PriorParameter#

class gammapy.modeling.PriorParameter(name, value, unit='', scale=1, min=nan, max=nan, error=0)[source]#

Attributes Summary

`conf_max`	Confidence maximum value as a `float`.
`conf_min`	Confidence minimum value as a `float`.
`error`
`factor`	Factor as a float.
`factor_max`	Factor maximum as a float.
`factor_min`	Factor minimum as a float.
`frozen`	Frozen (used in fitting) (bool).
`max`	Maximum as a float.
`min`	Minimum as a float.
`name`	Name as a string.
`prior`	Prior applied to the parameter as a `Prior`.
`quantity`	Value times unit as a `Quantity`.
`scale`	Scale as a float.
`scale_method`	Method used to set `factor` and `scale`.
`scan_max`	Stat scan maximum.
`scan_min`	Stat scan minimum.
`scan_n_sigma`	Stat scan n sigma.
`scan_values`	Stat scan values as a `ndarray`.
`type`
`unit`	Unit as a `Unit` object.
`value`	Value = factor x scale (float).

Methods Summary

`autoscale`()	Autoscale the parameters.
`check_limits`()	Emit a warning or error if value is outside the minimum/maximum range.
`copy`()	Deep copy.
`prior_stat_sum`()
`to_dict`()	Convert to dictionary.
`update_from_dict`(data)	Update parameters from a dictionary.

Attributes Documentation

conf_max#

Confidence maximum value as a float.

Return parameter maximum if defined, otherwise return the scan_max.

conf_min#

Confidence minimum value as a float.

Return parameter minimum if defined, otherwise return the scan_min.

factor_max#

Factor maximum as a float.

This factor_max = max / scale is for the optimizer interface.

factor_min#

Factor minimum as a float.

This factor_min = min / scale is for the optimizer interface.

Methods Documentation

autoscale()#

Autoscale the parameters.

Set factor and scale according to scale_method attribute.

Available scale_method.

scale10 sets scale to power of 10, so that abs(factor) is in the range 1 to 10
factor1 sets factor, scale = 1, value

In both cases the sign of value is stored in factor, i.e. the scale is always positive. If scale_method is None the scaling is ignored.

check_limits()#: Emit a warning or error if value is outside the minimum/maximum range.