I am trying to plot data from a csv file, I have successfully uploaded the csv as an array for each column. I'm then trying to find the peaks of each column, I need to then plot the peaks for each to a time constant (tau). I have been getting an error that I need to have the same size vectors to plot. I'm also trying to plot all sets of data on one plot and have a curve fit for each.
Please help me out!
code is below
Array=csvread("D:\Grad Lab\NMR\Data\T1 Data\compiledT1nolabel.csv");
tau = Array(:,1);
Water= Array(:,2);
Mineral_Oil = Array(:,3);
Glycerol = Array(:,4);
CuSO4_1=Array(:,5);
CuSO4_2=Array(:,6);
CuSO4_3=Array(:,7);
CuSO4_4=Array(:,8);
CuSO4_5=Array(:,9);
pks1 = findpeaks(Water);
pks2 = findpeaks(Mineral_Oil);
pks3 = findpeaks(Glycerol);
pks4 = findpeaks(CuSO4_1);
pks5 = findpeaks(CuSO4_2);
pks6 = findpeaks(CuSO4_3);
pks7 = findpeaks(CuSO4_4);
pks8 = findpeaks(CuSO4_5);
plot(pks1,tau)
The problem is that the pks vectors and the corresponding data arrays you are trying to plot don't have the same size: calling the plot function on vectors of different sizes produces the error.
In the sample script below, data contains a bunch of values. Invoking findpeaks with two outputs (i.e. locs and pks) allows both the locations and peak values to be stored. Now we can use locs and pks with plot to mark the peaks as follows:
data = [25 8 15 5 6 10 10 3 1 20 7];
[pks, locs] = findpeaks(data);
plot(data); hold
plot(locs, pks, 'd')
produces the following plot:
Alternatively, if you are just interested in plotting, you could use
findpeaks(data)
without any output: it will produce a plot like this:
For the OP's specific case, I modified his script as follows (just covered one set of peaks, the pattern should be clear):
Array=csvread("D:\Grad Lab\NMR\Data\T1 Data\compiledT1nolabel.csv");
tau = Array(:,1);
Water = Array(:,2);
[pks1, locs1] = findpeaks(Water);
figure
plot(tau, Water); hold on;
plot(tau(locs1), pks1, 'd');
Related
I have a 420*940*12 matrix (the value of each grid ranges from 0-100) and I want to plot data only inside polygon S, with lat (420*1) and lon (940*1) as grid references.
We can create a single plot of only points without its values (0-100):
S = shaperead(polygon);
N = length(S);
[X,Y] = meshgrid(lon,lat);
data= test;
for k = 1:N
idx = insidepoly(X(:),Y(:),S(k).X,S(k).Y);
hold on
plot(X(idx), Y(idx), 'r*')
end
But this figure is only showing the points not its values (0-100)
And the output is something like this:
But I have to plot multiple data together, lets say 12 months of a year so, how can I make 12 plots together according to values (0-100) as in the below figure?
enter image description here
one possible solution is to use montage, see here:
img = imread('peppers.png');
img = repmat(img,1,1,1,6);
montage(img)
I have four sets of data, the distribution of which I would like to represent in MATLAB in one figure. Current code is:
[n1,x1]=hist([dataset1{:}]);
[n2,x2]=hist([dataset2{:}]);
[n3,x3]=hist([dataset3{:}]);
[n4,x4]=hist([dataset4{:}]);
bar(x1,n1,'hist');
hold on; h1=bar(x1,n1,'hist'); set(h1,'facecolor','g')
hold on; h2=bar(x2,n2,'hist'); set(h2,'facecolor','g')
hold on; h3=bar(x3,n3,'hist'); set(h3,'facecolor','g')
hold on; h4=bar(x4,n4,'hist'); set(h4,'facecolor','g')
hold off
My issue is that I have different sampling sizes for each group, dataset1 has an n of 69, dataset2 has an n of 23, dataset3 and dataset4 have n's of 10. So how do I normalize the distributions when representing these three groups together?
Is there some way to..for example..divide the instances in each bin by the sampling for that group?
You can normalize your histograms by dividing by the total number of elements:
[n1,x1] = histcounts(randn(69,1));
[n2,x2] = histcounts(randn(23,1));
[n3,x3] = histcounts(randn(10,1));
[n4,x4] = histcounts(randn(10,1));
hold on
bar(x4(1:end-1),n4./sum(n4),'histc');
bar(x3(1:end-1),n3./sum(n3),'histc');
bar(x2(1:end-1),n2./sum(n2),'histc');
bar(x1(1:end-1),n1./sum(n1),'histc');
hold off
ax = gca;
set(ax.Children,{'FaceColor'},mat2cell(lines(4),ones(4,1),3))
set(ax.Children,{'FaceAlpha'},repmat({0.7},4,1))
However, as you can see above, you can do some more things to make your code more simple and short:
You only need to hold on once.
Instead of collecting all the bar handles, use the axes handle.
Plot the bar in ascending order of the number of elements in the dataset, so all histograms will be clearly visible.
With the axes handle set all properties at one command.
and as a side note - it's better to use histcounts.
Here is the result:
EDIT:
If you want to also plot the pdf line from histfit, then you can save it first, and then plot it normalized:
dataset = {randn(69,1),randn(23,1),randn(10,1),randn(10,1)};
fits = zeros(100,2,numel(dataset));
hold on
for k = numel(dataset):-1:1
total = numel(dataset{k}); % for normalizing
f = histfit(dataset{k}); % draw the histogram and fit
% collect the curve data and normalize it:
fits(:,:,k) = [f(2).XData; f(2).YData./total].';
x = f(1).XData; % collect the bar positions
n = f(1).YData; % collect the bar counts
f.delete % delete the histogram and the fit
bar(x,n./total,'histc'); % plot the bar
end
ax = gca; % get the axis handle
% set all color and transparency for the bars:
set(ax.Children,{'FaceColor'},mat2cell(lines(4),ones(4,1),3))
set(ax.Children,{'FaceAlpha'},repmat({0.7},4,1))
% plot all the curves:
plot(squeeze(fits(:,1,:)),squeeze(fits(:,2,:)),'LineWidth',3)
hold off
Again, there are some other improvements you can introduce to your code:
Put everything in a loop to make thigs more easily changed later.
Collect all the curves data to one variable so you can plot them all together very easily.
The new result is:
I haven't used MATLAB in a while and I am stuck on a small detail. I would really appreciate it if someone could help me out!
So I am trying to plot a transfer function using a specific function called freqs but I can't figure out how I can label specific points on the graph.
b = [0 0 10.0455]; % Numerator coefficients
a = [(1/139344) (1/183.75) 1]; % Denominator coefficients
w = logspace(-3,5); % Frequency vector
freqs(b,a,w)
grid on
I want to mark values at points x=600 Hz and 7500 Hz with a marker or to be more specific, points (600,20) and (7500,-71), both of which should lie on the curve. For some reason, freqs doesn't let me do that.
freqs is very limited when you want to rely on it plotting the frequency response for you. Basically, you have no control on how to modify the graph on top of what MATLAB generates for you.
Instead, generate the output response in a vector yourself, then plot the magnitude and phase of the output yourself so that you have full control. If you specify an output when calling freqs, you will get the response of the system.
With this, you can find the magnitude of the output by abs and the phase by angle. BTW, (600,20) and (7500,-71) make absolutely no sense unless you're talking about magnitude in dB.... which I will assume is the case for the moment.
As such, we can reproduce the plot that freqs gives by the following. The key is to use semilogx to get a semi-logarithmic graph on the x-axis. On top of this, declare those points that you want to mark on the magnitude, so (600,20) and (7500,-71):
%// Your code:
b = [0 0 10.0455]; % Numerator coefficients
a = [(1/139344) (1/183.75) 1]; % Denominator coefficients
w = logspace(-3,5); % Frequency vector
%// New code
h = freqs(b,a,w); %// Output of freqs
mag = 20*log10(abs(h)); %// Magnitude in dB
pha = (180/pi)*angle(h); %// Phase in degrees
%// Declare points
wpt = [600, 7500];
mpt = [20, -71];
%// Plot the magnitude as well as markers
figure;
subplot(2,1,1);
semilogx(w, mag, wpt, mpt, 'r.');
xlabel('Frequency');
ylabel('Magnitude (dB)');
grid;
%// Plot phase
subplot(2,1,2);
semilogx(w, pha);
xlabel('Frequency');
ylabel('Phase (Degrees)');
grid;
We get this:
If you check what freqs generates for you, you'll see that we get the same thing, but the magnitude is in gain (V/V) instead of dB. If you want it in V/V, then just plot the magnitude without the 20*log10() call. Using your data, the markers I plotted are not on the graph (wpt and mpt), so adjust the points to whatever you see fit.
There are a couple issues before we attempt to answer your question. First, there is no data-point at 600Hz or 7500Hz. These frequencies fall between data-points when graphed using the freqs command. See the image below, with datatips added interactively. I copy-pasted your code to generate this data.
Second, it does not appear that either (600,20) or (7500,-71) lie on the curves, at least with the data as you entered above.
One solution is to use plot a marker on the desired position, and use a "text" object to add a string describing the point. I put together a script using your data, to generate this figure:
The code is as follows:
b = [0 0 10.0455];
a = [(1/139344) (1/183.75) 1];
w = logspace(-3,5);
freqs(b,a,w)
grid on
figureHandle = gcf;
figureChildren = get ( figureHandle , 'children' ); % The children this returns may vary.
axes1Handle = figureChildren(1);
axes2Handle = figureChildren(2);
axes1Children = get(axes1Handle,'children'); % This should be a "line" object.
axes2Children = get(axes2Handle,'children'); % This should be a "line" object.
axes1XData = get(axes1Children,'xdata');
axes1YData = get(axes1Children,'ydata');
axes2XData = get(axes2Children,'xdata');
axes2YData = get(axes2Children,'ydata');
hold(axes1Handle,'on');
plot(axes1Handle,axes1XData(40),axes1YData(40),'m*');
pointString1 = ['(',num2str(axes1XData(40)),',',num2str(axes1YData(40)),')'];
handleText1 = text(axes1XData(40),axes1YData(40),pointString1,'parent',axes1Handle);
hold(axes2Handle,'on');
plot(axes2Handle,axes2XData(40),axes2YData(40),'m*');
pointString2 = ['(',num2str(axes2XData(40)),',',num2str(axes2YData(40)),')'];
handleText2 = text(axes2XData(40),axes2YData(40),pointString2,'parent',axes2Handle);
I am having difficulty with calculating 2D area of contours produced from a Kernel Density Estimation (KDE) in Matlab. I have three variables:
X and Y = meshgrid which variable 'density' is computed over (256x256)
density = density computed from the KDE (256x256)
I run the code
contour(X,Y,density,10)
This produces the plot that is attached. For each of the 10 contour levels I would like to calculate the area. I have done this in some other platforms such as R but am having trouble figuring out the correct method / syntax in Matlab.
C = contourc(density)
I believe the above line would store all of the values of the contours allowing me to calculate the areas but I do not fully understand how these values are stored nor how to get them properly.
This little script will help you. Its general for contour. Probably working for contour3 and contourf as well, with adjustments of course.
[X,Y,Z] = peaks; %example data
% specify certain levels
clevels = [1 2 3];
C = contour(X,Y,Z,clevels);
xdata = C(1,:); %not really useful, in most cases delimters are not clear
ydata = C(2,:); %therefore further steps to determine the actual curves:
%find curves
n(1) = 1; %n: indices where the certain curves start
d(1) = ydata(1); %d: distance to the next index
ii = 1;
while true
n(ii+1) = n(ii)+d(ii)+1; %calculate index of next startpoint
if n(ii+1) > numel(xdata) %breaking condition
n(end) = []; %delete breaking point
break
end
d(ii+1) = ydata(n(ii+1)); %get next distance
ii = ii+1;
end
%which contourlevel to calculate?
value = 2; %must be member of clevels
sel = find(ismember(xdata(n),value));
idx = n(sel); %indices belonging to choice
L = ydata( n(sel) ); %length of curve array
% calculate area and plot all contours of the same level
for ii = 1:numel(idx)
x{ii} = xdata(idx(ii)+1:idx(ii)+L(ii));
y{ii} = ydata(idx(ii)+1:idx(ii)+L(ii));
figure(ii)
patch(x{ii},y{ii},'red'); %just for displaying purposes
%partial areas of all contours of the same plot
areas(ii) = polyarea(x{ii},y{ii});
end
% calculate total area of all contours of same level
totalarea = sum(areas)
Example: peaks (by Matlab)
Level value=2 are the green contours, the first loop gets all contour lines and the second loop calculates the area of all green polygons. Finally sum it up.
If you want to get all total areas of all levels I'd rather write some little functions, than using another loop. You could also consider, to plot just the level you want for each calculation. This way the contourmatrix would be much easier and you could simplify the process. If you don't have multiple shapes, I'd just specify the level with a scalar and use contour to get C for only this level, delete the first value of xdata and ydata and directly calculate the area with polyarea
Here is a similar question I posted regarding the usage of Matlab contour(...) function.
The main ideas is to properly manipulate the return variable. In your example
c = contour(X,Y,density,10)
the variable c can be returned and used for any calculation over the isolines, including area.
I am looking for a way to merge two Matlab plots. I have the figure files for each of them as fig1.fig and fig2.fig One figure contains a plot which runs for a certain range e.g 1 to 100 and the other figure contains the continuation of the first plot e.g 101 to 200. Each of these plots takes around 8 hours, so I do not want to replot them. Is there any simple way of merging these two plots?
It sounds like you want to join up your data, so you need to extract the x and y data from each of your plots. If you have a line plot, you can load the first .fig file
e.g.
and then type
a = gca
handles = findobj(a)
isLine = strcmp(get(handles, 'Type'), 'line')
XData1 = get(handles(isLine), 'XData')
YData1 = get(handles(isLine), 'YData')
That will extract the x and y data for your line, from your first plot.
Now close all your figures and load your second plot:
a = gca
handles = findobj(a)
isLine = strcmp(get(handles, 'Type'), 'line')
XData2 = get(handles(isLine), 'XData')
YData2 = get(handles(isLine), 'YData')
You can now plot your merged plot with:
figure
plot([XData1 XData2], [YData1 YData2])
title('mergedPlot')