I have an assignment which sounds like:
"“Grades per assignment”: A plot with the assignments on the x-axis and the grades on the y-axis. The x-axis must show all assignments from 1 to M, and the y-axis must show all grade −3 to 12. The plot must contain:
Each of the given grades marked by a dot. You must add a small random number (between -0.1 and 0.1) to the x- and y-coordinates of each dot, to be able tell apart the different dots which otherwise would be on top of each other when more than one student has received the same grade in the same assignment.
The average grade of each of the assignments plotted as a line"
For now i have created this function:
function gradesPlot(grades)
figure(2);
n_assignments=size(grades,2);
hold on; % Retain current plot when adding new plots.
for i = 1:n_assignments % Loop through every assignment.
% Scatter plot of assignment vs grades for that assignment.
% One assignment on every iteration.
n_assignments2=([1:size(grades,2)]);
scatter(n_assignments2,grades(:,i)'jitter', 'on', 'jitterAmount', 0.1)
hold off; % Set the hold state to off.
end
%Titles to the plot
title('Grades per assignment');
xlabel('Assignment');
ylabel('Given grades');
break;
end
when i run the code it says that the vectors must be same length.
And it looks like it doesn't loop over the matrix more than ones.
The test grades i am using as input is looking like this:
grades=[[-3,4,10];[7,4,12];[7,10,12];[0,4,4];[2,2,2];[2,2,2]]
I hope some of you guys can help me get this function to work - maybe in an easier way?
Thank you in advance
You should not turn off hold since it is tells MatLab to plot everything in the current active plot, roughly speaking. You can find a possible solution to your problem down below: I added some explanations in comments.
function gradesPlot(grades)
figure(2);
% Extract the relevant information: number of assignements, number of grades
[n_assignments,n_grades] = size(grades);
hold on; % Retain current plot when adding new plots.
for i = 1:n_assignments % Loop through every assignment.
% Scatter plot of assignment vs grades for that assignment.
% One assignment on every iteration
% For Scatter, you have to provide 2 vectors of the same size: in this
% way, we are putting al the dots corresponding to the grades of the
% i-th assignement in correspondence of the i-th coordinate on the x
% axis. We are also temporary saving in h the handle to the attributes
% of the dots, in order to retrieve the color.
h = scatter(i*ones(n_grades,1),grades(i,:),'jitter', 'on', 'jitterAmount', 0.1);
% This plots the horizontal line corresponding to the average of the
% grades related to the i-th assignement
l = line([i-0.5 i+0.5],[1,1]*mean(grades(i,2:end)));
% For using the same color as the dots.
l.Color = h.CData;
end
%Titles to the plot
title('Grades per assignment');
xlabel('Assignment');
ylabel('Given grades');
axis([0 n_assignments+1 -4 13])
end
Remember that the break command must be used inside a loop, not for exiting a function. Use return if you desire.
Related
I want to set the limit for X axis in this plot from 0 to 325. When i am using xlim to set the limits (commented in the code). It doesn't work properly. When i use xlim, the entire structure of plot changes. Any help will be appreciated.
figure
imagesc(transpose(all_area_for_visual));
colormap("jet")
colorbar('Ticks',0:3,'TickLabels',{'Home ','Field','Bad house','Good house'})
xlabel('Time (min)')
tickLocs = round(linspace(1,length(final_plot_mat_missing_part(2:end,1)),8));
timeVector = final_plot_mat_missing_part(2:end,1);
timeForTicks = (timeVector(tickLocs))./60;
xticks(tickLocs);
xticklabels(timeForTicks);
%xlim([0 325]);
ylabel('Car identity')
yticks(1:length(Ucolumnnames_fpm))
yticklabels([Ucolumnnames_fpm(1,:)])
If I get you right, you want to plot only part of the data in all_area_for_visual, given by a condition on tickLocs. So you should first condition the data, and then plot it:
% generate the vector of x values:
tickLocs = round(linspace(1,length(final_plot_mat_missing_part(2:end,1)),8));
% create an index vector (of logicals) that marks the columns to plot from the data matix:
validX = tickLocs(tickLocs<=325);
% plot only the relevant part of the data:
imagesc(transpose(all_area_for_visual(:,validX)));
% generate the correct ticks for the data that was plotted:
timeVector = final_plot_mat_missing_part(2:end,1);
timeForTicks = (timeVector(tickLocs(validX)))./60;
xticks(tickLocs(validX));
% here you continue with setting the labels, colormap and so on...
imagesc puts the data in little rectangles centered around integers 1:width and 1:height by default. You can specify what the x and y locations of each data point by adding two vectors to the call:
imagesc(x,y,transpose(all_area_for_visual));
where x and y are vectors with the locations along the x and y axes you want to place the data.
Note that xlim and xticks don’t change the location of the data, only the region of the axis shown, and the location of tick marks along the axis. With xticklabels you can change what is shown at each tick mark, so you can use that to “fake” the data locations, but the xlim setting still applies to the actual locations, not to the labels assigned to the ticks.
I think it is easier to plot the data in the right locations to start with. Here is an example:
% Fake your data, I'm making a small matrix here for illustration purposes
all_area_for_visual = min(floor(cumsum(rand(20,5)/2)),3);
times = linspace(0,500,20); % These are the locations along the time axis for each matrix element
car_id_names = [4,5,8,15,18]; % These are the labels to put along the y-axis
car_ids = 1:numel(car_id_names); % These are the locations to use along the y-axis
% Replicate your plot
figure
imagesc(times,car_ids,transpose(all_area_for_visual));
% ^^^ ^^^ NOTE! specifying locations
colormap("jet")
colorbar('Ticks',0:3,'TickLabels',{'Home ','Field','Bad house','Good house'})
xlabel('Time (min)')
ylabel('Car identity')
set(gca,'YTick',car_ids,'YTickLabel',car_id_names) % Combine YTICK and YTICKLABEL calls
% Now you can specify your limit, in actual time units (min)
xlim([0 325]);
I wish to highlight/mark some parts of a array via plot in MATLAB. After some research (like here) I tried to hold the first plot, find the indexes for highlighting and then a new plot, only with those points. However, those points are being drawn but all shifted to the beginning of the axis:
I'm currently trying using this code:
load consumer; % the main array to plot (157628x10 double) - data on column 9
load errors; % a array containing the error indexes (1x5590 double)
x = 1:size(consumer,1)'; % returns a (157628x1 double)
idx = (ismember(x,errors)); % returns a (157628x1 logical)
fig = plot(consumer(:,9));
hold on, plot(consumer(idx,9),'r.');
hold off
Another thing I would like to do was highlighting the whole section of the graph, like a "patch" on the same sections. Any ideas?
The trouble is that you are only providing the y-axis data to the plot function. By default, this means all data is plotted on the 1:numel(y) x locations of your plot, where y is your y-axis data.
You have 2 options...
Also provide x-axis data. You've already got the array x anyway!
figure; hold on;
plot(x, consumer(:,9));
plot(x(idx), consumer(idx,9), 'r.');
Aside: I'm slightly confused why you create idx. If errors is as you describe it (indexes of the array) then you should just be able to use consumer(errors,9).
Make all data which you don't want to appear equal to NaN. Because of the way you're loading your error indices in, this is less quick and easy. Basically you'd copy consumer(:,9) into a new variable, and index all undesirable points to set them equal to NaN.
This method has the benefit of breaking up discontinuous sections too.
y = consumer(:,9); % copy your y data before changes
idx = ~ismember(x, errors); % get the indices you *don't* want to re-plot
y(idx) = NaN; % Set equal to NaN so they aren't plotted
figure; hold on;
plot(x, consumer(:,9));
plot(x, y, 'r'); % Plot all points, NaNs wont show
I have some problems with a scatter plot.
I am plotting a matrix containing grades per assignment for students e.g. [assignments x grades], but if more than one student gets the same grade in the same assignment, the points will be on top of each other. I want to add a small random number (between -0.1 and 0.1) to the x- and y-coordinates of each dot.
On the x-axis it should be number of assignments and on the y-axis it should be all the grades.
the grades matrix is defined as a 12x4 matrix
My code looks like this:
n_assignments = size(grades,2); % Total number of assignments.
n_students = size(grades,1); % Total number of student.
hold on; % Retain current plot when adding new plots.
for i = 1:n_assignments % Loop through every assignment.
% Scatter plot of assignment vs grades for that assignment.
% One assignment on every iteration.
scatter(i*ones(1, n_students), grades(i, :), 'jitter', 'on', 'jitterAmount', 0.1);
end
hold off; % Set the hold state to off.
set(gca, 'XTick', 1:n_assignments); % Display only integer values in x-axis.
xlabel('assignment'); % Label for x-axis.
ylabel('grades'); % Label for y-axis.
grid on; % Display grid lines.
But I keep getting the error message:
X and Y must be vectors of the same length.
Please note that the scatter plot jitter is an undocumented
feature. You can also have semi-transparent markers in line and
scatter plots, which could be another alternative to solve your
current problem.
I will cover the scatter 'jitter' feature in this answer.
Note that 'jitter' only affects the x-axis but not the y-axis (more info on Undocumented Matlab).
Have a look at this example I made based on your description:
Suppose you have a class with 20 students and they have completed 5 assignments. The grades for the assignments are stored in a matrix (grades) where the rows are the assignments and the columns are the students.
Then I simply generate a scatter plot of the data in the grades matrix, one row at a time, in a for loop and using hold on to keep all the graphics on the same figure.
n_assignments = 5; % Total number of assignments.
n_students = 20; % Total number of students.
grades = randi(10, n_assignments, n_students); % Random matrix of grades.
hold on; % Retain current plot when adding new plots.
for i = 1:n_assignments % Loop through every assignment.
% Scatter plot of assignment vs grades for that assignment.
% One assignment on every iteration.
scatter(i*ones(1, n_students), grades(i, :), 'jitter', 'on', 'jitterAmount', 0.1);
end
hold off; % Set the hold state to off.
set(gca, 'XTick', 1:n_assignments); % Display only integer values in x-axis.
xlabel('assignment'); % Label for x-axis.
ylabel('grades'); % Label for y-axis.
grid on; % Display grid lines.
This is the result:
If you still want to add jitter in the y-axis, you would have to do that manually by adding random noise to your grades data, which is something I personally wouldn't recommend, because the grades in the scatter plot could get mixed, thus rendering the plot completely unreliable.
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:
for an implicit equation(name it "y") of lambda and beta-bar which is plotted with "ezplot" command, i know it is possible that by a root finding algorithm like "bisection method", i can find solutions of beta-bar for each increment of lambda. but how to build such an algorithm to obtain the lines correctly.
(i think solutions of beta-bar should lie in an n*m matrix)
would you in general show the methods of plotting such problem? thanks.
one of my reasons is discontinuity of "ezplot" command for my equation.
ok here is my pic:
alt text http://www.mojoimage.com/free-image-hosting-view-05.php?id=5039TE-beta-bar-L-n2-.png
or
http://www.mojoimage.com/free-image-hosting-05/5039TE-beta-bar-L-n2-.pngFree Image Hosting
and my code (in short):
h=ezplot('f1',[0.8,1.8,0.7,1.0]);
and in another m.file
function y=f1(lambda,betab)
n1=1.5; n2=1; z0=120*pi;
d1=1; d2=1; a=1;
k0=2*pi/lambda;
u= sqrt(n1^2-betab^2);
wb= sqrt(n2^2-betab^2);
uu=k0*u*d1;
wwb=k0*wb*d2 ;
z1=z0/u; z1_b=z1/z0;
a0_b=tan(wwb)/u+tan(uu)/wb;
b0_b=(1/u^2-1/wb^2)*tan(uu)*tan(wwb);
c0_b=1/(u*wb)*(tan(uu)/u+tan(wwb)/wb);
uu0= k0*u*a; m=0;
y=(a0_b*z1_b^2+c0_b)+(a0_b*z1_b^2-c0_b)*...
cos(2*uu0+m*pi)+b0_b*z1_b*sin(2*uu0+m*pi);
end
fzero cant find roots; it says "Function value must be real and finite".
anyway, is it possible to eliminate discontinuity and only plot real zeros of y?
heretofore,for another function (namely fTE), which is :
function y=fTE(lambda,betab,s)
m=s;
n1=1.5; n2=1;
d1=1; d2=1; a=1;
z0=120*pi;
k0=2*pi/lambda;
u = sqrt(n1^2-betab^2);
w = sqrt(betab^2-n2^2);
U = k0*u*d1;
W = k0*w*d2 ;
z1 = z0/u; z1_b = z1/z0;
a0_b = tanh(W)/u-tan(U)/w;
b0_b = (1/u^2+1/w^2)*tan(U)*tanh(W);
c0_b = -(tan(U)/u+tanh(W)/w)/(u*w);
U0 = k0*u*a;
y = (a0_b*z1_b^2+c0_b)+(a0_b*z1_b^2-c0_b)*cos(2*U0+m*pi)...
+ b0_b*z1_b*sin(2*U0+m*pi);
end
i'd plotted real zeros of "y" by these codes:
s=0; % s=0 for even modes and s=1 for odd modes.
lmin=0.8; lmax=1.8;
bmin=1; bmax=1.5;
lam=linspace(lmin,lmax,1000);
for n=1:length(lam)
increment=0.001; tolerence=1e-14; xstart=bmax-increment;
x=xstart;
dx=increment;
m=0;
while x > bmin
while dx/x >= tolerence
if fTE(lam(n),x,s)*fTE(lam(n),x-dx,s)<0
dx=dx/2;
else
x=x-dx;
end
end
if abs(real(fTE(lam(n),x,s))) < 1e-6 %because of discontinuity some answers are not correct.%
m=m+1;
r(n,m)=x;
end
dx=increment;
x=0.99*x;
end
end
figure
hold on,plot(lam,r(:,1),'k'),plot(lam,r(:,2),'c'),plot(lam,r(:,3),'m'),
xlim([lmin,lmax]);ylim([1,1.5]),
xlabel('\lambda(\mum)'),ylabel('\beta-bar')
you see i use matrix to save data for this plot.
![alt text][2]
because here lines start from left(axis) to rigth. but if the first line(upper) starts someplace from up to rigth(for the first figure and f1 function), then i dont know how to use matrix. lets improve this method.
[2]: http://www.mojoimage.com/free-image-hosting-05/2812untitled.pngFree Image Hosting
Sometimes EZPLOT will display discontinuities because there really are discontinuities or some form of complicated behavior of the function occurring there. You can see this by generating your plot in an alternative way using the CONTOUR function.
You should first modify your f1 function by replacing the arithmetic operators (*, /, and ^) with their element-wise equivalents (.*, ./, and .^) so that f1 can accept matrix inputs for lambda and betab. Then, run the code below:
lambda = linspace(0.8,1.8,500); %# Create a vector of 500 lambda values
betab = linspace(0.7,1,500); %# Create a vector of 500 betab values
[L,B] = meshgrid(lambda,betab); %# Create 2-D grids of values
y = f1(L,B); %# Evaluate f1 at every point in the grid
[c,h] = contour(L,B,y,[0 0]); %# Plot contour lines for the value 0
set(h,'Color','b'); %# Change the lines to blue
xlabel('\lambda'); %# Add an x label
ylabel('$\overline{\beta}$','Interpreter','latex'); %# Add a y label
title('y = 0'); %# Add a title
And you should see the following plot:
Notice that there are now additional lines in the plot that did not appear when using EZPLOT, and these lines are very jagged. You can zoom in on the crossing at the top left and make a plot using SURF to get an idea of what's going on:
lambda = linspace(0.85,0.95,100); %# Some new lambda values
betab = linspace(0.95,1,100); %# Some new betab values
[L,B] = meshgrid(lambda,betab); %# Create 2-D grids of values
y = f1(L,B); %# Evaluate f1 at every point in the grid
surf(L,B,y); %# Make a 3-D surface plot of y
axis([0.85 0.95 0.95 1 -5000 5000]); %# Change the axes limits
xlabel('\lambda'); %# Add an x label
ylabel('$\overline{\beta}$','Interpreter','latex'); %# Add a y label
zlabel('y'); %# Add a z label
Notice that there is a lot of high-frequency periodic activity going on along those additional lines, which is why they look so jagged in the contour plot. This is also why a very general utility like EZPLOT was displaying a break in the lines there, since it really isn't designed to handle specific cases of complicated and poorly behaved functions.
EDIT: (response to comments)
These additional lines may not be true zero crossings, although it is difficult to tell from the SURF plot. There may be a discontinuity at those lines, where the function shoots off to -Inf on one side of the line and Inf on the other side of the line. When rendering the surface or computing the contour, these points on either side of the line may be mistakenly connected, giving the false appearance of a zero crossing along the line.
If you want to find a zero crossing given a value of lambda, you can try using the function FZERO along with an anonymous function to turn your function of two variables f1 into a function of one variable fcn:
lambda_zero = 1.5; %# The value of lambda at the zero crossing
fcn = #(x) f1(lambda_zero,x); %# A function of one variable (lambda is fixed)
betab_zero = fzero(fcn,0.94); %# Find the value of betab at the zero crossing,
%# using 0.94 as an initial guess