PYME.localization.cModels.gauss_app module

Fast gaussian models)

PYME.localization.cModels.gauss_app.NRFilter()

Perform a filter on an X, Y, I dataset using an R^2 dependant LUT

PYME.localization.cModels.gauss_app.genGauss()

Generate a (fast) Gaussian. . Arguments are: ‘X’, ‘Y’, ‘A’=1,’x0’=0, ‘y0’=0,sigma=0,b=0,b_x=0,b_y=0

PYME.localization.cModels.gauss_app.genGauss3D()

Generate a (fast) 3D Gaussian. . Arguments are: ‘X’, ‘Y’, ‘Z’, ‘A’=1,’x0’=0, ‘y0’=0, ‘z0’=0,sigma=0, sigma_z=1, b=0

PYME.localization.cModels.gauss_app.genGaussA()

Generate a (fast) astigmatic Gaussian. . Arguments are: ‘X’, ‘Y’, ‘A’=1,’x0’=0, ‘y0’=0,sigma_x=1, sigma_y = 1,b=0,b_x=0,b_y=0

PYME.localization.cModels.gauss_app.genGaussInArray()

Generate a Gaussian in pre-allocated memory. . Arguments are: out, X, Y, A=1,x0=0, y0=0,sigma=0, b=0,b_x=0,b_y=0

PYME.localization.cModels.gauss_app.genGaussJac()

Generate jacobian for Gaussian. . Arguments are: ‘X’, ‘Y’, ‘A’=1,’x0’=0, ‘y0’=0,sigma=0,b=0,b_x=0,b_y=0

PYME.localization.cModels.gauss_app.genGaussJacW()

Generate jacobian for a weighted Gaussian. . Arguments are: ‘X’, ‘Y’, ‘W’,’A’=1,’x0’=0, ‘y0’=0,sigma=0,b=0,b_x=0,b_y=0

PYME.localization.cModels.gauss_app.genMultiGauss()

Generate multiple Gaussians. . Arguments are: ‘X’, ‘Y’, ‘P’,sigma=1

PYME.localization.cModels.gauss_app.genMultiGaussJac()

Generate multiple Gaussians. . Arguments are: ‘X’, ‘Y’, ‘P’,sigma=1

PYME.localization.cModels.gauss_app.genSplitGaussInArray()

Generate a double Gaussian in pre-allocated memory. . Arguments are: out, X, Y, X1, Y1, A=1, A1=1,x0=0, y0=0,sigma=0, b=0,b_x=0,b_y=0

PYME.localization.cModels.gauss_app.genSplitGaussInArrayPVec()

Generate a double Gaussian in pre-allocated memory. . Arguments are: out, X, Y, X1, Y1, A=1, A1=1,x0=0, y0=0,sigma=0, b=0,b_x=0,b_y=0

PYME.localization.cModels.gauss_app.splitGaussWeightedMisfit()

Generate a double Gaussian in pre-allocated memory. . Arguments are: out, X, Y, X1, Y1, A=1, A1=1,x0=0, y0=0,sigma=0, b=0,b_x=0,b_y=0