lsst.meas.modelfit
15.0-4-g535e784+7
|
Functions | |
def | makeGaussian (x, y, scale, muX, muY, varX, varXY, varY) |
def | buildUncertanty (imShape, W, uncertanty) |
def | measureMoments (image, W) |
def lsst.meas.modelfit.regularizedMoments.regularizedMomentsContinued.buildUncertanty | ( | imShape, | |
W, | |||
uncertanty | |||
) |
Propagate pixel uncertainties to uncertainties in weighted moments Parameters ---------- imShape : tuple(float, float) The shape of image for which weighted moments have been calculated W : iterable An iterable object with six elements corresponding to the moments used in the weighted moment calculation, scale, mean in x, mean in y, variance in x, covariance between x and y, and variance in y. uncertanty : `float` Uncertainty in the pixel value. This is a single value, as this routine assumes errors are background dominated, and uncorrelated Returns ------- covarianceMatrix : 2D 6x6 numpy array of floats This is the covariance matrix on the measured moments with uncertainties propagated from pixel uncertainties
Definition at line 65 of file regularizedMomentsContinued.py.
def lsst.meas.modelfit.regularizedMoments.regularizedMomentsContinued.makeGaussian | ( | x, | |
y, | |||
scale, | |||
muX, | |||
muY, | |||
varX, | |||
varXY, | |||
varY | |||
) |
Create an elliptical Gaussian. Parameters ---------- x : 2D numpy array An array containing the x coordinates the Gaussian will be evaluated on. most likely the result of a numpy.indices call y : 2D numpy array An array containing the y coordinates the Gaussian will be evaluated on. most likely the result of a numpy.indices call scale : `float` The value the resulting Gaussian will have when summed over all pixels. muX : `float` The central position of the Gaussian in the x direction muY : `float` The central position of the Gaussian in the y direction varX : `float` The variance of the Gaussian about the muX position varXY : `float` The covariance of the Gaussian in x and y varY : `float` The variance of the Gaussian about the muY position Returns ------- Gaussian : 2D numpy array The Gaussian array generated from the input values
Definition at line 25 of file regularizedMomentsContinued.py.
def lsst.meas.modelfit.regularizedMoments.regularizedMomentsContinued.measureMoments | ( | image, | |
W | |||
) |
Calculate weighted moments of the input image with the given weight array Parameters ---------- image : 2D numpy array of floats This is the input postage stamp of a source for which the weighted moments are to be measured W : 2D numpy array of floats Array of floats that are used as weights when calculating moments on the input image. Array must be the same shape image Returns ------- moments : 6 element numpy array These are the weighted moments as measured from the input image in the order of 0th, 1st X, 1st Y, 2nd X, 2nd XY, 2nd Y Raises ------ AssertionError: Raises if the input arrays are not the same shape
Definition at line 105 of file regularizedMomentsContinued.py.