util - Miscellaneous Utilities

Functions

large_poisson(lam[, thresh])	Draw samples from a Poisson distribution, taking care of large values of lam.
large_gamma(lam, theta[, thresh])	Draw samples from a Gamma distribution, taking care of large values of lam.
make_emccd_noise(photo_electron_flux, ...)	Draw samples from a Poisson-Gamma-Normal distribution, which is an accurate model of EMCCDs (following [R57dca7afaa11-Hirsch2013]).
inverse_truncated(M[, rcond, svd])	Invert M truncating the number of modes.
inverse_truncated_modal(M, num_modes[, svd])	Invert M with num_modes modes.
inverse_tikhonov(M[, rcond, svd])	Invert M using Tikhonov regularization.
read_fits(filename[, extension])	Read an array from a fits file.
write_fits(data, filename[, shape, overwrite])	Write the data to a fits-file.
read_grid(filename[, fmt])	Read a grid from a file.
write_grid(grid, filename[, fmt, overwrite])	Write a grid to a file.
read_field(filename[, fmt])	Read a field from a file.
write_field(field, filename[, fmt, overwrite])	Write a field to a file.
read_mode_basis(filename[, fmt])	Read a mode basis from a file.
write_mode_basis(mode_basis, filename[, ...])	Write a mode basis to a file.
generate_convolution_matrix(grid, kernel)	Create the matrix that applies a convolution with kernel.
make_laplacian_matrix(grid)	Make the Laplacian operator using the 5-point stencil approximation
make_derivative_matrix(grid[, axis])	Make the derivative operator using the central difference approximation.

Classes

SpectralNoiseFactory(psd, output_grid)
SpectralNoise()	A spectral noise object.
SpectralNoiseFactoryFFT(psd, output_grid[, ...])	A spectral noise factory based on FFTs.
SpectralNoiseFFT(factory, C)	A single realization of FFT spectral noise.
SpectralNoiseFactoryMultiscale(psd, ...)	A spectral noise factory based on multiscale Fourier transforms.
SpectralNoiseMultiscale(factory, C_1, C_2)	A single realization of multiscale spectral noise.
SVD([matrix, num_modes, M])	The Singular Value Decomposition for the provided matrix.