I am trying to give an input to an R program from an output the edge set of maple code 

Now how to Build a function which takes a list of edge sets as inputs and returns a list on the below format

Show I want for one edge set of the list

Now I have edge set of a Graph G say {{1,2},{2,3},{3,4},{4,5}}

Now want to pick the first values of each index make one set 

from<-c(1,2,3,4)

Similiarly first values of each index make one more set 

to<-c(2,3,4,5)

Then I want to form a list [from<-c(1,2,3,4),to<-c(2,3,4,5),ft <- cbind(from, to),Graph1<-ftM2graphNEL(ft)]

Now it will take second graph in the Edge list say {{1, 2}, {1, 7}, {2, 3}, {3, 4}, {4, 5}, {5, 6}, {6, 7}}

It will append to the previous list like

[from<-c(1,2,3,4),to<-c(2,3,4,5),ft <- cbind(from, to),Graph1<-ftM2graphNEL(ft),from<-c(1,1,2,3,4,5,6),to<-c(2,7,3,4,5,6,7),ft <- cbind(from, to),Graph2<-ftM2graphNEL(ft)]

This time Graph1 is changed to Graph2 to be observed.

Like that it will need  increase graph number based on the number of edge sets in the list of edges.

To be done all edge sets in list

As then I can copy the entire contents in the list and paste in R so that i can run 

As I can have 100 or more graphs done in maple doing for each of them manually typing may be difficult.

Kind help please

Your help will be surely Acknowledged 

Kind help

A toy code i simply tried for graph attached

But I have errors some come with double quotes can something be done if possible please guide

Kind help

As with 100 of lines it will easy to copy paste 

If the contents of the list can be written to txt file it would be helful 

please help

toy_try.mw

I have tried something to my knoewledge please help

Hello,

is there a limit to the matrix size on which the Determinant(A) can operate? I am working on a project that generates a 22x22 matrix of coefficients of unknowns, which I built out of the GenerateMatrix() function.  If I use subs(omega=1, AA), the determinant is calculated. Still, I want the determinant in terms of omega so I can solve for Determinant(A)=0 in order to find the natural frequencies and then find my unknown coefficients.

When I use the Determinant function on my symbolic matrix is always returns 0. I know from using smaller matrices that it can do symbolic determinants. If there is a better way to do what I am trying to do, please let me know!

Thanks!

Please check: Finding_Chi_Version1.mw

My end goal is to find the following three expressions:

chi_1 := collect(X_A,[nnu[1],nnu[2]]);

chi_2 := collect(X_B,[nnu[1],nnu[2]]);

chi_3 := collect(X_C,[nnu[1],nnu[2]]);

I expect these three expressions to be linear combinations of random variables nu[1] (nnu[1]) and nu[2] (nnu[2]).

While calling solve(), I encounter this error:

Error, (in assuming) when calling 'SolveTools:-Engine:-Dispatch'. Received: 'badly formed input to solve: not fully algebraic'

What is exactly the issue here? If it can help you answer my doubt, that argmin expression I defined is composed by conditional means and variances which I computed as in here: conditional_distributions_Version1.mw

The two formulas I am trying to implement in Maple are conditional distribution of a multivariate normal distribution. Am I already doing any mistake in conditional_distributions_Version1.mw? An alternative interpretation of mine for these two formulas is: conditional_distributions_Version2.mw. Please check the light-blue-highlighted differences in the conditional variance calculation. This alternative interpretation leads to Finding_Chi_Version2.mw, which I also can't solve() (solver stuck in "evaluating") but at least I don't get the error mentioned above...

I am a bit lost to be honest: Is Finding_Chi_Version1 or Finding_Chi_Version2 the correct interpretation? 

Thanks!

Hello,
I m wondering if/how (i) can use the collect function twice:  collect(a, x, form, func ):  
collect(a, x, form, collect(x)), but it seems I can't use a func with opt. 
Can someone help please? 

Merci 

Hello Y'all,

I've been on this problem for a few days now and can't seem to find a solution and hope you fine people here can help me.

Is there a way to symbolically work with matrices? In detail I'm trying to calculate blocks in a block matrix equation symbolically/analytically. The first problem I had was that of course matrices dont commutate, which is solvable by just using the LinearAlgebra package and typing in

A.B instead of A*B

For now the big problem that remains is that of course in addition to that the inversion of a matrix A is not just 1/A (or \frac{1}{A} in LaTeX) but simply A^(-1). There is the MatrixInverse function but that needs a declared matrix. And since I dont have explicit matrices I can't use Matrix or the like to declare that A is a matrix. Any help here would appreciated. I tried to work with assume, but that didn't work either and I am kind of out of options (that I find on the web) right now. In essence I just want Maple to write A^(-1) and only cancel that if an A is next to it... (albeit with not just A but of course A also being setup by addition and multiplication of matrices...).

A smaller, related interest would be a general identity matrix. One that basically just fulfills A.I=I.A=A and I^(-1)=I. At least to me that seems kind of similar but I can't just define a Mtrix as being a Matrix and not having elements...

Thank you in advance and have a nice weekend y'all! :)

Good day! 

I attempted to download the geocoding package for Maple and I cannot get it to work. Executing the worksheet produces no results.

I am using Maple 2022. 

Can anyone shed some light on this please?

Thanks for reading ..

https://maple.cloud/app/5769608062566400/Google+Maps+and+Geocoding?activeGroup=MathApps

How to use collect() or coeffs() on random variables instead of standard variables?

I need to re-organize a linear combination of RVs nu[1], nu[2], u[1], u[2], u[3] by collecting the coefficients on each of these 5 RVs. Note that the Xs are correlated with each other and the Ys are correlated with each other (but Xs and Ys are uncorrelated).

For example, nu is a 2D gaussian vector where nu[1] and nu[2] are defined in terms of _R1, _R2, means, standard deviations and correlation coefficient. They are quite "nested" and the 3D gaussian vector u is even worse, so when these enter a linear combination it becomes hard to identify them back as simply nu[1], nu[2], u[1], u[2], u[3].

Is there a way to "isolate" them in a linear combination by using collect()-like or coeffs()-like functions (i) directly on the RVs or (ii) indireclty on the explicit expressions of _Rs, means, standard devs, correlation coeffs? 

(I already checked the answers to these two somewhat similar questions but did not help for my case:

https://mapleprimes.com/questions/235215-Reduce-Length-Of-Sum-Of-Products

https://mapleprimes.com/questions/234292-Re-How-To-Collect-Using-A-Term-By-Multiplication

)

See my script below: 

For example, I would want collect() on nu[1] (or equivalently on _R1*sigma__v[1]+nu__0[1]) to give me X__1+X__3 (as you easily see from my definition of Omega).

Download collect.mw

I can derive a symbolic solution by hand for the following ODE, but cannot get Maple to do it for me.  Any tricks?

Download ode-piecewise.mw

I obtain the adjacency matrix from a graph. We know that it is indexed according to the order of vertices in the Vertices. But what if I want to rearrange it in a different order? Here is a specific example.

with(GraphTheory):
g:=Graph({{2,3},{1,2}});
Vertices(g); #[1,2,3]
AdjacencyMatrix(g);

I would like to display this matrix in the order of [3, 1, 2].

I have give this below fit command my data is only continous data either positive or negative float data. Their never any complex number at all.

I use the below fit command

Error, complex argument to max/min

It can be observed it is running into error in C1 I dont know why can someone suggest where should I check and why is this happening kind help.   In Excel we can see the intercept coming big.

I attach the toycode to see the error I get too

toycode.mw

# countourplot3d piggybacks on top of plot3d.
# For the "coloring=[lowColor, highColor]", the "filledregions=true" option must be present.
# If "filledregions=true" is not present, plot3d will throw an error.
# This code shows the three cases, only one of which will work.
Note to support. I cannot add a new tag. contourplot3d should be a tag.

restart;
with(plots);
with(ColorTools);
cGr4s := Color([0.50, 0.50, 0.50]);
contourplot3d(-5*d/(d^2 + y^2 + 1), d = -3 .. 3, y = -3 .. 3, color = black, thickness = 3, coloring = [cGr4s, cGr4s], contours = [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2]);
contourplot3d(-5*d/(d^2 + y^2 + 1), d = -3 .. 3, y = -3 .. 3, filledregions = false, color = black, thickness = 3, coloring = [cGr4s, cGr4s], contours = [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2]);
contourplot3d(-5*d/(d^2 + y^2 + 1), d = -3 .. 3, y = -3 .. 3, filledregions = true, color = black, thickness = 3, coloring = [cGr4s, cGr4s], contours = [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2]);

I'm having a symmetric bivariate polynomial P(x,y) with a high degree (larger than 8). I want to know if there exists a root of P(x,y) or not. I may not need a specific root but rather to know if P(x,y) has a root or not. I've been doing some research but I only find the command that helps solve univariate functions or solve systems of bivariate functions. 

In conclusion, my question is: How can I know that a symmetric bivariate polynomial has a root or not using Maple?

Here is the polynomial I want to check

P(x,y)=x^12*y^3 + 10*x^11*y^4 + 43*x^10*y^5 + 105*x^9*y^6 + 161*x^8*y^7 + 161*x^7*y^8 + 105*x^6*y^9 + 43*x^5*y^10 + 10*x^4*y^11 + x^3*y^12 - x^12*y^2 - 8*x^11*y^3 - 17*x^10*y^4 + 8*x^9*y^5 + 82*x^8*y^6 + 128*x^7*y^7 + 82*x^6*y^8 + 8*x^5*y^9 - 17*x^4*y^10 - 8*x^3*y^11 - x^2*y^12 - x^12*y - 4*x^11*y^2 - 62*x^10*y^3 - 341*x^9*y^4 - 902*x^8*y^5 - 1410*x^7*y^6 - 1410*x^6*y^7 - 902*x^5*y^8 - 341*x^4*y^9 - 62*x^3*y^10 - 4*x^2*y^11 - x*y^12 + x^12 - 8*x^11*y - 62*x^10*y^2 - 680*x^9*y^3 - 3169*x^8*y^4 - 7312*x^7*y^5 - 9540*x^6*y^6 - 7312*x^5*y^7 - 3169*x^4*y^8 - 680*x^3*y^9 - 62*x^2*y^10 - 8*x*y^11 + y^12 + 10*x^11 - 17*x^10*y - 341*x^9*y^2 - 3169*x^8*y^3 - 11838*x^7*y^4 - 21793*x^6*y^5 - 21793*x^5*y^6 - 11838*x^4*y^7 - 3169*x^3*y^8 - 341*x^2*y^9 - 17*x*y^10 + 10*y^11 + 43*x^10 + 8*x^9*y - 902*x^8*y^2 - 7312*x^7*y^3 - 21793*x^6*y^4 - 30696*x^5*y^5 - 21793*x^4*y^6 - 7312*x^3*y^7 - 902*x^2*y^8 + 8*x*y^9 + 43*y^10 + 105*x^9 + 82*x^8*y - 1410*x^7*y^2 - 9540*x^6*y^3 - 21793*x^5*y^4 - 21793*x^4*y^5 - 9540*x^3*y^6 - 1410*x^2*y^7 + 82*x*y^8 + 105*y^9 + 161*x^8 + 128*x^7*y - 1410*x^6*y^2 - 7312*x^5*y^3 - 11838*x^4*y^4 - 7312*x^3*y^5 - 1410*x^2*y^6 + 128*x*y^7 + 161*y^8 + 161*x^7 + 82*x^6*y - 902*x^5*y^2 - 3169*x^4*y^3 - 3169*x^3*y^4 - 902*x^2*y^5 + 82*x*y^6 + 161*y^7 + 105*x^6 + 8*x^5*y - 341*x^4*y^2 - 680*x^3*y^3 - 341*x^2*y^4 + 8*x*y^5 + 105*y^6 + 43*x^5 - 17*x^4*y - 62*x^3*y^2 - 62*x^2*y^3 - 17*x*y^4 + 43*y^5 + 10*x^4 - 8*x^3*y - 4*x^2*y^2 - 8*x*y^3 + 10*y^4 + x^3 - x^2*y - x*y^2 + y^3

Say I have 20 userdefined functions defined by me say

Now i required function which picks one of the userdefined from the above 20 functions randomly

Can anyone help me fix a corrupted maple file?

I have tried to fix it myself and searched all over for a solution but can' seem to fix it myself. Please help

Download Styrkelære2regneopgaver.mwStyrkelære2regneopgaver.mwStyrkelære2regneopgaver.mw

Hello everyone,

Here is a stylized version of my problem. Given three normally distributed random variables {A, B, C}, I want to find the X_1, X_2, X_3 that maximize the following expression (gamma being a constant and A being a linear combination of other normally distributed random variables):

Max{ Exp[A|B,C] - (gamma/2)*Var[A|B,C] }

All the details are here: 070423_Optimization.mw

In particular, I am seeking your help to:

1. Correlate three random variables (an example of the procedure for correlating two random variables is already provided in the script).
2. Verify my understanding of the linear projection theorem (https://stats.stackexchange.com/questions/30588/deriving-the-conditional-distributions-of-a-multivariate-normal-distribution) in two dimensions, that is, to compute conditional means and variances of the form E[X|Y,Z] and V[X|Y,Z].
3. Implement and adapt the linear projection theorem to my problem in Maple.
4. Combine all together to obtain Expr = E[A|B,C] + V[A|B,C] and find the optimal {X_1, X_2, X_3} by solving the linear system of three equations in the three variables {X_1, X_2, X_3}, where the three equations are obtained by setting to 0 the partial derivatives of Expr with respect to {X_1, X_2, X_3}.

In relation to point 2., did I correctly interpret the matrix form of the three-dimensions version of the linear projection theorem?

In relation to point 3., I attach a stylized script for the three-dimensions version (note that I need the two-dimensions version for my problem): LinearProjectionTheorem_3dimensions.mw. Assuming a correct interpretation of the theorem:

• Did I correctly implement E[X_2|Y_1,Y_2,Y_3] and E[X_3|Y_1,Y_2,Y_3] as in the picture above?
• How to adapt it accordingly to include E[X_1|Y_1,Y_2,Y_3] and V[X_1|Y_1,Y_2,Y_3], V[X_2|Y_1,Y_2,Y_3], and V[X_3|Y_1,Y_2,Y_3]? 
• How to apply it to the random variables in my script to eventually find the optimal {X_1,X_2,X_3}?

You can play around with my script 070423_Optimization.mw and send me the updated version. The problem I am trying to solve is quite convoluted, so let me know if you need any further clarification. Thanks a lot!