I'm writing a user-defined function to convert integers to binary. The largest number that could be converted with the function should be a binary number with
16 1 s. If a larger number is entered as d, the function should display an error
message. With my code, I'm trying to add the numbers 0 or 1 to my vector x based on the remainder, then I want to reverse my final vector to display a number in binary. Here's what I have:
function [b] = bina(d)
% Bina is a function that converts integers to binary
x = [];
y = 2;
in = d/2;
if d >=(2^16 -1)
fprintf('This number is too big')
else
while in > 1
if in >= 1
r = rem(in,y);
x = [x r]
end
end
end
end
As you insist on a loop:
x = [];
y = 2;
in = d;
if d >=(2^16 -1)
fprintf('This number is too big')
else
ii = 1;
while in > 0
r = logical(rem(in,y^ii));
x = [r x];
in = in - r*2^(ii-1);
ii = ii+1;
end
end
b = x;
You had the right ideas, but you need to update the variables in your while-loop with every iteration. This is mainly in, where you need to subtract the remainder. And just store the binary remainders in your variable x.
You can check your result with
x = double( dec2bin(d, 16) ) - 48
You could also use a for loop, by pre-calculating the number of iterations with
find( d < 2.^(1:16),1)
and then
if d >=(2^16 -1)
fprintf('This number is too big')
else
for ii = 1:find( d < 2.^(1:16),1)
r = logical(rem(in,y^ii));
x = [r x];
in = in - r*2^(ii-1)
end
end
Related
I have created a user-defined function in which the inputs are j =indices, new_loc = a 51x2 matrix of cell locations, and the size of my first col of the 51x2 matrix = 51.
function [x,y,w,z] = check_location(j,new_loc,size)
disp(j);
a = j / size + 1; %Finds 1st element of compared array
b = mod(j,size); %Finds 1st element of comparing array
int8(a) %Must be whole integer
int8(b) %" "
fprintf('a = %g',a)
if b == 0 %1st element cannot be 0
b = b + 1;
else
;
end
fprintf('b = %g',b)
x = new_loc(a,1); % [x y]
y = new_loc(a,2);
w = new_loc(b,1); % [w z]
z = new_loc(b,2);
I am confused as I have tested my output with a fprintf function, and fprintf('a = %g',a) is showing a decimal number, while a = j / size + 1 is evaluating an integer. Also, I am getting the error: Subscript indices must either be real positive integers or logicals.
for j = 1:numel(D)
if D(j) < 8 & D(j) ~= 0
[x1,y1,x2,y2] = check_location(j,new_location,numel(new_location(:,1)));
% smallest_int = check_intensity(x1,y1,x2,y2,B);
% [row,col] = find(B == smallest_int) %Convert smallest_int vals w/ it's location
% new_location(row,col) = []; %Check new_location w/ smallest_int vals and delete
end
end
Here is the for loop in which I am testing my function.
These lines:
int8(a) %Must be whole integer
int8(b) %" "
both return int8 values, but they're not stored anywhere, so they're lost. You need to assign the integer value back to the original variable.
a = int8(a) %Must be whole integer
b = int8(b) %" "
I'm attempting to create a loop that reads through a matrix (A) and stores the non-zero values into a new matrix (w). I'm not sure what is wrong with my code.
function [d,w] = matrix_check(A)
[nrow ncol] = size(A);
total = 0;
for i = 1:nrow
for j = 1:ncol
if A(i,j) ~= 0
total = total + 1;
end
end
end
d = total;
w = [];
for i = 1:nrow
for j = 1:ncol
if A(i,j) ~= 0
w = [A(i,j);w];
end
end
end
The second loop is not working (at at least it is not printing out the results of w).
You can use nonzeros and nnz:
w = flipud(nonzeros(A)); %// flipud to achieve the same order as in your code
d = nnz(A);
The second loop is working. I'm guessing you're doing:
>> matrix_check(A)
And not:
>> [d, w] = matrix_check(A)
MATLAB will only return the first output unless otherwise specified.
As an aside, you can accomplish your task utilizing MATLAB's logical indexing and take advantage of the (much faster, usually) array operations rather than loops.
d = sum(sum(A ~= 0));
w = A(A ~= 0);
I can't seem to find a fix to my infinite loop. I have coded a Jacobi solver to solve a system of linear equations.
Here is my code:
function [x, i] = Jacobi(A, b, x0, TOL)
[m n] = size(A);
i = 0;
x = [0;0;0];
while (true)
i =1;
for r=1:m
sum = 0;
for c=1:n
if r~=c
sum = sum + A(r,c)*x(c);
else
x(r) = (-sum + b(r))/A(r,c);
end
x(r) = (-sum + b(r))/A(r,c);
xxx end xxx
end
if abs(norm(x) - norm(x0)) < TOL;
break
end
x0 = x;
i = i + 1;
end
When I terminate the code it ends at the line with xxx
The reason why your code isn't working is due to the logic of your if statements inside your for loops. Specifically, you need to accumulate all values for a particular row that don't belong to the diagonal of that row first. Once that's done, you then perform the division. You also need to make sure that you're dividing by the diagonal coefficient of A for that row you're concentrating on, which corresponds to the component of x you're trying to solve for. You also need to remove the i=1 statement at the beginning of your loop. You're resetting i each time.
In other words:
function [x, i] = Jacobi(A, b, x0, TOL)
[m n] = size(A);
i = 0;
x = [0;0;0];
while (true)
for r=1:m
sum = 0;
for c=1:n
if r==c %// NEW
continue;
end
sum = sum + A(r,c)*x(c); %// NEW
end
x(r) = (-sum + b(r))/A(r,r); %// CHANGE
end
if abs(norm(x) - norm(x0)) < TOL;
break
end
x0 = x;
i = i + 1;
end
Example use:
A = [6 1 1; 1 5 3; 0 2 4]
b = [1 2 3].';
[x,i] = Jacobi(A, b, [0;0;0], 1e-10)
x =
0.048780487792648
-0.085365853612062
0.792682926806031
i =
20
This means it took 20 iterations to achieve a solution with tolerance 1e-10. Compare this with MATLAB's built-in inverse:
x2 = A \ b
x2 =
0.048780487804878
-0.085365853658537
0.792682926829268
As you can see, I specified a tolerance of 1e-10, which means we are guaranteed to have 10 decimal places of accuracy. We can certainly see 10 decimal places of accuracy between what Jacobi gives us with what MATLAB gives us built-in.
I'm trying to write my own program to sort vectors in matlab. I know you can use the sort(A) on a vector, but I'm trying to code this on my own. My goal is to also sort it in the fewest amount of swaps which is kept track of by the ctr variable. I find and sort the min and max elements first, and then have a loop that looks at the ii minimum vector value and swaps it accordingly.
This is where I start to run into problems, I'm trying to remove all the ii minimum values from my starting vector but I'm not sure how to use the ~= on a vector. Is there a way do this this with a loop? Thanks!
clc;
a = [8 9 13 3 2 8 74 3 1] %random vector, will be function a once I get this to work
[one, len] = size(a);
[mx, posmx] = max(a);
ctr = 0; %counter set to zero to start
%setting min and max at first and last elements
if a(1,len) ~= mx
b = mx;
c = a(1,len);
a(1,len) = b;
a(1,posmx) = c;
ctr = ctr + 1;
end
[mn, posmn] = min(a);
if a(1,1) ~= mn
b = mn;
c = a(1,1);
a(1,1) = b;
a(1,posmn) = c;
ctr = ctr + 1;
end
ii = 2; %starting at 2 since first element already sorted
mini = [mn];
posmini = [];
while a(1,ii) < mx
[mini(ii), posmini(ii - 1)] = min(a(a~=mini))
if a(1,ii) ~= mini(ii)
b = mini(ii)
c = a(1,ii)
a(1,ii) = b
a(1,ii) = c
ctr = ctr + 1;
end
ii = ii + 1;
end
I'm trying to multiply (element wise) a vector V of length N by a randomly generated number in the range (a,b), while keeping the sum of the vector equal to a total amount, E. I want to do this in MATLAB, but I'm not sure how. Getting random numbers between a certain range I know how to do:
minrand = 0;
maxrand = 1;
randfac = (maxrand-minrand).*rand(1,N) + minrand;
But yeah, beyond that I'm pretty clueless. I guess the random numbers can't really be generated like this, because if we call the random numbers the vector R, then I want that
R_1*V1 + R_2*V2 .... + R_N*V_N = E. So I guess it's a big equation. Is there any way to solve it, while putting constraints on the max and min values of R?
You can pick pairs of two elements (in all combinations) and add and subtract an equal random number.
% Make up a random vector
N=10;
randfac = 10*rand(1,N);
%OP Answer here: Given randfac with sum E re-randomize it
E = sum(randfac);
minrand = 0;
maxrand = 2;
disp(randfac)
% v = [6.4685 2.9652 6.6567 1.6153 7.3581 0.0237 7.1025
% 3.2381 1.9176 1.3561]
disp(sum(randfac))
% E = 38.7019
r = minrand + (maxrand-minrand)*rand(N*N,1);
k = 1;
for i=1:N
for j=1:N
randfac(i) = randfac(i)-r(k);
randfac(j) = randfac(j)+r(k);
k = k + 1;
end
end
disp(randfac)
% v = [5.4905 0.7051 4.7646 1.3479 9.3722 -1.4222 7.9275
% 7.5777 1.7549 1.1836]
disp(sum(randfac))
% E = 38.7019
Just divide the vector with the sum and multiply with the target E.
randfac = (maxrand-minrand).*rand(1,N) + minrand;
randfac = E*randfac/sum(randfac);
as long as the operator is linear, the result is going to retain it's randomness. Below is some sample code:
minrand = 0;
maxrand = 1;
N = 1000; %size
v = (maxrand-minrand).*rand(1,N) + minrand;
E = 100; %Target sum
A = sum(v);
randfac = (E/A)*v;
disp(sum(randfac))
% 100.0000
First of all with random numbers in the interval of [a b] you can't guarantee that you will have the same summation (same E). For example if [a b]=[1 2] of course the E will increase.
Here is an idea, I don't know how random is this!
For even N I randomize V then divide it in two rows and multiply one of them with random numbers in [a b] but the second column will be multiplied to a vector to hold the summation fixed.
N = 10;
V = randi(100,[1 N]);
E = sum(V);
idx = randperm(N);
Vr = V(idx);
[~,ridx] = sort(idx);
Vr = reshape(Vr,[2 N/2]);
a = 1;
b = 3;
r1 = (b - a).*rand(1,N/2) + a;
r2 = (sum(Vr) - r1.*Vr(1,:))./Vr(2,:);
r = reshape([r1;r2],1,[]);
r = r(ridx);
Enew = sum(V.*r);
The example results are,
V = [12 82 25 51 81 51 31 87 6 74];
r = [2.8018 0.7363 1.9281 0.5451 1.9387 -0.4909 1.3076 0.8904 2.9236 0.8440];
with E = 500 as well as Enew.
I'm simply assigning one random number to a pair (It can be considered as half random!).
Okay, I have found a way to somewhat do this, but it is not elegant and there are probably better solutions. Starting with an initial vector e, for which sum(e) = E, I can randomize its values and end up with an e for which sum(e) is in the range [(1-threshold)E,(1+thresholdE)]. It is computationally expensive, and not pretty.
The idea is to first multiply e by random numbers in a certain range. Then, I will check what the sum is. If it is too big, I will decrease the value of the random numbers smaller than half of the range until the sum is no longer too big. If it is too small, I do the converse, and iterate until the sum is within the desired range.
e = somepredefinedvector
minrand = 0;
maxrand = 2;
randfac = (maxrand-minrand).*rand(1,N) + minrand;
e = randfac.*e;
threshold = 0.001;
while sum(e) < (1-threshold)*E || sum(e) > (1+threshold)*E
if sum(e) > (1+threshold)*E
for j = 1:N
if randfac(j) > (maxrand-minrand)/2
e(j) = e(j)/randfac(j);
randfac(j) = ((maxrand-minrand)/2-minrand).*rand(1,1) + minrand;
e(j) = randfac(j)*e(j);
end
if sum(e) > (1-threshold)*E && sum(e) < (1+threshold)*E
break
end
end
elseif sum(e) < (1-threshold)*E
for j = 1:N
if randfac(j) < (maxrand-minrand)/2
e(j) = e(j)/randfac(j);
randfac(j) = (maxrand-(maxrand-minrand)/2).*rand(1,1) + (maxrand-minrand)/2;
e(j) = randfac(j)*e(j);
end
if sum(e) > (1-threshold)*E && sum(e) < (1+threshold)*E
break
end
end
end
end