MaplePrimes Questions

Hello all.

I am using a k-means cluster routine to partition a set of points into a fixed number of clusters.

The solution assigns points belong to clusters, and this is given in matrix-form. The attached file gives an example of a simple problem that is concerns two clusters (matrices). The entries of each cluster / matrix represent the coordinates of the points in the plane.

I am looking to ..

1. Isolate and label each cluster solution (there may be up to 10), and 

2. For each matrix / cluster, arrange the entries into separate ordered pairs. 

For example, in this instance, I wish to obtain the following form ..

A: = [[-6.08, 52.99], [-7.26, 55.29], [-6.24, 53.29]]

B: = [[-9.72, 51.46], ... , [-9.81, 53.76]]

I have made several attempts to solve for this, but I simply cannot get the solution to output this form.

Any advise / help you can give will be gratefully received. 

Thanks for reading!

Download MaplePrimes_May_31.mw

When I try to solve an equation, or enter any equations using log, the answer is always incorrect. for example: log(0.5/1.65)=-1.194, when the correct answer is -0.519? 

I put together the attached worksheet to help me determine the cheapest way to buy "refreshments" for a party by comparing price and volume of different bottle size options.  The spreadsheet works fine as is.  However, when I right click on the output of line (14) and format pct_difference as percent with 2 decimal places and execute the worksheet, Maple hangs on that line and progresses no further.  This doesn't happen in Maple 2018 but the problem does show up in Maple 2024.  Suggestions please?

cost_comparison_-_liquid_(v01MP).mw

how to determine lambda, m0, and n0? a_i, and c_i are constants and c^2 = c[1]^2 + c[2]^2. solA.mw

This question is as much an observation of somthing I accidently stumbled across. I was using eval[recurse] to evaluate expressions reduced with LargeExpressions. I found eval['recurse'](eval['recurse']([Expr1 , Expr2] , [Q=.. Q1=.....])[]) to be better than simplify(eval['recurse']([Expr1 , Expr2] , [Q=.. Q1=.....])[]).

I only realised what was happening  when I put the below together. Then I could see the wood from the trees. 

It would be interesting to know why.

restart

 

Pt:=[[(sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(Q[6])*(t^2 + 1)/(sqrt(sqrt(Q[2])/(4*a*c - b^2)^2)*sqrt((2*sqrt(Q[2])*a*c^2*e^2 + 2*sqrt(Q[2])*b^2*c^2*f - 8*sqrt(Q[2])*a^3*c*f + 2*sqrt(Q[2])*a^2*b^2*f + 16*sqrt(Q[2])*a^2*c^2*f + 2*sqrt(Q[2])*a^2*c*d^2 - 4*sqrt(Q[2])*a^2*c*e^2 - 8*sqrt(Q[2])*a*c^3*f - 4*sqrt(Q[2])*a*c^2*d^2 + 2*sqrt(Q[2])*a^3*e^2 + 2*sqrt(Q[2])*c^3*d^2 - 2*sqrt(Q[2])*b*c^2*d*e + 4*sqrt(Q[2])*a*b*c*d*e - 2*sqrt(Q[2])*a^2*b*d*e - 4*sqrt(Q[2])*a*b^2*c*f + sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] - 2*Q[11])*signum((sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] - 8*((a - c)^2*sqrt(Q[2])/4 + Q[5]/4)*Q[8])*Q[4])*Q[4])*(t^2 - 1)) + 2*sqrt(2*sqrt(Q[2]) - 2*Q[10])*t*sqrt(Q[6])*Q[9]/(sqrt(sqrt(Q[2])/(4*a*c - b^2)^2)*sqrt((2*sqrt(Q[2])*a*c^2*e^2 + 2*sqrt(Q[2])*b^2*c^2*f - 8*sqrt(Q[2])*a^3*c*f + 2*sqrt(Q[2])*a^2*b^2*f + 16*sqrt(Q[2])*a^2*c^2*f + 2*sqrt(Q[2])*a^2*c*d^2 - 4*sqrt(Q[2])*a^2*c*e^2 - 8*sqrt(Q[2])*a*c^3*f - 4*sqrt(Q[2])*a*c^2*d^2 + 2*sqrt(Q[2])*a^3*e^2 + 2*sqrt(Q[2])*c^3*d^2 - 2*sqrt(Q[2])*b*c^2*d*e + 4*sqrt(Q[2])*a*b*c*d*e - 2*sqrt(Q[2])*a^2*b*d*e - 4*sqrt(Q[2])*a*b^2*c*f + sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] + 2*Q[11])*signum((sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] + 8*(-(a - c)^2*sqrt(Q[2])/4 + Q[5]/4)*Q[8])*Q[4])*Q[4])*(t^2 - 1)) + b*e - 2*c*d)/(4*a*c - b^2),

 (-sqrt(2*sqrt(Q[2]) - 2*Q[10])*sqrt(Q[6])*(t^2 + 1)*Q[9]/(sqrt(sqrt(Q[2])/(4*a*c - b^2)^2)*sqrt((2*sqrt(Q[2])*a*c^2*e^2 + 2*sqrt(Q[2])*b^2*c^2*f - 8*sqrt(Q[2])*a^3*c*f + 2*sqrt(Q[2])*a^2*b^2*f + 16*sqrt(Q[2])*a^2*c^2*f + 2*sqrt(Q[2])*a^2*c*d^2 - 4*sqrt(Q[2])*a^2*c*e^2 - 8*sqrt(Q[2])*a*c^3*f - 4*sqrt(Q[2])*a*c^2*d^2 + 2*sqrt(Q[2])*a^3*e^2 + 2*sqrt(Q[2])*c^3*d^2 - 2*sqrt(Q[2])*b*c^2*d*e + 4*sqrt(Q[2])*a*b*c*d*e - 2*sqrt(Q[2])*a^2*b*d*e - 4*sqrt(Q[2])*a*b^2*c*f + sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] - 2*Q[11])*signum((sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] - 8*((a - c)^2*sqrt(Q[2])/4 + Q[5]/4)*Q[8])*Q[4])*Q[4])*(t^2 - 1)) + 2*sqrt(2*sqrt(Q[2]) + 2*Q[10])*t*sqrt(Q[6])/(sqrt(sqrt(Q[2])/(4*a*c - b^2)^2)*sqrt((2*sqrt(Q[2])*a*c^2*e^2 + 2*sqrt(Q[2])*b^2*c^2*f - 8*sqrt(Q[2])*a^3*c*f + 2*sqrt(Q[2])*a^2*b^2*f + 16*sqrt(Q[2])*a^2*c^2*f + 2*sqrt(Q[2])*a^2*c*d^2 - 4*sqrt(Q[2])*a^2*c*e^2 - 8*sqrt(Q[2])*a*c^3*f - 4*sqrt(Q[2])*a*c^2*d^2 + 2*sqrt(Q[2])*a^3*e^2 + 2*sqrt(Q[2])*c^3*d^2 - 2*sqrt(Q[2])*b*c^2*d*e + 4*sqrt(Q[2])*a*b*c*d*e - 2*sqrt(Q[2])*a^2*b*d*e - 4*sqrt(Q[2])*a*b^2*c*f + sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] + 2*Q[11])*signum((sqrt(Q[2])*sqrt(2*sqrt(Q[2]) + 2*Q[10])*sqrt(2*sqrt(Q[2]) - 2*Q[10])*Q[7] + 8*(-(a - c)^2*sqrt(Q[2])/4 + Q[5]/4)*Q[8])*Q[4])*Q[4])*(t^2 - 1)) - 2*a*e + b*d)/(4*a*c - b^2)],

[Q[2] = (a^2 - 2*a*c + b^2 + c^2)*(4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)^2, Q[4] = 1/((a^2 - 2*a*c + b^2 + c^2)*(4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)^2), Q[5] = (a^2 - 2*a*c + b^2 + c^2)*(4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)*(a + c), Q[6] = signum((4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)/(4*a*c - b^2))*(4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)/(4*a*c - b^2), Q[7] = csgn((4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)*(b*I + a - c)*I)*b, Q[8] = 4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2, Q[9] = csgn((4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)*(b*I + a - c)*I), Q[10] = (a - c)*(4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2), Q[11] = (a + c)*(a^2 - 2*a*c + b^2 + c^2)*(4*a*c*f - a*e^2 - b^2*f + b*d*e - c*d^2)^2]]:

length(Pt);  # was >27,000

5002

(1)

valsh:=[a = -9, b = -9, c = 16, d = -10, e = 7, f = -36]

[a = -9, b = -9, c = 16, d = -10, e = 7, f = -36]

(2)

S1:=eval['recurse'](Pt,valsh)[];

length(%)

 

[-(1/657)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*Q[6]^(1/2)*(t^2+1)*431649^(1/2)/(Q[2]^(1/4)*((-28903750*Q[2]^(1/2)+Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]-2*Q[11])*signum((Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]-8*((625/4)*Q[2]^(1/2)+(1/4)*Q[5])*Q[8])*Q[4])*Q[4])^(1/2)*(t^2-1))-(2/657)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*t*Q[6]^(1/2)*Q[9]*431649^(1/2)/(Q[2]^(1/4)*((-28903750*Q[2]^(1/2)+Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]+2*Q[11])*signum((Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]+8*(-(625/4)*Q[2]^(1/2)+(1/4)*Q[5])*Q[8])*Q[4])*Q[4])^(1/2)*(t^2-1))-257/657, (1/657)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[6]^(1/2)*(t^2+1)*Q[9]*431649^(1/2)/(Q[2]^(1/4)*((-28903750*Q[2]^(1/2)+Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]-2*Q[11])*signum((Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]-8*((625/4)*Q[2]^(1/2)+(1/4)*Q[5])*Q[8])*Q[4])*Q[4])^(1/2)*(t^2-1))-(2/657)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*t*Q[6]^(1/2)*431649^(1/2)/(Q[2]^(1/4)*((-28903750*Q[2]^(1/2)+Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]+2*Q[11])*signum((Q[2]^(1/2)*(2*Q[2]^(1/2)+2*Q[10])^(1/2)*(2*Q[2]^(1/2)-2*Q[10])^(1/2)*Q[7]+8*(-(625/4)*Q[2]^(1/2)+(1/4)*Q[5])*Q[8])*Q[4])*Q[4])^(1/2)*(t^2-1))-24/73], [Q[2] = 377479229074, Q[4] = 1/377479229074, Q[5] = 114273866, Q[6] = 23123/657, Q[7] = -9, Q[8] = 23123, Q[9] = 1, Q[10] = -578075, Q[11] = 2642354603518]

 

2074

(3)

simplify(S1);# this is  simplify with side retations
length(%)

[-(257/248003853501618)*377479229074^(3/4)*((377479229074^(1/4)*(t^2-1)*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2)+(1/168849)*657^(1/2)*23123^(1/2)*431649^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(t^2+1))*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)-14)^(1/2)+(2/168849)*23123^(1/2)*657^(1/2)*431649^(1/2)*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)*t)/(((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)-14)^(1/2)*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2)*(t-1)*(t+1)), -(12/13777991861201)*377479229074^(3/4)*((377479229074^(1/4)*(t^2-1)*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2)-(1/141912)*657^(1/2)*23123^(1/2)*431649^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)*(t^2+1))*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)-14)^(1/2)+(1/70956)*(2*377479229074^(1/2)-1156150)^(1/2)*t*23123^(1/2)*657^(1/2)*431649^(1/2)*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2))/(((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)-14)^(1/2)*((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2)*(t-1)*(t+1))]

 

2316

(4)

simplify(%%);
length(%)

[-(1/71716466988)*(-2471*706^(1/2)+249218)^(1/2)*(2471*706^(1/2)+249218)^(1/2)*((73^(1/2)*(t^2+1)*(46246*706^(1/2)-1156150)^(1/2)+(257/3)*706^(1/4)*(14+2*706^(1/2))^(1/2)*t^2)*(-14+2*706^(1/2))^(1/2)+2*73^(1/2)*(t*(46246*706^(1/2)+1156150)^(1/2)*(14+2*706^(1/2))^(1/2)-257*706^(1/4)))*706^(1/4)/(t^2-1), (1/71716466988)*(-2471*706^(1/2)+249218)^(1/2)*((73^(1/2)*(t^2+1)*(46246*706^(1/2)+1156150)^(1/2)-72*706^(1/4)*(14+2*706^(1/2))^(1/2)*t^2)*(-14+2*706^(1/2))^(1/2)-2*73^(1/2)*((14+2*706^(1/2))^(1/2)*(46246*706^(1/2)-1156150)^(1/2)*t-216*706^(1/4)))*(2471*706^(1/2)+249218)^(1/2)*706^(1/4)/(t^2-1)]

 

744

(5)

 

S2:=eval['recurse'](eval['recurse'](Pt,valsh)[]);# I find this interesting
length(%)

[-(1/162938531750563026)*(2*377479229074^(1/2)-1156150)^(1/2)*23123^(1/2)*657^(1/2)*(t^2+1)*431649^(1/2)*377479229074^(3/4)/(((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2)*(t^2-1))-(1/81469265875281513)*(2*377479229074^(1/2)+1156150)^(1/2)*t*23123^(1/2)*657^(1/2)*431649^(1/2)*377479229074^(3/4)/(((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)-14)^(1/2)*(t^2-1))-257/657, (1/162938531750563026)*(2*377479229074^(1/2)+1156150)^(1/2)*23123^(1/2)*657^(1/2)*(t^2+1)*431649^(1/2)*377479229074^(3/4)/(((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)+14)^(1/2)*(t^2-1))-(1/81469265875281513)*(2*377479229074^(1/2)-1156150)^(1/2)*t*23123^(1/2)*657^(1/2)*431649^(1/2)*377479229074^(3/4)/(((9/377479229074)*377479229074^(1/2)*(2*377479229074^(1/2)-1156150)^(1/2)*(2*377479229074^(1/2)+1156150)^(1/2)+(625/8162419)*377479229074^(1/2)-14)^(1/2)*(t^2-1))-24/73]

 

1283

(6)

simplify(S2); #
length(%)

 

[-(1/406325592)*(14+2*706^(1/2))^(1/2)*(((181442/3)*(14+2*706^(1/2))^(1/2)*t^2+706^(3/4)*73^(1/2)*(46246*706^(1/2)-1156150)^(1/2)*(t^2+1))*(-14+2*706^(1/2))^(1/2)+2*(46246*706^(1/2)+1156150)^(1/2)*73^(1/2)*706^(3/4)*(14+2*706^(1/2))^(1/2)*t-362884*73^(1/2))*(-14+2*706^(1/2))^(1/2)/(t^2-1), (14+2*706^(1/2))^(1/2)*((-2*706^(3/4)*73^(1/2)*(46246*706^(1/2)-1156150)^(1/2)*t-50832*(-14+2*706^(1/2))^(1/2)*t^2)*(14+2*706^(1/2))^(1/2)+(304992+(t^2+1)*(46246*706^(1/2)+1156150)^(1/2)*706^(3/4)*(-14+2*706^(1/2))^(1/2))*73^(1/2))*(-14+2*706^(1/2))^(1/2)/(406325592*t^2-406325592)]

 

705

(7)
 

 

Download 2024-05-31_Eval_Recurse_vs_Simplify_Side_Rels.mw

counts_and_bins_data_output_from_histogram().mw

The Historgram( ) function is the combination of a binning computation and a visualization of the result of the binning computation. In order to generate any histogram you need to know the set of bin boundaries and the number of counts in each bin.

 

These bin boundaries look like: bin_bounds := [[`x__1,min`, `x__1,max`], [`x__2,min`, `x__2,max`], () .. (), [`x__N,min`, `x__N,max`]]where there are N bins in total.

The counts data looks like: counts := [H__1, H__2, () .. (), H__N]where there are N bins in total.

 

The Histogram( ) command passed this data around internally. Can I have Histogram( ) output this data? In other words, can I get the x-y data from the histogram, the bins-counts data?


Download counts_and_bins_data_output_from_histogram().mw

Can anyone helps me with my optimization Problem.  Following are the issues :-

  • I have to minimize the function TRC, i am unable to do. 
  • I am unable to add a constraint with if statement. 
  • Check whether i have represented I1 and I2 with respect to alpha and beta right or wrong

Attaching the sheet below, the background marked in yellow is the problem area. Thankyou

Basic_model.mw

How do I solve equation (1) for omega, rho, lambda1, and lambda2? verif.mw

Why this code does not work. Thank you.
restart;
with(plots);
with(geometry);
_EnvHorizontalName := 'x';
_EnvVerticalName := 'y';
x0 := 10;
y0 := 9;
a := 7;
b := 5;
c := sqrt(a^2 - b^2);
ellipse(el, x^2/a^2 + y^2/b^2 - 1);
point(F1, -c, 0);
point(F2, c, 0);
point(P, x0, y0);
eq := simplify((a^2 - x0^2)*(y - y0)^2 + (b^2 - y0^2)*(x - x0)^2 + 2*x0*y0*(x - x0)*(y - y0)) = 0;
eq := (a^2 - x0^2)*m^2 + 2*x0*y0*m + b^2 - y0^2 = 0;
sol := solve(%, m);
m1 := sol[1];
m2 := sol[2];
(y - y0 - m1) + (-x + x0);
(y - y0 - m2) + (-x + x0);
line(tang1, (y - y0 - m1) + (-x + x0));
line(tang2, (y - y0 - m2) + (-x + x0));
display*[textplot*([[-c, 0, "F1"], [c, 0, "F2"], [coordinates(P)[], "P"]], align = {"above", 'right'}), draw*([el(color = red), P(color = black, symbol = solidcircle, symbolsize = 16), tang1(color = green), tang2(color = green), F1(color = blue, symbol = solidcircle, symbolsize = 16), F2(color = red, symbol = solidcircle, symbolsize = 16)], axes = none)];
 

weibull_damage.mw
i have weibull plot...and i want to get size and shpae parametr...how can i get ...parameters .i don't know how to perform linear regression to get these parameters in maple..please help

I noticed that in a legend with:

  1. Three elements
  2. linestyle = [solid, longdash, dash]
  3. thickness = [4, 4, 4]

The three different linestyles are distinguishable in the plots (of course, since the curves span the whole plot area) but indistinguishable in the legend box. Since the legend box is too narrow, the symbols for a solid line, a longdash line, and a dash line are equivalent, resulting in confusion regarding which element is associated to each linestyle. Note that I don't want to use three different colors to achieve that or change my font sizes

  1. How can I "show more" of the linestyle in the legend box? "Longer" line symbols in the legend box would allow to dinstinguish a solid from a longdash from a dash even when all three are quite thick.
  2. Alternatively, can I reduce the thickness of the line symbols in the legend box (leaving unaltered the thickness of the lines in the actual plot)? "Slimmer" line symbols in the legend box would allow to dinstinguish a solid from a longdash from a dash even when all three are quite short.

Can_I_change_the_location_of_the_color_bar_caption_in_Maple_2024.mw

In Maple 2024,

can I change the location of the color bar caption in Maple 2024? It conflicts with the color bar labels sometimes. See the attached maple sheet for an example.

I am using fsolve() to solve a highly nonlinear system of 6 equations in 6 variables: lambda_d1, lambda_i1, lambda_d2, lambda_i2, lambda_d3, lambda_i3.

fsolve() doesn't "solve"! I usually help fsolve() with some initial conditions and with the expected signs of the solution but in this case it's not enough. I noticed that if I comment out the expected signs line (that is, if I don't impose my 6 lambdas to be strictly positive), the fsolve() works.
How do I help fsolve() to pin down only positive solutions at each iteration? I have no reasons to believe that there aren't any positive solutions for all 6 lambdas...

Worksheet: fsolve_help.mw

thank you.

can we express 'X' in terms of 'L'? i.e., X = (some const)*L XintoL.mw

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