PointOfInterestFinderOptions

giant.image_processing.point_source_finder:

class giant.image_processing.point_source_finder.PointOfInterestFinderOptions(point_spread_function=<class 'giant.point_spread_functions.gaussians.IterativeGeneralizedGaussian'>, image_flattener_options=<factory>, centroid_size=1, min_size=2, max_size=50, threshold=8, reject_saturation=True)[source]

This class defines the options used to configure the PointOfInterestFinder.

It includes parameters for the point spread function to be fit, image flattening, centroid size, minimum and maximum blob size, threshold for point of interest detection, and saturation rejection.

These options allow for fine-tuning the point of interest detection process to suit different types of images and detection requirements.

Parameters:
image_flattener_options: ImageFlattenerOptions

The options to use when flattening the image

centroid_size: int = 1

This specifies how many pixels to include when identifying a centroid in a region of interest.

This sets the +/- number from the peak brightness pixel in both axes (so that a value of 1 means a 3x3 grid will be considered, a value of 2 will result in a 5x5 grid, etc).

property options_dict: Dict

Determine the options input to the dataclass.

This property method will ignore all internal properties and functions

min_size: int = 2

This specifies the minimum number of pixels that must be connected for a blob to be considered a point of interest.

Individual pixels are clumped using a connected components algorithm, and then the size of each blob is compared against this value. See locate_subpixel_poi_in_roi() for more details.

max_size: int = 50

This specifies the maximum number of pixels that must be connected for a blob to be considered a point of interest.

Individual pixels are clumped using a connected components algorithm, and then the size of each blob is compared against this value. see locate_subpixel_poi_in_roi() for more details.

threshold: float = 8

This specifies the sigma multiplier to use when identifying a pixel as a point of interest.

The sigma multiplier is applied to a rough noise estimate of the image (see flatten_image_and_get_noise_level()) and then any pixels above this DN value are labeled as interesting pixels that require further processing (see locate_subpixel_poi_in_roi()).

reject_saturation: bool = True

This boolean flag specifies whether to ignore clumps of pixels that contain saturated DN values when identifying points of interest in an image.

Set to True to reject any clumps containing saturated pixels.

Summary of Methods

apply_options

Update the options as attributes of the object class

local_vars

this is used to overwrite options in variables only used in __init__

override_options

This method is used for special cases when certain options should be overwritten