Tools

class sf3dmodels.model.disc2d.Tools

Methods Summary

average_pixels_cube(data, frac_pixels[, …])	data: datacube with shape (nchan, nx0, ny0) frac_pixels: number of pixels to average av_method: function to compute average
fit_one_gauss_cube(data, vchannels[, …])	Fit Gaussian profile along velocity axis to input data lw_chan: initial guess for line width is lw_chan*np.mean(dvi).
get_sky_from_disc_coords(R, az, z, incl, PA)
get_tb(I, nu, beam[, full])	nu in GHz Intensity in mJy/beam beam object from radio_beam if full: use full Planck law, else use rayleigh-jeans approximation
weighted_std(prop, weights[, weighted_mean])

Methods Documentation

static average_pixels_cube(data, frac_pixels, av_method=<function median at 0x7f0278c2add0>)

data: datacube with shape (nchan, nx0, ny0) frac_pixels: number of pixels to average av_method: function to compute average

static fit_one_gauss_cube(data, vchannels, lw_chan=1.0, sigma_fit=None, verbose=True)

Fit Gaussian profile along velocity axis to input data lw_chan: initial guess for line width is lw_chan*np.mean(dvi). sigma_fit: cube w/ channel weights for each pixel, passed to curve_fit

static get_sky_from_disc_coords(R, az, z, incl, PA)

static get_tb(I, nu, beam, full=True)

nu in GHz Intensity in mJy/beam beam object from radio_beam if full: use full Planck law, else use rayleigh-jeans approximation

static weighted_std(prop, weights, weighted_mean=None)