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authorMarti Bolivar <mbolivar@leaflabs.com>2011-08-31 11:26:53 -0400
committerMarti Bolivar <mbolivar@leaflabs.com>2011-08-31 13:06:07 -0400
commitb8545bfea262e3fcd4e3796c8d61fdf3c6f9cb70 (patch)
tree822107859f1703967c2bd2b215c83d3a8d68d848 /.gdbinit
parent796f6922f5d06b9b208a56d343266deee3940a90 (diff)
downloadlibrambutan-b8545bfea262e3fcd4e3796c8d61fdf3c6f9cb70.tar.gz
librambutan-b8545bfea262e3fcd4e3796c8d61fdf3c6f9cb70.zip
test-session.cpp: Better analog noise readings.
Update measure_adc_noise() to actually use the Welford online algorithm, instead of accumulating data in an array on the stack. This allows us to increase the number of samples (to 1000). Revised algorithm tested on host PC and compared (in Python) against numpy with a list of 100 values in [0, 1) drawn using random.random(). Results (Python): >>> r = [random.random() for i in xrange(100)] >>> numpy.mean(r) 0.50073064742634854 >>> numpy.var(r) 0.083726090293309297 Results (C++, x86 host PC): n: 100 mean: 0.500731 variance: 0.084572 So this algorithm for variance has some inaccuracies, but it appears to be good to a couple of significant figures.
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