_task.py File Reference

Go to the source code of this file.

Classes
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyPictureConnections
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyPictureBackgroundFixerConnections
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyPictureStarFixerConnections
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyPictureStarFixerConfig
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyPictureStarFixerTask
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyMosaicConnections
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyMosaicConfig
class	lsst.pipe.tasks.prettyPictureMaker._task.PrettyMosaicTask

Namespaces
namespace	lsst
namespace	lsst.pipe
namespace	lsst.pipe.tasks
namespace	lsst.pipe.tasks.prettyPictureMaker
namespace	lsst.pipe.tasks.prettyPictureMaker._task

Functions
Struct	lsst.pipe.tasks.prettyPictureMaker._task.run (self, Mapping[str, Exposure] images, Projection[Any]|None image_wcs=None, Box|None image_box=None)
None	lsst.pipe.tasks.prettyPictureMaker._task.runQuantum (self, QuantumContext butlerQC, InputQuantizedConnection inputRefs, OutputQuantizedConnection outputRefs)
dict[str, Exposure]	lsst.pipe.tasks.prettyPictureMaker._task.makeInputsFromRefs (self, Iterable[DatasetRef] refs, Butler|QuantumContext butler)
dict[str, DeferredDatasetHandle]	lsst.pipe.tasks.prettyPictureMaker._task.makeInputsFromArrays (self, **kwargs)
dict[int, DeferredDatasetHandle]	lsst.pipe.tasks.prettyPictureMaker._task.makeInputsFromExposures (self, **kwargs)
	lsst.pipe.tasks.prettyPictureMaker._task.findBackgroundPixels (self, image, threshold_pair=None)
	lsst.pipe.tasks.prettyPictureMaker._task._findControlPoints (self, Exposure exposure, Point2I origin, bool use_detection_mask=False, tuple[float, float]|None threshhold_pair=None)
	lsst.pipe.tasks.prettyPictureMaker._task.fixBackground (self, image, list[float] yloc, list[float] xloc, list[float] values)
	lsst.pipe.tasks.prettyPictureMaker._task.run (self, Exposure inputCoadd, list[Exposure]|None neighbors=None)

Variables
	lsst.pipe.tasks.prettyPictureMaker._task.logger = logging.getLogger(__name__)
	lsst.pipe.tasks.prettyPictureMaker._task.doWrite
	lsst.pipe.tasks.prettyPictureMaker._task.r
	lsst.pipe.tasks.prettyPictureMaker._task.g
	lsst.pipe.tasks.prettyPictureMaker._task.b
	lsst.pipe.tasks.prettyPictureMaker._task.array : `numpy.array`
	lsst.pipe.tasks.prettyPictureMaker._task.mean : `float`
	lsst.pipe.tasks.prettyPictureMaker._task.sigma : `float`
tuple	lsst.pipe.tasks.prettyPictureMaker._task.lower_pos = (array - mu) < sigma
	lsst.pipe.tasks.prettyPictureMaker._task.sigma_ratio = min_sig / sigma
	lsst.pipe.tasks.prettyPictureMaker._task.arr : `numyp.ndarray`
	lsst.pipe.tasks.prettyPictureMaker._task.maxLikely = np.median(image[image < max_search_flux], axis=None)
	lsst.pipe.tasks.prettyPictureMaker._task.mask = image < maxLikely
tuple	lsst.pipe.tasks.prettyPictureMaker._task.initial_std = (image[mask] - maxLikely).std()
	lsst.pipe.tasks.prettyPictureMaker._task.sub_image = image[image < max(maxLikely + 3 * initial_std, max_search_flux)]
	lsst.pipe.tasks.prettyPictureMaker._task.center = mode(np.round(sub_image, 2)).mode
	lsst.pipe.tasks.prettyPictureMaker._task._
	lsst.pipe.tasks.prettyPictureMaker._task.sigma_hat
	lsst.pipe.tasks.prettyPictureMaker._task.floc
	lsst.pipe.tasks.prettyPictureMaker._task.mu_hat = center
	lsst.pipe.tasks.prettyPictureMaker._task.new_cut = image[image < (mu_hat + 3 * sigma_hat)]
	lsst.pipe.tasks.prettyPictureMaker._task.positivity_ratio = np.sum(new_cut > mu_hat) / np.sum(new_cut < mu_hat)
	lsst.pipe.tasks.prettyPictureMaker._task.threshold_pos = min(mu_hat + pos_sigma_mult * sigma_hat, max_search_flux)
	lsst.pipe.tasks.prettyPictureMaker._task.threshold_neg = mu_hat - pos_sigma_mult * sigma_hat