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This is an application of vector position to better understand the vector speed and acceleration is a well defined vector space. Fully developed with embedded components for proper use.

 

    Vector_Posición.mw                   (in spanish)

 

L. Araujo C.

Physics Pure

Computer Science

With the package VectorCalculus we can study the speed and acceleration to their respective components. Considering the visualizaccion and algebraic calculations and to check with their respective commands. Both 2D and 3D.

 

Velocidad-Aceleració.mw     (in spanish)

 

Lenin Araujo Castillo

Physics Pure

Computer Science

Hi MaplePrime-ers!

I've been using the Maple(17) toolbox in Matlab(2012b) to quickly enumerate systems of equations by: (i) solving them symbolically, (ii) using unapply to make them functions, (iii) then supplying the points (driver equations) to get the system solution.  Speed is a must, because there may be 3 million+ systems to solve.  Symbolics is also very important because I am evaluating topology, so the structure of the equations may change, and therefore a functional approach will not work.

I have had success (seen in the first code snippet).  I would like similiar behaviour in the second code snippet, but sometimes I get 'solutions may be lost' as an error message,  or 'Error, (in unapply) variables must be unique and of type name'

The system of equations include:  Linear equations, 5th order polynomials, absolute functions, and pieceiwse functions.

Here is code with a topology that solves:

#Interconnection Equations
eq2[1] := FD_T + EM2_T = 0;
eq2[2] := ICE_T + GEN_T = 0;
eq2[3] := EM2_A + GEN_A + BAT_A = 0;
eq2[4] := -FD_W + EM2_W = 0;
eq2[5] := -ICE_W + GEN_W = 0;
eq2[6] := -EM2_V + GEN_V = 0;
eq2[7] := -EM2_V + BAT_V = 0;

#ICE
eq_c[1] := ICE_mdot_g=((671.5) + (-21.94)*ICE_T + (0.1942)*ICE_W + (0.5113)*ICE_T^2 + (-0.01271)*ICE_T*ICE_W + ( -0.0008761)*ICE_W^2 + (-0.006071)*ICE_T^3 + (9.867e-07)*ICE_T^2*ICE_W + (5.616e-05)*ICE_T*ICE_W^2 + (1.588e-06)*ICE_W^3 + (3.61e-05)*ICE_T^4 + (8.98e-07)*ICE_T^3*ICE_W + (-2.814e-07)*ICE_T^2*ICE_W^2 + (-8.121e-08)*ICE_T*ICE_W^3 + ( -8.494e-08 )*ICE_T^5 + (-2.444e-09)*ICE_T^4*ICE_W + (-9.311e-10)*ICE_T^3*ICE_W^2 + ( 5.835e-10)*ICE_T^2*ICE_W^3 ) *1/3600/1000 * ICE_T * ICE_W;

#BAT
eq_c[2] := BAT = 271;

#EM2
EM2_ReqPow_eq := (-148.3) + (4.267)*abs(EM2_W) + (12.77)*abs(EM2_T) + (-0.0364)*abs(EM2_W)^2 + ( 1.16)*abs(EM2_W)*abs(EM2_T) + (-0.258)*abs(EM2_T)^2 + ( 0.0001181)*abs(EM2_W)^3 + (-0.0005994)*abs(EM2_W)^2*abs(EM2_T) + ( 0.0001171)*abs(EM2_W)*abs(EM2_T)^2 + (0.001739 )*abs(EM2_T)^3 + (-1.245e-07 )*abs(EM2_W)^4 + ( 1.2e-06)*abs(EM2_W)^3*abs(EM2_T) + ( -1.584e-06)*abs(EM2_W)^2*abs(EM2_T)^2 + ( 4.383e-07)*abs(EM2_W)*abs(EM2_T)^3 + (-2.947e-06)*abs(EM2_T)^4;
eq_c[3] := EM2_P = piecewise( EM2_T = 0, 0, EM2_W = 0, 0, EM2_W*EM2_T < 0,-1 * EM2_ReqPow_eq, EM2_ReqPow_eq);
eq_c[4] := EM2_A = EM2_P/EM2_V;

#GEN
GEN_ReqPow_eq:= (-5.28e-12) + ( 3.849e-14)*abs(GEN_W) + (-71.9)*abs(GEN_T) + (-1.168e-16)*abs(GEN_W)^2 +(1.296)*abs(GEN_W)*abs(GEN_T) + (2.489)*abs(GEN_T)^2 + (1.451e-19)*abs(GEN_W)^3 + (0.0001326)*abs(GEN_W)^2*abs(GEN_T) + (-0.008141)*abs(GEN_W)*abs(GEN_T)^2 + (-0.004539)*abs(GEN_T)^3 +(-6.325e-23)*abs(GEN_W)^4 + (-2.091e-07)*abs(GEN_W)^3*abs(GEN_T) + ( 3.455e-06)*abs(GEN_W)^2*abs(GEN_T)^2 + ( 2.499e-05)*abs(GEN_W)*abs(GEN_T)^3 + (-5.321e-05)*abs(GEN_T)^4;
eq_c[5] := GEN_P = piecewise( GEN_T = 0, 0, GEN_W = 0, 0, GEN_W*GEN_T < 0,-1 * GEN_ReqPow_eq, GEN_ReqPow_eq);
eq_c[6] := GEN_A = GEN_P/GEN_V;

#ASSUMPTIONS
assume(BAT_V::nonnegative);
assume(FD_W::nonnegative);

#FINAL EQUATIONS

sys_eqs2 := convert(eq2,set) union {eq_c[1],eq_c[2],eq_c[3],eq_c[4],eq_c[5],eq_c[6]};

#Selecting which variables to solve for:

drivers2:= { ICE_T,ICE_W,FD_T,FD_W};
symvarnames2:=select(type,indets(convert(sys_eqs2,list)),name);
notdrivers2:=symvarnames2 minus drivers2;


#Symbolic solve

sol2:=solve(sys_eqs2,notdrivers2) assuming real:
symb_sol2:=unapply(sol2,convert(drivers2,list)):


#Enumerate (there will generally be about 40, not 6)

count := 0;
for i1 from 1 to 40 do
     for i2 from 1 to 40 do
          for i3 from 1 to 40 do
               for i4 from 1 to 40 do
                    count := count + 1;
                    solsol2(count) := symb_sol2(i1,i2,i3,i4);
               od;
          od;
     od;
od;
count;



This works great!  I would like simliar output in my second code snippet, but this time with more inputs to symb_sol.  However, if I try and change the interconnection equations a little, and add a piecewise function, and another driver... (differences in bold)

#Interconnection Equations
eq1[1] := FD_T+EM2_T = 0;
eq1[2] := ICE_T+GBb_T = 0;
eq1[3] := GEN_T+GBa_T = 0;
eq1[4] := EM2_A+GEN_A+BAT_A = 0;
eq1[5] := -FD_W+EM2_W = 0;
eq1[6] := -GEN_W+GBa_W = 0;
eq1[7] := -ICE_W+GBb_W = 0;
eq1[8] := -EM2_V+GEN_V = 0;
eq1[9] := -EM2_V+BAT_V = 0;

#ICE
eq_c[1] := ICE_mdot_g=((671.5) + (-21.94)*ICE_T + (0.1942)*ICE_W + (0.5113)*ICE_T^2 + (-0.01271)*ICE_T*ICE_W + ( -0.0008761)*ICE_W^2 + (-0.006071)*ICE_T^3 + (9.867e-07)*ICE_T^2*ICE_W + (5.616e-05)*ICE_T*ICE_W^2 + (1.588e-06)*ICE_W^3 + (3.61e-05)*ICE_T^4 + (8.98e-07)*ICE_T^3*ICE_W + (-2.814e-07)*ICE_T^2*ICE_W^2 + (-8.121e-08)*ICE_T*ICE_W^3 + ( -8.494e-08 )*ICE_T^5 + (-2.444e-09)*ICE_T^4*ICE_W + (-9.311e-10)*ICE_T^3*ICE_W^2 + ( 5.835e-10)*ICE_T^2*ICE_W^3 ) *1/3600/1000 * ICE_T * ICE_W;

#BAT
eq_c[2] := BAT = 271;

#EM2
EM2_ReqPow_eq := (-148.3) + (4.267)*abs(EM2_W) + (12.77)*abs(EM2_T) + (-0.0364)*abs(EM2_W)^2 + ( 1.16)*abs(EM2_W)*abs(EM2_T) + (-0.258)*abs(EM2_T)^2 + ( 0.0001181)*abs(EM2_W)^3 + (-0.0005994)*abs(EM2_W)^2*abs(EM2_T) + ( 0.0001171)*abs(EM2_W)*abs(EM2_T)^2 + (0.001739 )*abs(EM2_T)^3 + (-1.245e-07 )*abs(EM2_W)^4 + ( 1.2e-06)*abs(EM2_W)^3*abs(EM2_T) + ( -1.584e-06)*abs(EM2_W)^2*abs(EM2_T)^2 + ( 4.383e-07)*abs(EM2_W)*abs(EM2_T)^3 + (-2.947e-06)*abs(EM2_T)^4;
eq_c[3] := EM2_P = piecewise( EM2_T = 0, 0, EM2_W = 0, 0, EM2_W*EM2_T < 0,-1 * EM2_ReqPow_eq, EM2_ReqPow_eq);
eq_c[4] := EM2_A = EM2_P/EM2_V;

#GEN
GEN_ReqPow_eq:= (-5.28e-12) + ( 3.849e-14)*abs(GEN_W) + (-71.9)*abs(GEN_T) + (-1.168e-16)*abs(GEN_W)^2 +(1.296)*abs(GEN_W)*abs(GEN_T) + (2.489)*abs(GEN_T)^2 + (1.451e-19)*abs(GEN_W)^3 + (0.0001326)*abs(GEN_W)^2*abs(GEN_T) + (-0.008141)*abs(GEN_W)*abs(GEN_T)^2 + (-0.004539)*abs(GEN_T)^3 +(-6.325e-23)*abs(GEN_W)^4 + (-2.091e-07)*abs(GEN_W)^3*abs(GEN_T) + ( 3.455e-06)*abs(GEN_W)^2*abs(GEN_T)^2 + ( 2.499e-05)*abs(GEN_W)*abs(GEN_T)^3 + (-5.321e-05)*abs(GEN_T)^4;
eq_c[5] := GEN_P = piecewise( GEN_T = 0, 0, GEN_W = 0, 0, GEN_W*GEN_T < 0,-1 * GEN_ReqPow_eq, GEN_ReqPow_eq);
eq_c[6] := GEN_A = GEN_P/GEN_V;

#GB
FiveSpeedGearbox_R := proc(ig)
local i ,eq;
i[1]:=3.32;
i[2]:=2;
i[3]:=1.36;
i[4]:=1.01;
i[5]:=0.82;
eq:= piecewise(ig=1,i[1],ig=2, i[2],ig=3,i[3],ig=4,i[4],ig=5,i[5],1);
return eq(ig);
end proc;


eq_c[7] := GBb_T = -1/GB_R * GBa_T;
eq_c[8] := GBb_W = GB_R * GBa_W;
eq_c[9] := GB_R = FiveSpeedGearbox_R(ig);

 

#System Equations
sys_eqs := convert(eq1,set) union convert(eq_c,set);

 

 #Solve for variables
symvarnames:=select(type,indets(convert(sys_eqs,list)),name);
drivers:= {ig, ICE_T,ICE_W,FD_T,FD_W};
not_drivers := symvarnames minus drivers;

#Assumptinons

assume(BAT_V::nonnegative);
assume(FD_W::nonnegative);

sol:=(solve(sys_eqs,not_drivers) assuming real);

symb_sol:=unapply(sol,convert(drivers,list)): ---> Error, (in unapply) variables must be unique and of type name

Subsequent parts don't work...

count := 0;
for i1 from 1 to 40 do
     for i2 from 1 to 40 do
          for i3 from 1 to 40 do
               for i4 from 1 to 40 do
                    for i5 from 1 to 40 do
                         count := count + 1;
                         solsol2(count) := symb_sol2(i1,i2,i3,i4,5);
                    od;
               od; 
          od;
     od;
od;
count;

While running the last line sol:, 1 of 2 things will happen, depending on the solver. Maple17 will take a long time (30+ minutes) to solve, then report nothing, or sol will solve, but will report "some solutions have been lost".

Afterwards, evaluating symb_sol(0,0,0,0,0) will return a viable solution (real values for each of the variables).  Whereas evaluating symb_sol(0,X,0,0,0), where X <> 0, will return and empty list [].

Does anyone know how to (i) speed up the symbolic solve time?  (ii) Return ALL of the solutions?

 

Thanks in advance for reading this.  I've really no idea why this isn't working.  I've also attached two worksheets with the code: noGB.mw   withGB.mw

 Adam

Greetings to all.

The multiplicative partition function is defined here at Wikipedia and was recently the subject of a discussion at Math Stackexchange.

I posted two solutions to the task of computing this function at the above page that use Maple code. One of them employs the Polya Enumeration Theorem and is of mostly theoretical interest as it cannot be used to effectively compute the function for n with many factors. I posted two additional implementations in order to remedy this defect, one of them in Maple and the other in Perl. I think the Maple implementation is easy enough to read not to require additional commentary. Note, however, that even though the Maple code and the Perl code implement the same algorithm (dynamic programming), the Maple version is dramatically slower than the Perl version and consumes a lot of memory. E.g. Maple takes 58 seconds for the value for 9! and Perl takes 1.5 seconds.

My question is, can someone explain this difference? Note that both are interpreted languages so there is no gain due to potential compilations.

Your commentary is appreciated.

This is with Maple 15 (X86 64 LINUX).

Best regards,

Marko Riedel

Hi,

I have been solving a system of non-linear ODE's for their steady states. This involves solving the rhs of the ODE's =0.

Hence I have been using "solve" in maple to solve a non-linear system.

Recently I have added more detail to the problem and now I am solving eight equations for eight variables and i've left overnight and maple still didnt find a solution. When sigma1=sigma2=0 below the problem is effectively 5-d and maple breezes through the calculation.

Dear Maple users

I am trying to simulate the distribution of Q-values (Karl Peason) in a Contingency table. In that regard I need to use a two dimensional iteration. It require quite a lot of time to perform the computations. Using the values below, it required 1.3 mio iterations and took about 5 minuttes on my computer. My question is if there are ways I can speed it up? It might be using different commands, which are executed faster, performing computations in the...

Multithreading loops...

December 11 2012 vicaut 55

How is it possible to let multiple cores compute a loop faster?

For exaple:

for i = 1 to 1000 do

*computation(i)*

end do

The goal is to let a quad core cpu split the 1000 independant computations in 4 packages of 250 each to speed up the computation by the factor 4 so that core1 computes i from 1 to 250, core2 from 251 to 500 and so on, at the same time. Is this possible?

xsys11demo.mw

The attached worksheet (xsys11demo.mw, first-order non-linear ODE system) is ~x100 (one hundred) times slower that the "same" program in Mathematica 8. Both give the same/satisfactory numerical results and have similar/identical structure (I can supply the Mathematica 8 notebook, if requested).

I assume that my attached worksheet must be sub-optimally programmed and would be grateful...

Hi all

Can anyone suggest ways of speeding up this code ?

div_vec := proc(a::Vector,b::Vector)
# procedure returns the element-byelement
# division of vector a by vector b
local i,c:
c:=Vector(Dimension(a)):
for i from 1 to Dimension(a) do
c[i]:= a[i]/b[i]:
end do:
return c:
end proc:
Thanks
LR

well first of all this site was very useful for doing my homework, but there is still something I didnt find on it and im sure other people may find it useful.

 

I have a system of 5 ode's and 6 initial conditions that ive solved successfully and plotted the graphs i need:  Position VS Time

          Speed VS Time

The only thing I initially know is the final position, which i can read on the first graph and...

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It is a fairly old computer by todays standards ( single...

Hi,

 

I've got a pretty intensive run going on in Maple and I wanted to speed it up. It involves computing every power up to some large number (100,000+) of small matrices (2x2) but with very complicated abstract polynomials inside. There's really no way to speed this up as far as coding is concerned so my only option is to use multithreading, since I need mutiple runs, or run this on some faster server/cloud.

 

1) Multithreading will...

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