Maple 2024 Questions and Posts

These are Posts and Questions associated with the product, Maple 2024

This second order (Euler type) ode has no solution for the given two initial conditions. but Maple gives solution with one unresolved constant of integration.

ode:=x^2*diff(y(x),x$2)-2*y(x)=0;
ic:=y(0)=4,D(y)(0)=-1;

sol_no_IC:=dsolve(ode)

The IC's are given at x=0 as a trick to see what Maple will do. We see that at x=0 there is division by zero. So no solution exist for these IC's. But see what happens

sol_with_IC:=dsolve([ode,ic])

It seems Maple simply threw away the part of the solution it could not handle due to the x=0 and just returned the rest.

odetest(sol_with_IC,[ode,ic])

The correct answer should have been the NULL solution (i.e. no solution). 

What Am I missing here? Why does Maple do this? Should Maple have returned such a solution?

Maple 2024 on windows 10.

update:

Reported to Maplesoft support.

update:

Here is another example ode. This is first order ode. Maple gives a solution that does not satisfy the initial condition also. I wish I can understand how Maple comes up with these solutions since when I solve these by hand I see it is not possible to satisfy the IC, hence no solution exist.

14876

interface(version);

`Standard Worksheet Interface, Maple 2024.0, Windows 10, March 01 2024 Build ID 1794891`

Physics:-Version();

`The "Physics Updates" version in the MapleCloud is 1722 and is the same as the version installed in this computer, created 2024, April 12, 17:58 hours Pacific Time.`

restart;

14876

ode:=diff(y(x),x)+y(x)/x=x^2;
ic:=y(0)=a;

diff(y(x), x)+y(x)/x = x^2

y(0) = a

dsolve(ode)

y(x) = ((1/4)*x^4+c__1)/x

sol:=dsolve([ode,ic])

y(x) = (1/4)*x^3

odetest(sol,[ode,ic])

[0, a]

Student:-ODEs:-ODESteps([ode,ic])

Error, (in Student:-ODEs:-applyICO1) numeric exception: division by zero

 

 

Download another_strange_solution_ode_maple_2024.mw

I have a simple tank design worksheet that calculates dimensions of a tank that I need to build to hold a given amount of liquid.  My question is this - when I include a "with(Units);" statement, the volume function gets rendered in operator prefix notation.  Why is this?  Is there a setting to prevent this from happening?  Thanks.

Without "with(Units);"...

With "with(Units);"...

I've included a worksheet that shows the function both with and without the inclusion of "with(Units);".

Tank_Design_Calculation_-_Units_Question_(v00).mw

I have two expressions, wo_theta and with_theta, which depend on multiple variables.

I would need your help to:

  1. Verify, as formally as possible, that wo_theta > with_theta always, i.e., for any value of theta different from zero (and regardless of the values taken up by the other variables)
  2. Show the above in a way that is easy and immediate to interpret (perhaps using some type of plot?)

In other words, I want to verify that as soon as I introduce any theta in my expression such expression becomes smaller:

restart;

local gamma;

gamma

(1)

assume(0 < gamma, 0 < nu__02, 0 < nu__01, 0 <= sigma__v, delta__1::real, delta__2::real, delta__3::real, theta::real);
interface(showassumed=0);

1

(2)

wo_theta := X__3*(-X__3*lambda__3 - delta__3*lambda__3 + DEV) + X__2*(-X__2*lambda__2 - delta__2*lambda__2 - nu__02) + X__1*(-X__1*lambda__1 - delta__1*lambda__1 - nu__01) + X__2*(nu__02 + DEV/2) + X__1*(nu__01 + DEV/2) - gamma*X__2^2*sigma__v^2/4 - gamma*X__1^2*sigma__v^2/4 + gamma*X__2*X__1*sigma__v^2/2;

X__3*(-X__3*lambda__3-delta__3*lambda__3+DEV)+X__2*(-X__2*lambda__2-delta__2*lambda__2-nu__02)+X__1*(-X__1*lambda__1-delta__1*lambda__1-nu__01)+X__2*(nu__02+(1/2)*DEV)+X__1*(nu__01+(1/2)*DEV)-(1/4)*gamma*X__2^2*sigma__v^2-(1/4)*gamma*X__1^2*sigma__v^2+(1/2)*gamma*X__2*X__1*sigma__v^2

(3)

with_theta := X__3*(-X__3*lambda__3 - theta*lambda__3 - delta__3*lambda__3 + DEV) + X__2*(-X__2*lambda__2 + theta*lambda__2 - delta__2*lambda__2 - nu__02) + X__1*(-X__1*lambda__1 + theta*lambda__1 - delta__1*lambda__1 - nu__01) + X__2*(nu__02 + DEV/2) + X__1*(nu__01 + DEV/2) - gamma*X__2^2*sigma__v^2/4 - gamma*X__1^2*sigma__v^2/4 + gamma*X__2*X__1*sigma__v^2/2 + theta*(lambda__1*(X__1 + delta__1 - theta) + lambda__2*(X__2 + delta__2 - theta) - lambda__3*(X__3 + delta__3 + theta));

X__3*(-X__3*lambda__3-theta*lambda__3-delta__3*lambda__3+DEV)+X__2*(-X__2*lambda__2+theta*lambda__2-delta__2*lambda__2-nu__02)+X__1*(-X__1*lambda__1+theta*lambda__1-delta__1*lambda__1-nu__01)+X__2*(nu__02+(1/2)*DEV)+X__1*(nu__01+(1/2)*DEV)-(1/4)*gamma*X__2^2*sigma__v^2-(1/4)*gamma*X__1^2*sigma__v^2+(1/2)*gamma*X__2*X__1*sigma__v^2+theta*(lambda__1*(X__1+delta__1-theta)+lambda__2*(X__2+delta__2-theta)-lambda__3*(X__3+delta__3+theta))

(4)

collect(with_theta, theta);

(-lambda__1-lambda__2-lambda__3)*theta^2+(-X__3*lambda__3+X__2*lambda__2+X__1*lambda__1+lambda__1*(X__1+delta__1)+lambda__2*(X__2+delta__2)-lambda__3*(X__3+delta__3))*theta+X__3*(-X__3*lambda__3-delta__3*lambda__3+DEV)+X__2*(-X__2*lambda__2-delta__2*lambda__2-nu__02)+X__1*(-X__1*lambda__1-delta__1*lambda__1-nu__01)+X__2*(nu__02+(1/2)*DEV)+X__1*(nu__01+(1/2)*DEV)-(1/4)*gamma*X__2^2*sigma__v^2-(1/4)*gamma*X__1^2*sigma__v^2+(1/2)*gamma*X__2*X__1*sigma__v^2

(5)

solve(wo_theta > with_theta, theta) assuming 0 < gamma, 0 < nu__02, 0 < nu__01, 0 < sigma__v, delta__1::real, delta__2::real, delta__3::real, theta::real;

solve(with_theta < wo_theta, theta);

Warning, solve may be ignoring assumptions on the input variables.

 

Warning, solutions may have been lost

 

difference_term := (-lambda__1 - lambda__2 - lambda__3)*theta^2 + (X__1*lambda__1 + X__2*lambda__2 - X__3*lambda__3 + lambda__1*(X__1 + delta__1) + lambda__2*(X__2 + delta__2) - lambda__3*(X__3 + delta__3))*theta;

(-lambda__1-lambda__2-lambda__3)*theta^2+(-X__3*lambda__3+X__2*lambda__2+X__1*lambda__1+lambda__1*(X__1+delta__1)+lambda__2*(X__2+delta__2)-lambda__3*(X__3+delta__3))*theta

(6)

# I would expect such difference_term in theta to be always < 0, i.e., for any theta different from 0)
# (Note that lambda_1, lambda_2, and lambda_3 are always > 0, while theta, the three X and the three delta can be positive or negative. In other words, it suffices to show that the linear term in theta is always negative...)
solve(difference_term<0);

Warning, solve may be ignoring assumptions on the input variables.

 

{X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1, theta < 0, lambda__1 < 0, lambda__2 < 0, lambda__3 < 0}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, X__2 < (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2, theta < 0, lambda__2 < 0, lambda__3 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < lambda__1, theta < 0, lambda__2 < 0, lambda__3 < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, X__1 < (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1, theta < 0, lambda__1 < 0, lambda__3 < 0}, {X__1 = X__1, X__2 = X__2, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__2 = 0, theta < 0, lambda__3 < 0, -(1/2)*delta__3-(1/2)*theta < X__3}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, 0 < lambda__1, theta < 0, lambda__3 < 0, (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < lambda__2, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1, theta < 0, lambda__1 < 0, lambda__3 < 0}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, 0 < lambda__2, theta < 0, lambda__3 < 0, (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2 < X__2}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < lambda__1, 0 < lambda__2, theta < 0, lambda__3 < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, X__1 < -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1, theta < 0, lambda__1 < 0, lambda__2 < 0}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__3 = 0, X__2 < -(1/2)*delta__2+(1/2)*theta, theta < 0, lambda__2 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, 0 < lambda__1, theta < 0, lambda__2 < 0, -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, lambda__3 = 0, X__1 < -(1/2)*delta__1+(1/2)*theta, theta < 0, lambda__1 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, lambda__3 = 0, 0 < lambda__1, theta < 0, -(1/2)*delta__1+(1/2)*theta < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, 0 < lambda__2, X__1 < -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1, theta < 0, lambda__1 < 0}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__3 = 0, 0 < lambda__2, theta < 0, -(1/2)*delta__2+(1/2)*theta < X__2}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, 0 < lambda__1, 0 < lambda__2, theta < 0, -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < lambda__3, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1, theta < 0, lambda__1 < 0, lambda__2 < 0}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, 0 < lambda__3, X__2 < (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2, theta < 0, lambda__2 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < lambda__1, 0 < lambda__3, theta < 0, lambda__2 < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, 0 < lambda__3, X__1 < (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1, theta < 0, lambda__1 < 0}, {X__1 = X__1, X__2 = X__2, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__2 = 0, 0 < lambda__3, X__3 < -(1/2)*delta__3-(1/2)*theta, theta < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, 0 < lambda__1, 0 < lambda__3, theta < 0, (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < lambda__2, 0 < lambda__3, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1, theta < 0, lambda__1 < 0}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, 0 < lambda__2, 0 < lambda__3, theta < 0, (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2 < X__2}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < lambda__1, 0 < lambda__2, 0 < lambda__3, theta < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, lambda__1 < 0, lambda__2 < 0, lambda__3 < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, 0 < theta, lambda__2 < 0, lambda__3 < 0, (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2 < X__2}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, 0 < lambda__1, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1, lambda__2 < 0, lambda__3 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, 0 < theta, lambda__1 < 0, lambda__3 < 0, (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1 < X__1}, {X__1 = X__1, X__2 = X__2, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__2 = 0, 0 < theta, X__3 < -(1/2)*delta__3-(1/2)*theta, lambda__3 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, 0 < theta, 0 < lambda__1, X__1 < (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1, lambda__3 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, 0 < lambda__2, lambda__1 < 0, lambda__3 < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, 0 < theta, 0 < lambda__2, X__2 < (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2, lambda__3 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, 0 < lambda__1, 0 < lambda__2, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1, lambda__3 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, 0 < theta, lambda__1 < 0, lambda__2 < 0, -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1 < X__1}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__3 = 0, 0 < theta, lambda__2 < 0, -(1/2)*delta__2+(1/2)*theta < X__2}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, 0 < theta, 0 < lambda__1, X__1 < -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1, lambda__2 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, lambda__3 = 0, 0 < theta, lambda__1 < 0, -(1/2)*delta__1+(1/2)*theta < X__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, lambda__3 = 0, 0 < theta, 0 < lambda__1, X__1 < -(1/2)*delta__1+(1/2)*theta}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, 0 < theta, 0 < lambda__2, lambda__1 < 0, -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1 < X__1}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__3 = 0, 0 < theta, 0 < lambda__2, X__2 < -(1/2)*delta__2+(1/2)*theta}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__3 = 0, 0 < theta, 0 < lambda__1, 0 < lambda__2, X__1 < -(1/2)*(2*X__2*lambda__2-lambda__1*theta-lambda__2*theta+delta__1*lambda__1+delta__2*lambda__2)/lambda__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, 0 < lambda__3, lambda__1 < 0, lambda__2 < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, 0 < theta, 0 < lambda__3, lambda__2 < 0, (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2 < X__2}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, 0 < lambda__1, 0 < lambda__3, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1, lambda__2 < 0}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, 0 < theta, 0 < lambda__3, lambda__1 < 0, (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1 < X__1}, {X__1 = X__1, X__2 = X__2, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, lambda__2 = 0, 0 < theta, 0 < lambda__3, -(1/2)*delta__3-(1/2)*theta < X__3}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__2 = 0, 0 < theta, 0 < lambda__1, 0 < lambda__3, X__1 < (1/2)*(2*X__3*lambda__3+lambda__1*theta+lambda__3*theta-delta__1*lambda__1+delta__3*lambda__3)/lambda__1}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, 0 < lambda__2, 0 < lambda__3, lambda__1 < 0, -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1 < X__1}, {X__1 = X__1, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, lambda__1 = 0, 0 < theta, 0 < lambda__2, 0 < lambda__3, X__2 < (1/2)*(2*X__3*lambda__3+lambda__2*theta+lambda__3*theta-delta__2*lambda__2+delta__3*lambda__3)/lambda__2}, {X__2 = X__2, X__3 = X__3, delta__1 = delta__1, delta__2 = delta__2, delta__3 = delta__3, 0 < theta, 0 < lambda__1, 0 < lambda__2, 0 < lambda__3, X__1 < -(1/2)*(2*X__2*lambda__2-2*X__3*lambda__3-lambda__1*theta-lambda__2*theta-lambda__3*theta+delta__1*lambda__1+delta__2*lambda__2-delta__3*lambda__3)/lambda__1}

(7)
 

NULL

Download inequality.mw

I have a problem with the order  of the Eigenvalues and Vectors flipping. It is a bit random. I only found it trying to understand why a procedure sometimes rotated a conic one way and  then the other. This a really causing a quite a problem, I have only tried this in Maple 2024 so far. I have included screen shots to prove the effect.

restart

 

with(LinearAlgebra):

 

M:=Matrix([[0,1],[1,0]]);

a,b:=Eigenvectors(M)  ;#click here and press enter again possible a 4 times, output can filp

 

Matrix(2, 2, {(1, 1) = 0, (1, 2) = 1, (2, 1) = 1, (2, 2) = 0})

 

Vector[column](%id = 36893491125752073860), Matrix(%id = 36893491125752073980)

(1)

a

Vector(2, {(1) = 1, (2) = -1})

(2)

b

Matrix(2, 2, {(1, 1) = 1, (1, 2) = -1, (2, 1) = 1, (2, 2) = 1})

(3)

 

 

Download 2024-03-21_Q_Eigenvector_output_flipping.mw

I do not know if this caused by same crash in Reproducible--Server-Crash-Kernel-Connection-Has-Been-Lost  or not.

Could someone be able to find out? It happens each time the code is run on windows 10. 

 

26028

interface(version);

`Standard Worksheet Interface, Maple 2024.0, Windows 10, March 01 2024 Build ID 1794891`

Physics:-Version();

`The "Physics Updates" version in the MapleCloud is 1715 and is the same as the version installed in this computer, created 2024, April 3, 20:27 hours Pacific Time.`

restart;

10168

u:=Int(2/3/alpha^(3/2)*sin(1/2*3^(1/2)*ln(alpha))*sin(alpha)*3^(1/2),alpha = 0 .. x)

Int((2/3)*sin((1/2)*3^(1/2)*ln(alpha))*sin(alpha)*3^(1/2)/alpha^(3/2), alpha = 0 .. x)

value(u);


Download another_server_crash_on_int_maple_2024_april_4_2024.mw

ps. reported to Maplesoft.

The above is new crash in Maple 2024. Below shows no crash in Maple 2023:

26028

interface(version);

`Standard Worksheet Interface, Maple 2023.2, Windows 10, November 24 2023 Build ID 1762575`

Physics:-Version();

`The "Physics Updates" version in the MapleCloud is 1715. The version installed in this computer is 1672 created 2024, February 7, 18:34 hours Pacific Time, found in the directory C:\Users\Owner\maple\toolbox\2023\Physics Updates\lib\`

restart;

23104

u:=Int(2/3/alpha^(3/2)*sin(1/2*3^(1/2)*ln(alpha))*sin(alpha)*3^(1/2),alpha = 0 .. x)

Int((2/3)*sin((1/2)*3^(1/2)*ln(alpha))*sin(alpha)*3^(1/2)/alpha^(3/2), alpha = 0 .. x)

value(u);

int((2/3)*sin((1/2)*3^(1/2)*ln(alpha))*sin(alpha)*3^(1/2)/alpha^(3/2), alpha = 0 .. x)

 

 

Download int_on_maple_2023.mw

Update:

Here is a movie showing the crash. It also happens from the command line. All on windows 10.

My ini file has  nothing in it, other than one command which prints the process ID which I had there for over a year now.  This is after restarting Maple fresh and nothing else running other than this one worksheet.

 

Here is movie showing the crash from command line also. On windows 10 pro.

 

 

I just discoverd today the step solutions for series in Student package 

Now i try to solve this with my own steps here ..

Note: SummationSteps(Sum(1/n^2, n = 1 .. infinity))was not capable to get a closed form?

"maple.ini in users"

(1)

NULL

Euler's Basel Problem
In the Student Basics package, there is a command :

 

SummationSteps

generate steps for evaluating summations

NULL

help("SummationSteps")

The SummationSteps command accepts an expression that is expected to contain summations and displays the steps required to evaluate each summation given.

2024

with(Student[Basics])

 

" restart; with(Student[Basics])"

"maple.ini in users"

 

[CompleteSquareSteps, CurveSketchSteps, ExpandSteps, FactorSteps, FractionSteps, GCDSteps, LCMSteps, LinearSolveSteps, LongDivision, ModuloSteps, OutputStepsRecord, PartialFractionSteps, PowerSteps, PracticeSheet, SimplifySteps, SolveSteps, SummationSteps, TrigSteps]

(2)

Try this out this SummationStepscommand for the Basel problem series  ( p-series example)

SummationSteps(Sum(1/n, n = 1 .. infinity))

"[[,,[]],["&bullet;",,"Apply the P-test on" (1)/(n)", which shows the summation diverges if" p<=1 "for" (&sum;)1/((n)^p)],[,,p=1],["&bullet;",,"Since" 0<1 "and" 1<=1", we get that the summation diverges"],[,,([[(&sum;)(1)/(n)" diverges"]])],["&bullet;",,"We know the summation diverges, so now we should find what it diverges to"],[,,[]],["&bullet;",,"Evaluate sum" (&sum;)1/n],[,,infinity]]"

(3)

Now the Basel Problem from Euler

SummationSteps(Sum(1/n^2, n = 1 .. infinity))

"[[,,[]],["&bullet;",,"Apply the P-test on" (n)^(-2)", which shows the summation diverges if" p<=1 "for" (&sum;)1/((n)^p)],[,,p=2],["&bullet;",,"Since" 1<2", we get that the summation converges"],[,,([[(&sum;)(n)^(-2)" converges"]])]]"

(4)

f := sum(1/n^2, n = 1 .. infinity)

(1/6)*Pi^2

(5)

How do we get this value from Euler ( The Basel Problem)

# Step 1: Define the series f
f := sum(1/n^2, n = 1 .. infinity);

# Step 2: Write the series as a product of terms (1 - 1/p)
g := convert(product(1 - 1/p, p = primes), hypergeom);

# Step 3: Compare with the Taylor series of the sine function
h := series(sin(x), x = 0, 10);

# Step 4: Set up equations between corresponding terms
eq := seq(coeff(h, x, 2*k)/k!, k = 1 .. 5) =
      seq(coeff(g, x, k), k = 1 .. 5);

# Step 5: Solve the equations to find the value of the series
sol := solve({eq, seq(coeff(g, x, k) = 0, k = 6 .. 10)});

# Step 6: Replace x with pi/2 to find the value
sol_pi := subs(x = Pi/2, sol);

# Step 7: Compute the value of the series
value := sol_pi[1][2];

value;

(1/6)*Pi^2

 

1-1/primes

 

series(x-(1/6)*x^3+(1/120)*x^5-(1/5040)*x^7+(1/362880)*x^9+O(x^11),x,11)

 

(0, 0, 0, 0, 0) = (0, 0, 0, 0, 0)

 

Error, invalid input: solve expects its 1st argument, eqs, to be of type {`and`, `not`, `or`, rtable, algebraic, relation(algebraic), relation({rtable, algebraic}), {list, set}({`and`, `not`, `or`, algebraic, relation(algebraic)})}, but received {0 = 0, (0, 0, 0, 0, 0) = (0, 0, 0, 0, 0)}

 

sol

 

Error, attempting to assign to `value` which is protected.  Try declaring `local value`; see ?protect for details.

 

value

(6)

NULL

Download Het_Basel_Probleem_van_Euler.mw

@ecterrab

Fetching package "Physics Updates" from MapleCloud...

ID: 5137472255164416
Version: 1713
URL: https://maple.cloud

An error occurred, the package was not installed:
Could not open workbook: /tmp/cloudDownload3108059082303936092/Physics Updates_1712064079729.maple

 

Same problem on Maple 2024 for Windows and Linux!!!

The following is a simple example of what I would like to do: 

M := Array(1 .. 10, 1 .. 2);

for i to 10 do
    M[i, 1] := i;
    M[i, 2] := 3*i;
end do;

Mt := Interpolation:-LinearInterpolation(M);
E := t -> Mt(t);
diffeq := D(C)(t) = E(t);
dsolve({diffeq, C(0) = 0}, {C(t)}, numeric);
Error, (in dsolve/numeric/process_input) unknown Interpolation:-LinearInterpolation([Vector(10, [1.,2.,3.,4.,5.,6.,7.,8.,9.,10.], datatype = float[8], attributes = [source_rtable = (Vector(10, [1.,2.,3.,4.,5.,6.,7.,8.,9.,10.], datatype = float[8], attributes = [source_rtable = (Array(1..10, 1..2, [[1.,3.],[2.,6.],[3.,9.],[4.,12.],[5.,15.],[6.,18.],[7.,21.],[8.,24.],[9.,27.],[10.,30.]], datatype = float[8]))]))])],Vector(10, [3.,6.,9.,12.,15.,18.,21.,24.,27.,30.], datatype = float[8], attributes = [source_rtable = (Array(1..10, 1..2, [[1.,3.],[2.,6.],[3.,9.],[4.,12.],[5.,15.],[6.,18.],[7.,21.],[8.,24.],[9.,27.],[10.,30.]], datatype = float[8]))]),uniform = true,verify = false) present in ODE system is not a specified dependent variable or evaluatable procedure

Hello,

I would like to generate a ColumnGraph such that the bars are centered over 1, 2, and 3. For example, I have a vector:

x:= Vector([1,2,3]);

When you execute ColumnGraph(x), you a get the first bar centered over 0.375, instead of 1, second bar centered over 1.375, instead of 2, and so on.

Thanks for your help.

I have seen this quite a bit in blocks of code. The `>` symbol seems to appear erratically. I don't know how to specifically reproduce this. Does it mean something? I would post the worksheet but it will not run without the package.

Hello

I have the following procedure that uses the Lie Derivatives of a vector field to build a set of equations.

LieDerList:=proc(h::symbol,f::list,vars::list)
description "This function returns the system of equations based on the Lie derivative.":
local i,n:=numelems(vars),L:=Array(0..n):
L[0]:=h:
for i from 1 to n do
    L[i]:=inner(f,map((a,b) -> diff(b,a),vars,L[i-1])):
end do:
return(zip((w,v)->simplify(w-v),[seq(L)],[seq](cat(h,i),i=0..n))):
end proc:

Below it is an example on how to call the procedure.

I used CodeTools:-ThreadSafetyCheck to check all the procedures used within LieDerList and LieDerList itself, but nothing wrong came out. However when I try to run 

LieEq4:=Threads:-Map(w->LieDerList(x,w,[x,y,z]),models4):

where models4 is a list of 1765 elements, maple returns "Error, (in factors) attempting to assign to `LinearAlgebra:-Modular:-Create` which is protected". If I change Threads to Grid, there is no problem at all.  

What am I overlooking? Is there a method to ensure the procedure is thread-safe?

Many thanks.   

PS.  I found one problem - inner, which is related to LinearAlgebra package, is not thread-safe.  

This is not new in Maple 2024, and also happens in Maple 2023. But it causes the famous "kernel connection has been lost" each time. 

I think many of the kernel connection has been lost problems I see might be related. It could be memory problem in this case. I wonder if someone will be able to track what causes it. Is it expected that server.exe crash on such input?

ps. Reported to Maplesoft support.

 


 

36292

interface(version);

`Standard Worksheet Interface, Maple 2024.0, Windows 10, March 01 2024 Build ID 1794891`

Physics:-Version();

`The "Physics Updates" version in the MapleCloud is 1708 and is the same as the version installed in this computer, created 2024, March 27, 16:20 hours Pacific Time.`

restart;

238376

integrand:=(2*x^2022+1)/(x^2023+x);

(2*x^2022+1)/(x^2023+x)

int(integrand,x);


 

Download reproducible_server_crash_test.mw

 

For reference, another software give this result instantly and with no crash:

My PC is windows 10, with 128 GB RAM.

 

May be someone could find what causes this new internal error in Maple 2024. 

I did report it already to Maplesoft. It does not happen in Maple 2023. Attached both worksheets.

interface(version);

`Standard Worksheet Interface, Maple 2024.0, Windows 10, March 01 2024 Build ID 1794891`

Physics:-Version();

`The "Physics Updates" version in the MapleCloud is 1708 and is the same as the version installed in this computer, created 2024, March 27, 16:20 hours Pacific Time.`

integrand:=(d*x)^m/(a+b*arctanh(c*x^n))^2;

(d*x)^m/(a+b*arctanh(c*x^n))^2

int(integrand,x);

Error, (in int/gparse/gmon) too many levels of recursion

 

 

Download int_gparse_gmon_error_maple_2024_march_27_2024.mw
 

130032

interface(version);

`Standard Worksheet Interface, Maple 2023.2, Windows 10, November 24 2023 Build ID 1762575`

integrand:=(d*x)^m/(a+b*arctanh(c*x^n))^2;

(d*x)^m/(a+b*arctanh(c*x^n))^2

int(integrand,x);

2*x*(c*exp(n*ln(x))-1)*(c*exp(n*ln(x))+1)*exp(m*(ln(d)+ln(x)-((1/2)*I)*Pi*csgn(I*d*x)*(-csgn(I*d*x)+csgn(I*d))*(-csgn(I*d*x)+csgn(I*x))))/(b*c*n*exp(n*ln(x))*(-b*ln(1-c*exp(n*ln(x)))+b*ln(c*exp(n*ln(x))+1)+2*a))+int(-2*exp(m*(ln(d)+ln(x)-((1/2)*I)*Pi*csgn(I*d*x)*(-csgn(I*d*x)+csgn(I*d))*(-csgn(I*d*x)+csgn(I*x))))*(c^2*m*(exp(n*ln(x)))^2+c^2*n*(exp(n*ln(x)))^2+(exp(n*ln(x)))^2*c^2-m+n-1)/(b*c*n*exp(n*ln(x))*(-b*ln(1-c*exp(n*ln(x)))+b*ln(c*exp(n*ln(x))+1)+2*a)), x)

 

 

Download int_gparse_gmon_NO_error_maple_2023.mw

I setup my package to display the a message when it is loaded. It is quiet convienent but I don't need it all the time. Obviously I can "#" in the code to hide it premanently. I was wondering if there is away to optionally turn it off/on. Something along the lines.

with(RationalTrigonometry,false) or with(RationalTrigonometry)[false]....

Or put something in the .ini flie to set the default behaviour.

restart:with(RationalTrigonometry):
 "Default global settings:-

     GeomClr = "Blue",

      Prntmsg = true,

       Prjpsn = 3 can be set to 1,

      Normalgpt = 1 or set to 0, 

    Metric is a 3 x3 symmetric matrix defaults to the Identity 

    matrix "


 

Suppose I have, a row vector  R = [R1 , R2  , R] and a column vector C =  [C1 , C2  , C]. I need a multiplication like as follows

RC = [ R1 [C], R2[C], R3 [C]  ], so that RC will be a 3/3 matrix. 

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