Plotting Polar Plots using time series data
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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
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?
3 个评论
Mathieu NOE
2025-2-6
hello
your angle range is very narrow (178 to 180 °) and I suspect that if you want to plot your density on a polar diagram this will be unreadable as the plot will appear as a very narrow area
instead you can still do a density plot in cartesian coordinates
I am using dscatteravailable here : Flow Cytometry Data Reader and Visualization - File Exchange - MATLAB Central
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] = dscatter(speed(:),angle(:));
xlabel('speed');
ylabel('angle (°)');
grid on
hold on
lb = min(F,[],'all');
ub = max(F,[],'all');
threshold = lb+0.1*(ub-lb); % threshold is 10% of F range above min value
[row,col]=find(F>threshold);
% k = boundary(___,s) specifies shrink factor s using any of the previous syntaxes.
% s is a scalar between 0 and 1. Setting s to 0 gives the convex hull,
% and setting s to 1 gives a compact boundary that envelops the points.
% The default shrink factor is 0.5.
s = 0.75;
k = boundary(row,col,s);
plot(ctrs1(col(k)),ctrs2(row(k)),'r')
hold off
Jake
2025-2-7
Mathieu NOE
2025-2-7
hello Jake
glad I could be of some help !
采纳的回答
Mathieu NOE
2025-2-6
编辑：Mathieu NOE
2025-2-6
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).
9 个评论
Mathieu NOE
2025-2-7
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
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
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')
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
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)]
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?
Mathieu NOE
2025-2-7
编辑：Mathieu NOE
2025-2-7
be carefull that polarhistogram awaits angle in radians and not in degrees
h1=polarhistogram(angle_01*pi/180); hold on
h2=polarhistogram(angle_02*pi/180);
Mathieu NOE
2025-2-7
fyi
you can of course do the same dscatter plot with the two data sets
load('sampleData_02.mat')
% whos
% angle_01 1x10000 80000 double
% angle_02 1x10000 80000 double
% speed_01 1x10000 80000 double
% speed_02 1x10000 80000 double
figure(1)
[hAxes,col,ctrs1,ctrs2,F] = dscatter(speed_01(:),angle_01(:));
hold on
[hAxes,col,ctrs1,ctrs2,F] = dscatter(speed_02(:),angle_02(:));
xlabel('speed');
ylabel('angle (°)');
grid on
Mathieu NOE
2025-2-7
you can do it also in polar plot with
dscatterpolar
as shown already above :
load('sampleData_02.mat')
% whos
% angle_01 1x10000 80000 double
% angle_02 1x10000 80000 double
% speed_01 1x10000 80000 double
% speed_02 1x10000 80000 double
figure(1)
[hAxes,col,ctrs1,ctrs2,F] = dscatterpolar(speed_01(:),angle_01(:)*pi/180); % make sure you pass the data speed first and angle in second (and in rad).
hold on
[hAxes,col,ctrs1,ctrs2,F] = dscatterpolar(speed_02(:),angle_02(:)*pi/180);
grid on
% set R and angle limits to the plot
rlim(gca,[0 25]); % rounded speed values with N increment
thetalim(gca,[180-10 180+10])
% add R axis label
rruler = hAxes.RAxis;
rruler.Label.String = 'Speed (m/s)';
% add angle axis label
truler = hAxes.ThetaAxis;
truler.Label.String = 'Direction (°)';
Jake
2025-2-7
Mathieu NOE
2025-2-7
as always, my pleasure !
tx for accepting my suggestions !
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