abcd

Many accounts with the same e-mail addre...

Asked: abcd 45 Product: MaplePrimes

June 04 2016

1 0

I found useful to use the email address of a relative I live with, to create my own account on Maple Primes.
But I have just realized that his own account has disappeared.

Is there a way to have two differents accounts with the same email address ???

If not I will create my own account on my private email addresss

Sorry for the mess

Use of advanced search...

Asked: abcd 45 Products: Maple , MapleSim Add-Ons

May 31 2016

0 2

Hi all,

Is it possible, and how, to disable the automatic completion in the "Advanced Search / keyword" field ?

Underlying this question is my looking for informations about cmaple (beyond what the help page displays : if I can't find any I will ask some specific ones later). But every time I type "cmaple" in the keyword textfield, it is replaced by "campée" (which is a french word ... I guess english people will obtain something different)

How to remove an index from a table?...

Asked: abcd 45 Product: Maple

May 23 2016

2 2

I would like to remove from a table, the index that verifies some constraint.

For example :

restart:
a := table([1=c, 2=g, 3=y]);

for k in [indices(a, `nolist`)] do
if is(k, even) then
a[k] := 'a[k]':
end if:
end do:

# This does not work as expected
eval(a);

I have found this workaround

b := map(u -> if `not`(is(u, even)) then u=a[u] end if, [indices(a, `nolist`)]);
eval(b);

But is there a way to force Maple to evaluate k to 2 before it "unevaluate" 'a[k]' ?

How to define an abstract operator 'Math...

Asked: abcd 45 Product: Maple

May 20 2016

1 11

Hi,
I would like to present you a recurring problem of mine.

Context:

It is very common, in Modeling and Simulation activities, to account for Uncertainties.

In order to set these ideas down, consider a computational code F (typically a code that solves a set of PDEs in space (M) and time (t) ) and its response Y = F(M,t) (here Y is a short for Y(M,t)).

This response Y usually depends also on some set P of parameters (each of them considered as a scalar quantity) .
A more convenient way to note Y is Y(M, t | P) where the "|" character is used here to express that Y is considered as a function of M and t for each given value of P.
Generally one does not consider Y as a whole but more often one focuses on some quantity of interest (Q) derived from Y through applying it some operator G (for example the operator max(Y) over some space and time domain).

Applying G generally makes Q to appear as a function of P alone.
In Uncertainty Quantification activities, a major concern is to understand how uncertainties about P modify the values of Q ?
The classical framework is to consider P as a (multi-dimensionnal) random variable.
One of the most common problems is then to assess some basic characteristics of Q, where Q is considered as a function of P (a quick and notional notation is Q = H(P) = (G°F)(X, t | P)).

The simpler and faster method to do this is based on a Taylor expansion of H (provided some conditions hold) arround some particular point p* (p* could be the mean of the multi-dimensional distribution of P)
One writes, for every value p of P :

Q = H(p) = H(p*) + (H')^t (p-p*) + 1/2 (p-p*)^t H" (p-p*) ...

where
H' is the gradient vector of H according to P at point P = p*
H" is the hessian matrix of H according to P at point P = p*
(p-p*) is the vector of differences, assumed to be "small"

Let E the usual "mathematical expectation" operator.
Let us assume p* denotes the mean of P.
Then, applying E to the previous formula gives :

E(Q) = E(H(p*)) + E(...) + ....

Assuming some conditions hold, the first order mathematical expectation E(Q) of Q is simply E(H(p*)) = H(p*) = H(E(P))

Some little algebra gives the first order approximation of the variance V(Q) = E(Q^2)-(E(Q))^2 of Q :

V(Q) = (H')^tV(P) H' where V(P) is the variance matrix of P

-----------------------------------------------------------------------------------------------------------------------

Problem

I would like to define the operator E so that I could derive automatically approximations of the first 4 moments of Q, up to any desired order.
In particular, order 2 is often necessary as soon as (G°F) is highly non linear regarding P ; and estimations of the 3rd and 4th moments is of great help to determine how much symetric or flat is the distribution of Q.

The idea is to define an operator E with suitable properties and to apply it to a multivariate taylor expansion of Q^n where n is any positive integer

I tried to do this by my own (look to the supplied .mw file) but I do not have sufficient skill in Maple to complete the job.

Could someone help me ?

Even if I am not qualified in saying this, I believe that this type of approximation of the different moments of Q could be included in a future release of Maple ?

Thanks in advance

Download MathematicalExpectation.mw

Can we trust Maple?...

Asked: abcd 45

April 03 2016

4 48

>

# CAN WE TRUST MAPLE ?
#
# I want to solve numerically systems of ordinary differential equations (ODE)
#
# File "MC.m" below contains an example of one of them (a second degree ODE
# reduced to a couple of 2 first order ODEs ; details about these equations
# are of no importane here).
#
# I am going to show you a very disturbing behaviour of MAPLE ...
#

restart:
with(plots):

read "/Users/marcsancandi/Desktop/MAPLE++SCILAB/BUG-LSODE/MC.m":

# A very quick look to the ODE system
#
# (0.2345... is the mass of the "moving mass" ; some of you will
# probably recognize the structure of a mass-spring-damper system)
#
# Here again, the detailed expression of the 2 RHSs does not matter
#

map(u -> if is(rhs(u), numeric) then u else lhs(u)=RHS end if, convert(MC, list));

(1)

SOLVER = LSODE[ADAMSFULL]

>	sol := dsolve(MC, numeric, method=lsode[adamsfull]); display( odeplot(sol, [t, X[1](t)], 0..9, color=red, gridlines=true, labels=["", "t"], title="X (red), V (blue)"), odeplot(sol, [t, V[1](t)], 0..9, color=blue) );

>	# Now, for reasons detailled at the end of the worksheet, I do the # following "four stages program" # # # 1/ : capture de list of points odeplot returns aux := plots:-odeplot(sol, [t, V[1](t), X[1](t)], 0..9): ListOfPoints := op(1, op(1, aux)); N := LinearAlgebra:-Dimensions(ListOfPoints)[1];

$ListOfPoints := Vector(4, {(1) = ` 1..201 x 1..3 `*Array, (2) = `Data Type: `*float[8], (3) = `Storage: `*rectangular, (4) = `Order: `*C_order})$

(2)

>	# 2/ : Extract from ListOfPoints the ones close to t=8 seconds AllTheTimes := convert(ListOfPoints[..,1], list): GoodRows := zip((u,v)-> if verify(u, 7.8..8.2, `interval`) then v end if, AllTheTimes, [seq(1..N)]);

(3)

>

# 3/ : print the extract of ListOfPoints for GoodRows only

printf("\n What odeplot gives\n");
printf("------------------------------------------------\n");
printf(" t V(t) X(t)\n");
printf("------------------------------------------------\n");

for k in GoodRows do
printf("%-15.12f %-15.12f %-15.12f\n", seq(ListOfPoints[k,n], n=1..3))
end do;
print():

What odeplot gives
------------------------------------------------
t V(t) X(t)

------------------------------------------------
7.830000000000   0.002817384181   0.006597587127
7.875000000000   0.002964569411   0.006727757784
7.920000000000   0.003166704318   0.006865745263
7.965000000000   0.003385619552   0.007013165777
8.010000000000   0.003558854571   0.007170093728
8.055000000000   0.003842118974   0.007336171867
8.100000000000   0.004302831211   0.007517231266
8.145000000000   0.003951552171   0.007708525735
8.190000000000   0.003970924524   0.007886798955

(4)

>

# 4/ Now evaluate "pointwise" sol(t) for the times retained

print();
printf("\n What sol(t) gives for the same values of t\n");
printf("------------------------------------------------\n");
printf("        t               V(t)           X(t)\n");
printf("------------------------------------------------\n");

for MyTime in ListOfPoints[GoodRows, 1] do
   MySol := map(u -> rhs(u), sol(MyTime)):
   printf("%-15.12f %-15.12f %-15.12f\n", seq(MySol[n], n=1..3))
end do:
print():

What sol(t) gives for the same values of t
------------------------------------------------
        t               V(t)           X(t)
------------------------------------------------
7.830000000000   0.000000000000   0.000987586956
7.875000000000   0.004000359093   0.001166940047
7.920000000000   0.004016468258   0.001347371362
7.965000000000   0.004032379719   0.001528593353
8.010000000000   0.004048109517   0.001710597919
8.055000000000   0.004063691706   0.001893215210
8.100000000000   0.004079090715   0.002076599938
8.145000000000   0.004094338959   0.002260632651
8.190000000000   0.004109918301   0.002445352658

(5)

>	# observe the differences between this table and the previous one !!!

>

# So ... what does the completely reconstructed "pointwise curve" look like ?
# ... case of X alone

PointwiseCurve := []:
for MyTime in ListOfPoints[.., 1] do
   MySol          := map(u -> rhs(u), sol(MyTime))[[1,3]]:
   PointwiseCurve := [op(PointwiseCurve), MySol];
end do:

display(
  odeplot(sol, [t, X[1](t)], 0..9, color=red, gridlines=true),
  PLOT(POINTS(PointwiseCurve))
);

>	# Astonishing : the odeplot and the pointwise ona are exactly the same ! # # Let's make a zoom around t=8 display( odeplot(sol, [t, X[1](t)], 0..9, color=red, gridlines=true, view=[7.5..8.5, 0.006..0.009]), PLOT(POINTS(PointwiseCurve), VIEW(7.5..8.5, 0.006..0.009)) );

>	# Do you see that X(8.1) is close to 0.0075 ? # Yes ? # Are you sure ? # Let's ask for a confirmation ... sol(8.1);

(6)

>

# Conclusion :
#
# MAPLE is MAGIC !!!
#
# REMARK : Have you seen the answer for X[1](t) is the initial value of X[1](0) ?
#          (see top of worksheet)
#
#
# You don't believe me ... ABRACABADRA
# ... and look to the values of sol(8.1) left to the stars
#

ListOfTimes := [1.0, 8.1, 10.0, 8.1, 1.0, 8.1, 10.0, 8.1]:
printf("------------------------------------------------\n");
printf("   t          V(t)            X(t)\n");
printf("------------------------------------------------\n");

k := 0:
for MyTime in ListOfTimes do
   k     := k+1:
   MySol := map(u -> rhs(u), sol(MyTime)):
   if is(k, odd) then
      printf("%6.3f %-15.12f %-15.12f\n", MyTime, seq(MySol[n], n=2..3))
   else
      printf("%6.3f %-15.12f %-15.12f ***\n", MyTime, seq(MySol[n], n=2..3))
   end if:
end do:

------------------------------------------------

   t          V(t)            X(t)
------------------------------------------------
1.000 0.000000000000   0.000987586956
8.100 0.004283834684   0.007512460823   ***

10.000 0.004613814863   0.015687722648
8.100 0.000000000000   0.000987586956   ***
1.000 0.000000000000   0.000987586956

8.100 0.004283834684   0.007512460823   ***
10.000 0.004613814863   0.015687722648
8.100 0.000000000000   0.000987586956   ***

>	# In fact the value of sol(8.1) depends on the value T had during # the previous evaluation sol(T). # Which suggests that, maybe, some global variable has not been # properly erased when sol(..) is evaluated (?)

SOLVER = RKF45 (slower)

>

# Let's do the same operations after replacing lsode by rkf45
#

restart:
with(plots):

read "/Users/marcsancandi/Desktop/MAPLE++SCILAB/BUG-LSODE/MC.m":
sol := dsolve(MC, numeric, method=rkf45, maxfun=500000);

display(
odeplot(sol, [t, X[1](t)], 0..9, color=red, gridlines=true, labels=["", "t"], title="X (red), V (blue)"),
odeplot(sol, [t, V[1](t)], 0..9, color=blue)
);

>	# (Visual) comparison with the previous curves provides a very good agreement

>

# 1/ : capture de list of points odeplot returns

aux          := plots:-odeplot(sol, [t, V[1](t), X[1](t)], 0..9):
ListOfPoints := op(1, op(1, aux)):
N            := LinearAlgebra:-Dimensions(ListOfPoints)[1]:

# 2/ : Extract from LisrOfPoints the ones close to t=8 seconds

AllTheTimes := convert(ListOfPoints[..,1], list):
GoodRows    := zip((u,v)-> if verify(u, 7.8..8.2, `interval`) then v end if, AllTheTimes, [seq(1..N)]):

# 3/ : print the extract of ListOfPoints for GoodRows only

printf("\n What odeplot gives\n");
printf("------------------------------------------------\n");
printf("        t               V(t)           X(t)\n");
printf("------------------------------------------------\n");

for k in GoodRows do
   printf("%-15.12f %-15.12f %-15.12f\n", seq(ListOfPoints[k,n], n=1..3))
end do;
print():

What odeplot gives
------------------------------------------------
        t               V(t)           X(t)
------------------------------------------------
7.830000000000   0.002815865032   0.006594922503
7.875000000000   0.002960849581   0.006724509859
7.920000000000   0.003162952386   0.006862303055
7.965000000000   0.003381243400   0.007009462432
8.010000000000   0.003556187082   0.007165994538
8.055000000000   0.003835074137   0.007331726709
8.100000000000   0.004281464768   0.007511890647
8.145000000000   0.003952037325   0.007703617600
8.190000000000   0.003971371977   0.007881895231

(7)

>

# Observe these results are very similar to those obtained with lsode
#
# But what are the results I obtaine by pointwise evaluations of
# sol(t) for t in 7.8..8.2 ???
#
# 4/ Now evaluate "pointwise" sol(t) for the times retained

print();
printf("\n What sol(t) gives for the same values of t\n");
printf("------------------------------------------------\n");
printf("        t               V(t)           X(t)\n");
printf("------------------------------------------------\n");

for MyTime in ListOfPoints[GoodRows, 1] do
   MySol := map(u -> rhs(u), sol(MyTime)):
   printf("%-15.12f %-15.12f %-15.12f\n", seq(MySol[n], n=1..3))
end do:
print():

What sol(t) gives for the same values of t
------------------------------------------------
t V(t) X(t)
------------------------------------------------

7.830000000000   0.002815850376   0.006594922415
7.875000000000   0.002960860137   0.006724509763
7.920000000000   0.003162950433   0.006862302956
7.965000000000   0.003381213356   0.007009462330
8.010000000000   0.003556219238   0.007165994431
8.055000000000   0.003835077964   0.007331726592

8.100000000000   0.004281482695   0.007511890548
8.145000000000   0.003952038054   0.007703617628
8.190000000000   0.003971371542   0.007881895259

(8)

>

ListOfTimes := [1.0, 8.1, 10.0, 8.1, 1.0, 8.1, 10.0, 8.1]:

printf("------------------------------------------------\n");
printf("   t          V(t)            X(t)\n");
printf("------------------------------------------------\n");

k := 0:
for MyTime in ListOfTimes do
   k     := k+1:
   MySol := map(u -> rhs(u), sol(MyTime)):
   if is(k, odd) then
      printf("%6.3f %-15.12f %-15.12f\n", MyTime, seq(MySol[n], n=2..3))
   else
      printf("%6.3f %-15.12f %-15.12f ***\n", MyTime, seq(MySol[n], n=2..3))
   end if:
end do:

------------------------------------------------
t V(t) X(t)
------------------------------------------------

1.000 0.001763825587 0.001540242179

8.100 0.004281482695 0.007511890548 ***

10.000 0.004614016677 0.015687242808

8.100 0.004281482695 0.007511890548 ***

1.000 0.001763825587 0.001540242179

8.100 0.004281482695 0.007511890548 ***

10.000 0.004614016677 0.015687242808

8.100 0.004281482695 0.007511890548 ***

>

# Wow, these two tables give very close results (at least if you don't look
# farther than the tenth decimal position ... which could probably change
# by fixing Digits to 15 or 20 (?) ... even if this hypothesis is not
# fully satisfactory ?)
#
# Here pointwise evaluations of sol(t) always give the correct answer (up to
# the decimal representation induced by the default value of Digits).
#
#
#------------------------------------------------------------------------
#
# Question : why the "magics" no longer operate with rkf45 ?
# (of course it is humor at the second degree !)
#
#------------------------------------------------------------------------
#
#
# It could be funny to play with "Magic MAPLE".
#
# But I have to solve serious problems, and among them, what interests me
# in the solution of the "MC" system, is "events capturing".
# Example of such an event "event" E_n is "the moving mass has reached the
# position X = S_n where S_n is a given stroke (for exemple S_N = 0.006).
# And "capturing E_n" then means "find the time T_n such that X(T_n) = S_n".
#
# I thus wrote a fixed-point method to do this, that is a procédure that
# repeatedly asks for evaluations of procedure "sol".
# But, for the behaviour depicted above, it doesn't work correctly with lsode.
# So, despite the funny magical behaviour of MAPLE, I have a serious problem !
#
# A problem I can sum up while saying
#
# "I CANNOT TRUST MAPLE WHEN IT SAYS ME sol(t) = xxx"
#
#
# Has anyone already been faced with these kind of behaviour ?
#
# Maplesoft support seems to beat around the bush with me, asking for the
# ODEs equations, or criticizing the expressions of their RHSs ..., wanting
# to see where these equations come from (they come from a more than 10.000
# lines application I have developped, but it's not the point here given
# rkf45 proceeds correctly).
#
# If anyone is interested to investigate this problem, I can provide
# her the "MC.m" file that contains the ODE system used here
#
# Thanks a lot for the time you spent to reading me
#
#

>

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