I am trying to create a plot that looks like this with rings of constant values (colors) extending from 0 to 100 in 10 unit increments.
Rings of single values extending outward from center
However, my code is not producing this, and I do not know where it has gone wrong.
% values representing the colors that each ring should be
% starting from the center and moving outwards in 10 unit increments.
values = [364,358,354,348,339,335,330,325,320,310];
xCoord = linspace(0,2*pi,10);
yCoord = linspace(0,100,10);
[TH,R] = meshgrid(xCoord,yCoord);
[X,Y] = pol2cart(TH,R);
[Z] = meshgrid(values);
contour_ticks = 300:5:375;
figure
hold on
contourf(X,Y,Z,contour_ticks);
a=gca; cb=colorbar; colormap('jet'); caxis([300 375]);
This produces a plot resembling this:
Incorrect plot
Any ideas what I'm doing wrong? Any help is greatly appreciated. Thanks.
If you just want to plot circles, you can use the following approach:
radii = 100:-10:10; %// descending order, so that bigger circles don't cover small ones
colors = parula(numel(radii)); %// or use some other colormap
for n = 1:numel(radii)
r = radii(n);
rectangle('Position', [-r -r 2*r 2*r], 'Curvature', [1 1], 'FaceColor', colors(n,:),...
'EdgeColor', 'none') %// plot each circle using sequential colors, no edge
hold on
end
axis equal
axis([-1 1 -1 1]*max(radii))
Related
I generate a random number between 1 and 2 as a radius for my circle. Then I plot my circle and saves it as a png. Also, several data points are generated both inside and outside the circle to make it noisy.
Then I will use Hough Transform to estimate the radius for the circle but, the number which it returns is more than 100. Although they are the same circles(I plotted to make sure).
I have tried to use polyfit function to map these two numbers but, the estimated radius seems to be smaller than the real one in some examples. After mapping It returns the same number. For example, a random radius is 1.2 and Hough estimates it 110 however it seems that it should be near 1.(Because I plot it and it is clear that is it smaller). Also, for Hough Transform I am using this code https://www.mathworks.com/matlabcentral/fileexchange/35223-circle-detection-using-hough-transforms
I tried the predefined Matlab function (imfindcircles) but it returns null for all my circles.
r1 = 1 + abs((1)*randn(1,1)); %radius of inner circle
r1 = abs(r1);
r2 = (1.2)*r1; %radius of outercircle
k = 500; %number of random numbers
% circle coordinate points
t = 0:2*pi/59:2*pi;
xv = cos(t)';
yv = sin(t)';
%%%%%%%%random points
xq = 2*randn(k,1)-1;
yq = 2*randn(k,1)-1; %distribution 1
xq1 = 2*(rand(k,1))-1; %distribution 2
yq1 = 2*(rand(k,1))-1;
in = inpolygon(xq1,yq1,r1*xv,r1*yv); %number of points inside the geometry
in1= inpolygon(xq,yq,r2*xv,r2*yv); %points inside outer circle
in2 = xor(in,in1); %points between circle
in3= inpolygon(xq1,yq1,r2*xv,r2*yv); %points inside outer circle
fig = figure(22);hold on;
% Random points
plot(xq(in2),yq(in2),'bo','MarkerFaceColor','r','MarkerSize',5,'Marker','o','MarkerEdgeColor','none');
axis equal;
plot(xq1(~in2),yq1(~in2),'bo','MarkerFaceColor','r','MarkerSize',5,'Marker','o','MarkerEdgeColor','none');
axis equal;
img= getframe(fig);
figure;
imshow(img.cdata)
hold on;
[r,c,rad] = circlefinder(img.cdata);
[m I] = max(rad);
%ploting the bigest estimated circle
angle = 2*pi*randn(k,1);
haffpointX = rad(I).*cos(angle)+ c(I);
haffpointY = rad(I).*sin(angle)+ r(I);
scatter(haffpointX,haffpointY,'g');
axis equal
I expect that for different random circles with noisy data Hough Transform estimates its circle with the number between the range of 1 and 2 so, I can use its results.
Thank you in advance
I am trying to create my own voronoi diagram. I have an arbitrary shape defined by their x and y coordinates stored in separate vectors. Inside this shape are some points of interest (with known coordinates) that belong to two different groups and act as seeds to the voronoi diagram. As an example, the whole diagram ranges from x=-10 to x=90 and y=-20 to y=60. The boundary shape is not rectangular but falls within the axes range above.
What I have done so far is to create a 3D matrix (100 X 80 X 3), C, with all ones so that the default colour will be white. I then looped through from i=1:100, j=1:80, testing individual pixels to see if they fall within the shape using inpolygon. If they do, I then find out which point is the pixel closest to and assign it a colour based on whether the closest point belongs to group 1 or 2.
All is good so far. I then used imagesc to display the image with a custom axis range. The problem is that the voronoi diagram has the general shape but it is off in terms of position as the pixel coordinates are different from the actual world coordinates.
I tried to map it using imref2d but I do not know how it really works or how to display the image after using imref2d. Please help me on this.
I am open to other methods too!
Thank you!
Edit:
As requested, let me give a more detailed example and explanation of my problem.
Let us assume a simple diamond shape boundary with the following vectors and 4 points with the following coordinate vectors:
%Boundary vectors
Boundary_X = [-5 40 85 40 -5];
Boundary_Y = [20 50 20 -10 20];
%Point vectors
Group_One_X = [20 30];
Group_One_Y = [10 40];
Group_Two_X = [50 70];
Group_Two_Y = [5 20];
Next I plot all of them, with different groups having different colours.
%Plot boundary and points
hold on
plot(Boundary_X,Boundary_Y)
scatter(Group_One_X,Group_One_Y,10,'MarkerFaceColor','Black',...
'MarkerEdgeColor','Black')
scatter(Group_Two_X,Group_Two_Y,10,'MarkerFaceColor','Red',...
'MarkerEdgeColor','Red')
hold off
axis([-10, 90, -20, 60])
This is the result:
Boundary with points
Next I test the whole graph area pixel by pixel, and colour them either cyan or yellow depending on whether they are closer to group 1 or 2 points.
%Create pixel vector with default white colour
C=ones(100,80,3);
Colour_One = [0 1 1];
Colour_Two = [1 1 0];
%Loop through whole diagram
for i=1:100
for j=1:80
x=i;
y=j
if inpolygon(x,y,Boundary_X,Boundary_Y)
%Code for testing which point is pixel closest to
%If closest to group 1, assign group 1 colour, else group 2
%colour
end
end
end
%Display image
hold on
imagesc(C)
hold off
This is the result
Failed Voronoi Diagram
The shape is somewhat correct for the right side but not for the others. I understand that this because my world coordinates start from negative values but the pixel coordinates start from 1.
Hence I am at a lost as to how can I solve this problem.
Thank you!
One thing to notice is that you have to convert between image and plot coordinates. The plot coordinates are (x,y) where x goes to the right, and y goes up. The matrix coordinates are (i,j) where i goes down, and j to the right. An easy way to do this is with the use of vec_X,vec_Y as shown below.
Another solution for the newer Matlab versions would be - as you said - using imref2d but unfortunately I have no experience with that command.
%Boundary vectors
Boundary_X = [-5 40 85 40 -5];
Boundary_Y = [20 50 20 -10 20];
%Point vectors
Group_One_X = [20 30];
Group_One_Y = [10 40];
Group_Two_X = [50 70];
Group_Two_Y = [5 20];
%Coordinate system
min_X = -10;
max_X = 90;
min_Y = -20;
max_Y = 60;
axis([min_X, max_X, min_Y, max_Y])
%Create pixel vector with default white colour
rows_N = 100;
columns_N = 80;
C=ones(rows_N,columns_N,3);
%These vectors say where each of the pixels is in the plot coordinate
%system
vec_X = linspace(min_X,max_X,columns_N);
vec_Y = linspace(min_Y,max_Y,rows_N);
Colour_One = [0 1 1];
Colour_Two = [1 1 0];
%Loop through whole diagram
for i=1:100
for j=1:80
if inpolygon(vec_X(j),vec_Y(i),Boundary_X,Boundary_Y)
%calculate distance to each point
Distances_One = zeros(size(Group_One_X));
Distances_Two = zeros(size(Group_Two_X));
for k=1:numel(Group_One_X);
Distances_One(k) = norm([Group_One_X(k),Group_One_Y(k)]-[vec_X(j),vec_Y(i)]);%assuming euclidean norm, but can be adjusted to whatever norm you need
end
for k=1:numel(Group_Two_X);
Distances_Two(k) = norm([Group_Two_X(k),Group_Two_Y(k)]-[vec_X(j),vec_Y(i)]);%assuming euclidean norm, but can be adjusted to whatever norm you need
end
if min(Distances_One) < min(Distances_Two);
C(i,j,:) = Colour_One;
else
C(i,j,:) = Colour_Two;
end
end
end
end
%Display image
imagesc(vec_X,vec_Y,C) %lets you draw the image according to vec_X and vec_Y
%Plot boundary and points
hold on
plot(Boundary_X,Boundary_Y)
scatter(Group_One_X,Group_One_Y,10,'MarkerFaceColor','Black',...
'MarkerEdgeColor','Black')
scatter(Group_Two_X,Group_Two_Y,10,'MarkerFaceColor','Red',...
'MarkerEdgeColor','Red')
hold off
I have a vector of values that I want to plot as brightness on a circle through the radius of it (I.e. If it was 0 3 1 5 I'd want a circle that was dark at the centre, then a bright ring around it, then a slightly darker ring, then a brighter ring).
To do this I've attempted to rotate my radial vector (E) around the y axis, as such
[X,Y,Z] = cylinder(E);
h = surf(X,Y,Z),
However I'm clearly not doing it right, as this appears to be rotating my curve around the x axis. I've tried just swapping X and Y, but it still rotates it around the x axis. Any help would be greatly appreciated.
One way would be to rotate your vector and create a surface. The Z data of the surface (your rotated vector) will be color coded according to the colormap you choose, if you display the surface from the top you get your circles at the different brightness.
If you are really only interested from the "top view" of this surface, then no need to create a full surface, a simple pcolor will do the job.
example:
%% // input data (and assumptions)
E=[0 3 1 5 2 7];
nBrightness = 10 ; %// number of brightness levels
r = (0:numel(E)) ; %// radius step=1 by default for consecutive circles
%// otherwise define different thickness for each circle
So if I use stairs([E 0]) you get your different brightness levels:
I had to add a last 0 to the vector to "close" the last level, we'll have to do that again in the solution below.
Now to rotate/replicate that around Y, color code the height, and look at it from the top:
%% // replicate profile around axis
ntt = 50 ; %// define how many angular division for the plot
theta = linspace(0,2*pi,ntt) ; %// create all the angular divisions
[rr,tt]=meshgrid(r,theta) ; %// generate a grid
z = repmat( [E 0] , ntt , 1 ) ; %// replicate our "E" vector to match the grid
[xx,yy,zz] = pol2cart(tt,rr,z) ; %// convert everything to cartesian coordinates
pcolor(xx,yy,zz) %// plot everything
colormap(gray(nBrightness)) %// make sure we use only "nBrightness" colors (Shades of gray)
caxis([0 nBrightness])
shading flat ; axis equal %// refine the view (axis ratio and "spokes" not visible) etc...
colorbar
axis off
will yield the following :
Note that your problem was not fully defined, I had to take assumptions on:
What radius each brightness circle should have ? (I made them all the same but you can modify that)
How many brightness levels you want ? (You can also modify that easily though).
Have you tried the rotate function?
direction = [0 1 0];
rotate(h,direction,90);
In this example a 90 degree rotation is performed around the y axis.
Using this library http://www.mathworks.com/matlabcentral/fileexchange/45952-circle-plotter
%http://www.mathworks.com/matlabcentral/fileexchange/45952-circle-plotter
x0 = 0;
y0 = 0;
colors = [0 3 1 5];
maxC = max(colors);
sz = numel(colors);
for i=fliplr(1:sz)
c = colors(i);
circles(x0,y0,i,'facecolor',[c/maxC c/maxC 0]) % http://au.mathworks.com/help/matlab/ref/colorspec.html
end
I have two datasets. One detailing a list of angles (which I am plotting onto a rose plot):
angles
-0.8481065519
0.0367932161
2.6273740453
...
n
The other, detailing directional statistics from this group of angles:
angle,error
-0.848106563,0.8452778824
Where angle essentially defines the directional mean, and error the circular variance, essentially an error bar either side of the angle
I have thus far plotted a rose histogram using the set of angles, as such:
h = rose(angles,36)
I would like to create a plot of the directional statistic angle (it does not need a length/magnitude - just to the edge of the circle plot) with the error around it.
As an example:
I added the lines by hand in Matlab. If possible it would be good to perhaps have shading within the arc too. Alternatively, (and possibly preferred) would be to have just a sliver above the rose plot bins (so it doesn't cover the data) with a centre line (showing the angle and shading surrounding for the error.
Thanks in advance.
How about this?
%// Data
angles = 2*pi*.8*randn(1,1e4);
angle = -0.848106563;
error = 0.8452778824;
%// Plot rose
rose(angles, 36);
axis image %// make axis square
hold on
%// Plot mean
a = axis;
a = a(2); %// size of axis
plot([0 cos(angle)*a], [0 sin(angle)*a], 'r')
%// Plot error as many shaded triangles that compose a circular wedge
t = linspace(-error/2+angle,error/2+angle,100); %// increase "100" if needed
for k = 1:numel(t)-1
h = patch([0 cos(t(k))*a cos(t(k+1))*a 0], ...
[0 sin(t(k))*a sin(t(k+1))*a 0], [.5 0 0], 'edgecolor', 'none');
%// change color [.5 0 0] to something else if desired. Note also alpha
set(h,'Facealpha',.3) %// make transparent
end
%// Place rose on top by rearranging order of axis children
ch = get(gca,'children');
set(gca,'children',[ch(2:end); ch(1)]);
For this to work, you need to use a figure renderer capable of transparency. So you may need to adjust the figure's renderer property.
I was trying use the code shown below to plot in such a way that each iso-surface will be different in color and there will be a color bar at the right. I made a ss(k) color matrix for different colors. Number of iso-surfaces is 10 but I have only 8 colors. That's why I wrote ss(9)='r' and ss(10)='r'.
I need a solution to plot the iso-surface with different color and bar at the right side.
ss=['y','m','c','r','g','b','w','k','r','r']
k=1;
for i=.1:.1:1
p=patch(isosurface(x,y,z,v,i));
isonormals(x,y,z,v,p)
hold on;
set(p,'FaceColor',ss(k),'EdgeColor','none');
daspect([1,1,1])
view(3); axis tight
camlight
lighting gouraud
k=k+1;
end
Another possibility is to draw the patches with direct color-mapping (by setting the property 'CDataMapping'='direct'), while assigning the 'CData' of each patch to an index in the colormap of your choice. This is in fact recommended for maximum graphics performance.
Consider the following example:
%# volumetric data, and iso-levels we want to visualize
[x,y,z,v] = flow(25);
isovalues = linspace(-2.5,1.5,6);
num = numel(isovalues);
%# plot isosurfaces at each level, using direct color mapping
figure('Renderer','opengl')
p = zeros(num,1);
for i=1:num
p(i) = patch( isosurface(x,y,z,v,isovalues(i)) );
isonormals(x,y,z,v,p(i))
set(p(i), 'CData',i);
end
set(p, 'CDataMapping','direct', 'FaceColor','flat', 'EdgeColor','none')
%# define the colormap
clr = hsv(num);
colormap(clr)
%# legend of the isolevels
%#legend(p, num2str(isovalues(:)), ...
%# 'Location','North', 'Orientation','horizontal')
%# fix the colorbar to show iso-levels and their corresponding color
caxis([0 num])
colorbar('YTick',(1:num)-0.5, 'YTickLabel',num2str(isovalues(:)))
%# tweak the plot and view
box on; grid on; axis tight; daspect([1 1 1])
view(3); camproj perspective
camlight; lighting gouraud; alpha(0.75);
rotate3d on
I also included (commented) code to display the legend, but I found it to be redundant, and a colorbar looks nicer.
Matlab usually plots different iso-surfaces in different colors automatically, so you don't need to care about that. What kind of bar do you need? A colorbar or a legend? Either way, it is just to use the colorbar or legend function..
%Create some nice data
[x y z] = meshgrid(1:5,1:5,1:5);
v = ones(5,5,5);
for i=1:5
v(:,:,i)=i;
end
v(1:5,3:5,2)=1
v(1:5,4:5,3)=2
%Plot data
for i=1:5
isosurface(x,y,z,v,i)
end
%Add legend and/or colorbar
legend('one','Two','Three','Four')
colorbar
Since the color bar encodes value->color, it is impossible to do what you ask for, unless there is no intersection in z-values between all pairs of surfaces. So the solution below assumes this is the case. If this is not the case, you can still achieve it by adding a constant value to each surface, so to separate the surfaces along the z axis, and eliminate any intersection.
The solution is based on constructing a colormap matrix of piecewise constant values, distributed similarly to the z values of your surfaces. So for example, if you have 3 surfaces, the first has z values between 1 and 10, the 2nd between 11 and 30, and the 3rd between 31 and 60, you should do something like this (I plot in 2D for simplicity)
r = [1 0 0];
g = [0 1 0];
b = [0 0 1];
cmap = [r(ones(10,1),:); g(ones(20,1),:); b(ones(30,1),:)];
z1 = 1:10;
z2 = 11:30;
z3 = 31:60;
figure; hold on
plot(z1,'color',r)
plot(z2,'color',g)
plot(z3,'color',b)
colorbar
colormap(cmap)
More complex colormaps (i.e, more colors) can be constructed with different mixtures of red, green, and blue (http://www.mathworks.com/help/techdoc/ref/colorspec.html)