How can I find the exact y-coordinate of the red gaussian at x = 0.5 without using Data Cursor?
I want the blue line to end when it touches the gaussian. But I need to find the point of intersection between the gaussian of the histfit shown in red, and the blue line at 0.5. I can access the data points of the histfit plot as follows:
C = get(get(gca, 'Children'), 'YData');
C{1,1}
line([0.5 0.5],[0 max(C{1,1})],'Color','b');
However, the data points of the gaussian don't relate to this axes. Meaning, x-axis of C{1,1} is from 1 - 100 and not from 0.1 to 0.9.
Whats the easiest way to find the y-coordinate of the gaussian at 0.5 so that I can replace max(C{1,1}) by that?
Getting XData as well should give you the right x-values:
C = get(get(gca, 'Children'), 'XData');
Alternatively, the values of YData should be at regular intervals, even if not on the correct scale (since it originated from hist), so you could probably find the y-value corresponding to x=0.5 in the plot.
The point x=0.5 between 0.1 and 0.85 (approximately, from the plot) scales to the point x=53.33 between 1 and 100. If the y-value at x=53 isn't accurate enough for plotting, you can just interpolate the value between 53 and 54 and that should be enough.
Here is some code to that should do the job:
XPlotRange = [0.1 0.85];
XDataRange = [1 100];
XPlotToInterp = 0.5;
XDataToInterp = XDataRange(1) + (XPlotToInterp - XPlotRange(1))*diff(XDataRange)/diff(XDataRange);
XData1 = floor(XDataToInterp);
XData2 = ceil(XDataToInterp);
YInterp = interp1([XData1 XData2], [YData(XData1) YData(XData2)], XDataToInterp);
Here YInterp is the interpolated y-value for the corresponding x-value.
Related
I have a matrix of data. I used the polarplot command in MATLAB to plot this matrix with respect to theta.
The data oscillates between 3999.20 and 4001.52 As you can see in the following plot, the order of magnitude of oscillation of data is too small to see.
How can I modify my polar plot to see small oscillations?
My code is as below:
yf=[%750 data point]
theta = 0:4*pi/749:4*pi;
rho = yf
pax = polaraxes;
polarplot(theta,rho)
pax.ThetaDir = 'counterclockwise';
pax.ThetaZeroLocation='right'
pax.ThetaColor='r'
pax.ThetaTick=[0 30 60 90 120 150 180 210 240 270 300 330 ];
pax.RDir='normal';
pax.RTick=[3999.34 3999.67 4000 4000.33 4000.66 4000.99 4001.33 ]
pax.FontSize = 12;
Desired output:
Actual output
2-axis plot
To give an example of setting the r limits as suggested by #beaker
The following code uses the same data with using rlim to set manual limits in the second example. This scales the polar axis so that it only plots values between [3999,4000], exaggerating the scale of the oscillation.
theta = 0:0.01:2*pi;
rho = sin(2*theta).*cos(2*theta) + 3999 %To approximate your data
figure;
subplot(1,2,1)
polarplot(theta,rho)
title('Automatic r-limits')
subplot(1,2,2)
polarplot(theta,rho)
rlim([3999, 4000])
title('rlim([3999, 4000])')
Something like that maybe, where you subtract the mean of the data and scale the amplitude by a factor of 10?
yf=[%750 data point]
amp = yf - mean(yf);
amp = amp*10; % choose whatever scaling factor works for you
theta = 0:4*pi/749:4*pi;
rho = mean(yf) + amp;
Without the actual data, it's difficult to say what this will look like, but the general principle should work.
I have this 3D plot that I'm making but the data are not linear. This implies that on my plot, the distance between the ticks that I want to show is not equal. How can I adapt the scale of the x and y axis so that this is the case, i.e. so that the axis gets divided into equal parts with the current ticks?
I want the same ticks and tick labels, but that they just have an equal distance in between them on the axes, in stead of small between 0.1 and 0.5 and large between 1 and 5.
The current plot looks like this:
RMSEval = xlsread('RMSEvalues.xlsx');
X = RMSEval(:,1);
Y = RMSEval(:,2);
Z = RMSEval(:,3);
figure(1);
xi = linspace(min(X),max(X),30);
yi= linspace(min(Y),max(Y),30);
[XI,YI] = meshgrid(xi,yi);
ZI = griddata(X,Y,Z,XI,YI);
contourf(XI,YI,ZI);
colormap('jet');
xticks([1e-13 5e-13 1e-12 5e-12 1e-11]);
yticks([1e-18 5e-18 1e-17 5e-17 1e-16]);
colorbar;
A plot where the distance between 0.1 and 0.5 is the same as between 1 and 5 would be a log plot, specifically a log-log plot since you want it on both axes. One way to achieve this would be to transform the X and Y values of your data logarithmically and modify the tick mark labels to match the untransformed values rather than the logarithmic ones you're actually plotting.
A rough guess at a solution is below. I say a rough guess because without posting the data you're importing from the xlsx file or a paired down version of that data (as in an MWE) I can't actually test it.
RMSEval = xlsread('RMSEvalues.xlsx');
X = log(RMSEval(:,1));
Y = log(RMSEval(:,2));
Z = RMSEval(:,3);
figure(1);
xi = linspace(min(X),max(X),30);
yi= linspace(min(Y),max(Y),30);
[XI,YI] = meshgrid(xi,yi);
ZI = griddata(X,Y,Z,XI,YI);
contourf(XI,YI,ZI);
colormap('jet');
xticks(log([1e-13 5e-13 1e-12 5e-12 1e-11]));
xticklabels(cellfun(#num2str,num2cell(),'UniformOutput',false));
yticks(log([1e-18 5e-18 1e-17 5e-17 1e-16]));
yticklabels(cellfun(#num2str,num2cell([1e-18 5e-18 1e-17 5e-17 1e-16]),'UniformOutput',false));
colorbar;
I want to visualize the peaks of a function, and I want to have markers for it appear above the line they are associated with.
I fabricated a minimum example where I already have the peaks, the question is just how to visualize the markers correctly:
y = [0.1 0.3 10.0 1.0 0.5 0.1 24.0 0.6 0.1 0.2]
x = (1:length(y))
plot(x,y);
hold on;
peaks = [3 7];
plot(x(peaks), y(peaks), 'v', 'MarkerSize', 24);
print('-dpng', 'example.png', '-S640,480');
So, as a result, the markers appear centered on the line like this:
The result that I want could be achieved by carefully tuning a parameter OFFSET like this:
plot(x(peaks), y(peaks)+OFFSET, 'v', 'MarkerSize', 24);
As shown in the following figure, for this exact example OFFSET=2.56 works for the exported png, but with the interactive plot and exporting vector graphics, it's wrong again.
Can anyone recommend a way to get this result without having to manually doing trial/error?
Currently I am using Octave with gnuplot to export to latex+tikz, and it would be good if the solution would work there.
In my actual (more complicated) use case I am plotting multiple lines after each other into the same figure, and the y limits change, so the offsets can not just be calculated easily, as the markersize doesn't change with the y limits.
Edit: Additionally I am using a semilogx plot, so drawing lines inside the diagram in the x/y-Axis scales would look distorted.
One way to do this is with annotations, but there are some drawbacks (see below).
Annotations enable you to place various graphic objects into your figure. One very annoying thing about them is that they work in so-called normalized coordinates,
which span the whole figure window (not just the plot area) and go from [0,0] to [1,1], forcing you to convert to these coordinates first. I wrote a simple function to do this, provided your plot scale is linear (if you want logarithmic, you will have to modify this function):
## Convert from data coordinates to normalized figure coordinates.
function [xf yf] = figcoords(xa, ya)
axp = get(gca, "position");
lf = axp(1);
bf = axp(2);
rf = lf + axp(3);
tf = bf + axp(4);
xl = xlim();
yl = ylim();
la = xl(1);
ra = xl(2);
ba = yl(1);
ta = yl(2);
xf = lf + (xa-la).*(rf-lf)./(ra-la);
yf = bf + (ya-ba).*(tf-bf)./(ta-ba);
endfunction
With this out of your way, you can proceed to annotating the plot using the annotation function:
y = [0.1 0.3 10.0 1.0 0.5 0.1 24.0 0.6 0.1 0.2];
x = (1:length(y));
peaks = [3 7];
## Plot the data as you would normally
plot(x,y);
## Plot peak markers (no `hold on` needed)
[xp yp] = figcoords(peaks, y(peaks)); # Transform to figure coordinates
for coords = [xp; yp]
xpi = coords(1);
ypi = coords(2);
annotation("arrow", [xpi xpi], [ypi+eps ypi]);
endfor
Plot with annotated peaks
Here, we actually draw little arrows pointing from top onto the peaks.
As their height is very small, we only see the arrowheads.
The arguments to the annotation function are the x and y coordinates
of the endpoints of the arrow. Note that we added a small number (eps)
to the y-value of the starting point to make the arrow point downward.
If you want, you can tweak the appearance of the markers to make them more visually appealing:
y = [0.1 0.3 10.0 1.0 0.5 0.1 24.0 0.6 0.1 0.2];
x = (1:length(y));
peaks = [3 7];
coloridx = get(gca, "ColorOrderIndex")
peakcolor = get(gca, "ColorOrder")(coloridx,:); # Save current plot colour
plot(x,y);
## Plot peak markers
[xp yp] = figcoords(peaks, y(peaks));
for coords = [xp; yp]
xpi = coords(1);
ypi = coords(2);
annotation("arrow", [xpi xpi], [ypi+eps ypi], "headstyle", "plain",...
"color", peakcolor);
endfor
Plot with annotated peaks in the same color
Drawbacks
While this approach works fine regardless of the size of the markers or your plot, there are some drawbacks:
First, the annotations are fixed relative to the figure window, not the plot.
This is fine when you display the plot for the first time, but once you zoom
or pan, the alignment is lost: The markes stay in place while the plot moves.
If you don't need an interactive plot (eg, you just want to export it to image),
just be sure to set the plot limits before adding the annotations and you should
be fine.
Second, this method is very slow compared to plotting the points using the
plot function. On my computer, for example, when drawing a simple example with
seven annotated peaks, it takes about a second before the markers appear.
Plotting a signal with thousands of peaks is near impossible.
Concerning the Matlab part, you could draw the peak markers yourself. Somewhere along these lines (extending your example):
y = [0.1 0.3 10.0 1.0 0.5 0.1 24.0 0.6 0.1 0.2]
x = (1:length(y))
figure, plot(x,y);
leglengthx=0.2;
leglengthy=0.5;
hold on;
peaks = [3 7];
peaks_max=[10 24];
for ii=1:2
line([peaks(ii) peaks(ii)+leglengthx],[peaks_max(ii) peaks_max(ii)+leglengthy]);
line([peaks(ii) peaks(ii)-leglengthx],[peaks_max(ii) peaks_max(ii)+leglengthy]);
line([peaks(ii)-leglengthx peaks(ii)+leglengthx],[peaks_max(ii)+leglengthy peaks_max(ii)+leglengthy]);
end
plot(x(peaks), y(peaks), 'v', 'MarkerSize', 24);
I have added the maxima of the peaks, which should not be an issue to automatically extract and two variables that control the triangle size of the marker. And then its just drawing three lines for every peak.
I don't know how this will translate to Octave.
What about drawing the little triangles?
y = [0.1 0.3 10.0 1.0 0.5 0.1 24.0 0.6 0.1 0.2];
x = (1:length(y));
peaks = [3 7];
plot(x,y);
hold on; line([peaks(1) peaks(1)+0.2], [y(x==peaks(1)) y(x==peaks(1))+1], 'color','b')
hold on; line([peaks(1) peaks(1)-0.2], [y(x==peaks(1)) y(x==peaks(1))+1], 'color','b')
hold on; line([peaks(1)+0.2 peaks(1)-0.2], [y(x==peaks(1))+1 y(x==peaks(1))+1], 'color','b')
hold on; line([peaks(2) peaks(2)+0.2], [y(x==peaks(2)) y(x==peaks(2))+1], 'color','b')
hold on; line([peaks(2) peaks(2)-0.2], [y(x==peaks(2)) y(x==peaks(2))+1], 'color','b')
hold on; line([peaks(2)+0.2 peaks(2)-0.2], [y(x==peaks(2))+1 y(x==peaks(2))+1], 'color','b')
There can be a problem if the y-values of the peaks exists in other locations on the vector. If so, you can specify first or other matching specs for the find function.
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:
For this given example:
a=rand(100,1)
ecdf(a)
The obtained plot will have on x proportion of bin values, and on y the proportion of points. I wanted to add a line y=0.5 (50% percent of values) and when cross the line in the plot gather and shows the predicted x value.
It is possible but it suppresses my knowledge.
Thanks in advance
Not sure I interpret your question correctly - but could it be as simple as
a=rand(100,1)
ecdf(a)
hold on
plot([0 1],[1 1]*0.5);
This adds a line at a height of 0.5 from 0 to 1 (which I believe are the limits of the plot that ecdf produced for you).
If you want to find the point where these two lines intersect, you need to obtain the points in the plot using a different form of the ecdf function:
a = rand(100,1)
[f x] = ecdf(a);
figure
plot(x, f); % now you have to make the plot yourself...
hold all
plot(x, 0.5 * ones(size(x))); % add the line at y=0.5
title 'cumulative probability of rand()'
xest = interp1(f, x, 0.5); % interpolate - find x where f would be 0.5
fprintf(1, 'The intercept is at x=%.2f\n", xest);