Added PowerScale similar to LogScale as per 20355 #2
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| return self._transform | ||
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| def set_default_locators_and_formatters(self, axis): | ||
| axis.set_major_locator(AutoLocator()) |
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Other scales use their own custom locator so I don't think AutoLocator is supposed to be used here. I think we would probably have to define a new tick locator PowerLocator to be used here.
| PowerNorm = make_norm_from_scale( | ||
| functools.partial(scale.PowerScale))(Normalize) | ||
| PowerNorm.__name__ = PowerNorm.__qualname__ = "PowerNorm" | ||
| PowerNorm.__doc__ = "Normalize a given value to the 0-1 range using a power-law scale." |
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Is there any reason to define PowerNorm like this. I see that only LogNorm uses this kind of definition, while all other norms define a class like this:
@make_norm_from_scale(
scale.FuncScale,
init=lambda functions, vmin=None, vmax=None, clip=False: None)
class FuncNorm(Normalize):
"""
Arbitrary normalization using functions for the forward and inverse.It would be better if we do what other norms follow.
PR summary
Added PowerScale PowerTransform InversePowerTransform to scale.py
Changed PowerNorm and made it similar to LogNorm in colors.py
PR checklist