I am beginner in Matlab.
I have a histogram of a set of data I need to do 2 things.
1) I need the vertical axes to be normalized.
2) To curve a fit that passes through all the pick points of my Histogram bars.
Thank you
You can do it along these lines:
data = randn(1,1000); %// example data
num_bars = 15; %// specify number of bars
[n x] = hist(data,num_bars); %// use two-output version of hist to get values
n_normalized = n/numel(data)/(x(2)-x(1)); %// normalize to unit area
bar(x, n_normalized, 1); %// plot histogram (with unit-width bars)
hold on
plot(x, n_normalized, 'r'); %// plot line, in red (or change color)
For (1) try axis([xmin xmax ymin ymax])
For (2) try first drawing the histogram, then call hold on, then use the plot command.
Related
I want to represent data with 2 variables in 2D format. The value is represented by color and the 2 variables as the 2 axis. I am using the contourf function to plot my data:
clc; clear;
load('dataM.mat')
cMap=jet(256); %set the colomap using the "jet" scale
F2=figure(1);
[c,h]=contourf(xrow,ycol,BDmatrix,50);
set(h, 'edgecolor','none');
xlim([0.0352 0.3872]);
ylim([0.0352 0.3872]);
colormap(cMap);
cb=colorbar;
caxis([0.7 0.96]);
% box on;
hold on;
Both xrow and ycol are 6x6 matrices representing the coordinates. BDmatrix is the 6x6 matrix representing the corresponding data. However, what I get is this:
The following is the xrow and yrow matices:
The following is the BDmatrix matices:
Would it be possible for the contour color to vary smoothly rather than appearing as straight lines joining the data points? The problem of this figure is the coarse-granularity which is not appealing. I have tried to replace contourf with imagec but it seems not working. I am using MATLAB R2015b.
You can interpolate your data.
newpoints = 100;
[xq,yq] = meshgrid(...
linspace(min(min(xrow,[],2)),max(max(xrow,[],2)),newpoints ),...
linspace(min(min(ycol,[],1)),max(max(ycol,[],1)),newpoints )...
);
BDmatrixq = interp2(xrow,ycol,BDmatrix,xq,yq,'cubic');
[c,h]=contourf(xq,yq,BDmatrixq);
Choose the "smoothness" of the new plot via the parameter newpoints.
To reduce the Color edges, you can increase the number of value-steps. By default this is 10. The following code increases the number of value-steps to 50:
[c,h]=contourf(xq,yq,BDmatrixq,50);
A 3D-surf plot would be more suitable for very smooth color-shading. Just rotate it to a top-down view. The surf plot is also much faster than the contour plot with a lot of value-steps.
f = figure;
ax = axes('Parent',f);
h = surf(xq,yq,BDmatrixq,'Parent',ax);
set(h, 'edgecolor','none');
view(ax,[0,90]);
colormap(Jet);
colorbar;
Note 1: Cubic interpolation is not shape-preserving. That means, the interpolated shape can have maxima which are greater than the maximum values of the original BDmatrix (and minima which are less). If BDmatrix has noisy values, the interpolation might be bad.
Note 2: If you generated xrow and yrow by yourself (and know the limits), than you do not need that min-max-extraction what I did.
Note 3: After adding screenshots of your data matrices to your original posting, one can see, that xrow and ycol come from an ndgrid generator. So we also must use this here in order to be consistent. Since interp2 needs meshgrid we have to switch to griddedInterpolant:
[xq,yq] = ndgrid(...
linspace(min(min(xrow,[],1)),max(max(xrow,[],1)),newpoints ),...
linspace(min(min(ycol,[],2)),max(max(ycol,[],2)),newpoints )...
);
F = griddedInterpolant(xrow,ycol,BDmatrix,'cubic');
BDmatrixq = F(xq,yq);
I'm trying to plot two lines (data and linear fit) in a single graph with logarithmic scale. My code:
Iots = I_An./Temp.^2; % I Over T Squared
Oot = 1./Temp; % One Over T
[p,~] = polyfit(Oot,Iots,1);
linfit = polyval(p,Oot);
figure('color','w','units','normalized','outerposition',[0 0 1 1]);
hold on
loglog(Oot,Iots,'.','LineWidth',2);
loglog(Oot,linfit,':r','LineWidth',2);
The result is not a logarithmic scale graph:
If I run just one of the plot lines, it works on its own. What should I do? Are there any contradicting commands?
You want to call hold on after creating your first loglog plot. Also, you only need to use loglog on the first plot to create the logarithmic axes. After than you can just call normal plot and it will use the logarithmic axes.
x = linspace(0, 100);
loglog(x, x, '.', 'LineWidth', 2);
hold on
plot(x, x.^2, '.r', 'LineWidth',2);
I am having trouble plotting a histogram of the x-values of my data points together with a line showing the relationship between x and y, mainly because the scale in the y direction of the histogram is not of the same magnitude as the scale in the line plot. For example:
% generate data
rng(1, 'twister')
x = randn(10000,1);
y = x.^2
% plot line, histogram, then histogram and line.
subplot(3,1,1)
scatter(x, y, 1, 'filled')
ax = gca;
maxlim = max(ax.XLim); % store maximum y-value to rescale histogram to this value
subplot(3,1,2)
h = histogram(x, 'FaceAlpha', 0.2)
subplot(3,1,3)
scatter(x, y, 1, 'filled')
hold on
h = histogram(x, 'FaceAlpha', 0.2)
Produces the following:
where the line chart is completely obscured by the histogram.
Now, one might naively try to rescale the histogram using:
h.Values = h.Values/max(h.Values) * maxlim;
which gives
You cannot set the read-only property 'Values' of Histogram.
Alternatively one can get the bin counts using histcounts, but as far as I can tell, the bar function does not allow one to set the face alpha or have other configurability as per the call to histogram.
As discussed in the comments there are several solutions that depend on the version of Matlab you are using. To restate the problem, the histogram function allows you to control many graphics properties like transparency, but only gives you a limited number of options to change the height of the bars. With histcounts you can get the bar heights and rescale them however you want, but you must plot the bars yourself.
First option: use histogram
As you cannot rescale the histogram heights, you must plot them on separate axis.
From release 2016a and onwards, you can use yyaxis left for the scatter plot and yyaxis right for the histogram, see Matlab documentation:
Prior to this one must manually create and set separate y-axis. Although I have not found a good simple example of this, this is perhaps the most relevant answer here: plot two histograms (using the same y-axis) and a line plot (using a different y-axis) on the same figure
Using histcounts and manually creating a bar chart
Using my example, we can get counts as follows:
[Values, Edges] = histcounts(x);
And rescaling:
Values = Values / max(Values) * maxlim;
and finding centres of bars:
bar_centres = 0.5*(Edges(1:end-1) + Edges(2:end));
Up to release 2014a, bar charts had a 'children' property for the patches that allows transparency to be controlled, e.g.:
% plot histogram
b1 = bar(bar_centres,Values);
% change transparency
set(get(b1,'Children'),'FaceAlpha',0.3)
After 2014a bar charts no longer have this property, and to get around it I plot the patches myself using the code from this mathworks q&a, replicated here:
function ptchs = createPatches(x,y,offset,c,FaceAlpha)
%createPatches.m
% This file will create a bar plot with the option for changing the
% FaceAlpha property. It is meant to be able to recreate the functionality
% of bar plots in versions prior to 2014b. It will create the rectangular
% patches with a base centered at the locations in x with a bar width of
% 2*offset and a height of y.
% Ensure x and y are numeric vectors
validateattributes(x,{'numeric'},{'vector'});
validateattributes(y,{'numeric'},{'vector'});
validateattributes(c,{'char'},{'scalar'});
%#TODO Allow use of vector c
% Check size(x) is same as size(y)
assert(all(size(x) == size(y)),'x and y must be same size');
% Default FaceAlpha = 1
if nargin < 5
FaceAlpha = 1;
end
if FaceAlpha > 1 || FaceAlpha <= 0
warning('FaceAlpha has been set to 1, valid range is (0,1]');
FaceAlpha = 1;
end
ptchs = cell(size(x)); % For storing the patch objects
for k = 1:length(x)
leftX = x(k) - offset; % Left Boundary of x
rightX = x(k) + offset; % Right Boundary of x
ptchs{k} = patch([leftX rightX rightX leftX],...
[0 0 y(k) y(k)],c,'FaceAlpha',FaceAlpha, ...
'EdgeColor', 'none');
end
end
I made one change: that is, imposed the no edge condition. Then, it is perfectly fine to use:
createPatches(bin_centres, Values, 1,'k', 0.2)
to create the bars.
I read in an image in MATLAB and display it using imagesc. I then set the colormap to grey.
On top of this image, I plot points with the jet colour scheme. How do I then display the jet colorbar, to correspond to the colours of the points plotted on top of the original image? I tried redefining the colorbar after all of the plots, but this changes the original grey scale image back to colours, which isn't desired.
Code:
%Create Figure with handle.
h5=figure('units','normalized','outerposition',[0 0 1 1]);
whitebg(h5,[0 0 0]);
subplot(2,5,1);
k=1;
for i=16:25
subplot(2,5,k);
imagesc(squeeze(ana(:,:,i)));
title(['Z=',num2str(i)]);
colormap gray
axis equal
k=k+1;
colorbar
end
%Adapt colour values so that they are between 0 and 1. We want to scale
%both data sets equally, so we find the smallest value across Ix and Iy. We
%also find what will be the new largest value across Ix and Iy, after we
%add the magnitude of the smallest value to make all numbers greater than
%or equal to 0.
absolutemin=min(min(Ix(:,1)),min(Iy(:,1)));
absolutemax=max(abs(absolutemin)+(max(Ix(:,1))),abs(absolutemin)+max(Iy(:,1)));
%Add the smallest value, and divide by the largest maximum value for both Ix
%and Iy.
ixcolours=uint8(((Ix(:,1)+abs(absolutemin))/absolutemax).*255)+1;
iycolours=uint8(((Iy(:,1)+abs(absolutemin))/absolutemax).*255)+1;
mycolours=jet(256);
o=1;
for k=16:25; %For all 3D slices
for i=1:471; %and for all x and y seed slices
if k==seed_locs(i,3);
subplot(2,5,o);
hold all%go to the corresponding z subplot
plot(seed_locs(i,1),seed_locs(i,2),'MarkerFaceColor',mycolours(ixcolours(i),:),'MarkerEdgeColor',mycolours(ixcolours(i),:),'MarkerSize',10,'Marker','s') %plot the x and y seedlocs
%hold on
end
end
for i=1:486;
if k==test_locs(i,3);
subplot(2,5,o);
hold all
plot(test_locs(i,1),test_locs(i,2),'MarkerFaceColor',mycolours(iycolours(i),:),'MarkerEdgeColor',mycolours(iycolours(i),:),'MarkerSize',10,'Marker','s') %plot the x and y seedlocs
% hold on
end
end
o=o+1; %go to the next z subplot
end
colormap jet
colorbar
I think the following example can help you to improve your code. You firstly need to define two colormaps:
colormap([cool(64);gray(64)]);
Then let's say we have two different sets of datapoints to plot:
[X,Y,Z] = peaks(25);
h(1) = surf(X,Y,Z);hold on
h(2) = pcolor(X,Y,Z);
So the data is defined with two different handles. Now we need to make the CData using the minimum and maximum values.
cmin = min(Z(:));
cmax = max(Z(:));
C1 = min(64,round((64-1)*(Z-cmin)/(cmax-cmin))+1); % CData for the first datapoints
C2 = 64+C1; % CData for the second datapoints
Now we update the CDatas for each object.
set(h(1),'CData',C1);
set(h(2),'CData',C2);
Now you can set the CLim property of axes:
caxis([min(C1(:)) max(C2(:))])
colorbar;
I have a Matlab figure with two histograms on it
,
created with hist() function. Now I want to add two plots in the same figure (bell distribution actually:
,
but they have different scale. I thought I could use plotyy, but I already have my first plot-scale on the figure. How can I add the second plot-scale?
Generally, this is one way to do it:
%// example data
rng(0,'twister')
data = randn(1000,3);
x = linspace(-4,4,100);
y = 16 - x.^2;
%// generate two axes at same position
ax1 = axes;
ax2 = axes('Position', get(ax1, 'Position'),'Color','none');
%// move second axis to the right, remove x-ticks and labels
set(ax2,'YAxisLocation','right')
set(ax2,'XTick',[])
%// plot hist and line plot
hist(ax1,data); hold on
plot(ax2,x,y)
ylabel(ax1,'label of hist')
ylabel(ax2,'label of plot')
xlabel(ax1,'Hello World!')