Normalized Wind Rose Plot help
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Douglas Leaffer
il 22 Giu 2023
Commentato: Star Strider
il 22 Dic 2023
I am trying to generate a normalized (to the max) wind rose plot of air pollutant concentration (UFP) by wind direction. See photo below. A data vector is attached. The simple code: polarplot(N.WD_Deg,N.UFPConc) doesn't generate what I want. Any help is appreciated. Thank you
load winddata.mat
polarplot(N.WD_Deg,N.UFPConc)
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E. Cheynet
il 25 Giu 2023
For the direction with meteorological conventions, you can simply give a new direction newD = 90-oldD
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Star Strider
il 23 Giu 2023
Perhaps something like this —
LD = load('winddata.mat');
N = LD.N;
N.WD_Rad = deg2rad(N.WD_Deg) % Add Radian Variable (For Convenience, Since 'polarplot' Requires It)
[UDir,ix,iv] = unique(N.WD_Rad); % Unique Radian Values & Indices (Sorted)
Concv = accumarray(iv, (1:numel(iv)).', [], @(x)numel(N.UFPConc(x))); % Accumulate Count Values Of 'UFPConc' By Direction (Use 'numel' To Count Occurrences)
[sDir, sConc] = stairs(UDir, Concv); % Return 'stairs' Stepwise Result
figure
polarplot(sDir, sConc) % Plot 'stairs' Stepwise Result
figure
polarplot(UDir, Concv) % Plot Continuous Result
figure
polarhistogram(N.WD_Rad, UDir) % Plot Using 'polarhistogram'
Make appropriate changes to get the result you want.
Using the accumarray function, it is possible to get other parameters of the concentration, such as the mean or median values, as well as standard deviations (std and metrics derived from it, such as confidence intervals) and plot them also using the patch function (although that is more complicated and requires calculating them in polar coordinates and then using the pol2cart function first, and plotting them in Cartesian coordinates), not only the counts.
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