Is it possible in imagesc to specify the x-axis a column vector such that the ticks and data points(pixels) are placed on the corresponding points? As far as I understood from the manual you only specify the corners of the image and this is not a problem as long as your data is evenly spaced like 100:100:1000.
In my case the x-axis consists of 21 elements which are evenly spaced like 1200:50:1700, whereas the y-axis is the vertical concatenation of two evenly spaced column vectors 200:50:450 and 500:25:725. My aim is to have the data points(pixels) at the correct locations, but it seems impossible to do so. Is there a workaround?
One option is to make Y also evenly spaced, and than use repelem:
X = 1200:50:1700;
Y = [0 50 100 200:50:450 500:25:725 800];
% set the spacing factor:
spacing = round(diff(Y)/min(diff(Y)));
The spacing vector looks like:
spacing =
Columns 1 through 14
2 2 4 2 2 2 2 2 2 1 1 1 1 1
Columns 15 through 19
1 1 1 1 3
and defines the distance between elements as multiplications of the smallest distance between elements in the vector.
We then define our new 'Y' for the image, so it will be evenly spaced, with the smallest space between elements in the vector.
% Define the new Y:
Y_spaced = Y(1):min(diff(Y)):Y(end); % = 0:25:800
% some arbitrary data:
data = rand(numel(Y),numel(X));
We use the spacing vector as input for repelem to duplicate each row in data as much as needed:
% spacing the data:
data_spaced = repelem(data,spacing([1 1:end]),1,1);
And we can plot it using imagesc (either in the matrix ij orientation, or in cartesian xy orientation):
imagesc(X,Y_spaced,data_spaced)
axis xy
The result:
Try replace imagesc with surf command:
surf(1200:50:1700, [200:50:450 500:25:725], rand(16,11), 'EdgeColor','none');
view([0 90]);
Note: with this way you loose last column and last row compare to imagesc, but you can just duplicated these data before displaying.
Use contourf or interpolate the data to a grid that fits all data points using e.g. interp2 or plot using contourf
Initialize data
X=[1200:50:1700]
Y=[200:50:450 500:25:725]
V = peaks(max(size(X,2),size(Y,2)))(1:size(Y,2),1:size(X,2));
Plot using contourf
contourf(X,Y,V);
view([0 -90]);
Interpolate and plot
Xq=linspace(min(X),max(X),100);
Yq=linspace(min(Y),max(Y),100)';
Vq = interp2(X,Y,V,Xq,Yq,'nearest');
imagesc(Vq)
If you want to have your pixels exactly at the correct location, you need to use a grid that has points exactly at all the point of your Y vector of course, so you need to adjust the "100"s accordingly to your screen and data resolution.
The alternative is to use pcolor
pcolor(X,Y,V)
view([0 -90]);
(Be careful with all the up-down flipping between image data and real data)
Related
I'd like to create a heat map to analyze the porosity of some specimens that I have 3D-printed. the X-Y coordinates are fixed since they are the positions in which the specimens are printed on the platform.
Heatmap:
Tbl = readtable('Data/heatmap/above.csv');
X = Tbl(:,1);
Y = Tbl(:,2);
porosity = Tbl(:,3);
hmap_above = heatmap(Tbl, 'X', 'Y', 'ColorVariable', 'porosity');
The first question is: how can I sort the Y-axis of the plot? since it goes from the lower value (top) to the higher value (bottom) and I need it the other way around.
The second question is: I only have around 22 data points and most of the chart is without color, so I'd like to get a smoother heatmap without the black parts.
The data set is quite simple and is shown below:
X
Y
porosity
74.4615
118.3773
0.039172163
84.8570
69.4699
0.046314637
95.2526
20.5625
0.041855213
105.6482
-28.3449
0.049796110
116.0438
-77.2522
0.045010692
25.5541
107.9817
0.038562053
35.9497
59.0743
0.041553065
46.3453
10.1669
0.036152061
56.7408
-38.7404
0.060719664
67.1364
-87.6478
0.037756115
-23.3533
97.5861
0.052840845
-12.9577
48.6787
0.045216851
-2.5621
-0.2286
0.033645353
7.8335
-49.1360
0.030670865
18.2290
-98.0434
0.024952472
-72.2607
87.1905
0.036199237
-61.8651
38.2831
0.026725885
-51.4695
-10.6242
0.029212058
-41.0739
-59.5316
0.028572611
-30.6783
-108.4390
0.036796151
-121.1681
76.7949
0.031688096
-110.7725
27.8876
0.034619855
-100.3769
-21.0198
0.039070101
-89.9813
-69.9272
NaN
-79.5857
-118.8346
NaN
If you want to assign color to the "black parts" you will have to interpolate the porosity over a finer grid than you currently have.
The best tool for 2D interpolation over a uniformly sampled grid is griddata
First you have to define the X-Y grid you want to interpolate over, and choose a suitable mesh density.
% this will be the number of points over each side of the grid
gridres = 100 ;
% create a uniform vector on X, from min to max value, made of "gridres" points
xs = linspace(min(X),max(X),gridres) ;
% create a uniform vector on Y, from min to max value, made of "gridres" points
ys = linspace(min(Y),max(Y),gridres) ;
% generate 2D grid coordinates from xs and ys
[xq,yq]=meshgrid(xs,ys) ;
% now interpolate the pososity over the new grid
InterpolatedPorosity = griddata(X,Y,porosity,xq,yq) ;
% Reverse the Y axis (flip the `yq` matrix upside down)
yq = flipud(yq) ;
Now my version of matlab does not have the heatmap function, so I'll just use pcolor for display.
% now display
hmap_above = pcolor(xq,yq,InterpolatedPorosity);
hmap_above.EdgeColor = [.5 .5 .5] ; % cosmetic adjustment
colorbar
colormap jet
title(['Gridres = ' num2str(gridres)])
And here are the results with different grid resolutions (the value of the gridres variable at the beginning):
Now you could also ask MATLAB to further graphically smooth the domain by calling:
shading interp
Which in the 2 cases above would yield:
Notes: As you can see on the gridres=100, you original data are so scattered that at some point interpolating on a denser grid is not going to produce any meaningful improvment. No need to go overkill on your mesh density if you do not have enough data to start with.
Also, the pcolor function uses the matrix input in the opposite way than heatmap. If you use heatmap, you have to flip the Y matrix upside down as shown in the code. But if you end up using pcolor, then you don't need to flip the Y matrix.
The fact that I did it in the code (to show you how to do) made the result display in the wrong orientation for a display with pcolor. Simply comment the yq = flipud(yq) ; statement if you stick with pcolor.
Additionally, if you want to be able to follow the isolevels generated by the interpolation, you can use contour to add a layer of information:
Right after the code above, the lines:
hold on
contour(xq,yq,InterpolatedPorosity,20,'LineColor','k')
will yield:
I populate a grid data=zeros(n,n); with 0's and 1's (could also be thought of as an adjacency grid, if you'd like). I just want to plot the grid with colors according to whether the value at that point is 0 or 1. For example,
scatter(1:n,1:n,data);
It gives me the error:
Error using scatter (line 77)
C must be a single color, a vector the same length as X, or an M-by-3 matrix.
Any suggestions?
you are telling matlab to plot only n points ((1,1), (2,2), ..., (n,n)) where you want actually the cartesian product (1:nX1:n).
Try
[X,Y] = meshgrid(1:n,1:n);
scatter(X(:), Y(:), 10, data(:));
scatter allows you to plot points with different options (color, size, etc) for each point depending on a 'Z' value, but it creates a lot of graphic objects (one for each point).
In your case, you only have 2 subsets of data (among all your points). The points with value 1 and with value 0. So another option is to extract these 2 subsets then plot each subset with each a set of common properties.
%% // prepare test data
n = 10 ;
data=randi([0 1],n); %// create a 10x10 matrix filled with `0` and `1`
%% // extract the 2 subsets
[x0 , y0] = find( data == 0 ) ;
[x1 , y1] = find( data == 1 ) ;
%% // display
figure ; axes('Nextplot','add')
plotOptions = {'LineStyle','none','MarkerEdgeColor','k','MarkerSize',10} ; %// common options for both plots
plot(x0,y0,'o','MarkerFaceColor','r', plotOptions{:} ) %// circle marker, red fill
plot(x1,y1,'d','MarkerFaceColor','g', plotOptions{:} ) %// diamond marker, green fill
This way you have full control on each subset property (you can control the size, color, shape etc...). And you only have 2 graphic objects to handle (instead of n^2).
I am trying to adjust the scale of the x-axis so that the values are closer together, but I am not able to do so.
I need the output to be like this photo:
However, what I actually get is the photo below:
Here's the code I have written to reproduce this error:
x = [0.1 1 10 100 1000 10000];
y = [1.9904 19.8120 82.6122 93.0256 98.4086 99.4016];
figure;
bar(x,y);
ylabel('Y values');
xlabel('X values');
set(gca,'XTick', [0.1 1 10 100 1000 10000])
How can I adjust the x-axis so that it looks like the first photo?
Because your data has such huge dynamic range, and because of the linear behaviour of the x axis, your graph is naturally going to appear like that. One compromise that I can suggest is that you transform your x data so that it gets mapped to a smaller scale, then remap your x data so that it falls onto a small exponential scale. After, simply plot the data using this remapped scale, then rename the x ticks so that they have the same values as your x data. To do this, I would take the log10 of your data first, then apply an exponential to this data. In this way, you are scaling the x co-ordinates down to a smaller dynamic range. When you apply the exponential to this smaller range, the x co-ordinates will then spread out in a gradual way where higher values of x will certainly make the value go farther along the x-axis, but not too far away like you saw in your original plot.
As such, try something like this:
x = [0.1 1 10 100 1000 10000]; %// Define data
y = [1.9904 19.8120 82.6122 93.0256 98.4086 99.4016];
xplot = (1.25).^(log10(x)); %// Define modified x values
figure;
bar(xplot,y); %// Plot the bar graph on the modified scale
set(gca,'XTick', xplot); %// Define ticks only where the bars are located
set(gca,'XTickLabel', x); %// Rename these ticks to our actual x data
This is what I get:
Note that you'll have to play around with the base of the exponential, which is 1.25 in what I did, to suit your data. Obviously, the bigger the dynamic range of your x data, the smaller this exponent will have to be in order for your data to be closer to each other.
Edit from your comments
From your comments, you want the bars to be equidistant in between neighbouring bars. As such, you simply have to make the x axis linear in a small range, from... say... 1 to the total number of x values. You'd then apply the same logic where we rename the ticks on the x axis so that they are from the true x values instead. As such, you only have to change one line, which is xplot. The other lines should stay the same. Therefore:
x = [0.1 1 10 100 1000 10000]; %// Define data
y = [1.9904 19.8120 82.6122 93.0256 98.4086 99.4016];
xplot = 1:numel(x); %// Define modified x values
figure;
bar(xplot,y); %// Plot the bar graph on the modified scale
set(gca,'XTick', xplot); %// Define ticks only where the bars are located
set(gca,'XTickLabel', x); %// Rename these ticks to our actual x data
This is what I get:
I'd like to create a quasi boxplot graph as shown on pages 15/16 of the attached report.
comisef.eu/files/wps031.pdf
Ideally I only want to show the median, the maximum and minimum values as in the report.
I would also like to have similar spacing to that shown in the report.
Currently I have two matrices with the all the necessary values stored in them but have no idea how to do this in matlab.
The boxplot function gives too much data (outliers etc) which makes the resulting graph look confused especially when I try to plot 200 on one page as in the original report.
Is there another function that can so the same thing as in the report in matlab?
Baz
OK here is some test data each row represents 10 sets of estimations of a data set, and each column represents the test number for a given observation.
As boxplot works on the columns of the input matrix you will need to transpose the matrix.
Is it possible to turn outliers and the inter-quartile ranges off? Ideally I just want to see the maximum, minimum and median values?
You can repeat the data below to get up to 200. Or I can send more data if necessary.
0.00160329732202511 0.000859407819412016 0.000859407819411159 0.0659939338995606 0.000859407819416322 0.000859407819416519 2.56395024851142e-15 2.05410662537078e-14 0.000859407819416209
1.67023155116586e-06 8.88178419700125e-16 1.67023155115637e-06 0.000730536218639616 1.67023155105582e-06 3.28746017489609e-15 4.41416632660789e-15 1.67023155094400e-06 1.67023155097567e-06
1.42410590843629e-06 1.42410590840224e-06 1.76149166727218e-15 5.97790925044131e-15 1.42410590843863e-06 2.87802701599909e-15 9.31529385335274e-16 9.17306727455842e-16 0.000820358763518906
8.26849110292527e-16 3.23505095414772e-15 4.38139485761850e-07 4.38139485938112e-07 4.38139485981887e-07 0.000884647755317917 3.72611754134110e-15 4.38139485974329e-07 4.38139485923219e-07
0.000160661751819407 0.000870787937135265 0.000870787937136209 1.16934122581182e-15 9.02860049358913e-16 1.18053134896556e-15 1.40433338743068e-15 0.000870787937135929 1.13510916297112e-15
1.16934122581182e-15 3.80292342262841e-05 3.80292342263200e-05 0.00284904319356532 1.74649997619656e-15 3.80292342264024e-05 0.00284904319356537 1.01267920724547e-15 0.00284904319356540
0.100091800399985 0.100091773169254 0.100091803903140 0.000770464183529358 0.100091812455930 3.49996706323281e-05 3.49996706323553e-05 1.05090687851466e-15 0.100091846333800
0.00100555294602561 0.00100555294601056 0.105365907420183 0.000121078082591672 9.02860049358913e-16 0.000121078082591805 4.49679158258033e-15 7.77684615168284e-16 0.000121078082591693
0.122539456858702 0.000363547764643498 0.000363547764643509 0.122516928568610 0.0101487499394213 0.122408366511784 0.000363547764643519 1.13510916297112e-15 0.122521393586646
0.000460749357561036 0.000460749357560646 3.27600489447913e-13 1.18053134896556e-15 0.000460749357561239 1.54689304063675e-15 0.000460749357560827 0.000460749357561205 1.16934122581182e-15
Instead of using boxplot, I suggest just drawing lines from the min to the max and making a mark at the median. Boxplot draws boxes from the 25 to 75 percentile, which doesn't sound like what you want. Something like this:
% fake data
nPoints = 100;
data = 10*rand(10, nPoints);
% find statistics
minData = min(data, [], 1);
maxData = max(data, [], 1);
medData = median(data);
% x coordinates of each line. Change this to change the spacing.
x = 1:nPoints;
figure
hold on
%plot lines
line([x; x], [minData; maxData])
% plot cross at median
plot(x, medData, '+')
EDIT: To have horizontal lines and a second axis you can do something like this:
figure
h1 = subplot(1,2,1);
h2 = subplot(1,2,2);
% left subplot
axes(h1)
hold on
%plot lines
line([minData; maxData], [x; x])
% plot cross at median
plot(medData, x, '+')
% link the axes so they will have the same limits
linkaxes([h1,h2],'y')
% turn off ticks on y axis.
set(h2, 'YTick', [])
I think it's a question of playing with the settings. You can try:
boxplot(X, 'plotstyle', 'compact', 'colors', 'k', 'medianstyle', 'line', 'outliersize', 0);
Explanation:
'plotstyle', 'compact': makes the boxes filled and the lines undashed
'colors', 'k': color is black
'medianstyle', 'line': the median is marked by a line
'outliersize', 0: if outlier size is zero, you don't see them
Other you can try:
'orientation', 'vertical': this flips the orientation, depends on your data
'whisker', 10 (or higher): this sets the maximum whisker length as a function of the interquartile limits (if you crank it up, it will eventually default to max and min values), I wasn't sure if this is what you wanted. Right now, it goes to the 25th and 75th percentile values.
The spacing is going to depend on how much data you have. If you edit with some data, I can try it out for you.
I am currently a begineer, and i am using matlab to do a data analysis. I have a a text file with data at the first row is formatted as follow:
time;wave height 1;wave height 2;.......
I have column until wave height 19 and rows total 4000 rows.
Data in the first column is time in second. From 2nd column onwards, it is wave height elevation which is in meter. At the moment I like to ask matlab to plot a 3d graph with time on the x axis, wave elevation on the y axis, and wave elevation that correspond to wave height number from 1 to 19, i.e. data in column 2 row 10 has a let say 8m which is correspond to wave height 1 and time at the column 1 row 10.
I have try the following:
clear;
filename='abc.daf';
path='C:\D';
a=dlmread([path '\' filename],' ', 2, 1);
[nrows,ncols]=size(a);
t=a(1:nrows,1);%define t from text file
for i=(1:20),
j=(2:21);
end
wi=a(:,j);
for k=(2:4000),
l=k;
end
r=a(l,:);
But everytime i use try to plot them, the for loop wi works fine, but for r=a(l,:);, the plot only either give me the last time data only but i want all data in the file to be plot.
Is there a way i can do that. I am sorry as it is a bit confusing but i will be very thankful if anyone can help me out.
Thank you!!!!!!!!!!
Once you load your data as you do in your code above your variable a should be a 4000-by-20 array. You could then create a 3-D plot in a couple of different ways. You could create a 3-D line plot using the function PLOT3, plotting one line for each column of wave elevation data:
t = a(:,1); %# Your time vector
for i = 2:20 %# Loop over remaining columns
plot3(t,(i-1).*ones(4000,1),a(:,i)); %# Plot one column
hold on; %# Continue plotting to the same axes
end
xlabel('Time'); %# Time on the x-axis
ylabel('Wave number'); %# Wave number (1-19) on y-axis
zlabel('Wave elevation'); %# Elevation on z-axis
Another way to plot your data in 3-D is to make a mesh or surface plot, using the functions MESH or SURF, respectively. Here's an example:
h = surf(a(:,1),1:19,a(:,2:20)'); %'# Plot a colored surface
set(h,'EdgeColor','none'); %# Turn off edge coloring (easier to see surface)
xlabel('Time'); %# Time on the x-axis
ylabel('Wave number'); %# Wave number (1-19) on y-axis
zlabel('Wave elevation'); %# Elevation on z-axis
I don't quite understand what your function does, for example, I do not see any plot command.
Here's how I'd try to make a 3D plot according to your specs:
%# Create some data - time from 0 to 2pi, ten sets of data with frequency 1 through 10.
%# You would just load A instead (I use uppercase just so I know that A is a 2D array,
%# rather than a vector)
x = linspace(0,2*pi,100)';%#' linspace makes equally spaced points
w = 1:10;
[xx,ww]=ndgrid(x,w); %# prepare data for easy calculation of matrix A
y = ww.*sin(xx.*ww);
A = [x,y]; %# A is [time,data]
%# find size of A
[nRows,nCols] = size(A);
%# create a figure, loop through the columns 2:end of A to plot
colors = hsv(10);
figure,
hold on,
for i=1:nCols-1,
%# plot time vs waveIdx vs wave height
plot3(A(:,1),i*ones(nRows,1),A(:,1+i),'Color',colors(i,:)),
end
%# set a reasonable 3D view
view(45,60)
%# for clarity, label axes
xlabel('time')
ylabel('wave index')
zlabel('wave height')
Or, you could try gnuplot. Fast, free and relatively easy to use. I use it to generate heat maps for datasets in the millions of rows.