class ChiantiPy.core.radLoss(temperature, eDensity, elementList=0, ionList=0, minAbund=0, doContinuum=1, abundance=None, verbose=0, allLines=1, keepIons=0)[source] [edit on github]

Bases: ChiantiPy.base.specTrails

Calculate the emission spectrum as a function of temperature and density.

includes elemental abundances or ionization equilibria

temperature and density can be arrays but, unless the size of either is one (1), the two must have the same size

the returned spectrum will be convolved with a filter of the specified width on the specified wavelength array

the default filter is gaussianR with a resolving power of 1000. Other filters, such as gaussian, box and lorentz, are available in ChiantiPy.filters. When using the box filter, the width should equal the wavelength interval to keep the units of the continuum and line spectrum the same.

A selection of ions can be make with ionList containing the names of the desired lines in Chianti notation, i.e. C VI = c_6

a minimum abundance can be specified so that the calculation can be speeded up by excluding elements with a low abundance. With solar photospheric abundances -

setting minAbund = 1.e-4 will include H, He, C, O, Ne setting minAbund = 2.e-5 adds N, Mg, Si, S, Fe setting minAbund = 1.e-6 adds Na, Al, Ar, Ca, Ni

Setting em will multiply the spectrum at each temperature by the value of em.

em [for emission measure], can be a float or an array of the same length as the temperature/density.

abundance: to select a particular set of abundances, set abundance to the name of a CHIANTI abundance file,
without the ‘.abund’ suffix, e.g. ‘sun_photospheric_1998_grevesse’ If set to a blank (‘’), a gui selection menu will popup and allow the selection of an set of abundances

Methods Summary

radLossPlot([title]) to plot the radiative losses vs temperature

Methods Documentation

radLossPlot(title=0)[source] [edit on github]

to plot the radiative losses vs temperature