Normalized Wind Rose Plot help

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)

[VBBV]

Try using polarhistogram function

[VBBV]

One way is to use the data for air pollution concentration directly and compare with direction data as shown below

Data = load('winddata.mat')

Data = struct with fields:
    N: [133872×3 table]

Data.N;
% 
subplot(121)
polarplot(Data.N.WD_Deg(1:10000:end),'linewidth',2,'Color','red')
title('Wind direction [deg]')
subplot(122) % normalized plot of air pollutant data
polarplot(Data.N.UFPConc(1:10000:end)./max(Data.N.UFPConc(1:10000:end)),'linewidth',2,'Color','red')
title('Air pollutant concentration')

since polarplot by default uses direction data for its axes, yoou can use that pollutant data directly. Othwerwise, you can also apply conditions for direction data bins and filter the air pollutant concentration data , then plot it. Further, the data points in the table are many, so its better to filter the air pollutant data using bin averaged directional means which will be representative of the air pollutant concentration

[Douglas Leaffer]

Thank you VBBV and Star Strider. Both of your suggested codes worked for me - but I can't seem to rotate the compass points to have 0 at the top and then clockwise ticks, with 90 deg at right, 180 at bottom and 270 at left. Is there a simple programmatic fix for this?

[E. Cheynet]

For the direction with meteorological conventions, you can simply give a new direction newD = 90-oldD

Answer 1

[Star Strider]

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)

N = 133872×4 table
    WD_Deg      WS      UFPConc    WD_Rad
    ______    ______    _______    ______

      30      25.927    0.11886    0.5236
      30      25.927    0.13314    0.5236
      30      25.927    0.16629    0.5236
      30      25.927    0.15657    0.5236
      30      25.927    0.15257    0.5236
      30      25.927    0.15486    0.5236
      30      25.927    0.12457    0.5236
      30      25.927    0.12457    0.5236
      30      25.927    0.15829    0.5236
      30      25.927    0.13657    0.5236
      30      25.927      0.124    0.5236
      30      25.927      0.108    0.5236
      30      25.927    0.10343    0.5236
      30      25.927    0.12914    0.5236
      30      25.927    0.18229    0.5236
      30      25.927    0.19371    0.5236

[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.

.

[Douglas Leaffer]

Thank you VBBV and Star Strider. Both of your suggested codes worked for me - but I can't seem to rotate the compass points to have 0 at the top and then clockwise ticks, with 90 deg at right, 180 at bottom and 270 at left. Is there a simple programmatic fix for this?

[Star Strider]

It is straightforward to add those using the ThetaZeroLocation and ThetaDir properties (that I believe existed before R2022a, so you should have them) —

LD = load('winddata.mat');
N = LD.N;

N.WD_Rad = deg2rad(N.WD_Deg)                                                % Add Radian Variable (For Convenience, Since 'polarplot' Requires It)

N = 133872×4 table
    WD_Deg      WS      UFPConc    WD_Rad
    ______    ______    _______    ______

      30      25.927    0.11886    0.5236
      30      25.927    0.13314    0.5236
      30      25.927    0.16629    0.5236
      30      25.927    0.15657    0.5236
      30      25.927    0.15257    0.5236
      30      25.927    0.15486    0.5236
      30      25.927    0.12457    0.5236
      30      25.927    0.12457    0.5236
      30      25.927    0.15829    0.5236
      30      25.927    0.13657    0.5236
      30      25.927      0.124    0.5236
      30      25.927      0.108    0.5236
      30      25.927    0.10343    0.5236
      30      25.927    0.12914    0.5236
      30      25.927    0.18229    0.5236
      30      25.927    0.19371    0.5236

[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
Ax = gca;
Ax.ThetaZeroLocation = 'top';
Ax.ThetaDir = 'clockwise';

figure
polarplot(UDir, Concv)                                                      % Plot Continuous Result
Ax = gca;
Ax.ThetaZeroLocation = 'top';
Ax.ThetaDir = 'clockwise';

figure
polarhistogram(N.WD_Rad, UDir)                                              % Plot Using 'polarhistogram' 
Ax = gca;
Ax.ThetaZeroLocation = 'top';
Ax.ThetaDir = 'clockwise';

.

[Douglas Leaffer]

Excellent. It worked fine. Thank you

[Star Strider]

As always, my pleasure!

Answer 2

[Douglas Leaffer]

Hello, it seems the plots generated from these suggested answers are not what I need. I need a normalized [0 1] wind rose of UFP (air pollution particle) by wind degree sector, as show in these 3 examples. My dataset is attached. The code I ran is given below. I could use some more help if anyone is able. Thank you.

load CR_1hr_wind.mat
NC = normalize(CT1,"norm",Inf,"DataVariables","UFPConc");
NC.WD_Rad = deg2rad(NC.WD_Deg)                                                % Add Radian Variable (For Convenience, Since 'polarplot' Requires It)
[UDir,ix,iv] = unique(NC.WD_Rad);                                            %  Unique Radian Values & Indices (Sorted)
Concv = accumarray(iv, (1:numel(iv)).', [], @(x)numel(NC.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)  
figure
%subplot (121)
polarplot(UDir, Concv, 'LineWidth', 4)                                                      % Plot Continuous Result
Ax = gca;
Ax.ThetaZeroLocation = 'top';
Ax.ThetaDir = 'clockwise';

[Star Strider]

To normalise them, divide by the maximum:

Concv = Concv/max(Concv);

Try this —

load CR_1hr_wind.mat
NC = normalize(CT1,"norm",Inf,"DataVariables","UFPConc");
NC.WD_Rad = deg2rad(NC.WD_Deg)                                                % Add Radian Variable (For Convenience, Since 'polarplot' Requires It)

NC = 1887×4 table
    WD_Deg      WS      UFPConc    WD_Rad 
    ______    ______    _______    _______

     320      14.816    0.65284     5.5851
     310      16.668    0.58952     5.4105
     350      11.112    0.83406     6.1087
     340      12.964    0.80568     5.9341
      80      16.668    0.76419     1.3963
      90      14.816     0.6441     1.5708
      80      24.075    0.50655     1.3963
      70      25.927    0.50655     1.2217
      70      24.075     0.5262     1.2217
      80       18.52    0.57205     1.3963
      60      14.816    0.58079     1.0472
      50      12.964    0.73362    0.87266
      40      14.816    0.50873    0.69813
      50      7.4078    0.63755    0.87266
     360      7.4078    0.48472     6.2832
       0           0     0.6441          0

[UDir,ix,iv] = unique(NC.WD_Rad);                                            %  Unique Radian Values & Indices (Sorted)
Concv = accumarray(iv, (1:numel(iv)).', [], @(x)numel(NC.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)  

Concv = Concv/max(Concv);

figure
%subplot (121)
polarplot(UDir, Concv, 'LineWidth', 4)                                                      % Plot Continuous Result
Ax = gca;
Ax.ThetaZeroLocation = 'top';
Ax.ThetaDir = 'clockwise';

If you want to scale over different limits, use the rescale function.

If you intend something else, please be specific.

.

[Douglas Leaffer]

That seems to be more of what I need. Thanks again

[Star Strider]

As always, my pleasure!