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Let's see how we can display patterns, or even images, on 3D plot surfaces. Here's a simple example.

The underlying mechanism is the COLOR() component of a POLYGONS(), GRID(), or MESH() piece of a PLOT3D() data structure. (See here, here, and here for some older posts which relate to that.)

The data stored in the MESH() of a 3D plot structure can be a list-of-lists or, more efficient, an Array. The dimensions of that Array are m-by-n-by-3 where m and n are usually the size of the grid of points in the x-y plane (or of points in the two independent parameter spaces). In modern Maple quite a few kinds of 3D plots will produce a GRID() or a MESH() which represent the m-by-n independent data points that can be controlled with the usual grid=[m,n] option.

The plot,color help-page describes how colors may specified (for each x-y point pair to be plotted) using a procedure f(x,y). And that's fine for explicit plots, though there are some subtleties there. What is not documented on that help-page is the possibility of efficiently using an m-by-n-by-3 or an m*n-by-3 datatype=float[8], order=C_order Array of RGB values or am m*n float[8] Vector of hue values to specify the color data. And that's what I've been learning about, by experiment.

A (three-layer, RGB or HSV) color image used by the ImageTools package is also an m-by-n-by-3 Array. And all these Arrays under discussion have m*n*3 entries, and with either some or no manipulation they can be interchanged. I wrote earlier about converting ImageTools image structures to and from 2D density-plots. But there is also an easy way to get a 3D density-plot from an ImageTools image with a single command. That command is ImageTools:-Preview, and it even has a useful options to rescale. The rescaling is often necessary so that the dimensions of the COLOR() Array in the result match the dimensions of the grid in the MESH() Array.

For the first example, producing the banded torus above, we can get the color data directly from a densityplot, without reshaping/manipulating the color Array or using any ImageTools routines. The color data is stored in a m*n Vector of hue values.

But first a quick note: Some plots/plottools commands produce a MESH() with the data in a list-of-lists-of-lists, or a POLYGONS() call on a sequence of listlists (eg. `torus` in Maple 14). For convenience conversion of the data to a 3-dimensional Array may be done. It's handy to use `op` to see the contents of the PLOT3D() structure, but a possible catastrophe if a huge listlist gets printed in the Standard GUI.

restart:
with(ImageTools):with(plots):with(plottools):
N:=128:

d:=densityplot((x,y)->frem((x-2*y),1/2),0..1,0..1,
                      colorstyle=HUE,style=patchnogrid,grid=[N,N]):
#display(d);

c:=indets(d,specfunc(anything,COLOR))[1];

                         /     [ 1 .. 16384 Vector[column] ]\
                         |     [ Data Type: float[8]       ]|
               c := COLOR|HUE, [ Storage: rectangular      ]|
                         \     [ Order: C_order            ]/

T:=display(torus([0,0,0],1,2,grid=[N,N]),
           style=surface,scaling=constrained,axes=none,
           glossiness=0.7,lightmodel=LIGHT3):
#op(T); # Only view the operands in full with Maple 16!

# The following commands both produce the banded torus.

#op(0,T)(MESH(op([1,1..-1],T),c),op([2..-1],T)); # alternate way, M16 only

subsop([1,1]=[op([1,1],T),c][],T);

Most of the examples in this post use the command `op` or `indets` extract or replace the various parts of of the strcutures. Perhaps in future there could be an easy mechanism to pass the COLOR() Array directly to the plotting commands, using their `color` optional parameter.

In the next example we'll use an image file that is bundled with Maple as example data, and we'll use it to cover a sphere. We won't downsize the image, so that it looks sharp and clear (but note that this may make your Standard GUI session act a bit sluggish). Because we're not scaling down the image we must specify a grid=[m,n] size in the plotting command that matches the dimensions of the image. We'll use ImageTools:-Preview as a convenient mechanism to produce both the color Array as well as a 3D densityplot so that we can view the original image. Note that the data portion of the sphere plot structure is an m-by-n-by-3 Array in a MESH() which matches the dimensions of the m-by-n-by-3 Array in the COLOR() portion of the result from ImageTools:-Preview.

restart:
with(ImageTools):with(plots):with(plottools):
im:=Read(cat(kernelopts(mapledir),"/data/images/tree.jpg")):

p:=Preview(im):

op(1,p);

                 /                    [ 235 x 354 2-D  Array ]  
                 |                    [ Data Type: float[8]  ]  
             GRID|0 .. 266, 0 .. 400, [ Storage: rectangular ], 
                 \                    [ Order: C_order       ]  

                    /     [ 235 x 354 x 3 3-D  Array ]\\
                    |     [ Data Type: float[8]      ]||
               COLOR|RGB, [ Storage: rectangular     ]||
                    \     [ Order: C_order           ]//

q:=plot3d(1, x=0..2*Pi, y=0..Pi, coords=spherical, style=surface,
          grid=[235,354]):

display(PLOT3D(MESH(op([1,1],q), op([1,4..-1],p)), op(2..-1,q)),
           orientation=[-120,30,160]);

Apart from the online description of this new Maple 16 feature here, there is also the help-page for subexpressionmenu.

I don't know of a complete listing of its current functionality, but the key thing is that it acts in context. By that I mean that the choice of displayed actions depends on the kind of subexpression that one has selected with the mouse cursor.

Apart from arithmetic operations, rearrangements and some normalizations of equations, and plot previews, one of the more interesting pieces of functionality is the various trigonometric substitutions. Some of the formulaic trig substitutions provide functionality that has otherwise been previously (I think) needed in Maple.

In Maple 16 it is now much easier to do some trigonometric identity solving, step by step.

Here is an example executed in a worksheet. (This was produced by merely selecting subexpressions of the output at each step, and waiting briefly for the new Smart Popup menus to appear automatically. I did not right-click and use the traditional context-sensitive menus. I did not have to type in any of the red input lines below: the GUI inserts them as a convenience, for reproduction. This is not a screen-grab movie, however, and doesn't visbily show my mouse cursor selections. See the 2D Math version further below for an alternate look and feel.)

expr:=sin(3*a)=3*sin(a)-4*sin(a)^3:

expr;

sin(3*a) = 3*sin(a)-4*sin(a)^3

# full angle reduction identity: sin(3*a)=-sin(a)^3+3*cos(a)^2*sin(a)
-sin(a)^3+3*cos(a)^2*sin(a) = 3*sin(a)-4*sin(a)^3;

-sin(a)^3+3*cos(a)^2*sin(a) = 3*sin(a)-4*sin(a)^3

# subtract -sin(a)^3 from both sides
(-sin(a)^3+3*cos(a)^2*sin(a) = 3*sin(a)-4*sin(a)^3) -~ (-sin(a)^3);

3*cos(a)^2*sin(a) = 3*sin(a)-3*sin(a)^3

# divide both sides by 3
(3*cos(a)^2*sin(a) = 3*sin(a)-3*sin(a)^3) /~ (3);

cos(a)^2*sin(a) = sin(a)-sin(a)^3

# divide both sides by sin(a)
(cos(a)^2*sin(a) = sin(a)-sin(a)^3) /~ (sin(a));

cos(a)^2 = (sin(a)-sin(a)^3)/sin(a)

# normal 1/sin(a)*(sin(a)-sin(a)^3)
cos(a)^2 = normal(1/sin(a)*(sin(a)-sin(a)^3));

cos(a)^2 = 1-sin(a)^2

# Pythagoras identity: cos(a)^2=1-sin(a)^2
1-sin(a)^2 = 1-sin(a)^2;

1-sin(a)^2 = 1-sin(a)^2

 

The very first step above could also be done as a pair of simpler sin(x+y) reductions involving sin(2*a+a) and sin(a+a), depending on what one allows onself to use. There's room for improvement to this whole approach, but it looks like progress.

Download trigident1.mw

In a Document, rather than using 1D Maple notation in a Worksheet as above, the actions get documented in the more usual way, similar to context-menus, with annotated arrows between lines.

expr := sin(3*a) = 3*sin(a)-4*sin(a)^3:

expr

sin(3*a) = 3*sin(a)-4*sin(a)^3

(->)

2*cos(a)*sin(2*a)-sin(a) = 3*sin(a)-4*sin(a)^3

(->)

4*cos(a)^2*sin(a)-sin(a) = 3*sin(a)-4*sin(a)^3

(->)

4*cos(a)^2*sin(a) = 4*sin(a)-4*sin(a)^3

(->)

cos(a)^2*sin(a) = sin(a)-sin(a)^3

(->)

cos(a)^2 = (sin(a)-sin(a)^3)/sin(a)

(->)

cos(a)^2 = 1-sin(a)^2

(->)

1-sin(a)^2 = 1-sin(a)^2

(->)

1 = 1

``

Download trigident2.mw

 

I am not quite sure what is the best way to try and get some of the trig handling in a more programmatic way, ie. by using the "names" of the various transformational formulas. But some experts here may discover such by examination of the code. Ie,

eval(SubexpressionMenu);

showstat(SubexpressionMenu::TrigHandler);

The above can leads to noticing the following (undocumented) difference, for example,

> trigsubs(sin(2*a));
              
                                 1       2 tan(a)
[-sin(-2 a), 2 sin(a) cos(a), --------, -----------,
                              csc(2 a)            2
                                        1 + tan(a)

    -1/2 I (exp(2 I a) - exp(-2 I a)), 2 sin(a) cos(a), 2 sin(a) cos(a)]

> trigsubs(sin(2*a),annotate=true);

["odd function" = -sin(-2 a), "double angle" = 2 sin(a) cos(a),

                               1                       2 tan(a)
    "reciprocal function" = --------, "Weierstrass" = -----------,
                            csc(2 a)                            2
                                                      1 + tan(a)

    "Euler" = -1/2 I (exp(2 I a) - exp(-2 I a)),

    "angle reduction" = 2 sin(a) cos(a),

    "full angle reduction" = 2 sin(a) cos(a)]

And that could lead one to try constructions such as,

> map(rhs,indets(trigsubs(sin(a),annotate=true),
>                identical("double angle")=anything));

                             {2 sin(a/2) cos(a/2)}

Since the `annotate=true` option for `trigsubs` is not documented in Maple 16 there is more potential here for useful functionality.

Here is a hacked-up and short `convert/identifier` procedure.

The shortness of the procedure should is a hint that it's not super robust. But it can be handy, in some simple display situations.

If I had made into a single procedure (named `G`, or whatever) then I could have declared its first parameter as x::uneval and thus avoided the need for placing single-right (uneval) quotes around certain examples. But for fun I wanted it to be an extension of `convert`. And while I could code special-evaluation rules on my `convert` extension I suppose that there no point in doing so since `convert` itself doesn't have such rules.

For the first two examples below I also typed in the equivalent expressions in 2D Math input mode, and then used the right-click context-menu to convert to Atomic Identifier. Some simple items come out the same, while some other come out with a different underlying structure and display.

 

restart:

`convert/identifier`:=proc(x)
   cat(`#`,convert(convert(:-Typesetting:-Typeset(x),`global`),name));
end proc:

convert( 'sqrt(4)', identifier);

`#msqrt(mn("4"))`

eval(value(%));
lprint(%);

`#msqrt(mn("4"))`

`#msqrt(mn("4"))`

`#msqrt(mn("4"))`

`#msqrt(mn("4"))`

lprint(%);

`#msqrt(mn("4"))`

convert( 'int(BesselJ(0,Pi*sqrt(t)),t)', identifier);

`#mrow(mo("∫"),mrow(msub(mi("J",fontstyle = "normal",msemantics = "BesselJ"),mn("0")),mo("⁡"),mfenced(mrow(mi("π"),mo("⁢"),msqrt(mi("t"))))),mspace(width = "0.3em"),mo("ⅆ"),mi("t"))`

eval(value(%));
#lprint(%);

`#mrow(mo("∫"),mrow(msub(mi("J",fontstyle = "normal",msemantics = "BesselJ"),mn("0")),mo("⁡"),mfenced(mrow(mi("π"),mo("⁢"),msqrt(mi("t"))))),mspace(width = "0.3em"),mo("ⅆ"),mi("t"))`

`#mrow(mo("∫"),msub(mo("J"),mn("0")),mfenced(mrow(mi("π",fontstyle = "normal"),mo("⁢"),msqrt(mi("t")))),mo("⁢"),mo("ⅆ"),mi("t"))`

`#mrow(mo("∫"),msub(mo("J"),mn("0")),mfenced(mrow(mi("π",fontstyle = "normal"),mo("⁢"),msqrt(mi("t")))),mo("⁢"),mo("ⅆ"),mi("t"))`

#lprint(%);

convert( Vector[row](['Zeta(0.5)', a.b.c, 'limit(sin(x)/x,x=0)', q*s*t]), identifier);

Vector[row](4, {(1) = Zeta(.5), (2) = a.b.c, (3) = limit(sin(x)/x, x = 0), (4) = q*s*t})

eval(value(%));
#lprint(%);

Vector[row](4, {(1) = Zeta(.5), (2) = a.b.c, (3) = limit(sin(x)/x, x = 0), (4) = q*s*t})

 

Download atomic1.mw

As it stands this hack may be useful in a pinch for demos and purely visual effect, but unless it's robustified then it won't allow you to programmatically generate atomic names which match and inter-operate computationally with those from the context-menu conversion. Identifiers (names) with similar typeset appearance still have to match exactly if they are to be properly compared, added, subtracted with each other.

Extra points for commenting that the round-brackets (eg. in function-application) are displayed as black while the rest is in blue by default, if you have a workaround.  That also happens when using the usual context-menu driven convert-to-atomic-identifier of the Standard GUI.

Extra points for noticing that function names like `sin` are italicized and not in an upright font, if you have a workaround. How to discern which instances of fontstyle="normal" should be removed?

Points off for commenting that this whole hack doesn't provide anything new or extra for getting around automatic simplification.  :)

This is a one-liner hack. But maybe together we could turn it into something that closely matched what the context-menu generates.

Many of us know that issuing plotting commands produces various kinds of plot data structure, the details of which are documented on the plot,structure help-page. That page covers most of the details, and a thorough read can reveal that the numeric data of a plot is often stored within such structures as either Array or Matrix.

But what about the result of a call to

Someone asked me the other week whether a color gradient could be easily applied to a high density point-plot, either vertically or horizontally graded.

Without thinking, I said, "Sure, easy." But when I got to a computer, and gave it a little thought, I realized that it's not that easy to do it efficiently. And it really ought to be, even for tens of thousands of points.

There is a help-page plot,color which briefly describes some things that can be done with coloring plots. As of Maple 16, it mentions a "color data structure" which can be created by calls to the new ColorTools package. There is an example on that page for a single color, but not for several colors concurrently. Using Colortools to get a list of colors, for many points, can be done. (And there ought to be such an example.) But for the case of many data points that uses quite a lot of memory, and is slow.

Also, there is no 2D plotting equivalent to the 3D plotting colorfunc functionality. There ought to be. And just as the 3D colorfunc should be fixed to take three arguments (x,y, & z) any new 2D colorfunc should be made to take two arguments (x & y).

So, how can we apply a color gradient on a 25000 2D-point-plot, shaded by y-value? One way is to notice that the various 2D and 3D plot data structures can now store an efficient m-by-3 (or m-by-n-by-3) C_order, float[8] Array for the purpose of representing the chosen colors. (That is not documented, but can be learned by observation and inspection of various example plot structures.) We know that such an Array is relatively memory-light, and can be produced very quickly.

What this task has become is a 2D version of this method of inserting a custom made color sequence into a 3D plot, but more efficient on account of using a float[8] Array.

To get some decent timings the attached worksheet uses the time[real] command. Timings are computed both immediately after computation (same execution block) as well as after plot rendering (next execution block).

It takes about 1 sec for the Maple 16.01 64bit Standard GUI on Windows 7 to throw up and render the plot, for both methods.

It takes 3.4 sec, and a 108 MB increase in allocated memory, to compute the plot data structure result using ColorTools and a list. But it takes only 0.45 sec, and a 20.5 MB increase in allocated memory, to compute an equivalent plot data structure using the float[8] Array. (Timings on an Intel i7-960.)

[worksheet upload is misbehaving. So inlining the code.]

restart:
N:=25000:

xy:=LinearAlgebra:-RandomMatrix(N,2,generator=0.0..1.0,
                                outputoptions=[datatype=float[8]]):

str:=time[real]():

plots:-pointplot(xy,
                    color=[seq(ColorTools:-Color([xy[i,2],0,0]),i=1..N)],
                    symbolsize=4);

time[real]()-str;

                             3.323

time[real]()-str; # in new execution group

                             4.400
kernelopts(bytesalloc);

                           107646976


restart:
N:=25000:

xy:=LinearAlgebra:-RandomMatrix(N,2,generator=0.0..1.0,
                                outputoptions=[datatype=float[8]]):

str:=time[real]():

p:=plots:-pointplot(xy,color=red,symbolsize=4):

c:=Array(1..N*3,(i)->`if`(irem(i,3)=1,xy[(i+2)/3,2],0),
         datatype=float[8],order=C_order):

subsindets(p,specfunc(anything,COLOUR),z->'COLOUR'('RGB',c));

time[real]()-str;

                             0.483

time[real]()-str; # in new execution group

                             1.357
kernelopts(bytesalloc);

                            20545536
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