Hi experts,

I want to compute the following formula using Maple but It returns the formula of integration only.

int(sin(x)/(a*b+a^2*sin(x)^2-d^2*cos(x)^2)(c+cos(x)), x = 0 .. x)

Could you please help to give me some suggestion about how to solve it?

Thank a lot.

Hey there,

I'm trying to numerically intergrate a function s(K,i,j) dK using runge kutta over a 2D grid of i,j values. Essentialy, performing the same sort of integral many different times for slightly different combinations of i and j. The function is more or less gaussian, and so the bulk of the result will come from the values of K around the peak of said gaussian. For some combinations of i and j, the function seems to have a singularity on the right edge of the gaussian peak, which causes my script to spit out an error, telling me the calculation cannot be performed further to the right past the singularity. Now, like i said before, the singularity is on the very edge of the gaussian and therefore I am perfectly happy to stop the integration before the singularity, because anything past it wont contribute very much to the result.

How can I use dsolve events to halt my integration just before hitting the singularity?

RK := (i, j) -> dsolve({diff(n(K), K) = K*s(K, a[i], b[j]), n(0) = 0}, numeric, method = rkf45)

Hello,

I have this error I'm not sure how to solve

restart;

`assuming`([simplify(int(ln(1+x)^3/(x+a), x = 0 .. 1))], [a > 0]);

combine(expand((eval(%, a = I)+eval(%, a = -I))*(1/2)))

What is the precise problem here?

Hello guys, I'm a new user of Maple and I'd love some help.

I'm trying to solve a cubic equation with four variables, and plot the imaginary part of 'w' as a function of 'x' for different values of 'y' and 'z'. When I ask for all the equation roots, the result is huge.

I want to know if there's an "easier" way to select each root of the equation and make it a function without having to "select element" and copy/paste, because I've tried this way and it's not working.

I know this is a stupid question, but I could really use some help.

Thanks for your time!

I don't quite understand the behavior of PDEtools[declare].  My reading of the documentation is that PDEtools[declare](y(t)) tells Maple that y is a function of t, and therefore y(t) is displayed as y and the derivative of y is displayed as y_t.  I did not expect other variables to be similarly affected but apparently they are.  For instance, in the worksheet below, why is the derivative of p displayed as p_s?

Download mw.mw

For a very simple sheet:

restart;

with(Statistics);

X := RandomVariable(Uniform(0, 1))

Sample(X, 2)

Maple always show: 0.8147236863931789, 0.9057919370756192 when I click the "execute the entire sheet." on the top.

While, if I only execute Sample(X, 2), then it seems generate random samples.

Why? is this because of the " Pseudo-random algorithm " built in Maple?

I'm trying to execute the linked code but i am having the following error:

Error, (in sombrea2) cannot determine if this expression is true or false: -(1/4)*105^(1/2) <= (1/4)*105^(1/2)
 

The entire procedure is downloadable here: http://www.mediafire.com/file/llcfhydpjy8tken/maple17.mw/file

If someone can help me to find a solution I'll be very thankful.

I was working on a project about optimal strategies for HIV treatment, models used from [Butler, Kirschner, and Lenhart] 1997. This model explains the spread of HIV viruses in the human body, where there is one control function u(t).

My work is following pontryagin maximum principle. But i have a problem solving the differential equation system, where there are 6 differential equations with 6 initial conditions. Everything works normally and I get a numerical solution for the system

restart;
with(linalg);
with(DEtools);
with(plots);

Model declaration

dx[1] := -T*V*k*u+B*T*r-T*m1+A; dx[2] := T*V*k*u-Ti*m2; dx[3] := N*Ti*m2-V*m3; H := A*T-(1-u)^2+add(dx[i]*L[i], i = 1 .. 3); satu := -(diff(H, T)); dua := -(diff(H, Ti)); tiga := -(diff(H, V)); empat := diff(H, L[1]); lima := diff(H, L[2]); enam := diff(H, L[3])

eq1 := diff(L1(t), t) = -A-(-V(t)*k*u(t)+B*r-m1)*L1(t)-u(t)*k*V(t)*L2(t); eq2 := diff(L2(t), t) = -N*m2*L3(t)+m2*L2(t); eq3 := diff(L3(t), t) = T(t)*k*u(t)*L1(t)-T(t)*k*u(t)*L2(t)+m3*L3(t); eq4 := diff(T(t), t) = -T(t)*V(t)*k*u(t)+B*T(t)*r-T(t)*m1+A; eq5 := diff(Ti(t), t) = T(t)*V(t)*k*u(t)-Ti(t)*m2; eq6 := diff(V(t), t) = N*Ti(t)*m2-V(t)*m3

Value for parameter

 u(t):=-1/(2)*L1(t)*k*V(t)*T(t)+1/(2)*L2(t)*k*V(t)*T(t)+1; s:=10;  m1:=0.02;  m2:=0.5;  m3:=4.4;  r:=0.03;  Tm:=1500;  k:=0.000024;  N:=300;    A:=1;  B:=1-(T(t)+Ti(t))/(Tm): 

Numerical Solution with BVP
 

fcns := {L1(t), L2(t), L3(t), T(t), Ti(t), V(t)}; a := dsolve({eq1, eq2, eq3, eq4, eq5, eq6, L1(20) = 0, L2(20) = 0, L3(20) = 0, T(0) = 800, Ti(0) = 0.4e-1, V(0) = 1.5}, fcns, type = numeric, method = bvp[midrich])

The plot

odeplot(a, [[t, u(t)], [t, V(t)]], 0 .. 20, numpoints = 1000)

Output

Blue: V(t)
Red: u(t)
Based on graphs v (t) and u (t) have negative values, whereas in fact v (t) shows many viruses where it is never negative (this is irrational) and u (t) is limited in interval [0,1]. My question are:
How to provide positive assumptions for the system solution?
So v (t), T (t), Ti (t) are never negative?

Hello.

Can you please tell how the guess vector is defined in Newton's method in "fsolve" if not set initial interval for unknowns? Maybe someone knows what "norm of errors", "new norm" and "incr" in "infolevel[fsolve]" are?

Thanks!

In my expresions I have an integer, nx, which actually has values of only +1 and -1 but I do not specify which.

THe results come out as powers of nx, say nx^n, where n is a positive integer.

How do I reduce the expression nx^n,= 1 for n even and nx^n,= nx for n odd?

I have the following system

pendsys := { diff(x(t),t) = a * x(t) + y(t), diff(y(t),t) = -x(t) + a * y(t) }:

with critical point being (0,0). After plotting the phase portrait, I found out that (0,0) is (asymptotically) stable when a<0 and unstable when a>0. Also, (0,0) is a center when a = 0. Also, as initial condition, I have x(0)=0, y(0)=1. I was thinking we have Hopf bifurcation at a = 0. My question is, how do I plot the bifurcation diagram for this system?

tes_A.mwtes_A.mw

Maple 2018.2.1, using Physicsupdates 266.

I undertsand method=Fourier needs boundary conditions to work, but I do not think this error message is right. Compare

restart;
pde := diff(u(r, theta), r, r)+diff(u(r, theta), theta, theta) = 0;
iv := u(2, theta) = 3*sin(2*theta)+1;
pdsolve([pde,iv], u(r,theta), method = Fourier)

With

restart;
pde := diff(u(r, theta), r, r)+diff(u(r, theta), theta, theta) = 0;
pdsolve(pde, u(r,theta), method = Fourier)

Error, (in pdsolve/info) wrong extra arguments: {method = Fourier}
 

pdsolve should return no solution instead. The way it is above, I thought at first I had wrong syntax with the "method = Fourier" settings and I think this error message can be misleading to a user.
 

Why doesn't PlotVector plot the arrows all in one size?  (as seen in the Maple help page here)

Am pondering how to best provide user-configurable options for a few packages I've written. The easiest method is to use global variables, preassign their default values during the package definition (but don't protect them) and save them with the mla used for the package. A user could then assign new values, say in their Maple initialization file or in a worksheet.  For example

  FooDefaultBar := true:
  FooDefaultBaz := false:

That works for a few variables, but is unwieldy if there are many, as the names generally have to be long and verbose to avoid accidental collision. Better may be to use a single record

  FooDefaults := Record('Bar' = true, 'Baz' = false):

To change one or more values, the user could do

   use FooDefaults in
      Bar := false;
   end use:

A drawback of using a global variable or record is that the user can assign any type to the variable, so the using program will have to check it. While one could use a record with typed fields, for example,

  FooDefaults := Record('Bar' :: truefalse = true, 'Baz' :: truefalse := false):

that only has an effect on assignments if kernelopts(assertlevel) is 2, which isn't the default.

A different approach is to use a Maple object to handle configuration variables. The object should be defined separate from the package it is configuring, so that the target package doesn't have to be loaded to customize its configuration. I've created a small object for this, but am not satisfied with its usage. Here is how it is currently used

# Create configuration object for package foo
Configure('fooDefaults', 'Bar' :: truefalse = true, 'Baz' :: truefalse = false):

The Assign method is used to reassign one or more fields

Assign(fooDefaults, 'Bar' = false, 'Baz' = true):

If a value does not match the declared type, an error is raised. Values from the object are available via the index operator:

   fooDefaults['Bar'];

Am not wild about this approach, the assignment seems clunky and would require a user to consult a help page to learn about the existence of the Assign method, though that would probably be necessary, regardless, to learn about the defaults themselves. Any thoughts on improvements? Attached is the current code.

Configure := module()

option object;

local Default # record of values
    , Type    # record of types
    , nomen   # string corresponding to name of assigned object
    , all :: static := {}
    ;

export
    ModuleApply :: static := proc()
        Object(Configure, _passed);
    end proc;

export
    ModuleCopy :: static := proc(self :: Configure
                                 , proto :: Configure
                                 , nm :: name
                                 , defaults :: seq(name :: type = anything)
                                 , $
                                )
    local eq;
        self:-Default := Record(defaults);
        self:-Type    := Record(seq(op([1,1], eq) = op([1,2], eq), eq = [defaults]));
        self:-nomen   := convert(nm,'`local`');
        nm := self;
        protect(nm);
        self:-all := {op(self:-all), self:-nomen};
        nm;
    end proc;

export
    ModulePrint :: static := proc(self :: Configure)
    local default;
        if self:-Default :: 'record' then
            self:-nomen(seq(default = self:-Default[default]
                            , default = exports(self:-Default)
                           ));
        else
            self:-nomen();
        end if;
    end proc;

export
    Assign :: static := proc(self :: Configure
                             , eqs :: seq(name = anything)
                             , $
                            )
    local eq, nm, val;
        # Check eqs
        for eq in [eqs] do
            (nm, val) := op(eq);
            if not assigned(self:-Default[nm]) then
                error "%1 is not a default of %2", nm, self:-nomen;
            elif not val :: self:-Type[nm] then
                error ("%1 must be of type %2, received %3"
                       , nm, self:-Type[nm], val);
            end if;
        end do;
        # Assign defaults
        for eq in [eqs] do
            (nm, val) := op(eq);
            self:-Default[nm] := val;
        end do;
        self;
    end proc;

export
    `?[]` :: static := proc(self :: Configure
                            , indx :: list
                            , val :: list
                           )
    local opt;
        opt := op(indx);
        if not assigned(self:-Default[opt]) then
            error "'%0' is not an assigned field of this Configure object", indx[];
        elif nargs = 2 then
            self:-Default[opt];
        elif not val :: [self:-Type[opt]] then
            error "value for %1 must be of type %2", opt, self:-Type[opt];
        else
            self:-Default[opt] := op(val);
        end if;
    end proc;

export
    ListAll :: static := proc(self :: Configure)
        self:-all;
    end proc;

end module:

Later: Observing that this is just a glorified record with an assurance that the values match their declared types, but with less nice methods to set and get the values, I concluded that what I really want is a record that enforces types regardless the setting of . Maybe created with

   FooDefaults := Record[strict]('Bar' :: truefalse = true, 'Baz :: truefalse = false):

In the meantime, I'll probably just use a record and not worry about whether a user has assigned an invalid value.

Hi

Initially I tried to find pemutations of 1..9, ie [[1,2,3],[4,5,6],[7,8,9]],[[1,2,4],[3,5,6],[7,8,9]],...etc, But maybe not all of them?

I wonder if someone out there can change my code to reflect the following:

1/According to the pdf excerpt, there are a total of 199 unique sums, the smallest sum is 774 and the largest 2556.(From displaying 280 outcomes, the code got the 774).

2/Show which sums have the greatest probability (specifically, 1566, 1575, 1638, 1656, 1674, 1692, 1755, and 1764, each of which can be shown with effort to have a 3/280, or 1.07%, probability – the calculations to determine this probability is a brute-force computation, and requires enumerating all outcomes of the sample space within a computational software package). We then finally reveal the prediction, which of course is correct..(I don't get it)

predict_perfect.mw