2D Plotting a 3D point cloud as set of lines - matlab

Question

I have a three dimensional array of points.
I need to plot them on a 2D [x,z] grid, where every line is based on the value of Y inside a range.
es. the first line is made by points with 0 < y < 1, the second with 1 < y < 2, etc..
I can plot points just fine using this script(to have a better looking graph i'm also changing the color for every set of point by moving inside an rgb triplet).
set is the range of the line (in my case Y is time and i need to plot every 0.1 seconds). i is the index for my array of points.
w= 0;
yend = 100;
set = 0.1;
numberOfColors = 1/2*(Yinterval)*(1/set);
incrementOfColor = 1/numberOfColors;
red = 0;
green = 0;
blue = 1;
color=[red green blue];
while w < yend
while y(i)>w&&y(i)<w+set
figure(1)
hold on
plot(x(i),z(i),'.','Color',color);
hold on
i=i+1;
end
w=w+set;
if red < 1-incrementOfColor && blue > 0
red = red + incrementOfColor;
blue = blue - incrementOfColor;
end
if red > incrementOfColor && blue < incrementOfColor
red = red-incrementOfColor;
green = green + incrementOfColor;
blue = 0;
end
color = [red green blue];
end
And this is the result:
http://i.imgur.com/HTyzWai.png
When there's too much data the plot becomes cumbersome to read, and with too little data isolated points don't really tell much.
I've tried converting the points inside a "set" interval into an array but it really didn't work out:
while w < yend
while y(i)>w&&y(i)<w+set
vX(a,:)=x(i);
vZ(a,:)=z(i);
i=i+1;
a=a+1;
end
figure(2)
hold on
plot(vX,vZ,'-','Color',color);
Gave this result: imgur.com/S7OasUn.jpg
Is my conversion wrong or arrays are just not the proper way to handle this? If so, what should I use?
I'm rather new to matlab so if this is really obvious or i'm asking something in the wrong way, please excuse me.
edit:
This is the result i want to achieve:
imgur.com/jPZTO8E.png
and it was obtained with Origin's contour profile tool.
I guess you mean this with functional example:
myPoints[i]:
i=0, x = 1, y= 0.03, z = 1
i=1, x = 2, y= 0.06, z = 3
i=2, x = 2.5, y = 0.09, z = 4
i=3, x = 1.2, y = 1.01, z = 3.1
i=4, x = 1.3, y = 1.04, z = 1.1
i=5, x = 1.2, y = 1.06, z = 2.5
i=6, x = 2, y = 1.09, z = 3.1
i=7, x = 1.2, y = 2.02, z = 3.1
etc..
i want the points i 0,1,2 plotted as one line, i 3,4,5 as another line and i 7 etc.. plotted as a third line. In my data i have a lot of points.
this is one example of the data i'm using.
https://drive.google.com/file/d/0B9GHAkIYepQcRXdBdy03dFJtT1k/view?usp=sharing
where:
x = myPoints(:,1);
y = myPoints(:,2);
z = myPoints(:,3);
In this specific case, i only care about the points with y value between 85.85 and 90.85, and i want to "place an edge" (?) every 0.1
x = myPoints(:,1);
y = myPoints(:,2);
z = myPoints(:,3);
ymin = 85.85;
ymax = 90.85;
set = 0.1;
nbins = (ymax-ymin)/set;
binedge = linspace(ymin, ymax, (nbins + 1));

Answer 1

I think I'm understanding what you're attempting to accomplish and I believe you can accomplish your task with a vectorized use of plot rather than having to loop through each of your points.
Given your example data we can give this method a shot:
load('mypoints.mat');
x = myPoints(:,1);
y = myPoints(:,2);
z = myPoints(:,3);
% Bin your data by y values
ymin = 85.85;
ymax = 90.85;
set = 0.1;
nbins = (ymax-ymin)/set;
binedge = linspace(ymin, ymax, (nbins + 1));
[~, ~, binidx] = histcounts(y, binedge);
binloop = unique(binidx);
% Fix for error with unique. If you try to use a for loop with a column
% vector it passes the whole vector as your iterator, so you need to
% transpose it to a row vector.
temp = size(binloop);
if temp(1) ~= 1
binloop = binloop';
end
% Plot
figure
hold on
for ii = binloop
if ii == 0
% These fall outside of our bins, don't plot them
continue
else
dataidx = find(binidx == ii);
% Plot has its own color cycle, or you can add your color changing logic to this loop
plot(x(dataidx), z(dataidx), '-', 'LineWidth', 0.25);
end
end
hold off
What I've done here is to utilize the third output of histcounts to bin your y data and return a bin index for each value in your y vector.
To break the code down a bit:
Define your bin boundaries:
ymin = 85.85;
ymax = 90.85;
set = 0.1;
nbins = (ymax-ymin)/set;
binedge = linspace(ymin, ymax, (nbins + 1));
The linspace call returns the edges of each data bin. Given your example data we get binedge = [86.85, 86.95, 86.05, ..., 90.85]. We then plug in these edges and your y vector to histcounts to obtain our bin indices:
[~, ~, binidx] = histcounts(y, binedge);
Where the bins are defined per the documentation:
The value X(i) is in the kth bin if edges(k) ≤ X(i) < edges(k+1). The
last bin also includes the right bin edge, so that it contains X(i) if
edges(end-1) ≤ X(i) ≤ edges(end).
We can use unique to loop through all of the bins that are present. We can utilize find with MATLAB's logical indexing to plot all data from a single bin in each loop iteration. I ignore where ii == 0 as it indicates where data does not fall under one of the bins (and 0 index is meaningless in MATLAB).
I also played around a bit with the line sizes to try and make the plot a bit easier to read. There's a lot of data to visualize here but it helps a bit. You'll need to do a bit of pruning of your data since your x values wrap back, but that should be trivial.