Maple Questions and Posts

These are Posts and Questions associated with the product, Maple

seq(x) in the help page:  When x is a sparse Matrix, Vector or rtable, only the nonzero entries are scanned.
Is the statement correct/complete?

V := Vector(6, [11,22,0,44], storage=sparse):
entries(V);
seq(V);

                        [11], [22], [44]
                      11, 22, 44, 0, 0, 0

 

how to find back the system which solution is maxwell equations?

as maxwell equations is an invariant, 

if solution is maxwell which is invariant, how to find back the system which solve it, the solution is maxwell?

will there a multiple systems which solution is maxwell equations?

if can not find, how to enumerate all combinations of systems to search maxwell equations?

How can I plot this fourier transform as a amplitude spectrum?

F(w)=(10/w)*exp(-7iw)*sin(4*w)

I ploted |f(w)| vs w. But it is not the answer. |F(w)|=(10/w)*sin(4*w)

Hi, 

I'm stuck on this problem to which a careful reading of the help pages would probably give an answer:

Why is the return of Array(-1..1, [1$3]) of a different type than the one of Array(-1..1, [0$3]) ?

restart:

B := Array(-1..1,[1$3]);
lprint(B);

B := Array(-1..1, {(1) = 1})

 

Array(-1 .. 1, {-1 = 1, 0 = 1, 1 = 1})

 

B := Array(-1..1,[0$3]);
lprint(B)

B := Array(-1..1, {(1) = 0})

 

Array(-1 .. 1, {})

 

seq(B[n], n=-1..1)

0, 0, 0

(1)

 


 

Download Zero_Array.mw

Hello

I am definitely missing something on how Maple deals with functions and outputs.  I need to define a new function using an output of a previous calculation but I didn't figure out how to do it. 

 

aux := rsolve({y(0) = y0, y(n) = 4*y(n-1)*(1-y(n-1))}, y(n));
solucao := (n,y0)-> aux;
solucao(3,1/2);

Neither n nor y0 are replaced for the given values.  What am I missing?

 

Many thanks

 

Ed

 

Hi

I am trying to compute a limit to demonstrate the link between the binomial and Poisson distribution. (lambda = np)

Thank you for your help

ComplémentCalculSymbolique.mw

Hi,

I try to symbolically calculate the variance of the binomial distribution (np(1-p)), but the result is not simplified

Thanks for your help.

 

ComplémentCalculSymbolique.mw

Hi everybody
I have some problems with fsolve(complex equation). It results some answers (I expect answers in the range 10e6 to 10e11) but substitution them into the main equation leads to numbers of order 10e-8 to 10e8. I know fsolve solves equation numerically, so 10e-8 t0 10e-6 is acceptable, but what about 10e7? How can I handle this problem? I have an Array of this kind of equations to solve and then analyze answers.
How can I increase the speed of calculations? I try to do some parallelization (thanks dohashi for posts about parallel programming) but I couldn't do. I upload the code below.

Thanks.

EQ1 := 1.780876811*10^90*(-(1.857495893*10^(-32)*I)*(-(.9215096529*(-1.077177489*10^(-57)*omega^2+1.251444314*10^(-43)-7.423792254*10^(-74)*omega^4))*(1.042248387*10^(-7)*omega-3.773917830*10^(-22)*omega^3)+1.022012860*10^(-43)-9.365146438*10^(-58)*omega^2+1.290731820*10^(-74)*omega^4+8.072440803*10^(-47)*omega^2*(7.038725244*10^(-13)-9.109383000*10^(-28)*omega^2))*exp(-.9800000000*I-4.717786244*10^(-17)*omega^2)-(1.857495893*10^(-32)*I)*((.9215096529*(5.411991727*10^(-58)*omega^2-1.370413754*10^(-43)+1.063387455*10^(-73)*omega^4))*(1.042248387*10^(-7)*omega-3.773917830*10^(-22)*omega^3)-1.119171234*10^(-43)+3.850718130*10^(-58)*omega^2+1.279097989*10^(-74)*omega^4+1.703871878*10^(-48)*omega^2*(5.154059190*10^(-14)+3.036461000*10^(-28)*omega^2)+8.072440803*10^(-47)*omega^2*(7.038725244*10^(-13)+9.109383000*10^(-28)*omega^2))*exp(.9800000000*I-4.717786244*10^(-17)*omega^2)+2.054040475*10^(-31)*((1.936145393*10^(-59)+1.043762907*10^(-58)*I)*omega^2+4.297601656*10^(-46)-1.690952584*10^(-44)*I+(-1.159596547*10^(-75)+1.164619044*10^(-74)*I)*omega^4)*exp(-4.717786244*10^(-17)*omega^2)*(1.042248387*10^(-7)*omega-3.773917830*10^(-22)*omega^3)+(2.799879047*10^(-71)*I)*(-6.704964363*10^(-12)-3.118737242*10^(-28)*omega^2)*omega*exp(.9800000000*I-1.090999486*10^(-14)*omega^2)-(2.799879047*10^(-71)*I)*(8.281232388*10^(-12)+2.177273887*10^(-28)*omega^2)*omega*exp(-.9800000000*I-1.090999486*10^(-14)*omega^2)+3.476335242*10^(-51)*((.1388433141*I)*(-2.893776471*10^(-25)-1.303697368*10^(-38)*omega^2+7.808106616*10^(-55)*omega^4)+4.959435112*10^(-25)-3.098806468*10^(-39)*omega^2-3.391707726*10^(-55)*omega^4-1.314961283*10^(-30)*(-2.854029409*10^(-11)+1.827522021*10^(-27)*omega^2)*omega^2)*exp(-4.717786244*10^(-17)*omega^2)-2.814230381*10^(-37)*(9.949004410*10^(-35)*(-6.832852706*10^(-13)-1.621609260*10^(-14)*I-(2.889900216*10^(-30)*I)*omega^2-(.9082907587*I)*(8.002616800*10^(-12)-1.954522389*10^(-30)*omega^2)-(.4487255373*I)*(9.612550267*10^(-12)+9.109383000*10^(-28)*omega^2)+4.081082866*10^(-29)*omega^2)*exp(-1.090999486*10^(-14)*omega^2)-1.995292057*10^(-54)*omega)*omega)/omega^2

Test_MaplePrime971127.mw

Hi,

I’m looking for a MathApps or animation of  Galton Board ’s experiment ( statistics distributions). Any ldeas?

Thanks

Hi there. Thank you all in advanced.

The general question is how to pass a pair of values to a list of functions that expect that pair of values as input.
I already know this solution for passing a list of values to a list of functions that expect one value as input.

map(eval~,[f(x),g(x)],x=~[p,q,t])

Well f(x) and g(x) take every element of the list, but what if f(x) and g(x) expect two values. The concrete case is to pass p and q to iquo and irem. The following were my tries:

  • map(eval~,[iquo(x),irem(x)],x=[p,q])
  • map(eval~,[iquo(x),irem(x)],x=(p,q))
  • map(eval~,[iquo(op(x)),irem(op(x))],x=[p,q])

I searched and found some partial related topics in the site but not quite with this approach.

 

Hello,

How do I tell maple which branch to choose when calculating an asymptotic series of a RootOf expression. e.g.

restart;

sol:=RootOf((8*n-8)*_Z^6+(n^4+36*n^2-68*n+56)*_Z^5+(n^5+10*n^4+80*n^3-200*n^2+224*n-152)*_Z^4+(n^6+28*n^5+69*n^4-268*n^3+468*n^2-356*n+200)*_Z^3+(3*n^7+32*n^6+7*n^5-204*n^4+380*n^3-544*n^2+272*n-128)*_Z^2+(3*n^8+14*n^7-20*n^6-32*n^5+252*n^4-240*n^3+304*n^2-80*n+32)*_Z-n^9-12*n^8-44*n^7-40*n^6-4*n^5-128*n^4+48*n^3-64*n^2);

asympt(sol,n,2);

 

Now the series contains RootOf(_Z^6-_Z^5) which occurs in the denominator to order 1/n and thus blows up if 0 is chosen. I know that the solution must be greater zero and smaller than n/2.

how I can remove this error in dsolve?

Error, (in dsolve/numeric/bvp) singularity encountered
dsolv.mw

Given these functions identify their symmetries:

a) f(x)=4x^2-1/2

b)s(t)=t^3-4t

c) g(k)=-|2k-7|

d) x-y^2=3

e) h(a)=1/a-1

It is my pleasure to announce the return of the Maple Conference! On October 15-17th, in Waterloo, Ontario, Canada, we will gather a group of Maple enthusiasts, product experts, and customers, to explore and celebrate the different aspects of Maple.

Specifically, this conference will be dedicated to exploring Maple’s impact on education, new symbolic computation algorithms and techniques, and the wide range of Maple applications. Attendees will have the opportunity to learn about the latest research, share experiences, and interact with Maple developers.

In preparation for the conference we are welcoming paper and extended abstract submissions. We are looking for presentations which fall into the broad categories of “Maple in Education”, “Algorithms and Software”, and “Applications of Maple” (a more extensive list of topics can be found here).

You can learn more about the event, plus find our call-for-papers and abstracts, here: https://www.maplesoft.com/mapleconference/

Hi,

I am trying to curve fit data using NLPSolve. I noticed that the evaluation time for NLPSolve seems really long. Did I mess up in using NLPSolve? 

 

Thanks you for any suggests or comments.
 

restart; kernelopts(version); interface(version); multithread_capability := kernelopts(multithreaded); Number_of_CPUs := kernelopts(numcpus)
NULL

8

(1)

``

``

"#` How` can I decrease the evaluation time of NLPSolve or are there better methods"?"" ""

``

SoS:=proc(E0::float,E00::float,alpha::float,beta:: float)::float;

NULL

NULL

Experimental Data

 

Erealm := Vector[row]([1235.773, 1383.61, 1457.262, 1500.264, 1550.184, 1612.161, 512.7612, 656.6554, 743.6461, 793.375, 855.7937, 939.1199, 79.9523, 128.1375, 167.1459, 193.592, 230.5401, 287.8348, 22.389, 29.41424, 35.91883, 40.86366, 48.79128, 63.4475, 15.34275, 17.10101, 18.63288, 19.77424, 21.5671, 24.84739, 13.8321, 14.52843, 15.07626, 15.47014, 16.07713, 17.16574, 13.13383, 13.63704, 13.95888, 14.16849, 14.46123, 14.93971, 12.76736, 13.2203, 13.50072, 13.673, 13.89852, 14.23242]); LFm := Vector[row]([.156795, .1248161, .1108722, .1032334, 0.9474591e-1, 0.8496174e-1, .361361, .3020133, .2706018, .2546556, .2356126, .2121333, .6883826, .6532309, .6155578, .5906291, .5578895, .5123917, .394458, .5326358, .6095816, .6489291, .6894866, .7232845, .1456468, .2226473, .2826954, .3228541, .3789496, .4632182, 0.6758032e-1, 0.9437384e-1, .1198126, .1387971, .1680719, .2181531, 0.5173809e-1, 0.586771e-1, 0.6591736e-1, 0.7206892e-1, 0.8243504e-1, .1024519, 0.457877e-1, 0.493836e-1, 0.5191291e-1, 0.539114e-1, 0.5708074e-1, 0.6330242e-1])

NULL``

Enter Initial Guesses for HN equation

 

ind0 := min[index](Erealm); ind00 := max[index](Erealm); indLF := max[index](LFm); E0_g := Erealm(ind0); E00_g := 3*Erealm(ind00); `α_g` := 2.0*LFm(indLF)/Pi; `β_g` := `α_g`/(10.0); m := ArrayTools[Dimensions](LFm); maxx := rhs(m[1]); Ecomplex := Vector[row]([seq(Complex(Erealm[k], Erealm[k]*LFm[k]), k = 1 .. maxx)]); `ωτ` := Vector[row]([seq(abs((((E0_g-E00_g)/(Ecomplex[k]-E00_g))^(1/`β_g`)-1)^(1/`α_g`)/(I)), k = 1 .. maxx)]); Erealc := Vector[row]([seq(Re(E00_g+(E0_g-E00_g)/(1+(I*`ωτ`[k])^`α_g`)^`β_g`), k = 1 .. maxx)]); Eimagc := Vector[row]([seq(Im(E00_g+(E0_g-E00_g)/(1+(I*`ωτ`[k])^`α_g`)^`β_g`), k = 1 .. maxx)]); LFc := Vector[row]([seq(Eimagc[k]/Erealc[k], k = 1 .. maxx)]); pltm := plots:-loglogplot(Erealm, LFm, style = point, symbol = solidcircle, gridlines = true, color = red); pltc := plots:-loglogplot(Erealc, LFc, style = point, symbol = diamond, gridlines = true, color = blue); plots:-display(pltm, pltc, title = "Wicket Plot from Guesses       measured - red    calculated - blue"); Sum_of_Squares := SoS(E0_g, E00_g, `α_g`, `β_g`)

.2049941769

(2.1)

``

NULL

NULL

NULL

Run Optimizer

 

lol := .7; hil := 1.3; le0 := lol*E0_g; he0 := hil*E0_g; le00 := lol*E00_g; he00 := hil*E00_g; al := lol*`α_g`; ah := hil*`α_g`; bl := lol*`β_g`; bh := hil*`β_g`; parameterRange := le0 .. he0, le00 .. he00, al .. ah, bl .. bh; soln := Optimization:-NLPSolve(SoS, parameterRange); HN := soln[2]; E0_s := HN[1]; E00_s := HN[2]; `α_s` := HN[3]; `β_s` := HN[4]; `ωτ_s` := Vector[row]([seq(abs((((E0_s-E00_s)/(Ecomplex[k]-E00_s))^(1/`β_s`)-1)^(1/`α_s`)/(I)), k = 1 .. maxx)]); Erealc_s := Vector[row]([seq(Re(E00_s+(E0_s-E00_s)/(1+(I*`ωτ_s`[k])^`α_s`)^`β_s`), k = 1 .. maxx)]); Eimagc_s := Vector[row]([seq(Im(E00_s+(E0_s-E00_s)/(1+(I*`ωτ_s`[k])^`α_s`)^`β_s`), k = 1 .. maxx)]); LFc_s := Vector[row]([seq(Eimagc_s[k]/Erealc_s[k], k = 1 .. maxx)])

[0.648163470800135894e-2, Vector[column](%id = 18446747242105787086)]

(3.1)

NULL

NULL

NULL

Plot Wicket Plot with Optimized HN Parameters

 

pltm_s := plots:-loglogplot(Erealm, LFm, style = point, symbol = solidcircle, gridlines = true, color = red); pltc_s := plots:-loglogplot(Erealc_s, LFc_s, style = point, symbol = diamond, gridlines = true, color = blue); plots:-display(pltm_s, pltc_s, title = "Wicket Plot after Optimization  (measured - red    calculated - blue)"); E0_soln := E0_s; E00_soln := E00_s; `α_soln` := `α_s`; `β_soln` := `β_s`; Sum_of_Squares := soln[1]

0.648163470800135894e-2

(4.1)

NULL


 

Download HN_fit_of_DMA_data_ss_proc_v5a.mw

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