CODEWITHSUNDEEP
matlabplotmatlab-figure
modellero
modellero

Reputation: 213

How can I create a plot like this in MATLAB?

I am trying to plot the ranges of different cellular base stations in MATLAB, like this:

sample plot

But I can't figure out how to do it.

Upvotes: 1

Views: 2400

Answers (3)

gnovice
gnovice

Reputation: 125854

Here's an example of how you can create a plot like this. Note that I created sample data for the plot by randomly generating the positions of cellular base stations using uniformly distributed pseudorandom numbers:

%# Initializations:
minRange = 0;       %# Lower x and y range
maxRange = 3.5;     %# Upper x and y range
resolution = 1000;  %# The number of data points on the x and y axes
cellRange = linspace(minRange, maxRange, resolution);
[x, y] = meshgrid(cellRange);   %# Create grids of x and y coordinates
cellCoverage = zeros(size(x));  %# Initialize the image matrix to zero

%# Create the sample image data:
numBases = 200;
cellRadius = 0.75;
for iBase = 1:numBases
    point = rand(1,2).*(maxRange - minRange) + minRange;
    index = ((x - point(1)).^2 + (y - point(2)).^2) <= cellRadius^2;
    cellCoverage(index) = cellCoverage(index) + 1;
end

%# Create the plot:
imagesc(cellRange, cellRange, cellCoverage);  %# Scaled plot of image data
axis equal;  %# Make tick marks on each axis equal
set(gca, 'XLim', [minRange maxRange], ...  %# Set the x axis limit
         'YLim', [minRange maxRange], ...  %# Set the y axis limit
         'YDir', 'normal');                %# Flip the y axis direction
xlabel('X-distance (km)');  %# Add an x axis label
ylabel('Y-distance (km)');  %# Add a y axis label
colormap(jet);              %# Set the colormap
colorbar;                   %# Display the color bar

And here's the resulting plot:

enter image description here

Note also that the data in the image matrix cellCoverage contains no noise and has no smoothing applied, which is why the edges appear sharper than the original image in the post (which I'm guessing is generated from real data, not "fake" sample data like I used here).

Upvotes: 5

zamazalotta
zamazalotta

Reputation: 433

You need to get the coordinate of each station then create a circle polygon around it (with a given radius), then convert this polygon into a grid. Then you sum up these grids (matrices) on top of each other. For speed, instead of using polygons you can also define which cells will be covered by a station, like all cells within 5 rows or columns of a station get the value. You can also apply a 2D Gaussian filter to your matrix, where only the cells containing a station have a value of 1. The bandwidth of your Gaussian kernel will be your coverage radius (range). http://www.mathworks.ch/help/toolbox/images/ref/fspecial.html

Upvotes: 0

jdl
jdl

Reputation: 6323

Use "image"

image(x),colormap(hsv) <- where x is a matrix of cellular intensities(x,y)

Upvotes: 0

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