Better than last week! 35./90.

A new release of AllanTools is now available on PyPi.
A loop around the Sipoonkorpi National Park. Warm +26 C or so at the start. Around 67 km in total. Almost the same route as in June 2017.
The AllanTools functions mtotdev() and htotdev() are now almost 10-times faster, after an update to the code that more efficiently calculates moving averages.
The old code used numpy.mean() for each iteration of a loop:
for j in range(0, 6*m): # summation of the 6m terms.
xmean1 = np.mean(xstar[j : j+m])
xmean2 = np.mean(xstar[j+m : j+2*m])
xmean3 = np.mean(xstar[j+2*m : j+3*m])
However this can be computed much faster by noticing that the new mean differs from the old (already computed!) mean by just two points, one at the start is dropped, and a new one at the end is added:
for j in range(0, 6*m): # summation of the 6m terms.
if j == 0:
# intialize the sum
xmean1 = np.sum( xstar[0:m] )
xmean2 = np.sum( xstar[m:2*m] )
xmean3 = np.sum( xstar[2*m:3*m] )
else:
# j>=1, subtract old point, add new point
xmean1 = xmean1 - xstar[j-1] + xstar[j+m-1] #
xmean2 = xmean2 - xstar[m+j-1] + xstar[j+2*m-1] #
xmean3 = xmean3 - xstar[2*m+j-1] + xstar[j+3*m-1] #
No major mistakes but slow going on the 2nd stage of Jukola this year.
The not-so-dramatic errors were: #2 has a 90-degree wiggle just before the control - my route to #7 was OK but very slow through the green/tick aprts - then no worries until #15 where the 'safe' choice along the road was no good at all - finally a bit of a Z-bend into #17.