Parameter¶
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class
gammapy.modeling.Parameter(name, value, unit='', scale=1, min=nan, max=nan, frozen=False, error=0)[source]¶ Bases:
objectA model parameter.
Note that the parameter value has been split into a factor and scale like this:
value = factor x scale
Users should interact with the
value,quantityorminandmaxproperties and consider the fact that there is afactor`andscalean implementation detail.That was introduced for numerical stability in parameter and error estimation methods, only in the Gammapy optimiser interface do we interact with the
factor,factor_minandfactor_maxproperties, i.e. the optimiser “sees” the well-scaled problem.- Parameters
Attributes Summary
Factor (float).
Factor max (float).
Factor min (float).
Frozen? (used in fitting) (bool).
Maximum (float).
Minimum (float).
Name (str).
Value times unit (
Quantity).Scale (float).
Unit (
Unit).Value = factor x scale (float).
Methods Summary
autoscale([method])Autoscale the parameters.
Emit a warning or error if value is outside the min/max range
copy()A deep copy
to_dict()Convert to dict.
Attributes Documentation
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error¶
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factor¶ Factor (float).
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factor_max¶ Factor max (float).
This
factor_max = max / scaleis for the optimizer interface.
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factor_min¶ Factor min (float).
This
factor_min = min / scaleis for the optimizer interface.
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frozen¶ Frozen? (used in fitting) (bool).
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max¶ Maximum (float).
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min¶ Minimum (float).
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name¶ Name (str).
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scale¶ Scale (float).
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type¶
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value¶ Value = factor x scale (float).
Methods Documentation
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autoscale(method='scale10')[source]¶ Autoscale the parameters.
Set
factorandscaleaccording tomethodAvailable methods:
scale10setsscaleto power of 10, so that abs(factor) is in the range 1 to 10factor1setsfactor, scale = 1, value
In both cases the sign of value is stored in
factor, i.e. thescaleis always positive.- Parameters
- method{‘factor1’, ‘scale10’}
Method to apply