DeblendDefault

class lsst.ts.wep.deblend.DeblendDefault

Bases: object

Default deblend class.

Methods Summary

deblendDonut(imgToDeblend, iniGuessXY, **kwargs)	Deblend the donut image.
generateMultiDonut(template, spaceCoef, ...)	Gemerate multiple donut images.

Methods Documentation

deblendDonut(imgToDeblend, iniGuessXY, **kwargs)

Deblend the donut image.

Parameters:

• imgToDeblend (numpy.ndarray) – Image to deblend.

• iniGuessXY (list[tuple]) – The list contains the initial guess of (x, y) positions of neighboring stars as [star 1, star 2, etc.].

• **kwargs (dict[str, any]) – Dictionary of input argument: new value for that input argument.

Return type:

tuple[ndarray, float, float]

Returns:

• numpy.ndarray – Deblended donut image.

• float – Position x of donut in pixel.

• float – Position y of donut in pixel.

Raises:

NotImplementedError – Child class should implement this.

generateMultiDonut(template, spaceCoef, magRatio, theta)

Gemerate multiple donut images.

Only one neightboring star will be generated for test, which is the baseline of LSST.

Parameters:

• template (numpy.ndarray) – Template donut image.

• spaceCoef (float) – Spacing coefficient to decide the distance between donuts.

• magRatio (float) – Magnitude ratio of new donut compared with the original one.

• theta (float) – Theta angle of generated neighboring star in degree.

Return type:

tuple[ndarray, ndarray, ndarray, float, float]

Returns:

• numpy.ndarray – Image of donuts.

• numpy.ndarray – Image of bright star.

• numpy.ndarray – Image of neighboring star.

• float – Position x of neighboring star.

• float – Position y of neighboring star.

Raises:

• ValueError – spaceCoef should be greater than zero.

• ValueError – magRatio should be postive and less than 1.