The best fit will be considered to be that one that gives the smallest deviation from the measured data. A loop over the previously created variable listCalibration will provide this information. Previously, the variables indicating the different properties around the best fit will be initialized to values that will certainly will be overwritten. Remember that the initial model set up could provide a better fit than any of the calibration simulation. So this case should also be included in the check loop. If the decviation of a case is smaller than the previous "devBestFit", then that case should replace the current one (index, boundary condition used, roughness used, and deviation from the data).
Find out which is the best fit
indexBestFit = -1
bcBestFit = 1e100
roughnessBestFit = 1e100
devBestFit = 1e100
for i in range(1,len(timeSeriesToCompare)-1): # case 0 is data so don't use it.
case = listCalibration[i-1]
if case[2] < devBestFit:
indexBestFit = i
bcBestFit = case[0]
roughnessBestFit = case[1]
devBestFit = case[2]
