kai.reduce.prep_analysis

Functions

euclidean(x1, y1, x2, y2)
removeEdges(imgArr, finalTable[, cutoff, x, y, scale])	Ignores stars close to the edge, i.e., within 100 * scale pixels by default.
psfRadius(starPeak, imagePeak[, scale])	Arbitrary function that ties the predicted radius of the star to the peak brightness in the image.
isBrightSpeckleStar(starPeak, imagePeak)	Can this star have halo speckles? If it's half the peak brightness, it is assumed yes.
isNearBrightStar(nearStarPeak, mainPeak)	Is the main star near another bright star?
isInPSFRadius(starCoo, mainCoo, psfr)	Is star within the psf radius from earlier?
isInSecondaryRadius(starCoo, mainCoo, psfr)	Is star within the secondary radius, defined as 1.35x the psf radius? (arbitrarily)
getTableIndex(mainIndex, starIndex)	Helper function to get star being considered in removeCloseStars.
removeCloseStars(imgArr, newTable[, pixelDist, x, y, ...])	In order of brightest stars in table, checks if it's a valid star, and tracks secondaries near it.
getStats(imgArr)	Returns mean median and mode of pixel values in image array.
getNStarsHelper(imgArr[, expStars, counter, ...])	Attempts to get N stars. If stars aren't found, returns what it can and presents the error.
getNStars(imgArr[, numStars, fwhm, scale])	Reformats table of chosen psf stars and adds the relevant secondaries to it.
generate_list(imgPath[, numPSFStars, fwhm, scale, ...])	Plots the table generated by PSFListGen, and prints the list of stars in a format that can be used.
plot_starlist_on_image_arcsec(starList, imagePath, refCoo)	Plot a NIRC2 image and overlay a starlist. Input in relative arcsec coordinates.
plot_starlist_on_image_pixel(starList, imagePath, refStar)	Plot a NIRC2 image and overlay a starlist. Input in pixel coordinates.
modded_plot_starlist_on_image_pixel(starList, ...[, ...])	Plot a NIRC2 image and overlay a starlist. Input in pixel coordinates.
prepStarfinder(dirName, targetName, targetCoords, ...)	Creates a _psf.list file and saves it in the source_list/ directory.

Module Contents

kai.reduce.prep_analysis.euclidean(x1, y1, x2, y2)

kai.reduce.prep_analysis.removeEdges(imgArr, finalTable, cutoff=100, x='xcentroid', y='ycentroid', scale=0.009942)

Ignores stars close to the edge, i.e., within 100 * scale pixels by default.

kai.reduce.prep_analysis.psfRadius(starPeak, imagePeak, scale=0.009942)

Arbitrary function that ties the predicted radius of the star to the peak brightness in the image. returns a radius: 10 < (Ratio of “magnitudes” cubed * 80) < 60 and scaled acc. to plate scale in arcsec

kai.reduce.prep_analysis.isBrightSpeckleStar(starPeak, imagePeak)

Can this star have halo speckles? If it’s half the peak brightness, it is assumed yes.

kai.reduce.prep_analysis.isNearBrightStar(nearStarPeak, mainPeak)

Is the main star near another bright star?

kai.reduce.prep_analysis.isInPSFRadius(starCoo, mainCoo, psfr)

Is star within the psf radius from earlier?

kai.reduce.prep_analysis.isInSecondaryRadius(starCoo, mainCoo, psfr)

Is star within the secondary radius, defined as 1.35x the psf radius? (arbitrarily)

kai.reduce.prep_analysis.getTableIndex(mainIndex, starIndex)

Helper function to get star being considered in removeCloseStars.

kai.reduce.prep_analysis.removeCloseStars(imgArr, newTable, pixelDist=10, x='xcentroid', y='ycentroid', verbose=False, scale=0.009942)

In order of brightest stars in table, checks if it’s a valid star, and tracks secondaries near it. Removes all invalid stars from table, i.e, those that are likely halo speckles, or too close for valid psf generation. Edge stars are already removed from table using the removeEdges() method.

Terminology? main - Star that is being considered for psf-ness. star - Star that is being checked for nearness to main psf radius - Radius (arbitrary function tied to brightness) that is checked for halo speckles/close bright stars secondary radius - Radius in which, if star found, mark as secondary

Pseudocode:

Sort the table by brightest imagePeak = brightest star peak value in image invalidStarIndices = indices of stars to be removed from table

for each star in table, that is not marked invalid yet:

set this star to the main star find the psf radius of this star

for all star-lookalikes less bright than main star:

if star-lookalike is within psf radius (arbitrary function tied to brightness):

if main star can have halo speckles (arbitrary brightness limit tied to imagePeak):

if lookalike is too bright to be a halo speckle (arbitrary brightness limit tied to mainPeak):

add main star to invalidIndices (another bright star is too near it!) add bright star to invalidIndices (too close to main star)

else lookalike is probably halo speckle:

add lookalike to invalidIndices (too close to main star, not actually a star) keep the main star!!

else main star cannot have halo speckles:

if there is a BRIGHT star-lookalike nearby:

its definitely a star and not halo speckle AND star is too close! add main star to invalidIndices (another bright star is too near it!) add bright star to invalidIndices (too close to main star)

else if star-lookalike is within secondary radius (arbitrary function tied to brightness):

set the “psf?” value of this star in table to 0 (secondary)

from the table, remove all the invalid stars! return table

kai.reduce.prep_analysis.getStats(imgArr)

Returns mean median and mode of pixel values in image array.

kai.reduce.prep_analysis.getNStarsHelper(imgArr, expStars=10, counter=0, starsFound=0, fwhm=4.5, scale=0.009942)

Attempts to get N stars. If stars aren’t found, returns what it can and presents the error. If so, starfinding may have to be done manually.

kai.reduce.prep_analysis.getNStars(imgArr, numStars=10, fwhm=4.5, scale=0.009942)

Reformats table of chosen psf stars and adds the relevant secondaries to it.

kai.reduce.prep_analysis.generate_list(imgPath, numPSFStars=7, fwhm=4.5, scale=0.009942, targName='')

Plots the table generated by PSFListGen, and prints the list of stars in a format that can be used. @params imgPath - path to .fits image, Eg. /g/lu/data/microlens/18jun22/combo/mag18jun22_ob040361_kp.fits numPSFStars - number of stars to be found scale - defaults to nirc2 scale. Enter in arcsec/pixel. targName - name of target (can be anything, not important) fwhm - full-width half maximum variable for finicky images

kai.reduce.prep_analysis.plot_starlist_on_image_arcsec(starList, imagePath, refCoo, scale=9.942 / 1000, magCut=23, label=True, verbose=True, flip=False)

Plot a NIRC2 image and overlay a starlist. Input in relative arcsec coordinates. @params starList - any astropy Table with a “name” (including target),

“m”, “x” (relative arcsec coordinates), and “y” (relative arcsec coordinates) column.

imagePath - path to image from root. refCoo - reference pixel coordinates of a star in image file. scale - plate scale. Defaults to NIRC2 plate scale. magCut - highest magnitude of star allowed to be plotted. label - if True, adds labels. Defaults to true. verbose - if True, prints the astropy table inputted. Defaults to true. flip - if True, flips image in x (helps in case image is backwards).

Ensure that the image passed in is at a Position Angle of 0.

The image is NOT Flipped on plotting by default. In order to flip image, set flip = True.

kai.reduce.prep_analysis.plot_starlist_on_image_pixel(starList, imagePath, refStar, scale=9.942 / 1000, magCut=23, label=True, verbose=True, flip=False, axes='pixel')

Plot a NIRC2 image and overlay a starlist. Input in pixel coordinates. @params starList - any astropy Table with a “name” (including target),

“m”, “x” (pixel coordinates), and “y” (pixel coordinates) column.

imagePath - path to image from root. refStar - name of reference star in astropy table, generally the target. scale - plate scale. Defaults to NIRC2 plate scale. magCut - highest magnitude of star allowed to be plotted. label - if True, adds labels. Defaults to true. verbose - if True, prints the astropy table inputted. Defaults to true. flip - if True, flips image in x (helps in case image is backwards). axes - determines units on the axes of plot (pixel or arcsec). Defaults to pixel.

Ensure that the image passed in is at a Position Angle of 0.

The image is NOT Flipped on plotting by default. In order to flip image, set flip = True.

kai.reduce.prep_analysis.modded_plot_starlist_on_image_pixel(starList, imagePath, refStar, scale=9.942 / 1000, magCut=23, label=True, verbose=True, flip=False, axes='pixel')

Plot a NIRC2 image and overlay a starlist. Input in pixel coordinates. @params starList - any astropy Table with a “name” (including target),

“m”, “x” (pixel coordinates), and “y” (pixel coordinates) column.

imagePath - path to image from root. refStar - name of reference star in astropy table, generally the target. scale - plate scale. Defaults to NIRC2 plate scale. magCut - highest magnitude of star allowed to be plotted. label - if True, adds labels. Defaults to true. verbose - if True, prints the astropy table inputted. Defaults to true. flip - if True, flips image in x (helps in case image is backwards). axes - determines units on the axes of plot (pixel or arcsec). Defaults to pixel.

Ensure that the image passed in is at a Position Angle of 0.

The image is NOT Flipped on plotting by default. In order to flip image, set flip = True.

kai.reduce.prep_analysis.prepStarfinder(dirName, targetName, targetCoords, psfStars, filterName)

Creates a _psf.list file and saves it in the source_list/ directory.