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Fix RungeKutta23 interpolator #17
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Hello @hgrecco I have been looking into this for a comparison with SciPy's implementation uses: C = np.array([0, 1/2, 3/4])
A = np.array([
[0, 0, 0],
[1/2, 0, 0],
[0, 3/4, 0]
])
B = np.array([2/9, 1/3, 4/9])
E = np.array([5/72, -1/12, -1/9, 1/8])
P = np.array([[1, -4 / 3, 5 / 9],
[0, 1, -2/3],
[0, 4/3, -8/9],
[0, -1, 1]]) whereas `numbakit-ode's implementation uses C = np.array([0, 1 / 2, 3 / 4], dtype=float)
A = np.array([[0, 0, 0], [1 / 2, 0, 0], [0, 3 / 4, 0]], dtype=float)
B = np.array([2 / 9, 1 / 3, 4 / 9], dtype=float)
B2 = np.array([7 / 24, 1 / 4, 1 / 3, 1 / 8], dtype=float)
P = np.array([[1, -4 / 3, 5 / 9], [0, 1, -2 / 3], [0, 4 / 3, -8 / 9], [0, -1, 1]]) Other implementations such as Moreover, I tried to check it locally whether removing E = np.array([5/72, -1/12, -1/9, 1/8]) solve the error or not. Unfortunately, it still gives an error after running Could you help me in the above? I am eager to learn more about this implementation. Thanks! |
The AdaptiveRungeKutta class (from which RungeKutta23 derives) uses |
Thank you @maurosilber for your reply and guidance. It seems slightly tricky to figure out the cause of mismatch with the scipy's implementation but I would take a look at it. Thanks! |
RungaKutta23 interpolator does not match the SciPy result. Test hast been temporarily disabled.
numbakit-ode/nbkode/testsuite/test_against_scipy.py
Line 86 in 67c186a
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