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Add a quadrature rule for higher degree polynomials #72
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btalamini
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btalamini:feature/quadrature_precision_10_rule
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Add a quadrature rule for higher degree polynomials #72
btalamini
wants to merge
16
commits into
sandialabs:main
from
btalamini:feature/quadrature_precision_10_rule
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…t matrix log, exp, and sqrt
Before: the primal output was computed in-line in the custom jvp function. The advantage is that this avoids a second call to the eigendecomposition. The downside is that this in-line computation doesn't itself have a custom jvp, so its derivative can be wrong. After: I re-compute the primal value through the base function (e.g., log_symm), which has the custom jvp defined on it. The eigendecomposition is repeated. We can refactor to eliminate this later if profiling reveals it to be a performance bottleneck.
Put a leading underscore on functions menat for internal use. Most Python tools will ignore these when reporting contents of a module.
Replace all calls except in the new viscoelastic model. Changes are about to merge there and I want to handle the conflicts separately.
Also: now a ValueError is emitted if a user asks for a quadrature rule precision that is above what we have implemented. Before the error was a bit obscure. Improved the unit testing of the quadrature rules by making subtests for every polynomial degree check. This way, if the test fails, you can figure out which quadrature rules are broken.
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UnboundLocalError: local variable 'xi' referenced before assignment
. Now they getValueError: Quadrature of precision this high is not implemented.
subTest
facility ofunittest
(orpytest
) is used so that you see which precision checks failed.