is it possible to add an integration rule to Maple int? - maple

I'd like Maple to return ln(abs(x)) for int(1/x,x) instead of ln(x).
Is there a way to give a rule using a pattern, for int to use in this case as it is possible to do in Mathematica? i.e. somehow to override int result for a specific result like the above? Or may be there is some global option one can set?
Maple 2018.1

A procedure way:
REALINT2 := proc (f, x) local func, a;
func := int(f, x);
a := selectfun(func, ln);
`assuming`([simplify(eval(func, [seq(a[k] = map(proc (x) options operator, arrow;
abs(x) end proc, a[k]), k = 1 .. nops(a))]))], [x in real]) end proc:
REALINT2(1+1/x, x);
REALINT2(1/sin(x), x);
REALINT2(x/(x^2+1), x);
REALINT2(tan(x), x);
REALINT2((diff(f(x), x))/f(x), x);
REALINT2(1+1/abs(x), x);
`assuming`([REALINT2(1/x, x)], [x < 0])
# x + ln(|x|)
# ln(1 - cos(x)) - ln(|sin(x)|)
# 1 / 2 \
# - ln\x + 1/
# 2
# -ln(|cos(x)|)
# ln(|f(x)|)
# / x - ln(-x) x < 0
# |
# < undefined x = 0
# |
# \ x + ln(x) 0 < x
# ln(-x)

Related

Code Horner’s Method for Polynomial Evaluation

I am trying to code Horner’s Method for Polynomial Evaluation but for some reason its not working for me and I'm not sure where I am getting it wrong.
These are the data I have:
nodes = [-2, -1, 1]
x = 2
c (coefficients) = [-3, 3, -1]
The code I have so far is:
function y = horner(x, nodes, c)
n = length(c);
y = c(1);
for i = 2:n
y = y * ((x - nodes(i - 1)) + c(i));
end
end
I am supposed to end up with a polynomial such as (−1)·(x+2)(x+1)+3·(x+2)−3·1 and if x =2 then I am supposed to get -3. But for some reason I don't know where I am going wrong.
Edit:
So I changed my code. I think it works but I am not sure:
function y = horner(x, nodes, c)
n = length(c);
y = c(n);
for k = n-1:-1:1
y = c(k) + y * (x - nodes((n - k) + 1));
end
end
This works:
function y = horner(x, nodes, c)
n = length(c);
y = 0;
for i = 1:n % We iterate over `c`
tmp = c(i);
for j = 1:i-1 % We iterate over the relevant elements of `nodes`
tmp *= x - nodes(j); % We multiply `c(i) * (x - nodes(1)) * (x -nodes(2)) * (x- nodes(3)) * ... * (x - nodes(i -1))
end
y += tmp; % We added each product to y
end
% Here `y` is as following:
% c(1) + c(2) * (x - nodes(1)) + c(3) * (x - nodes(1)) * (x - nodes(2)) + ... + c(n) * (x - nodes(1)) * ... * (x - nodes(n - 1))
end
(I'm sorry this isn't python but I don't know python)
In the case where we didn't have nodes, horner's method works like this:
p = c[n]
for i=n-1 .. 1
p = x*p + c[i]
for example for a quadratic (with coeffs a,b,c) this is
p = x*(x*a+b)+c
Note that if your language supports fma
fma(x,y,x) = x*y+z
then horner's method can be written
p = c[n]
for i=n-1 .. 1
p = fma( x, p, c[i])
When you do have nodes, the change is simple:
p = c[n]
for i=n-1 .. 1
p = (x-nodes[i])*p + c[i]
Or, using fma
p = c[n]
for i=n-1 .. 1
p = fma( (x-nodes[i]), p, c[i])
For the quadratic above this leads to
p = (x-nodes[1]*((x-nodes[2])*a+b)+c

Translate an equation into a code

Can you help me please translate this equation into a code?
I tried this code but its only the first part
theSum = sum(M(:, y) .* S(:, y) ./ (1 + K(:, y)))
EDIT: sorry, I was having a brainfart. The answer below makes no assumptions on the nature of M, K, etc, which is why I recommended functions like that. But they're clearly matrices. I'll make another answer, I'll leave this here for reference though in case it's useful
I would start by making the M, K, X, L, and O expressions into simple functions, so that you can easily call them as M(z,y), X(z,y) (or X(z,j) depending on the input you need ) etc.
Then you will convert each summation into a for loop and collect the result (you can think about vectorisation later, right now focus on translating the problem). The double summation is essentially a nested for loop, where the result of the inner loop is used in the outer one at each outer iteration.
So your end result should look something like:
Summation1 = 0;
for z = 1 : Z
tmp = M(z,y) / K(z,y) * (X(z,y) / (1 + L(z,y));
Summation1 = Summation1 + tmp;
end
Summation2 = 0;
for j = 1 : Y
if j ~= y
for z = 1 : Z
tmp = (M(z,j) * X(z,j) * O(j)) / (K(z,j)^2 * (1 + L(z,j)) * X(z,y);
Summation2 = Summation2 + tmp;
end
end
end
Result = Summation1 - Summation2;
(Btw, this assumes that all operations are on scalars. If M(z,y) outputs a vector, adjust for elementwise operations appropriately)
IF M, K, etc are all matrices, and all operations are expected to be element-wise, then this is a vectorised approach for this equation.
Left summation is
S1 = M(1:Z,y) ./ K(1:Z,y) .* X(1:Z,y) ./ (1 + L(1:Z,y));
S1 = sum(S1);
Right summation is (assuming (O is a horizontal vector)
S2 = M(1:Z, 1:Y) .* X(1:X, 1:Y) .* repmat(O(1:Y), [Z,1]) ./ ...
(K(1:Z, 1:Y) .^ 2 .* (1 + L(1:Z, 1:Y))) .* X(1:Z, 1:Y);
S2(:,y) = []; % remove the 'y' column from the matrix
S2 = sum(S2(:)); % add all elements
End result: S1 - S2
this is lambda version vectorized:
equation = #(y,M,K,X,L,O) ...
sum(M(:,y)./K(:,y).*X(:,y)./(1+L(:,y))) ...
-sum(sum( ...
bsxfun( ...
#times ...
,M(:,[1:y-1,y+1:end]) ...
.* X(:,[1:y-1,y+1:end]) ...
.* O(:,[1:y-1,y+1:end]) ...
./ (K(:,[1:y-1,y+1:end]) .^ 2 ...
.*(1+ L(:,[1:y-1,y+1:end]))) ...
,X(:,y) ...
) ...
));
%%% example:
y = 3;
Y = 5;
Z = 10;
M = rand(Y, Z);K = rand(Y, Z);X = rand(Y, Z);L = rand(Y, Z);O = rand(Y, Z);
equation(y,M,K,X,L,O)

Trapezodial Rule Matlab

I am completing an assignment for a class. We were to follow a flow chart to find the values for the trap rule code. I believe the problem is with my main code.
I am not sure if there is a problem with my function code or my main code, any help would be appreciated.
when I run the section, it display the function as the answer
The following is my mainscript code:
f = #(x) (4*sin (x)) / (exp(2*x)) ;
trap_haskell(f , 0 , 3 , 7)
The rest is my trapezoidal rule code
function [f] = trap_haskell(f, a, b, n)
x = a ;
h = (b - a) / n ;
s = f (a) ;
for k=1:1:n-1
x = x + h ;
s = s + 2 * f(x) ;
end
s = s + f(b) ;
I = (b - a) * s / (2 * n) ;
end
You're returning f as the output argument of trap_haskell which is the input function into trap_haskell itself. The variable I in your code actually stores the integral so it's simply a matter of changing the output variable of the function definition to return the integral instead:
%// ------ Change here
%// |
%// V
function [I] = trap_haskell(f, a, b, n)

Not enough input arguments error in matlab

This is my matlab code , I got Not enough input argument error in line 2 and i don't know how to fix it. Anyhelp ? Thanks in advance .
function [] = Integr1( F,a,b )
i = ((b - a)/500);
x = a;k = 0; n = 0;
while x <= b
F1 = F(x);
x = x + i;
F2 = F(x);
m = ((F1+F2)*i)/2;
k = k +m;
end
k
x = a; e = 0; o = 0;
while x <= (b - 2*i)
x = x + i;
e = e + F(x);
x = x + i;
o = o + F(x);
end
n = (i/3)*(F(a) + F(b) + 2*o + 4*e)
This code performs integration by the trapezoidal rule. The last line of code gave it away. Please do not just push the Play button in your MATLAB editor. Don't even think about it, and ignore that it's there. Instead, go into your Command Prompt, and you need to define the inputs that go into this function. These inputs are:
F: A function you want to integrate:
a: The starting x point
b: The ending x point
BTW, your function will not do anything once you run it. You probably want to return the integral result, and so you need to modify the first line of your code to this:
function n = Integr1( F,a,b )
The last line of code assigns n to be the area under the curve, and that's what you want to return.
Now, let's define your parameters. A simple example for F is a linear function... something like:
F = #(x) 2*x + 3;
This defines a function y = 2*x + 3. Next define the starting and ending points:
a = 1; b = 4;
I made them 1 and 4 respectively. Now you can call the code:
out = Integr1(F, a, b);
out should contain the integral of y = 2*x + 3 from x = 1 to x = 4.

Combining functions with boundaries in matlab

I have a function like this:
f(x) = { x if 0 < x < n
{ n-x if n < x < 2*n
How to enter this function in MATLAB?
Best way is to put this in a sub-function or nested function, or in a separate m-file:
function y = f(x)
n = 4; %// Or whatever your N is
if x <= 0 || x >= 2*n
y = 0;
elseif x < n
y = x;
else
y = n-x;
end
end
or, more generally, when x is a vector/matrix,
function y = f(x)
y = x;
y(x >= n) = n-x(x >= n);
y(x <= 0 | x >= 2*n) = 0;
end
Alternatively, you can of course pass the n as an argument:
function y = f(x, n)
...
end
Alternatively, you can use this anonymous function:
f = #(x) (x>0 & x<n).*x + (x>=n & x<=2*n).*(n-x);
again, optionally, pass the n:
f = #(x,n) ...