Consider:
textscan('5,6,7', '%s', 'Delimiter',','){1}{1:3}
ans = 55
ans = 66
ans = 77
Excellent! Now I want those three answers in different variables, or some structure I can do things with.
So I try:
X = textscan('55,66,77', '%s', 'Delimiter',','){1}{1:3}
X = 55
Only one value.
So I try:
X = [textscan('55,66,77', '%s', 'Delimiter',','){1}{1:3}] '
X = 556677
It's made it into one string.
So I try:
X Y Z = textscan('55,66,77', '%s', 'Delimiter',','){1}{1:3}
^
syntax error
There must be some way to handle multiple answers ... but how?
This question originally was asked mistakely about MATLAB, while it's about Octave.
The answer to the question, as #excaza wrote in the comments is:
[a, b, c] = textscan('5,6,7', '%d%d%d', 'Delimiter', ','){:};
The first answer, that I wrote for MATLAB use is this:
You need to define three separate outputs inside textscan:
a = textscan('5,6,7', '%s%s%s', 'Delimiter', ',');
[b, c, d] = a{:}
b =
'5'
c =
'6'
d =
'7'
If you want the output as numbers and not as text, you can use %d:
a = textscan('5,6,7', '%d%d%d', 'Delimiter', ',');
[b, c, d] = a{:}
b =
5
c =
6
d =
7
Related
Using Octave's symbolic package, I define a symbolic function of t like this:
>> syms a b c d t real;
>> f = poly2sym([a b c], t) + d * exp(t)
f = (sym)
2 t
a⋅t + b⋅t + c + d⋅ℯ
I also have another function with known coefficients:
>> g = poly2sym([2 3 5], t) + 7 * exp(t)
g = (sym)
2 t
2⋅t + 3⋅t + 7⋅ℯ + 5
I would like to solve f == g for the coefficients a, b, c, d such that the equation holds for all values of t. That is, I simply want to equate the coefficients of t^2 in both equations, and the coefficients of exp(t), etc. I am looking for this solution:
a = 2
b = 3
c = 5
d = 7
When I try to solve the equation using solve, this is what I get:
>> solve(f == g, a, b, c, d)
ans = (sym)
t 2 t
-b⋅t - c - d⋅ℯ + 2⋅t + 3⋅t + 7⋅ℯ + 5
───────────────────────────────────────
2
t
It solves for a in terms of b, c, d, t. This is understandable since in essence there is no difference between the variables b, c and t. But I was wondering if there was a method to somehow separate the terms (using their symbolic form w. r. t. the variable t) and solve the resulting system of linear equations on a, b, c, d.
Note: The function I wrote here is a minimal example. What I am really trying to do is to solve a linear ordinary differential equation using the method of undetermined coefficients. For example, I define something like y = a*exp(-t) + b*t*exp(-t), and solve for diff(y, t, t) + diff(y,t) + y == t*exp(-t). But I believe solving the problem with simpler functions will lead me to the right direction.
I have found a terribly slow and dirty method to get the job done. The coefficients have to be linear in a, b, ... though.
The idea is to follow these steps:
Write the equation in f - g form (which equals zero)
Use expand() to separate the terms
Use children() to get the terms in the equation as a symbolic vector
Now that we have the terms in a vector, we can find those that are the same function of t and add their coefficients together. The way I checked this was by checking if the division of two terms had t as a symbolic variable
For each term, find other terms with the same function of t, add all these coefficients together, save the obtained equation in a vector
Pass the vector of created equations to solve()
This code solves the equation I wrote in the note at the end of my question:
pkg load symbolic
syms t a b real;
y = a * exp(-t) + b * t * exp(-t);
lhs = diff(y, t, t) + diff(y, t) + y;
rhs = t * exp(-t);
expr = expand(lhs - rhs);
chd = children(expr);
used = false(size(chd));
equations = [];
for z = 1:length(chd)
if used(z)
continue
endif
coefficients = 0;
for zz = z + 1:length(chd)
if used(zz)
continue
endif
division = chd(zz) / chd(z);
vars = findsymbols(division);
if sum(has(vars, t)) == 0 # division result has no t
used(zz) = true;
coefficients += division;
endif
endfor
coefficients += 1; # for chd(z)
vars = findsymbols(chd(z));
nott = vars(!has(vars, t));
if length(nott)
coefficients *= nott;
endif
equations = [equations, expand(coefficients)];
endfor
solution = solve(equations == 0);
How can I make a function with a vector as input and a matrix as an output?
I have to write a function that will convert cubic meters to liters and English gallons. The input should be a vector containing volume values in m ^ 3 to be converted. The result should be a matrix in which the first column contains the result in m ^ 3, the second liter, the third English gallon.
I tried this:
function [liter, gallon] = function1 (x=[a, b, c, d]);
liter= a-10+d-c;
gallon= b+15+c;
endfunction
You're almost there.
The x=[a,b,c,d] part is superfluous, your argument should be just x.
function [liter, gallon] = function1 (x);
a = x(1); b = x(2); c = x(3); d = x(4);
liter = a - 10 + d - c;
gallon = b + 15 + c;
endfunction
If you want your code to be safe and guard against improper inputs, you can perform such checks manually inside the function, e.g.
assert( nargin < 1 || nargin > 4, "Wrong number of inputs supplied");
The syntax x=[a,b,c,d] does not apply to octave; this is reserved for setting up default arguments, in which case a, b, c, and d should be given specific values that you'd want as the defaults. if you had said something like x = [1,2,3,4], then this would be fine, and it would mean that if you called the function without an argument, it would set x up to this default value.
I am new to Octave, so I am trying to make some simple examples work before moving onto more complex projects.
I am trying to resolve the ODE dy/dx = a*x+b, but without success. Here is the code:
%Funzione retta y = a*x + b. Ingressi: vettore valori t; coefficienti a,b
clear all;
%Inizializza argomenti
b = 1;
a = 1;
x = ones(1,20);
function y = retta(a, x, b) %Definisce funzione
y = ones(1,20);
y = a .* x .+ b;
endfunction
%Calcola retta
x = [-10:10];
a = 2;
b = 2;
r = retta(a, x, b)
c = b;
p1 = (a/2)*x.^2+b.*x+c %Sol. analitica di dy/dx = retta %
plot(x, r, x, p1);
% Risolve eq. differenziale dy/dx = retta %
y0 = b; x0 = 0;
p2 = lsode(#retta, y0, x)
And the output is:
retta3code
r =
-18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22
p1 =
Columns 1 through 18:
82 65 50 37 26 17 10 5 2 1 2 5 10 17 26 37 50 65
Columns 19 through 21:
82 101 122
error: 'b' undefined near line 9 column 16
error: called from:
error: retta at line 9, column 4
error: lsode: evaluation of user-supplied function failed
error: lsode: inconsistent sizes for state and derivative vectors
error: /home/fabio/octave_file/retta3code.m at line 21, column 4
So, the function retta works properly the first time, but it fails when used in lsode.
Why does that happen? What needs to be changed to make the code work?
Somehow you still miss some important parts of the story. To solve an ODE y'=f(y,x) you need to define a function
function ydot = f(y,x)
where ydot has the same dimensions as y, both have to be vectors, even f they are of dimension 1. x is a scalar. For some traditional reason, lsode (a FORTRAN code used in multiple solver packages) prefers the less used order (y,x), in most text books and other solvers you find the order (x,y).
Then to get solution samples ylist over sample points xlist you call
ylist = lsode("f", y0, xlist)
where xlist(1) is the initial time.
The internals of f are independent of the sample list list and what size it has. It is a separate issue that you can use multi-evaluation to compute the exact solution with something like
yexact = solexact(xlist)
To pass parameters, use anonymous functions, like in
function ydot = f(y,x,a,b)
ydot = [ a*x+b ]
end
a_val = ...
b_val = ...
lsode(#(y,x) f(y,x,a_val, b_val), y0, xlist)
The code as modified below works, but I'd prefer to be able to define the parameters a and b out of the function and then pass them to rdot as arguments.
x = [-10,10];
a = 1;
b = 0;
c = b;
p1 = (a/2).*(x.^2)+b.*x+c %Sol. analitica di dy/dx = retta %
function ydot = rdot(ydot, x)
a = 1;
b = 0;
ydot = ones(1,21);
ydot = a.*x .+ b;
endfunction
y0 = p1(1); x0 = 0;
p2 = lsode("rdot", y0, x, x0)'
plot(x, p1, "-k", x, p2, ".r");
I've encountered this code and don't know what its performing :
yk = y == k;
Recreating :
>> a = 1
a = 1
>> b = 2
b = 2
>> c = 3
c = 3
>> a = b == c
a = 0
>>
I think it is a boolean operation. If y == k then yk = 1 else yk = 0 ?
In order to figure out what your statement means, you can refer to Octave's operator precedence. As you can see from that list, assignment (=) has the lowest precedence of any operator (including ==). As a result, the line that you have posted translates to
Perform the relational operation y == k
Assign the result to the variable yk
I wrote this mips code to find the gcf but I am confused on getting the number of instructions executed for this code. I need to find a linear function as a function of number of times the remainder must be calculated before an answer. i tried running this code using Single step with Qtspim but not sure on how to proceed.
gcf:
addiu $sp,$sp,-4 # adjust the stack for an item
sw $ra,0($sp) # save return address
rem $t4,$a0,$a1 # r = a % b
beq $t4,$zero,L1 # if(r==0) go to L1
add $a0,$zero,$a1 # a = b
add $a1,$zero,$t4 # b = r
jr gcf
L1:
add $v0,$zero,$a1 # return b
addiu $sp,$sp,4 # pop 2 items
jr $ra # return to caller
There is absolutely nothing new to show here, the algorithm you just implemented is the Euclidean algorithm and it is well known in the literature1.
I will nonetheless write an informal analysis here as link only questions are evil.
First lets rewrite the code in an high level formulation:
unsigned int gcd(unsigned int a, unsigned int b)
{
if (a % b == 0)
return b;
return gcd(b, a % b);
}
The choice of unsigned int vs int was dicated by the MIPS ISA that makes rem undefined for negative operands.
Out goal is to find a function T(a, b) that gives the number of step the algorithm requires to compute the GDC of a and b.
Since a direct approach leads to nothing, we try by inverting the problem.
What pairs (a, b) makes T(a, b) = 1, in other words what pairs make gcd(a, b) terminates in one step?
We clearly must have that a % b = 0, which means that a must be a multiple of b.
There are actually an (countable) infinite number of pairs, we can limit our selves to pairs with the smallest, a and b2.
To recap, to have T(a, b) = 1 we need a = nb and we pick the pair (a, b) = (1, 1).
Now, given a pair (c, d) that requires N steps, how do we find a new pair (a, b) such that T(a, b) = T(c, d) + 1?
Since gcd(a, b) must take one step further then gcd(c, d) and since starting from gcd(a, b) the next step is gcd(b, a % b) we must have:
c = b => b = c
d = a % b => d = a % c => a = c + d
The step d = a % c => a = c + d comes from the minimality of a, we need the smallest a that when divided by c gives d, so we can take a = c + d since (c + d) % c = c % c d % c = 0 + d = d.
For d % c = d to be true we need that d < c.
Our base pair was (1, 1) which doesn't satisfy this hypothesis, luckily we can take (2, 1) as the base pair (convince your self that T(2, 1) = 1).
Then we have:
gcd(3, 2) = gcd(2, 1) = 1
T(3, 2) = 1 + T(2, 1) = 1 + 1 = 2
gcd(5, 3) = gcd(3, 2) = 1
T(5, 3) = 1 + T(3, 2) = 1 + 2 = 3
gcd(8, 5) = gcd(5, 3) = 1
T(8, 5) = 1 + T(5, 3) = 1 + 3 = 4
...
If we look at the pair (2, 1), (3, 2), (5, 3), (8, 5), ... we see that the n-th pair (starting from 1) is made by the number (Fn+1, Fn).
Where Fn is the n-th Fibonacci number.
We than have:
T(Fn+1, Fn) = n
Regarding Fibonacci number we know that Fn ∝ φn.
We are now going to use all the trickery of asymptotic analysis, particularly in the limit of the big-O notation considering φn or φn + 1 is the same.
Also we won't use the big-O symbol explicitly, we rather assume that each equality is true in the limit. This is an abuse, but makes the analysis more compact.
We can assume without loss of generality that N is an upper bound for both number in the pair and that it is proportional to φn.
We have N ∝ φn that gives logφ N = n, this ca be rewritten as log(N)/log(φ) = n (where logs are in base 10 and log(φ) can be taken to be 1/5).
Thus we finally have 5logN = n or written in reverse order
n = 5 logN
Where n is the number of step taken by gcd(a, b) where 0 < b < a < N.
We can further show that if a = ng and b = mg with n, m coprimes, than T(a, b) = T(n, m) thus the restriction of taking the minimal pairs is not bounding.
1 In the eventuality that you rediscovered such algorithm, I strongly advice against continue with reading this answer. You surely have a sharp mind that would benefit the most from a challenge than from an answer.
2 We'll later see that this won't give rise to a loss of generality.