autowisp.processing_steps.lc_detrending module

Class Inheritance Diagram

Functions for detrending light curves (EPD or TFA).

autowisp.processing_steps.lc_detrending._add_catalog_info(lc_fnames, catalog_sources, magnitude_expression, result=None)

Fill the catalog information fields in result.

autowisp.processing_steps.lc_detrending._check_fit_datasets_available(lc_fname, fit_datasets, detrending_mode)

Raise ConfigurationError if an input dataset is missing from a lightcurve.

Without this, a mismatch between the datasets EPD produced and the ones TFA was configured to correct only surfaces deep inside the fitting, as a confusing error about the lightcurve structure.

Parameters:

• lc_fname (str) – The lightcurve to check.

• fit_datasets ([]) – See Correction.__init__().

• detrending_mode (str) – Either 'epd' or 'tfa'.

Returns:

None

autowisp.processing_steps.lc_detrending._generate_statistics(lc_fnames, configuration, *, detrending_mode, catalog_fname, output_fname, mark_progress)

Compute, augment and save the detrending statistics (see caller).

autowisp.processing_steps.lc_detrending._get_default_fit_datasets(sphotref_dr, detrending_mode, apphot_version=0, shapefit_version=0)

Return the datasets to detrend if the user did not specify any.

Parameters:

• sphotref_dr (DataReductionFile) – The single photometric reference, opened for reading.

• detrending_mode (str) – Either 'epd' or 'tfa'.

• apphot_version (int) – The version of the aperture photometry whose apertures to detrend.

• shapefit_version (int) – See _shape_fit_varies().

Returns:

The same format the --<mode>-datasets argument parses to.

Return type:

[(str, dict, str)]

autowisp.processing_steps.lc_detrending._shape_fit_varies(sphotref_dr, shapefit_version)

Whether star shape was fit rather than assumed constant accross each star.

Shape fitting is performed on a grid (see the shape-grid option of wisp-fit-star-shape). If only the outer boundaries of that grid are specified, the PSF/PRF is assumed not to vary accross the star, so the shape fitted magnitudes carry no information beyond aperture photometry and detrending them is a waste of time.

Parameters:

• sphotref_dr (DataReductionFile) – The single photometric reference, opened for reading.

• shapefit_version (int) – The version of the shape fit to inspect.

Returns:

Whether the grid the shape was fit on has any internal splits.

Return type:

bool

autowisp.processing_steps.lc_detrending.calculate_detrending_performance(lc_fnames, start_status, configuration, mark_progress, detrending_mode)

Create a statistics file after de-trending directly from LCs.

Parameters:

• lc_fnames – Iterable over the filenames of the de-trended lightcurves to rederive the statistics for.

• catalog_fname – The filename of the catalog to add information to the statistics.

• magnitude_column – The column from the catalog to use as brightness indicator in the statistics file.

• output_statistics_fname – The filename to save the statistics under.

• recalc_arguments – Passed directly to recalculate_correction_statistics()

autowisp.processing_steps.lc_detrending.correct_target_lc(target_lc_fname, configuration, correct)

Perform reconstructive detrending on the target LC.

autowisp.processing_steps.lc_detrending.detrend_light_curves(lc_collection, configuration, correct)

Detrend all lightcurves and create statistics file.

autowisp.processing_steps.lc_detrending.extract_target_lc(lc_fnames, target_id)

Return target LC fname, & LC fname list with the target LC removed.

autowisp.processing_steps.lc_detrending.get_transit_parameters(configuration, unwind_limb_darkening=True)

Return the parameters to pass to pytransit model.

autowisp.processing_steps.lc_detrending.resolve_fit_datasets(configuration, detrending_mode, lc_fnames)

Return the datasets to detrend, filling in a default if none were set.

The relevant entry is removed from configuration.

Parameters:

• configuration (dict) – The configuration of the detrending step. The <mode>_datasets entry is consumed.

• detrending_mode (str) – Either 'epd' or 'tfa'.

• lc_fnames ([str]) – The lightcurves about to be corrected. The first one is used to verify the datasets to correct actually exist.

Returns:

See Correction.__init__().

Return type:

[(str, dict, str)]