lsst.meas.algorithms.testUtils Namespace Reference

Functions
def	plantSources (bbox, kwid, sky, coordList, addPoissonNoise=True)
def	makeRandomTransmissionCurve (rng, minWavelength=4000.0, maxWavelength=7000.0, nWavelengths=200, maxRadius=80.0, nRadii=30, perturb=0.05)

Function Documentation

makeRandomTransmissionCurve()

def lsst.meas.algorithms.testUtils.makeRandomTransmissionCurve	(		rng,
			minWavelength = 4000.0,
			maxWavelength = 7000.0,
			nWavelengths = 200,
			maxRadius = 80.0,
			nRadii = 30,
			perturb = 0.05
	)

Create a random TransmissionCurve with nontrivial spatial and
wavelength variation.

Parameters
----------
rng : numpy.random.RandomState
    Random number generator.
minWavelength : float
    Average minimum wavelength for generated TransmissionCurves (will be
    randomly perturbed).
maxWavelength : float
    Average maximum wavelength for generated TransmissionCurves (will be
    randomly perturbed).
nWavelengths : int
    Number of samples in the wavelength dimension.
maxRadius : float
    Average maximum radius for spatial variation (will be perturbed).
nRadii : int
    Number of samples in the radial dimension.
perturb: float
    Fraction by which wavelength and radius bounds should be randomly
    perturbed.

Definition at line 89 of file testUtils.py.

plantSources()

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 31 of file testUtils.py.