lsst.meas.algorithms.testUtils Namespace Reference

Functions
def	plantSources

Function Documentation

def lsst.meas.algorithms.testUtils.plantSources	(		bbox,
			kwid,
			sky,
			coordList,
			addPoissonNoise = True
	)

Make an exposure with stars (modelled as Gaussians)

@param bbox: parent bbox of exposure
@param kwid: kernel width (and height; kernel is square)
@param sky: amount of sky background (counts)
@param coordList: a list of [x, y, counts, sigma], where:
    * x,y are relative to exposure origin
    * counts is the integrated counts for the star
    * sigma is the Gaussian sigma in pixels
@param addPoissonNoise: add Poisson noise to the exposure?

Definition at line 30 of file testUtils.py.

def plantSources(bbox, kwid, sky, coordList, addPoissonNoise=True):
    """Make an exposure with stars (modelled as Gaussians)

    @param bbox: parent bbox of exposure
    @param kwid: kernel width (and height; kernel is square)
    @param sky: amount of sky background (counts)
    @param coordList: a list of [x, y, counts, sigma], where:
        * x,y are relative to exposure origin
        * counts is the integrated counts for the star
        * sigma is the Gaussian sigma in pixels
    @param addPoissonNoise: add Poisson noise to the exposure?
    """
    # make an image with sources
    img = afwImage.ImageD(bbox)
    meanSigma = 0.0
    for coord in coordList:
        x, y, counts, sigma = coord
        meanSigma += sigma

        # make a single gaussian psf
        psf = SingleGaussianPsf(kwid, kwid, sigma)

        # make an image of it and scale to the desired number of counts
        thisPsfImg = psf.computeImage(afwGeom.PointD(int(x), int(y)))
        thisPsfImg *= counts

        # bbox a window in our image and add the fake star image
        imgSeg = img.Factory(img, thisPsfImg.getBBox())
        imgSeg += thisPsfImg
    meanSigma /= len(coordList)

    img += sky

    # add Poisson noise
    if (addPoissonNoise):
        numpy.random.seed(seed=1) # make results reproducible
        imgArr = img.getArray()
        imgArr[:] = numpy.random.poisson(imgArr)

    # bundle into a maskedimage and an exposure
    mask = afwImage.MaskU(bbox)
    var = img.convertFloat()
    img -= sky
    mimg = afwImage.MaskedImageF(img.convertFloat(), mask, var)
    exposure = afwImage.makeExposure(mimg)

    # insert an approximate psf
    psf = SingleGaussianPsf(kwid, kwid, meanSigma)
    exposure.setPsf(psf)

    return exposure