GaussianModel#

class sunkit_spex.models.models.GaussianModel(

amplitude=Parameter('amplitude', value=1.0, bounds=(0, None)),

mean=Parameter('mean', value=0.0, bounds=(0, None)),

stddev=Parameter('stddev', value=1.0),

edges=True,

**kwargs,

)[source]#

Bases: FittableModel

Attributes Summary

`amplitude`
`input_units`	This property is used to indicate what units or sets of units the evaluate method expects, and returns a dictionary mapping inputs to units (or `None` if any units are accepted).
`mean`
`n_inputs`
`n_outputs`
`param_names`	Names of the parameters that describe models of this type.
`return_units`	This property is used to indicate what units or sets of units the output of evaluate should be in, and returns a dictionary mapping outputs to units (or `None` if any units are accepted).
`stddev`

Methods Summary

`__call__`(*inputs[, model_set_axis, ...])	Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.
`evaluate`(x, amplitude, mean, stddev)	Evaluate the Gaussian model at `x` with parameters `amplitude`, `mean`, and `stddev`.

Attributes Documentation

amplitude = Parameter('amplitude', value=1.0, bounds=(0, None))#

input_units#

mean = Parameter('mean', value=0.0, bounds=(0, None))#

n_inputs = 1#

n_outputs = 1#

param_names = ('amplitude', 'mean', 'stddev')#

Names of the parameters that describe models of this type.

The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.

When defining a custom model class the value of this attribute is automatically set by the Parameter attributes defined in the class body.

return_units#

stddev = Parameter('stddev', value=1.0)#

Methods Documentation

__call__(

*inputs,

model_set_axis=None,

with_bounding_box=False,

fill_value=nan,

equivalencies=None,

inputs_map=None,

**new_inputs,

)#: Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.

evaluate(x, amplitude, mean, stddev)[source]#: Evaluate the Gaussian model at x with parameters amplitude, mean, and stddev.