mirar.pipelines.winter.generator package

Module for generating custom processors and catalogues for WINTER

Submodules

mirar.pipelines.winter.generator.astrometry module

Module for astrometric calibration for the winter pipeline.

mirar.pipelines.winter.generator.astrometry.winter_astrometric_ref_catalog_generator(image: Image) → Gaia2Mass | CatalogFromFile[source]

Function to generate a reference catalog for WINTER astrometry

Parameters:: image – Image
Returns:: catalogue

mirar.pipelines.winter.generator.astrometry.winter_astrometry_sextractor_catalog_purifier(catalog: Table, _) → Table[source]: Function to purify the Sextractor catalog for WINTER astrometry

mirar.pipelines.winter.generator.candidates module

Module for candidate-related functions for WINTER

exception mirar.pipelines.winter.generator.candidates.NoGoodCandidatesError[source]

Bases: ProcessorError

Error raised when no candidates pass quality cuts

mirar.pipelines.winter.generator.candidates.winter_candidate_annotator_filterer(source_batch: SourceBatch) → SourceBatch[source]: Function to perform basic filtering to weed out bad candidates with None magnitudes, to be added. :param source_batch: Source batch :return: updated batch

mirar.pipelines.winter.generator.candidates.winter_candidate_avro_fields_calculator(source_table: SourceBatch) → SourceBatch[source]: Function to calculate the AVRO fields for WINTER

mirar.pipelines.winter.generator.candidates.winter_candidate_quality_filterer(source_table: SourceBatch) → SourceBatch[source]: Function to perform quality filtering on WINTER candidates

mirar.pipelines.winter.generator.candidates.winter_new_source_updater(source_table: SourceBatch) → SourceBatch[source]

Function to add relevant fields for new sources

Parameters:: source_table – Original source table
Returns:: Updated source table

mirar.pipelines.winter.generator.candidates.winter_skyportal_annotator(source_batch: SourceBatch) → SourceBatch[source]

Function to update the candidate table with the skyportal fields

Parameters:: source_batch – Original source table
Returns:: Updated source table

mirar.pipelines.winter.generator.candidates.winter_source_entry_updater(source_table: SourceBatch) → SourceBatch[source]

Function to update the source table with new source averages

Parameters:: source_table – Original source table
Returns:: Updated source table

mirar.pipelines.winter.generator.photometry module

Module for photometric for the Winter pipeline.

mirar.pipelines.winter.generator.photometry.winter_astrostat_catalog_purifier(sci_catalog: ~astropy.table.table.Table, ref_catalog: ~astropy.table.table.Table, image: ~mirar.data.image_data.Image) -> (<class 'astropy.table.table.Table'>, <class 'astropy.table.table.Table'>)[source]: Default function to purify the photometric image catalog

mirar.pipelines.winter.generator.photometry.winter_photcal_color_columns_generator(image)[source]

Returns the color columns for WINTER photometric calibration

Parameters:: image – Image
Returns:: color columns

mirar.pipelines.winter.generator.photometry.winter_photometric_catalog_generator(image: Image) → Gaia2Mass | PS1 | CatalogFromFile[source]

Function to crossmatch WIRC to GAIA/2mass for photometry

Parameters:: image – Image
Returns:: catalogue

mirar.pipelines.winter.generator.photometry.winter_photometric_catalogs_purifier(sci_catalog: ~astropy.table.table.Table, ref_catalog: ~astropy.table.table.Table, image: ~mirar.data.image_data.Image) -> (<class 'astropy.table.table.Table'>, <class 'astropy.table.table.Table'>)[source]: Default function to purify the photometric image catalog

mirar.pipelines.winter.generator.photometry.winter_ref_photometric_catalogs_purifier(sci_catalog: ~astropy.table.table.Table, ref_catalog: ~astropy.table.table.Table, image: ~mirar.data.image_data.Image) -> (<class 'astropy.table.table.Table'>, <class 'astropy.table.table.Table'>)[source]: Default function to purify the photometric image catalog

mirar.pipelines.winter.generator.photometry.winter_reference_phot_calibrator(_: Image, **kwargs) → PhotCalibrator[source]

Generates a resampler for reference images

Parameters:

_ – image
kwargs – kwargs

Returns:

Swarp processor

mirar.pipelines.winter.generator.realbogus module

Functions to apply rbscore

mirar.pipelines.winter.generator.realbogus.apply_rb_to_table(model: Module, table: DataFrame) → DataFrame[source]

Apply the realbogus score to a table of sources

Parameters:

model – Pytorch model
table – Table of sources

Returns:

Table of sources with realbogus score

mirar.pipelines.winter.generator.realbogus.apply_xrb_to_table(clf: XGBClassifier, table: DataFrame) → DataFrame[source]

Apply the xrealbogus score to a table of sources

Parameters:

clf – xgboost model
table – DataFrame of sources

Returns:

Table of sources with ‘xrealbogus’ score

mirar.pipelines.winter.generator.reduce module

Module with generators for WINTER pipeline

exception mirar.pipelines.winter.generator.reduce.ReductionQualityError[source]

Bases: ProcessorError

Error raised when the quality of the reduction is too poor

mirar.pipelines.winter.generator.reduce.mask_stamps_around_bright_stars(image: Image)[source]: Masks the stamps around bright stars in the image :param image: :return: masked image

mirar.pipelines.winter.generator.reduce.select_winter_dome_flats_images(images: ImageBatch) → ImageBatch[source]: Selects the flat for the winter data, get the top 250 images sorted by median counts

mirar.pipelines.winter.generator.reduce.select_winter_flat_images(images: ImageBatch) → ImageBatch[source]: Selects the flat for the winter data, get the top 250 images sorted by median counts

mirar.pipelines.winter.generator.reduce.select_winter_sky_flat_images(images: ImageBatch) → ImageBatch[source]: Selects the flat for the winter data, get the top 250 images sorted by median counts

mirar.pipelines.winter.generator.reduce.winter_anet_sextractor_config_path_generator(image: Image) → str[source]: Generates the sextractor config file path for the winter image

mirar.pipelines.winter.generator.reduce.winter_boardid_6_channel_masker(images: ImageBatch) → ImageBatch[source]: Masks the bad channel pixels for board 6 images. This is required because swarp does not handle masked pixels distributed across the image well, producing a fully masked image. :param images: ImageBatch :return: ImageBatch with masked bad channel pixels

mirar.pipelines.winter.generator.reduce.winter_boardid_6_demasker(images: ImageBatch) → ImageBatch[source]: Demasks images from board 6 by replacing the bad channel pixels with the median of the unmasked pixels. This is required because swarp does not handle masked pixels distributed across the image well, producing a fully masked image. :param images: ImageBatch :return: ImageBatch

mirar.pipelines.winter.generator.reduce.winter_fourier_filtered_image_generator(batch: ImageBatch) → ImageBatch[source]: Generates a fourier filtered image for the winter data

mirar.pipelines.winter.generator.reduce.winter_imsub_catalog_purifier(sci_catalog: Table, ref_catalog: Table)[source]

Parameters:

sci_catalog
ref_catalog

Returns:

mirar.pipelines.winter.generator.reduce.winter_lab_master_flat_path_generator(images: ImageBatch) → Path[source]: Generates a master flat for the winter data using the lab flats :param images: ImageBatch :return: ImageBatch with master flat applied

mirar.pipelines.winter.generator.reduce.winter_master_flat_path_generator(images: ImageBatch) → Path[source]

Generates a master flat path for the winter data

Parameters:: images
Returns:: Path to master flat

mirar.pipelines.winter.generator.reduce.winter_stackid_annotator(batch: ImageBatch) → ImageBatch[source]

Generates a stack id for WINTER images as the minimum of the RAWID of the images for which the stack was requested.

Parameters:: batch – ImageBatch
Returns:: ImageBatch with stackid added to the header

mirar.pipelines.winter.generator.references module

Module containing reference-related functions for the winter pipeline.

mirar.pipelines.winter.generator.references.ref_sextractor(image: Image)[source]

Generates a sextractor instance for reference images to get photometry

Parameters:: image – Image
Returns:: Sextractor

mirar.pipelines.winter.generator.references.winter_astrometric_ref_catalog_namer(batch: ImageBatch) → ImageBatch[source]

Function to name the reference catalog to use for WINTER astrometry, and add this to header

Parameters:: batch – ImageBatch
Returns:: ImageBatch

mirar.pipelines.winter.generator.references.winter_photometric_ref_catalog_namer(batch: ImageBatch) → ImageBatch[source]: Function to name the reference catalog to use for WINTER astrometry

mirar.pipelines.winter.generator.references.winter_reference_generator(image: Image)[source]

Gets a reference image generator for the winter data

Parameters:: image – Image
Returns:: Reference image generator

mirar.pipelines.winter.generator.references.winter_reference_image_resampler_for_zogy(**kwargs) → Swarp[source]

Generates a resampler for reference images

Parameters:: kwargs – kwargs
Returns:: Swarp processor

mirar.pipelines.winter.generator.references.winter_reference_psf_phot_sextractor(output_sub_dir: str) → Sextractor[source]

Returns a Sextractor processor for WINTER reference images

Parameters:: output_sub_dir – str
Returns:: Sextractor processor

mirar.pipelines.winter.generator.references.winter_reference_psfex(output_sub_dir: str, norm_fits: bool) → PSFex[source]

Returns a PSFEx processor for WINTER

Parameters:

output_sub_dir – str
norm_fits – bool

mirar.pipelines.winter.generator.references.winter_reference_sextractor(output_sub_dir: str) → Sextractor[source]

Returns a Sextractor processor for WINTER reference images

Parameters:: output_sub_dir – str
Returns:: Sextractor processor

mirar.pipelines.winter.generator.references.winter_reference_stack_annotator(stacked_image: Image, image: Image) → Image[source]

Generates a stack id for WINTER reference images

Parameters:

stacked_image – Image
image – Image

mirar.pipelines.winter.generator.references.winter_wfau_component_image_stacker(**kwargs) → Swarp[source]

Generates a resampler for reference images

Parameters:: kwargs – kwargs
Returns:: Swarp processor

mirar.pipelines.winter.generator.utils module

Some utility functions for the WINTER pipeline

mirar.pipelines.winter.generator.utils.check_winter_local_catalog_overlap(ref_cat_path: Path, image: Image) → bool[source]: Returns a function that returns the local reference catalog

mirar.pipelines.winter.generator.utils.winter_ref_catalog_namer(image: Image, output_dir: Path) → Path[source]

Function to name the reference catalog to use for WINTER astrometry

Parameters:

image – Image
output_dir – Path

Returns:

Output path