How do I plot the following data in the same figure using MATLAB?
Frequency is measured in Hertz (Hz) and should be horizontal axis.
Fall Time is measured in microseconds (us) and should be vertical axis.
freq1 goes with falltime1
freq2 goes with falltime2
freq3 goes with falltime3
They should all be in different colors and the graph should have a legend.
How can I achieve this in MATLAB?
The hold on command is probably what you want.
figure
hold on
plot(freq1, falltime1, 'r-o') % plot in red, circles connected with lines
plot(freq2, falltime2, 'g-o') % plot in green, circles connected with lines
plot(freq3, falltime3, 'b-o') % plot in blue, circles connected with lines
legend('1', '2', '3') % legend text
xlabel('Hertz (Hz)')
ylabel('Fall Time (\mus)')
Related
I need to develop an algorithm that assigns a probability to each pixel of a picture according to its RGB color code. If the pixel is completely red the probability is one. The probability lowers the less red the pixel gets. The blue pixels should be assigned with the lowest probability. I work with python. Thanks a lot for your help!
Color pattern of interest
RGB has 3 components: red, green, blue.
You could do it so it's: p = Math.max(0, red - (green + blue)/2)
If you want to discard green, p = Math.max(0, red - blue).
If values are within [0..255] (0x0..0xFF) you can normalize that to the interval [0..1]
Face and feature landmarks
I have a face image that has labelled face features. The image is stored in standard JPEG format and the landmarks are stored in [x y] format (x,y of point corresponds to its coordinates on the image as shown below)
Interpolated 3d face mesh
I have generated depth information (a 3d mesh) for each of the labelled points, and have a matrix in [x y z] format, where the coordinates x and y are the same as that of the points.
The sparse mesh looks like this:
I then interpolated over xrange, yrange and zrange to get a better mesh. Using mesh(xrange,yrange,zrange) gives me the following
The colours for face image pixels can be obtained using imread(face_image.jpg).
Given that the (x,y) value of each of the interpolated point corresponds to (x,y) in the image, is it possible to make the colour of the pixel at (x,y,z)[3dmesh] the same as colour of (x,y)[face image]?
This would effectively superimpose/warp the face on the3d mesh, giving me a 3d face model.
I would suggest this:
n=50000; % chose something appropriate
[C,map] = rgb2ind(FaceImageRGB,n);
To map the color in your RGB image into a linear index. Make sure the mesh and the RGB image have the same x-y dimensions.
Then use surf to plot the surface with the indexed values for color (should be in the form surf(X,Y,Z,C)) and the map as color map.
surf(3dmesh, C), shading flat;
colormap(map);
Edit: a working example (with a colorful image this time...):
rgbim=imread('http://upload.wikimedia.org/wikipedia/commons/0/0d/Loriculus_vernalis_-Ganeshgudi,_Karnataka,_India_-male-8-1c.jpg');
n=50000; % chose something apropriate
[C,map] = rgb2ind(rgbim,n);
% Creation of mesh with the same dimensions as the image:
[X,Y] = meshgrid(-floor(size(rgbim, 2)/2):floor(size(rgbim, 2)/2), -floor(size(rgbim, 1)/2):floor(size(rgbim, 1)/2));
% An arbitrary function for Z:
Z=-(X.^2+Y.^2);
% Display the surface with the image as color value:
surf(X, Y, Z, double(C)), shading flat
colormap(map);
Result:
I have a 512*512 matrix which contains calculated probabilities. I am trying to plot the ocuucrences of 0s and 1s of these using a heatmap so that my final image is somewhat like an inverted flattened gaussian function;
the problem is my code returns an image where all values are along the 0 only; this is not possible as I have an almost equal probability of 0s and 1s. Is there some problem with my plotting of the values?
X = reshape(prob_to_1,512,512); % prob_to_1 is the matrix of probabilities which
% is reshaped to a 512*512 matrix
colormap('hot');
imagesc(X);
set(gca, 'XTick', [0:0.05:1]*512, 'XTickLabel',[0:0.05:1]) % 10 ticks
set(gca, 'YTick', [0:0.1:1]*512, 'YTickLabel',[0:0.1:1]*100) % 20
colorbar('YTickLabel',{'100%','90%','80%','70%','60%','50%','40%','30%','20%','10%','0%'})
I have attached an image showing my output. As you can see, the black line which shows the no.of 1s should have been at the extreme right on the x-axes (close to prob of 1).
Any suggestions/ideas?
Thanks!
Well, the second image is a histogram of the same data. hist(X,nbins) is sufficient for plotting it.
Though I have found a lot of topics on color tint and temperature, but till now I have not seen any definite solution, which is the reason I am creating this post..My apologies for that.
I am interested in adjusting color temp and tint in images from RGB values, somewhat similar to the iPhoto application found in iOS where it can be adjusted with a slider bar from left to right.
Whatever I have found, temp and tint are orthogonal properties, where temp adjustment is along the blue (left; cool colors)--yellow(right; warm colors) and tint along the green (left) -- magenta (right) axis.
How do I adjust them using formulas from RGB values i.e., uderlying implementation of the color temp and tint slider bars.
I can convert them to HSV space and then I can rotate the hue wheel channel towards those (blue, yello, green, magenta) angles, but how to do them in a systematic fashion similar to the slider bar implementation by changing gradually from low level (middle of the slider bar) to high level (right/left ends of the slider bar).
Thanks!
You should try using HSL instead of HSV. HSL saturation separates itself from the hue and luminosity has very definitive range when it comes to mathematical calculation.
In HSL, to add tint you move the L factor between 50-100 and to add shade the L factor varies between 0-50. Also saturation for HSL controls the tone directly unlike HSV.
For temperature, you have to devise your own stratagy changing the color between red and blue but one golden hint that I can give you is "every pure RGB color has one of 3 color values as zero, second fixed to 255 and 3rd varies with the factor of 255/60.
Hope this helps-
Whereas color temparature is a physical value, its expression
in terms of RGB values
not
trivial. If all you need is a pair of orthogonal axes in the RGB colorspace for the visual adjustment of white balance, they can be defined with relative ease in such a way as to resemble the true color temperature and its derivative the tint.
Let us name our RGB temperature BY—for the balance between blue and yellow, and our RGB tint GR—for the balance balance between green and red. Now, these functions must satisfy the following obvious requirements:
They shall not depend on brightness, or be invariant to multiplication of all the RGB components by the same factor:
BY(r,g,b) = BY(kr, kg, kb),
GR(r,g,b) = GR(kr, kg, kb).
They shall be zero for neutral gray:
BY(0,0,0) = 0,
GR(0,0,0) = 0.
They shall belong the to same range, symmetrical around zero point. I will use [-1..+1]
Any combination of BY and GR shall define a valid color.
Now, one of the ways to define them could be:
BY = (r + g - 2b)/(r + g + 2b),
GR = (r - g )/(r + g) .
so that each pair of BY and GR determines a specific proportion
r:g:b = (1 + BY)(1 + GR)
(1 + BY)(1 - GR)
1 - BY
The following image shows the colors of maximum brightness on our BY-GR plane. BY is directed right, GR down, and the neutral point (0,0) is at the center:
Proper
adjustment of white balance consists of multiplication of the linear RGB values by individual factors:
r_new = wb_r * r_old
g_new = wb_g * g_old
b_new = wb_b * b_old
It happens to work on gamma-compressed RGB too, but not so well on sRGB, because of a
piece-wise
definition of its transfer function, but the distortion will be small and often unnoticeable. If you want a perfect adjustment, however, make sure to work in linear RGB.
Once a BY-GR pair is chosen and the corresponding RGB proportion calculated, only one degree of freedom remains—the overall multiplier (see req. 1). Choose it so that no pixels become clipped.
So I have this matrix in MATLAB, 200 deep x 600 wide. It represents an image that is 2cm deep x 6cm wide. How can I plot this image so that it is locked into proper dimensions, i.e. 2cm x 6cm? If I use the image or imagesc commands it stretches it all out of shape and shows it the wrong size. Is there a way to lock it into showing an image where the x and y axes are proportional?
Second question, I need to then set this image into a 640x480 frame (20 pixel black margin on left and right, 280 pixel black margin on bottom). Is there a way to do this?
To keep aspect ratio, you can use axis equal or axis image commands.
Quoting the documentation:
axis equal sets the aspect ratio so that the data units are the same in every direction. The aspect ratio of the x-, y-, and z-axis is adjusted automatically according to the range of data units in the x, y, and z directions.
axis image is the same as axis equal except that the plot box fits tightly around the data`
For second question:
third_dimension_size=1; %# for b&w images, use 3 for rgb
framed_image=squeeze(zeros(640,480,third_dimension_size));
framed_image(20:20+600-1,140:140+200-1)= my_600_200_image;
imagesc(framed_image'); axis image;
set(gca,'DataAspectRatio',[1 1 1])
Second question:
new_image = zeros(480,640);
new_image(20:(200+20-1),20:(600+20-1)) = old_image;
As an alternative to the other answers, you might want:
set(gca, 'Units', 'centimeters', 'Position', [1 1 6 2])
Make sure you do this after plotting the image to get the other axis properties correct.
For the second question, take care with the number of colour channels:
new_image = zeros(480,640, size(old_image));
new_image(20:(200+20-1),20:(600+20-1),:) = old_image;