Add Basis.derivatives
#102
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This spiraled a bit more than I had anticipated, but I think overall it's a step towards making the interface more composable. |
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It also simplifies the tensor product derivative spaghetti by quite a bit. |
modepy/modes.py
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| @@ -766,6 +791,28 @@ def gradients(self) -> tuple[BasisGradientType, ...]: | |||
| Each function returns a tuple of derivatives, one per reference axis. | |||
| """ | |||
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| def functions_dr(self, axis: int) -> tuple[BasisFunctionType, ...]: | |||
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Still unsure about the name. Suggestions?
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Maybe just derivatives? deriv_functions?
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I agree, that's probably the sanest. Renamed to that in the latest.
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axis_derivative_functions?
I'm also leaning towards derivatives, so that's perfectly fine by me!
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axis_derivatives is another option, but it's unlikely that we'd have any other type (directional?) derivative, so 🤷. I say let's leave it as derivatives.
cc @a-alveyblanc