simulate_data_pyoof

pyoof.simulate_data_pyoof(I_coeff, K_coeff, wavel, d_z, illum_func, telgeo, noise, resolution, box_factor, work_dir=None)

Routine to generate data and test the pyoof package algorithm. It has the default setting for the pyoof FITS file input.

Parameters

I_coefflist

List which contains 4 parameters, the illumination amplitude, \(A_{E_\mathrm{a}}\), the illumination taper, \(c_\mathrm{dB}\) and the two coordinate offset, \((x_0, y_0)\). The illumination coefficients must be listed as follows, I_coeff = [i_amp, c_dB, x0, y0].

K_coeffndarray

Constants coefficients, \(K_{n\ell}\), for each of them there is only one Zernike circle polynomial, \(U^\ell_n(\varrho, \varphi)\).

wavelQuantity

Wavelength, \(\lambda\), of the observation in length units.

d_zQuantity

Radial offset \(d_z\), added to the sub-reflector in length units. This characteristic measurement adds the classical interference pattern to the beam maps, normalized squared (field) radiation pattern, which is an out-of-focus property. The radial offset list must be as follows, d_z = [d_z-, 0., d_z+] all of them in length units.

illum_funcfunction

Illumination function, \(E_\mathrm{a}(x, y)\), to be evaluated with the key I_coeff. The illumination functions available are illum_parabolic and illum_gauss.

telgeolist

List that contains the blockage distribution, optical path difference (OPD) function, and the primary radius (float) in lenght units. The list must have the following order, telego = [block_dist, opd_func, pr].

noisefloat

Noise amplitude added to the generated data. The noise comes from a random Gaussian, see normal.

resolutionint

Fast Fourier Transform resolution for a rectangular grid. The input value has to be greater or equal to the telescope resolution and with power of 2 for faster FFT processing. It is recommended a value higher than resolution = 2 ** 8.

box_factorint

Related to the FFT resolution (resolution key), defines the image pixel size level. It depends on the primary radius, pr, of the telescope, e.g. a box_factor = 5 returns x = np.linspace(-5 * pr, 5 * pr, resolution), an array to be used in the FFT2 (fft2).

work_dirstr

Default is None, it will store the FITS file in the current directory, for other provide the desired path.

Returns

pyoof_fitsHDUList

The output fits file is stored in the directory 'data_generated/'. Every time the function is executed a new file will be stored (with increased numbering). The file is ready to use for the pyoof package.

Raises

ValueError

If the known a priori radial offset d_z is different than: [d_z-, 0., d_z+], negative, zero, and positive float.