I have 2 variables x and y
x= randi([50 100],1,1000)';
y= randi([8 100],1,1000)';
acc = accumarray(x, y);
figure
bar(acc)
how can I get the same plot using the hist function?
in particular I need the variable unknown for which
hist(unknown) produces the same plot than bar(acc)
You have to sort your y vector.
So we obtain:
hist(x,sort(y));
And if you can use histogram() instead of hist(); (recommanded by mathworks)
histogram(x,sort(y));
And be careful because here your bins are not regular ! perhaps you have better to use y = linespace(8,100,1000) (regular bins spacing) but of course the result will be a little be different.
Related
I'm trying to plot this equation but i'm some difficulties, some help please.
I here is what i have tried.
x=[0:pi/20:4*pi];
y= (25*sin(3)*t);
plot (x,y)
Your code isn't working because t is undefined. You either need to change your definition of x to be t, for example:
t=[0:pi/20:4*pi];
or you need to make your y a function of x, rather than t, for example:
y= (25*sin(3)*x);
I am curious if your original equation/function that you are trying to plot is y(t)=25 sin(3 t). If this is the case, then you need to change your parenthesis so that sin is a function of the independent variable (x or t). This would look like:
y = 25*sin(3*x);
I think you meant to get oscillations:
x = [0:pi/20:4*pi];
y = 25*sin(3*x);
plot(x,y)
You need to assign equal vector length value to t as of x.
However, I believe, you need to replace x with t in your equation.
y= (25*sin(3)*x); # will plot a straight line since you have a constant sin(3)
# which you are just multiplying with x resulting in x verses constant x
I assume you want to write the equation as
x=[0:pi/20:4*pi];
y= (25*sin(3*x));
plot (x,y)
Plot Matlab
I have a parametric B-Spline surface, S
S=[x(:);y(:);z(:)];
Right now, I am plotting the surface by just plotting each column of S as a single point:
plot3(S(1,:),S(2,:),S(3,:),'.')
The result is this:
Unfortunately, by plotting individual points, we lose the sense of depth and curvy-ness when we look at this picture.
Any ideas on how to implement SURF or MESH command for a parametric surface? These functions seem to require a matrix representing a meshgrid which I dont think I can use since the X x Y domain of S is not a quadrilateral. However, I like the lighting and color interpolation that can be conveniently included when using these functions, as this would fix the visualization problem shown in figure above.
I am open to any other suggestions as well.
Thanks.
Without seeing your equations it's hard to offer an exact solution, but you can accomplish this by using fsurf (ezsurf if you have an older version of MATLAB).
There are specific sections regarding plotting parametric surfaces using ezsurf and fsurf
syms s t
r = 2 + sin(7*s + 5*t);
x = r*cos(s)*sin(t);
y = r*sin(s)*sin(t);
z = r*cos(t);
fsurf(x, y, z, [0 2*pi 0 pi]) % or ezsurf(x, y, z, [0 2*pi 0 pi])
If you want to have a piece-wise function, you can either write a custom function
function result = xval(s)
if s < 0.5
result = 1 - 2*s;
else
result = 2 * x - 1;
end
end
And pass a function handle to fsurf
fsurf(#xval, ...)
Or you can define x to be piece-wise using a little bit of manipulation of the function
x = (-1)^(s > 0.5) * (1 - 2*s)
I want to write a bimodal Probability Density Function (PDF with multiple peaks, Galtung S) without using the pdf function from statistics toolbox. Here is my code:
x = 0:0.01:5;
d = [0.5;2.5];
a = [12;14]; % scale parameter
y = 2*a(1).*(x-d(1)).*exp(-a(1).*(x-d(1)).^2) + ...
2*a(2).*(x-d(2)).*exp(-a(2).*(x-d(2)).^2);
plot(x,y)
Here's the curve.
plot(x,y)
I would like to change the mathematical formula to to get rid of the dips in the curve that appear at approx. 0<x<.5 and 2<x<2.5.
Is there a way to implement x>d(1) and x>d(2) in line 4 of the code to avoid y < 0? I would not want to solve this with a loop because I need to convert the formula to CDF later on.
If you want to plot only for x>max(d1,d2), you can use logical indexing:
plot(x(x>max(d)),y(x>max(d)))
If you to plot for all x but plot max(y,0), you just can write so:
plot(x,max(y,0))
It seems to be very basic question, but I wonder when I plot x values against y values, what interpolation technique is used behind the scene to show me the discrete data as continuous? Consider the following example:
x = 0:pi/100:2*pi;
y = sin(x);
plot(x,y)
My guess is it is a Lagrangian interpolation?
No, it's just a linear interpolation. Your example uses a quite long dataset, so you can't tell the difference. Try plotting a short dataset and you'll see it.
MATLAB's plot performs simple linear interpolation. For finer resolution you'd have to supply more sample points or interpolate between the given x values.
For example taking the sinus from the answer of FamousBlueRaincoat, one can just create an x vector with more equidistant values. Note, that the linear interpolated values coincide with the original plot lines, as the original does use linear interpolation as well. Note also, that the x_ip vector does not include (all) of the original points. This is why the do not coincide at point (~0.8, ~0.7).
Code
x = 0:pi/4:2*pi;
y = sin(x);
x_ip = linspace(x(1),x(end),5*numel(x));
y_lin = interp1(x,y,x_ip,'linear');
y_pch = interp1(x,y,x_ip,'pchip');
y_v5c = interp1(x,y,x_ip,'v5cubic');
y_spl = interp1(x,y,x_ip,'spline');
plot(x,y,x_ip,y_lin,x_ip,y_pch,x_ip,y_v5c,x_ip,y_spl,'LineWidth',1.2)
set(gca,'xlim',[pi/5 pi/2],'ylim',[0.5 1],'FontSize',16)
hLeg = legend(...
'No Interpolation','Linear Interpolation',...
'PChip Interpolation','v5cubic Interpolation',...
'Spline Interpolation');
set(hLeg,'Location','south','Fontsize',16);
By the way..this does also apply to mesh and others
[X,Y] = meshgrid(-8:2:8);
R = sqrt(X.^2 + Y.^2) + eps;
Z = sin(R)./R;
figure
mesh(Z)
No, Lagrangian interpolation with 200 equally spaced points would be an incredibly bad idea. (See: Runge's phenomenon).
The plot command simply connects the given (x,y) points by straight lines, in the order given. To see this for yourself, use fewer points:
x = 0:pi/4:2*pi;
y = sin(x);
plot(x,y)
I want to plot relations like y^2=x^2(x+3) in MATLAB without using ezplot or doing algebra to find each branch of the function.
Does anyone know how I can do this? I usually create a linspace and then create a function over the linspace. For example
x=linspace(-pi,pi,1001);
f=sin(x);
plot(x,f)
Can I do something similar for the relation I have provided?
What you could do is use solve and allow MATLAB's symbolic solver to symbolically solve for an expression of y in terms of x. Once you do this, you can use subs to substitute values of x into the expression found from solve and plot all of these together. Bear in mind that you will need to cast the result of subs with double because you want the numerical result of the substitution. Not doing this will still leave the answer in MATLAB's symbolic format, and it is incompatible for use when you want to plot the final points on your graph.
Also, what you'll need to do is that given equations like what you have posted above, you may have to loop over each solution, substitute your values of x into each, then add them to the plot.
Something like the following. Here, you also have control over the domain as you have desired:
syms x y;
eqn = solve('y^2 == x^2*(x+3)', 'y'); %// Solve for y, as an expression of x
xval = linspace(-1, 1, 1000);
%// Spawn a blank figure and remember stuff as we throw it in
figure;
hold on;
%// For as many solutions as we have...
for idx = 1 : numel(eqn)
%// Substitute our values of x into each solution
yval = double(subs(eqn(idx), xval));
%// Plot the points
plot(xval, yval);
end
%// Add a grid
grid;
Take special care of how I used solve. I specified y because I want to solve for y, which will give me an expression in terms of x. x is our independent variable, and so this is important. I then specify a grid of x points from -1 to 1 - exactly 1000 points actually. I spawn a blank figure, then for as many solutions to the equation that we have, we determine the output y values for each solution we have given the x values that I made earlier. I then plot these on a graph of these points. Note that I used hold on to add more points with each invocation to plot. If I didn't do this, the figure would refresh itself and only remember the most recent call to plot. You want to put all of the points on here generated from all of the solution. For some neatness, I threw a grid in.
This is what I get:
Ok I was about to write my answer and I just saw that #rayryeng proposed a similar idea (Good job Ray!) but here it goes. The idea is also to use solve to get an expression for y, then convert the symbolic function to an anonymous function and then plot it. The code is general for any number of solutions you get from solve:
clear
clc
close all
syms x y
FunXY = y^2 == x^2*(x+3);
%//Use solve to solve for y.
Y = solve(FunXY,y);
%// Create anonymous functions, stored in a cell array.
NumSol = numel(Y); %// Number of solutions.
G = cell(1,NumSol);
for k = 1:NumSol
G{k} = matlabFunction(Y(k))
end
%// Plot the functions...
figure
hold on
for PlotCounter = 1:NumSol
fplot(G{PlotCounter},[-pi,pi])
end
hold off
The result is the following:
n = 1000;
[x y] = meshgrid(linspace(-3,3,n),linspace(-3,3,n));
z = nan(n,n);
z = (y .^ 2 <= x .^2 .* (x + 3) + .1);
z = z & (y .^ 2 >= x .^2 .* (x + 3) - .1);
contour(x,y,z)
It's probably not what you want, but I it's pretty cool!