Maple 2023 Questions and Posts

These are Posts and Questions associated with the product, Maple 2023

For instance, given nine integer x1, x2, …, x9 satisfying x1, x2, …, x9 ≥ -5 and x13x23+…+x93=0, the goal is to maximize x1 + x2 + … + x9. However, according to Optimization/Options,  is not accepted by the Optimization:-Maximize command. A probable method is applying floor into the optimization variables; unfortunately, I can only get: Error, (in Optimization:-NLPSolve) no improved point could be found

(*restart;*)
vars := [x || (1 .. 9)]:
Optimization:-Maximize(`?()`(`+`, floor~(expr)), [add(floor~(expr) ^~ 3) = 0, expr[] >=~ -5], initialpoint = (unapply~(expr) =~ rand(-5 .. 10))()); # Alternatives to exhaustive search?
Error, (in Optimization:-NLPSolve) no improved point could be found

Is there any workaround to solve this problem? 

Hafiz_basin_of_attraction_.mw

[moderator: see also this earlier Question]

The code below runs as expected up through the 4th line. At that point ans_all should contain all the multipule ansers to the equation being looked at. I want to look at just the first solution and I would expect the way to do this would be ans_all[1]. However the command ans_all[999999999] is valid, which indicates to me that that's not how you do that. So.... how do I get just the first answer?

equ := sqrt(1 + (-4 + 4*sqrt(2))*x + (16 - 12*sqrt(2))*x^2 + (-24 + 16*sqrt(2))*x^3 + (15 - 8*sqrt(2))*x^4)/(1 + (-4 + 4*sqrt(2))*x + (22 - 12*sqrt(2))*x^2 + (-36 + 28*sqrt(2))*x^3 + (33 - 20*sqrt(2))*x^4):
anit_dev_equ := int(equ,x):
ans_root := eval(anit_dev_equ, [x = 1]) - eval(anit_dev_equ, [x = 0]):
ans_all := allvalues(ans_root):
ans_all[999999999]

How does a user retain existing inline output (for example, computational output or inline plots) when re-executing an execution group in recent versions of Maple?  The "Replace existing output when re-executing groups" option is not available in Maple 2023 or in Maple 2020.

For example, I want to execute the same execution group 2 times to generate 2 different inline plots as the output. I want to retain the first inline plot when I generate the second inline plot.  However, the default Maple 2023 behavior is to overwrite the first inline plot with the second inline plot.

Several Maple versions ago (for example, Maple 18), there was the Tools > Option > Display > "Replace existing output when re-executing groups" option. When that option is checked, the second plot overwrites the first plot. In contrast, when that option is unchecked, the second plot appears after the retained first plot.

Where is the "Replace existing output when re-executing groups" option in recent Maple versions? Or do recent versions, like Maple 2023, use a different method to retain existing output when re-executing an execution group?

I think that the following worksheet is self-explaining: 
 

restartNULL

interface(version)

`Standard Worksheet Interface, Maple 2023.1, Windows 10, July 7 2023 Build ID 1723669`

(1)

evalf(LinearAlgebra:-MatrixFunction(`<|>`(`<,>`(1, 0, 0), `<,>`(1, 1, I), `<,>`(3, 0, 2)), 'x'/(exp('x')-1), 'x'))

Matrix(%id = 36893489913840207380)

(2)

(* Yet in many cases, the input may be inexact, for we need to speed up computations and decrease memory usage. *)

m := Matrix([[1, 1, 3], [0, 1, 0], [0, I, 2]], datatype = complex(sfloat)):
Digits := 10:
do
    print(CodeTools:-Usage(LinearAlgebra:-MatrixFunction(m, 'x'/(exp('x') - 1), 'x'), quiet), Digits++)
until Digits > 20:

Matrix(3, 3, {(1, 1) = .5819767069, (1, 2) = -.3333333333+.1931757357*I, (1, 3) = -.8068242642, (2, 1) = 0., (2, 2) = .5819767069, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352855}), 10

 

Matrix(3, 3, {(1, 1) = .5819767069, (1, 2) = -.33333333332+.19317573586*I, (1, 3) = -.8068242642, (2, 1) = 0., (2, 2) = .5819767069, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352855}), 11

 

Matrix(3, 3, {(1, 1) = .5819767069, (1, 2) = -.333333333321+.193175735853*I, (1, 3) = -.8068242642, (2, 1) = 0., (2, 2) = .5819767069, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352855}), 12

 

Matrix(3, 3, {(1, 1) = .5819767069, (1, 2) = -.3333333333209+.1931757358526*I, (1, 3) = -.8068242642, (2, 1) = 0., (2, 2) = .5819767069, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352855}), 13

 

Matrix(3, 3, {(1, 1) = .5819767069, (1, 2) = -.33333333332087+.19317573585263*I, (1, 3) = -.8068242642, (2, 1) = 0., (2, 2) = .5819767069, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352855}), 14

 

Matrix(3, 3, {(1, 1) = .5819767069, (1, 2) = -.333333333320870+.193175735852624*I, (1, 3) = -.8068242642, (2, 1) = 0., (2, 2) = .5819767069, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352855}), 15

 

Matrix(3, 3, {(1, 1) = .5819767068693265, (1, 2) = .9999999999999999-3.806824264*I, (1, 3) = -.8068242641099854, (2, 1) = 0., (2, 2) = .5819767068693265, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352854993314}), 16

 

Matrix(3, 3, {(1, 1) = .58197670686932644, (1, 2) = .99999999999999997-3.806824264*I, (1, 3) = -.80682426410998598, (2, 1) = 0., (2, 2) = .58197670686932644, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .31303528549933112}), 17

 

Matrix(3, 3, {(1, 1) = .581976706869326423, (1, 2) = -.999999999999999997+2.19317573589001464*I, (1, 3) = -.806824264109985348, (2, 1) = 0., (2, 2) = .581976706869326423, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .313035285499331308}), 18

 

Matrix(3, 3, {(1, 1) = .5819767068693264245, (1, 2) = -.2500000000000000000-0.5682426411e-1*I, (1, 3) = -.8068242641099853627, (2, 1) = 0., (2, 2) = .5819767068693264245, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414214*I, (3, 3) = .3130352854993313037}), 19

 

Matrix(%id = 36893489913905117652), 20

(3)

# Is `linalg:-matfunc` better than `LinearAlgebra:-MatrixFunction`?!
Digits := 10:
linalg:-matfunc(m, 'x'/(exp('x') - 1), 'x');

Matrix(3, 3, {(1, 1) = .5819767070, (1, 2) = -.3386968877+.2092663986*I, (1, 3) = -.8068242645, (2, 1) = 0., (2, 2) = .5819767070, (2, 3) = 0., (3, 1) = 0., (3, 2) = -.2689414215*I, (3, 3) = .3130352855})

(4)

(*
Even for a 3×3 matrix, the number of digits has to be set to 20.
So … how can you certify that the following output is validated?
*)
_seed := 1234:

LinearAlgebra:-MatrixFunction(LinearAlgebra:-RandomMatrix(50, density = .5, generator = -2*Pi .. 2*Pi, datatype = complex[8]), 'x'/(exp('x')-1), 'x')

Warning, the use of _seed is deprecated.  Please consider using one of the alternatives listed on the _seed help page.

 

Matrix(%id = 36893490216779135924)

(5)


 

Download funm.mws

How do you confirm the validity of the last output? 

> op(3, eval(LinearAlgebra:-MatrixFunction));
 = 
  Copyright (c) 2002 Waterloo Maple Inc. All rights reserved.

And does this mean that LinearAlgebra['MatrixFunction'] is so out-dated that the return value is less effective in certain cases?

Wolfram's marketing literature states that a compiled function may generate the dates for the years 1 through 5.7 million in a couple of seconds rather than in minutes (comparing to the "uncompiled implementation").
The given function in this link can be translated into Maple language as follows: 

(*
  Note that this is only a mathematical program that outputs some data,
   hence 'Easter(-2, 1)' will never return real Gregorian Easter dates!
*)
Easter:=proc(BEGIN::integer[4],END::integer[4],$)::Array(BEGIN..END,[integer[1..12],integer[1..31]]);# the parent function
	description "https://www.wolfram.com/language/12/code-compilation/compute-the-date-of-easter.html";
	local computus::procedure[[integer[1 .. 12], integer[1 .. 31]]](integer):=proc(Year::integer,` $`)::[integer[1..12],integer[1..31]];# the child function
		options threadsafe;
		local a::nonnegint,b::integer,c::nonnegint,d::integer,e::nonnegint,f::integer,g::nonnegint,h::nonnegint,i::nonnegint,j::nonnegint,k::nonnegint,Month::integer[1..12],Day::integer[1..31];
		(* For compatibility, when `Year` is nonpositive, the command `iquo` must be replaced with slower `floor`. *)
		if Year<=0 then
			a,b,c:=Year mod 19,floor(Year/100),Year mod 100;
			d,e,f:=floor(b/4),b mod 4,floor((8*b+13)/25);
			g,h,i:=19*a+b-d-f+15 mod 30,floor(c/4),c mod 4;
			j:=floor((a+11*g)/319);k:=2*e+2*h-i-g+j+32 mod 7;
			Month:=floor((g-j+k+90)/25);Day:=g-j+k+Month+19 mod 32
		else
			a,b,c:=irem(Year,19),iquo(Year,100),irem(Year,100):
			d,e,f:=iquo(b,4),irem(b,4),iquo(8*b+13,25);
			g,h,i:=irem(19*a+b-d-f+15,30),iquo(c,4),irem(c,4);
			j:=iquo(a+11*g,319);k:=irem(2*e+2*h-i-g+j+32,7);
			Month:=iquo(g-j+k+90,25);Day:=irem(g-j+k+Month+19,32)
		fi;
		[Month,Day]
	end;
	Array(BEGIN..END,computus)
end:

However, as "no nested procedures can be translated" to optimized native machine code (cf. ), executing Easter(1, 5700000) has to take at least two minutes

Is there some workaround that can provide improved performance for such a numerical procedure that contains a nested procedure? In other words, is it possible to produce the `result` (without modifying the algorithm) in two seconds in modern Maple as that Wolfram marketing literature claims?

What am I doing wrong, why cant I get the result correct?

Hello

I have programs below for the cases n=3 and n=4. If n is increasing by 1, then there is one loop more. As you can see, that additional loop has always the structure:

x[i+1] from ceil(((n-2)*24-d[i])/(n-i)) to x[i]

whereas d[i] is the sum of the values of x before.

Now I want to write "nequaln":=proc(k), which goes through all the values for n from 3 to k and produces a list [a_3,a_4,a_5,...,a_n].

I guess that I need to program a kind of dynamical loop, but I failed completely. May someone help me? That would be very kind.

 

nequal3:=proc()
    local u,v,a_3;
    a_3:=0;
    for u from ceil((3-2)*24/(3-0)) to (3-2)*24-3+1 do
        for v from ceil(((3-2)*24-u)/(3-1)) to u do
            if (3-2)*24-u-v>=1 then
                a_3:=a_3+1;
            end if;
        end do;
    end do;
    print(a_3);
end proc:

 

nequal4:=proc()
    local u,v,w,a_4;
    a_4:=0;
    for u from ceil((4-2)*24/(4-0)) to (4-2)*24-4+1 do
        for v from ceil(((4-2)*24-u)/(4-1)) to u do
            for w from ceil(((4-2)*24-u-v)/(4-2)) to v do
                if (4-2)*24-u-v-w>=1 then
                    a_4:=a_4+1;
                end if;
            end do;
        end do;
    end do;
    print(a_4);
end proc:

The old question "Longest distance in a graph via Maple code" offers some general methods to find longest paths in a given graph, while for directed acyclic graphs, the longest paths can be found much more directly via built-in functions. However, it apprears that even for small dags, Maple cannot solve this in an acceptable time. In the following example, I'd like to count the number of nodes that on longest paths for certain source and target vertexes.
 

restart;

_seed := 1234

Warning, the use of _seed is deprecated.  Please consider using one of the alternatives listed on the _seed help page.

 

G := GraphTheory:-RandomGraphs:-RandomNetwork(200, .2, 'acyclic', 'weights' = 0. .. 2)

G__0 := applyop(`-`, -1, G)``

GRAPHLN(directed, weighted, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200], Array(1..200, {(1) = {2, 3, 4}, (2) = {5}, (3) = {4, 5}, (4) = {5}, (5) = {6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18}, (6) = {11, 12, 13, 14, 15, 17, 18, 19, 21}, (7) = {9, 10, 11, 16, 17, 20, 22}, (8) = {12, 14, 16, 17, 19, 20, 21, 22, 23}, (9) = {11, 14, 21, 23}, (10) = {11, 13, 18, 19, 20, 21, 23}, (11) = {14, 15, 16, 17, 18, 21, 23}, (12) = {13, 15, 18, 19, 20, 22}, (13) = {14, 15, 16, 17, 21}, (14) = {19, 20, 22}, (15) = {19, 20, 22, 23}, (16) = {17, 18, 21}, (17) = {19, 20, 23}, (18) = {19, 20, 21}, (19) = {20, 24, 25}, (20) = {22, 23, 25}, (21) = {23, 24, 25}, (22) = {23, 24, 25}, (23) = {24, 25}, (24) = {26, 27, 29}, (25) = {27, 28, 29}, (26) = {28, 29, 30}, (27) = {28, 29, 31, 32, 33}, (28) = {32, 33}, (29) = {32, 33}, (30) = {34, 35, 38, 39}, (31) = {32, 37, 38, 39}, (32) = {33, 36, 37, 38}, (33) = {35, 36, 39}, (34) = {36, 38, 39}, (35) = {37, 39}, (36) = {37, 39}, (37) = {39, 40}, (38) = {39, 40}, (39) = {40}, (40) = {41, 42}, (41) = {43, 44, 47, 48, 49}, (42) = {44, 45, 46, 47, 48, 49}, (43) = {47, 49, 50, 55, 56, 57}, (44) = {45, 48, 50, 51, 52, 53, 54, 56}, (45) = {46, 47, 49, 50, 52, 56}, (46) = {47, 48, 49, 50, 51, 52, 53, 56, 57}, (47) = {49, 50, 51, 52, 54, 56, 57}, (48) = {49, 51, 52, 53, 54, 55, 56, 57}, (49) = {50, 52, 53, 54, 57}, (50) = {51, 57}, (51) = {53, 54, 57}, (52) = {53, 55, 57}, (53) = {54, 56}, (54) = {56, 58}, (55) = {58}, (56) = {58}, (57) = {58}, (58) = {59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75}, (59) = {60, 61, 66, 68, 70, 71, 74, 75, 76, 77}, (60) = {61, 63, 67, 68, 70, 72, 73, 77}, (61) = {62, 66, 69, 70, 71, 72, 73, 75, 76, 77}, (62) = {65, 68, 75, 76, 77}, (63) = {65, 66, 69, 70, 72, 73, 76, 77}, (64) = {65, 67, 68, 69, 70, 71, 73, 77}, (65) = {66, 70, 72, 73, 74, 76}, (66) = {68, 70, 71, 72, 73, 74, 75, 76, 77}, (67) = {69, 70, 71, 74, 76}, (68) = {73, 74}, (69) = {71, 76, 77}, (70) = {71, 73, 77}, (71) = {72, 76, 77}, (72) = {75}, (73) = {75, 76}, (74) = {76}, (75) = {76}, (76) = {77, 78, 79, 80, 81, 82, 83, 85, 86}, (77) = {79, 80, 82, 84, 85}, (78) = {79, 83, 85, 87}, (79) = {81, 82, 83, 85, 86, 87}, (80) = {83, 86}, (81) = {83, 84, 87}, (82) = {87}, (83) = {85, 86, 87}, (84) = {85, 87}, (85) = {87}, (86) = {87}, (87) = {88, 89}, (88) = {90, 91, 92, 93, 94}, (89) = {90, 91, 93, 94, 95}, (90) = {96, 97, 99, 101, 103, 104, 107, 108, 109, 110, 112, 115, 117, 118, 120}, (91) = {92, 94, 96, 97, 98, 100, 101, 102, 105, 106, 107, 110, 113, 116, 117, 118, 120}, (92) = {95, 97, 98, 99, 101, 103, 106, 107, 108, 111, 112, 113, 115, 117, 119, 120}, (93) = {95, 96, 98, 100, 104, 106, 109, 111, 112, 113, 116, 118, 119, 120}, (94) = {95, 99, 100, 102, 103, 104, 106, 108, 109, 110, 111, 112, 113, 114, 115, 117, 118, 119, 120}, (95) = {97, 98, 99, 100, 102, 103, 104, 105, 107, 108, 109, 111, 112, 113, 114, 115, 116, 117, 118, 120}, (96) = {98, 100, 102, 103, 104, 106, 107, 110, 111, 114, 119, 120, 121}, (97) = {99, 100, 102, 104, 106, 107, 108, 109, 111, 114, 118, 119}, (98) = {102, 103, 107, 110, 111, 112, 113, 114, 116, 117, 119, 120, 121}, (99) = {101, 102, 104, 106, 107, 112, 117, 120}, (100) = {101, 104, 105, 106, 109, 110, 116, 117, 119, 120, 121}, (101) = {102, 105, 109, 110, 111, 112, 113, 114, 115, 117, 118, 119, 120}, (102) = {103, 106, 107, 108, 110, 112, 113, 114, 117, 118, 119}, (103) = {104, 105, 107, 108, 109, 110, 111, 113, 115, 116, 119, 120, 121}, (104) = {105, 106, 109, 110, 114, 115, 116, 118, 119}, (105) = {106, 108, 109, 110, 113, 114, 116, 117}, (106) = {107, 108, 109, 112, 114, 117, 118, 119, 121}, (107) = {110, 114, 116, 119, 120}, (108) = {111, 112, 113, 114, 118, 119, 120, 121}, (109) = {113, 116, 117, 118, 121}, (110) = {111, 113, 117, 119, 120, 121}, (111) = {112, 113, 115, 118, 120}, (112) = {113, 114, 116, 117, 118, 119, 120}, (113) = {116, 117, 119, 121}, (114) = {115, 116, 117, 121}, (115) = {116, 120}, (116) = {119, 121}, (117) = {118, 119, 121}, (118) = {121}, (119) = {121}, (120) = {121}, (121) = {122, 123, 124, 125, 126}, (122) = {123, 124, 125, 126, 127}, (123) = {126}, (124) = {126, 127}, (125) = {127}, (126) = {127}, (127) = {128, 129}, (128) = {130}, (129) = {130}, (130) = {131, 132}, (131) = {132, 133, 135}, (132) = {134, 135}, (133) = {134, 136, 137, 138, 140, 141, 142}, (134) = {135, 136, 139, 140, 141}, (135) = {136, 137, 139, 140, 141, 142}, (136) = {145, 146, 147}, (137) = {139, 141, 143, 145, 147, 148}, (138) = {139, 140, 143, 144, 145, 148}, (139) = {141, 143, 145}, (140) = {143, 145, 146, 147, 148}, (141) = {142, 144, 145, 146, 147}, (142) = {143, 144, 146, 148}, (143) = {145, 146, 147, 148}, (144) = {146, 149}, (145) = {147}, (146) = {149}, (147) = {149}, (148) = {149}, (149) = {150, 151, 152, 153, 154, 155, 156, 157, 158}, (150) = {152, 153, 155, 157, 158}, (151) = {152, 153, 159}, (152) = {154, 158}, (153) = {154, 155, 156}, (154) = {156, 158, 159}, (155) = {158}, (156) = {157, 158, 159}, (157) = {158}, (158) = {159}, (159) = {160, 161, 162, 163}, (160) = {161, 163, 166, 167}, (161) = {165, 166, 167}, (162) = {163, 165}, (163) = {164, 166, 167}, (164) = {166}, (165) = {166, 168, 169}, (166) = {169}, (167) = {168}, (168) = {169, 170, 171, 172, 173, 174, 177, 178, 179, 180, 182}, (169) = {170, 171, 172, 173, 174, 175, 176, 177, 178, 180, 181, 182}, (170) = {172, 173, 174, 175, 176, 180, 182, 183, 185}, (171) = {172, 174, 176, 177, 181, 182, 185}, (172) = {175, 176, 177, 183, 185}, (173) = {175, 176, 178, 183, 185}, (174) = {175, 180, 181, 183, 184, 185}, (175) = {181, 182, 183, 185}, (176) = {177, 178, 179, 182}, (177) = {178, 179, 184, 185}, (178) = {179, 180, 182, 183, 184}, (179) = {180, 182, 185}, (180) = {181, 182}, (181) = {184}, (182) = {185}, (183) = {187, 188, 190}, (184) = {187, 188, 189}, (185) = {186, 188, 190}, (186) = {187, 188, 190, 191, 193, 194, 196}, (187) = {188, 190, 192, 193, 194, 195}, (188) = {189, 190, 191, 192, 194}, (189) = {190, 191, 196}, (190) = {191, 192, 195, 196}, (191) = {193, 196, 199}, (192) = {194, 196, 198, 199}, (193) = {197, 199}, (194) = {195, 196, 197}, (195) = {196, 198, 199}, (196) = {198, 199}, (197) = {198}, (198) = {199, 200}, (199) = {200}, (200) = {}}), `GRAPHLN/table/1`, )

(1)

t, s := combinat:-randcomb(GraphTheory:-Vertices(G__0), 5^2), combinat:-randcomb(GraphTheory:-Vertices(G__0), integermul2exp(5, 2))

[12, 13, 22, 23, 41, 65, 70, 80, 88, 97, 105, 119, 124, 127, 129, 132, 135, 138, 146, 150, 165, 170, 189, 193, 199], [6, 13, 28, 29, 31, 41, 42, 49, 55, 85, 98, 104, 136, 141, 162, 166, 167, 168, 192, 199]

(2)

"DataFrame((`M__1`:=CodeTools:-Usage(Matrix(numelems(s),numelems(t),(i,j)->numelems((GraphTheory:-BellmanFordAlgorithm(`G__0`,s[i],t[j]))[1]),datatype=integer[2]))),'columns'=t,'rows'=s)"

memory used=7.99GiB, alloc change=0 bytes, cpu time=5.74m, real time=5.63m, gc time=22.55s

 

module DataFrame () description "two-dimensional rich data container"; local columns, rows, data, binder; option object(BaseDataObject); end module

(3)

"DataFrame((`M__2`:=CodeTools:-Usage(Matrix(numelems(s),numelems(t),proc(i::posint,j::posint,` $`)::nonnegint;  uses ListTools,GraphTheory; local ts::list(posint):=TopologicSort(`G__0`,'output'='permutation'),q::posint:=Search(t[j],ts),p::posint:=Search(s[i],ts); if  p>q then 0 elif q=p then 1 else numelems(BellmanFordAlgorithm(`G__0`,s[i],t[j])[1]) fi end,datatype=integer))),':-columns'=t,':-rows'=s)"

memory used=4.34GiB, alloc change=32.00MiB, cpu time=3.26m, real time=3.19m, gc time=14.34s

 

module DataFrame () description "two-dimensional rich data container"; local columns, rows, data, binder; option object(BaseDataObject); end module

(4)

EqualEntries(M__ || (1 .. 2))

true

(5)

 


 

Download longest_paths_in_a_DAG.mw

Unfortunately, I have to wait for almost four minutes in the above instance. Can this task be done in 0.4s?

Hi, I am using ArchLinux and used Maple's official installer to install it. Whenever I export my Maple files as PDF all my "-" symbols are converted to "K" for some reason. Has anyone else had this issue or have an idea on how to fix it?

Below is a screenshot of what I mean. "-" has been replaced with "K"

Hello

I have a list with n positive integer numbers and a positive integer k.

I would like to write a Malple programm, that calculates, in how many ways k can be written as a sum of numbers in the list.

Easy examles: let the list be [2,3,6,9].

k=9 can be written in 4 ways: 9=9, 9=6+3, 9=3+3+3, 9=3+2+2+2. The result therefore shoud be 4.

k=8 can be written in 3 ways: 8=6+2, 8=3+3+2, 8=2+2+2+2. The result therefore shoud be 3.

Thank you very much your help!

GraphTheory:-GraphEqual says that G1 and G2 are equal, but GraphTheory:-AllPairsDistance gives different results instead: 

restart;

with(GraphTheory)

M := `<|>`(`<,>`(0, 0, 0), `<,>`(1, 0, 0), `<,>`(1, 1, 0))

G__1 := Graph(convert(-M, Matrix, datatype = integer[8]))

G__2 := Graph(convert(-M, Matrix, datatype = integer))

GraphEqual(G__1, G__2)

true

(1)

AllPairsDistance(G__1)

AllPairsDistance(G__2)

Matrix(%id = 36893491227039185244)

 

Error, (in GraphTheory:-AllPairsDistanceExt) negative cycle detected

 

 

Download allpairs.mw

So, which one is incorrect? Any reasons?

I have a very simple procedure that I wrote to get information for an inequality using data from two lists, upon which I can create a pointplot . Now I know people will see what I have done and probably cringe, and believe me I do as well. I know it is not efficient and there is probably a numerous number of ways to do it better but my procedural skills for Maple are lacking. 

From my file you will see what I am attempting to do,nonetheless I will mention it here. I have two lists X,W. for each value in I want to fine the value in W that yields F(X,L)<G(X,L) where F(X,L) is a complicated integral that I have to evalute numerically, I have tried using unapply as outline in https://www.mapleprimes.com/questions/229070-How-Can-I-Speed-Up-This-Numerical-Integral it however only made my problem worse. For small lists it seems to be reasonable but for larger precision it is not the useful. I have looked through the ?do help page and some other resources but to no avail. From what I have seen though I believe I should be using the until command in do but I can't figure it out with having two lists. 

Any help,tips or tricks will be greatly appreciated.

NumericScale.mw

Here is a symmetric matrix with three real parameters (`k__1`, `k__2`, and `k__3`).

mm:=<0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
,0,0,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|0,0,1,0,0,0,0,0,0,0,0,0,0\
,k__3-1/2,0,k__3-1/2,0,0,0,0,0,0,0,0,-1/2,0,1-2*k__3,0,-1/\
2,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,\
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,\
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|0,0,0,0,0,1,0,\
k__3,0,-1/2,0,0,0,0,0,0,0,0,0,k__3,0,-2*k__3,0,0,0,0,0,0,0\
,0,-1/2,0,0,0,0,0|0,0,0,0,0,0,-2*k__3,0,k__3-1,0,-1/2,0,0,\
0,0,0,0,0,0,0,k__3,0,1-2*k__3,0,0,0,0,0,0,0,0,k__1,0,0,0,0\
|0,0,0,0,0,k__3,0,1-4*k__3,0,k__3-1,0,0,0,0,0,0,0,0,0,(1-k\
__2)/2,0,k__3-1/2,0,0,0,0,0,0,0,0,1-2*k__3,0,0,0,0,0|0,0,0\
,0,0,0,k__3-1,0,1-4*k__3,0,k__3,0,0,0,0,0,0,0,0,0,k__3-1/2\
,0,(1-k__2)/2,0,0,0,0,0,0,0,0,1-2*k__3,0,0,0,0|0,0,0,0,0,-\
1/2,0,k__3-1,0,-2*k__3,0,0,0,0,0,0,0,0,0,1-2*k__3,0,k__3,0\
,0,0,0,0,0,0,0,k__1,0,0,0,0,0|0,0,0,0,0,0,-1/2,0,k__3,0,1,\
0,0,0,0,0,0,0,0,0,-2*k__3,0,k__3,0,0,0,0,0,0,0,0,-1/2,0,0,\
0,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,\
0,0,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,-2*k__3,0,k__3,0\
,k__1,0,0,0,0,0,0,0,0,k__3-1,0,1-2*k__3,0,0,0,0,0,0,-1/2,0\
|0,0,k__3-1/2,0,0,0,0,0,0,0,0,0,0,k__2,0,-k__1+5*k__3-1/2,\
0,0,0,0,0,0,0,0,k__3-1/2,0,-k__1+5*k__3-1/2,0,1-2*k__3,0,0\
,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,k__3,0,1-2*k__3,0,k__3,\
0,0,0,0,0,0,0,0,k__3-1/2,0,k__3-1/2,0,0,0,0,0,0,-2*k__3,0|\
0,0,k__3-1/2,0,0,0,0,0,0,0,0,0,0,-k__1+5*k__3-1/2,0,k__2,0\
,0,0,0,0,0,0,0,1-2*k__3,0,-k__1+5*k__3-1/2,0,k__3-1/2,0,0,\
0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,k__1,0,k__3,0,-2*k__3,0,\
0,0,0,0,0,0,0,1-2*k__3,0,k__3-1,0,0,0,0,0,0,-1/2,0|0,0,0,0\
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
,0,0,0,0,0,0,0,0,0,0|0,0,0,0,0,k__3,0,(1-k__2)/2,0,1-2*k__\
3,0,0,0,0,0,0,0,0,0,1-4*k__3,0,k__3-1/2,0,0,0,0,0,0,0,0,k_\
_3-1,0,0,0,0,0|0,0,0,0,0,0,k__3,0,k__3-1/2,0,-2*k__3,0,0,0\
,0,0,0,0,0,0,1-2*k__3,0,k__3-1/2,0,0,0,0,0,0,0,0,k__3,0,0,\
0,0|0,0,0,0,0,-2*k__3,0,k__3-1/2,0,k__3,0,0,0,0,0,0,0,0,0,\
k__3-1/2,0,1-2*k__3,0,0,0,0,0,0,0,0,k__3,0,0,0,0,0|0,0,0,0\
,0,0,1-2*k__3,0,(1-k__2)/2,0,k__3,0,0,0,0,0,0,0,0,0,k__3-1\
/2,0,1-4*k__3,0,0,0,0,0,0,0,0,k__3-1,0,0,0,0|0,0,0,0,0,0,0\
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
|0,0,-1/2,0,0,0,0,0,0,0,0,0,0,k__3-1/2,0,1-2*k__3,0,0,0,0,\
0,0,0,0,1,0,k__3-1/2,0,-1/2,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,\
0,0,0,0,k__3-1,0,k__3-1/2,0,1-2*k__3,0,0,0,0,0,0,0,0,1-4*k\
__3,0,(1-k__2)/2,0,0,0,0,0,0,k__3,0|0,0,1-2*k__3,0,0,0,0,0\
,0,0,0,0,0,-k__1+5*k__3-1/2,0,-k__1+5*k__3-1/2,0,0,0,0,0,0\
,0,0,k__3-1/2,0,k__2,0,k__3-1/2,0,0,0,0,0,0,0|0,0,0,0,0,0,\
0,0,0,0,0,0,1-2*k__3,0,k__3-1/2,0,k__3-1,0,0,0,0,0,0,0,0,(\
1-k__2)/2,0,1-4*k__3,0,0,0,0,0,0,k__3,0|0,0,-1/2,0,0,0,0,0\
,0,0,0,0,0,1-2*k__3,0,k__3-1/2,0,0,0,0,0,0,0,0,-1/2,0,k__3\
-1/2,0,1,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|0,0,0,0,0,-1/2,0,1-2*\
k__3,0,k__1,0,0,0,0,0,0,0,0,0,k__3-1,0,k__3,0,0,0,0,0,0,0,\
0,-2*k__3,0,0,0,0,0|0,0,0,0,0,0,k__1,0,1-2*k__3,0,-1/2,0,0\
,0,0,0,0,0,0,0,k__3,0,k__3-1,0,0,0,0,0,0,0,0,-2*k__3,0,0,0\
,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
,0,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|0,0,0,0,0,0,0,0,0,0,0,0,-1/\
2,0,-2*k__3,0,-1/2,0,0,0,0,0,0,0,0,k__3,0,k__3,0,0,0,0,0,0\
,1,0|0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0>#assuming'real':
cc:={evalindets}(LinearAlgebra:-IsDefinite(mm,query='positive_semidefinite'),`and`,op):

As the title says, I hope to find some values satisfying andseq('cc') (so `mm` becomes positive semidefinite). Unfortunately, these don't work: 

# SMTLIB:-Satisfy(cc);
Optimization:-Maximize(0, cc, initialpoint = eval({k__ || (1 .. 3)} =~ 'rand(-2e1 .. 2e1)'()));
Error, (in Optimization:-NLPSolve) no feasible point found for the nonlinear constraints
timelimit(1e2, RealDomain:-solve(cc, [k__ || (1 .. 3)](*, 'maxsols' = 1*)));
Error, (in RegularChains:-SemiAlgebraicSetTools:-CylindricalAlgebraicDecompose) time expired

 Is there a way to do so as accurately (and precisely) as possible?

 

Maple introduced "Copy as LaTeX" a few versions ago and I have used this feature exensively when it suddenly stopped working.

After som experiments I found the root cause and easy (but irritating) workaround for OSX

Problem:

"Copy as LaTeX" suddenly stops working ("Copy as MathML" still works fine)

Cause:

This problem appears if in “Display Setting”-tab in settings dialogue the “Input display” is set to “Maple Notation

In that case all attempts on “Copy as LaTeX” will be a null-function and not move anything at all into the copy buffer.

The “Copy as MathML” is not affected by this in the same way.

I have confirmed this on OSX in Maple versions 2022, 2023, and 2024

Workaround:

Adjusting “Display Setting”-tab in settings dialogue so that the “Input display” is set to “2-D Math” and “Apply Globally” makes it work again.

A bit annoying as a prefer the maple notation input and I cannot have this setting if I want the copy to latex to work.

Note:

in OSX this can also be fixed by removing the Maple preferences file and letting Maple restore it.

~/Library/Preferences/Maple/2023/Maple Preferences

Edit: Added 2024 as affected version.

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