I have written a code in MATLAB for university and I have been told that indentation is important and it caused me to lose 3 marks out of 8 for it. Is indentation not just "style"?
The code if as follows:
function[pp,pb,pd]=demopoly(fname,N)
%The function reads the data from the file and computes the coefficients of a polynomial of degree N of three polynomials pp, pb, and pd that best fit the population, births and deaths in the data.
%The function returns the three variables pp, pb and pd in this order.
C=csvread(fname);
pp=polyfit(C(:,1),C(:,2),N);
pb=polyfit(C(:,1),C(:,3),N);
pd=polyfit(C(:,1),C(:,4),N);
end
Can someone let me know where the indentations should have occurred?
Indentation is just Ctrl+A and Ctrl+I away. Seems difficult? Other answers have pointed out why indentation is important. Regarding the question where indentation should have occured, the fact is there's no indentation problem in the code that you showed.
If I had to cut your marks for the code you showed, I'll cut for:
Having no line breaks in that first comment. It's too long and requires scrolling to read.
Extra line breaks in code.
Although Matlab code is not sensitive to indendation (unlike, for example, Python), it's very important to use a indentation in order to improve the code readability and it's maintainability.
If you are too lazy to manually indent your code while writing it down, Matlab offers you a Smart Indent function that you can apply to your files once they are completed (more info here). If you are too lazy even for a CTRL+A CTRL+I, you could write a small "batch script of madness" that applies the Smart Indent to all the .m files located within a specific folder:
files = dir(fullfile(folder,'*.m'));
for i = 1:numel(files)
file_name = files(i).name;
file_path = fullfile(folder,file_name);
file_handle = matlab.desktop.editor.openDocument(file_path);
file_handle.smartIndentContents()
file_handle.save()
file_handle.close()
end
This is how I would format (and optimize a little bit) your function:
% The function reads the data from the file and computes
% the coefficients of a polynomial of degree N of three
% polynomials (pp, pb, and pd) that best fit the population,
% births and deaths in the data.
% The function returns the three variables pp, pb and pd
% in this order.
function [pp,pb,pd] = demopoly(fname,N)
C = csvread(fname);
C_1 = C(:,1);
pp = polyfit(C_1,C(:,2),N);
pb = polyfit(C_1,C(:,3),N);
pd = polyfit(C_1,C(:,4),N);
end
Related
In my code, I have a lot of constant values and parameters that take significant space in my code.
For example in C++, I would make a header and a separate file where I would define these parameters as, e.g., "const-type" and share the header with main or other .cpp files.
How do you keep such structuring in MATLAB, is it worth it?
An example: Coefficients.m looks as follows:
classdef coefficients
properties(Constant)
% NIST data
A_N = 28.98641;
end
end
Another file: Gas.m where I would like to use A_N looks as follows:
function Gas()
clear all
clc
import Coefficients.* % Does not work
% A simple print
Values.A_N % Does not work
coefficients.A_N % Does not work
Constant.A_N % Does not work
end
Ok so assuming the class coefficients defined as:
classdef coefficients
properties(Constant)
% NIST data
A_N = 28.98641;
end
end
This code must be saved in a file named coefficients.m (The class name and file name have to match to avoid weird effect sometimes).
Then assuming the following Gas.m file:
function Gas()
% Usage with "disp()"
disp('The A_N coefficient taken from NIST data is:')
disp(coefficients.A_N)
% Usage with fprintf
fprintf('\nFrom NIST data, the coefficient A_N = %f\n',coefficients.A_N)
% Usage in calculation (just use it as if it was a variable/constant name
AN2 = coefficients.A_N^2 ;
fprintf('\nA_N coefficient squared = %.2f\n',AN2)
% If you want a shorter notation, you can copy the coefficient value in
% a variable with a shorter name, then use that variable later in code
A_N = coefficients.A_N ;
fprintf('\nA_N coefficient cubed = %.2f\n',A_N^3)
end
Then running this file (calling it from the command line) yields:
>> Gas
The A_N coefficient taken from NIST data is:
28.98641
From NIST data, the coefficient A_N = 28.986410
A_N coefficient squared = 840.21
A_N coefficient cubed = 24354.73
Or if you simply need to access the coefficient in the Matlab console:
>> coefficients.A_N
ans =
28.98641
Now all these examples assume that the class file coefficient.m is visible in the current Matlab scope. For Matlab, it means the file must be in the MATLAB search path (or the current folder works too).
For more info about what is the Matlab search path and how it works you can read:
What Is the MATLAB Search
Path?
Files and Folders that MATLAB
Accesses
In your case, I would make a folder containing all these sorts of classes, then add this folder to the Matlab path, so you never have to worry again about individual script, function or program calling for it.
See this link for tips on using a class definition for this. Highlights of the tips are:
Properties can be accessed directly to get the value
Properties can be added that give the units of the constant (highly advised!)
Comments can be added that act as help text for the constants
The doc command automatically creates a reference page for this classdef
E.g.,
classdef myconstants
properties(Constant)
% g is the gravity of Earth
% (https://en.wikipedia.org/wiki/Gravity_of_Earth)
g = 9.8;
g_units = 'm/s/s';
% c is the speed of light in a vacuum
c = 299792458;
c_units = 'm/s';
end
end
>> help myconstants.g
This works (plots an "empty" figure):
function testme
plot(1)
This works (returns 1):
function testme
plot = #(x)x;
plot(1)
This does not (Error: "Undefined function or variable 'plot'."):
function testme
if 0
plot = #(x)x;
end
plot(1)
What's going on here? Why does rewriting but not redefining an already defined function render the function undefined?
Note 1: this is not specific for builtin functions; the following code returns the same error:
function testme
if 0
myfun = #(x)x;
end
myfun(1)
function x=myfun(x)
x=x*2;
Note 2: the error occurs in a function environment, not in a script; the following code does not return an error (and plots the same empty figure as in the first example):
if 0
plot = #(x)x;
end
plot(1)
Update: For the interested reader, here is some background information
on my original problem. The above examples are just minimum working
samples to illustrate the main issue (which indeed feature dead end if
statements). In practice, I was trying to make a function useable for
colleagues who did not have certain library/toolbox functions
available, by overwriting those functions for simplified custom ones
if they did not exist, as a quick fix. In particular, it concerned
imdilate (and imerode). The function looked something like the
following:
function [myoutputs] = myfunction(myinputs)
% if the images toolbox is not available, use the following simplified
% replacement function
if ~exist('imdilate','file')
imdilate = #(IM,SE)vecdilate(IM,SE);
end
%% The original function goes here, which uses a lot of imdilate(IM,SE).
%% local functions
function M = vecdilate(IM,SE)
% simplified version of imdilate (can only process 1-D vertical arrays)
nSE = size(SE);
nIM = size(IM);
SE = logical(SE); % make logical if it isn't yet
% copy and shift xth column x down. new border entries are 0:
M = repmat([IM;zeros(nSE)],nSE);
M = M(1:end-nSE(1));
M = reshape(M,[size(M,1)/nSE(1) nSE(1)]);
% shrink back to column by taking max of every row:
M = max(M(:,SE),[],2);
M = M(ceil(nSE(1)/2)-1+(1:nIM(1))); % clip to obtain correct size
You might see that the replacement function covers some
functionality of imdilate, but not all, and it might not be as
efficient. The purpose simply was to use function A if it was available, and
function B if it was not. To my surprise however, the former case
returned an error, which eventually resulted in this question. For your interest, I solved the practical problem by renaming the function in the
original code, and by using an if/else statement:
function [myoutputs] = myfunction(myinputs)
% if the images toolbox is not available, use the following simplified
% replacement function
if ~exist('imdilate','file')
mydilate = #(IM,SE)vecdilate(IM,SE);
else
mydilate = #(IM,SE)imdilate(IM,SE);
end
%% The original function goes here, which uses a lot of mydilate(IM,SE).
%% local functions
function M = vecdilate(IM,SE)
etc. etc. etc.
Just-in-time-compilation (JIT) does not mean that there is no compilation and that every line is interpreted separately, so you can still mess with the code;)
The error would also appear if you use a not-defined function, where you woun't even expect the code to run, like
function [] = test()
if false
a = #(x)x;
end
a(1)
end
Scripts are stored command line entries, i.e. the compiler has no choice but to handle every line separately (you may want to think of it as a keyboard macro).
Functions in contrast are encapsulated pieces of code. The compiler (in general) does not expect anything unknown + it thinks that this encapsulated piece of code might be reused. Therefore, it makes sure to do a proper job compile all code once beforehand (if the compile would do this all the time, it is called ahead-of-time compilation).
This becomes in particular obvious when your clear the variables in between:
function [] = test()
if false
plot = #(x)x;
else
clear all % clear vs clear all
end
plot(1)
end
(Note that clear clears all variables but clear all would also clear excising code (see MATLAB Execution Engine))
Have a look at this interesting blog post from Loren
MATLAB provides the best of both worlds by compiling MATLAB code on-the-fly, or just-in-time. MATLAB code is compiled whether it be in classes, functions, scripts, or simply at the command line. There is no explicit compile step for the user to initiate and MATLAB code can be executed in blocks as small as one line at a time. The MATLAB JIT compiler generates native machine level code that is optimized for the MATLAB code being executed and for the specific hardware platform.
Anyway, you should not write dead ends in your code or overwrite (native) functions. It is good to use function handles to overcome this problem, but make sure that you define it for all cases
function [] = test()
if false % dead end definition
fnc = #(x)x;
else
fnc = #plot;
end
fnc(1)
end
I want to include Matlab figures into latex preferably with vectorised formats but with LaTeX MATLAB fonts for all text. I have been using the MATLAB function matlab2tikz which worked perfect for simple figures, but now my figures have too many data points which cause an error. So matlab2tikz is not suitable.
I've been looking at matlabfrag which I think will accomplish what I want, but when I run the script in LaTeX as detailed by the user guide it has an error File not found.
This is my code:
\documentclass{article}
\usepackage{pstool}
\begin{document}
\psfragfig{FileName}
\end{document}
Where FileName is the name of the .eps and .tex that matlabfrag creates. Has anyone come across this problem? Or recommend any other functions/methods to use?
I'm using Texmaker on Windows 7.
My advice would be to rethink your workflow.
Instead of reusing your Matlab code to plot figures and be dissappointed by ever changing outputs with matlab2tikz, start reusing your latex code to plot figures and don't bother about plotting in Matlab anymore (at least not for beautiful plots).
matlab2tikz is just generating latex code based on the latex-package pgfplots. To understand the working of this package is pretty easy, as it is intended to be similar to Matlab.
So why bother and always let matlab2tikz do the work for you? Because again and again you won't be entirely happy with the results. Just try to write the pgfplots-code from scratch and just load the data from Matlab.
Here is a convenient function I wrote to create latex-ready text files:
function output = saveData( filename, header, varargin )
in = varargin;
numCols = numel(in);
if all(cellfun(#isvector, in))
maxLength = max(cellfun(#numel, in));
output = cell2mat(cellfun(#(x) [x(:); NaN(maxLength - numel(x) + 1,1)],in,'uni',0));
fid = fopen(filename, 'w');
fprintf(fid, [repmat('%s\t',1,numCols),'\r\n'], header{:});
fclose(fid);
dlmwrite(filename,output,'-append','delimiter','\t','precision','%.6f','newline', 'pc');
else
disp('saveData: only vector inputs allowed')
end
end
Which could for example look like the following, in case of a bode diagram:
w G0_mag G0_phase GF_mag GF_phase
10.000000 40.865743 -169.818991 0.077716 -0.092491
10.309866 40.345290 -169.511901 0.082456 -0.101188
10.629333 39.825421 -169.196073 0.087474 -0.110690
10.958700 39.306171 -168.871307 0.092787 -0.121071
11.298273 38.787575 -168.537404 0.098411 -0.132411
In your tikzpicture you can then just load that file by
\pgfplotstableread[skip first n=1]{mydata.txt}\mydata
and store the table into the variable \mydata.
Now check pfgplots how to plot your data. You will find the basic plot command \addplot
\addplot table [x expr= \thisrowno{0}, y expr= \thisrowno{3} ] from \mydata;
where you directly access the columns of your text file by \thisrowno{0} (confusing, I know).
Regarding your problem with to many data points: pgfplots offers the key each nth point={ ... } to speed things up. But I'd rather filter/decimate the data already in Matlab.
The other way around is also possible, if you have to few data points the key smooth smoothes things up.
I am writing a code that generates a function f in a loop. This function f changes in every loop, for example from f = x + 2x to f = 3x^2 + 1 (randomly), and I want to evaluate f at different points in every loop. I have tried using subs, eval, matlabFunction etc but it is still running slowly. How would you tackle a problem like this in the most efficient way?
This is as fast as I have been able to do it. ****matlabFunction and subs go slower than this.
The code below is my solution and it is one loop. In my larger code the function f and point x0 change in every loop so you can imagine why I want this to go as fast as possible. I would greatly appreciate it if someone could go through this, and give me any pointers. If my coding is crap feel free to tell me :D
x = sym('x',[2,1]);
f = [x(1)-x(1)cos(x(2)), x(2)-3x(2)^2*cos(x(1))];
J = jacobian(f,x);
x0 = [2,1];
N=length(x0); % Number of equations
%% Transform into string
fstr = map2mat(char(f));
Jstr = map2mat(char(J));
% replace every occurence of 'xi' with 'x(i)'
Jstr = addPar(Jstr,N);
fstr = addPar(fstr,N);
x = x0;
phi0 = eval(fstr)
J = eval(Jstr)
function str = addPar(str,N)
% pstr = addPar(str,N)
% Transforms every occurence of xi in str into x(i)
% N is the maximum value of i
% replace every occurence of xi with x(i)
% note that we do this backwards to avoid x10 being
% replaced with x(1)0
for i=N:-1:1
is = num2str(i);
xis = ['x' is];
xpis = ['x(' is ')'];
str = strrep(str,xis,xpis);
end
function r = map2mat(r)
% MAP2MAT Maple to MATLAB string conversion.
% Lifted from the symbolic toolbox source code
% MAP2MAT(r) converts the Maple string r containing
% matrix, vector, or array to a valid MATLAB string.
%
% Examples: map2mat(matrix([[a,b], [c,d]]) returns
% [a,b;c,d]
% map2mat(array([[a,b], [c,d]]) returns
% [a,b;c,d]
% map2mat(vector([[a,b,c,d]]) returns
% [a,b,c,d]
% Deblank.
r(findstr(r,' ')) = [];
% Special case of the empty matrix or vector
if strcmp(r,'vector([])') | strcmp(r,'matrix([])') | ...
strcmp(r,'array([])')
r = [];
else
% Remove matrix, vector, or array from the string.
r = strrep(r,'matrix([[','['); r = strrep(r,'array([[','[');
r = strrep(r,'vector([','['); r = strrep(r,'],[',';');
r = strrep(r,']])',']'); r = strrep(r,'])',']');
end
There are several ways to get huge boosts in speed for this sort of problem:
The java GUI front end slows everything down. Go back to version 2010a or earlier. Go back to when it was based on C or fortran. The MATLAB script runs as fast as if you had put it into the MATLAB "compiler".
If you have MatLab compiler (or builder, I forget which) but not the coder, then you can process your code and have it run a few times faster without modifying the code.
write it to a file, then call it as a function. I have done this for changing finite-element expressions, so large ugly math that makes $y = 3x^2 +1$ look simple. In that it gave me solid speed increase.
vectorize, vectorize, vectorize. It used to reliably give 10x to 12x speed increase. Pull it out of loops. The java, I think, obscures this some by making everything slower.
have you "profiled" your function to make sure that "eval" or such are the problem? If you fix "eval" and your bottleneck is elsewhere then you will have problems.
If you have the choice between eval and subs, stick with eval. subs gives you a symbolic solution, not a numeric one.
If there is a clean way to have multiple instances of MatLab running, especially if you have a decently core-rich cpu that MatLab does not fully utilize, then get several of them going. If you are at an educational institution you might try running several different versions (2010a, 2010b, 2009a,...) on the same system. I (fuzzily) recall they didn't collide when I did it. Running more than about 8 started slowing things down more than it improved them. Make sure they aren't colliding on file access if you are using files to share control.
You could write your program in LabVIEW (not MathScript, not MatLab) and because it is a compiled language, there are times that code can run 1000x faster.
You could go all numeric and make it a matrix activity. This depends on your code, but if you could randomly populate the columns in the matrix then matrix multiply it to a matrix $ \left[ 1, x, x^{2}, ...\right] $, that would likely be several hundreds or thousands of times faster than your current level of equation handling and still in MatLab.
About your coding:
don't redeclare "x" as a symbol every loop, that is expensive.
what is this "map2mat" then "addPar" stuff?
the string handling functions are horrible for runtime. Stick to one language. The symbolic toolbox IS maple, and you don't have to get goofy hand-made parsing to make it work with the rest of MatLab.
I have a Matlab project in which I need to make a GUI that receives two mathematical functions from the user. I then need to find their intersection point, and then plot the two functions.
So, I have several questions:
Do you know of any algorithm I can use to find the intersection point? Of course I prefer one to which I can already find a Matlab code for in the internet. Also, I prefer it wouldn't be the Newton-Raphson method.
I should point out I'm not allowed to use built in Matlab functions.
I'm having trouble plotting the functions. What I basically did is this:
fun_f = get(handles.Function_f,'string');
fun_g = get(handles.Function_g,'string');
cla % To clear axes when plotting new functions
ezplot(fun_f);
hold on
ezplot(fun_g);
axis ([-20 20 -10 10]);
The problem is that sometimes, the axes limits do not allow me to see the other function. This will happen, if, for example, I will have one function as log10(x) and the other as y=1, the y=1 will not be shown.
I have already tried using all the axis commands but to no avail. If I set the limits myself, the functions only exist in certain limits. I have no idea why.
3 . How do I display numbers in a static text? Or better yet, string with numbers?
I want to display something like x0 = [root1]; x1 = [root2]. The only solution I found was turning the roots I found into strings but I prefer not to.
As for the equation solver, this is the code I have so far. I know it is very amateurish but it seemed like the most "intuitive" way. Also keep in mind it is very very not finished (for example, it will show me only two solutions, I'm not so sure how to display multiple roots in one static text as they are strings, hence question #3).
function [Sol] = SolveEquation(handles)
fun_f = get(handles.Function_f,'string');
fun_g = get(handles.Function_g,'string');
f = inline(fun_f);
g = inline(fun_g);
i = 1;
Sol = 0;
for x = -10:0.1:10;
if (g(x) - f(x)) >= 0 && (g(x) - f(x)) < 0.01
Sol(i) = x;
i = i + 1;
end
end
solution1 = num2str(Sol(1));
solution2 = num2str(Sol(2));
set(handles.roots1,'string',solution1);
set(handles.roots2,'string',solution2);
The if condition is because the subtraction will never give me an absolute zero, and this seems to somewhat solve it, though it's really not perfect, sometimes it will give me more than two very similar solutions (e.g 1.9 and 2).
The range of x is arbitrary, chosen by me.
I know this is a long question, so I really appreciate your patience.
Thank you very much in advance!
Question 1
I think this is a more robust method for finding the roots given data at discrete points. Looking for when the difference between the functions changes sign, which corresponds to them crossing over.
S=sign(g(x)-f(x));
h=find(diff(S)~=0)
Sol=x(h);
If you can evaluate the function wherever you want there are more methods you can use, but it depends on the size of the domain and the accuracy you want as to what is best. For example, if you don't need a great deal of accurac, your f and g functions are simple to calculate, and you can't or don't want to use derivatives, you can get a more accurate root using the same idea as the first code snippet, but do it iteratively:
G=inline('sin(x)');
F=inline('1');
g=vectorize(G);
f=vectorize(F);
tol=1e-9;
tic()
x = -2*pi:.001:pi;
S=sign(g(x)-f(x));
h=find(diff(S)~=0); % Find where two lines cross over
Sol=zeros(size(h));
Err=zeros(size(h));
if ~isempty(h) % There are some cross-over points
for i=1:length(h) % For each point, improve the approximation
xN=x(h(i):h(i)+1);
err=1;
while(abs(err)>tol) % Iteratively improve aproximation
S=sign(g(xN)-f(xN));
hF=find(diff(S)~=0);
xN=xN(hF:hF+1);
[~,I]=min(abs(f(xN)-g(xN)));
xG=xN(I);
err=f(xG)-g(xG);
xN=linspace(xN(1),xN(2),15);
end
Sol(i)=xG;
Err(i)=f(xG)-g(xG);
end
else % No crossover points - lines could meet at tangents
[h,I]=findpeaks(-abs(g(x)-f(x)));
Sol=x(I(abs(f(x(I))-g(x(I)))<1e-5));
Err=f(Sol)-g(Sol)
end
% We also have to check each endpoint
if abs(f(x(end))-g(x(end)))<tol && abs(Sol(end)-x(end))>1e-12
Sol=[Sol x(end)];
Err=[Err g(x(end))-f(x(end))];
end
if abs(f(x(1))-g(x(1)))<tol && abs(Sol(1)-x(1))>1e-12
Sol=[x(1) Sol];
Err=[g(x(1))-f(x(1)) Err];
end
toc()
Sol
Err
This will "zoom" in to the region around each suspected root, and iteratively improve the accuracy. You can tweak the parameters to see whether they give better behaviour (the tolerance tol, the 15, number of new points to generate, could be higher probably).
Question 2
You would probably be best off avoiding ezplot, and using plot, which gives you greater control. You can vectorise inline functions so that you can evaluate them like anonymous functions, as I did in the previous code snippet, using
f=inline('x^2')
F=vectorize(f)
F(1:5)
and this should make plotting much easier:
plot(x,f(x),'b',Sol,f(Sol),'ro',x,g(x),'k',Sol,G(Sol),'ro')
Question 3
I'm not sure why you don't want to display your roots as strings, what's wrong with this:
text(xPos,yPos,['x0=' num2str(Sol(1))]);