plot_data

pyoof.plot_data(u_data, v_data, beam_data, d_z, angle, title, res_mode)

Real data beam maps, \(P^\mathrm{obs}(x, y)\), figures given given 3 out-of-focus radial offsets, \(d_z\).

Parameters:

u_data : ndarray

\(x\) axis value for the 3 beam maps in radians. The values have to be flatten, in one dimension, and stacked in the same order as the d_z = [d_z-, 0., d_z+] values from each beam map.

v_data : ndarray

\(y\) axis value for the 3 beam maps in radians. The values have to be flatten, one dimensional, and stacked in the same order as the d_z = [d_z-, 0., d_z+] values from each beam map.

beam_data : ndarray

Amplitude value for the beam map in mJy. The values have to be flatten, one dimensional, and stacked in the same order as the d_z = [d_z-, 0., d_z+] values from each beam map. If res_mode = False, the beam map will be normalized.

d_z : list

Radial offset \(d_z\), added to the sub-reflector in meters. 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 meters.

wavel : float

Wavelength, \(\lambda\), of the observation in meters.

angle : str

Angle unit, it can be 'degrees' or 'radians'.

title : str

Figure title.

res_mode : bool

If True the beam map will not be normalized. This feature is used to compare the residual outputs from the least squares minimization (fit_beam).

Returns:

fig : Figure

Figure from the three observed beam maps. Each map with a different offset \(d_z\) value. From left to right, \(d_z^-\), \(0\) and \(d_z^+\).