peakfind

sofia_redux.instruments.forcast.peakfind.peakfind(coadded, newimage=None, refine=True, npeaks=4, fwhm=4.5, sharplo=0.2, sharphi=1.0, roundlo=-0.75, roundhi=0.75, silent=False, maxiter=1000, epsilon=5, eps=1e-07, ncut=30, chopnoddist=None, positive=False, smooth=True, return_object=False, coordinates=False)

Find peaks (stars) in FORCAST images

Identifies the desired number of peaks in the image using the DAO search algorithm followed by optional (default=True) Levenberg- Marquardt least squares fitting of a gaussian psf to refine the fit.

Parameters:

coaddednumpy.ndarray

Reference image to find peak positions

newimagenumpy.ndarray, optional

Secondary image to compare to coadded. If provided, the return value will be the shifts required to move the sources in newimage onto the sources in coadded. If not provided, the return value is the positions of the peaks in coadded

refinebool, optional

If set, the x, y coordinates are fine tuned by fitting a Gaussian to the profile of each found center

npeaksint, optional

Number of peaks to find; usually determined from the chop/nod mode

fwhmfloat, optional

Expected FWHM in pixels

roundlofloat, optional

The lower bound on roundness for object detection

roundhifloat, optional

The upper bound on roundness for object detection

sharplofloat, optional

The lower bound on sharpness for object detection

sharphifloat, optional

The upper bound on sharpness for object detection

silentbool, optional

If set, output will be suppressed

maxiterint, optional

Maximum number of iterations for iteratefind

epsilonint or float, optional

Maximum nod/chop deviation for exclusion in chopnod_sort

epsfloat, optional

Precision to terminate iteration

ncutint, optional

Positive integer cutout region used for Gaussian fitting (pixels)

chopnoddist(list or tuple) of float, optional

If provided, will be used to identify the expected positions of the peaks and prioritize those that are nearest to where they should be. Format is [chop distance, nod distance]

positivebool, optional

If set, only positive peaks will be returned.

smoothbool, optional

If True, the data will be smoothed before searching for peaks.

return_objectbool, optional

If set, return the PeakFinder object rather than the DataFrame

coordinatesbool, optional

If set, return tuples of (x, y) coordinates as a list

Returns:

pandas.DataFrame or PeakFinder or list

The default DataFrame represents either shift_image distances to move newimage on top of coadded, or positions of the peaks in coadded if newimage was not supplied as an input parameter. The PeakFinder object contains lots of useful little attributes such as the fits, tables and models of coadded and newimage.

If coordinates=True, a list of (x, y) coordinates will be returned.