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Using Maple 2025.2, I need to run my test in command line (for other reasons).

Only problem is that plottools:-exportplot does not work as well as in the GUI.  The gridlines do not show.

I reported this to Maplesoft years ago. Was hoping may be it is fixed in Maple 2025.2 but it does not seem to be.

Anyone knows of a trick to show gridlines in plot (2D) when using cmaple.exe?

Here is example. Started cmaple.exe from command line (which on windows is 

c:/Program Files/Maple 2025/bin.X86_64_WINDOWS/cmaple.exe
> p:=plot(x^3, x = -8 .. 8, color = "blue",axis=[gridlines=[10,color="red"]]):> plottools:-exportplot("filename2.png",p);

You might want to use setdirectory() to some folder such as c:\tmp to save the plot to.

But the plot is missing the gridlines

In the UI it looks like this

This is really a big problem for me. I have to run the program in command line, but the plots geneated from command line do not look as good as when running the same program in maplew.exe vs. cmaple.exe.

This is a problem in Maple for years and years and no one in Maplesoft seems to care to fix it.

So I am asking hoping someone will have a trick to make gridline show using cmaple.exe.

Updated

I just found the case number. Actually I only reported this to Maplesoft 6 months ago. I thought it was longer than this.

Maybe they will fix it in Maple 2026?

I know Maplesoft is very busy with A.I. stuff these days, but hopefully someone will be able to have 1-2 hrs spare time from AI work and look at this and fix it.

It should not be hard to fix I would imagine, since code works in worksheet so someone just needs to use /copy same code that works in worksheet and make sure it works in cmaple.exe

Case - 00177734 | exporting plot using command line maple 2025 losses gridlines.Hello,Thank you for contacting Maplesoft.I have forwarded this inquiry to our Math Team / R&D Team. Once they review the situation and provide any further updates and/or insights, we will contact you. Thank you for your patience.Best Regards,HarishTechnical Support AnalystMaplesofthttps://www.maplesoft.com--------------- Original Message ---------------Sent: 2025-04-01, 3:34 a.m.To: support@maplesoft.comSubject: exporting plot using command line maple 2025 losses gridlines.When I export a plot to postscript using command line Maple 2025,the generated plot is missing gridlines.Same exact code executed inside GUI Maple 2025 shows the grid linesas expected.What to do to obtain same plot from command line Maple as fromthe GUI?I am using Linux Arch based distribution with Maple 2025 linux.Here is the command I used/home/me/maple2025/bin/maple A.mplHere is A.mpl----------------------p:=plot(25*t^2+10*t+20,axes=boxed,labels=[t,x(t)],axis=[gridlines=[color=lightblue]],'color' = 'red'):plotsetup(ps, plotoutput="p.ps",plotoptions=`color,noborder`);print(p);------------------------If you run the above, you will see p.ps file generated.But looking at the plot inside it, shows no gridlines.Could this be fixed or do I need different options tomake gridlines show running command line Maple?

Dear Maple user, please help me to show two legends inside the plot. Here is the codes attached. restart:
h:=z->1-(delta2/2)*(1 + cos(2*(Pi/L1)*(z - d1 - L1))):
K1:=((4/h(z)^4)-(sin(alpha)/F)-h(z)^2+Nb*h(z)^4):
T1:=Int(K1,z=0..1):
L1:=0.2: F:=10:
d1:=0.2:
T2:=evalf(T1):
T3:=unapply(T2,alpha,Nb,delta2):
plot([seq(seq(T3(alpha, Nb, delta2), Nb in [0.1, 0.2,0.3]), alpha in [Pi/6, Pi/4, Pi/3])], delta2 = 0.02.. 0.1,  titlefont = ["ROMAN", 15], labels = ["δ1", "T3"], labeldirections = ["horizontal", "vertical"], labelfont = ["SYMBOL", 11], linestyle = [solid, solid,solid,longdash, longdash,longdash, spacedash,spacedash, spacedash], symbol = [BOX, CROSS, CIRCLE, BOX, CROSS, CIRCLE, BOX, CROSS, CIRCLE], color = [blue,red, green, blue,red, green,blue,red, green], axes = boxed,size = [1000, 1000]);

a million time i try to figure out how i can get this plot ? why my graph  in countor is not same the 3D plot? where is problem?

Bgraph1.mw

Syntax for merging and overlaying all three graphs on a single plot.
Include three sets of iso-profit lines on the same axes:
– Case 1: thin solid lines
– case 2: brown dashed lines
– Case 3: grey semi-dashed lines
Also add vector arrows to show the direction of maximum profit increase.
Combined plot = Plot 1 + Plot 2 +  Plot 3
Attaching sheet:
case_1.mw                  case_2.mw                 Case_3.mw
 

sample graph: 

In the current graph, the three curves appear close together and are hard to distinguish because of a scaling issue. How can we adjust the scale so that each line is clearly visible and separate?

restart

L1 := ((3.26592*rho0^2-0.9411e-1*rho0+.3000)/(3.6288*rho0^2+.48)-.35)*(3.000000000-(3.333333333*(3.26592*rho0^2-0.9411e-1*rho0+.3000))/(3.6288*rho0^2+.48))+(.9*(.5+(.6250000000*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24)))*(0.163690476e-1-(.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24))+.1408958333+(0.2430555555e-1*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24)+(-(.3149801588*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24)+0.207886905e-1)*(0.163690476e-1-(.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24))-0.1000000000e-1*(0.163690476e-1-(.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24))^2+(1/2)*(3.000000000-(3.333333333*(3.26592*rho0^2-0.9411e-1*rho0+.3000))/(3.6288*rho0^2+.48))^2-(.1583333333*(3.26592*rho0^2-0.9411e-1*rho0+.3000))/(3.6288*rho0^2+.48)+(.6200396825*(-.339960-(.5000000000*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24)))*(0.163690476e-1-(.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1))/(1.8144*rho0^2+.24)); L2 := ((3.14725824*rho0^2-.10491*rho0+.284952)/(3.6288*rho0^2+.48)-.32)*(2.891000000-(3.333333333*(3.14725824*rho0^2-.10491*rho0+.284952))/(3.6288*rho0^2+.48))+(.9*(.47+(.6250000000*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24)))*(0.282738095e-1-(.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24))+.1345516666+(0.2430555555e-1*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24)+(-(.3149801588*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24)+0.359077381e-1)*(0.282738095e-1-(.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24))-0.1000000000e-1*(0.282738095e-1-(.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24))^2+(1/2)*(2.891000000-(3.333333333*(3.14725824*rho0^2-.10491*rho0+.284952))/(3.6288*rho0^2+.48))^2-(.1583333333*(3.14725824*rho0^2-.10491*rho0+.284952))/(3.6288*rho0^2+.48)+(.6200396825*(-.364344-(.5000000000*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24)))*(0.282738095e-1-(.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1))/(1.8144*rho0^2+.24)); L3 := ((3.14725824*rho0^2-.105342*rho0+.284952)/(3.6288*rho0^2+.48)-.32)*(2.891000000-(3.333333333*(3.14725824*rho0^2-.105342*rho0+.284952))/(3.6288*rho0^2+.48))+(.9*(.47+(.6250000000*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24)))*(0.290674603e-1-(.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24))+.1344738889+(0.2430555555e-1*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24)+(-(.3149801588*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24)+0.369156746e-1)*(0.290674603e-1-(.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24))-0.1000000000e-1*(0.290674603e-1-(.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24))^2+(1/2)*(2.891000000-(3.333333333*(3.14725824*rho0^2-.105342*rho0+.284952))/(3.6288*rho0^2+.48))^2+(-.1949156746-(.3100198412*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24))*(0.290674603e-1-(.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1))/(1.8144*rho0^2+.24))-(.1583333333*(3.14725824*rho0^2-.105342*rho0+.284952))/(3.6288*rho0^2+.48)

((3.26592*rho0^2-0.9411e-1*rho0+.3000)/(3.6288*rho0^2+.48)-.35)*(3.000000000-3.333333333*(3.26592*rho0^2-0.9411e-1*rho0+.3000)/(3.6288*rho0^2+.48))+.9*(.5+.6250000000*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24))*(0.163690476e-1-.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24))+.1408958333+0.2430555555e-1*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24)+(-.3149801588*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24)+0.207886905e-1)*(0.163690476e-1-.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24))-0.1000000000e-1*(0.163690476e-1-.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24))^2+(1/2)*(3.000000000-3.333333333*(3.26592*rho0^2-0.9411e-1*rho0+.3000)/(3.6288*rho0^2+.48))^2-.1583333333*(3.26592*rho0^2-0.9411e-1*rho0+.3000)/(3.6288*rho0^2+.48)+.6200396825*(-.339960-.5000000000*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24))*(0.163690476e-1-.2480158730*(-.5126688*rho0^2-.887040*rho0+0.1584e-1)/(1.8144*rho0^2+.24))

 

((3.14725824*rho0^2-.10491*rho0+.284952)/(3.6288*rho0^2+.48)-.32)*(2.891000000-3.333333333*(3.14725824*rho0^2-.10491*rho0+.284952)/(3.6288*rho0^2+.48))+.9*(.47+.6250000000*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24))*(0.282738095e-1-.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24))+.1345516666+0.2430555555e-1*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24)+(-.3149801588*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24)+0.359077381e-1)*(0.282738095e-1-.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24))-0.1000000000e-1*(0.282738095e-1-.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24))^2+(1/2)*(2.891000000-3.333333333*(3.14725824*rho0^2-.10491*rho0+.284952)/(3.6288*rho0^2+.48))^2-.1583333333*(3.14725824*rho0^2-.10491*rho0+.284952)/(3.6288*rho0^2+.48)+.6200396825*(-.364344-.5000000000*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24))*(0.282738095e-1-.2480158730*(-.4981536*rho0^2-.88268544*rho0+0.2736e-1)/(1.8144*rho0^2+.24))

 

((3.14725824*rho0^2-.105342*rho0+.284952)/(3.6288*rho0^2+.48)-.32)*(2.891000000-3.333333333*(3.14725824*rho0^2-.105342*rho0+.284952)/(3.6288*rho0^2+.48))+.9*(.47+.6250000000*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24))*(0.290674603e-1-.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24))+.1344738889+0.2430555555e-1*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24)+(-.3149801588*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24)+0.369156746e-1)*(0.290674603e-1-.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24))-0.1000000000e-1*(0.290674603e-1-.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24))^2+(1/2)*(2.891000000-3.333333333*(3.14725824*rho0^2-.105342*rho0+.284952)/(3.6288*rho0^2+.48))^2+(-.1949156746-.3100198412*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24))*(0.290674603e-1-.2480158730*(-.49525056*rho0^2-.88268544*rho0+0.28128e-1)/(1.8144*rho0^2+.24))-.1583333333*(3.14725824*rho0^2-.105342*rho0+.284952)/(3.6288*rho0^2+.48)

(1)

G2 := plot([L1, L2, L3], rho0 = 0 .. .8, color = ["#00FF00", "#00BC00", "#008000"], labels = [typeset(Typesetting:-mo("ρ", mathvariant = "bold"), "\n"), typeset("\n", Typesetting:-mo("Retailer profit", mathvariant = "bold", mathcolor = "black"))], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("r"),mn("W"));`, `#msubsup(mi("Pi"),mi("r"),mn("D"));`, `#msubsup(mi("Pi"),mi("r"),mn("S"));`], axis[2] = [color = "#006000"])

 
 

``

Download Q_SEPERATE.mw

in this equation i can't do phase portrait and visualization and invistagation of thus point are really not easy which i do a lot substitution for do more simplify but still not work, i want to do phase portrait for thus point but the parameter are too much and each time i have to determine my point which behavior have for each point i have to know the jacobian of them and each time i have to change the parameter to be biger or smaller than zero so i have to replace thus point to be something very easy like A or B  but i don't know how to do that i need an expert to help me , i did my best in file but i can't finished

f2.mw

I have an ode y''(x) + ...=0 that depends on a parameter a and I would like to see how the solutions vary with a. I created a procedure using odeplot to yield a sequence of plots and display them. Not bad but I really need to look more closely. Plotting y for a=7 and overlaying a plot for y=7.1 is too crude. I want to look at y(x,7.1) - y (x,7) or y(x,7.1) /y (x,7) for x=0..3 say. The obvious solution is to compute y(x,7.1) for x=0..3 and save it as a vector and also y(x, 7). How can I do that so that the pointsx at which y(x, 7.1) are the same as the pointsx for which y(x,7) are evaluated. In other words, how can I specify to dsolve the intermediate points xj for which y(x) is calculated? 

I currently have a 3D plot where the axes are Pn​, w, and the objective value (TM1, TM2, TM3 are all positive). I want to convert this into a 2D regional plot with Pn on the x-axis and w on the y-axis. How do I write the syntax for generating such a 2D region plot?

restart

with(Optimization); with(plots); with(LinearAlgebra)

_local(Pi)

Pi

(1)
 

TM1 := (Pn-.35)*(3.000000000-3.333333333*Pn)+.1115859938-.2510684861*w

(Pn-.35)*(3.000000000-3.333333333*Pn)+.1115859938-.2510684861*w

(2)

TM2 := (Pn-.348)*(2.996666666-3.333333333*Pn)+.1017286174-.2299240474*w

(Pn-.348)*(2.996666666-3.333333333*Pn)+.1017286174-.2299240474*w

(3)

TM3 := (Pn-.348)*(2.996666666-3.333333333*Pn)+.1018208882-.2301325952*w

(Pn-.348)*(2.996666666-3.333333333*Pn)+.1018208882-.2301325952*w

(4)

S1 := plot3d(TM1, Pn = 0 .. 1, w = 0 .. 1, orientation = [165, 75, 0], color = "SkyBlue"); S2 := plot3d(TM2, Pn = 0 .. 1, w = 0 .. 1, orientation = [165, 75, 0], color = "Yellow"); S3 := plot3d(TM3, Pn = 0 .. 1, w = 0 .. 1, orientation = [165, 75, 0], color = "Red")

display({S1, S2, S3})

 

``

Download Plot_3D_to_2D.mw

 

I would like to combine all the plots into a single figure. The curves S1, S2, and S3 represent the manufacturer’s profit as Ce​ varies, and S12, S22, and S33 represent the retailer’s profit for the same changes in Ce​. I want all of these displayed together in one plot using a dual y-axis: one axis for the manufacturer’s profit and the other for the retailer’s profit, with Ce on the x-axis. How to create such a dual-axis plotwith appropriate scaling so that the differences between the curves are also clearly visible.

restart

with(Optimization); with(plots); with(Student[VectorCalculus]); with(LinearAlgebra)

``

_local(Pi)

Pi

(1)

`Π_12` := (0.1455251030e-2*Ce+.5352049476)*(0.369876310e-1-0.3638127575e-2*Ce)+(.8*(-.1671790360+1.121361872*Ce))*(0.1849381518e-1-0.1819063782e-2*Ce)-Ce*(0.1849381518e-1-0.1819063782e-2*Ce)

(0.1455251030e-2*Ce+.5352049476)*(0.369876310e-1-0.3638127575e-2*Ce)+(-.1337432288+.8970894976*Ce)*(0.1849381518e-1-0.1819063782e-2*Ce)-Ce*(0.1849381518e-1-0.1819063782e-2*Ce)

(2)

`Π_22` := (0.1455251030e-2*Ce+.5356096675)*(0.355258312e-1-0.3638127575e-2*Ce)+(.8*(-.1184158360+1.121361872*Ce))*(0.1776291535e-1-0.1819063782e-2*Ce)-Ce*(0.1776291535e-1-0.1819063782e-2*Ce)

(0.1455251030e-2*Ce+.5356096675)*(0.355258312e-1-0.3638127575e-2*Ce)+(-0.9473266880e-1+.8970894976*Ce)*(0.1776291535e-1-0.1819063782e-2*Ce)-Ce*(0.1776291535e-1-0.1819063782e-2*Ce)

(3)

`Π_32` := (0.1455251030e-2*Ce+.5356038465)*(0.355403838e-1-0.3638127575e-2*Ce)+(.8*(-.1179012835+1.121361872*Ce))*(0.1777019161e-1-0.1819063782e-2*Ce)-Ce*(0.1777019161e-1-0.1819063782e-2*Ce)

(0.1455251030e-2*Ce+.5356038465)*(0.355403838e-1-0.3638127575e-2*Ce)+(-0.9432102680e-1+.8970894976*Ce)*(0.1777019161e-1-0.1819063782e-2*Ce)-Ce*(0.1777019161e-1-0.1819063782e-2*Ce)

(4)

S12 := plot(`Π_12`, Ce = 0 .. 0.9e-1, color = [red], labels = ["Ce", "Manufacturer Profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("m"),mn("W"));`]); S22 := plot(`Π_22`, Ce = 0 .. 0.9e-1, color = [green], labels = ["Ce", "Manufacturer profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("m"),mn("D"));`]); S32 := plot(`Π_32`, Ce = 0 .. 0.9e-1, color = [blue], labels = ["Ce", "Manufacturer profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("m"),mn("S"));`])

 

 

 

`Π_1` := (-0.60726413e-1*Ce+.6173851967)*(0.1849381518e-1-0.1819063782e-2*Ce)-0.2500000000e-1*(0.1849381518e-1-0.1819063782e-2*Ce)^2

(-0.60726413e-1*Ce+.6173851967)*(0.1849381518e-1-0.1819063782e-2*Ce)-0.2500000000e-1*(0.1849381518e-1-0.1819063782e-2*Ce)^2

(5)

`Π_2` := (-0.60726413e-1*Ce+.5929853242)*(0.1776291535e-1-0.1819063782e-2*Ce)-0.2500000000e-1*(0.1776291535e-1-0.1819063782e-2*Ce)^2

(-0.60726413e-1*Ce+.5929853242)*(0.1776291535e-1-0.1819063782e-2*Ce)-0.2500000000e-1*(0.1776291535e-1-0.1819063782e-2*Ce)^2

(6)

`Π_3` := (-0.60726413e-1*Ce+.5932282299)*(0.1777019161e-1-0.1819063782e-2*Ce)-0.2500000000e-1*(0.1777019161e-1-0.1819063782e-2*Ce)^2

(-0.60726413e-1*Ce+.5932282299)*(0.1777019161e-1-0.1819063782e-2*Ce)-0.2500000000e-1*(0.1777019161e-1-0.1819063782e-2*Ce)^2

(7)

S1 := plot(`Π_1`, Ce = 0 .. 0.9e-1, color = [yellow], labels = ["Ce", "Retailer profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("r"),mn("W"));`]); S2 := plot(`Π_2`, Ce = 0 .. 0.9e-1, color = [black], labels = ["Ce", "Retailer  profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("r"),mn("D"));`]); S3 := plot(`Π_3`, Ce = 0 .. 0.9e-1, color = [grey], labels = ["Ce", "Retailer profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("r"),mn("S"));`])

 

 

 

dualaxisplot(plot(`Π_22`, Ce = 0 .. 0.9e-1, color = ["red"], labels = ["Ce", "Manufacturer profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("m"),mn("D"));`]), plot(`Π_2`, Ce = 0 .. 0.9e-1, color = ["green"], labels = ["Ce", "Retailer profit"], labeldirections = ["horizontal", "vertical"], legend = [`#msubsup(mi("Pi"),mi("r"),mn("D"));`]), title = "fairnes cost Comparison")

 

display({S1, S12, S2, S22, S3, S32})

 
 

``

Download All_plots_Combined.mw

How to do this with differential geometry for a vectorfield like this one ?
But lets start easier , with straight arrows 

Dear sir here not matching the table values in the given pdf and if the Bc ((D(D(f)))(1) = 0) is also not satisfying 

thin_film_base_paper_comparision.mw

restart;
with(PDEtools):
with(plots):
with(LinearAlgebra):

A1 := 1:

# A2: Density coefficient
A2 := 1:

# A3: Thermal conductivity coefficient (Maxwell model)
A3 := 1:

# A4: Heat capacity coefficient  
A4 := 1:

# A5: Electrical conductivity coefficient (Maxwell model)
A5 := 1:
 

 

# Default parameter values (can be varied in studies)
M := 0:               # Magnetic field parameter
               # Unsteadiness parameter  
lambda_val := 0.5:      # Film thickness parameter (β²)
R := 0:               # Radiation parameter
A_star := 0.5:          # Heat source parameter
B_star := 0.5:          # Heat sink parameter
Ec := 0:              # Eckert number
Pr := 1:            # Prandtl number

OdeSys := A1 * diff(f(eta), eta, eta, eta) +
                     A2 * lambda_val * (f(eta) * diff(f(eta), eta, eta) -
                     diff(f(eta), eta)^2 - S * diff(f(eta), eta) -
                     (S * eta/2) * diff(f(eta), eta, eta)) -
                     M * A5 * diff(f(eta), eta) = 0,(A3 + (4/3)*R) * diff(theta(eta), eta, eta) -
                   Pr * A4 * lambda_val * ((S/2) * (3*theta(eta) + eta*diff(theta(eta), eta)) +
                   2*diff(f(eta), eta)*theta(eta) - f(eta)*diff(theta(eta), eta)) +
                   lambda_val * (B_star * theta(eta) + A_star * diff(f(eta), eta)) = 0;

diff(diff(diff(f(eta), eta), eta), eta)+.5*f(eta)*(diff(diff(f(eta), eta), eta))-.5*(diff(f(eta), eta))^2-.5*S*(diff(f(eta), eta))-.2500000000*S*eta*(diff(diff(f(eta), eta), eta)) = 0, diff(diff(theta(eta), eta), eta)-.2500000000*S*(3*theta(eta)+eta*(diff(theta(eta), eta)))-1.0*(diff(f(eta), eta))*theta(eta)+.5*f(eta)*(diff(theta(eta), eta))+.25*theta(eta)+.25*(diff(f(eta), eta)) = 0

(1)

 

# Boundary conditions
    Cond :=f(0) = 0, D(f)(0) = 1, theta(0) = 1, f(1) = S/2,  D(theta)(1) = 0:
#(D(D(f)))(1) = 0:

SVals := [1, 1.2, 1.4, 1.6,1.8]:



for j to numelems(SVals) do
  
        Ans[j] := dsolve(eval([OdeSys, Cond], S = SVals[j]), numeric,
                         output = listprocedure):
end do:
       

interface(rtablesize = 100); interface(displayprecision = 6); Matrix([[Y, Nu, Nu, Nu, Nu, Nu], seq([k, seq([-(eval(diff(theta(eta), eta), Ans[j]))(k)][], j = 1 .. numelems(SVals))], k = 0)]); interface(rtablesize = 10); interface(displayprecision = -1)

Matrix(%id = 36893490264274272116)

(2)
 

 

Download thin_film_base_paper_comparision.mw
fin_base_paper.pdf

 

I'm Hi,looking to make this exercise dynamic by animating the trajectories and displaying the velocity vector. Do you have any ideas to help me build this pedagogical scenario within the Maple environment? Many thanks in advance.

Hello Maple Community,

I'm working on solving a PDE system for fluid flow in an L-shaped cavity (similar to previous work on H-shaped and square domains ) recently asked by some one here. I've implemented the governing equations in Maple but need help generating contour plots.

I'm attaching:
1. My Maple worksheet l_shape_cavity.mw
2. A PDF with the problem description and equations L_shape_cavity_work.pdf

The main issues I'm facing are:
- Setting up proper boundary conditions for the L-shaped domain
- Generating contour plots for velocity and pressure fields
- Ensuring the solution converges properly

Could you please help me with:
1. Correct implementation of the L-shaped domain geometry
2. Generating proper contour plots
3. Any suggestions for improving the numerical solution

Thank you for your assistance!

Is there a way to use alternative plotting packages in Maple such as open source options: Plotly or Matplotlib?

https://plotly.com/python/

https://matplotlib.org/

1234567LastPage 1 of 127


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