iccsa-21-wind

git clone https://git.igankevich.com/iccsa-21-wind.git
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commit 37f99067dbc862580be7ca3355ad81e90b9fb283
parent 257ceed13116940ad75cdb15a016aabab18d357f
Author: Ivan Gankevich <i.gankevich@spbu.ru>
Date:   Wed, 31 Mar 2021 18:05:13 +0300

turbulence, fix graph offsets

Diffstat:
gnuplot/daily-stats.gnuplot | 4++--
main.tex | 9++++++++-
2 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/gnuplot/daily-stats.gnuplot b/gnuplot/daily-stats.gnuplot @@ -1,7 +1,7 @@ load 'gnuplot/paired.pal' set terminal svg size 500,400 font 'Free Serif, 10' enhanced dynamic -set xtics nomirror out rotate 90 -set ytics nomirror out +set xtics nomirror out rotate 90 offset 0,0.25 +set ytics nomirror out offset 0.5,0 set border 1+2 set key top center outside maxrows 1 diff --git a/main.tex b/main.tex @@ -249,7 +249,7 @@ sampleToSpeed <- function(x, c1, c2) { } \end{lstlisting} -Over a period of one month we collected 2.7M samples and filtered out 14\% of +Over a period of one month we collected 3.1M samples and filtered out 12\% of them as having too large unnatural values. We attributed these values to measurement errors as they spread uniformly across all the time span and are surrounded by the values of regular magnitude. TODO picture of a large error. @@ -262,6 +262,13 @@ ones with data distributions close to unimodal, so we could easily fit them into the model. The statistics for each interval is presented in figure~\ref{fig-intervals}. +Unique feature of three-axis anemometer is that it measures both velocity of +incident air flow towards the arms and the turbulent flow that forms behind the +arms. Turbulence is complicated phenomena and there is no simple way of +excluding it from the statistics, therefore, it is important to choose +intervals with unimodal distributions (with one mean wind direction) to get +statistics that is not distorted by the turbulence. + \begin{figure} \centering \includegraphics{build/daily-stats.eps}