model fitting was using the current value of parameters for the range instead of initial value.
• WCS tranform errors are caught and display a warning instead of stopping everything
• fixes problems with BLAS multithreading

Dependencies: Alexandria 2.31.0, Elements 6.2.3

2024-01-10: Conda packages now available.

Fixes the numerical precision issues with position (see https://github.com/astrorama/SourceXtractorPlusPlus/issues/533)

Requirements: Alexandria 2.27.0, Elements 6.0.1

New in 0.19:

• Support for FITS Data cubes
• Columns from ASSOC catalogs can be used in mode fitting configuration
• Changes in some command line parameters (see below)
• Many bug fixes and internal enhancements

Details:

Several command line parameters have been modified to make their behavior more clear: use-cleaning, use-attractors-partition, partition-corethreshold become booleans, so instead of --use-cleaning' you have to write use-cleaning=true' this makes their behavior consistent between command line and configuration file use.

Also since it would have caused double negatives, the following parameters have also been renamed : segmentation-disable-filtering becomes the boolean segmentation-use-filtering (on by default) output-flush-unsorted becomes the boolean output-flush-sorted (on by default) progress-bar-disable becomes the boolean progress-bar (on by default)

How to use the new FITS cubes: g1 = load_fits_data_cube('cube.fits', sorted(glob('sim11_g_??.psf')))

to load individual slices: DataCubeSlice('cube.fits', "nopsf", image_layer=3)

• Added support for assoc mode using world coordinates
• Added support for assoc and MEF detection images
• Fixed a race condition
• Updated the documentation

• Added compatibility with cfitsio syntax for selecting a hdu in detection images
• Added support for multi-extension fits detection images, to be processed in sequence and get catalog with parts
• Added ErrorEllipse property
• Added model fitting without psf, use "nospsf" as filename to activate
• Stability improvements

New features:

• Model fitting improvements
  • Iterative deblending for model fitting
  • Custom user-made models can be provided in the form of ONNX compute graphs
  • Automatic fit resolution downgrade for very large models
  • Python priors are now evaluated in the C++ code for increased performance
  • Overall major improvements to stability, performance and memory usage

Changes that may require configuration files update:

• Multi-thresholding and grouping of split sources are now on by default
• In the model fitting Python configuration, source properties are now actual properties instead of getter functions: o.get_radius() => o.radius
• Iterative model fitting is on by default, if needed the new system can be turned off with use_iterative_fitting(False) (not all improvements from this release are available in the old system)
• Segmentation using a ML model was renamed from --segmentation-onnx-model to --segmentation-ml-model (experimental feature)
• The Onnx property that performs a measurement using an Onnx compute graph is renamed to MLMeasurement

Compatibility breaking change since 0.14:

FITS HDU numbering scheme in the python configuration file has been changed to start at 0 for the primary HDU instead of 1.

While 1 based indices are used internally by the cfitsio library we realized that 0 based indices are much more common. In case of manually specified HDU numbers, some Python configuration files may need to be adjusted.

New features:

• PSF stacks
• Association mode

Other changes: Bug fixes and performance improvements especially on machines with lots of CPU cores SourceXtractor++ now requires version 2.19 of the Alexandria library.

This release fixes a performance regression in 0.13 as well as some missing error bars in aperture photometry

Improvements:

• Multi-threaded computation for grouping/cleaning
• Variable PSF: Add support for other coordinates
• New segmentation mode: BFS, uses a combination of breadth first search and tile by tile processing using a Hilbert curve to optimize memory usage

Fixes:

• Python configuration now uses internal methods instead of astropy to load FITS files to avoid a few issues caused by the difference
• Fixed a problem with multiple dots in checkimage filenames
• Fixed a regression related to maximum number of simultaneous open files
• Fixed a problem with zero values in weight images
• Moffat checkimage parameter renamed to --debug-image-moffat to reflect its meant for internal testing use (very slow performance)
• Unsigned int check images are now saved as signed int check images to avoid compatibility issues
• Improved WCS error reporting

• Added model fitting re-normalization to fix accuracy issues and inconsistent error bars
• New option: model fitting resolution multiplier (--sampling-scale-factor)
• Better default parameters for model fitting sampling
• ONNX plugin, can load ONNX format neural networks and perform inference on all sources
• Fixed build on Fedora 33
• output format option is no longer case sensitive