vv

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@nm 

The new ode is solved via the Bernoulli method (use infolevel). Forcing "separable" ==>

dsolve(diff(y(x), x) = 3*x^2*y(x)^2 , y(x), ['separable']);

    

 

@Adam Ledger 

Sorry but the term is a standard one. See https://en.wikipedia.org/wiki/Pathological_(mathematics)

@Adam Ledger 

f(x) = x^2*ln(x),  f(0) = 0

is a "pathological" function; it is of class C^1 but not C^2  (f'' is unbounded at 0 and actually f''(0+) = - infinity).

Note that for such functions, the significance of O(...)  in Maple is different from the Landau symbol
(in the sense that sub-polynomial terms may be included in O, see ?series).
Note also that the new  MultiSeries:-multiseries  uses the standard (Landau) significance for O.

  

Here are the results in Maple 2017.

 

S1:=series(x^2*ln(x), x, 1);

series(+O(x^2),x,2)

(1)

S2:=series(x^2*ln(x), x, 2);

series(+O(x^2),x,2)

(2)

S:=series(x^2*ln(x), x, 3);

series(ln(x)*x^2,x)

(3)

whattype(S); op(0,S);

series

 

x

(4)

SS:=MultiSeries:-series(x^2*ln(x), x, 5);

series(-ln(1/x)*x^2,x)

(5)

whattype(SS);  op(0,SS);

series

 

x

(6)

M:=MultiSeries:-multiseries(x^2*ln(x), x, 5);

SERIES(Scale, [-1/_var[1/ln(1/x)]], 0, algebraic, [2], infinity, integer, _var[x], -_var[x]^2/_var[1/ln(1/x)])

(7)

whattype(M); op(0,M);

function

 

SERIES

(8)

diff(x^2*ln(x), x);

2*x*ln(x)+x

(9)

diff(x^2*ln(x), x,x);

2*ln(x)+3

(10)

 

@rlopez 

It depends of course on how the residuals are computed in the inplicit approach.
But the space is finite dimensional and so all the norms are equivalent (for linear models).
The main problem is here the model which I think is not adequate; even y = ax+b is much better.

@rlopez

No need for implicit functions here because the fitting curve can be inversed x = (y - A*y^3)/B, or equivalently  x = a*y - b*y^3.

The problem is that this curve passes thru (0,0) which is far from the provided data, so the "model" seems to be unsuitable.

@rlopez 

 

I had the impression that Analytic is more robust than a command in the Student package.

It's a disappointment not being so; in the next example Analytic looses roots!

 

h:=sin(x) - 1/(x+1);

sin(x)-1/(x+1)

(1)

plot(h, x=0..50);

 

Student:-Calculus1:-Roots(h,x=0..50, numeric);

[.6507516780, 2.880986321, 6.418396937, 9.327799981, 12.63975157, 15.64785930, 18.89982878, 21.94755715, 25.17096082, 28.24012763, 31.44675114, 34.52936974, 37.72493787, 40.81678838, 44.00451897, 47.10309963]

(2)

nops(%);

16

(3)

RootFinding:-Analytic(h, x, 0-I/10 .. 50+I/10):

sort([%]);

[.650751677964220, 2.88098632105449, 12.6397515714604, 21.9475571476892, 25.1709608227370, 28.2401276349762, 31.4467511436534, 34.5293697434195, 37.7249378670212, 40.8167883764839, 44.0045189699563, 47.1030996250431]

(4)

nops(%)

12

(5)

 

# Strangely, increasing the imaginary part ==> OK.
##################################################

RootFinding:-Analytic(h, x, 0-I .. 50+I):

sort([%]);

[.650751677964220, 2.88098632105449, 6.41839693725700, 9.32779998112870, 12.6397515714604, 15.6478593040306, 18.8998287837776, 21.9475571476892, 25.1709608227370, 28.2401276349762, 31.4467511436534, 34.5293697434195, 37.7249378670212, 40.8167883764839, 44.0045189699563, 47.1030996250431]

(6)

nops(%)

16

(7)

 

 

 

 

 

@Rouben Rostamian  

But actually Maple is wrong:  sol[1] (the red one) is not a solution! ( dy/dx should be >=0).

Edit. The solution of the Cauchy problem y(0)=a is unique (x >= 0)  for a > 0.
For a=0  there are two solutions: y = 0 and y = x^3 / 9 (Maple finds only y=0).

@quo 

factrix ignores the second argument. The factor is computed by the procedure.

If you already know the factor, use this simple one:

 

facm:=proc(A::Matrix, q::algebraic)
  local AA,qq;
  subs([qq=q,AA=1/q*A], qq*AA)
end proc;

proc (A::Matrix, q::algebraic) local AA, qq; subs([qq = q, AA = A/q], qq*AA) end proc

(1)

M:=Matrix([[0,-2*m*omega,0], [2*m*omega,0,0], [0,0,0]]);

_rtable[18446744074366181238]

(2)

facm(M,2);

2*_rtable[18446744074366175342]

(3)

facm(M,m);

m*_rtable[18446744074366169206]

(4)

But whose slope?

But in your approximations appears gamma itself, for which evalf is used!

I think that "solid" people parametrize and obtain the result if they want. Thank you for your thanks.

@Markiyan Hirnyk 

@Markiyan Hirnyk 

You need other tools for such problems. E.g. for the area:

f:=(1/10)*x^2-(69/790)*x+5569/255960-(3/79)*x*y-(77/4266)*y+(1/4)*y^4-(1/3)*y^3+(1/6)*y^2 - 3/1330:
evalf(Int( piecewise(f<0,1,0), x=0 .. 1, y=0..1));

       .1706012052

For a symbolic result, parametrize first. ==>

 

 

 

 

 

convert does not replace a space by \n; it simply inserts some \n 's.

Here is a test:


 

restart;

a:=add(f(i),i=1..1000000):

s:=convert(a,string):

length(s);

9888904

(1)

fprintf("d:/dnld/ss.txt","%s\n",s);

9888905

(2)

s1:=StringTools:-DeleteSpace(s):

length(s1);

9888895

(3)

fprintf("d:/dnld/ss1.txt","%s\n",s1);

9888896

(4)

close("d:/dnld/ss.txt");

close("d:/dnld/ss1.txt");

#####################

restart;

s:=readbytes("d:/dnld/ss.txt",infinity,TEXT):

length(s);

9888905

(5)

f:=x->x;

proc (x) options operator, arrow; x end proc

(6)

eval(parse(s));

500000500000

(7)

s1:=readbytes("d:/dnld/ss1.txt",infinity,TEXT):

eval(parse(s1));

500000500000

(8)

 

 

 

Just for fun, let's find for how many lists is the result of addList correct.
Denote by f(n) the number of "correct" lists with n elements.
Obviously such a list must have the entries in {±1, ±2,...,, ±n}.

f:=proc(n::posint)
   local v, i, P:=Iterator:-CartesianProduct([seq(1..n),seq(-n..-1)]$n);
   add(`if`(add(v) = add(v[v[i]],i=1..n),1,0), v=P) 
   end:

seq('f'(k)=f(k),k=1..6);
    
f(1) = 2, f(2) = 12, f(3) = 78, f(4) = 776, f(5) = 9520, f(6) = 172932

It seems that the sequence f(n) is a serious candidate for  https://oeis.org/

 

 

t=x was just a guess.
y must be >0 if the solution is supposed to pe real (otherwise y^(25/6) is complex in general).
You will need numeric solutions, so the value for x and the initial condition must be given.
[I suspect that the ODE does not have real solutions computable by Maple].

@mehdi jafari 

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