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norm in quick fit

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robrobo
2025-10-16 17:44:30 +02:00
parent 6b7641f152
commit 715deea1e0
1 changed files with 5 additions and 0 deletions
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src/mdevaluate/utils.py
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@@ -334,6 +334,11 @@ def quick1etau(t: ArrayLike, C: ArrayLike, n: int = 7) -> float:
C is C(t) the correlation function C is C(t) the correlation function
n is the minimum number of points around 1/e required n is the minimum number of points around 1/e required
""" """
# norm, if t=0 provided
if t[0] == 0:
C /= C[0]
C, t = C[t>0], t[t>0] # make sure t=0 is dropped
# first rough estimate, the closest time. This is returned if the interpolation fails! # first rough estimate, the closest time. This is returned if the interpolation fails!
tau_est = t[np.argmin(np.fabs(C - np.exp(-1)))] tau_est = t[np.argmin(np.fabs(C - np.exp(-1)))]
# reduce the data to points around 1/e # reduce the data to points around 1/e