norm in quick fit

src/mdevaluate/utils.py

@@ -334,6 +334,11 @@ def quick1etau(t: ArrayLike, C: ArrayLike, n: int = 7) -> float:
     C is C(t) the correlation function
     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!
     tau_est = t[np.argmin(np.fabs(C - np.exp(-1)))]
     # reduce the data to points around 1/e