satlas.models.models.MiscModel

class satlas.models.models.MiscModel(func, args, name_list=None)

Constructs a response from a supplied function. Call signature is

def func(x, par):

a = par[0]

b = par[1]

...

return y

__init__(func, args, name_list=None)

The MiscModel takes a supplied function func and list of starting argument parameters args to contruct an object that responds with the given function for the parameter values. A list of names can also be supplied to customize the parameter names.

Parameters:

• func (callable) – A callable function with call signature func(x, args).
• args (list of values) – List of starting values for the parameters. The number of parameters is based on the length of the list of arguments.
• name_list (list of strings, optional) – List of names to be supplied to the parameters. The order of the names and the order of the parameters is the same, so name_list[0] corresponds to args[0].

__call__(x)

Methods

__init__(func, args[, name_list])	The MiscModel takes a supplied function func and list of starting argument parameters args to contruct an object that responds with the given function for the parameter values.
__call__(x)
display_chisquare_fit([scaled])	Display all relevent info of the least-squares fitting routine, if this has been performed.
display_mle_fit([scaled])	Give a readable overview of the result of the MLE fitting routine.
get_chisquare_mapping()
get_lnprior_mapping(params)
get_result([selection])	Return the variable names, values and estimated error bars for the parameters as seperate lists.
get_result_dict([method, scaled])	Returns the fitted parameters in a dictionary of the form {name: [value, uncertainty]}.
get_result_frame([method, selected, bounds, ...])	Returns the data from the fit in a pandas DataFrame.
save(path)	Saves the current spectrum, including the results of the fitting and the parameters, to the specified file.
seperate_response(x)	Wraps the output of the __call__ in a list, for ease of coding in the fitting routines.
set_boundaries(boundaryDict)	Sets the boundaries of the fitparameters as supplied in the dictionary.
set_chisquare_mapping(mappingDict)	Sets the prior mapping for the different parameters.
set_expr(exprDict)	Sets the expression of the selected parameters to the given expressions.
set_literature_values(literatureDict)	Sets the lnprior and chisquare mapping to handle the given literature values and uncertainties.
set_lnprior_mapping(mappingDict)	Sets the prior mapping for the different parameters.
set_value(valueDict)	Sets the value of the given parameters to the given values.
set_variation(varyDict)	Sets the variation of the fitparameters as supplied in the dictionary.

Attributes

params