The original test was poorly constructed, and the τ₂ fitting parameter
was not defined for the test data: with α = 1, it could take any value
and the function would fit just the same.
Here, we replace the test data with the one where 0<α<1, and thus both
τ₁ and τ₂ are well-defined.
Also updated the documentation to reflect the actual function used in
the code: it was missing a prefactor of 2.
Closes #3955
function to estimate the error in time-correlated data due to Hess \ :ref:`149 <refHess2002a>`:
.. math:: \varepsilon^2(t) =
- \alpha\tau_1\left(1+\frac{\tau_1}{t}\left(e^{-t/\tau_1}-1\right)\right)
- + (1-\alpha)\tau_2\left(1+\frac{\tau_2}{t}\left(e^{-t/\tau_2}-1\right)\right)
+ 2 \alpha\tau_1\left(1+\frac{\tau_1}{t}\left(e^{-t/\tau_1}-1\right)\right)
+ + 2 (1-\alpha)\tau_2\left(1+\frac{\tau_2}{t}\left(e^{-t/\tau_2}-1\right)\right)
:label: eqntimecorrerror
where :math:`\tau_1` and :math:`\tau_2` are time constants (with
<ReferenceData>
<Sequence Name="result">
<Int Name="Length">3</Int>
- <Real>0.50082180382778319</Real>
- <Real>1</Real>
- <Real>103.32999340041971</Real>
+ <Real>1.2</Real>
+ <Real>0.99</Real>
+ <Real>34.5</Real>
</Sequence>
</ReferenceData>
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+# import numpy as np; t1, a, t2 = 1.2, 0.99, 34.5; t = np.linspace(1, 8001, 501); e2 = 2*a*t1*(1+t1/t*(np.exp(-t/t1)-1)) + 2*(1-a)*t2*(1+t2/t*(np.exp(-t/t2)-1)); np.savetxt('testERREST.xvg', np.array([t, e2]).T, ('%d', '%.7f'), header=open(__file__).readlines()[0])
+#
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biod.pnpi.spb.ru / alexxy / gromacs.git / commitdiff