Plotting Polar Plots using time series data

Question

Jake 2025-2-6

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2173733-plotting-polar-plots-using-time-series-data

评论： Mathieu NOE 2025-2-7

采纳的回答： Mathieu NOE

sampleData.mat

在 MATLAB Online 中打开

I have time series data for angle and speed (sample attached). I can plot the angel on a polarhistogram as follows.

load("sampleData.mat")

whos

Name Size Bytes Class Attributes angle 1x15000 120000 double ans 1x38 76 char speed 1x15000 120000 double time 1x15000 120000 double

figure

h=polarhistogram(angle);

set(gca,'ThetaTick', [0 30 60 90 120 150 180 210 240 270 300 330], ...

'ThetaTickLabel',{0 30 60 90 120 150 180 210 240 270 300 330})

set(gca,'ThetaZeroLocation','top','ThetaDir','clockwise');

h.DisplayStyle = 'stairs';

But I want to include the speed within the plot too, something similar to a countourf plot or Perfect Polar Plots as below. I tried using the custom function, but I couldn't make it work. How can I do this?

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Jake 2025-2-7

Hi @Mathieu NOE, thank you for this suggestion. I agree that this is kind of a better option when the angle range is very small. I like this one and the answer you suggested :)

Mathieu NOE 2025-2-7

hello Jake

glad I could be of some help !

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Answer 1

Mathieu NOE 2025-2-6

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2173733-plotting-polar-plots-using-time-series-data#answer_1559233

编辑：Mathieu NOE 2025-2-6

在 MATLAB Online 中打开

dscatterpolar.m

hello again

well, maybe I'm stupid but I coud not yet figure out how to use Perfect Polar Plots without having to spend some time to create a density map with the correct dimensions.

so the quick and dirty alternative I can propose is a modified version of dscatter (mentionned above in my comment ) , so let's call it dscatterpolar (see attached)

sorry to the community and to TMW to have frankensteined the original dscatter function !!!

result :

as i said before , the data does not cover a wide angular range so we're left with that narrow beam plot

the ticks in radial correspond to the wind speed

code : in one line

load('sampleData.mat')
% whos
%   Name       Size                Bytes  Class     Attributes
% 
%   angle      1x15000            120000  double              
%   speed      1x15000            120000  double              
%   time       1x15000            120000  double 
figure(1)
[hAxes,col,ctrs1,ctrs2,F] = dscatterpolar(speed(:),angle(:)*pi/180);  % make sure you pass the data speed first and angle in second (and in rad).

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Mathieu NOE 2025-2-7

在 MATLAB Online 中打开

dscatterpolar.m

EDIT

sligth modification : I finally prefer to use rlim and thetalim in the main code and not inside dscatterpolar function. So use the new (attached) version of it

now you can focus on your data if the angualr range is so small you would not see much in the full 0-360° polarplot

clc
clearvars
load('sampleData.mat')
% whos
%   Name       Size                Bytes  Class     Attributes
% 
%   angle      1x15000            120000  double              
%   speed      1x15000            120000  double              
%   time       1x15000            120000  double 
figure(1)
[hAxes,col,ctrs1,ctrs2,F] = dscatterpolar(speed(:),angle(:)*pi/180);  % make sure you pass the data speed first and angle in second (and in rad).
% set R and angle limits to the plot
rlim(gca,[5*floor(min(speed/5)) 5*ceil(max(speed/5))]); % rounded speed values with 5 increments
thetalim(gca,[165 195])
% add R axis label
rruler = hAxes.RAxis;
rruler.Label.String = 'Speed (m/s)';
% add angle axis label
truler = hAxes.ThetaAxis;
truler.Label.String = 'Direction (°)';

Mathieu NOE 2025-2-7

在 MATLAB Online 中打开

hello again

I f you like , this can be a demo for you , but again, as the angular range of your data is very small , you see only a very narrow beam and it's hard to see the density variations

full circle rendering

code :

load('sampleData.mat')
% whos
%   Name       Size                Bytes  Class     Attributes
% 
%   angle      1x15000            120000  double              
%   speed      1x15000            120000  double              
%   time       1x15000            120000  double 
% create 2D histogram data
[n,xedges,yedges] = histcounts2(angle, speed, 'BinMethod', 'auto');
xcenters = xedges(1:end-1) + diff(xedges) / 2;
ycenters = yedges(1:end-1) + diff(yedges) / 2;
% Points between the outmost bin are tricky, using the
% outermost bin (similar to imfilter's replicate option) is
% a decent approximation
xi = [xedges(1) xcenters xedges(end)];
yi = [yedges(1) ycenters yedges(end)];
n = [n(:,1) n n(:,end)];
n = [n(1,:); n; n(end,:)];
if numel(ycenters) == 1
    d = interp1(xi,n',angle);
elseif numel(xcenters) == 1
    d = interp1(yi,n',speed);
else
    [xi,yi] = meshgrid(xi, yi);
    d = interp2(xi, yi, n', angle, speed);
end
   
% Then set up the grid, as with the previous examples:
figure(5); clf
ph = makePolarGrid(...
  'ALabelScheme', 'normal',...
  'RTicks',        15:1:25,...  % Radial ticks (inner circles)
  'RUnits',        '[m/s]',...   % Add units to outer-most radial labels
  'RLabelAngle',  170,...        % Angle where the radial tick labels will go
  'RLabelFormat', '%.0f');      % Format for radial labels     
[md,mf] = meshgrid(xcenters, ycenters);
I = scatteredInterpolant(angle(:), speed(:), d(:),'linear','none');
Z = I(md,mf);
% Now convert to cartesian coords
[px,py] = polgrid2cart(md, mf, ph);
% And then use contourf to plot. Optional formatting adjustments follow.
[~,hc]  = contourf(px, py, Z);
uistack(hc, 'bottom');  % this will put the grid on top of the contours
% hc.LevelList(1:5) = [];    % this removes the countours on lowest level(s) 
hc.LineStyle = 'none';  % enable/disble contour lines
colormap jet
title('Wave Directional Spectrum')

Mathieu NOE 2025-2-7

在 MATLAB Online 中打开

tried to narrow down the circle grid with the hope that I would zoom into the area of interest , but I just get a small portion of the full circle rendering, so not very useful here

code :

the only difference in the code is this added parameters :

'ALim', [173,187],... % span of circle grid

load('sampleData.mat')
% whos
%   Name       Size                Bytes  Class     Attributes
% 
%   angle      1x15000            120000  double              
%   speed      1x15000            120000  double              
%   time       1x15000            120000  double 
% create 2D histogram data
[n,xedges,yedges] = histcounts2(angle, speed, 'BinMethod', 'auto');
xcenters = xedges(1:end-1) + diff(xedges) / 2;
ycenters = yedges(1:end-1) + diff(yedges) / 2;
% Points between the outmost bin are tricky, using the
% outermost bin (similar to imfilter's replicate option) is
% a decent approximation
xi = [xedges(1) xcenters xedges(end)];
yi = [yedges(1) ycenters yedges(end)];
n = [n(:,1) n n(:,end)];
n = [n(1,:); n; n(end,:)];
if numel(ycenters) == 1
    d = interp1(xi,n',angle);
elseif numel(xcenters) == 1
    d = interp1(yi,n',speed);
else
    [xi,yi] = meshgrid(xi, yi);
    d = interp2(xi, yi, n', angle, speed);
end
   
% Then set up the grid, as with the previous examples:
figure(5); clf
ph = makePolarGrid(...
  'ALabelScheme', 'normal',...
  'ALim',       [173,187],...     % span of circle grid
  'RTicks',        15:1:25,...  % Radial ticks (inner circles)
  'RUnits',        '[m/s]',...   % Add units to outer-most radial labels
  'RLabelAngle',  170,...        % Angle where the radial tick labels will go
  'RLabelFormat', '%.0f');      % Format for radial labels     
[md,mf] = meshgrid(xcenters, ycenters);
I = scatteredInterpolant(angle(:), speed(:), d(:),'linear','none');
Z = I(md,mf);
% Now convert to cartesian coords
[px,py] = polgrid2cart(md, mf, ph);
% And then use contourf to plot. Optional formatting adjustments follow.
[~,hc]  = contourf(px, py, Z);
uistack(hc, 'bottom');  % this will put the grid on top of the contours
% hc.LevelList(1:5) = [];    % this removes the countours on lowest level(s) 
hc.LineStyle = 'none';  % enable/disble contour lines
colormap jet
title('Wave Directional Spectrum')

Jake 2025-2-7

在 MATLAB Online 中打开

sampleData_02.mat

This is a very nice approach! I have two questions though - one related to this specifically, and the other one slightly different.

In this generated plot, can we fill the rest of the space too, something similar to the one below (taken from here) with a colorbar?

I tried plotting two polarhistogram plots with the following code:

clear; close all; clc

load("sampleData_02.mat");

whos

Name Size Bytes Class Attributes angle_01 1x10000 80000 double angle_02 1x10000 80000 double speed_01 1x10000 80000 double speed_02 1x10000 80000 double time 1x10000 80000 double

figure

h1=polarhistogram(angle_01); hold on

h2=polarhistogram(angle_02);

set(gca,'ThetaTick', [0 30 60 90 120 150 180 210 240 270 300 330], ...

'ThetaTickLabel',{0 30 60 90 120 150 180 210 240 270 300 330})

set(gca,'ThetaZeroLocation','top','ThetaDir','clockwise');

[min(angle_01), max(angle_01); min(angle_02), max(angle_02)]

ans = 2×2

179.3354 180.0000 177.7802 180.0000

As can be seen, the angle range is small, but the plot shows the angles very differently. What would be the reason for this, and can it be fixed?

Jake 2025-2-7

Hi @Mathieu NOE, Thank you for all the help - this is good :)

You're right - I made the silly mistake of passing degrees instead of radians to polarhistogram!

Mathieu NOE 2025-2-7

as always, my pleasure !

tx for accepting my suggestions !

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Plotting Polar Plots using time series data

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Plotting Polar Plots using time series data

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