xlens.processor.fpfs

FPFS shape measurement task wrapping anacal.fpfs.

Provides FpfsMeasurementTask, a Rubin-style Task that measures FPFS shapelet moments from coadd exposures and returns structured catalogs ready for shear estimation.

Classes

`FpfsMeasurementConfig`	Configuration for `FpfsMeasurementTask`.
`FpfsMeasurementTask`	Measure FPFS shapelet observables from coadd image data.

Module Contents

class FpfsMeasurementConfig[source]

Bases: lsst.pex.config.Config

Configuration for FpfsMeasurementTask.

npix[source]

bound[source]

sigma_shapelets[source]

sigma_shapelets1[source]

sigma_shapelets2[source]

snr_min[source]

r2_min[source]

pthres[source]

kmax_thres[source]

do_noise_bias_correction[source]

do_compute_detect_weight[source]

return_only_linear_modes[source]

psf_model_type[source]

badMaskPlanes[source]

noiseId[source]

rotId[source]

validate()[source]

setDefaults()[source]

class FpfsMeasurementTask(**kwargs: Any)[source]

Bases: lsst.pipe.base.Task

Measure FPFS shapelet observables from coadd image data.

Wraps anacal.fpfs.process_image() behind the Rubin Task interface. Call prepare_data() to extract arrays from an LSST ExposureF, then run() to perform the measurement.

_DefaultName = 'FpfsMeasurementTask'[source]

ConfigClass[source]

fpfs_config[source]

run(*, pixel_scale: float, mag_zero: float, noise_variance: float, gal_array: numpy.typing.NDArray, psf_array: numpy.typing.NDArray, mask_array: numpy.typing.NDArray, noise_array: numpy.typing.NDArray | None, detection: numpy.typing.NDArray | None, psf_object: xlens.utils.image.LsstPsf | None, base_column_name: str | None = None, begin_x: int = 0, begin_y: int = 0, **kwargs)[source]

Run FPFS measurement on image arrays.

Parameters:

pixel_scale (float) – Pixel scale in arcsec/pixel.
mag_zero (float) – Magnitude zeropoint.
noise_variance (float) – Per-pixel noise variance.
gal_array (NDArray) – Galaxy image array.
psf_array (NDArray) – PSF image array.
mask_array (NDArray) – Bad-pixel mask array.
noise_array (NDArray or None) – Noise realisation for noise-bias correction.
detection (NDArray or None) – External detection catalog with x1_det, x2_det columns (in arcsec). If None, peaks are detected internally.
psf_object (LsstPsf or None) – Position-dependent PSF model.
base_column_name (str or None) – Prefix prepended to all output column names.
begin_x (int) – Pixel origin offset for sub-images.
begin_y (int) – Pixel origin offset for sub-images.

Returns:

Structured array of FPFS shape measurements.

Return type:

np.ndarray

prepare_data(*, exposure: lsst.afw.image.ExposureF, seed: int, band: str | None, noise_corr: numpy.typing.NDArray | None = None, mask_array: numpy.typing.NDArray | None = None, noise_array: numpy.typing.NDArray | None = None, star_cat: numpy.typing.NDArray | None = None, detection: numpy.typing.NDArray | None = None, **kwargs)[source]

Prepares the data from LSST exposure Args: exposure (ExposureF): LSST exposure seed (int): random seed noise_corr (NDArray): image noise correlation function (None) detection (NDArray | None): external detection catalog (None)

Returns:: (dict)