Maple Questions and Posts

These are Posts and Questions associated with the product, Maple

Hello everyone!

I've imported some values I gathered in a dat file, from Python, with the ImportMatrix, to Maple. This procedure gave me a 602x2 matrix, with the elements of the first column being the values of the horizontal plot and the ones of the second column, the values of the vertical plot.

The code that gave the dat file also works fine when I plot it in Python, the problem is that I need to do the same plot in Maple. I tried using differents commands of the plots package, but nothing seens to work

So my question is, anyone knows how can I counterplot the elements of a matrix or do a different approach for the plot of the dat file?

Any help with the problem will be appreciated and if any more information is necessary, please let me know. Thanks!

Hello Everyone;

I have 2D domain meshing defined. I need to plot it like figure given at end. I need to heighlights boundry and ineer points saperately and need to mention the points on it. Domain and mesh is given in Maple file attched. Kindly guide me.

Thanks

Download Question2.mw

Hello,

How do we make the maple to produce as general solutions as possible for ode/pde ??

For example, I have the following ODE with initial conditions (cons);

eq:=diff(x[0](tau), tau) + x[0](tau) - diff(y[0](tau), tau) - y[0](tau)=0;

cons:= x[0](0)=1 , y[0](0)=1;

The general solution for this ode is as

x[0](tau) = y[0](tau) = exp( - tau ), 

but maple returns nothing.

when I use:

dsolve({cons, eq}, [v[0](tau), theta[0](tau)]);

Thanks.

Hi guys,

suppose we have metric in curve geometry such as ds2=A(r)*dt^2-B(r)*dr^2+r^2*dtheta^2+r^2*sin^2(theta)*dphi^2.

how we can calculate and find exact not symbolic different components of contravariant derivative of contravariant derivative of Weyl tensor and Riemann tensor.

with best regards,

Hello Everyone;

Hope you are fine. I am solving system of odes using rk-4 method. For this purpose I formulate the "residual" (on maple file) which is further function of "x" and "y". With the help of discritization point further I convert "residual" into system of ode's. Then i used "sys111 := solve(odes_Combine, `~`[diff](var, t))" to simplify the system. Finnally i applied RK-1. Code is pasted and attached. This all process is for "N=4". When i increase the value of "N", number of Odes increase accordingly. With increasing value of "N" the comand "sys111 := solve(odes_Combine, `~`[diff](var, t))" taking a lot of time due to heavy computation. Is that any way to proceed without this comand for rk-1?

Question1.mw

 


 

restart; with(PDEtools, Solve); with(LinearAlgebra); with(plots); DD := 30; Digits := DD; N := 4; nu := 1.0; t0, tf := 0, 1; Ntt := 10; h := evalf((tf-t0)/(Ntt-1)); xmin := 0; xmax := Pi; `Δxx` := 1.0*xmax/N; ymin := 0; ymax := xmax; `Δyy` := 1.0*ymax/N

0, 1

 

.111111111111111111111111111111

 

.785398163397448309615660845820

 

.785398163397448309615660845820

(1)

residual := 1.000000000*(diff(A[0, 0](t), t))-32.00000000*A[2, 0](t)-32.00000002*A[0, 2](t)+(diff(A[1, 1](t), t))*(4.000000001-8.000000003*y-8.000000003*x+16.00000000*x*y)+(diff(A[1, 0](t), t))*(-2.000000000+4.000000000*x)+(diff(A[0, 3](t), t))*(-4.000000000+40.00000000*y-95.99999994*y^2+64.00000001*y^3)+(diff(A[0, 2](t), t))*(3.000000000-16.00000001*y+16.00000001*y^2)+(diff(A[0, 1](t), t))*(-2.000000001+4.000000000*y)-A[3, 3](t)*(768.0000000-7680.000000*y+18432.00000*y^2-12288.00000*y^3-1536.000000*x+15360.00000*x*y-36863.99998*x*y^2+24576.00000*x*y^3)-A[3, 2](t)*(-576.0000002+3072.000000*y-3072.000000*y^2+1152.000000*x-6144.000000*x*y+6144.000000*x*y^2)-A[3, 1](t)*(384.0000000-768.0000000*y-768.0000006*x+1536.000000*x*y)-A[3, 0](t)*(-192.0000000+384.0000000*x)-A[2, 3](t)*(-128.0000000+1280.000000*y-3072.000000*y^2+2048.000000*y^3)-A[2, 2](t)*(96.00000000-512.0000002*y+512.0000002*y^2)-A[2, 1](t)*(-64.00000002+128.0000000*y)-A[3, 3](t)*(767.9999998-1536.000000*y-7679.999998*x+15360.00000*x*y+18432.00000*x^2-36864.00000*x^2*y-12288.00000*x^3+24576.00000*x^3*y)-A[2, 3](t)*(-575.9999998+1152.000000*y+3072.000000*x-6144.000000*x*y-3072.000000*x^2+6144.000000*x^2*y)-A[3, 2](t)*(-128.0000000+1280.000000*x-3072.000000*x^2+2048.000000*x^3)-A[1, 2](t)*(-64.00000002+128.0000000*x)-A[1, 3](t)*(384.0000000-768.0000000*y-767.9999998*x+1536.000000*x*y)-A[2, 2](t)*(96.00000004-512.0000002*x+512.0000002*x^2)+(diff(A[3, 3](t), t))*(16.00000000-160.0000000*y+383.9999999*y^2-256.0000000*y^3-160.0000000*x+1600.000000*x*y-3839.999999*x*y^2+2560.000000*x*y^3+384.0000000*x^2-3840.000000*x^2*y+9215.999998*x^2*y^2-6144.000001*x^2*y^3-256.0000000*x^3+2560.000000*x^3*y-6143.999998*x^3*y^2+4096.000000*x^3*y^3)+(diff(A[3, 2](t), t))*(-12.00000000+64.00000002*y-64.00000002*y^2+120.0000000*x-640.0000002*x*y+640.0000002*x*y^2-288.0000001*x^2+1536.000000*x^2*y-1536.000000*x^2*y^2+192.0000000*x^3-1024.000000*x^3*y+1024.000000*x^3*y^2)+(diff(A[3, 1](t), t))*(8.000000003-16.00000000*y-80.00000003*x+160.0000000*x*y+192.0000000*x^2-384.0000000*x^2*y-128.0000001*x^3+256.0000000*x^3*y)-A[0, 3](t)*(-191.9999999+384.0000000*y)+(diff(A[3, 0](t), t))*(-4.000000000+40.00000000*x-96.00000002*x^2+64.00000001*x^3)+(diff(A[2, 3](t), t))*(-12.00000000+120.0000000*y-287.9999999*y^2+192.0000000*y^3+64.00000000*x-640.0000000*x*y+1536.000000*x*y^2-1024.000000*x*y^3-64.00000000*x^2+640.0000000*x^2*y-1536.000000*x^2*y^2+1024.000000*x^2*y^3)+(diff(A[2, 2](t), t))*(8.999999999-48.00000002*y+48.00000002*y^2-48.00000000*x+256.0000001*x*y-256.0000001*x*y^2+48.00000000*x^2-256.0000001*x^2*y+256.0000001*x^2*y^2)+(diff(A[2, 1](t), t))*(-6.000000002+12.00000000*y+32.00000001*x-64.00000000*x*y-32.00000001*x^2+64.00000000*x^2*y)+(diff(A[2, 0](t), t))*(3.000000000-16.00000000*x+16.00000000*x^2)+(diff(A[1, 3](t), t))*(8.000000003-80.00000003*y+192.0000000*y^2-128.0000000*y^3-16.00000000*x+160.0000000*x*y-383.9999999*x*y^2+256.0000000*x*y^3)+(diff(A[1, 2](t), t))*(-6.000000000+32.00000001*y-32.00000001*y^2+12.00000000*x-64.00000002*x*y+64.00000002*x*y^2):

for i2 from 0 while i2 <= N-1 do odes11[0, i2] := simplify(eval(residual, [x = 0, y = i2*ymax/(N-1)])) = 0; odes11[N-1, i2] := simplify(eval(residual, [x = xmax, y = i2*ymax/(N-1)])) = 0 end do:

8

(2)

odes_Combine := {seq(seq(odes11[i, j], i = 0 .. N-1), j = 0 .. N-1)}:

sys111 := solve(odes_Combine, `~`[diff](var, t)):

ICS1 := {A[0, 0](0) = .444104979341173495851499233536, A[0, 1](0) = .198590961107083475045046921568, A[0, 2](0) = -0.167999146492673347540059075790e-1, A[0, 3](0) = -0.869171705198864625153083083786e-3, A[1, 0](0) = .198590961107083475045046921567, A[1, 1](0) = 0.888041604305848495880917177172e-1, A[1, 2](0) = -0.751243816645416714455046298805e-2, A[1, 3](0) = -0.388668563362181391196975707953e-3, A[2, 0](0) = -0.167999146492673347540059075793e-1, A[2, 1](0) = -0.751243816645416714455046298835e-2, A[2, 2](0) = 0.635518954643030408055028178047e-3, A[2, 3](0) = 0.328796368925226898150257328603e-4, A[3, 0](0) = -0.869171705198864625153083083734e-3, A[3, 1](0) = -0.388668563362181391196975707910e-3, A[3, 2](0) = 0.328796368925226898150257328592e-4, A[3, 3](0) = 0.170108305076655667148638268230e-5}:

f, diffs := eval(GenerateMatrix(`~`[`-`](`~`[rhs](sys222), `~`[lhs](sys222)), var1))

f, diffs := Matrix(16, 16, {(1, 1) = 0, (1, 2) = 0, (1, 3) = 32., (1, 4) = 0.494812294492356575865153049102e-27, (1, 5) = 0, (1, 6) = 0, (1, 7) = 0.120000000000000000001649374315e-7, (1, 8) = -0.107999999927999999998854228220e-6, (1, 9) = 32.0000000200000000000000000000, (1, 10) = -0.199999999999999999998350625685e-7, (1, 11) = 0.249999999859375000081951230025e-7, (1, 12) = -0.700000000203125000132933066388e-7, (1, 13) = 0.196000000000000000000494812294e-6, (1, 14) = 0.292000000072000000001204420404e-6, (1, 15) = -0.458000000726562499721923065316e-6, (1, 16) = 0.682900000453875000014432471170e-5, (2, 1) = 0, (2, 2) = 0, (2, 3) = 0, (2, 4) = -0.377561971763063776372092766396e-27, (2, 5) = 0, (2, 6) = 0, (2, 7) = 32.0000000000000000000000000000, (2, 8) = 0.719999999999999999998878327317e-7, (2, 9) = 0, (2, 10) = -0.125853990587687925457364255465e-27, (2, 11) = 0.906355783222184042180194163758e-27, (2, 12) = 0.135077431625990682476379737660e-25, (2, 13) = 96.0000000000000000000000000001, (2, 14) = 0.719999999999999999989394464730e-7, (2, 15) = -0.549999999914062500010607576813e-6, (2, 16) = 0.202000000048749999997617654955e-5, (3, 1) = 0, (3, 2) = 0, (3, 3) = 0, (3, 4) = 0.855583965847405137008732798371e-28, (3, 5) = 0, (3, 6) = 0, (3, 7) = -0.257808598553160159742093659020e-28, (3, 8) = -0.377264825438544618607975742790e-27, (3, 9) = 0, (3, 10) = 0.285194655282468379002910932790e-28, (3, 11) = 31.9999999925000000046874999970, (3, 12) = 0.326865301360930805043812804544e-26, (3, 13) = -0.773425795659480479226280977060e-28, (3, 14) = -0.313579545661510489918366218529e-27, (3, 15) = -0.149999999882812500075601322065e-6, (3, 16) = 0.324999999796875000093151106353e-6, (4, 1) = 0, (4, 2) = 0, (4, 3) = 0, (4, 4) = -0.384112032581666751703476763000e-29, (4, 5) = 0, (4, 6) = 0, (4, 7) = 0.265935771387910529598689301718e-29, (4, 8) = 0.399754551928273029196600976861e-28, (4, 9) = 0, (4, 10) = -0.128037344193888917234492254333e-29, (4, 11) = 0.173718566046259004921454811253e-28, (4, 12) = -0.553232882345597286403223410199e-27, (4, 13) = 0.797807314163731588796067905154e-29, (4, 14) = 0.427742792008362106477653509643e-28, (4, 15) = 31.9999999950000000007812499996, (4, 16) = 0.583137134641934297089284679036e-26, (5, 1) = 0, (5, 2) = 0, (5, 3) = 0, (5, 4) = 96.0000000000000000000000000001, (5, 5) = 0, (5, 6) = 0, (5, 7) = -0.125853990576278889372664086359e-27, (5, 8) = -0.780000000000000000003341913398e-7, (5, 9) = 0, (5, 10) = 32.0000000000000000000000000000, (5, 11) = 0.155215894719877680168982772333e-28, (5, 12) = 0.179999999957812500011610427218e-6, (5, 13) = -0.377561971728836668117992259076e-27, (5, 14) = 0.121999999999999999999928850210e-6, (5, 15) = 0.957742348838601502120463181878e-26, (5, 16) = 0.413250000106171874986265224797e-5, (6, 1) = 0, (6, 2) = 0, (6, 3) = 0, (6, 4) = -0.821348457439978150891092618719e-28, (6, 5) = 0, (6, 6) = 0, (6, 7) = -0.273782819058452669879599110853e-28, (6, 8) = 95.9999999999999999999999999997, (6, 9) = 0, (6, 10) = -0.273782819146659383630364206240e-28, (6, 11) = 0.294057068291966163490658104104e-27, (6, 12) = -0.253498333196688505804635565222e-27, (6, 13) = -0.821348457175358009638797332558e-28, (6, 14) = 95.9999999999999999999999999997, (6, 15) = 0.212121033252676198558579131631e-28, (6, 16) = 0.649999999999999999980740836208e-6, (7, 1) = 0, (7, 2) = 0, (7, 3) = 0, (7, 4) = 0.186123768597305842557431955743e-28, (7, 5) = 0, (7, 6) = 0, (7, 7) = 0.214460223691860703703477959545e-28, (7, 8) = 0.317673924810187018756335641686e-28, (7, 9) = 0, (7, 10) = 0.620412561991019475191439852476e-29, (7, 11) = 0.753895620987131323747484439705e-28, (7, 12) = 95.9999999700000000093749999970, (7, 13) = 0.643380671075582111110433878635e-28, (7, 14) = 0.348244413167432788858088750543e-30, (7, 15) = -0.195081345734130085456007896310e-26, (7, 16) = 0.162499999949218750020914346448e-6, (8, 1) = 0, (8, 2) = 0, (8, 3) = 0, (8, 4) = -0.835597462589282450911924283887e-30, (8, 5) = 0, (8, 6) = 0, (8, 7) = -0.168983990754200234313642237958e-29, (8, 8) = 0.255518912827614707211229660888e-30, (8, 9) = 0, (8, 10) = -0.278532487529760816970641427962e-30, (8, 11) = -0.912041057783558505972445866734e-29, (8, 12) = 0.152862192823148604497047654434e-28, (8, 13) = -0.506951972262600702940926713875e-29, (8, 14) = 0.212025424265299406832408057357e-29, (8, 15) = 0.158222957859551043617221056103e-27, (8, 16) = 96.0000000000000000000000000002, (9, 1) = 0, (9, 2) = 0, (9, 3) = 0, (9, 4) = -0.773425795970180636575593526265e-28, (9, 5) = 0, (9, 6) = 0, (9, 7) = 0.285194655390087477280223771532e-28, (9, 8) = -0.241100887243597349107036806234e-27, (9, 9) = 0, (9, 10) = -0.257808598656726878858531175422e-28, (9, 11) = 32.0000000125000000000000000004, (9, 12) = 0.999999999843750000174507862823e-8, (9, 13) = 0.855583966170262431840671314596e-28, (9, 14) = -0.104420360226003256663758222866e-27, (9, 15) = 0.600000000000000000027497059897e-7, (9, 16) = 0.900000000046874999977170328969e-6, (10, 1) = 0, (10, 2) = 0, (10, 3) = 0, (10, 4) = 0.643380671224932994877201196193e-28, (10, 5) = 0, (10, 6) = 0, (10, 7) = 0.620412562284547562356437593923e-29, (10, 8) = -0.782971264706294608812923943602e-28, (10, 9) = 0, (10, 10) = 0.214460223741644331625733732064e-28, (10, 11) = -0.117716452160171050903010422567e-27, (10, 12) = -0.324249553007268016939337229307e-26, (10, 13) = 0.186123768685364268706931278177e-28, (10, 14) = 0.210791990319339808396292213890e-27, (10, 15) = 95.9999999999999999999999999990, (10, 16) = 0.601289924118833452883693495332e-26, (11, 1) = 0, (11, 2) = 0, (11, 3) = 0, (11, 4) = -0.145794923079456919867181504653e-28, (11, 5) = 0, (11, 6) = 0, (11, 7) = -0.485983076931523066223938348837e-29, (11, 8) = 0.703045314344404024740114826873e-28, (11, 9) = 0, (11, 10) = -0.485983076931523066223938348844e-29, (11, 11) = 0.154061910958820937154327251969e-28, (11, 12) = 0.586431085917646726477197552134e-27, (11, 13) = -0.145794923079456919867181504651e-28, (11, 14) = 0.327116591013740734656854347967e-28, (11, 15) = 0.186427448215109472676159333906e-27, (11, 16) = 0.727156843809743343593213639608e-26, (12, 1) = 0, (12, 2) = 0, (12, 3) = 0, (12, 4) = 0.654542236344866764687318521378e-30, (12, 5) = 0, (12, 6) = 0, (12, 7) = 0.382930495785563772474113758933e-30, (12, 8) = -0.765771840140216030924576968705e-29, (12, 9) = 0, (12, 10) = 0.218180745448288921562439507126e-30, (12, 11) = -0.591357855581324858104400230586e-30, (12, 12) = 0.164090126078907967224367765176e-28, (12, 13) = 0.114879148735669131742234127680e-29, (12, 14) = -0.733606589050003370341598338138e-29, (12, 15) = 0.279365514914751130455040418258e-28, (12, 16) = -0.138821502091830040436688448298e-26, (13, 1) = 0, (13, 2) = 0, (13, 3) = 0, (13, 4) = 0.797807313447167969819086050522e-29, (13, 5) = 0, (13, 6) = 0, (13, 7) = -0.128037344212226672551029214969e-29, (13, 8) = 0.262885403001488132812902903311e-28, (13, 9) = 0, (13, 10) = 0.265935771149055989939695350174e-29, (13, 11) = -0.349411324204567081081722661297e-28, (13, 12) = 31.9999999950000000007812499995, (13, 13) = -0.384112032636680017653087644907e-29, (13, 14) = 0.119403167752948354510697994999e-28, (13, 15) = -0.452504513537780686847551220204e-27, (13, 16) = 0.149999999976562500006592455374e-6, (14, 1) = 0, (14, 2) = 0, (14, 3) = 0, (14, 4) = -0.506951972202161632959380608780e-29, (14, 5) = 0, (14, 6) = 0, (14, 7) = -0.278532487328297250365487744273e-30, (14, 8) = 0.100313589069551339782957918087e-28, (14, 9) = 0, (14, 10) = -0.168983990734053877653126869593e-29, (14, 11) = 0.876003797684675659527198447426e-29, (14, 12) = 0.309396538522635365039103628797e-27, (14, 13) = -0.835597461984891751096463232820e-30, (14, 14) = -0.169500948608311509445295032991e-28, (14, 15) = 0.104005614175784513152332127959e-27, (14, 16) = 95.9999999999999999999999999996, (15, 1) = 0, (15, 2) = 0, (15, 3) = 0, (15, 4) = 0.114879148750778899237620653952e-29, (15, 5) = 0, (15, 6) = 0, (15, 7) = 0.218180745498654813213727928025e-30, (15, 8) = -0.867251219227502985269662069579e-29, (15, 9) = 0, (15, 10) = 0.382930495835929664125402179841e-30, (15, 11) = -0.267864188359583543656192185112e-29, (15, 12) = -0.387791753042961333529856694716e-28, (15, 13) = 0.654542236495964439641183784074e-30, (15, 14) = -0.523627245808308931882255033583e-29, (15, 15) = 0.369199231034048272468531636165e-28, (15, 16) = -0.123439611085554953594747603640e-26, (16, 1) = 0, (16, 2) = 0, (16, 3) = 0, (16, 4) = -0.515746730509193430144544493936e-31, (16, 5) = 0, (16, 6) = 0, (16, 7) = -0.171915576836397810048181497977e-31, (16, 8) = 0.857347676859656256220355661580e-30, (16, 9) = 0, (16, 10) = -0.171915576836397810048181497979e-31, (16, 11) = 0.182597096197097886514765184582e-30, (16, 12) = -0.370616214664321329971866697584e-29, (16, 13) = -0.515746730509193430144544493932e-31, (16, 14) = 0.865925397235117524875431212196e-30, (16, 15) = -0.750058451906403875595888288641e-29, (16, 16) = 0.183460376006651920829411996611e-27}), Vector(16, {(1) = diff(A[0, 0](t), t), (2) = diff(A[0, 1](t), t), (3) = diff(A[0, 2](t), t), (4) = diff(A[0, 3](t), t), (5) = diff(A[1, 0](t), t), (6) = diff(A[1, 1](t), t), (7) = diff(A[1, 2](t), t), (8) = diff(A[1, 3](t), t), (9) = diff(A[2, 0](t), t), (10) = diff(A[2, 1](t), t), (11) = diff(A[2, 2](t), t), (12) = diff(A[2, 3](t), t), (13) = diff(A[3, 0](t), t), (14) = diff(A[3, 1](t), t), (15) = diff(A[3, 2](t), t), (16) = diff(A[3, 3](t), t)})

(3)

``

npts := Ntt:

``

``

``

``


 

Download Question1.mw

 

Suppose one has the following equation,

.

Based on that equation, I have two questions:

1. How may one solve it for \kappa using Maple?

2. How may we simplify it?

Thanks in advance.

Ps: I have tried to use the "solve" and "simplify" commands. However, Maplesoft does not return a result but rather the same equation.

A user found that the behaviour of calling a command from a library with a long form command name which invoked another command from that library with the short form name was unexpected:

restart;
ScientificConstants:-GetValue(Constant(g))

Error, (in ScientificConstants:-GetValue) `Constant(g)` is not a scientific constant object

 

 

 

We suggested to either

[Edit May 13 after Acer's improvements]

A) import the package such that all short form names of commands from the package are available in the Maple session and use the short form of both commands:

restart;
with(ScientificConstants):
GetValue(Constant(g));

9.80665

(1)

Download scientificConstantsGetValueShortFormsWithPackage.mw

or

B) use long forms for both command names:

restart;
ScientificConstants:-GetValue(ScientificConstants:-Constant(g))

9.80665

(1)

Download scientificConstantsGetValueLongFormLongForm.mw

or

C) to test that a long form command and a short form command work together, import the package for the short form command:

restart;
with(ScientificConstants):
ScientificConstants:-GetValue(Constant(g))

9.80665

(1)

Download scientificConstantsGetValueLongFormWithPackage.mw

Further details can be found in the article ?UsingPackages

Hello!

I'd like to sort variables which are non-commutative and obey certain commuting rules in a preferred order. Here is a minimal example

with(Physics)

Setup(mathematicalnotation = true):Setup(noncommutativeprefix = {q, w}, algebrarule = {%Commutator(q, w) = A})

If I want to rewrite q*w as A+w*q since I prefer the order w>q, what should I do? I tried sort(Simplify(q*w, algebrarules), [w, q]) but it doesn't work.

Thank you in advance.

Hello Guys

I got the Mapple 2022 Student version and I try a couple of time to firgure out why that doesn't work at my Student Version. Please, could anybody help me. Thx a lot. 

Newton Method:

f(x) = x^2 assigned to function why I doesn't have right click for this function?

g(x) = x - f(x)/f'(x);

g(1.3) doesn't work because faild he want 2 arguments. That I figure out if I assigned like this

g(x) := x->x f(x)/f'(x) but he do not calc that right. It make me really creapy. Maybe tha Student version doesn't have this fearure is it possible?

This is another think.

a := x^2;

D(a);
                            2 D(x) x ???? why no 2x?

Next example:

f := x -> 5*x^3 + x - 7

D2f := x -> diff(f(x), x)

                         D2f:=x->d/dx f(x) ??? why not 15x^2+1?
  

Hello.

Is there a way to reduce the time of the process of calculations in maple?

I have 26 coupled simple algebraic equations. But still, I could not get any solution for them.

My codes are as follows:

restart;
eq[1] := d[0] = 1:
eq[2] := d[0] + d[1] + d[2] + d[3] + d[4] + d[5] + d[6] + d[7] = 0:
eq[3] := b[0] = 1:
eq[4] := b[0] + b[1] + b[2] + b[3] + b[4] + b[5] + b[6] + b[7] = 0:
eq[5] := a[0] = -0.5:
eq[6] := d[1] = 1 + 1.0*a[2]:
eq[7] := a[0] + a[1] + a[2] + a[3] + a[4] + a[5] + a[6] + a[7] + a[8] + a[9] = 0.5:
eq[8] := d[1] + 2*d[2] + 3*d[3] + 4*d[4] + 5*d[5] + 6*d[6] + 7*d[7] = 1.0*a[2] + 3.0*a[3] + 6.0*a[4] + 10.0*a[5] + 15.0*a[6] + 21.0*a[7] + 28.0*a[8] + 36.0*a[9]:
eq[9] := 24*a[4] - 2.104513094*a[1]*a[2] + 6.313539282*a[0]*a[3] + 5.165076420*b[1] + 5.261282735*d[1] = 0:
eq[10] := -88.3895499*a[7]^2 - 191.5106915*a[7]*a[8] - 176.7790999*a[7]*a[9] - 117.8527333*a[8]^2 - 252.5415715*a[8]*a[9] - 151.5249428*a[9]^2 + 25.25415713*a[0]*a[4] + 63.13539282*a[0]*a[5] + 126.2707856*a[0]*a[6] + 220.9738749*a[0]*a[7] + 353.5581998*a[0]*a[8] + 530.3372997*a[0]*a[9] + 12.62707857*a[1]*a[4] + 42.09026188*a[1]*a[5] + 94.70308919*a[1]*a[6] + 176.7790999*a[1]*a[7] + 294.6318332*a[1]*a[8] + 454.5748283*a[1]*a[9] - 4.209026188*a[2]^2 - 12.62707857*a[2]*a[3] - 8.41805237*a[2]*a[4] + 10.52256547*a[2]*a[5] + 50.50831422*a[2]*a[6] + 117.8527333*a[2]*a[7] + 218.8693618*a[2]*a[8] + 359.8717391*a[2]*a[9] - 12.62707857*a[3]^2 - 31.56769641*a[3]*a[4] - 25.25415713*a[3]*a[5] + 50.5083143*a[3]*a[7] + 132.5843249*a[3]*a[8] + 252.5415713*a[3]*a[9] - 25.25415713*a[4]^2 - 58.92636665*a[4]*a[5] - 50.5083142*a[4]*a[6] - 18.9406178*a[4]*a[7] + 42.0902619*a[4]*a[8] + 138.8978642*a[4]*a[9] - 42.09026188*a[5]^2 - 94.7030892*a[5]*a[6] - 84.1805237*a[5]*a[7] - 46.2992881*a[5]*a[8] + 25.2541571*a[5]*a[9] - 63.1353929*a[6]^2 - 138.8978642*a[6]*a[7] - 126.2707857*a[6]*a[8] - 82.0760107*a[6]*a[9] - 2.104513094*a[1]*a[2] + 6.313539282*a[0]*a[3] + 26.30641368*d[5] + 31.56769641*d[6] + 36.82897914*d[7] + 15.78384820*d[3] + 21.04513094*d[4] + 5.261282735*d[1] + 10.52256547*d[2] + 36.15553494*b[7] + 25.82538210*b[5] + 30.99045852*b[6] + 10.33015284*b[2] + 15.49522926*b[3] + 20.66030568*b[4] + 5.165076420*b[1] + 3024.*a[9] + 360.*a[6] + 840.*a[7] + 1680.*a[8] + 24.*a[4] + 120.*a[5] = 0:
eq[11] := 120.*a[5] - 4.209026188*a[2]^2 + 25.25415713*a[0]*a[4] + 10.33015284*b[2] + 10.52256547*d[2] = 0:
eq[12] := -972.2850495*a[7]^2 - 2298.128299*a[7]*a[8] - 2298.128298*a[7]*a[9] - 1532.085532*a[8]^2 - 3535.581998*a[8]*a[9] - 2272.874142*a[9]^2 + 25.25415713*a[0]*a[4] + 126.2707856*a[0]*a[5] + 378.8123569*a[0]*a[6] + 883.8954995*a[0]*a[7] + 1767.790999*a[0]*a[8] + 3182.023798*a[0]*a[9] + 25.25415713*a[1]*a[4] + 126.2707856*a[1]*a[5] + 378.8123569*a[1]*a[6] + 883.8954995*a[1]*a[7] + 1767.790999*a[1]*a[8] + 3182.023798*a[1]*a[9] - 4.209026188*a[2]^2 - 25.25415713*a[2]*a[3] - 25.25415713*a[2]*a[4] + 42.09026184*a[2]*a[5] + 252.5415713*a[2]*a[6] + 707.1163996*a[2]*a[7] + 1532.085532*a[2]*a[8] + 2878.973912*a[2]*a[9] - 37.88123569*a[3]^2 - 126.2707857*a[3]*a[4] - 126.2707857*a[3]*a[5] + 353.5581998*a[3]*a[7] + 1060.674599*a[3]*a[8] + 2272.874141*a[3]*a[9] - 126.2707857*a[4]^2 - 353.5581998*a[4]*a[5] - 353.5581998*a[4]*a[6] - 151.5249424*a[4]*a[7] + 378.812357*a[4]*a[8] + 1388.978642*a[4]*a[9] - 294.6318332*a[5]^2 - 757.6247134*a[5]*a[6] - 757.624714*a[5]*a[7] - 462.992880*a[5]*a[8] + 277.795729*a[5]*a[9] - 568.2185354*a[6]^2 - 1388.978642*a[6]*a[7] - 1388.978642*a[6]*a[8] - 984.912128*a[6]*a[9] + 105.2256547*d[5] + 157.8384820*d[6] + 220.9738748*d[7] + 31.56769640*d[3] + 63.13539282*d[4] + 10.52256547*d[2] + 216.9332096*b[7] + 103.3015284*b[5] + 154.9522926*b[6] + 10.33015284*b[2] + 30.99045852*b[3] + 61.98091704*b[4] + 15120.*a[9] + 720.*a[6] + 2520.*a[7] + 6720.*a[8] + 120.*a[5] = 0:
eq[13] := 720.*a[6] - 25.25415713*a[2]*a[3] + 25.25415713*a[1]*a[4] + 126.2707856*a[0]*a[5] + 30.99045852*b[3] + 31.56769640*d[3] = 0:
eq[14] := -9722.850492*a[7]^2 - 25279.41129*a[7]*a[8] - 27577.53959*a[7]*a[9] - 18385.02639*a[8]^2 - 45962.56593*a[8]*a[9] - 31820.23799*a[9]^2 + 126.2707856*a[0]*a[5] + 757.6247138*a[0]*a[6] + 2651.686498*a[0]*a[7] + 7071.163996*a[0]*a[8] + 15910.11899*a[0]*a[9] + 25.25415713*a[1]*a[4] + 252.5415712*a[1]*a[5] + 1136.437071*a[1]*a[6] + 3535.581998*a[1]*a[7] + 8838.954995*a[1]*a[8] + 19092.14279*a[1]*a[9] - 25.25415713*a[2]*a[3] - 50.50831424*a[2]*a[4] + 126.2707856*a[2]*a[5] + 1010.166285*a[2]*a[6] + 3535.581998*a[2]*a[7] + 9192.513195*a[2]*a[8] + 20152.81739*a[2]*a[9] - 75.76247138*a[3]^2 - 378.8123569*a[3]*a[4] - 505.0831425*a[3]*a[5] + 2121.349198*a[3]*a[7] + 7424.722196*a[3]*a[8] + 18182.99313*a[3]*a[9] - 505.0831426*a[4]^2 - 1767.790999*a[4]*a[5] - 2121.349199*a[4]*a[6] - 1060.674600*a[4]*a[7] + 3030.498859*a[4]*a[8] + 12500.80778*a[4]*a[9] - 1767.790999*a[5]^2 - 5303.372998*a[5]*a[6] - 6060.997709*a[5]*a[7] - 4166.935929*a[5]*a[8] + 2777.95729*a[5]*a[9] - 4545.748282*a[6]^2 - 12500.80779*a[6]*a[7] - 13889.78642*a[6]*a[8] - 10834.03341*a[6]*a[9] + 315.6769641*d[5] + 631.3539280*d[6] + 1104.869374*d[7] + 31.56769640*d[3] + 126.2707856*d[4] + 1084.666048*b[7] + 309.9045852*b[5] + 619.8091704*b[6] + 30.99045852*b[3] + 123.9618341*b[4] + 60480.*a[9] + 720.*a[6] + 5040.*a[7] + 20160.*a[8] - 2.*10^(-7)*a[3]*a[6] = 0:
eq[15] := 2.*d[2] + 5.261282735*a[0]*d[1] - 2.630641368*d[0] = 0:
eq[16] := 17.36935863*d[5] + 27.36935863*d[6] + 39.36935863*d[7] + 3.369358632*d[3] + 9.369358632*d[4] - 2.630641368*d[0] - 2.630641368*d[1] - 0.630641368*d[2] + 36.82897914*a[6]*d[7] + 5.261282735*a[7]*d[1] + 10.52256547*a[7]*d[2] + 15.78384820*a[7]*d[3] + 21.04513094*a[7]*d[4] + 26.30641368*a[7]*d[5] + 31.56769641*a[7]*d[6] + 36.82897914*a[7]*d[7] + 5.261282735*a[8]*d[1] + 10.52256547*a[8]*d[2] + 15.78384820*a[8]*d[3] + 21.04513094*a[8]*d[4] + 26.30641368*a[8]*d[5] + 31.56769641*a[8]*d[6] + 36.82897914*a[8]*d[7] + 5.261282735*a[9]*d[1] + 10.52256547*a[9]*d[2] + 15.78384820*a[9]*d[3] + 21.04513094*a[9]*d[4] + 26.30641368*a[9]*d[5] + 31.56769641*a[9]*d[6] + 36.82897914*a[9]*d[7] + 10.52256547*a[0]*d[2] + 15.78384820*a[0]*d[3] + 21.04513094*a[0]*d[4] + 26.30641368*a[0]*d[5] + 31.56769641*a[0]*d[6] + 36.82897914*a[0]*d[7] + 5.261282735*a[1]*d[1] + 10.52256547*a[1]*d[2] + 15.78384820*a[1]*d[3] + 21.04513094*a[1]*d[4] + 26.30641368*a[1]*d[5] + 31.56769641*a[1]*d[6] + 36.82897914*a[1]*d[7] + 5.261282735*a[2]*d[1] + 10.52256547*a[2]*d[2] + 15.78384820*a[2]*d[3] + 21.04513094*a[2]*d[4] + 26.30641368*a[2]*d[5] + 31.56769641*a[2]*d[6] + 36.82897914*a[2]*d[7] + 5.261282735*a[3]*d[1] + 10.52256547*a[3]*d[2] + 15.78384820*a[3]*d[3] + 21.04513094*a[3]*d[4] + 26.30641368*a[3]*d[5] + 31.56769641*a[3]*d[6] + 36.82897914*a[3]*d[7] + 5.261282735*a[4]*d[1] + 10.52256547*a[4]*d[2] + 15.78384820*a[4]*d[3] + 21.04513094*a[4]*d[4] + 26.30641368*a[4]*d[5] + 31.56769641*a[4]*d[6] + 36.82897914*a[4]*d[7] + 5.261282735*a[5]*d[1] + 10.52256547*a[5]*d[2] + 15.78384820*a[5]*d[3] + 21.04513094*a[5]*d[4] + 26.30641368*a[5]*d[5] + 31.56769641*a[5]*d[6] + 36.82897914*a[5]*d[7] + 5.261282735*a[6]*d[1] + 10.52256547*a[6]*d[2] + 15.78384820*a[6]*d[3] + 21.04513094*a[6]*d[4] + 26.30641368*a[6]*d[5] + 31.56769641*a[6]*d[6] + 5.261282735*a[0]*d[1] = 0:
eq[17] := 6.*d[3] + 5.261282735*a[1]*d[1] + 10.52256547*a[0]*d[2] - 2.630641368*d[1] = 0:
eq[18] := 46.84679316*d[5] + 104.2161518*d[6] + 191.5855104*d[7] - 1.891924104*d[3] + 13.47743453*d[4] - 2.630641368*d[1] - 5.261282736*d[2] + 441.9477498*a[6]*d[7] + 36.82897914*a[7]*d[1] + 84.18052376*a[7]*d[2] + 142.0546338*a[7]*d[3] + 210.4513094*a[7]*d[4] + 289.3705504*a[7]*d[5] + 378.8123569*a[7]*d[6] + 478.7767289*a[7]*d[7] + 42.09026188*a[8]*d[1] + 94.70308923*a[8]*d[2] + 157.8384820*a[8]*d[3] + 231.4964403*a[8]*d[4] + 315.6769641*a[8]*d[5] + 410.3800533*a[8]*d[6] + 515.6057081*a[8]*d[7] + 47.35154462*a[9]*d[1] + 105.2256547*a[9]*d[2] + 173.6223302*a[9]*d[3] + 252.5415713*a[9]*d[4] + 341.9833778*a[9]*d[5] + 441.9477497*a[9]*d[6] + 552.4346872*a[9]*d[7] + 10.52256547*a[0]*d[2] + 31.56769641*a[0]*d[3] + 63.13539282*a[0]*d[4] + 105.2256547*a[0]*d[5] + 157.8384820*a[0]*d[6] + 220.9738749*a[0]*d[7] + 5.261282735*a[1]*d[1] + 21.04513094*a[1]*d[2] + 47.35154461*a[1]*d[3] + 84.18052376*a[1]*d[4] + 131.5320684*a[1]*d[5] + 189.4061784*a[1]*d[6] + 257.8028540*a[1]*d[7] + 10.52256547*a[2]*d[1] + 31.56769641*a[2]*d[2] + 63.13539282*a[2]*d[3] + 105.2256547*a[2]*d[4] + 157.8384820*a[2]*d[5] + 220.9738748*a[2]*d[6] + 294.6318332*a[2]*d[7] + 15.78384820*a[3]*d[1] + 42.09026188*a[3]*d[2] + 78.91924103*a[3]*d[3] + 126.2707856*a[3]*d[4] + 184.1448957*a[3]*d[5] + 252.5415712*a[3]*d[6] + 331.4608123*a[3]*d[7] + 21.04513094*a[4]*d[1] + 52.61282735*a[4]*d[2] + 94.70308923*a[4]*d[3] + 147.3159166*a[4]*d[4] + 210.4513094*a[4]*d[5] + 284.1092676*a[4]*d[6] + 368.2897915*a[4]*d[7] + 26.30641368*a[5]*d[1] + 63.13539282*a[5]*d[2] + 110.4869374*a[5]*d[3] + 168.3610475*a[5]*d[4] + 236.7577231*a[5]*d[5] + 315.6769640*a[5]*d[6] + 405.1187706*a[5]*d[7] + 31.56769641*a[6]*d[1] + 73.65795829*a[6]*d[2] + 126.2707856*a[6]*d[3] + 189.4061784*a[6]*d[4] + 263.0641367*a[6]*d[5] + 347.2446605*a[6]*d[6] = 0:
eq[19] := 24.*d[4] + 10.52256547*a[2]*d[1] + 21.04513094*a[1]*d[2] + 31.56769641*a[0]*d[3] - 5.261282736*d[2] = 0:
eq[20] := 67.38717264*d[5] + 281.0807590*d[6] + 729.5130625*d[7] - 15.78384821*d[3] - 7.56769641*d[4] - 5.261282736*d[2] + 4861.425246*a[6]*d[7] + 220.9738749*a[7]*d[1] + 589.2636663*a[7]*d[2] + 1136.437070*a[7]*d[3] + 1894.061785*a[7]*d[4] + 2893.705504*a[7]*d[5] + 4166.935926*a[7]*d[6] + 5745.320746*a[7]*d[7] + 294.6318332*a[8]*d[1] + 757.6247138*a[8]*d[2] + 1420.546338*a[8]*d[3] + 2314.964404*a[8]*d[4] + 3472.446605*a[8]*d[5] + 4924.560640*a[8]*d[6] + 6702.874204*a[8]*d[7] + 378.8123569*a[9]*d[1] + 947.0308923*a[9]*d[2] + 1736.223302*a[9]*d[3] + 2777.957285*a[9]*d[4] + 4103.800534*a[9]*d[5] + 5745.320747*a[9]*d[6] + 7734.085620*a[9]*d[7] + 31.56769641*a[0]*d[3] + 126.2707856*a[0]*d[4] + 315.6769641*a[0]*d[5] + 631.3539282*a[0]*d[6] + 1104.869374*a[0]*d[7] + 21.04513094*a[1]*d[2] + 94.70308923*a[1]*d[3] + 252.5415712*a[1]*d[4] + 526.1282735*a[1]*d[5] + 947.0308923*a[1]*d[6] + 1546.817124*a[1]*d[7] + 10.52256547*a[2]*d[1] + 63.13539282*a[2]*d[2] + 189.4061784*a[2]*d[3] + 420.9026188*a[2]*d[4] + 789.1924103*a[2]*d[5] + 1325.843249*a[2]*d[6] + 2062.422832*a[2]*d[7] + 31.56769641*a[3]*d[1] + 126.2707856*a[3]*d[2] + 315.6769641*a[3]*d[3] + 631.3539281*a[3]*d[4] + 1104.869374*a[3]*d[5] + 1767.790999*a[3]*d[6] + 2651.686498*a[3]*d[7] + 63.13539282*a[4]*d[1] + 210.4513094*a[4]*d[2] + 473.5154462*a[4]*d[3] + 883.8954995*a[4]*d[4] + 1473.159166*a[4]*d[5] + 2272.874141*a[4]*d[6] + 3314.608123*a[4]*d[7] + 105.2256547*a[5]*d[1] + 315.6769641*a[5]*d[2] + 662.9216246*a[5]*d[3] + 1178.527333*a[5]*d[4] + 1894.061784*a[5]*d[5] + 2841.092676*a[5]*d[6] + 4051.187706*a[5]*d[7] + 157.8384820*a[6]*d[1] + 441.9477497*a[6]*d[2] + 883.8954995*a[6]*d[3] + 1515.249428*a[6]*d[4] + 2367.577230*a[6]*d[5] + 3472.446605*a[6]*d[6] = 0:
eq[21] := 2.119408818*b[2] + 6.176017503*a[0]*b[1] + 42.07215928*a[2] + 0.5*d[0] = 0:
eq[22] := 0.5*d[5] + 0.5*d[6] + 0.5*d[7] + 0.5*d[3] + 0.5*d[4] + 0.5*d[0] + 0.5*d[1] + 0.5*d[2] + 44.50758518*b[7] + 21.19408818*b[5] + 31.79113227*b[6] + 2.119408818*b[2] + 6.358226454*b[3] + 12.71645291*b[4] + 1514.597734*a[9] + 631.0823892*a[6] + 883.5153448*a[7] + 1178.020460*a[8] + 126.2164778*a[3] + 252.4329557*a[4] + 420.7215928*a[5] + 42.07215928*a[2] + 12.35203501*a[0]*b[2] + 18.52805251*a[0]*b[3] + 24.70407001*a[0]*b[4] + 30.88008752*a[0]*b[5] + 37.05610502*a[0]*b[6] + 43.23212252*a[0]*b[7] + 6.176017503*a[1]*b[1] + 12.35203501*a[1]*b[2] + 18.52805251*a[1]*b[3] + 24.70407001*a[1]*b[4] + 30.88008752*a[1]*b[5] + 37.05610502*a[1]*b[6] + 43.23212252*a[1]*b[7] + 6.176017503*a[2]*b[1] + 12.35203501*a[2]*b[2] + 18.52805251*a[2]*b[3] + 24.70407001*a[2]*b[4] + 30.88008752*a[2]*b[5] + 37.05610502*a[2]*b[6] + 43.23212252*a[2]*b[7] + 6.176017503*a[3]*b[1] + 12.35203501*a[3]*b[2] + 18.52805251*a[3]*b[3] + 24.70407001*a[3]*b[4] + 30.88008752*a[3]*b[5] + 37.05610502*a[3]*b[6] + 43.23212252*a[3]*b[7] + 6.176017503*a[4]*b[1] + 12.35203501*a[4]*b[2] + 18.52805251*a[4]*b[3] + 24.70407001*a[4]*b[4] + 30.88008752*a[4]*b[5] + 37.05610502*a[4]*b[6] + 43.23212252*a[4]*b[7] + 6.176017503*a[5]*b[1] + 12.35203501*a[5]*b[2] + 18.52805251*a[5]*b[3] + 24.70407001*a[5]*b[4] + 30.88008752*a[5]*b[5] + 37.05610502*a[5]*b[6] + 43.23212252*a[5]*b[7] + 6.176017503*a[6]*b[1] + 12.35203501*a[6]*b[2] + 18.52805251*a[6]*b[3] + 24.70407001*a[6]*b[4] + 30.88008752*a[6]*b[5] + 37.05610502*a[6]*b[6] + 43.23212252*a[6]*b[7] + 6.176017503*a[7]*b[1] + 12.35203501*a[7]*b[2] + 18.52805251*a[7]*b[3] + 24.70407001*a[7]*b[4] + 30.88008752*a[7]*b[5] + 37.05610502*a[7]*b[6] + 43.23212252*a[7]*b[7] + 6.176017503*a[8]*b[1] + 12.35203501*a[8]*b[2] + 18.52805251*a[8]*b[3] + 24.70407001*a[8]*b[4] + 30.88008752*a[8]*b[5] + 37.05610502*a[8]*b[6] + 43.23212252*a[8]*b[7] + 6.176017503*a[9]*b[1] + 12.35203501*a[9]*b[2] + 18.52805251*a[9]*b[3] + 24.70407001*a[9]*b[4] + 30.88008752*a[9]*b[5] + 37.05610502*a[9]*b[6] + 43.23212252*a[9]*b[7] + 6.176017503*a[0]*b[1] = 0:
eq[23] := 6.358226454*b[3] + 6.176017503*a[1]*b[1] + 12.35203501*a[0]*b[2] + 126.2164778*a[3] + 0.5*d[1] = 0:
eq[24] := 2.5*d[5] + 3.0*d[6] + 3.5*d[7] + 1.5*d[3] + 2.0*d[4] + 0.5*d[1] + d[2] + 222.5379259*b[7] + 63.58226454*b[5] + 127.1645291*b[6] + 6.358226454*b[3] + 25.43290582*b[4] + 10602.18414*a[9] + 2524.329557*a[6] + 4417.576724*a[7] + 7068.122760*a[8] + 126.2164778*a[3] + 504.8659114*a[4] + 1262.164778*a[5] + 12.35203501*a[0]*b[2] + 37.05610502*a[0]*b[3] + 74.11221004*a[0]*b[4] + 123.5203501*a[0]*b[5] + 185.2805251*a[0]*b[6] + 259.3927351*a[0]*b[7] + 6.176017503*a[1]*b[1] + 24.70407002*a[1]*b[2] + 55.58415753*a[1]*b[3] + 98.81628005*a[1]*b[4] + 154.4004376*a[1]*b[5] + 222.3366301*a[1]*b[6] + 302.6248576*a[1]*b[7] + 12.35203501*a[2]*b[1] + 37.05610502*a[2]*b[2] + 74.11221004*a[2]*b[3] + 123.5203501*a[2]*b[4] + 185.2805251*a[2]*b[5] + 259.3927351*a[2]*b[6] + 345.8569801*a[2]*b[7] + 18.52805251*a[3]*b[1] + 49.40814003*a[3]*b[2] + 92.64026255*a[3]*b[3] + 148.2244201*a[3]*b[4] + 216.1606126*a[3]*b[5] + 296.4488402*a[3]*b[6] + 389.0891027*a[3]*b[7] + 24.70407001*a[4]*b[1] + 61.76017503*a[4]*b[2] + 111.1683151*a[4]*b[3] + 172.9284901*a[4]*b[4] + 247.0407002*a[4]*b[5] + 333.5049452*a[4]*b[6] + 432.3212252*a[4]*b[7] + 30.88008752*a[5]*b[1] + 74.11221004*a[5]*b[2] + 129.6963676*a[5]*b[3] + 197.6325601*a[5]*b[4] + 277.9207877*a[5]*b[5] + 370.5610502*a[5]*b[6] + 475.5533477*a[5]*b[7] + 37.05610502*a[6]*b[1] + 86.46424505*a[6]*b[2] + 148.2244201*a[6]*b[3] + 222.3366301*a[6]*b[4] + 308.8008752*a[6]*b[5] + 407.6171552*a[6]*b[6] + 518.7854702*a[6]*b[7] + 43.23212252*a[7]*b[1] + 98.81628005*a[7]*b[2] + 166.7524726*a[7]*b[3] + 247.0407001*a[7]*b[4] + 339.6809627*a[7]*b[5] + 444.6732602*a[7]*b[6] + 562.0175927*a[7]*b[7] + 49.40814002*a[8]*b[1] + 111.1683151*a[8]*b[2] + 185.2805251*a[8]*b[3] + 271.7447701*a[8]*b[4] + 370.5610502*a[8]*b[5] + 481.7293652*a[8]*b[6] + 605.2497153*a[8]*b[7] + 55.58415753*a[9]*b[1] + 123.5203501*a[9]*b[2] + 203.8085776*a[9]*b[3] + 296.4488401*a[9]*b[4] + 401.4411377*a[9]*b[5] + 518.7854703*a[9]*b[6] + 648.4818378*a[9]*b[7] = 0:
eq[25] := 25.43290582*b[4] + 12.35203501*a[2]*b[1] + 24.70407002*a[1]*b[2] + 37.05610502*a[0]*b[3] + 504.8659114*a[4] + d[2] = 0:
eq[26] := 10.0*d[5] + 15.0*d[6] + 21.0*d[7] + 3.0*d[3] + 6.0*d[4] + d[2] + 890.1517036*b[7] + 127.1645291*b[5] + 381.4935873*b[6] + 25.43290582*b[4] + 63613.10484*a[9] + 7572.988671*a[6] + 17670.30690*a[7] + 35340.61380*a[8] + 504.8659114*a[4] + 2524.329556*a[5] + 37.05610502*a[0]*b[3] + 148.2244201*a[0]*b[4] + 370.5610502*a[0]*b[5] + 741.1221004*a[0]*b[6] + 1296.963676*a[0]*b[7] + 24.70407002*a[1]*b[2] + 111.1683151*a[1]*b[3] + 296.4488402*a[1]*b[4] + 617.6017504*a[1]*b[5] + 1111.683151*a[1]*b[6] + 1815.749146*a[1]*b[7] + 12.35203501*a[2]*b[1] + 74.11221005*a[2]*b[2] + 222.3366301*a[2]*b[3] + 494.0814003*a[2]*b[4] + 926.4026256*a[2]*b[5] + 1556.356411*a[2]*b[6] + 2420.998862*a[2]*b[7] + 37.05610502*a[3]*b[1] + 148.2244201*a[3]*b[2] + 370.5610503*a[3]*b[3] + 741.1221006*a[3]*b[4] + 1296.963676*a[3]*b[5] + 2075.141881*a[3]*b[6] + 3112.712822*a[3]*b[7] + 74.11221004*a[4]*b[1] + 247.0407002*a[4]*b[2] + 555.8415753*a[4]*b[3] + 1037.570941*a[4]*b[4] + 1729.284901*a[4]*b[5] + 2668.039561*a[4]*b[6] + 3890.891028*a[4]*b[7] + 123.5203501*a[5]*b[1] + 370.5610502*a[5]*b[2] + 778.1782055*a[5]*b[3] + 1383.427921*a[5]*b[4] + 2223.366301*a[5]*b[5] + 3335.049452*a[5]*b[6] + 4755.533478*a[5]*b[7] + 185.2805251*a[6]*b[1] + 518.7854703*a[6]*b[2] + 1037.570941*a[6]*b[3] + 1778.693041*a[6]*b[4] + 2779.207876*a[6]*b[5] + 4076.171553*a[6]*b[6] + 5706.640175*a[6]*b[7] + 259.3927351*a[7]*b[1] + 691.7139604*a[7]*b[2] + 1334.019781*a[7]*b[3] + 2223.366302*a[7]*b[4] + 3396.809627*a[7]*b[5] + 4891.405863*a[7]*b[6] + 6744.211115*a[7]*b[7] + 345.8569802*a[8]*b[1] + 889.3465205*a[8]*b[2] + 1667.524727*a[8]*b[3] + 2717.447702*a[8]*b[4] + 4076.171553*a[8]*b[5] + 5780.752383*a[8]*b[6] + 7868.246300*a[8]*b[7] + 444.6732602*a[9]*b[1] + 1111.683151*a[9]*b[2] + 2038.085777*a[9]*b[3] + 3260.937242*a[9]*b[4] + 4817.293653*a[9]*b[5] + 6744.211114*a[9]*b[6] + 9078.745732*a[9]*b[7] = 0:

 

solve([seq(eq[i], i = 1 .. 26)],{seq(a[i], i = 0 .. 9),seq(b[i], i = 0 .. 7),seq(d[i], i = 0 .. 7)});

 

Thanks a lot.
 

Suppose I have a list of 10 thousand expressions containing the symbol x. I would like to integrate all of them in the range x=0..1 and store the result in a new list or array of 10 thousand elements. I run Maple on a server with 32 CPUs and would like to parallelize the computation. Could you give some code samples showing how this can be done? Since the starting expressions vary greatly in complexity, some kind of dynamics load balancing (rather than dividing the calculation "equally") would be also very useful. Thanks for any help!

Please, what is the maple code for solving the following initial value problems?

The function n->ceil(sqrt(4*n))-floor(sqrt(2*n))-1 counts the number of squares strictly between 2n and 4n.

Maple 2016 gives the same output as what I get when I create a plot here: plot(ceil(sqrt(4*n))-floor(sqrt(2*n))-1,n=10..100)

Note, however, that Maple does not plot at least the point of interest (72.4), which is nevertheless an element of the graph:

[10, 2], [11, 2], [12, 2], [13, 2], [14, 2], [15, 2], [16, 2], [17, 3], [18, 2], [19, 2], [20, 2], [21, 3], [22, 3], [23, 3], [24, 3], [25, 2], [26, 3], [27, 3], [28, 3], [29, 3], [30, 3], [31, 4], [32, 3], [33, 3], [34, 3], [35, 3], [36, 3], [37, 4], [38, 4], [39, 4], [40, 4], [41, 3], [42, 3], [43, 4], [44, 4], [45, 4], [46, 4], [47, 4], [48, 4], [49, 4], [50, 4], [51, 4], [52, 4], [53, 4], [54, 4], [55, 4], [56, 4], [57, 5], [58, 5], [59, 5], [60, 5], [61, 4], [62, 4], [63, 4], [64, 4], [65, 5], [66, 5], [67, 5], [68, 5], [69, 5], [70, 5], [71, 5], [72, 4], [73, 5], [74, 5], [75, 5], [76, 5], [77, 5], [78, 5], [79, 5], [80, 5], [81, 5], [82, 6], [83, 6], [84, 6], [85, 5], [86, 5], [87, 5], [88, 5], [89, 5], [90, 5], [91, 6], [92, 6], [93, 6], [94, 6], [95, 6], [96, 6], [97, 6], [98, 5], [99, 5], [100, 5]

What's going wrong here?
Regards
Prof.G

Have you ever wanted to create practice problems and quizzes that use buttons and other features to support a student making their way to an answer, such as the following?

Let’s take a look at how you can use Maple 2022 to create documents like these that can be deployed in Maple Learn. I know I’ve always wanted to learn, so let’s learn together. All examples have a document that you can use to follow along, found here, in Maple Cloud.  

The most important command you’ll want to take a look at is ShareCanvas. This command generates a Maple Learn document. Make sure to remember that command, instead of ShowCanvas, so that the end result gives you a link to a document instead of showing the results in Maple. You’ll also want to make sure you load the DocumentTools:-Canvas subpackage using with(DocumentTools:- Canvas).

If you take a look at our first example, below, the code may seem intimidating. However, let’s break it down, I promise it makes sense!

with(DocumentTools:-Canvas);
cv := NewCanvas([Text("Volume of Revolution", fontsize = 24), "This solid of revolution is created by rotating", f(x) = cos(x) + 1, Text("about the y=0 axis on the interval %1", 0 <= x and x <= 4*Pi), Plot3D("Student:-Calculus1:-VolumeOfRevolution(cos(x) + 1, x = 0 .. 4*Pi, output = plot, caption=``)")]);
ShareCanvas(cv);

The key command is Plot3D. This plots the desired graph and places it into a Maple Learn document. The code around it places text and a math group containing the equation being graphed. 


Let’s take a look at IntPractice now. The next example allows a student to practice evaluating an integral.

with(Grading):
IntPractice(Int(x*sin(x), x, 'output'='link'));

 This command allows you to enter an integral and the variable of integration, and then evaluates each step a student enters on their way to finding a result. The feedback given on every line is incredibly useful. Not only will it tell you if your steps are right, but will let you know if your last line is correct, i.e if the answer is correct.

Finally, let’s talk about SolvePractice.

with(Grading):
SolvePractice(2*x + 3 = 6*x - 9, 'output' = 'link');

This command takes an equation, and evaluates it for the specified variable. Like the IntPractice command, this command will check your steps and provide feedback. The image below shows how this command looks in Maple 2022.

These commands are the stepping stones for creating practice questions in Maple Learn. We can do so much more in Maple 2022 scripting than I realized, so let’s continue to learn together!

Some other examples of scripted documents in the Maple Learn Document Gallery are our steps documents, this document on the Four Color Visualization Theorem, and a color by numbers. As you can see, there’s a lot that can be done with Maple Scripting.

 Let us know in the comments if you’d like to see more on Maple 2022 scripting and Maple Learn.

hello 
i want to reflect a plot i have j:= plot(y(x),x=0..35) ,y(x) icludes heavside functions around  x=17.5 , for some reason maple using reflect function keeps returning the reflected function in the output and not just the plot. i would like to get rid of it .

reflect(j,[[17.5,0],[17.5,15]])
output : the reflected function of y(x)
the reflected graph. 

thanks for the help 

First 311 312 313 314 315 316 317 Last Page 313 of 2219