If I changed elements like `-p/2` to `- p/2`, with a space after the minus sign, then it appeared better in the exported .eps file. The symbol showed as minus rather than plusminus, and the extra whitespace didn't seem too glaring.

But then I tried something else. There is also a programmatic way to export the plot. before the display call, I added this command,

plotsetup(ps,plotoutput=`foo.eps`,plotoptions=`portrait,noborder`);

That command will make plots get written directly to the file. The plot won't also appear visually. Using the exporter, I found that the original syntax you used of `-p/2` would come out with the correct minus sign in the .eps file.

I used ghostview to preview the .eps file, rather than embedding it into latex.

Is the "90 degree rotation" issue just one of portrait versus landscape, for Postscript?

It's fun, no, that Maple has (at least) three distinct Postscript converters? (Ie, the menu driven one in Standard, the menu driven one in Classic, and that programmatic command available in each interface.)

The command plotsetup(default) will reset the plot device to its original default setting (ie, visual display of plots).

acer

Users will expect that their old code works, as is. And the syntax of the commands from the two packages is different. So the direct substitution of the package names, in commands, would not work I think.

One can observe that effort has been made to more strongly deprecate linalg, in the Maple help-system in Maple 12. For example, entering,

> ?linalg

> ?stats

takes one to the Student[LinearAlgebra] and Statistics help-pages, repectively, in Maple 12.

It's a little heavy handed in parts. For example issuing ?array takes one to the Array help-page, but I don't see any obvious cross-link from the top of that page to ?array(deprecated). One can find similar problems, when trying to access other older deprecates pages in Maple 12 without knowing in advance that they get accessed by the syntax ?<fcn>(deprecated). In the Standard interface, the help-browser should show a list of relevant matches, but in the Classic and commandline interfaces it's more problematic.

acer

I suspect that he is referring to the Mapleprimes points system.

For example, by clicking on the number beside your "red leaf". And so one can get to the rankings here.

To try to answer the question, about what they are used for, not much except to indicate how many posts have been made from the given member-handle. I believe that some ability to edit own's own posts (or perhaps to post blog entries?) is enabled once one attains a number (10?) of posts.

acer

I suspect that he is referring to the Mapleprimes points system.

For example, by clicking on the number beside your "red leaf". And so one can get to the rankings here.

To try to answer the question, about what they are used for, not much except to indicate how many posts have been made from the given member-handle. I believe that some ability to edit own's own posts (or perhaps to post blog entries?) is enabled once one attains a number (10?) of posts.

acer

One of the things that makes textbooks on Maple tricky is that the system keeps evolving. The linalg package gets replaced with LinearAlgebra, the stats package with Statistics, the networks package with GraphTheory, Maplets with embedded components, etc. And some parts get enhanced, for example the newer DAE solvers. So, given a mathematical or programming task, it's quite conceivable that the nicer ways to do it in Maple may change with the advent of a new release. And Maple has been getting new releases most every year, for some time.

So, a text written in 2002 (like the one you cited) may be partially out of date. I find it hard to tell whether the more general Maple books or the ones focussed on some discipline fall behind current maple functionality more quickly. The title of the book that you cited mentions probability and stochastic DEs. The newer Statistics package postdates the book, I believe (as does the Financial Modelling Toolbox, which does Wiener process stuff, etc).

So, depending on the hints you get (here, say) about changes in the product and the books age, you may wish to be extra careful in judging a particular book.

acer

One of the things that makes textbooks on Maple tricky is that the system keeps evolving. The linalg package gets replaced with LinearAlgebra, the stats package with Statistics, the networks package with GraphTheory, Maplets with embedded components, etc. And some parts get enhanced, for example the newer DAE solvers. So, given a mathematical or programming task, it's quite conceivable that the nicer ways to do it in Maple may change with the advent of a new release. And Maple has been getting new releases most every year, for some time.

So, a text written in 2002 (like the one you cited) may be partially out of date. I find it hard to tell whether the more general Maple books or the ones focussed on some discipline fall behind current maple functionality more quickly. The title of the book that you cited mentions probability and stochastic DEs. The newer Statistics package postdates the book, I believe (as does the Financial Modelling Toolbox, which does Wiener process stuff, etc).

So, depending on the hints you get (here, say) about changes in the product and the books age, you may wish to be extra careful in judging a particular book.

acer

I would like to thank all who posted to this thread. The points raised are very interesting. Hopefully, having several major contributors to this site offer their suggestions/needs will induce those ideas to be weighed and judged carefully.

ps. I'm still editing my list...

acer

LinearSolve uses a general (full rectangular dense) solver on tridiagonal linear floating-point systems. For real data, that means LAPACK dgetrf and dgetrs (NAG f07adf and f07aef). But LinearSolve could be taught to instead use dgttrf and dgttrs which are specialized.

> infolevel[LinearAlgebra]:=1:
> with(LinearAlgebra):

> f := n->Matrix(n,n,shape=band[1,1],scan=band[1,1],
>    [[1$(n-1)],[seq(i,i=1..n)],[1$(n-1)]],
>    storage=rectangular,datatype=float[8]):

> rtable_indfns(f(5)); # it's tridiagonal in structure...
                                  band[1, 1]
 
> rtable_options(f(5),storage); # ...and full storage, as dgttrf expects
                                  rectangular

> LinearSolve(evalf(f(5)),evalf(Vector(5,i->i)));
LinearSolve:   "using method"   LU
LinearSolve:   "calling external function"
LinearSolve:   "NAG"   hw_f07adf
LinearSolve:   "NAG"   hw_f07aef
                            [0.696969696969697017]
                            [                    ]
                            [0.303030303030302983]
                            [                    ]
                            [0.696969696969697017]
                            [                    ]
                            [0.606060606060606077]
                            [                    ]
                            [0.878787878787878896]

Moreover, if the (real) Matrix is symmetric positive-definite then dpttrf and dpttrs could be used.

> type(f(5),'Matrix'(symmetric));
                                     true

> IsDefinite(evalf(f(5)),query=positive_definite);
                                     true

acer

LinearSolve uses a general (full rectangular dense) solver on tridiagonal linear floating-point systems. For real data, that means LAPACK dgetrf and dgetrs (NAG f07adf and f07aef). But LinearSolve could be taught to instead use dgttrf and dgttrs which are specialized.

> infolevel[LinearAlgebra]:=1:
> with(LinearAlgebra):

> f := n->Matrix(n,n,shape=band[1,1],scan=band[1,1],
>    [[1$(n-1)],[seq(i,i=1..n)],[1$(n-1)]],
>    storage=rectangular,datatype=float[8]):

> rtable_indfns(f(5)); # it's tridiagonal in structure...
                                  band[1, 1]
 
> rtable_options(f(5),storage); # ...and full storage, as dgttrf expects
                                  rectangular

> LinearSolve(evalf(f(5)),evalf(Vector(5,i->i)));
LinearSolve:   "using method"   LU
LinearSolve:   "calling external function"
LinearSolve:   "NAG"   hw_f07adf
LinearSolve:   "NAG"   hw_f07aef
                            [0.696969696969697017]
                            [                    ]
                            [0.303030303030302983]
                            [                    ]
                            [0.696969696969697017]
                            [                    ]
                            [0.606060606060606077]
                            [                    ]
                            [0.878787878787878896]

Moreover, if the (real) Matrix is symmetric positive-definite then dpttrf and dpttrs could be used.

> type(f(5),'Matrix'(symmetric));
                                     true

> IsDefinite(evalf(f(5)),query=positive_definite);
                                     true

acer

> h := n-> Matrix(n,n,scan=band[1,1],[[seq(x[i]^2,i=2..n)],
>            [seq(x[i],i=1..n)],[seq(2*x[i],i=1..n-1)]]):

> h(5);
                [x[1]     2 x[1]      0         0         0   ]
                [                                             ]
                [    2                                        ]
                [x[2]      x[2]     2 x[2]      0         0   ]
                [                                             ]
                [             2                               ]
                [  0      x[3]       x[3]     2 x[3]      0   ]
                [                                             ]
                [                       2                     ]
                [  0        0       x[4]       x[4]     2 x[4]]
                [                                             ]
                [                                 2           ]
                [  0        0         0       x[5]       x[5] ]

acer

> h := n-> Matrix(n,n,scan=band[1,1],[[seq(x[i]^2,i=2..n)],
>            [seq(x[i],i=1..n)],[seq(2*x[i],i=1..n-1)]]):

> h(5);
                [x[1]     2 x[1]      0         0         0   ]
                [                                             ]
                [    2                                        ]
                [x[2]      x[2]     2 x[2]      0         0   ]
                [                                             ]
                [             2                               ]
                [  0      x[3]       x[3]     2 x[3]      0   ]
                [                                             ]
                [                       2                     ]
                [  0        0       x[4]       x[4]     2 x[4]]
                [                                             ]
                [                                 2           ]
                [  0        0         0       x[5]       x[5] ]

acer

g:=n->LinearAlgebra:-ToeplitzMatrix([0$(n-1),c,b,a,0$(n-1)]);

g(7);

acer

g:=n->LinearAlgebra:-ToeplitzMatrix([0$(n-1),c,b,a,0$(n-1)]);

g(7);

acer

Apparently there's neat stuff known about this (here, here) and the condition might be simply that numbcomb(3*i,i) is odd.

> G:=n->map(x->[op(x),seq(0,i=1..n-nops(x))],
>           {seq(`if`(type(binomial(3*i,i),odd),convert(i,base,2),
>                     NULL),i=0..(2^n-1))}):


> G(6);
{[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 1, 0],
 
    [0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 0, 1], [0, 0, 1, 0, 0, 0],
 
    [0, 0, 1, 0, 0, 1], [0, 0, 1, 0, 1, 0], [0, 1, 0, 0, 0, 0],
 
    [0, 1, 0, 0, 0, 1], [0, 1, 0, 0, 1, 0], [0, 1, 0, 1, 0, 0],
 
    [0, 1, 0, 1, 0, 1], [1, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 1],
 
    [1, 0, 0, 0, 1, 0], [1, 0, 0, 1, 0, 0], [1, 0, 0, 1, 0, 1],
 
    [1, 0, 1, 0, 0, 0], [1, 0, 1, 0, 0, 1], [1, 0, 1, 0, 1, 0]}

What I wonder about now is the OP's handle. Did the OP know of the connection to fibonacci numbers?

acer

Apparently there's neat stuff known about this (here, here) and the condition might be simply that numbcomb(3*i,i) is odd.

> G:=n->map(x->[op(x),seq(0,i=1..n-nops(x))],
>           {seq(`if`(type(binomial(3*i,i),odd),convert(i,base,2),
>                     NULL),i=0..(2^n-1))}):


> G(6);
{[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 1, 0],
 
    [0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 0, 1], [0, 0, 1, 0, 0, 0],
 
    [0, 0, 1, 0, 0, 1], [0, 0, 1, 0, 1, 0], [0, 1, 0, 0, 0, 0],
 
    [0, 1, 0, 0, 0, 1], [0, 1, 0, 0, 1, 0], [0, 1, 0, 1, 0, 0],
 
    [0, 1, 0, 1, 0, 1], [1, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 1],
 
    [1, 0, 0, 0, 1, 0], [1, 0, 0, 1, 0, 0], [1, 0, 0, 1, 0, 1],
 
    [1, 0, 1, 0, 0, 0], [1, 0, 1, 0, 0, 1], [1, 0, 1, 0, 1, 0]}

What I wonder about now is the OP's handle. Did the OP know of the connection to fibonacci numbers?

acer