Maple 2015 Questions and Posts

These are Posts and Questions associated with the product, Maple 2015

I wanted to make a 3d plot with lines linking points, but I am struggling with it
(I couldn't find anything in the plot3d documentation, so it might not be supported, which would be odd as its such a normal thing to want to do)

I have tried with no success:

plot3d([1, 2, 3], [4, 5, 6]);
plot3d(Matrix(2, 3, {(1, 1) = 1, (1, 2) = 2, (1, 3) = 3, (2, 1) = 4, (2, 2) = 5, (2, 3) = 6}))

Any thoughts?

hi, i am trying to get a list of equations using the coeff function. I have the following equation:

restart;
Lambda:=-(1/8)*(D[4](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), x))-(1/8)*(D[6](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), y, x))-(1/8)*(D[7](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), x, t))-(1/8)*(D[5](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), x, x))-(1/8)*(D[12](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), x, t, t))-(1/8)*(D[10](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), x, x, t))-(1/8)*(D[11](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), y, x, t))-(1/8)*(D[9](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), y, x, x))+(1/8*(-3*(D[8](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))-4))*(diff(u(x, y, t), x, x, x))-(1/8)*(D[1](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))+(1/4)*(D[8](a))(x, y, t, u(x, y, t), diff(u(x, y, t), x), diff(u(x, y, t), y), diff(u(x, y, t), t), diff(u(x, y, t), x, x), diff(u(x, y, t), y, x), diff(u(x, y, t), x, t), diff(u(x, y, t), y, t), diff(u(x, y, t), t, t))*(diff(u(x, y, t), x, x, x));

Now I am trying to get the coefficients of the derivatives of u(x,y,t). So by hand I have done the calculation of taking the coeffient of diff(u(x,y,t),x,x,x) and setting this equal to zero, and then the coefficient of diff(u(x,y,t),x,x,t) and so on. However when I use the coeff function, it will only allow me to compute the coeff of diff(u(x,y,t),x,x,x) and others of third order. However it will not let me use the deriviateves of u of second and first order.

coeff(Lambda,diff(u(x,y,t),x));

this will not work but 

coeff(Lambda,diff(u(x,y,t),x,x,x));

will work.

Any help would be great thanks.


 

I have a relatively complicated ODE that i am plotting. One of the variables in particular (B[2211], purple line in the graph) should under go an exponential-like decay to zero, but instead flies off into negative territory  (see graph below) despite having a very simple equation:

problem variable rate of change= -problem variable*constant +linear combination of variables that  are always posotive.

 

My intuition is that this is because i have somehow used the odeplot tool wrong - possibly due to a problem with stepsizes.

Here is a MWE i've made:

aa_problem_MWE.mw

 

Hi everybody,

Please take the example given in the help pages of DocumentTools[Tabulate] (the one where a cardinal sine is plotted)
Change plot(sin(x)/x) by plot(sin(x),/x, legend=sinc(x))

The legend doesn't appear if the list (named "A" in the help page) is displayed through DocumentTools:-tabulate.

Is it possible to circumvent this problem ?

TIA

Hi all,

I don't know why this file doesn't work anymore! It was ok last week. I even reinstall the Maple on my laptop, but it went wrong again...

 

Please help me.

 

Plot_Diff_Temperature.mw

"There were problems during the loading process. Your worksheet may be incomplete."

 

Pls fix this problem for me. I tried various things. The text in the worksheet is in Danish and contains danish letters (æøå) which may have caused the problem.

Maple Worksheet - Error

Failed to load the worksheet /maplenet/convert/1._Opgaver.mw .
 

Download 1._Opgaver.mw

Download 1._Opgaver.mw

 

 

Hi everybody,

I have written a module (let's say MyModule) that  I use as a package in a worksheet (with(MyModule)).

At some point in my worksheet I call the procedure MyProc which is part of MyModule.
I find it not to work as expected. So I modify it within MyModule and generate again the archive which contains this module.

Because my worksheet does a lot of things before the call to MyProc, I would like to test quickly the above modifications.
The idea is to do :
unwith(MyModule):  # packages() no longer exhibits its name
with(MyModule);      # to load the corrected one

Unfortunately, contrary to what happens with a "native" package,  the command unwith(MyModule) is ineffective:

  • once done showstat(MyProc) still displays the content of the procedure, and running  the command MyProc(...) proves that it still "exists" in the worksheet
     
  • forcing a reload of MyModule ( with(MyModule) ) and acanning again MyProc ( showstat(MyProc) ) reveals the code MyProc had when MyModule has been loaded for the first time.

 

Is it possible to "free" a user package through the "unwith" command ?

Hope to read you soon, TIA


PS : to be clearer

A worksheet contains  the definition of N procedures, plus the one of MyModule, and ends with the commands to generate an archive file named MyModule.mla.
MyModule is defined that way

MyModule := module()
option package

export Proc1 := eval(:-Proc1),
           ......
           MyProc := eval(:-MyProc),
           ......
           ProcN := eval(:-ProcN):
end module
 

 


 

restart

with(LinearAlgebra):

with(orthopoly):

with(student):

interface(rtablesize = 100)

10

(1)

alpha := 1; 1; beta := 1; 1; N := 2; 1; M := 2; 1; L := 1; 1; X := 2*x/L-1; 1; T := 2*t/L-1; 1; `ϰ` := 3; 1; epsilon := 4; 1; delta := 2; 1; tau := 5; 1; B := 1; 1; c := 1; 1; sigma := 1

1

 

1

 

2

 

2

 

1

 

2*x-1

 

2*t-1

 

3

 

4

 

2

 

5

 

1

 

1

 

1

(2)

``

u := expand(sum(sum(a[s, k]*P(s, T)*P(k, X), k = 0 .. M), s = 0 .. N));

4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t

(3)

v := expand(sum(sum(b[s, k]*P(s, T)*P(k, X), k = 0 .. M), s = 0 .. N));

4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x

(4)

eq := diff(u, t)-v*(1-v)+c*u*v/(v+u)-`ϰ`*(diff(u, x, x))

-(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)*(1-4*b[1, 1]*t*x-12*b[1, 2]*t*x^2-2*b[0, 1]*x-6*b[0, 2]*x^2+6*b[0, 2]*x-2*b[1, 0]*t+2*b[1, 1]*t+2*b[1, 1]*x-2*b[1, 2]*t+6*b[1, 2]*x^2-6*b[1, 2]*x-6*b[2, 0]*t^2+6*b[2, 0]*t-2*b[2, 1]*x+6*b[2, 1]*t^2-6*b[2, 1]*t-6*b[2, 2]*x^2+6*b[2, 2]*x-6*b[2, 2]*t^2+6*b[2, 2]*t-b[0, 0]+b[0, 1]-b[0, 2]+b[1, 0]-b[1, 1]+b[1, 2]-b[2, 0]+b[2, 1]-b[2, 2]-36*b[2, 2]*t^2*x^2+12*b[1, 2]*t*x-12*b[2, 1]*t^2*x-36*b[2, 2]*t*x+36*b[2, 2]*t*x^2+36*b[2, 2]*t^2*x+12*b[2, 1]*t*x)+(4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t)*(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)/(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x+4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x-12*b[2, 1]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t)+24*a[2, 1]*t*x+72*a[2, 2]*t*x^2-72*a[2, 2]*t*x-36*a[0, 2]+2*a[1, 0]-2*a[1, 1]+38*a[1, 2]-6*a[2, 0]+6*a[2, 1]-42*a[2, 2]+4*a[1, 1]*x-72*a[1, 2]*t+12*a[1, 2]*x^2-12*a[1, 2]*x+12*a[2, 0]*t-12*a[2, 1]*x-12*a[2, 1]*t-36*a[2, 2]*x^2+36*a[2, 2]*x-216*a[2, 2]*t^2+228*a[2, 2]*t

(5)

eq2 := diff(v, t)-epsilon*v*(-(tau+delta*B*v)/(1+B*v)+u/(v+u))-sigma*(diff(v, x, x))

-4*(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)*(-(5+8*b[1, 1]*t*x+24*b[1, 2]*t*x^2+4*b[0, 1]*x+12*b[0, 2]*x^2-12*b[0, 2]*x+4*b[1, 0]*t-4*b[1, 1]*t-4*b[1, 1]*x+4*b[1, 2]*t-12*b[1, 2]*x^2+12*b[1, 2]*x+12*b[2, 0]*t^2-12*b[2, 0]*t+4*b[2, 1]*x-12*b[2, 1]*t^2+12*b[2, 1]*t+12*b[2, 2]*x^2-12*b[2, 2]*x+12*b[2, 2]*t^2-12*b[2, 2]*t+2*b[0, 0]-2*b[0, 1]+2*b[0, 2]-2*b[1, 0]+2*b[1, 1]-2*b[1, 2]+2*b[2, 0]-2*b[2, 1]+2*b[2, 2]+72*b[2, 2]*t^2*x^2-24*b[1, 2]*t*x+24*b[2, 1]*t^2*x+72*b[2, 2]*t*x-72*b[2, 2]*t*x^2-72*b[2, 2]*t^2*x-24*b[2, 1]*t*x)/(1+4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)+(4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t)/(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x+4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x-12*b[2, 1]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t))+4*b[1, 1]*x-24*b[1, 2]*t+12*b[1, 2]*x^2-12*b[1, 2]*x+12*b[2, 0]*t-12*b[2, 1]*x-12*b[2, 1]*t-36*b[2, 2]*x^2+36*b[2, 2]*x-72*b[2, 2]*t^2+84*b[2, 2]*t-12*b[0, 2]+2*b[1, 0]-2*b[1, 1]+14*b[1, 2]-6*b[2, 0]+6*b[2, 1]-18*b[2, 2]-72*b[2, 2]*t*x+72*b[2, 2]*t*x^2+24*b[2, 1]*t*x

(6)

eq3 := subs({x = 0}, diff(u, x))

4*a[1, 1]*t-12*a[1, 2]*t+12*a[2, 1]*t^2-12*a[2, 1]*t-36*a[2, 2]*t^2+36*a[2, 2]*t+2*a[0, 1]-6*a[0, 2]-2*a[1, 1]+6*a[1, 2]+2*a[2, 1]-6*a[2, 2]

(7)

eq4 := subs({x = L}, diff(u, x))

4*a[1, 1]*t+12*a[1, 2]*t+12*a[2, 1]*t^2-12*a[2, 1]*t+36*a[2, 2]*t^2-36*a[2, 2]*t+2*a[0, 1]+6*a[0, 2]-2*a[1, 1]-6*a[1, 2]+2*a[2, 1]+6*a[2, 2]

(8)

eq5 := subs({x = 0}, diff(v, x))

4*b[1, 1]*t+2*b[0, 1]-6*b[0, 2]-2*b[1, 1]+6*b[1, 2]+2*b[2, 1]-6*b[2, 2]-12*b[1, 2]*t+12*b[2, 1]*t^2+36*b[2, 2]*t-36*b[2, 2]*t^2-12*b[2, 1]*t

(9)

eq6 := subs({x = L}, diff(v, x))

4*b[1, 1]*t+12*b[1, 2]*t+2*b[0, 1]+6*b[0, 2]-2*b[1, 1]-6*b[1, 2]+2*b[2, 1]+6*b[2, 2]+36*b[2, 2]*t^2+12*b[2, 1]*t^2-36*b[2, 2]*t-12*b[2, 1]*t

(10)

eq7 := subs({t = 0}, u)

a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x-2*a[1, 1]*x-6*a[1, 2]*x^2+6*a[1, 2]*x+2*a[2, 1]*x+6*a[2, 2]*x^2-6*a[2, 2]*x

(11)

eq8 := subs({t = 0}, v)

2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x-2*b[1, 1]*x-6*b[1, 2]*x^2+6*b[1, 2]*x+2*b[2, 1]*x+6*b[2, 2]*x^2-6*b[2, 2]*x+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]

(12)

eq11 := subs({t = t[j], x = x[i]}, eq)

-(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])*(1-2*b[0, 1]*x[i]-6*b[0, 2]*x[i]^2+6*b[0, 2]*x[i]-2*b[1, 0]*t[j]+2*b[1, 1]*t[j]+2*b[1, 1]*x[i]-2*b[1, 2]*t[j]+6*b[1, 2]*x[i]^2-6*b[1, 2]*x[i]-6*b[2, 0]*t[j]^2+6*b[2, 0]*t[j]-2*b[2, 1]*x[i]+6*b[2, 1]*t[j]^2-6*b[2, 1]*t[j]-6*b[2, 2]*x[i]^2+6*b[2, 2]*x[i]-6*b[2, 2]*t[j]^2+6*b[2, 2]*t[j]-b[0, 0]+b[0, 1]-b[0, 2]+b[1, 0]-b[1, 1]+b[1, 2]-b[2, 0]+b[2, 1]-b[2, 2]-36*b[2, 2]*t[j]*x[i]-36*b[2, 2]*t[j]^2*x[i]^2+36*b[2, 2]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]*x[i]+36*b[2, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]-4*b[1, 1]*t[j]*x[i])+(2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+12*a[1, 2]*t[j]*x[i]^2-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]-36*a[2, 2]*t[j]^2*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2)*(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])/(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2+12*a[1, 2]*t[j]*x[i]^2-36*b[2, 2]*t[j]^2*x[i]-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-36*a[2, 2]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2+4*b[1, 1]*t[j]*x[i])+24*a[2, 1]*t[j]*x[i]+72*a[2, 2]*t[j]*x[i]^2-72*a[2, 2]*t[j]*x[i]-36*a[0, 2]+2*a[1, 0]-2*a[1, 1]+38*a[1, 2]-6*a[2, 0]+6*a[2, 1]-42*a[2, 2]+4*a[1, 1]*x[i]-72*a[1, 2]*t[j]+12*a[1, 2]*x[i]^2-12*a[1, 2]*x[i]+12*a[2, 0]*t[j]-12*a[2, 1]*x[i]-12*a[2, 1]*t[j]-36*a[2, 2]*x[i]^2+36*a[2, 2]*x[i]-216*a[2, 2]*t[j]^2+228*a[2, 2]*t[j]

(13)

eq22 := subs({t = t[j], x = x[i]}, eq2)

-4*(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])*(-(5+4*b[0, 1]*x[i]+12*b[0, 2]*x[i]^2-12*b[0, 2]*x[i]+4*b[1, 0]*t[j]-4*b[1, 1]*t[j]-4*b[1, 1]*x[i]+4*b[1, 2]*t[j]-12*b[1, 2]*x[i]^2+12*b[1, 2]*x[i]+12*b[2, 0]*t[j]^2-12*b[2, 0]*t[j]+4*b[2, 1]*x[i]-12*b[2, 1]*t[j]^2+12*b[2, 1]*t[j]+12*b[2, 2]*x[i]^2-12*b[2, 2]*x[i]+12*b[2, 2]*t[j]^2-12*b[2, 2]*t[j]+2*b[0, 0]-2*b[0, 1]+2*b[0, 2]-2*b[1, 0]+2*b[1, 1]-2*b[1, 2]+2*b[2, 0]-2*b[2, 1]+2*b[2, 2]+72*b[2, 2]*t[j]*x[i]+72*b[2, 2]*t[j]^2*x[i]^2-72*b[2, 2]*t[j]^2*x[i]+24*b[1, 2]*t[j]*x[i]^2-24*b[2, 1]*t[j]*x[i]-72*b[2, 2]*t[j]*x[i]^2+24*b[2, 1]*t[j]^2*x[i]-24*b[1, 2]*t[j]*x[i]+8*b[1, 1]*t[j]*x[i])/(1+2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])+(2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+12*a[1, 2]*t[j]*x[i]^2-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]-36*a[2, 2]*t[j]^2*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2)/(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2+12*a[1, 2]*t[j]*x[i]^2-36*b[2, 2]*t[j]^2*x[i]-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-36*a[2, 2]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2+4*b[1, 1]*t[j]*x[i]))+4*b[1, 1]*x[i]-24*b[1, 2]*t[j]+12*b[1, 2]*x[i]^2-12*b[1, 2]*x[i]+12*b[2, 0]*t[j]-12*b[2, 1]*x[i]-12*b[2, 1]*t[j]-36*b[2, 2]*x[i]^2+36*b[2, 2]*x[i]-72*b[2, 2]*t[j]^2+84*b[2, 2]*t[j]-12*b[0, 2]+2*b[1, 0]-2*b[1, 1]+14*b[1, 2]-6*b[2, 0]+6*b[2, 1]-18*b[2, 2]-72*b[2, 2]*t[j]*x[i]+72*b[2, 2]*t[j]*x[i]^2+24*b[2, 1]*t[j]*x[i]

(14)

eq33 := subs({t = t[j], x = x[i]}, eq3)

4*a[1, 1]*t[j]-12*a[1, 2]*t[j]+12*a[2, 1]*t[j]^2-12*a[2, 1]*t[j]-36*a[2, 2]*t[j]^2+36*a[2, 2]*t[j]+2*a[0, 1]-6*a[0, 2]-2*a[1, 1]+6*a[1, 2]+2*a[2, 1]-6*a[2, 2]

(15)

eq44 := subs({t = t[j], x = x[i]}, eq4)

4*a[1, 1]*t[j]+12*a[1, 2]*t[j]+12*a[2, 1]*t[j]^2-12*a[2, 1]*t[j]+36*a[2, 2]*t[j]^2-36*a[2, 2]*t[j]+2*a[0, 1]+6*a[0, 2]-2*a[1, 1]-6*a[1, 2]+2*a[2, 1]+6*a[2, 2]

(16)

eq55 := subs({t = t[j], x = x[i]}, eq5)

4*b[1, 1]*t[j]+2*b[0, 1]-6*b[0, 2]-2*b[1, 1]+6*b[1, 2]+2*b[2, 1]-6*b[2, 2]-12*b[1, 2]*t[j]+12*b[2, 1]*t[j]^2+36*b[2, 2]*t[j]-36*b[2, 2]*t[j]^2-12*b[2, 1]*t[j]

(17)

eq66 := subs({t = t[j], x = x[i]}, eq6)

4*b[1, 1]*t[j]+12*b[1, 2]*t[j]+2*b[0, 1]+6*b[0, 2]-2*b[1, 1]-6*b[1, 2]+2*b[2, 1]+6*b[2, 2]+36*b[2, 2]*t[j]^2+12*b[2, 1]*t[j]^2-36*b[2, 2]*t[j]-12*b[2, 1]*t[j]

(18)

eq77 := subs({t = t[j], x = x[i]}, eq7)

a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]-2*a[1, 1]*x[i]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+2*a[2, 1]*x[i]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]

(19)

eq88 := subs({t = t[j], x = x[i]}, eq8)

2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]-2*b[1, 1]*x[i]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+2*b[2, 1]*x[i]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]

(20)

``

X1 := evalf(fsolve((1-(2*x-1)^2)*(diff(P(N, X), x)))):

0.

 

.5000000000

 

1.

(21)

T1 := evalf(fsolve(P(M, T))):

.2113248654

 

.7886751346

(22)

printlevel := 4;

4

(23)

``

(24)

for i to M-1 do for j from 0 to N-1 do s[i, j] := simplify(evalf(eq11)) end do end do;

-0.4000000000e-19*(0.8333333339e29*b[0, 0]*b[1, 0]*a[1, 2]+0.1154700538e21*b[0, 0]*b[1, 0]*a[2, 0]+0.2500000000e30*b[0, 0]^2-0.2500000000e30*b[0, 0]*b[0, 2]-0.2886751346e30*b[0, 0]*b[1, 0]+0.1443375675e30*b[0, 0]*b[1, 2]+0.2000000000e21*b[0, 0]*b[2, 0]+0.1000000000e21*b[0, 0]*b[2, 1]-0.3750000000e21*b[0, 0]*b[2, 2]+0.6250000000e29*b[0, 2]^2+0.1443375673e30*b[0, 2]*b[1, 0]-0.7216878375e29*b[0, 2]*b[1, 2]-0.1000000000e21*b[0, 2]*b[2, 0]-0.5000000000e20*b[0, 2]*b[2, 1]+0.1875000000e21*b[0, 2]*b[2, 2]+0.8333333334e29*b[1, 0]^2-0.8333333345e29*b[1, 0]*b[1, 2]-0.1154700538e21*b[1, 0]*b[2, 0]-0.5773502692e20*b[1, 0]*b[2, 1]+0.2165063510e21*b[1, 0]*b[2, 2]+0.2083333339e29*b[1, 2]^2+0.5773502700e20*b[1, 2]*b[2, 0]+0.2886751350e20*b[1, 2]*b[2, 1]-0.1082531756e21*b[1, 2]*b[2, 2]+0.4000000000e11*b[2, 0]^2+0.4000000000e11*b[2, 0]*b[2, 1]-0.1500000000e12*b[2, 0]*b[2, 2]-0.5000000000e11*b[2, 1]*b[2, 2]+0.1250000000e12*b[2, 2]^2+0.9000000000e31*b[0, 0]*a[0, 2]-0.5000000000e30*b[0, 0]*a[1, 0]-0.4946152423e31*b[0, 0]*a[1, 2]+0.8660254038e30*b[0, 0]*a[2, 0]-0.4500000000e31*b[0, 2]*a[0, 2]+0.2500000000e30*b[0, 2]*a[1, 0]+0.2473076211e31*b[0, 2]*a[1, 2]-0.4330127019e30*b[0, 2]*a[2, 0]-0.5196152423e31*b[1, 0]*a[0, 2]+0.2886751346e30*b[1, 0]*a[1, 0]-0.5000000000e30*b[1, 0]*a[2, 0]+0.2598076215e31*b[1, 2]*a[0, 2]-0.1443375675e30*b[1, 2]*a[1, 0]-0.1427831218e31*b[1, 2]*a[1, 2]+0.2500000004e30*b[1, 2]*a[2, 0]+0.3600000000e22*b[2, 0]*a[0, 2]-0.2000000000e21*b[2, 0]*a[1, 0]-0.1978460969e22*b[2, 0]*a[1, 2]+0.3464101615e21*b[2, 0]*a[2, 0]-0.2000000000e11*b[2, 1]*a[1, 2]+0.4000000000e11*b[2, 1]*a[2, 0]-0.4500000000e22*b[2, 2]*a[0, 2]+0.2500000000e21*b[2, 2]*a[1, 0]+0.2473076211e22*b[2, 2]*a[1, 2]-0.4330127020e21*b[2, 2]*a[2, 0]+0.3750000000e30*b[0, 0]^2*b[0, 2]+0.4330127019e30*b[0, 0]^2*b[1, 0]-0.2165063512e30*b[0, 0]^2*b[1, 2]-0.3000000000e21*b[0, 0]^2*b[2, 0]+0.6250000000e21*b[0, 0]^2*b[2, 2]-0.2500000000e30*b[0, 0]^2*a[0, 0]+0.1250000000e30*b[0, 0]^2*a[0, 2]+0.1443375673e30*b[0, 0]^2*a[1, 0]-0.7216878370e29*b[0, 0]^2*a[1, 2]-0.1000000000e21*b[0, 0]^2*a[2, 0]-0.1875000000e30*b[0, 0]*b[0, 2]^2-0.2500000000e30*b[0, 0]*b[1, 0]^2-0.6250000018e29*b[0, 0]*b[1, 2]^2-0.1200000000e12*b[0, 0]*b[2, 0]^2-0.2000000000e21*b[0, 0]^2*b[2, 1]-0.5000000000e12*b[0, 0]*b[2, 2]^2+0.1082531755e30*b[0, 2]^2*b[1, 0]-0.5412658781e29*b[0, 2]^2*b[1, 2]-0.7500000000e20*b[0, 2]^2*b[2, 0]+0.1562500000e21*b[0, 2]^2*b[2, 2]-0.6250000000e29*b[0, 2]^2*a[0, 0]+0.3125000000e29*b[0, 2]^2*a[0, 2]+0.3608439182e29*b[0, 2]^2*a[1, 0]-0.1804219592e29*b[0, 2]^2*a[1, 2]-0.2500000000e20*b[0, 2]^2*a[2, 0]+0.1250000000e30*b[0, 2]*b[1, 0]^2+0.3125000009e29*b[0, 2]*b[1, 2]^2+0.6000000000e11*b[0, 2]*b[2, 0]^2-0.5000000000e20*b[0, 2]^2*b[2, 1]+0.2500000000e12*b[0, 2]*b[2, 2]^2-0.7216878375e29*b[1, 0]^2*b[1, 2]-0.1000000000e21*b[1, 0]^2*b[2, 0]+0.2083333333e21*b[1, 0]^2*b[2, 2]-0.8333333334e29*b[1, 0]^2*a[0, 0]+0.4166666667e29*b[1, 0]^2*a[0, 2]+0.4811252244e29*b[1, 0]^2*a[1, 0]-0.2405626123e29*b[1, 0]^2*a[1, 2]-0.3333333333e20*b[1, 0]^2*a[2, 0]+0.3608439193e29*b[1, 0]*b[1, 2]^2+0.6928203230e11*b[1, 0]*b[2, 0]^2-0.6666666667e20*b[1, 0]^2*b[2, 1]+0.2886751346e12*b[1, 0]*b[2, 2]^2-0.2500000007e20*b[1, 2]^2*b[2, 0]+0.5208333348e20*b[1, 2]^2*b[2, 2]-0.2083333339e29*b[1, 2]^2*a[0, 0]+0.1041666670e29*b[1, 2]^2*a[0, 2]+0.1202813064e29*b[1, 2]^2*a[1, 0]-0.6014065325e28*b[1, 2]^2*a[1, 2]-0.8333333357e19*b[1, 2]^2*a[2, 0]-0.3464101620e11*b[1, 2]*b[2, 0]^2-0.1666666671e20*b[1, 2]^2*b[2, 1]-0.1443375675e12*b[1, 2]*b[2, 2]^2+100.*b[2, 0]^2*b[2, 2]-0.4000000000e11*b[2, 0]^2*a[0, 0]+0.2000000000e11*b[2, 0]^2*a[0, 2]+0.2309401077e11*b[2, 0]^2*a[1, 0]-0.1154700539e11*b[2, 0]^2*a[1, 2]-16.*b[2, 0]^2*a[2, 0]-32.*b[2, 0]^2*b[2, 1]-200.*b[2, 0]*b[2, 2]^2-0.4000000000e11*b[2, 1]^2*b[0, 0]+0.2000000000e11*b[2, 1]^2*b[0, 2]+0.2309401077e11*b[2, 1]^2*b[1, 0]-0.1154700540e11*b[2, 1]^2*b[1, 2]-16.*b[2, 1]^2*b[2, 0]+20.*b[2, 1]^2*b[2, 2]-0.4000000000e11*b[2, 1]^2*a[0, 0]+0.2000000000e11*b[2, 1]^2*a[0, 2]+0.2309401077e11*b[2, 1]^2*a[1, 0]-0.1154700539e11*b[2, 1]^2*a[1, 2]-16.*b[2, 1]^2*a[2, 0]-100.*b[2, 1]*b[2, 2]^2-0.2500000000e30*b[0, 0]^3+0.3125000000e29*b[0, 2]^3+0.4811252244e29*b[1, 0]^3-0.6014065329e28*b[1, 2]^3-16.*b[2, 0]^3+125.*b[2, 2]^3+0.2855662433e31*b[1, 0]*a[1, 2]-0.1732050810e21*b[0, 0]*b[1, 2]*b[2, 0]+0.3608439188e21*b[0, 0]*b[1, 2]*b[2, 2]-0.1443375675e30*b[0, 0]*b[1, 2]*a[0, 0]+0.7216878375e29*b[0, 0]*b[1, 2]*a[0, 2]+0.8333333345e29*b[0, 0]*b[1, 2]*a[1, 0]-0.4166666675e29*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502700e20*b[0, 0]*b[1, 2]*a[2, 0]+0.5000000000e12*b[0, 0]*b[2, 0]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 0]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 0]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 0]*a[2, 0]+0.2000000000e21*b[0, 0]*b[2, 1]*b[0, 2]+0.2309401077e21*b[0, 0]*b[2, 1]*b[1, 0]-0.1154700540e21*b[0, 0]*b[2, 1]*b[1, 2]-0.1600000000e12*b[0, 0]*b[2, 1]*b[2, 0]+0.3000000000e12*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 1]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 1]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 1]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 1]*a[2, 0]+0.5000000000e21*b[0, 0]*b[2, 2]*a[0, 0]-0.2500000000e21*b[0, 0]*b[2, 2]*a[0, 2]-0.2886751346e21*b[0, 0]*b[2, 2]*a[1, 0]+0.1443375674e21*b[0, 0]*b[2, 2]*a[1, 2]+0.2000000000e12*b[0, 0]*b[2, 2]*a[2, 0]-0.1250000002e30*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050808e21*b[0, 2]*b[1, 0]*b[2, 0]+0.3608439182e21*b[0, 2]*b[1, 0]*b[2, 2]-0.1443375673e30*b[0, 2]*b[1, 0]*a[0, 0]+0.7216878365e29*b[0, 2]*b[1, 0]*a[0, 2]+0.8333333334e29*b[0, 2]*b[1, 0]*a[1, 0]-0.4166666670e29*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502692e20*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254050e20*b[0, 2]*b[1, 2]*b[2, 0]-0.1804219594e21*b[0, 2]*b[1, 2]*b[2, 2]+0.7216878375e29*b[0, 2]*b[1, 2]*a[0, 0]-0.3608439188e29*b[0, 2]*b[1, 2]*a[0, 2]-0.4166666673e29*b[0, 2]*b[1, 2]*a[1, 0]+0.2083333338e29*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751350e20*b[0, 2]*b[1, 2]*a[2, 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2]^2-0.4946152423e31*a[0, 2]*a[1, 0]+0.5071152424e31*a[0, 2]*a[1, 2]-0.4330126983e30*a[0, 2]*a[2, 0]-0.5000000000e30*a[1, 0]*a[0, 0]+0.2886751346e30*a[1, 0]^2+0.2711324865e31*a[1, 0]*a[1, 2]-0.5000000002e30*a[1, 0]*a[2, 0]-0.4946152422e31*a[1, 2]*a[0, 0]-0.1427831217e31*a[1, 2]^2+0.2499999982e30*a[1, 2]*a[2, 0]+0.8660254038e30*a[2, 0]*a[0, 0]+0.3464101615e21*a[2, 0]^2-0.4330127019e30*b[0, 0]*b[0, 2]*b[1, 0]+0.2165063512e30*b[0, 0]*b[0, 2]*b[1, 2]+0.3000000000e21*b[0, 0]*b[0, 2]*b[2, 0]-0.6250000000e21*b[0, 0]*b[0, 2]*b[2, 2]+0.2500000000e30*b[0, 0]*b[0, 2]*a[0, 0]-0.1250000000e30*b[0, 0]*b[0, 2]*a[0, 2]-0.1443375673e30*b[0, 0]*b[0, 2]*a[1, 0]+0.7216878370e29*b[0, 0]*b[0, 2]*a[1, 2]+0.1000000000e21*b[0, 0]*b[0, 2]*a[2, 0]+0.2500000004e30*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101615e21*b[0, 0]*b[1, 0]*b[2, 0]-0.7216878365e21*b[0, 0]*b[1, 0]*b[2, 2]+0.2886751346e30*b[0, 0]*b[1, 0]*a[0, 0]-0.1443375673e30*b[0, 0]*b[1, 0]*a[0, 2]-0.1666666667e30*b[0, 0]*b[1, 0]*a[1, 0])/(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0])

 

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0]-0.1443375687e27*b[1, 0]*b[1, 2]^2-1732050807.*b[1, 0]*b[2, 0]^2-0.9999999993e18*b[1, 0]^2*b[2, 1]+0.2500000024e18*b[1, 2]^2*b[2, 0]-0.1666666683e18*b[1, 2]^2*b[2, 2]-0.8333333414e26*b[1, 2]^2*a[0, 0]+0.4166666707e26*b[1, 2]^2*a[0, 2]-0.4811252289e26*b[1, 2]^2*a[1, 0]+0.2405626157e26*b[1, 2]^2*a[1, 2]+0.8333333414e17*b[1, 2]^2*a[2, 0]+866025408.*b[1, 2]*b[2, 0]^2-0.2500000024e18*b[1, 2]^2*b[2, 1]-2.*b[2, 0]^2*b[2, 2]-1000000000.*b[2, 0]^2*a[0, 0]+500000000.*b[2, 0]^2*a[0, 2]-577350269.*b[2, 0]^2*a[1, 0]+288675136.*b[2, 0]^2*a[1, 2]+b[2, 0]^2*a[2, 0]-3.*b[2, 0]^2*b[2, 1]-3000000000.*b[2, 1]^2*b[0, 0]+1500000000.*b[2, 1]^2*b[0, 2]-1732050807.*b[2, 1]^2*b[1, 0]+866025408.*b[2, 1]^2*b[1, 2]+3.*b[2, 1]^2*b[2, 0]-2.*b[2, 1]^2*b[2, 2]-1000000000.*b[2, 1]^2*a[0, 0]+500000000.*b[2, 1]^2*a[0, 2]-577350269.*b[2, 1]^2*a[1, 0]+288675136.*b[2, 1]^2*a[1, 2]+b[2, 1]^2*a[2, 0]-0.1000000000e28*b[0, 0]^3+0.1250000000e27*b[0, 2]^3-0.1924500895e27*b[1, 0]^3+0.2405626157e26*b[1, 2]^3+b[2, 0]^3+0.1257735026e29*b[1, 0]*a[1, 2]-0.1732050816e19*b[0, 0]*b[1, 2]*b[2, 0]+0.1154700544e19*b[0, 0]*b[1, 2]*b[2, 2]+0.5773502720e27*b[0, 0]*b[1, 2]*a[0, 0]-0.2886751360e27*b[0, 0]*b[1, 2]*a[0, 2]+0.3333333348e27*b[0, 0]*b[1, 2]*a[1, 0]-0.1666666683e27*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 0]+4000000000.*b[0, 0]*b[2, 0]*b[2, 2]+0.2000000000e19*b[0, 0]*b[2, 0]*a[0, 0]-0.1000000000e19*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e19*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502720e18*b[0, 0]*b[2, 0]*a[1, 2]-2000000000.*b[0, 0]*b[2, 0]*a[2, 0]+0.3000000000e19*b[0, 0]*b[2, 1]*b[0, 2]-0.3464101614e19*b[0, 0]*b[2, 1]*b[1, 0]+0.1732050816e19*b[0, 0]*b[2, 1]*b[1, 2]+6000000000.*b[0, 0]*b[2, 1]*b[2, 0]-4000000000.*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e19*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e19*b[0, 0]*b[2, 1]*a[0, 2]-0.1154700538e19*b[0, 0]*b[2, 1]*a[1, 0]+0.5773502720e18*b[0, 0]*b[2, 1]*a[1, 2]+2000000000.*b[0, 0]*b[2, 1]*a[2, 0]-0.5000000023e27*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050807e19*b[0, 2]*b[1, 0]*b[2, 0]+0.1154700538e19*b[0, 2]*b[1, 0]*b[2, 2]+0.5773502690e27*b[0, 2]*b[1, 0]*a[0, 0]-0.2886751345e27*b[0, 2]*b[1, 0]*a[0, 2]+0.3333333331e27*b[0, 2]*b[1, 0]*a[1, 0]-0.1666666674e27*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254080e18*b[0, 2]*b[1, 2]*b[2, 0]-0.5773502720e18*b[0, 2]*b[1, 2]*b[2, 2]-0.2886751360e27*b[0, 2]*b[1, 2]*a[0, 0]+0.1443375680e27*b[0, 2]*b[1, 2]*a[0, 2]-0.1666666674e27*b[0, 2]*b[1, 2]*a[1, 0]+0.8333333414e26*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 0]-2000000000.*b[0, 2]*b[2, 0]*b[2, 2]-0.1000000000e19*b[0, 2]*b[2, 0]*a[0, 0]+0.5000000000e18*b[0, 2]*b[2, 0]*a[0, 2]-0.5773502690e18*b[0, 2]*b[2, 0]*a[1, 0]+0.2886751360e18*b[0, 2]*b[2, 0]*a[1, 2]+1000000000.*b[0, 2]*b[2, 0]*a[2, 0]+0.1732050807e19*b[0, 2]*b[2, 1]*b[1, 0]-0.8660254080e18*b[0, 2]*b[2, 1]*b[1, 2]-3000000000.*b[0, 2]*b[2, 1]*b[2, 0]+2000000000.*b[0, 2]*b[2, 1]*b[2, 2]+0.1000000000e19*b[0, 2]*b[2, 1]*a[0, 0]-0.5000000000e18*b[0, 2]*b[2, 1]*a[0, 2]+0.5773502690e18*b[0, 2]*b[2, 1]*a[1, 0]-0.2886751360e18*b[0, 2]*b[2, 1]*a[1, 2]-1000000000.*b[0, 2]*b[2, 1]*a[2, 0]-0.1000000005e19*b[1, 0]*b[1, 2]*b[2, 0]+0.6666666697e18*b[1, 0]*b[1, 2]*b[2, 2]+0.3333333348e27*b[1, 0]*b[1, 2]*a[0, 0]-0.1666666674e27*b[1, 0]*b[1, 2]*a[0, 2]+0.1924500905e27*b[1, 0]*b[1, 2]*a[1, 0]-0.9622504577e26*b[1, 0]*b[1, 2]*a[1, 2]-0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 0]+2309401076.*b[1, 0]*b[2, 0]*b[2, 2]+0.1154700538e19*b[1, 0]*b[2, 0]*a[0, 0]-0.5773502690e18*b[1, 0]*b[2, 0]*a[0, 2]+0.6666666662e18*b[1, 0]*b[2, 0]*a[1, 0]-0.3333333348e18*b[1, 0]*b[2, 0]*a[1, 2]-1154700538.*b[1, 0]*b[2, 0]*a[2, 0]+0.1000000005e19*b[1, 0]*b[2, 1]*b[1, 2]+3464101614.*b[1, 0]*b[2, 1]*b[2, 0]-2309401076.*b[1, 0]*b[2, 1]*b[2, 2]-0.1154700538e19*b[1, 0]*b[2, 1]*a[0, 0]+0.5773502690e18*b[1, 0]*b[2, 1]*a[0, 2]-0.6666666662e18*b[1, 0]*b[2, 1]*a[1, 0]+0.3333333348e18*b[1, 0]*b[2, 1]*a[1, 2]+1154700538.*b[1, 0]*b[2, 1]*a[2, 0]-1154700544.*b[1, 2]*b[2, 0]*b[2, 2]-0.5773502720e18*b[1, 2]*b[2, 0]*a[0, 0]+0.2886751360e18*b[1, 2]*b[2, 0]*a[0, 2]-0.3333333348e18*b[1, 2]*b[2, 0]*a[1, 0]+0.1666666683e18*b[1, 2]*b[2, 0]*a[1, 2]+577350272.*b[1, 2]*b[2, 0]*a[2, 0]-1732050816.*b[1, 2]*b[2, 1]*b[2, 0]+1154700544.*b[1, 2]*b[2, 1]*b[2, 2]+0.5773502720e18*b[1, 2]*b[2, 1]*a[0, 0]-0.2886751360e18*b[1, 2]*b[2, 1]*a[0, 2]+0.3333333348e18*b[1, 2]*b[2, 1]*a[1, 0]-0.1666666683e18*b[1, 2]*b[2, 1]*a[1, 2]-577350272.*b[1, 2]*b[2, 1]*a[2, 0]+4.*b[2, 0]*b[2, 1]*b[2, 2]+2000000000.*b[2, 0]*b[2, 1]*a[0, 0]-1000000000.*b[2, 0]*b[2, 1]*a[0, 2]+1154700538.*b[2, 0]*b[2, 1]*a[1, 0]-577350272.*b[2, 0]*b[2, 1]*a[1, 2]-2.*b[2, 0]*b[2, 1]*a[2, 0]+0.1732050853e28*a[2, 2]*b[0, 0]-0.8660254265e27*a[2, 2]*b[0, 2]+0.1000000026e28*a[2, 2]*b[1, 0]-0.5000000155e27*a[2, 2]*b[1, 2]-0.1732050853e19*a[2, 2]*b[2, 0]+0.1732050853e19*a[2, 2]*b[2, 1]+0.3464101700e19*a[2, 2]*b[2, 2]+0.1732050850e28*a[2, 2]*a[0, 0]-0.8660252810e27*a[2, 2]*a[0, 2]+0.1000000016e28*a[2, 2]*a[1, 0]-0.4999999275e27*a[2, 2]*a[1, 2]-0.1558845731e20*a[2, 2]*a[2, 0]+0.3600000000e29*a[0, 2]*a[0, 0]-0.1800000000e29*a[0, 2]^2+0.2178460968e29*a[0, 2]*a[1, 0]-0.2128460974e29*a[0, 2]*a[1, 2]+0.1732050772e28*a[0, 2]*a[2, 0]-0.2000000000e28*a[1, 0]*a[0, 0]-0.1154700538e28*a[1, 0]^2+0.1315470054e29*a[1, 0]*a[1, 2]-0.1999999997e28*a[1, 0]*a[2, 0]+0.2178460969e29*a[1, 2]*a[0, 0]-0.6288675165e28*a[1, 2]^2+0.9999999830e27*a[1, 2]*a[2, 0]-0.3464101615e28*a[2, 0]*a[0, 0]+0.3464101615e19*a[2, 0]^2-0.1000000000e19*b[0, 0]^2*a[2, 1]-0.4000000000e19*b[0, 0]^2*a[2, 2]+0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 1]+0.4000000000e19*b[0, 0]*b[0, 2]*a[2, 2]-0.1154700538e19*b[0, 0]*b[1, 0]*a[2, 1]-0.4618802152e19*b[0, 0]*b[1, 0]*a[2, 2]+0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 1]+0.2309401088e19*b[0, 0]*b[1, 2]*a[2, 2]+2000000000.*b[0, 0]*b[2, 0]*a[2, 1]+8000000000.*b[0, 0]*b[2, 0]*a[2, 2]-2000000000.*b[0, 0]*b[2, 1]*a[2, 1]-8000000000.*b[0, 0]*b[2, 1]*a[2, 2]+0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 1]+0.2309401076e19*b[0, 2]*b[1, 0]*a[2, 2]-0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 1]-0.1154700544e19*b[0, 2]*b[1, 2]*a[2, 2]-1000000000.*b[0, 2]*b[2, 0]*a[2, 1]-4000000000.*b[0, 2]*b[2, 0]*a[2, 2]+1000000000.*b[0, 2]*b[2, 1]*a[2, 1]+4000000000.*b[0, 2]*b[2, 1]*a[2, 2]+0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 1]+0.1333333339e19*b[1, 0]*b[1, 2]*a[2, 2]+1154700538.*b[1, 0]*b[2, 0]*a[2, 1]+4618802152.*b[1, 0]*b[2, 0]*a[2, 2]-1154700538.*b[1, 0]*b[2, 1]*a[2, 1]-4618802152.*b[1, 0]*b[2, 1]*a[2, 2]-577350272.*b[1, 2]*b[2, 0]*a[2, 1]-2309401088.*b[1, 2]*b[2, 0]*a[2, 2]+577350272.*b[1, 2]*b[2, 1]*a[2, 1]+2309401088.*b[1, 2]*b[2, 1]*a[2, 2]+2.*b[2, 0]*b[2, 1]*a[2, 1]+8.*b[2, 0]*b[2, 1]*a[2, 2]-1.*b[2, 1]^3-0.2500000000e18*b[0, 2]^2*a[2, 1]-0.1000000000e19*b[0, 2]^2*a[2, 2]-0.3333333331e18*b[1, 0]^2*a[2, 1]-0.1333333332e19*b[1, 0]^2*a[2, 2]-0.8333333414e17*b[1, 2]^2*a[2, 1]-0.3333333366e18*b[1, 2]^2*a[2, 2]-1.*b[2, 0]^2*a[2, 1]-4.*b[2, 0]^2*a[2, 2]-1.*b[2, 1]^2*a[2, 1]-4.*b[2, 1]^2*a[2, 2]+0.1732050850e19*a[2, 2]*a[2, 1]+0.6928203400e19*a[2, 2]^2+0.3600000000e20*a[0, 2]*a[2, 1]-0.2000000000e19*a[1, 0]*a[2, 1]+0.2178460969e20*a[1, 2]*a[2, 1]-0.3464101615e19*a[2, 0]*a[2, 1]+0.1732050807e28*b[0, 0]*b[0, 2]*b[1, 0]-0.8660254080e27*b[0, 0]*b[0, 2]*b[1, 2]-0.3000000000e19*b[0, 0]*b[0, 2]*b[2, 0]+0.2000000000e19*b[0, 0]*b[0, 2]*b[2, 2]+0.1000000000e28*b[0, 0]*b[0, 2]*a[0, 0]-0.5000000000e27*b[0, 0]*b[0, 2]*a[0, 2]+0.5773502690e27*b[0, 0]*b[0, 2]*a[1, 0]-0.2886751360e27*b[0, 0]*b[0, 2]*a[1, 2]-0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 0]+0.1000000005e28*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101614e19*b[0, 0]*b[1, 0]*b[2, 0]-0.2309401076e19*b[0, 0]*b[1, 0]*b[2, 2]-0.1154700538e28*b[0, 0]*b[1, 0]*a[0, 0]+0.5773502690e27*b[0, 0]*b[1, 0]*a[0, 2]-0.6666666662e27*b[0, 0]*b[1, 0]*a[1, 0])/(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2])

(25)

s[2, 2]

(26)

for i to M-1 do for j from 0 to N-1 do w[i, j] := simplify(evalf(eq22)) end do end do;

0.2000000000e-9*(-0.1889957658e30*b[0, 0]*b[1, 0]*a[1, 2]-0.7237604306e21*b[0, 0]*b[1, 0]*a[2, 0]+0.5000000000e31*b[0, 0]^2-0.8000000000e31*b[0, 0]*b[0, 2]-0.5273502692e31*b[0, 0]*b[1, 0]+0.4368802158e31*b[0, 0]*b[1, 2]-0.8660253998e30*b[0, 0]*b[2, 0]+0.2000000000e22*b[0, 0]*b[2, 1]+0.4330126925e30*b[0, 0]*b[2, 2]+0.2750000000e31*b[0, 2]^2+0.4368802154e31*b[0, 2]*b[1, 0]-0.3050426484e31*b[0, 2]*b[1, 2]+0.4330126987e30*b[0, 2]*b[2, 0]-0.1000000000e22*b[0, 2]*b[2, 1]-0.2165063448e30*b[0, 2]*b[2, 2]+0.1377991532e31*b[1, 0]^2-0.2377991534e31*b[1, 0]*b[1, 2]+0.4999999979e30*b[1, 0]*b[2, 0]-0.1154700538e22*b[1, 0]*b[2, 1]-0.2499999948e30*b[1, 0]*b[2, 2]+0.8444978848e30*b[1, 2]^2-0.2499999986e30*b[1, 2]*b[2, 0]+0.5773502700e21*b[1, 2]*b[2, 1]+0.1249999967e30*b[1, 2]*b[2, 2]-0.3464101607e21*b[2, 0]^2+0.8000000000e12*b[2, 0]*b[2, 1]+0.6062177789e21*b[2, 0]*b[2, 2]-0.1000000000e13*b[2, 1]*b[2, 2]-0.2165063475e21*b[2, 2]^2+0.4000000000e31*b[0, 0]*a[0, 0]-0.2000000000e31*b[0, 0]*a[0, 2]-0.2309401077e31*b[0, 0]*a[1, 0]+0.1154700539e31*b[0, 0]*a[1, 2]+0.2000000000e22*b[0, 0]*a[2, 0]-0.5000000000e31*b[0, 2]*a[0, 0]+0.2500000000e31*b[0, 2]*a[0, 2]+0.2886751346e31*b[0, 2]*a[1, 0]-0.1443375674e31*b[0, 2]*a[1, 2]-0.2200000000e22*b[0, 2]*a[2, 0]-0.1809401077e31*b[1, 0]*a[0, 0]+0.9047005384e30*b[1, 0]*a[0, 2]+0.1044658199e31*b[1, 0]*a[1, 0]-0.9547005384e21*b[1, 0]*a[2, 0]+0.2636751348e31*b[1, 2]*a[0, 0]-0.1318375674e31*b[1, 2]*a[0, 2]-0.1522329100e31*b[1, 2]*a[1, 0]+0.7611645506e30*b[1, 2]*a[1, 2]+0.1170170593e22*b[1, 2]*a[2, 0]-0.8660254022e30*b[2, 0]*a[0, 0]+0.4330127011e30*b[2, 0]*a[0, 2]+0.4999999991e30*b[2, 0]*a[1, 0]-0.2499999997e30*b[2, 0]*a[1, 2]-0.3464101607e21*b[2, 0]*a[2, 0]+0.1600000000e22*b[2, 1]*a[0, 0]-0.8000000000e21*b[2, 1]*a[0, 2]-0.9237604307e21*b[2, 1]*a[1, 0]+0.4618802156e21*b[2, 1]*a[1, 2]+0.8000000000e12*b[2, 1]*a[2, 0]+0.4330126960e30*b[2, 2]*a[0, 0]-0.2165063480e30*b[2, 2]*a[0, 2]-0.2499999966e30*b[2, 2]*a[1, 0]+0.1249999984e30*b[2, 2]*a[1, 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0]+80.*b[2, 1]*b[1, 1]*b[2, 2]-0.1600000000e12*b[2, 1]*b[1, 1]*a[0, 0]+0.8000000000e11*b[2, 1]*b[1, 1]*a[0, 2]+0.9237604307e11*b[2, 1]*b[1, 1]*a[1, 0]-0.4618802157e11*b[2, 1]*b[1, 1]*a[1, 2]-64.*b[2, 1]*b[1, 1]*a[2, 0]+0.4000000000e12*b[2, 2]*b[1, 1]*a[0, 0]-0.2000000000e12*b[2, 2]*b[1, 1]*a[0, 2]-0.2309401077e12*b[2, 2]*b[1, 1]*a[1, 0]+0.1154700539e12*b[2, 2]*b[1, 1]*a[1, 2]+160.*b[2, 2]*b[1, 1]*a[2, 0]+0.1666666671e20*a[1, 1]*b[1, 2]^2-0.3333333343e20*b[1, 1]*b[1, 2]^2+32.*a[1, 1]*b[2, 0]^2-64.*b[1, 1]*b[2, 0]^2+32.*a[1, 1]*b[2, 1]^2+200.*a[1, 1]*b[2, 2]^2+500.*a[2, 2]*b[2, 2]^2-200.*b[1, 1]*b[2, 2]^2+0.6428203230e31*b[0, 0]*b[0, 2]*b[1, 0]-0.4946152426e31*b[0, 0]*b[0, 2]*b[1, 2]+0.8660253998e30*b[0, 0]*b[0, 2]*b[2, 0]-0.4330126915e30*b[0, 0]*b[0, 2]*b[2, 2]-0.4000000000e31*b[0, 0]*b[0, 2]*a[0, 0]+0.2000000000e31*b[0, 0]*b[0, 2]*a[0, 2]+0.2309401077e31*b[0, 0]*b[0, 2]*a[1, 0]-0.1154700539e31*b[0, 0]*b[0, 2]*a[1, 2]-0.2000000000e22*b[0, 0]*b[0, 2]*a[2, 0]-0.3422649732e31*b[0, 0]*b[1, 0]*b[1, 2]+0.9999999986e30*b[0, 0]*b[1, 0]*b[2, 0]-0.4999999940e30*b[0, 0]*b[1, 0]*b[2, 2]-0.6547005380e30*b[0, 0]*b[1, 0]*a[0, 0]+0.3273502690e30*b[0, 0]*b[1, 0]*a[0, 2]+0.3779915319e30*b[0, 0]*b[1, 0]*a[1, 0])/((5000000000.+5000000000.*b[0, 0]-2500000000.*b[0, 2]-2886751346.*b[1, 0]+1443375675.*b[1, 2]+2.*b[2, 0]+2.*b[2, 1]-5.*b[2, 2])*(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0]))

 

0.1000000000e-8*(-0.1910683611e28*b[0, 0]*b[1, 0]*a[1, 2]-0.6618802152e19*b[0, 0]*b[1, 0]*a[2, 0]+0.2000000000e29*b[0, 0]^2-0.3200000000e29*b[0, 0]*b[0, 2]+0.2509401076e29*b[0, 0]*b[1, 0]-0.1947520867e29*b[0, 0]*b[1, 2]+0.3464101575e28*b[0, 0]*b[2, 0]+0.4000000000e20*b[0, 0]*b[2, 1]-0.1732050770e28*b[0, 0]*b[2, 2]+0.1100000000e29*b[0, 2]^2-0.1947520861e29*b[0, 2]*b[1, 0]+0.1320170597e29*b[0, 2]*b[1, 2]-0.1732050776e28*b[0, 2]*b[2, 0]-0.3200000000e20*b[0, 2]*b[2, 1]+0.8660253610e27*b[0, 2]*b[2, 2]+0.7821367200e28*b[1, 0]^2-0.1182136724e29*b[1, 0]*b[1, 2]+0.1999999974e28*b[1, 0]*b[2, 0]+0.2509401076e20*b[1, 0]*b[2, 1]-0.9999999740e27*b[1, 0]*b[2, 2]+0.3955341829e28*b[1, 2]^2-0.9999999854e27*b[1, 2]*b[2, 0]-0.1947520867e20*b[1, 2]*b[2, 1]+0.4999999757e27*b[1, 2]*b[2, 2]-0.3464101595e19*b[2, 0]^2+0.3464101575e19*b[2, 0]*b[2, 1]+0.8660254000e19*b[2, 0]*b[2, 2]+0.2000000000e11*b[2, 1]^2-0.1732050770e19*b[2, 1]*b[2, 2]-0.3464101620e19*b[2, 2]^2+0.1600000000e29*b[0, 0]*a[0, 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0]-0.4999999721e27*b[0, 2]*b[1, 2]*b[2, 2]+0.8582903797e28*b[0, 2]*b[1, 2]*a[0, 0]-0.4291451898e28*b[0, 2]*b[1, 2]*a[0, 2]+0.4955341816e28*b[0, 2]*b[1, 2]*a[1, 0]-0.2477670921e28*b[0, 2]*b[1, 2]*a[1, 2]-0.8582903797e19*b[0, 2]*b[1, 2]*a[2, 0]-0.5196152353e19*b[0, 2]*b[2, 0]*b[2, 2]-0.1732050796e28*b[0, 2]*b[2, 0]*a[0, 0]+0.8660253978e27*b[0, 2]*b[2, 0]*a[0, 2]-0.9999999927e27*b[0, 2]*b[2, 0]*a[1, 0]+0.4999999989e27*b[0, 2]*b[2, 0]*a[1, 2]+0.1732050796e19*b[0, 2]*b[2, 0]*a[2, 0]-0.2740341184e20*b[0, 2]*b[2, 1]*b[1, 0]+0.2062990923e20*b[0, 2]*b[2, 1]*b[1, 2]-0.3464101579e19*b[0, 2]*b[2, 1]*b[2, 0]+0.1732050734e19*b[0, 2]*b[2, 1]*b[2, 2]-0.1400000000e20*b[0, 2]*b[2, 1]*a[0, 0]+0.7000000000e19*b[0, 2]*b[2, 1]*a[0, 2]-0.8082903766e19*b[0, 2]*b[2, 1]*a[1, 0]+0.4041451904e19*b[0, 2]*b[2, 1]*a[1, 2]+0.1400000000e11*b[0, 2]*b[2, 1]*a[2, 0]+0.8660253850e27*b[0, 2]*b[2, 2]*a[0, 0]-0.4330126925e27*b[0, 2]*b[2, 2]*a[0, 2]+0.4999999890e27*b[0, 2]*b[2, 2]*a[1, 0]-0.2499999958e27*b[0, 2]*b[2, 2]*a[1, 2]-0.8660253850e18*b[0, 2]*b[2, 2]*a[2, 0]-0.1154700528e28*b[1, 0]*b[1, 2]*b[2, 0]+0.5773502436e27*b[1, 0]*b[1, 2]*b[2, 2]-0.6488033886e28*b[1, 0]*b[1, 2]*a[0, 0]+0.3244016943e28*b[1, 0]*b[1, 2]*a[0, 2]-0.3745868109e28*b[1, 0]*b[1, 2]*a[1, 0]+0.1872934064e28*b[1, 0]*b[1, 2]*a[1, 2]+0.6488033886e19*b[1, 0]*b[1, 2]*a[2, 0]+0.5999999941e19*b[1, 0]*b[2, 0]*b[2, 2]+0.1999999997e28*b[1, 0]*b[2, 0]*a[0, 0]-0.9999999986e27*b[1, 0]*b[2, 0]*a[0, 2]+0.1154700536e28*b[1, 0]*b[2, 0]*a[1, 0]-0.5773502712e27*b[1, 0]*b[2, 0]*a[1, 2]-0.1999999997e19*b[1, 0]*b[2, 0]*a[2, 0]-0.1697606779e20*b[1, 0]*b[2, 1]*b[1, 2]+0.3999999981e19*b[1, 0]*b[2, 1]*b[2, 0]-0.1999999938e19*b[1, 0]*b[2, 1]*b[2, 2]+0.4309401076e19*b[1, 0]*b[2, 1]*a[0, 0]-0.2154700538e19*b[1, 0]*b[2, 1]*a[0, 2]+0.2488033870e19*b[1, 0]*b[2, 1]*a[1, 0]-0.1244016942e19*b[1, 0]*b[2, 1]*a[1, 2]-4309401076.*b[1, 0]*b[2, 1]*a[2, 0]-0.9999999780e27*b[1, 0]*b[2, 2]*a[0, 0]+0.4999999890e27*b[1, 0]*b[2, 2]*a[0, 2]-0.5773502563e27*b[1, 0]*b[2, 2]*a[1, 0]+0.2886751296e27*b[1, 0]*b[2, 2]*a[1, 2]+0.9999999780e18*b[1, 0]*b[2, 2]*a[2, 0]-0.2999999972e19*b[1, 2]*b[2, 0]*b[2, 2]-0.9999999969e27*b[1, 2]*b[2, 0]*a[0, 0]+0.4999999984e27*b[1, 2]*b[2, 0]*a[0, 2]-0.5773502672e27*b[1, 2]*b[2, 0]*a[1, 0]+0.2886751351e27*b[1, 2]*b[2, 0]*a[1, 2]+0.9999999969e18*b[1, 2]*b[2, 0]*a[2, 0]-0.1999999987e19*b[1, 2]*b[2, 1]*b[2, 0]+0.9999999604e18*b[1, 2]*b[2, 1]*b[2, 2]-0.9082903786e19*b[1, 2]*b[2, 1]*a[0, 0]+0.4541451893e19*b[1, 2]*b[2, 1]*a[0, 2]-0.5244016944e19*b[1, 2]*b[2, 1]*a[1, 0]+0.2622008486e19*b[1, 2]*b[2, 1]*a[1, 2]+9082903786.*b[1, 2]*b[2, 1]*a[2, 0]+0.4999999916e27*b[1, 2]*b[2, 2]*a[0, 0]-0.2499999958e27*b[1, 2]*b[2, 2]*a[0, 2]+0.2886751296e27*b[1, 2]*b[2, 2]*a[1, 0]-0.1443375656e27*b[1, 2]*b[2, 2]*a[1, 2]-0.4999999916e18*b[1, 2]*b[2, 2]*a[2, 0]+0.1039230476e11*b[2, 0]*b[2, 1]*b[2, 2]+0.3464101619e19*b[2, 0]*b[2, 1]*a[0, 0]-0.1732050810e19*b[2, 0]*b[2, 1]*a[0, 2]+0.2000000002e19*b[2, 0]*b[2, 1]*a[1, 0]-0.1000000006e19*b[2, 0]*b[2, 1]*a[1, 2]-3464101619.*b[2, 0]*b[2, 1]*a[2, 0]+0.1732050770e19*b[2, 0]*b[2, 2]*a[0, 0]-0.8660253850e18*b[2, 0]*b[2, 2]*a[0, 2]+0.9999999780e18*b[2, 0]*b[2, 2]*a[1, 0]-0.4999999916e18*b[2, 0]*b[2, 2]*a[1, 2]-1732050770.*b[2, 0]*b[2, 2]*a[2, 0]-0.1732050770e19*b[2, 1]*b[2, 2]*a[0, 0]+0.8660253850e18*b[2, 1]*b[2, 2]*a[0, 2]-0.9999999780e18*b[2, 1]*b[2, 2]*a[1, 0]+0.4999999916e18*b[2, 1]*b[2, 2]*a[1, 2]+1732050770.*b[2, 1]*b[2, 2]*a[2, 0]+0.7600000000e20*a[2, 2]*b[0, 0]-0.8600000000e20*a[2, 2]*b[0, 2]+0.5187862044e20*a[2, 2]*b[1, 0]-0.5365212326e20*a[2, 2]*b[1, 2]+0.1385640638e20*a[2, 2]*b[2, 0]+0.7600000000e11*a[2, 2]*b[2, 1]-0.6928203240e19*a[2, 2]*b[2, 2]+0.1600000000e20*b[0, 0]*a[2, 1]-0.2000000000e20*b[0, 2]*a[2, 1]+0.1123760430e20*b[1, 0]*a[2, 1]-0.1254700541e20*b[1, 2]*a[2, 1]+0.3464101599e19*b[2, 0]*a[2, 1]+0.1600000000e11*b[2, 1]*a[2, 1]+0.4000000000e19*b[0, 0]^2*a[2, 1]+0.2800000000e20*b[0, 0]^2*a[2, 2]-0.1600000000e20*b[0, 0]*b[0, 2]*a[2, 1]-0.7600000000e20*b[0, 0]*b[0, 2]*a[2, 2]+0.6618802152e19*b[0, 0]*b[1, 0]*a[2, 1]+0.4033161506e20*b[0, 0]*b[1, 0]*a[2, 2]-0.1023760433e20*b[0, 0]*b[1, 2]*a[2, 1]-0.4787862058e20*b[0, 0]*b[1, 2]*a[2, 2]+0.3464101615e19*b[0, 0]*b[2, 0]*a[2, 1]+0.1385640644e20*b[0, 0]*b[2, 0]*a[2, 2]+4000000000.*b[0, 0]*b[2, 1]*a[2, 1]+0.4000000000e11*b[0, 0]*b[2, 1]*a[2, 2]-0.1023760430e20*b[0, 2]*b[1, 0]*a[2, 1]-0.4787862044e20*b[0, 2]*b[1, 0]*a[2, 2]+0.8582903797e19*b[0, 2]*b[1, 2]*a[2, 1]+0.3779571682e20*b[0, 2]*b[1, 2]*a[2, 2]-0.1732050796e19*b[0, 2]*b[2, 0]*a[2, 1]-0.6928203170e19*b[0, 2]*b[2, 0]*a[2, 2]-0.1400000000e11*b[0, 2]*b[2, 1]*a[2, 1]-0.6800000000e11*b[0, 2]*b[2, 1]*a[2, 2]-0.6488033886e19*b[1, 0]*b[1, 2]*a[2, 1]-0.2995213556e20*b[1, 0]*b[1, 2]*a[2, 2]+0.1999999997e19*b[1, 0]*b[2, 0]*a[2, 1]+0.7999999975e19*b[1, 0]*b[2, 0]*a[2, 2]+4309401076.*b[1, 0]*b[2, 1]*a[2, 1]+0.3109401076e11*b[1, 0]*b[2, 1]*a[2, 2]-0.9999999969e18*b[1, 2]*b[2, 0]*a[2, 1]-0.3999999981e19*b[1, 2]*b[2, 0]*a[2, 2]-9082903786.*b[1, 2]*b[2, 1]*a[2, 1]-0.4325981841e11*b[1, 2]*b[2, 1]*a[2, 2]+3464101619.*b[2, 0]*b[2, 1]*a[2, 1]+0.1385640645e11*b[2, 0]*b[2, 1]*a[2, 2]+4.*b[2, 1]^3+0.7000000000e19*b[0, 2]^2*a[2, 1]+0.3100000000e20*b[0, 2]^2*a[2, 2]+0.2488033870e19*b[1, 0]^2*a[2, 1]+0.1395213548e20*b[1, 0]^2*a[2, 2]+0.2622008486e19*b[1, 2]^2*a[2, 1]+0.1148803395e20*b[1, 2]^2*a[2, 2]-3464101619.*b[2, 0]^2*a[2, 1]-0.1385640646e11*b[2, 0]^2*a[2, 2]+12.*b[2, 1]^2*a[2, 2]-0.6928203080e19*b[0, 0]*a[2, 2]*b[2, 2]+0.3464101540e19*b[0, 2]*a[2, 2]*b[2, 2]-0.3999999912e19*b[1, 0]*a[2, 2]*b[2, 2]+0.1999999966e19*b[1, 2]*a[2, 2]*b[2, 2]+6928203080.*b[2, 0]*a[2, 2]*b[2, 2]-6928203080.*b[2, 1]*a[2, 2]*b[2, 2]-0.1732050810e19*b[2, 2]*a[2, 1]-0.9999999780e18*b[1, 0]*b[2, 2]*a[2, 1]+0.4999999916e18*b[1, 2]*b[2, 2]*a[2, 1]-0.1732050770e19*b[0, 0]*b[2, 2]*a[2, 1]+0.8660253850e18*b[0, 2]*b[2, 2]*a[2, 1]+1732050770.*b[2, 0]*b[2, 2]*a[2, 1]-1732050770.*b[2, 1]*b[2, 2]*a[2, 1]-0.2971281291e29*b[0, 0]*b[0, 2]*b[1, 0]+0.2178460977e29*b[0, 0]*b[0, 2]*b[1, 2]-0.3464101575e28*b[0, 0]*b[0, 2]*b[2, 0]+0.1732050730e28*b[0, 0]*b[0, 2]*b[2, 2]-0.1600000000e29*b[0, 0]*b[0, 2]*a[0, 0]+0.8000000000e28*b[0, 0]*b[0, 2]*a[0, 2]-0.9237604304e28*b[0, 0]*b[0, 2]*a[1, 0]+0.4618802176e28*b[0, 0]*b[0, 2]*a[1, 2]+0.1600000000e20*b[0, 0]*b[0, 2]*a[2, 0]-0.1830940113e29*b[0, 0]*b[1, 0]*b[1, 2]+0.3999999976e28*b[0, 0]*b[1, 0]*b[2, 0]-0.1999999933e28*b[0, 0]*b[1, 0]*b[2, 2]+0.6618802152e28*b[0, 0]*b[1, 0]*a[0, 0]-0.3309401076e28*b[0, 0]*b[1, 0]*a[0, 2]+0.3821367203e28*b[0, 0]*b[1, 0]*a[1, 0])/((1000000000.+1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1])*(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2]))

(27)

for j from 0 to N-1 do s[j] := simplify(evalf(eq33)) end do;

-1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-8*a[2, 2]+2.*a[0, 1]-6.*a[0, 2]

 

1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-7*a[2, 2]+2.*a[0, 1]-6.*a[0, 2]

(28)

for j from 0 to N-1 do w[j] := simplify(evalf(eq44)) end do

-1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-8*a[2, 2]+2.*a[0, 1]+6.*a[0, 2]

 

1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-7*a[2, 2]+2.*a[0, 1]+6.*a[0, 2]

(29)

for j from 0 to N-1 do ww[j] := simplify(evalf(eq55)) end do

-1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]+3.464101615*b[1, 2]-0.1000000000e-9*b[2, 1]-0.1000000000e-8*b[2, 2]

 

1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]-3.464101615*b[1, 2]+0.1000000000e-7*b[2, 2]

(30)

for j from 0 to N-1 do www[j] := simplify(evalf(eq66)) end do

-1.154700538*b[1, 1]-3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-9*b[2, 1]+0.1000000000e-8*b[2, 2]

 

1.154700538*b[1, 1]+3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-7*b[2, 2]

(31)

for i from 0 to M do www1[i] := simplify(evalf(eq77)) end do

a[0, 0]-1.*a[0, 1]+a[0, 2]-1.*a[1, 0]+a[1, 1]-1.*a[1, 2]+a[2, 0]-1.*a[2, 1]+a[2, 2]

 

a[0, 0]-.5000000000*a[0, 2]-1.*a[1, 0]+.5000000000*a[1, 2]+a[2, 0]-.5000000000*a[2, 2]

 

a[0, 0]+a[0, 1]+a[0, 2]-1.*a[1, 0]-1.*a[1, 1]-1.*a[1, 2]+a[2, 0]+a[2, 1]+a[2, 2]

(32)

for i from 0 to M do ww1[i] := simplify(evalf(eq88)) end do

b[0, 0]-1.*b[0, 1]+b[0, 2]-1.*b[1, 0]+b[1, 1]-1.*b[1, 2]+b[2, 0]-1.*b[2, 1]+b[2, 2]

 

-.5000000000*b[0, 2]+.5000000000*b[1, 2]-.5000000000*b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0]

 

b[0, 1]+b[0, 2]-1.*b[1, 1]-1.*b[1, 2]+b[2, 1]+b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0]

(33)

fsolve({s[0] = 0, s[1] = 0, s[1, 0] = 0, s[1, 1] = 0, w[0] = 0, w[1] = 0, w[1, 0] = 0, w[1, 1] = 0, ww[0] = 0, ww[1] = 0, ww1[0] = 0, ww1[1] = 0, ww1[2] = 0, www[0] = 0, www[1] = 0, www1[0] = 0, www1[1] = 0, www1[2] = 0}, {a[0, 0], a[0, 1], a[0, 2], a[1, 0], a[1, 1], a[1, 2], a[2, 0], a[2, 1], a[2, 2], b[0, 0], b[0, 1], b[0, 2], b[1, 0], b[1, 1], b[1, 2], b[2, 0], b[2, 1], b[2, 2]})

fsolve({-0.4000000000e-19*(0.8333333339e29*b[0, 0]*b[1, 0]*a[1, 2]+0.1154700538e21*b[0, 0]*b[1, 0]*a[2, 0]+0.2500000000e30*b[0, 0]^2-0.2500000000e30*b[0, 0]*b[0, 2]-0.2886751346e30*b[0, 0]*b[1, 0]+0.1443375675e30*b[0, 0]*b[1, 2]+0.2000000000e21*b[0, 0]*b[2, 0]+0.1000000000e21*b[0, 0]*b[2, 1]-0.3750000000e21*b[0, 0]*b[2, 2]+0.6250000000e29*b[0, 2]^2+0.1443375673e30*b[0, 2]*b[1, 0]-0.7216878375e29*b[0, 2]*b[1, 2]-0.1000000000e21*b[0, 2]*b[2, 0]-0.5000000000e20*b[0, 2]*b[2, 1]+0.1875000000e21*b[0, 2]*b[2, 2]+0.8333333334e29*b[1, 0]^2-0.8333333345e29*b[1, 0]*b[1, 2]-0.1154700538e21*b[1, 0]*b[2, 0]-0.5773502692e20*b[1, 0]*b[2, 1]+0.2165063510e21*b[1, 0]*b[2, 2]+0.2083333339e29*b[1, 2]^2+0.5773502700e20*b[1, 2]*b[2, 0]+0.2886751350e20*b[1, 2]*b[2, 1]-0.1082531756e21*b[1, 2]*b[2, 2]+0.4000000000e11*b[2, 0]^2+0.4000000000e11*b[2, 0]*b[2, 1]-0.1500000000e12*b[2, 0]*b[2, 2]-0.5000000000e11*b[2, 1]*b[2, 2]+0.1250000000e12*b[2, 2]^2+0.9000000000e31*b[0, 0]*a[0, 2]-0.5000000000e30*b[0, 0]*a[1, 0]-0.4946152423e31*b[0, 0]*a[1, 2]+0.8660254038e30*b[0, 0]*a[2, 0]-0.4500000000e31*b[0, 2]*a[0, 2]+0.2500000000e30*b[0, 2]*a[1, 0]+0.2473076211e31*b[0, 2]*a[1, 2]-0.4330127019e30*b[0, 2]*a[2, 0]-0.5196152423e31*b[1, 0]*a[0, 2]+0.2886751346e30*b[1, 0]*a[1, 0]-0.5000000000e30*b[1, 0]*a[2, 0]+0.2598076215e31*b[1, 2]*a[0, 2]-0.1443375675e30*b[1, 2]*a[1, 0]-0.1427831218e31*b[1, 2]*a[1, 2]+0.2500000004e30*b[1, 2]*a[2, 0]+0.3600000000e22*b[2, 0]*a[0, 2]-0.2000000000e21*b[2, 0]*a[1, 0]-0.1978460969e22*b[2, 0]*a[1, 2]+0.3464101615e21*b[2, 0]*a[2, 0]-0.2000000000e11*b[2, 1]*a[1, 2]+0.4000000000e11*b[2, 1]*a[2, 0]-0.4500000000e22*b[2, 2]*a[0, 2]+0.2500000000e21*b[2, 2]*a[1, 0]+0.2473076211e22*b[2, 2]*a[1, 2]-0.4330127020e21*b[2, 2]*a[2, 0]+0.3750000000e30*b[0, 0]^2*b[0, 2]+0.4330127019e30*b[0, 0]^2*b[1, 0]-0.2165063512e30*b[0, 0]^2*b[1, 2]-0.3000000000e21*b[0, 0]^2*b[2, 0]+0.6250000000e21*b[0, 0]^2*b[2, 2]-0.2500000000e30*b[0, 0]^2*a[0, 0]+0.1250000000e30*b[0, 0]^2*a[0, 2]+0.1443375673e30*b[0, 0]^2*a[1, 0]-0.7216878370e29*b[0, 0]^2*a[1, 2]-0.1000000000e21*b[0, 0]^2*a[2, 0]-0.1875000000e30*b[0, 0]*b[0, 2]^2-0.2500000000e30*b[0, 0]*b[1, 0]^2-0.6250000018e29*b[0, 0]*b[1, 2]^2-0.1200000000e12*b[0, 0]*b[2, 0]^2-0.2000000000e21*b[0, 0]^2*b[2, 1]-0.5000000000e12*b[0, 0]*b[2, 2]^2+0.1082531755e30*b[0, 2]^2*b[1, 0]-0.5412658781e29*b[0, 2]^2*b[1, 2]-0.7500000000e20*b[0, 2]^2*b[2, 0]+0.1562500000e21*b[0, 2]^2*b[2, 2]-0.6250000000e29*b[0, 2]^2*a[0, 0]+0.3125000000e29*b[0, 2]^2*a[0, 2]+0.3608439182e29*b[0, 2]^2*a[1, 0]-0.1804219592e29*b[0, 2]^2*a[1, 2]-0.2500000000e20*b[0, 2]^2*a[2, 0]+0.1250000000e30*b[0, 2]*b[1, 0]^2+0.3125000009e29*b[0, 2]*b[1, 2]^2+0.6000000000e11*b[0, 2]*b[2, 0]^2-0.5000000000e20*b[0, 2]^2*b[2, 1]+0.2500000000e12*b[0, 2]*b[2, 2]^2-0.7216878375e29*b[1, 0]^2*b[1, 2]-0.1000000000e21*b[1, 0]^2*b[2, 0]+0.2083333333e21*b[1, 0]^2*b[2, 2]-0.8333333334e29*b[1, 0]^2*a[0, 0]+0.4166666667e29*b[1, 0]^2*a[0, 2]+0.4811252244e29*b[1, 0]^2*a[1, 0]-0.2405626123e29*b[1, 0]^2*a[1, 2]-0.3333333333e20*b[1, 0]^2*a[2, 0]+0.3608439193e29*b[1, 0]*b[1, 2]^2+0.6928203230e11*b[1, 0]*b[2, 0]^2-0.6666666667e20*b[1, 0]^2*b[2, 1]+0.2886751346e12*b[1, 0]*b[2, 2]^2-0.2500000007e20*b[1, 2]^2*b[2, 0]+0.5208333348e20*b[1, 2]^2*b[2, 2]-0.2083333339e29*b[1, 2]^2*a[0, 0]+0.1041666670e29*b[1, 2]^2*a[0, 2]+0.1202813064e29*b[1, 2]^2*a[1, 0]-0.6014065325e28*b[1, 2]^2*a[1, 2]-0.8333333357e19*b[1, 2]^2*a[2, 0]-0.3464101620e11*b[1, 2]*b[2, 0]^2-0.1666666671e20*b[1, 2]^2*b[2, 1]-0.1443375675e12*b[1, 2]*b[2, 2]^2+100.*b[2, 0]^2*b[2, 2]-0.4000000000e11*b[2, 0]^2*a[0, 0]+0.2000000000e11*b[2, 0]^2*a[0, 2]+0.2309401077e11*b[2, 0]^2*a[1, 0]-0.1154700539e11*b[2, 0]^2*a[1, 2]-16.*b[2, 0]^2*a[2, 0]-32.*b[2, 0]^2*b[2, 1]-200.*b[2, 0]*b[2, 2]^2-0.4000000000e11*b[2, 1]^2*b[0, 0]+0.2000000000e11*b[2, 1]^2*b[0, 2]+0.2309401077e11*b[2, 1]^2*b[1, 0]-0.1154700540e11*b[2, 1]^2*b[1, 2]-16.*b[2, 1]^2*b[2, 0]+20.*b[2, 1]^2*b[2, 2]-0.4000000000e11*b[2, 1]^2*a[0, 0]+0.2000000000e11*b[2, 1]^2*a[0, 2]+0.2309401077e11*b[2, 1]^2*a[1, 0]-0.1154700539e11*b[2, 1]^2*a[1, 2]-16.*b[2, 1]^2*a[2, 0]-100.*b[2, 1]*b[2, 2]^2-0.2500000000e30*b[0, 0]^3+0.3125000000e29*b[0, 2]^3+0.4811252244e29*b[1, 0]^3-0.6014065329e28*b[1, 2]^3-16.*b[2, 0]^3+125.*b[2, 2]^3+0.2855662433e31*b[1, 0]*a[1, 2]-0.1732050810e21*b[0, 0]*b[1, 2]*b[2, 0]+0.3608439188e21*b[0, 0]*b[1, 2]*b[2, 2]-0.1443375675e30*b[0, 0]*b[1, 2]*a[0, 0]+0.7216878375e29*b[0, 0]*b[1, 2]*a[0, 2]+0.8333333345e29*b[0, 0]*b[1, 2]*a[1, 0]-0.4166666675e29*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502700e20*b[0, 0]*b[1, 2]*a[2, 0]+0.5000000000e12*b[0, 0]*b[2, 0]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 0]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 0]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 0]*a[2, 0]+0.2000000000e21*b[0, 0]*b[2, 1]*b[0, 2]+0.2309401077e21*b[0, 0]*b[2, 1]*b[1, 0]-0.1154700540e21*b[0, 0]*b[2, 1]*b[1, 2]-0.1600000000e12*b[0, 0]*b[2, 1]*b[2, 0]+0.3000000000e12*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 1]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 1]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 1]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 1]*a[2, 0]+0.5000000000e21*b[0, 0]*b[2, 2]*a[0, 0]-0.2500000000e21*b[0, 0]*b[2, 2]*a[0, 2]-0.2886751346e21*b[0, 0]*b[2, 2]*a[1, 0]+0.1443375674e21*b[0, 0]*b[2, 2]*a[1, 2]+0.2000000000e12*b[0, 0]*b[2, 2]*a[2, 0]-0.1250000002e30*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050808e21*b[0, 2]*b[1, 0]*b[2, 0]+0.3608439182e21*b[0, 2]*b[1, 0]*b[2, 2]-0.1443375673e30*b[0, 2]*b[1, 0]*a[0, 0]+0.7216878365e29*b[0, 2]*b[1, 0]*a[0, 2]+0.8333333334e29*b[0, 2]*b[1, 0]*a[1, 0]-0.4166666670e29*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502692e20*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254050e20*b[0, 2]*b[1, 2]*b[2, 0]-0.1804219594e21*b[0, 2]*b[1, 2]*b[2, 2]+0.7216878375e29*b[0, 2]*b[1, 2]*a[0, 0]-0.3608439188e29*b[0, 2]*b[1, 2]*a[0, 2]-0.4166666673e29*b[0, 2]*b[1, 2]*a[1, 0]+0.2083333338e29*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751350e20*b[0, 2]*b[1, 2]*a[2, 0]-0.2500000000e12*b[0, 2]*b[2, 0]*b[2, 2]+0.1000000000e21*b[0, 2]*b[2, 0]*a[0, 0]-0.5000000000e20*b[0, 2]*b[2, 0]*a[0, 2]-0.5773502692e20*b[0, 2]*b[2, 0]*a[1, 0]+0.2886751348e20*b[0, 2]*b[2, 0]*a[1, 2]+0.4000000000e11*b[0, 2]*b[2, 0]*a[2, 0]-0.1154700538e21*b[0, 2]*b[2, 1]*b[1, 0]+0.5773502700e20*b[0, 2]*b[2, 1]*b[1, 2]+0.8000000000e11*b[0, 2]*b[2, 1]*b[2, 0]-0.1500000000e12*b[0, 2]*b[2, 1]*b[2, 2]+0.1000000000e21*b[0, 2]*b[2, 1]*a[0, 0]-0.5000000000e20*b[0, 2]*b[2, 1]*a[0, 2]-0.5773502692e20*b[0, 2]*b[2, 1]*a[1, 0]+0.2886751348e20*b[0, 2]*b[2, 1]*a[1, 2]+0.4000000000e11*b[0, 2]*b[2, 1]*a[2, 0]-0.2500000000e21*b[0, 2]*b[2, 2]*a[0, 0]+0.1250000000e21*b[0, 2]*b[2, 2]*a[0, 2]+0.1443375673e21*b[0, 2]*b[2, 2]*a[1, 0]-0.7216878370e20*b[0, 2]*b[2, 2]*a[1, 2]-0.1000000000e12*b[0, 2]*b[2, 2]*a[2, 0]+0.1000000001e21*b[1, 0]*b[1, 2]*b[2, 0]-0.2083333336e21*b[1, 0]*b[1, 2]*b[2, 2]+0.8333333345e29*b[1, 0]*b[1, 2]*a[0, 0]-0.4166666673e29*b[1, 0]*b[1, 2]*a[0, 2]-0.4811252250e29*b[1, 0]*b[1, 2]*a[1, 0]+0.2405626127e29*b[1, 0]*b[1, 2]*a[1, 2]+0.3333333338e20*b[1, 0]*b[1, 2]*a[2, 0]-0.2886751346e12*b[1, 0]*b[2, 0]*b[2, 2]+0.1154700538e21*b[1, 0]*b[2, 0]*a[0, 0]-0.5773502692e20*b[1, 0]*b[2, 0]*a[0, 2]-0.6666666667e20*b[1, 0]*b[2, 0]*a[1, 0]+0.3333333336e20*b[1, 0]*b[2, 0]*a[1, 2]+0.4618802154e11*b[1, 0]*b[2, 0]*a[2, 0]+0.6666666676e20*b[1, 0]*b[2, 1]*b[1, 2]+0.9237604307e11*b[1, 0]*b[2, 1]*b[2, 0]-0.1732050808e12*b[1, 0]*b[2, 1]*b[2, 2]+0.1154700538e21*b[1, 0]*b[2, 1]*a[0, 0]-0.5773502692e20*b[1, 0]*b[2, 1]*a[0, 2]-0.6666666667e20*b[1, 0]*b[2, 1]*a[1, 0]+0.3333333336e20*b[1, 0]*b[2, 1]*a[1, 2]+0.4618802154e11*b[1, 0]*b[2, 1]*a[2, 0]-0.2886751346e21*b[1, 0]*b[2, 2]*a[0, 0]+0.1443375673e21*b[1, 0]*b[2, 2]*a[0, 2]+0.1666666667e21*b[1, 0]*b[2, 2]*a[1, 0]-0.8333333339e20*b[1, 0]*b[2, 2]*a[1, 2]-0.1154700538e12*b[1, 0]*b[2, 2]*a[2, 0]+0.1443375675e12*b[1, 2]*b[2, 0]*b[2, 2]-0.5773502700e20*b[1, 2]*b[2, 0]*a[0, 0]+0.2886751350e20*b[1, 2]*b[2, 0]*a[0, 2]+0.3333333338e20*b[1, 2]*b[2, 0]*a[1, 0]-0.1666666670e20*b[1, 2]*b[2, 0]*a[1, 2]-0.2309401080e11*b[1, 2]*b[2, 0]*a[2, 0]-0.4618802160e11*b[1, 2]*b[2, 1]*b[2, 0]+0.8660254050e11*b[1, 2]*b[2, 1]*b[2, 2]-0.5773502700e20*b[1, 2]*b[2, 1]*a[0, 0]+0.2886751350e20*b[1, 2]*b[2, 1]*a[0, 2]+0.3333333338e20*b[1, 2]*b[2, 1]*a[1, 0]-0.1666666670e20*b[1, 2]*b[2, 1]*a[1, 2]-0.2309401080e11*b[1, 2]*b[2, 1]*a[2, 0]+0.1443375675e21*b[1, 2]*b[2, 2]*a[0, 0]-0.7216878375e20*b[1, 2]*b[2, 2]*a[0, 2]-0.8333333345e20*b[1, 2]*b[2, 2]*a[1, 0]+0.4166666675e20*b[1, 2]*b[2, 2]*a[1, 2]+0.5773502700e11*b[1, 2]*b[2, 2]*a[2, 0]+120.*b[2, 0]*b[2, 1]*b[2, 2]-0.8000000000e11*b[2, 0]*b[2, 1]*a[0, 0]+0.4000000000e11*b[2, 0]*b[2, 1]*a[0, 2]+0.4618802154e11*b[2, 0]*b[2, 1]*a[1, 0]-0.2309401078e11*b[2, 0]*b[2, 1]*a[1, 2]-32.*b[2, 0]*b[2, 1]*a[2, 0]+0.2000000000e12*b[2, 0]*b[2, 2]*a[0, 0]-0.1000000000e12*b[2, 0]*b[2, 2]*a[0, 2]-0.1154700538e12*b[2, 0]*b[2, 2]*a[1, 0]+0.5773502696e11*b[2, 0]*b[2, 2]*a[1, 2]+80.*b[2, 0]*b[2, 2]*a[2, 0]+0.2000000000e12*b[2, 1]*b[2, 2]*a[0, 0]-0.1000000000e12*b[2, 1]*b[2, 2]*a[0, 2]-0.1154700538e12*b[2, 1]*b[2, 2]*a[1, 0]+0.5773502696e11*b[2, 1]*b[2, 2]*a[1, 2]+80.*b[2, 1]*b[2, 2]*a[2, 0]-0.2500000000e12*b[2, 2]^2*a[0, 0]+0.1250000000e12*b[2, 2]^2*a[0, 2]+0.1443375673e12*b[2, 2]^2*a[1, 0]-0.7216878370e11*b[2, 2]^2*a[1, 2]-100.*b[2, 2]^2*a[2, 0]+0.5000000000e20*a[1, 1]*b[0, 0]-0.2500000000e20*a[1, 1]*b[0, 2]-0.2886751346e20*a[1, 1]*b[1, 0]+0.1443375675e20*a[1, 1]*b[1, 2]+0.2000000000e11*a[1, 1]*b[2, 0]+0.2000000000e11*a[1, 1]*b[2, 1]-0.5000000000e11*a[1, 1]*b[2, 2]-0.4330127014e30*a[2, 2]*b[0, 0]+0.2165063507e30*a[2, 2]*b[0, 2]+0.2499999997e30*a[2, 2]*b[1, 0]-0.1250000000e30*a[2, 2]*b[1, 2]-0.1732050806e21*a[2, 2]*b[2, 0]+0.5000000000e11*a[2, 2]*b[2, 1]+0.2165063506e21*a[2, 2]*b[2, 2]-0.4330127015e30*a[2, 2]*a[0, 0]+0.2165063508e30*a[2, 2]*a[0, 2]+0.2499999998e30*a[2, 2]*a[1, 0]-0.1250000000e30*a[2, 2]*a[1, 2]-0.1732050806e21*a[2, 2]*a[2, 0]+0.9000000000e31*a[0, 2]*a[0, 0]-0.4500000000e31*a[0, 2]^2-0.4946152423e31*a[0, 2]*a[1, 0]+0.5071152424e31*a[0, 2]*a[1, 2]-0.4330126983e30*a[0, 2]*a[2, 0]-0.5000000000e30*a[1, 0]*a[0, 0]+0.2886751346e30*a[1, 0]^2+0.2711324865e31*a[1, 0]*a[1, 2]-0.5000000002e30*a[1, 0]*a[2, 0]-0.4946152422e31*a[1, 2]*a[0, 0]-0.1427831217e31*a[1, 2]^2+0.2499999982e30*a[1, 2]*a[2, 0]+0.8660254038e30*a[2, 0]*a[0, 0]+0.3464101615e21*a[2, 0]^2-0.4330127019e30*b[0, 0]*b[0, 2]*b[1, 0]+0.2165063512e30*b[0, 0]*b[0, 2]*b[1, 2]+0.3000000000e21*b[0, 0]*b[0, 2]*b[2, 0]-0.6250000000e21*b[0, 0]*b[0, 2]*b[2, 2]+0.2500000000e30*b[0, 0]*b[0, 2]*a[0, 0]-0.1250000000e30*b[0, 0]*b[0, 2]*a[0, 2]-0.1443375673e30*b[0, 0]*b[0, 2]*a[1, 0]+0.7216878370e29*b[0, 0]*b[0, 2]*a[1, 2]+0.1000000000e21*b[0, 0]*b[0, 2]*a[2, 0]+0.2500000004e30*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101615e21*b[0, 0]*b[1, 0]*b[2, 0]-0.7216878365e21*b[0, 0]*b[1, 0]*b[2, 2]+0.2886751346e30*b[0, 0]*b[1, 0]*a[0, 0]-0.1443375673e30*b[0, 0]*b[1, 0]*a[0, 2]-0.1666666667e30*b[0, 0]*b[1, 0]*a[1, 0])/(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0]) = 0, -0.1000000000e-17*(0.3333333348e27*b[0, 0]*b[1, 0]*a[1, 2]+0.1154700538e19*b[0, 0]*b[1, 0]*a[2, 0]+0.1000000000e28*b[0, 0]^2-0.1000000000e28*b[0, 0]*b[0, 2]+0.1154700538e28*b[0, 0]*b[1, 0]-0.5773502720e27*b[0, 0]*b[1, 2]-0.2000000000e19*b[0, 0]*b[2, 0]+0.2000000000e19*b[0, 0]*b[2, 1]+0.2000000000e19*b[0, 0]*b[2, 2]+0.2500000000e27*b[0, 2]^2-0.5773502690e27*b[0, 2]*b[1, 0]+0.2886751360e27*b[0, 2]*b[1, 2]+0.1000000000e19*b[0, 2]*b[2, 0]-0.1000000000e19*b[0, 2]*b[2, 1]-0.1000000000e19*b[0, 2]*b[2, 2]+0.3333333331e27*b[1, 0]^2-0.3333333348e27*b[1, 0]*b[1, 2]-0.1154700538e19*b[1, 0]*b[2, 0]+0.1154700538e19*b[1, 0]*b[2, 1]+0.1154700538e19*b[1, 0]*b[2, 2]+0.8333333414e26*b[1, 2]^2+0.5773502720e18*b[1, 2]*b[2, 0]-0.5773502720e18*b[1, 2]*b[2, 1]-0.5773502720e18*b[1, 2]*b[2, 2]+1000000000.*b[2, 0]^2-2000000000.*b[2, 0]*b[2, 1]-2000000000.*b[2, 0]*b[2, 2]+1000000000.*b[2, 1]^2+2000000000.*b[2, 1]*b[2, 2]+0.3600000000e29*b[0, 0]*a[0, 2]-0.2000000000e28*b[0, 0]*a[1, 0]+0.2178460969e29*b[0, 0]*a[1, 2]-0.3464101615e28*b[0, 0]*a[2, 0]-0.1800000000e29*b[0, 2]*a[0, 2]+0.1000000000e28*b[0, 2]*a[1, 0]-0.1089230484e29*b[0, 2]*a[1, 2]+0.1732050808e28*b[0, 2]*a[2, 0]+0.2078460968e29*b[1, 0]*a[0, 2]-0.1154700538e28*b[1, 0]*a[1, 0]-0.1999999999e28*b[1, 0]*a[2, 0]-0.1039230490e29*b[1, 2]*a[0, 2]+0.5773502720e27*b[1, 2]*a[1, 0]-0.6288675165e28*b[1, 2]*a[1, 2]+0.1000000005e28*b[1, 2]*a[2, 0]-0.3600000000e20*b[2, 0]*a[0, 2]+0.2000000000e19*b[2, 0]*a[1, 0]-0.2178460969e20*b[2, 0]*a[1, 2]+0.3464101615e19*b[2, 0]*a[2, 0]+0.3600000000e20*b[2, 1]*a[0, 2]-0.2000000000e19*b[2, 1]*a[1, 0]+0.2178460969e20*b[2, 1]*a[1, 2]-0.3464101615e19*b[2, 1]*a[2, 0]+0.7200000000e20*b[2, 2]*a[0, 2]-0.4000000000e19*b[2, 2]*a[1, 0]+0.4356921938e20*b[2, 2]*a[1, 2]-0.6928203230e19*b[2, 2]*a[2, 0]+0.1500000000e28*b[0, 0]^2*b[0, 2]-0.1732050807e28*b[0, 0]^2*b[1, 0]+0.8660254080e27*b[0, 0]^2*b[1, 2]+0.3000000000e19*b[0, 0]^2*b[2, 0]-0.2000000000e19*b[0, 0]^2*b[2, 2]-0.1000000000e28*b[0, 0]^2*a[0, 0]+0.5000000000e27*b[0, 0]^2*a[0, 2]-0.5773502690e27*b[0, 0]^2*a[1, 0]+0.2886751360e27*b[0, 0]^2*a[1, 2]+0.1000000000e19*b[0, 0]^2*a[2, 0]-0.7500000000e27*b[0, 0]*b[0, 2]^2-0.9999999993e27*b[0, 0]*b[1, 0]^2-0.2500000024e27*b[0, 0]*b[1, 2]^2-3000000000.*b[0, 0]*b[2, 0]^2-0.3000000000e19*b[0, 0]^2*b[2, 1]-0.4330127018e27*b[0, 2]^2*b[1, 0]+0.2165063520e27*b[0, 2]^2*b[1, 2]+0.7500000000e18*b[0, 2]^2*b[2, 0]-0.5000000000e18*b[0, 2]^2*b[2, 2]-0.2500000000e27*b[0, 2]^2*a[0, 0]+0.1250000000e27*b[0, 2]^2*a[0, 2]-0.1443375672e27*b[0, 2]^2*a[1, 0]+0.7216878400e26*b[0, 2]^2*a[1, 2]+0.2500000000e18*b[0, 2]^2*a[2, 0]+0.4999999997e27*b[0, 2]*b[1, 0]^2+0.1250000012e27*b[0, 2]*b[1, 2]^2+1500000000.*b[0, 2]*b[2, 0]^2-0.7500000000e18*b[0, 2]^2*b[2, 1]+0.2886751358e27*b[1, 0]^2*b[1, 2]+0.9999999993e18*b[1, 0]^2*b[2, 0]-0.6666666662e18*b[1, 0]^2*b[2, 2]-0.3333333331e27*b[1, 0]^2*a[0, 0]+0.1666666666e27*b[1, 0]^2*a[0, 2]-0.1924500895e27*b[1, 0]^2*a[1, 0]+0.9622504527e26*b[1, 0]^2*a[1, 2]+0.3333333331e18*b[1, 0]^2*a[2, 0]-0.1443375687e27*b[1, 0]*b[1, 2]^2-1732050807.*b[1, 0]*b[2, 0]^2-0.9999999993e18*b[1, 0]^2*b[2, 1]+0.2500000024e18*b[1, 2]^2*b[2, 0]-0.1666666683e18*b[1, 2]^2*b[2, 2]-0.8333333414e26*b[1, 2]^2*a[0, 0]+0.4166666707e26*b[1, 2]^2*a[0, 2]-0.4811252289e26*b[1, 2]^2*a[1, 0]+0.2405626157e26*b[1, 2]^2*a[1, 2]+0.8333333414e17*b[1, 2]^2*a[2, 0]+866025408.*b[1, 2]*b[2, 0]^2-0.2500000024e18*b[1, 2]^2*b[2, 1]-2.*b[2, 0]^2*b[2, 2]-1000000000.*b[2, 0]^2*a[0, 0]+500000000.*b[2, 0]^2*a[0, 2]-577350269.*b[2, 0]^2*a[1, 0]+288675136.*b[2, 0]^2*a[1, 2]+b[2, 0]^2*a[2, 0]-3.*b[2, 0]^2*b[2, 1]-3000000000.*b[2, 1]^2*b[0, 0]+1500000000.*b[2, 1]^2*b[0, 2]-1732050807.*b[2, 1]^2*b[1, 0]+866025408.*b[2, 1]^2*b[1, 2]+3.*b[2, 1]^2*b[2, 0]-2.*b[2, 1]^2*b[2, 2]-1000000000.*b[2, 1]^2*a[0, 0]+500000000.*b[2, 1]^2*a[0, 2]-577350269.*b[2, 1]^2*a[1, 0]+288675136.*b[2, 1]^2*a[1, 2]+b[2, 1]^2*a[2, 0]-0.1000000000e28*b[0, 0]^3+0.1250000000e27*b[0, 2]^3-0.1924500895e27*b[1, 0]^3+0.2405626157e26*b[1, 2]^3+b[2, 0]^3+0.1257735026e29*b[1, 0]*a[1, 2]-0.1732050816e19*b[0, 0]*b[1, 2]*b[2, 0]+0.1154700544e19*b[0, 0]*b[1, 2]*b[2, 2]+0.5773502720e27*b[0, 0]*b[1, 2]*a[0, 0]-0.2886751360e27*b[0, 0]*b[1, 2]*a[0, 2]+0.3333333348e27*b[0, 0]*b[1, 2]*a[1, 0]-0.1666666683e27*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 0]+4000000000.*b[0, 0]*b[2, 0]*b[2, 2]+0.2000000000e19*b[0, 0]*b[2, 0]*a[0, 0]-0.1000000000e19*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e19*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502720e18*b[0, 0]*b[2, 0]*a[1, 2]-2000000000.*b[0, 0]*b[2, 0]*a[2, 0]+0.3000000000e19*b[0, 0]*b[2, 1]*b[0, 2]-0.3464101614e19*b[0, 0]*b[2, 1]*b[1, 0]+0.1732050816e19*b[0, 0]*b[2, 1]*b[1, 2]+6000000000.*b[0, 0]*b[2, 1]*b[2, 0]-4000000000.*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e19*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e19*b[0, 0]*b[2, 1]*a[0, 2]-0.1154700538e19*b[0, 0]*b[2, 1]*a[1, 0]+0.5773502720e18*b[0, 0]*b[2, 1]*a[1, 2]+2000000000.*b[0, 0]*b[2, 1]*a[2, 0]-0.5000000023e27*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050807e19*b[0, 2]*b[1, 0]*b[2, 0]+0.1154700538e19*b[0, 2]*b[1, 0]*b[2, 2]+0.5773502690e27*b[0, 2]*b[1, 0]*a[0, 0]-0.2886751345e27*b[0, 2]*b[1, 0]*a[0, 2]+0.3333333331e27*b[0, 2]*b[1, 0]*a[1, 0]-0.1666666674e27*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254080e18*b[0, 2]*b[1, 2]*b[2, 0]-0.5773502720e18*b[0, 2]*b[1, 2]*b[2, 2]-0.2886751360e27*b[0, 2]*b[1, 2]*a[0, 0]+0.1443375680e27*b[0, 2]*b[1, 2]*a[0, 2]-0.1666666674e27*b[0, 2]*b[1, 2]*a[1, 0]+0.8333333414e26*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 0]-2000000000.*b[0, 2]*b[2, 0]*b[2, 2]-0.1000000000e19*b[0, 2]*b[2, 0]*a[0, 0]+0.5000000000e18*b[0, 2]*b[2, 0]*a[0, 2]-0.5773502690e18*b[0, 2]*b[2, 0]*a[1, 0]+0.2886751360e18*b[0, 2]*b[2, 0]*a[1, 2]+1000000000.*b[0, 2]*b[2, 0]*a[2, 0]+0.1732050807e19*b[0, 2]*b[2, 1]*b[1, 0]-0.8660254080e18*b[0, 2]*b[2, 1]*b[1, 2]-3000000000.*b[0, 2]*b[2, 1]*b[2, 0]+2000000000.*b[0, 2]*b[2, 1]*b[2, 2]+0.1000000000e19*b[0, 2]*b[2, 1]*a[0, 0]-0.5000000000e18*b[0, 2]*b[2, 1]*a[0, 2]+0.5773502690e18*b[0, 2]*b[2, 1]*a[1, 0]-0.2886751360e18*b[0, 2]*b[2, 1]*a[1, 2]-1000000000.*b[0, 2]*b[2, 1]*a[2, 0]-0.1000000005e19*b[1, 0]*b[1, 2]*b[2, 0]+0.6666666697e18*b[1, 0]*b[1, 2]*b[2, 2]+0.3333333348e27*b[1, 0]*b[1, 2]*a[0, 0]-0.1666666674e27*b[1, 0]*b[1, 2]*a[0, 2]+0.1924500905e27*b[1, 0]*b[1, 2]*a[1, 0]-0.9622504577e26*b[1, 0]*b[1, 2]*a[1, 2]-0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 0]+2309401076.*b[1, 0]*b[2, 0]*b[2, 2]+0.1154700538e19*b[1, 0]*b[2, 0]*a[0, 0]-0.5773502690e18*b[1, 0]*b[2, 0]*a[0, 2]+0.6666666662e18*b[1, 0]*b[2, 0]*a[1, 0]-0.3333333348e18*b[1, 0]*b[2, 0]*a[1, 2]-1154700538.*b[1, 0]*b[2, 0]*a[2, 0]+0.1000000005e19*b[1, 0]*b[2, 1]*b[1, 2]+3464101614.*b[1, 0]*b[2, 1]*b[2, 0]-2309401076.*b[1, 0]*b[2, 1]*b[2, 2]-0.1154700538e19*b[1, 0]*b[2, 1]*a[0, 0]+0.5773502690e18*b[1, 0]*b[2, 1]*a[0, 2]-0.6666666662e18*b[1, 0]*b[2, 1]*a[1, 0]+0.3333333348e18*b[1, 0]*b[2, 1]*a[1, 2]+1154700538.*b[1, 0]*b[2, 1]*a[2, 0]-1154700544.*b[1, 2]*b[2, 0]*b[2, 2]-0.5773502720e18*b[1, 2]*b[2, 0]*a[0, 0]+0.2886751360e18*b[1, 2]*b[2, 0]*a[0, 2]-0.3333333348e18*b[1, 2]*b[2, 0]*a[1, 0]+0.1666666683e18*b[1, 2]*b[2, 0]*a[1, 2]+577350272.*b[1, 2]*b[2, 0]*a[2, 0]-1732050816.*b[1, 2]*b[2, 1]*b[2, 0]+1154700544.*b[1, 2]*b[2, 1]*b[2, 2]+0.5773502720e18*b[1, 2]*b[2, 1]*a[0, 0]-0.2886751360e18*b[1, 2]*b[2, 1]*a[0, 2]+0.3333333348e18*b[1, 2]*b[2, 1]*a[1, 0]-0.1666666683e18*b[1, 2]*b[2, 1]*a[1, 2]-577350272.*b[1, 2]*b[2, 1]*a[2, 0]+4.*b[2, 0]*b[2, 1]*b[2, 2]+2000000000.*b[2, 0]*b[2, 1]*a[0, 0]-1000000000.*b[2, 0]*b[2, 1]*a[0, 2]+1154700538.*b[2, 0]*b[2, 1]*a[1, 0]-577350272.*b[2, 0]*b[2, 1]*a[1, 2]-2.*b[2, 0]*b[2, 1]*a[2, 0]+0.1732050853e28*a[2, 2]*b[0, 0]-0.8660254265e27*a[2, 2]*b[0, 2]+0.1000000026e28*a[2, 2]*b[1, 0]-0.5000000155e27*a[2, 2]*b[1, 2]-0.1732050853e19*a[2, 2]*b[2, 0]+0.1732050853e19*a[2, 2]*b[2, 1]+0.3464101700e19*a[2, 2]*b[2, 2]+0.1732050850e28*a[2, 2]*a[0, 0]-0.8660252810e27*a[2, 2]*a[0, 2]+0.1000000016e28*a[2, 2]*a[1, 0]-0.4999999275e27*a[2, 2]*a[1, 2]-0.1558845731e20*a[2, 2]*a[2, 0]+0.3600000000e29*a[0, 2]*a[0, 0]-0.1800000000e29*a[0, 2]^2+0.2178460968e29*a[0, 2]*a[1, 0]-0.2128460974e29*a[0, 2]*a[1, 2]+0.1732050772e28*a[0, 2]*a[2, 0]-0.2000000000e28*a[1, 0]*a[0, 0]-0.1154700538e28*a[1, 0]^2+0.1315470054e29*a[1, 0]*a[1, 2]-0.1999999997e28*a[1, 0]*a[2, 0]+0.2178460969e29*a[1, 2]*a[0, 0]-0.6288675165e28*a[1, 2]^2+0.9999999830e27*a[1, 2]*a[2, 0]-0.3464101615e28*a[2, 0]*a[0, 0]+0.3464101615e19*a[2, 0]^2-0.1000000000e19*b[0, 0]^2*a[2, 1]-0.4000000000e19*b[0, 0]^2*a[2, 2]+0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 1]+0.4000000000e19*b[0, 0]*b[0, 2]*a[2, 2]-0.1154700538e19*b[0, 0]*b[1, 0]*a[2, 1]-0.4618802152e19*b[0, 0]*b[1, 0]*a[2, 2]+0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 1]+0.2309401088e19*b[0, 0]*b[1, 2]*a[2, 2]+2000000000.*b[0, 0]*b[2, 0]*a[2, 1]+8000000000.*b[0, 0]*b[2, 0]*a[2, 2]-2000000000.*b[0, 0]*b[2, 1]*a[2, 1]-8000000000.*b[0, 0]*b[2, 1]*a[2, 2]+0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 1]+0.2309401076e19*b[0, 2]*b[1, 0]*a[2, 2]-0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 1]-0.1154700544e19*b[0, 2]*b[1, 2]*a[2, 2]-1000000000.*b[0, 2]*b[2, 0]*a[2, 1]-4000000000.*b[0, 2]*b[2, 0]*a[2, 2]+1000000000.*b[0, 2]*b[2, 1]*a[2, 1]+4000000000.*b[0, 2]*b[2, 1]*a[2, 2]+0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 1]+0.1333333339e19*b[1, 0]*b[1, 2]*a[2, 2]+1154700538.*b[1, 0]*b[2, 0]*a[2, 1]+4618802152.*b[1, 0]*b[2, 0]*a[2, 2]-1154700538.*b[1, 0]*b[2, 1]*a[2, 1]-4618802152.*b[1, 0]*b[2, 1]*a[2, 2]-577350272.*b[1, 2]*b[2, 0]*a[2, 1]-2309401088.*b[1, 2]*b[2, 0]*a[2, 2]+577350272.*b[1, 2]*b[2, 1]*a[2, 1]+2309401088.*b[1, 2]*b[2, 1]*a[2, 2]+2.*b[2, 0]*b[2, 1]*a[2, 1]+8.*b[2, 0]*b[2, 1]*a[2, 2]-1.*b[2, 1]^3-0.2500000000e18*b[0, 2]^2*a[2, 1]-0.1000000000e19*b[0, 2]^2*a[2, 2]-0.3333333331e18*b[1, 0]^2*a[2, 1]-0.1333333332e19*b[1, 0]^2*a[2, 2]-0.8333333414e17*b[1, 2]^2*a[2, 1]-0.3333333366e18*b[1, 2]^2*a[2, 2]-1.*b[2, 0]^2*a[2, 1]-4.*b[2, 0]^2*a[2, 2]-1.*b[2, 1]^2*a[2, 1]-4.*b[2, 1]^2*a[2, 2]+0.1732050850e19*a[2, 2]*a[2, 1]+0.6928203400e19*a[2, 2]^2+0.3600000000e20*a[0, 2]*a[2, 1]-0.2000000000e19*a[1, 0]*a[2, 1]+0.2178460969e20*a[1, 2]*a[2, 1]-0.3464101615e19*a[2, 0]*a[2, 1]+0.1732050807e28*b[0, 0]*b[0, 2]*b[1, 0]-0.8660254080e27*b[0, 0]*b[0, 2]*b[1, 2]-0.3000000000e19*b[0, 0]*b[0, 2]*b[2, 0]+0.2000000000e19*b[0, 0]*b[0, 2]*b[2, 2]+0.1000000000e28*b[0, 0]*b[0, 2]*a[0, 0]-0.5000000000e27*b[0, 0]*b[0, 2]*a[0, 2]+0.5773502690e27*b[0, 0]*b[0, 2]*a[1, 0]-0.2886751360e27*b[0, 0]*b[0, 2]*a[1, 2]-0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 0]+0.1000000005e28*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101614e19*b[0, 0]*b[1, 0]*b[2, 0]-0.2309401076e19*b[0, 0]*b[1, 0]*b[2, 2]-0.1154700538e28*b[0, 0]*b[1, 0]*a[0, 0]+0.5773502690e27*b[0, 0]*b[1, 0]*a[0, 2]-0.6666666662e27*b[0, 0]*b[1, 0]*a[1, 0])/(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2]) = 0, 0.1000000000e-8*(-0.1910683611e28*b[0, 0]*b[1, 0]*a[1, 2]-0.6618802152e19*b[0, 0]*b[1, 0]*a[2, 0]+0.2000000000e29*b[0, 0]^2-0.3200000000e29*b[0, 0]*b[0, 2]+0.2509401076e29*b[0, 0]*b[1, 0]-0.1947520867e29*b[0, 0]*b[1, 2]+0.3464101575e28*b[0, 0]*b[2, 0]+0.4000000000e20*b[0, 0]*b[2, 1]-0.1732050770e28*b[0, 0]*b[2, 2]+0.1100000000e29*b[0, 2]^2-0.1947520861e29*b[0, 2]*b[1, 0]+0.1320170597e29*b[0, 2]*b[1, 2]-0.1732050776e28*b[0, 2]*b[2, 0]-0.3200000000e20*b[0, 2]*b[2, 1]+0.8660253610e27*b[0, 2]*b[2, 2]+0.7821367200e28*b[1, 0]^2-0.1182136724e29*b[1, 0]*b[1, 2]+0.1999999974e28*b[1, 0]*b[2, 0]+0.2509401076e20*b[1, 0]*b[2, 1]-0.9999999740e27*b[1, 0]*b[2, 2]+0.3955341829e28*b[1, 2]^2-0.9999999854e27*b[1, 2]*b[2, 0]-0.1947520867e20*b[1, 2]*b[2, 1]+0.4999999757e27*b[1, 2]*b[2, 2]-0.3464101595e19*b[2, 0]^2+0.3464101575e19*b[2, 0]*b[2, 1]+0.8660254000e19*b[2, 0]*b[2, 2]+0.2000000000e11*b[2, 1]^2-0.1732050770e19*b[2, 1]*b[2, 2]-0.3464101620e19*b[2, 2]^2+0.1600000000e29*b[0, 0]*a[0, 0]-0.8000000000e28*b[0, 0]*a[0, 2]+0.9237604304e28*b[0, 0]*a[1, 0]-0.4618802176e28*b[0, 0]*a[1, 2]-0.1600000000e20*b[0, 0]*a[2, 0]-0.2000000000e29*b[0, 2]*a[0, 0]+0.1000000000e29*b[0, 2]*a[0, 2]-0.1154700538e29*b[0, 2]*a[1, 0]+0.5773502720e28*b[0, 2]*a[1, 2]+0.2000000000e20*b[0, 2]*a[2, 0]+0.1123760430e29*b[1, 0]*a[0, 0]-0.5618802152e28*b[1, 0]*a[0, 2]+0.6488033868e28*b[1, 0]*a[1, 0]-0.1123760430e20*b[1, 0]*a[2, 0]-0.1254700541e29*b[1, 2]*a[0, 0]+0.6273502703e28*b[1, 2]*a[0, 2]-0.7244016946e28*b[1, 2]*a[1, 0]+0.3622008492e28*b[1, 2]*a[1, 2]+0.1254700541e20*b[1, 2]*a[2, 0]+0.3464101599e28*b[2, 0]*a[0, 0]-0.1732050800e28*b[2, 0]*a[0, 2]+0.1999999990e28*b[2, 0]*a[1, 0]-0.1000000000e28*b[2, 0]*a[1, 2]-0.3464101599e19*b[2, 0]*a[2, 0]+0.1600000000e20*b[2, 1]*a[0, 0]-0.8000000000e19*b[2, 1]*a[0, 2]+0.9237604304e19*b[2, 1]*a[1, 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2]-0.9999999969e18*b[1, 2]*b[2, 0]*a[2, 1]-0.3999999981e19*b[1, 2]*b[2, 0]*a[2, 2]-9082903786.*b[1, 2]*b[2, 1]*a[2, 1]-0.4325981841e11*b[1, 2]*b[2, 1]*a[2, 2]+3464101619.*b[2, 0]*b[2, 1]*a[2, 1]+0.1385640645e11*b[2, 0]*b[2, 1]*a[2, 2]+4.*b[2, 1]^3+0.7000000000e19*b[0, 2]^2*a[2, 1]+0.3100000000e20*b[0, 2]^2*a[2, 2]+0.2488033870e19*b[1, 0]^2*a[2, 1]+0.1395213548e20*b[1, 0]^2*a[2, 2]+0.2622008486e19*b[1, 2]^2*a[2, 1]+0.1148803395e20*b[1, 2]^2*a[2, 2]-3464101619.*b[2, 0]^2*a[2, 1]-0.1385640646e11*b[2, 0]^2*a[2, 2]+12.*b[2, 1]^2*a[2, 2]-0.6928203080e19*b[0, 0]*a[2, 2]*b[2, 2]+0.3464101540e19*b[0, 2]*a[2, 2]*b[2, 2]-0.3999999912e19*b[1, 0]*a[2, 2]*b[2, 2]+0.1999999966e19*b[1, 2]*a[2, 2]*b[2, 2]+6928203080.*b[2, 0]*a[2, 2]*b[2, 2]-6928203080.*b[2, 1]*a[2, 2]*b[2, 2]-0.1732050810e19*b[2, 2]*a[2, 1]-0.9999999780e18*b[1, 0]*b[2, 2]*a[2, 1]+0.4999999916e18*b[1, 2]*b[2, 2]*a[2, 1]-0.1732050770e19*b[0, 0]*b[2, 2]*a[2, 1]+0.8660253850e18*b[0, 2]*b[2, 2]*a[2, 1]+1732050770.*b[2, 0]*b[2, 2]*a[2, 1]-1732050770.*b[2, 1]*b[2, 2]*a[2, 1]-0.2971281291e29*b[0, 0]*b[0, 2]*b[1, 0]+0.2178460977e29*b[0, 0]*b[0, 2]*b[1, 2]-0.3464101575e28*b[0, 0]*b[0, 2]*b[2, 0]+0.1732050730e28*b[0, 0]*b[0, 2]*b[2, 2]-0.1600000000e29*b[0, 0]*b[0, 2]*a[0, 0]+0.8000000000e28*b[0, 0]*b[0, 2]*a[0, 2]-0.9237604304e28*b[0, 0]*b[0, 2]*a[1, 0]+0.4618802176e28*b[0, 0]*b[0, 2]*a[1, 2]+0.1600000000e20*b[0, 0]*b[0, 2]*a[2, 0]-0.1830940113e29*b[0, 0]*b[1, 0]*b[1, 2]+0.3999999976e28*b[0, 0]*b[1, 0]*b[2, 0]-0.1999999933e28*b[0, 0]*b[1, 0]*b[2, 2]+0.6618802152e28*b[0, 0]*b[1, 0]*a[0, 0]-0.3309401076e28*b[0, 0]*b[1, 0]*a[0, 2]+0.3821367203e28*b[0, 0]*b[1, 0]*a[1, 0])/((1000000000.+1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1])*(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2])) = 0, 0.2000000000e-9*(-0.1889957658e30*b[0, 0]*b[1, 0]*a[1, 2]-0.7237604306e21*b[0, 0]*b[1, 0]*a[2, 0]+0.5000000000e31*b[0, 0]^2-0.8000000000e31*b[0, 0]*b[0, 2]-0.5273502692e31*b[0, 0]*b[1, 0]+0.4368802158e31*b[0, 0]*b[1, 2]-0.8660253998e30*b[0, 0]*b[2, 0]+0.2000000000e22*b[0, 0]*b[2, 1]+0.4330126925e30*b[0, 0]*b[2, 2]+0.2750000000e31*b[0, 2]^2+0.4368802154e31*b[0, 2]*b[1, 0]-0.3050426484e31*b[0, 2]*b[1, 2]+0.4330126987e30*b[0, 2]*b[2, 0]-0.1000000000e22*b[0, 2]*b[2, 1]-0.2165063448e30*b[0, 2]*b[2, 2]+0.1377991532e31*b[1, 0]^2-0.2377991534e31*b[1, 0]*b[1, 2]+0.4999999979e30*b[1, 0]*b[2, 0]-0.1154700538e22*b[1, 0]*b[2, 1]-0.2499999948e30*b[1, 0]*b[2, 2]+0.8444978848e30*b[1, 2]^2-0.2499999986e30*b[1, 2]*b[2, 0]+0.5773502700e21*b[1, 2]*b[2, 1]+0.1249999967e30*b[1, 2]*b[2, 2]-0.3464101607e21*b[2, 0]^2+0.8000000000e12*b[2, 0]*b[2, 1]+0.6062177789e21*b[2, 0]*b[2, 2]-0.1000000000e13*b[2, 1]*b[2, 2]-0.2165063475e21*b[2, 2]^2+0.4000000000e31*b[0, 0]*a[0, 0]-0.2000000000e31*b[0, 0]*a[0, 2]-0.2309401077e31*b[0, 0]*a[1, 0]+0.1154700539e31*b[0, 0]*a[1, 2]+0.2000000000e22*b[0, 0]*a[2, 0]-0.5000000000e31*b[0, 2]*a[0, 0]+0.2500000000e31*b[0, 2]*a[0, 2]+0.2886751346e31*b[0, 2]*a[1, 0]-0.1443375674e31*b[0, 2]*a[1, 2]-0.2200000000e22*b[0, 2]*a[2, 0]-0.1809401077e31*b[1, 0]*a[0, 0]+0.9047005384e30*b[1, 0]*a[0, 2]+0.1044658199e31*b[1, 0]*a[1, 0]-0.9547005384e21*b[1, 0]*a[2, 0]+0.2636751348e31*b[1, 2]*a[0, 0]-0.1318375674e31*b[1, 2]*a[0, 2]-0.1522329100e31*b[1, 2]*a[1, 0]+0.7611645506e30*b[1, 2]*a[1, 2]+0.1170170593e22*b[1, 2]*a[2, 0]-0.8660254022e30*b[2, 0]*a[0, 0]+0.4330127011e30*b[2, 0]*a[0, 2]+0.4999999991e30*b[2, 0]*a[1, 0]-0.2499999997e30*b[2, 0]*a[1, 2]-0.3464101607e21*b[2, 0]*a[2, 0]+0.1600000000e22*b[2, 1]*a[0, 0]-0.8000000000e21*b[2, 1]*a[0, 2]-0.9237604307e21*b[2, 1]*a[1, 0]+0.4618802156e21*b[2, 1]*a[1, 2]+0.8000000000e12*b[2, 1]*a[2, 0]+0.4330126960e30*b[2, 2]*a[0, 0]-0.2165063480e30*b[2, 2]*a[0, 2]-0.2499999966e30*b[2, 2]*a[1, 0]+0.1249999984e30*b[2, 2]*a[1, 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0]^2+0.7750000000e21*b[0, 2]^2*b[2, 1]+0.3247595222e21*b[0, 2]*b[2, 2]^2+0.9047005385e30*b[1, 0]^2*b[1, 2]-0.2886751343e30*b[1, 0]^2*b[2, 0]+0.1443375658e30*b[1, 0]^2*b[2, 2]+0.4465819851e29*b[1, 0]^2*a[0, 0]-0.2232909926e29*b[1, 0]^2*a[0, 2]-0.2578342293e29*b[1, 0]^2*a[1, 0]+0.1289171141e29*b[1, 0]^2*a[1, 2]+0.1511966127e21*b[1, 0]^2*a[2, 0]-0.7410254048e30*b[1, 0]*b[1, 2]^2+0.3999999999e21*b[1, 0]*b[2, 0]^2+0.1178632794e21*b[1, 0]^2*b[2, 1]+0.3749999972e21*b[1, 0]*b[2, 2]^2-0.7216878338e29*b[1, 2]^2*b[2, 0]+0.3608439079e29*b[1, 2]^2*b[2, 2]+0.5111645502e30*b[1, 2]^2*a[0, 0]-0.2555822751e30*b[1, 2]^2*a[0, 2]-0.2951209907e30*b[1, 2]^2*a[1, 0]+0.1475604954e30*b[1, 2]^2*a[1, 2]+0.2377991535e21*b[1, 2]^2*a[2, 0]-0.2000000000e21*b[1, 2]*b[2, 0]^2+0.2294658202e21*b[1, 2]^2*b[2, 1]-0.1874999980e21*b[1, 2]*b[2, 2]^2+0.5888972742e12*b[2, 0]^2*b[2, 2]-0.3464101617e21*b[2, 0]^2*a[0, 0]+0.1732050808e21*b[2, 0]^2*a[0, 2]+0.2000000001e21*b[2, 0]^2*a[1, 0]-0.1000000001e21*b[2, 0]^2*a[1, 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2]-0.8660254038e30*b[0, 0]*b[2, 0]*a[0, 0]+0.4330127019e30*b[0, 0]*b[2, 0]*a[0, 2]+0.5000000000e30*b[0, 0]*b[2, 0]*a[1, 0]-0.2500000002e30*b[0, 0]*b[2, 0]*a[1, 2]-0.3464101612e21*b[0, 0]*b[2, 0]*a[2, 0]-0.1900000000e22*b[0, 0]*b[2, 1]*b[0, 2]-0.6082903767e21*b[0, 0]*b[2, 1]*b[1, 0]+0.9969655116e21*b[0, 0]*b[2, 1]*b[1, 2]-0.3464101613e21*b[0, 0]*b[2, 1]*b[2, 0]+0.1732050794e21*b[0, 0]*b[2, 1]*b[2, 2]-0.1000000000e21*b[0, 0]*b[2, 1]*a[0, 0]+0.5000000000e20*b[0, 0]*b[2, 1]*a[0, 2]+0.5773502692e20*b[0, 0]*b[2, 1]*a[1, 0]-0.2886751364e20*b[0, 0]*b[2, 1]*a[1, 2]+0.2800000000e12*b[0, 0]*b[2, 1]*a[2, 0]+0.4330126990e30*b[0, 0]*b[2, 2]*a[0, 0]-0.2165063495e30*b[0, 0]*b[2, 2]*a[0, 2]-0.2499999983e30*b[0, 0]*b[2, 2]*a[1, 0]+0.1249999993e30*b[0, 0]*b[2, 2]*a[1, 2]+0.1732050788e21*b[0, 0]*b[2, 2]*a[2, 0]+0.2711324867e31*b[0, 2]*b[1, 0]*b[1, 2]-0.4999999979e30*b[0, 2]*b[1, 0]*b[2, 0]+0.2499999944e30*b[0, 2]*b[1, 0]*b[2, 2]+0.2059401077e31*b[0, 2]*b[1, 0]*a[0, 0]-0.1029700538e31*b[0, 2]*b[1, 0]*a[0, 2]-0.1188995766e31*b[0, 2]*b[1, 0]*a[1, 0]+0.5944978833e30*b[0, 2]*b[1, 0]*a[1, 2]+0.1054700538e22*b[0, 2]*b[1, 0]*a[2, 0]+0.2499999986e30*b[0, 2]*b[1, 2]*b[2, 0]-0.1249999961e30*b[0, 2]*b[1, 2]*b[2, 2]-0.1895725943e31*b[0, 2]*b[1, 2]*a[0, 0]+0.9478629716e30*b[0, 2]*b[1, 2]*a[0, 2]+0.1094497884e31*b[0, 2]*b[1, 2]*a[1, 0]-0.5472489422e30*b[0, 2]*b[1, 2]*a[1, 2]-0.8737604313e21*b[0, 2]*b[1, 2]*a[2, 0]-0.8227241301e21*b[0, 2]*b[2, 0]*b[2, 2]+0.4330127007e30*b[0, 2]*b[2, 0]*a[0, 0]-0.2165063504e30*b[0, 2]*b[2, 0]*a[0, 2]-0.2499999993e30*b[0, 2]*b[2, 0]*a[1, 0]+0.1249999998e30*b[0, 2]*b[2, 0]*a[1, 2]+0.1732050801e21*b[0, 2]*b[2, 0]*a[2, 0]+0.9969655114e21*b[0, 2]*b[2, 1]*b[1, 0]-0.8448929178e21*b[0, 2]*b[2, 1]*b[1, 2]+0.1732050802e21*b[0, 2]*b[2, 1]*b[2, 0]-0.8660253908e20*b[0, 2]*b[2, 1]*b[2, 2]-0.1150000000e22*b[0, 2]*b[2, 1]*a[0, 0]+0.5750000000e21*b[0, 2]*b[2, 1]*a[0, 2]+0.6639528096e21*b[0, 2]*b[2, 1]*a[1, 0]-0.3319764049e21*b[0, 2]*b[2, 1]*a[1, 2]-0.6200000000e12*b[0, 2]*b[2, 1]*a[2, 0]-0.2165063465e30*b[0, 2]*b[2, 2]*a[0, 0]+0.1082531732e30*b[0, 2]*b[2, 2]*a[0, 2]+0.1249999974e30*b[0, 2]*b[2, 2]*a[1, 0]-0.6249999876e29*b[0, 2]*b[2, 2]*a[1, 2]-0.8660253820e20*b[0, 2]*b[2, 2]*a[2, 0]+0.2886751339e30*b[1, 0]*b[1, 2]*b[2, 0]-0.1443375645e30*b[1, 0]*b[1, 2]*b[2, 2]-0.1044658198e31*b[1, 0]*b[1, 2]*a[0, 0]+0.5223290991e30*b[1, 0]*b[1, 2]*a[0, 2]+0.6031336920e30*b[1, 0]*b[1, 2]*a[1, 0]-0.3015668461e30*b[1, 0]*b[1, 2]*a[1, 2]-0.5511966128e21*b[1, 0]*b[1, 2]*a[2, 0]-0.9499999983e21*b[1, 0]*b[2, 0]*b[2, 2]+0.5000000002e30*b[1, 0]*b[2, 0]*a[0, 0]-0.2500000001e30*b[1, 0]*b[2, 0]*a[0, 2]-0.2886751347e30*b[1, 0]*b[2, 0]*a[1, 0]+0.1443375675e30*b[1, 0]*b[2, 0]*a[1, 2]+0.1999999999e21*b[1, 0]*b[2, 0]*a[2, 0]-0.5178632795e21*b[1, 0]*b[2, 1]*b[1, 2]+0.2000000000e21*b[1, 0]*b[2, 1]*b[2, 0]-0.9999999929e20*b[1, 0]*b[2, 1]*b[2, 2]+0.2577350271e21*b[1, 0]*b[2, 1]*a[0, 0]-0.1288675135e21*b[1, 0]*b[2, 1]*a[0, 2]-0.1488033873e21*b[1, 0]*b[2, 1]*a[1, 0]+0.7440169378e20*b[1, 0]*b[2, 1]*a[1, 2]-0.8165807531e11*b[1, 0]*b[2, 1]*a[2, 0]-0.2499999988e30*b[1, 0]*b[2, 2]*a[0, 0]+0.1249999994e30*b[1, 0]*b[2, 2]*a[0, 2]+0.1443375666e30*b[1, 0]*b[2, 2]*a[1, 0]-0.7216878336e29*b[1, 0]*b[2, 2]*a[1, 2]-0.9999999907e20*b[1, 0]*b[2, 2]*a[2, 0]+0.4749999988e21*b[1, 2]*b[2, 0]*b[2, 2]-0.2499999998e30*b[1, 2]*b[2, 0]*a[0, 0]+0.1249999999e30*b[1, 2]*b[2, 0]*a[0, 2]+0.1443375672e30*b[1, 2]*b[2, 0]*a[1, 0]-0.7216878364e29*b[1, 2]*b[2, 0]*a[1, 2]-0.9999999982e20*b[1, 2]*b[2, 0]*a[2, 0]-0.9999999984e20*b[1, 2]*b[2, 1]*b[2, 0]+0.4999999937e20*b[1, 2]*b[2, 1]*b[2, 2]+0.5639528091e21*b[1, 2]*b[2, 1]*a[0, 0]-0.2819764046e21*b[1, 2]*b[2, 1]*a[0, 2]-0.3255983061e21*b[1, 2]*b[2, 1]*a[1, 0]+0.1627991531e21*b[1, 2]*b[2, 1]*a[1, 2]+0.3179571668e12*b[1, 2]*b[2, 1]*a[2, 0]+0.1249999979e30*b[1, 2]*b[2, 2]*a[0, 0]-0.6249999893e29*b[1, 2]*b[2, 2]*a[0, 2]-0.7216878241e29*b[1, 2]*b[2, 2]*a[1, 0]+0.3608439123e29*b[1, 2]*b[2, 2]*a[1, 2]+0.4999999891e20*b[1, 2]*b[2, 2]*a[2, 0]+0.2424871127e12*b[2, 0]*b[2, 1]*b[2, 2]-0.3464101619e21*b[2, 0]*b[2, 1]*a[0, 0]+0.1732050810e21*b[2, 0]*b[2, 1]*a[0, 2]+0.2000000002e21*b[2, 0]*b[2, 1]*a[1, 0]-0.1000000002e21*b[2, 0]*b[2, 1]*a[1, 2]-0.1385640646e12*b[2, 0]*b[2, 1]*a[2, 0]+0.1039230484e22*b[2, 0]*b[2, 2]*a[0, 0]-0.5196152421e21*b[2, 0]*b[2, 2]*a[0, 2]-0.5999999998e21*b[2, 0]*b[2, 2]*a[1, 0]+0.3000000001e21*b[2, 0]*b[2, 2]*a[1, 2]+0.4156921934e12*b[2, 0]*b[2, 2]*a[2, 0]+0.1732050805e21*b[2, 1]*b[2, 2]*a[0, 0]-0.8660254025e20*b[2, 1]*b[2, 2]*a[0, 2]-0.9999999985e20*b[2, 1]*b[2, 2]*a[1, 0]+0.4999999996e20*b[2, 1]*b[2, 2]*a[1, 2]+0.6928203188e11*b[2, 1]*b[2, 2]*a[2, 0]-0.4330127000e21*b[2, 2]^2*a[0, 0]+0.2165063500e21*b[2, 2]^2*a[0, 2]+0.2499999989e21*b[2, 2]^2*a[1, 0]-0.1249999995e21*b[2, 2]^2*a[1, 2]-0.1732050796e12*b[2, 2]^2*a[2, 0]+0.2000000000e21*a[1, 1]*b[0, 0]-0.1000000000e21*a[1, 1]*b[0, 2]-0.1154700538e21*a[1, 1]*b[1, 0]+0.5773502700e20*a[1, 1]*b[1, 2]+0.8000000000e11*a[1, 1]*b[2, 0]+0.8000000000e11*a[1, 1]*b[2, 1]-0.2000000000e12*a[1, 1]*b[2, 2]+0.5000000000e21*a[2, 2]*b[0, 0]-0.2500000000e21*a[2, 2]*b[0, 2]-0.2886751346e21*a[2, 2]*b[1, 0]+0.1443375675e21*a[2, 2]*b[1, 2]+0.2000000000e12*a[2, 2]*b[2, 0]+0.2000000000e12*a[2, 2]*b[2, 1]-0.5000000000e12*a[2, 2]*b[2, 2]+0.5000000000e21*b[0, 0]^2*a[2, 2]-0.5000000000e21*b[0, 0]*b[0, 2]*a[2, 2]-0.5773502692e21*b[0, 0]*b[1, 0]*a[2, 2]+0.2886751350e21*b[0, 0]*b[1, 2]*a[2, 2]+0.4000000000e12*b[0, 0]*b[2, 0]*a[2, 2]+0.4000000000e12*b[0, 0]*b[2, 1]*a[2, 2]+0.2886751346e21*b[0, 2]*b[1, 0]*a[2, 2]-0.1443375675e21*b[0, 2]*b[1, 2]*a[2, 2]-0.2000000000e12*b[0, 2]*b[2, 0]*a[2, 2]-0.2000000000e12*b[0, 2]*b[2, 1]*a[2, 2]-0.1666666669e21*b[1, 0]*b[1, 2]*a[2, 2]-0.2309401077e12*b[1, 0]*b[2, 0]*a[2, 2]-0.2309401077e12*b[1, 0]*b[2, 1]*a[2, 2]+0.1154700540e12*b[1, 2]*b[2, 0]*a[2, 2]+0.1154700540e12*b[1, 2]*b[2, 1]*a[2, 2]+160.*b[2, 0]*b[2, 1]*a[2, 2]+0.1250000000e21*b[0, 2]^2*a[2, 2]+0.1666666667e21*b[1, 0]^2*a[2, 2]+0.4166666678e20*b[1, 2]^2*a[2, 2]+80.*b[2, 0]^2*a[2, 2]+80.*b[2, 1]^2*a[2, 2]+0.6666666667e20*a[1, 1]*b[1, 0]^2-0.1333333333e21*b[1, 1]*b[1, 0]^2+0.2000000000e21*a[1, 1]*b[0, 0]^2-0.4000000000e21*b[1, 1]*b[0, 0]^2+0.5000000000e20*a[1, 1]*b[0, 2]^2-0.1000000000e21*b[1, 1]*b[0, 2]^2-0.2000000000e21*b[0, 0]*a[1, 1]*b[0, 2]-0.2309401077e21*b[0, 0]*a[1, 1]*b[1, 0]+0.1154700540e21*b[0, 0]*a[1, 1]*b[1, 2]+0.1600000000e12*b[0, 0]*a[1, 1]*b[2, 0]+0.1600000000e12*b[0, 0]*a[1, 1]*b[2, 1]-0.4000000000e12*b[0, 0]*a[1, 1]*b[2, 2]-0.1000000000e13*b[0, 0]*a[2, 2]*b[2, 2]+0.4000000000e21*b[0, 0]*b[1, 1]*b[0, 2]+0.4618802154e21*b[0, 0]*b[1, 1]*b[1, 0]-0.2309401080e21*b[0, 0]*b[1, 1]*b[1, 2]-0.3200000000e12*b[0, 0]*b[1, 1]*b[2, 0]+0.6000000000e12*b[0, 0]*b[1, 1]*b[2, 2]-0.4000000000e21*b[0, 0]*b[1, 1]*a[0, 0]+0.2000000000e21*b[0, 0]*b[1, 1]*a[0, 2]+0.2309401077e21*b[0, 0]*b[1, 1]*a[1, 0]-0.1154700539e21*b[0, 0]*b[1, 1]*a[1, 2]-0.1600000000e12*b[0, 0]*b[1, 1]*a[2, 0]+0.1154700538e21*b[0, 2]*a[1, 1]*b[1, 0]-0.5773502700e20*b[0, 2]*a[1, 1]*b[1, 2]-0.8000000000e11*b[0, 2]*a[1, 1]*b[2, 0]-0.8000000000e11*b[0, 2]*a[1, 1]*b[2, 1]+0.2000000000e12*b[0, 2]*a[1, 1]*b[2, 2]+0.5000000000e12*b[0, 2]*a[2, 2]*b[2, 2]-0.2309401077e21*b[0, 2]*b[1, 1]*b[1, 0]+0.1154700540e21*b[0, 2]*b[1, 1]*b[1, 2]+0.1600000000e12*b[0, 2]*b[1, 1]*b[2, 0]-0.3000000000e12*b[0, 2]*b[1, 1]*b[2, 2]+0.2000000000e21*b[0, 2]*b[1, 1]*a[0, 0]-0.1000000000e21*b[0, 2]*b[1, 1]*a[0, 2]-0.1154700538e21*b[0, 2]*b[1, 1]*a[1, 0]+0.5773502696e20*b[0, 2]*b[1, 1]*a[1, 2]+0.8000000000e11*b[0, 2]*b[1, 1]*a[2, 0]-0.6666666676e20*b[1, 0]*a[1, 1]*b[1, 2]-0.9237604307e11*b[1, 0]*a[1, 1]*b[2, 0]-0.9237604307e11*b[1, 0]*a[1, 1]*b[2, 1]+0.2309401077e12*b[1, 0]*a[1, 1]*b[2, 2]+0.5773502692e12*b[1, 0]*a[2, 2]*b[2, 2]+0.1333333335e21*b[1, 0]*b[1, 1]*b[1, 2]+0.1847520861e12*b[1, 0]*b[1, 1]*b[2, 0]-0.3464101615e12*b[1, 0]*b[1, 1]*b[2, 2]+0.2309401077e21*b[1, 0]*b[1, 1]*a[0, 0]-0.1154700538e21*b[1, 0]*b[1, 1]*a[0, 2]-0.1333333333e21*b[1, 0]*b[1, 1]*a[1, 0]+0.6666666672e20*b[1, 0]*b[1, 1]*a[1, 2]+0.9237604307e11*b[1, 0]*b[1, 1]*a[2, 0]+0.4618802160e11*b[1, 2]*a[1, 1]*b[2, 0]+0.4618802160e11*b[1, 2]*a[1, 1]*b[2, 1]-0.1154700540e12*b[1, 2]*a[1, 1]*b[2, 2]-0.2886751350e12*b[1, 2]*a[2, 2]*b[2, 2]-0.9237604320e11*b[1, 2]*b[1, 1]*b[2, 0]+0.1732050810e12*b[1, 2]*b[1, 1]*b[2, 2]-0.1154700540e21*b[1, 2]*b[1, 1]*a[0, 0]+0.5773502700e20*b[1, 2]*b[1, 1]*a[0, 2]+0.6666666676e20*b[1, 2]*b[1, 1]*a[1, 0]-0.3333333340e20*b[1, 2]*b[1, 1]*a[1, 2]-0.4618802160e11*b[1, 2]*b[1, 1]*a[2, 0]+64.*b[2, 0]*a[1, 1]*b[2, 1]-160.*b[2, 0]*a[1, 1]*b[2, 2]-400.*b[2, 0]*a[2, 2]*b[2, 2]+240.*b[2, 0]*b[1, 1]*b[2, 2]-0.1600000000e12*b[2, 0]*b[1, 1]*a[0, 0]+0.8000000000e11*b[2, 0]*b[1, 1]*a[0, 2]+0.9237604307e11*b[2, 0]*b[1, 1]*a[1, 0]-0.4618802157e11*b[2, 0]*b[1, 1]*a[1, 2]-64.*b[2, 0]*b[1, 1]*a[2, 0]-160.*b[2, 1]*a[1, 1]*b[2, 2]-400.*b[2, 1]*a[2, 2]*b[2, 2]-0.1600000000e12*b[2, 1]*b[1, 1]*b[0, 0]+0.8000000000e11*b[2, 1]*b[1, 1]*b[0, 2]+0.9237604307e11*b[2, 1]*b[1, 1]*b[1, 0]-0.4618802160e11*b[2, 1]*b[1, 1]*b[1, 2]-64.*b[2, 1]*b[1, 1]*b[2, 0]+80.*b[2, 1]*b[1, 1]*b[2, 2]-0.1600000000e12*b[2, 1]*b[1, 1]*a[0, 0]+0.8000000000e11*b[2, 1]*b[1, 1]*a[0, 2]+0.9237604307e11*b[2, 1]*b[1, 1]*a[1, 0]-0.4618802157e11*b[2, 1]*b[1, 1]*a[1, 2]-64.*b[2, 1]*b[1, 1]*a[2, 0]+0.4000000000e12*b[2, 2]*b[1, 1]*a[0, 0]-0.2000000000e12*b[2, 2]*b[1, 1]*a[0, 2]-0.2309401077e12*b[2, 2]*b[1, 1]*a[1, 0]+0.1154700539e12*b[2, 2]*b[1, 1]*a[1, 2]+160.*b[2, 2]*b[1, 1]*a[2, 0]+0.1666666671e20*a[1, 1]*b[1, 2]^2-0.3333333343e20*b[1, 1]*b[1, 2]^2+32.*a[1, 1]*b[2, 0]^2-64.*b[1, 1]*b[2, 0]^2+32.*a[1, 1]*b[2, 1]^2+200.*a[1, 1]*b[2, 2]^2+500.*a[2, 2]*b[2, 2]^2-200.*b[1, 1]*b[2, 2]^2+0.6428203230e31*b[0, 0]*b[0, 2]*b[1, 0]-0.4946152426e31*b[0, 0]*b[0, 2]*b[1, 2]+0.8660253998e30*b[0, 0]*b[0, 2]*b[2, 0]-0.4330126915e30*b[0, 0]*b[0, 2]*b[2, 2]-0.4000000000e31*b[0, 0]*b[0, 2]*a[0, 0]+0.2000000000e31*b[0, 0]*b[0, 2]*a[0, 2]+0.2309401077e31*b[0, 0]*b[0, 2]*a[1, 0]-0.1154700539e31*b[0, 0]*b[0, 2]*a[1, 2]-0.2000000000e22*b[0, 0]*b[0, 2]*a[2, 0]-0.3422649732e31*b[0, 0]*b[1, 0]*b[1, 2]+0.9999999986e30*b[0, 0]*b[1, 0]*b[2, 0]-0.4999999940e30*b[0, 0]*b[1, 0]*b[2, 2]-0.6547005380e30*b[0, 0]*b[1, 0]*a[0, 0]+0.3273502690e30*b[0, 0]*b[1, 0]*a[0, 2]+0.3779915319e30*b[0, 0]*b[1, 0]*a[1, 0])/((5000000000.+5000000000.*b[0, 0]-2500000000.*b[0, 2]-2886751346.*b[1, 0]+1443375675.*b[1, 2]+2.*b[2, 0]+2.*b[2, 1]-5.*b[2, 2])*(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0])) = 0, -1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-8*a[2, 2]+2.*a[0, 1]+6.*a[0, 2] = 0, -1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-8*a[2, 2]+2.*a[0, 1]-6.*a[0, 2] = 0, 1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-7*a[2, 2]+2.*a[0, 1]-6.*a[0, 2] = 0, 1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-7*a[2, 2]+2.*a[0, 1]+6.*a[0, 2] = 0, 1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]-3.464101615*b[1, 2]+0.1000000000e-7*b[2, 2] = 0, 1.154700538*b[1, 1]+3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-7*b[2, 2] = 0, a[0, 0]-.5000000000*a[0, 2]-1.*a[1, 0]+.5000000000*a[1, 2]+a[2, 0]-.5000000000*a[2, 2] = 0, -.5000000000*b[0, 2]+.5000000000*b[1, 2]-.5000000000*b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0] = 0, -1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]+3.464101615*b[1, 2]-0.1000000000e-9*b[2, 1]-0.1000000000e-8*b[2, 2] = 0, -1.154700538*b[1, 1]-3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-9*b[2, 1]+0.1000000000e-8*b[2, 2] = 0, a[0, 0]+a[0, 1]+a[0, 2]-1.*a[1, 0]-1.*a[1, 1]-1.*a[1, 2]+a[2, 0]+a[2, 1]+a[2, 2] = 0, a[0, 0]-1.*a[0, 1]+a[0, 2]-1.*a[1, 0]+a[1, 1]-1.*a[1, 2]+a[2, 0]-1.*a[2, 1]+a[2, 2] = 0, b[0, 0]-1.*b[0, 1]+b[0, 2]-1.*b[1, 0]+b[1, 1]-1.*b[1, 2]+b[2, 0]-1.*b[2, 1]+b[2, 2] = 0, b[0, 1]+b[0, 2]-1.*b[1, 1]-1.*b[1, 2]+b[2, 1]+b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0] = 0}, {a[0, 0], a[0, 1], a[0, 2], a[1, 0], a[1, 1], a[1, 2], a[2, 0], a[2, 1], a[2, 2], b[0, 0], b[0, 1], b[0, 2], b[1, 0], b[1, 1], b[1, 2], b[2, 0], b[2, 1], b[2, 2]})

(34)

``


 

Download aisha.mw

The set and list produced by map (see below) contain duplicates.  How to remove duplicates?
 

p := (1+5^(1/2))*(1/2)

1/2+(1/2)*5^(1/2)

(1)

with(Bits)

[And, FirstNonzeroBit, GetBits, Iff, Implies, Join, Nand, Nor, Not, Or, Settings, Split, String, Xor]

(2)

with(LinearAlgebra)

[`&x`, Add, Adjoint, BackwardSubstitute, BandMatrix, Basis, BezoutMatrix, BidiagonalForm, BilinearForm, CARE, CharacteristicMatrix, CharacteristicPolynomial, Column, ColumnDimension, ColumnOperation, ColumnSpace, CompanionMatrix, CompressedSparseForm, ConditionNumber, ConstantMatrix, ConstantVector, Copy, CreatePermutation, CrossProduct, DARE, DeleteColumn, DeleteRow, Determinant, Diagonal, DiagonalMatrix, Dimension, Dimensions, DotProduct, EigenConditionNumbers, Eigenvalues, Eigenvectors, Equal, ForwardSubstitute, FrobeniusForm, FromCompressedSparseForm, FromSplitForm, GaussianElimination, GenerateEquations, GenerateMatrix, Generic, GetResultDataType, GetResultShape, GivensRotationMatrix, GramSchmidt, HankelMatrix, HermiteForm, HermitianTranspose, HessenbergForm, HilbertMatrix, HouseholderMatrix, IdentityMatrix, IntersectionBasis, IsDefinite, IsOrthogonal, IsSimilar, IsUnitary, JordanBlockMatrix, JordanForm, KroneckerProduct, LA_Main, LUDecomposition, LeastSquares, LinearSolve, LyapunovSolve, Map, Map2, MatrixAdd, MatrixExponential, MatrixFunction, MatrixInverse, MatrixMatrixMultiply, MatrixNorm, MatrixPower, MatrixScalarMultiply, MatrixVectorMultiply, MinimalPolynomial, Minor, Modular, Multiply, NoUserValue, Norm, Normalize, NullSpace, OuterProductMatrix, Permanent, Pivot, PopovForm, ProjectionMatrix, QRDecomposition, RandomMatrix, RandomVector, Rank, RationalCanonicalForm, ReducedRowEchelonForm, Row, RowDimension, RowOperation, RowSpace, ScalarMatrix, ScalarMultiply, ScalarVector, SchurForm, SingularValues, SmithForm, SplitForm, StronglyConnectedBlocks, SubMatrix, SubVector, SumBasis, SylvesterMatrix, SylvesterSolve, ToeplitzMatrix, Trace, Transpose, TridiagonalForm, UnitVector, VandermondeMatrix, VectorAdd, VectorAngle, VectorMatrixMultiply, VectorNorm, VectorScalarMultiply, ZeroMatrix, ZeroVector, Zip]

(3)

with(VectorCalculus)

[`&x`, `*`, `+`, `-`, `.`, `<,>`, `<|>`, About, AddCoordinates, ArcLength, BasisFormat, Binormal, Compatibility, ConvertVector, CrossProduct, Curl, Curvature, D, Del, DirectionalDiff, Divergence, DotProduct, Flux, GetCoordinateParameters, GetCoordinates, GetNames, GetPVDescription, GetRootPoint, GetSpace, Gradient, Hessian, IsPositionVector, IsRootedVector, IsVectorField, Jacobian, Laplacian, LineInt, MapToBasis, Nabla, Norm, Normalize, PathInt, PlotPositionVector, PlotVector, PositionVector, PrincipalNormal, RadiusOfCurvature, RootedVector, ScalarPotential, SetCoordinateParameters, SetCoordinates, SpaceCurve, SurfaceInt, TNBFrame, Tangent, TangentLine, TangentPlane, TangentVector, Torsion, Vector, VectorField, VectorPotential, VectorSpace, Wronskian, diff, eval, evalVF, int, limit, series]

(4)

b := proc (x, w) options operator, arrow; (-1)^GetBits(x, w, output = number) end proc

proc (x, w) options operator, arrow; (-1)^Bits:-GetBits(x, w, output = number) end proc

(5)

l := proc (x, t, u, v) options operator, arrow; frac(x)*Vector([b(floor(x), 0)*t, b(floor(x), 1)*u, b(floor(x), 2)*v])+(1-frac(x))*Vector([b(floor(x), 0)*v, b(floor(x), 1)*t, b(floor(x), 2)*u]) end proc

proc (x, t, u, v) options operator, arrow; VectorCalculus:-`+`(VectorCalculus:-`*`(frac(x), VectorCalculus:-Vector([VectorCalculus:-`*`(b(floor(x), 0), t), VectorCalculus:-`*`(b(floor(x), 1), u), VectorCalculus:-`*`(b(floor(x), 2), v)])), VectorCalculus:-`*`(VectorCalculus:-`+`(1, VectorCalculus:-`-`(frac(x))), VectorCalculus:-Vector([VectorCalculus:-`*`(b(floor(x), 0), v), VectorCalculus:-`*`(b(floor(x), 1), t), VectorCalculus:-`*`(b(floor(x), 2), u)]))) end proc

(6)

map(l, {0, 1, 2, 3, 4, 5, 6, 7, 8}, 0, 1, p)

{Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian])}

(7)

map(l, [0, 1, 2, 3, 4, 5, 6, 7, 8], 0, 1, p)

[Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian])]

(8)

q := ListTools:-MakeUnique(%)

q := [Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian])]

(9)

Equal(q[1], q[9])

true

(10)

qq := [op({q[]})]

qq := [Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = -1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = -1/2-(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian]), Vector(3, {(1) = 1/2+(1/2)*5^(1/2), (2) = 0, (3) = 1}, attributes = [coords = cartesian])]

(11)

LinearAlgebra:-Equal(qq[1], qq[5])

true

(12)

NULL


 

Download cp.mw

 

Hi, I would like to plot multiple curves with arrows pointed at each curve. I don't know how to plot the arrows with values. A similar figure is attached. Thanks for helping . . .

Hi there,

I have a function X that I am trying to plot a phase portrait for against it's derivative dX/dt. I currently have the code:

plot([X,diff(X,t),t=0..10],numpoints=1000) 

which sketches a graph but does not give any arrows to indicate direction.

Could anybody help?

 

Many thanks

Hi there,

I have a function defined as:

U:=-[0.25*exp(1/2*epsilon*t)*(1/v^2-1+exp(epsilon*t))^(-0.5)]*sin(4*t)

which I am trying to plot on a 2D graph of axes (t,u(t)).

In the specific case I have epsilon=1/10 and v=2

When I try plot(U), maple returns the error message:

 

Warning, unable to evaluate the function to numeric values in the region; see the plotting command's help page to ensure the calling sequence is correct

 

Could anybody help me out please?

Many thanks


 

 

Hi there,

I have an ode that I want to plot, I am trying to plot 2 different graphs on one graph and have tried using display but cannot seem to add a legend to it. Someone suggested adding a legend to each individual graph before combining them but I cannot find out how to add a legend to a DEplot. My code is as follows:

 

ode:=diff(u(t),t$2)-0.1*(1-64*u(t)^2)*diff(u(t),t$1)+16*u(t)=0

Q1:=v/4*sin(4*t)+epsilon*(1/8*(v-v^3)*t*sin(4*t)+v^3/128*(cos(4*t)-cos(12*t)))

A:=DEplot(ode,u(t),t=0..10, [[u(0)=0, D(u)(0)=v]], u=-0.5..0.5, linecolor=black, linestyle=dash, title="Numerical Solution"):

B:=plot(Q1, t=0..10, u=-0.5..0.5,color=blue, legend="Regular Perturbation Expansion"):

display([A,B],title="Comparing the regular perturbation expansion to the numerical solution")

 

Many thanks

Good day everyone,

I'm relatively new to Maple, and I study engineering (not maths), so maybe my problem is related to a bad approach of the equations.

The problem is that I'm asking Maple to do a double integral of a "complex" expression and it only solve the first integral, but not the second.

Here is the code:

https://www.dropbox.com/home/C%C3%81LCULO%20FUERZAS

Thanks.

Dears!

Hope everyone should be fine. I am face to import excel sheet in maple. I saved execl sheet with name "Employees.xlsx" at desktop. When I use the following command
S := Import("Employees.xlsx", 1, "A1:B101");

I got the following error. 

"Error, (in ExcelTools:-Import) Could not open the file"

Please help me to fix this problem. I am waiting positive response. 

Special request to:

@Carl Love
@Preben Alsholm
@acer

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