Rename a_min and a_max to lower and upper and add them to Scalar init #536
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jrapin
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Feb 21, 2020
| super().__init__(init=np.array([init]), mutable_sigma=mutable_sigma) | ||
| if bounded: | ||
| self.set_mutation(sigma=(upper - lower) / 6) # type: ignore |
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@teytaud
what do you think of these defaults for scalars, if both lower and upper bounds are provided:
- sigma is set to a sixth of b - a (so that the full range is covered from start)
- we also set
full_range_sampling=Truewhich means that parametrization.sample() will sample uniformly within the bounds ( this is used by some new algorithms) - if init is not provided, it is set it is set to the middle point
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If neither or only one is provided, we are back to normal and the user need to use the Scalar methods to update sigma
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Also forgot to mention, by default it's using clipping, but once again to use a different method one can set it manually through the set_bounds method
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