MVC¶

class turbustat.statistics.MVC(centroid, moment0, linewidth, header=None)[source] [edit on github]¶

Bases: turbustat.statistics.base_statistic.BaseStatisticMixIn, turbustat.statistics.base_pspec2.StatisticBase_PSpec2D

Implementation of Modified Velocity Centroids (Lazarian & Esquivel, 03)

Parameters:

centroid : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject Normalized first moment array. moment0 : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject Moment 0 array. linewidth : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject Normalized second moment array header : FITS header Header of any of the arrays. Used only to get the spatial scale.

Attributes Summary

centroid	Normalized centroid array.
linewidth	Linewidth array.
moment0	Zeroth moment (integrated intensity) array.

Methods Summary

compute_pspec()	Compute the 2D power spectrum.
run([verbose, save_name, logspacing, ...])	Full computation of MVC.

Attributes Documentation

centroid¶

Normalized centroid array.

linewidth¶

Linewidth array. Square root of the velocity dispersion.

moment0¶

Zeroth moment (integrated intensity) array.

Methods Documentation

compute_pspec()[source] [edit on github]¶

Compute the 2D power spectrum.

The quantity calculated here is the same as Equation 3 in Lazarian & Esquivel (2003), but the inputted arrays are not in the same form as described. We can, however, adjust for the use of normalized Centroids and the linewidth.

An unnormalized centroid can be constructed by multiplying the centroid array by the moment0. Velocity dispersion is the square of the linewidth subtracted by the square of the normalized centroid.

run(verbose=False, save_name=None, logspacing=False, return_stddev=True, low_cut=None, high_cut=0.5, ang_units=False, unit=Unit("deg"), use_wavenumber=False, **kwargs)[source] [edit on github]¶

Full computation of MVC. For fitting parameters and radial binning options, see StatisticBase_PSpec2D.

Parameters:

verbose: bool, optional Enables plotting. save_name : str,optional Save the figure when a file name is given. logspacing : bool, optional Return logarithmically spaced bins for the lags. return_stddev : bool, optional Return the standard deviation in the 1D bins. low_cut : float, optional Low frequency cut off in frequencies used in the fitting. high_cut : float, optional High frequency cut off in frequencies used in the fitting. ang_units : bool, optional Convert frequencies to angular units using the given header. unit : u.Unit, optional Choose the angular unit to convert to when ang_units is enabled. use_wavenumber : bool, optional Plot the x-axis as the wavenumber rather than spatial frequency. kwargs : Passed to fit_pspec.