PlasmaCalcs.quantities.quantity_loader.MetaQuantTracking

class PlasmaCalcs.quantities.quantity_loader.MetaQuantTracking(*args, **kw)

Bases: MetaBehaviorHaver

metaclass which predefines some things for tracking calcs, in the class namespace:

KNOWN_VARS - dict of {var: LoadableVar} for all functions decorated with @known_var

KNOWN_PATTERNS - dict of {pattern: LoadablePattern} for all functions decorated with @known_pattern.

KNOWN_SETTERS - dict of {var: f} for all functions decorated with @known_setter

known_var - instance of DecoratingVars; use @known_var or @known_var(name=varname) to decorate functions.

use this for vars, which require exact match for name.

E.g. name=’n’ for number density.

(Note, if function.__name__ is ‘get_{var}’, name=’{var}’ is implied, if not provided explicitly.)

known_pattern - instance of DecoratingPatterns; use @known_pattern(pattern) to decorate functions.

use this for patterns, which require regex match for name.

E.g. pattern=’mean_(.+)’ for mean of any var.

decorated functions will be supplied with kwarg _match=re.fullmatch(pattern, var).

known_setter - instance of DecoratingSetters; use @known_setter or @known_setter(name=varname).

use this for setters, which are functions that set the value of vars.

For more details see setvars or set_var.

Also, copy base classes’ KNOWN_VARS, KNOWN_PATTERNS, and KNOWN_SETTERS to this class, if they exist.

Note that __prepare__ gets called before class definition begins, and fills class namespace,

then __init__ gets called after class definition ends. For example:

class MySubclass(metaclass=MetaQuantTracking):

# <– __prepare__ runs here. Roughly: locals().update(__prepare__())

pass # or, define other functions, variables, etc, as desired.

# <– __init__ runs here. Roughly: MetaQuantTracking.__init__(MySubclass)

__init__(*args, **kw)

initialize cls (with metaclass=MetaBehaviorHaver)

Methods

__init__(*args, **kw)
mro()

mro()

Return a type’s method resolution order.