That 'error' typically can occure, if functions are used which are not defined for all Reals.

A brute and easy way is log( abs(t) ) instead of log(t) or similar for (square) roots etc.

Visually the data approach 0 (while the model 'never' would do that)
and seem to be quite disturbed beyond ~ 27 (as the plot shows)

hirnyk's suggestion looks good:

L:= map('t -> [t[1], (t[2])^(1/4)]', DATA);
L:= map('t -> [t[1], ln(t[2])]', DATA);
with(plots):
pointplot(L);

Visually the data approach 0 (while the model 'never' would do that)
and seem to be quite disturbed beyond ~ 27 (as the plot shows)

hirnyk's suggestion looks good:

L:= map('t -> [t[1], (t[2])^(1/4)]', DATA);
L:= map('t -> [t[1], ln(t[2])]', DATA);
with(plots):
pointplot(L);

I always try to separate data and programs (and usually do that even for 2 different drives),
so it is easy to make backups (not only Maple - always).

It seems that Maple (usually) takes the very directory, where I explicitely stored the last file.

I always try to separate data and programs (and usually do that even for 2 different drives),
so it is easy to make backups (not only Maple - always).

It seems that Maple (usually) takes the very directory, where I explicitely stored the last file.

I am not quite used to functional usage of Maple, but:

  subsindets(f,integer,evalhf);

gives me 

    Error, (in subsindets) invalid input: 
    evalhf expects 1 argument, but received 2

which I do not understand (what 2 arguments??), so I tried 

  evalindets(f,numeric,' x -> evalhf(x)'); %/1.0;

with the undesired effect, that exponents become floats. After some hacks
I came up with an ugly command to remove that

  #evalindets( %, '`^`', 't -> [op(1,t),op(2,t)]' );
  evalindets( %, '`^`', 't -> op(1,t)^floor(op(2,t))' );
 
                                     2                2  3
  87.00000000 x y - 56.00000000 x y z  - 62.00000000 x  z
                          3                    4
         + 97.00000000 x y  z - 73.00000000 y z

which should do.

oh män, why does Maple insist in that childish name/euphemism?

why dont you call it simply 'bug report', so every new user can find and use it? and if s/he uses
it at laest gets a formal feed back like "thx, received your msg"?

a change request in commercial SW dev is like 'want to have screen in blue, willing to pay for it'

oh män, why does Maple insist in that childish name/euphemism?

why dont you call it simply 'bug report', so every new user can find and use it? and if s/he uses
it at laest gets a formal feed back like "thx, received your msg"?

a change request in commercial SW dev is like 'want to have screen in blue, willing to pay for it'

The actual structure of the JNF is given through algebraic (=roots of char polynomial counted with multiplicity) vs geometric multiplicity (=dimension of solutions for A - lambda*id ) for the Eigenvalues (though I do not have a reasonable reference at hand and after forgetting the precise statement after some time have to look it up in older notes again)

The actual structure of the JNF is given through algebraic (=roots of char polynomial counted with multiplicity) vs geometric multiplicity (=dimension of solutions for A - lambda*id ) for the Eigenvalues (though I do not have a reasonable reference at hand and after forgetting the precise statement after some time have to look it up in older notes again)

for me it works ... hm ... see the appended sheet (zipped)

Download 102_graphing_Riemann_surface_of_Log.mws.zip
View file details

for me it works ... hm ... see the appended sheet (zipped)

Download 102_graphing_Riemann_surface_of_Log.mws.zip
View file details

Take tau: interval ---> Reals with inverse t

Then f(x) = f(t(y)) and instead of setting restrictions on x to be in the interval
one minimizes or solves for g: = f@t (restriction is now: y is real)

At the boundary that may need care (but one check in advance) and also it might be
that 'choosing a transformation which is reasonable for the task' is needed.

Other example: instead of having a condition like ' 0 <= x ' one can take y = x^2.

Not very detailled, but that's a simple recipe, which often works.

Take tau: interval ---> Reals with inverse t

Then f(x) = f(t(y)) and instead of setting restrictions on x to be in the interval
one minimizes or solves for g: = f@t (restriction is now: y is real)

At the boundary that may need care (but one check in advance) and also it might be
that 'choosing a transformation which is reasonable for the task' is needed.

Other example: instead of having a condition like ' 0 <= x ' one can take y = x^2.

Not very detailled, but that's a simple recipe, which often works.

For 0 <= x < 1 one can use a (inverse) transformation ]0 ... 1[ ---> IR like to be derived
from a probability density or arctan(x)/(Pi/2) or similar, it will depend a bit on the
problem and its (assumed) solution and if a good scaling is possible it would help. 

Then no side-relations are needed, just final transformations to the original task.