PlasmaCalcs.quantities.collisions.cross_section_tools.CrossTable

class PlasmaCalcs.quantities.collisions.cross_section_tools.CrossTable(kT, cross, crossunits, fc=1.3333333333333333)

Bases: object

stores data about a cross sections table.

kT: temperatures [eV]. array of values cross: cross sections [crossunits]. array of values crossunits: conversion factor; cross * crossunits = cross section [cm^-2]. single value. | fc numerical factor, based on convention of the cross table. | when getting the collision frequency, the formula needs to use fc * cross. | PlasmaCalcs ‘collisions_cross_section’ (‘collcross’) already includes the fc factor. | The value of fc should probably be set as follows: | tables utilizing Bruno+2010 should have fc=4/3. | tables utilizing Vranjes+2013 should have fc=1. | By default, should prefer to use Bruno+2010 (hence the default is 4/3), | as explained in Wargnier+2022.

note: some cross tables are available by default;: these can be loaded with cls.default(name), where name is one of cls.DEFAULTS.keys().

__init__(kT, cross, crossunits, fc=1.3333333333333333)

Methods

`__init__`(kT, cross, crossunits[, fc])
`from_defaults`(name)
`from_file`(filename[, fc])
`interp`(value[, input, output, log])
`keys`()
`lims`(attr)

Attributes

`DEFAULTS`
`T`
`collcross_si`
`cross_si`

property T: temperatures [K], associated with kT.

property collcross_si: cross sections, in [m^-2], multiplied by fc.

property cross_si: cross sections, in [m^-2].

classmethod from_defaults(name): return CrossTable from one of the default cross table files.

name = one of cls.DEFAULTS.keys().

classmethod from_file(filename, fc=1.3333333333333333): return CrossTable from file. Be sure to put the appropriate value of fc.

Bruno+2010 should have fc=4/3. Vranjes+2013 should have fc=1.

see help(CrossTable) for more fc info.

interp(value, input='T', output='collcross_si', *, log=True, **kw_interp)

interpolate value from input (default: ‘T’) to output (default: ‘collcross_si’)

returns result like value (e.g., number if number; array if array),

with numerical values corresponding to output variable instead of input variable.

value: number or array-like: values to interpolate

note: if value is an xarray, return an xarray with same dims, attrs, and coords as value.
input: str: input variable; should be an attribute of self.

value is a value of this variable.
output: str: output variable; should be an attribute of self.

result is a value of this variable.
log: bool, default True: whether to interpolate on log scale.

True –> interpolate log10(value) against log10(input).

additional kwargs go to np.interp.

example: interp(2000, ‘T’, ‘cross_si’) –> single value, with cross section at T=2000 K.

keys(): returns keys of self, as a list.

These are: [‘kT’, ‘cross’, ‘cross_si’, ‘crossunits’, ‘T’]

lims(attr): return self.attr.min(), self.attr.max()