autowisp.magnitude_fitting.master_photref_collector_zarr module

Class Inheritance Diagram

Define class for collecting statistics and making a master photref.

class autowisp.magnitude_fitting.master_photref_collector_zarr.MasterPhotrefCollector(statistics_fname, num_photometries, num_frames, **config)

Bases: object

Class collecting magfit output to generate a master photometric reference.

Variables:

• _statistics_fname – The file name to save the collected statistics under.

• _grcollect – The running grcollect process responsible for generating the statistics.

• _dimensions – How many photometry measurements are being fit based on how many images, and what is the total number of coluns included in the statistics (usually twice the number of photometries).

• _source_name_format – A %-substitution string for turning a source ID tuple to as string in the statistics file.

• _stat_quantities – The quantities that grcollect is told to calculate for each input magnitude and error estimate.

__init__(statistics_fname, num_photometries, num_frames, **config)

Prepare for collecting magfit results for master photref creation.

Parameters:

• statistics_fname (str) – The filename where to save the statistics relevant for creating a master photometric reference.

• num_photometries (int) – The number of photometric measurements available for each star (e.g. number of apertures + 1 if psf fitting + …).

• outlier_threshold (float) – A threshold value for outlier rejection. The units of this are determined by the rejection_units argument.

• max_rejection_iterations (int) – The maximum number of iterations between rejecting outliers and re-deriving the statistics to allow.

• tempstore_dir (str) – A location in the file system to use for storing temporary files during statistics collection.

• rejection_center (str) – Outliers are define around some central value, either 'mean', or 'median'.

• rejection_units (str) – The units of the outlier rejection threshold. One of 'stddev', 'meddev', or 'absolute'.

• max_memory (str) – The maximum amount of RAM the statistics process is allowed to use (if exceeded intermediate results are dumped to files in temp_dir).

Returns:

None

_add_catalog_info(catalog, statistics, catalog_columns)

Add the catalog data for each source to the statistics.

_calculate_statistics(statistics)

Calculate and fill in the statics from all input collected so far.

_create_reference(statistics, residual_scatter, *, enough_counts_flags, outlier_average, outlier_threshold, reference_fname, primary_header)

Create the master photometric reference.

Parameters:

• statistics – The return value of _read_statistics().

• residual_scatter – The return value of _fit_scatter().

• enough_counts_flags (bool array) – Flag for each photometry for each star indicating whether sufficient number of points remained after rejection to use in the master.

• outlier_average – See fit_outlier_average argument to generate_master().

• outlier_threshold – See fit_outlier_threshold argument to generate_master().

• reference_fname (str) – The name to use for the generated master photometric reference file.

• primary_header (fits.Header) – The header to use for the primary (non-table) HDU of the resulting master FITS file.

Returns:

None

_fit_scatter(statistics, fit_terms_expression, *, enough_counts_flags, outlier_average, outlier_threshold, max_rej_iter, scatter_quantity='medianmeddev')

Fit for the dependence of scatter on source properties.

Parameters:

• statistics – The return value of _read_statistics().

• fit_terms_expression (str) – A fitting terms expression to use to generate the terms to include in the fit of the scatter.

• enough_counts_flags – Boolean array indicating which sources have enough observations to participate in the fit.

• outlier_average – See fit_outlier_average argument to generate_master().

• outlier_threshold – See fit_outlier_threshold argument to generate_master().

• max_rej_iter – See fit_max_rej_iter argument to generate_master().

• scatter_quantity (str) – The name of the field in statistics which contains the estimated scatter to fit.

Returns:

The residuals of the scatter from statistics from the best-fit values found.

Return type:

numpy array

_get_enough_count_flags(statistics, min_nobs_median_fraction)

Return median number of observations per source in the stat. file.

_get_stat_dtype(catalog_columns)

Return the dtype to use for statistics.

_init_data(num_sources)

Create the file-based array for holding magfit data.

_save_statistics(statistics)

Save the given statistics as a master statistics file.

add_input(fit_results)

Ingest a fitted frame’s photometry into the statistics.

generate_master(*, master_reference_fname, catalog, fit_terms_expression, min_nobs_median_fraction=0.5, fit_outlier_average='median', fit_outlier_threshold=3.0, fit_max_rej_iter=20, extra_header=None)

Finish the work of the object and generate a master.

Parameters:

• master_reference_fname (str) – The file name to use for the newly created master photometric reference.

• catalog – See master_catalog argument to MagnitudeFit.__init__().

• fit_terms_expression (str) – An expression expanding to the terms to include in the scatter fit. May use any catalog column.

• parse_source_id (callable) – Should convert a string source ID into the source ID format expected by the catalog.

• min_nobs_median_fraction (float) – The minimum fraction of the median number of observations a source must have to be inclruded in the master.

• fit_outlier_average (str) – The averaging method to use for scaling averaging residuals from scatter fit. The result is used as the unit for fit_outlier_threshold.

• fit_outlier_threshold (float) – A factor to multiply the fit_outlier_average averaged residual from scatter fit in order to get the threshold to consider a scatter point an outlier, and hence discard from cantributing to the reference.

• fit_max_rej_iter (int) – The maximum number of iterations to allow for fitting/rejecting outliers. If this number is reached, the last result is accepted.

• extra_header (None or dict-like) – Header keywords to add to the generated FITS header in addition to the ones describing the master fit.

Returns:

None