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This is Maple:

These are some primes:

22424170499, 106507053661, 193139816479, 210936428939, 329844591829, 386408307611,
395718860549, 396412723027, 412286285849, 427552056871, 454744396991, 694607189303,
730616292977, 736602622363, 750072072203, 773012980121, 800187484471, 842622684461

This is a Maple prime:


In plain text (so you can check it in Maple!) that number is:

111111111111111111111111111111111111111111111111111111111111111111111111111111
111111111111111111111111111111116000808880608061111111111111111111111111111111
111111111111111111111111111866880886008008088868888011111111111111111111111111
111111111111111111111116838888888801111111188006080011111111111111111111111111
111111111111111111110808080811111111111111111111111118860111111111111111111111
111111111111111110086688511111111111111111111111116688888108881111111111111111
111111111111111868338111111111111111111111111111880806086100808811111111111111
111111111111183880811111111111111111100111111888580808086111008881111111111111
111111111111888081111111111111111111885811188805860686088111118338011111111111
111111111188008111111111111111111111888888538888800806506111111158500111111111
111111111883061111111111111111111116580088863600880868583111111118588811111111
111111118688111111111001111111111116880850888608086855358611111111100381111111
111111160831111111110880111111111118080883885568063880505511111111118088111111
111111588811111111110668811111111180806800386888336868380511108011111006811111
111111111088600008888688861111111108888088058008068608083888386111111108301111
111116088088368860808880860311111885308508868888580808088088681111111118008111
111111388068066883685808808331111808088883060606800883665806811111111116800111
111581108058668300008500368880158086883888883888033038660608111111111111088811
111838110833680088080888568608808808555608388853680880658501111111111111108011
118008111186885080806603868808888008000008838085003008868011111111111111186801
110881111110686850800888888886883863508088688508088886800111111111111111118881
183081111111665080050688886656806600886800600858086008831111111111111111118881
186581111111868888655008680368006880363850808888880088811111111111111111110831
168881111118880838688806888806880885088808085888808086111111111111111111118831
188011111008888800380808588808068083868005888800368806111111111111111111118081
185311111111380883883650808658388860008086088088000868866808811111111111118881
168511111111111180088888686580088855665668308888880588888508880800888111118001
188081111111111111508888083688033588663803303686860808866088856886811111115061
180801111111111111006880868608688080668888380580080880880668850088611111110801
188301111111111110000608808088360888888308685380808868388008006088111111116851
118001111111111188080580686868000800008680805008830088080808868008011111105001
116800111111118888803380800830868365880080868666808680088685660038801111180881
111808111111100888880808808660883885083083688883808008888888386880005011168511
111688811111111188858888088808008608880856000805800838080080886088388801188811
111138031111111111111110006500656686688085088088088850860088888530008888811111
111106001111111111111111110606880688086888880306088008088806568000808508611111
111118000111111111111111111133888000508586680858883868000008801111111111111111
111111860311111111111111111108088888588688088036081111860803011111111863311111
111111188881111111111111111100881111160386085000611111111888811111108833111111
111111118888811111111111111608811111111188680866311111111111811111888861111111
111111111688031111111111118808111111111111188860111111111111111118868811111111
111111111118850811111111115861111111111111111888111111111111111080861111111111
111111111111880881111111108051111111111111111136111111111111188608811111111111
111111111111116830581111008011111111111111111118111111111116880601111111111111
111111111111111183508811088111111111111111111111111111111088880111111111111111
111111111111111111600010301111111111111111111111111111688685811111111111111111
111111111111111111111110811801111111111111111111158808806881111111111111111111
111111111111111111111181110888886886338888850880683580011111111111111111111111
111111111111111111111111111008000856888888600886680111111111111111111111111111
111111111111111111111111111111111111111111111111111111111111111111111111111111

This is a 3900 digit prime number. It took me about 400 seconds of computation to find using Maple.

It turns out be be really easy to do because prime numbers are realy quite common.  If you have a piece of ascii art where all the characters are numerals, you could just call on it and get a prime number that is still ascii art with a couple digits in the corner messed up (for a number this size, I expect fewer than 10 of the least significant digits would be altered).  You may notice, however, that my Maple Prime has beautiful corners!  This is possible because I found the prime in a slightly different way.

To get the ascii art in Maple, I started out by using to import ( )  and process the original image.  First then and to get a nice 78 pixel wide image.  Then to make it a pure 1-bit black or white image.

Then, from the image, I create a new Array of the decimal digits of the ascii art and my prime number.  For each of the black pixels I randomly use one of the digits or and for the white pixels (the background) I use 's.  Now I convert the Array to a large integer and test if it is prime using (it probably isn't) so, I just randomly change one of the black pixels to a different digit (there are 4 other choices) and call again. For the Maple Prime I had to do this about 1000 times before I landed on a prime number. That was surprisingly fast to me! It is a great object lesson in how dense the prime numbers really are.

So that you can join the fun without having to replicate my work, here is a small interactive Maple document that you can use to find prime numbers that draw ascii art of your source images. It has a tool that lets you preview both the pixelated image and the initial ascii art before you launch the search for the prime version.

Prime_from_Picture.mw

Of course, with Maple.

Dear All,

The following code plots the bifurcation diagram for a three-dimensional continuous dynamical system as a variable Re varies. However, the resulting plot (by pointplot command) is rather ugly, comparing with other bifurcation diagrams, see attached. Could anyone point me out how to improve its looking?

``

restart:
with(plots): with(DEtools): with(plottools):with(LinearAlgebra):
doSol:=proc( R )
             local t_start:=2500,
                   t_end:=5000,
                   b:=-3,
                   c:=3,
                   v1:=1,
                   f:=-4,
                   v2:=2.0,
                   omega:=0.1*sqrt(R),
                   epsilon:=evalf(1/R),
                   k:=0.1,
                   kH:=(c+1)/(b-1),
                   sys, evs, w, M, T, i, tt, solA, N_alpha,
                   r_center, z_center, Zshift, alpha, alpha1,
                   alpha2, del_alpha, m, Z, Rshift, RR;
             sys:=diff(u1(t),t)=v1*u1(t)-(omega+k*u2(t)^2)*u2(t)-(u1(t)^2+u2(t)^2-b*z(t)^2)*u1(t),
                  diff(u2(t),t)=(omega+k*u1(t)^2)*u1(t)+v1*u2(t)-(u1(t)^2+u2(t)^2-b*z(t)^2)*u2(t),
                  diff(z(t),t)=z(t)*(kH*v1+c*u1(t)^2+c*u2(t)^2+z(t)^2)+epsilon*z(t)*(v2+f*z(t)^4):
             solA:=dsolve({sys, u1(0)=0.6, u2(0)=0.6, z(0)=0.1},
                          {u1(t),u2(t),z(t)},
                          numeric, method=rkf45, maxfun=10^7,
                          events=[[[u1(t)=0, u2(t)>0], halt]]
                         );
             evs:=Array():
             evs(1,1..4):=Array([t,u1(t),u2(t),z(t)]);
             interface(warnlevel=0):

             for i from 2 do
                 w:=solA(t_end):
                 if   rhs(w[1])<t_end
                 then evs(i,1..4):=Array(map(rhs, w));
                      solA(eventclear);
                 else break;
                 fi
             od:

             interface(warnlevel=3):
             M:=DeleteRow(convert(evs,matrix),1):

             T:=M[..,1]:

             for i from 1 do
                 tt:=T[i]:
                 if   tt>=t_start
                 then break;
                 end if;
             end do:

             RR:=M[i..,3]: Z:=M[i..,4]:

             N_alpha:=numelems(RR):

             r_center:=add(RR[i],i=1..N_alpha)/N_alpha:
             z_center:=add(Z[i],i=1..N_alpha)/N_alpha:

             Zshift:=Z-~r_center: Rshift:=RR-~z_center:

             alpha:=(arctan~(Zshift/~Rshift)+(Pi/2)*sign~(Rshift))/~(2*Pi)+~0.5:

             return alpha;
  end proc:

i_start:=125: i_end:=250: i_delta:=0.1:

M:=[seq( [j, doSol(j)], j=i_start..i_end, i_delta)]:

S:=seq([Vector(numelems(M[i,2]),fill=M[i,1]),M[i,2]], i=1..numelems(M),1):
display(seq( pointplot(S[i],
             symbolsize=1,
             symbol=point) ,
             i=1..numelems(M)),
             axes=boxed,
             view=[i_start..i_end,0..1],
             size=[650,400],
             axesfont= ["TimesNewRoman", 16],
             labels=["Re",phi[n]],
             labelfont = ["TimesNewRoman", 16],
             labeldirections=[horizontal, vertical]);

``


 

Bifurcation_diagram.mw

Thank you.

Very kind wishes,

Wang Zhe

How can I do a color inversion on a jpg image in Maple?

Looking at  http://www.maplesoft.com/support/help/maple/view.aspx?path=ImageTools

and

http://www.maplesoft.com/support/help/maple/view.aspx?path=ImageTools%2fFormats

it seems to only support jpeg,tiff,bmp.

This seems like something from 1980's days. Is there another package to load other image formats? Such as png for example, and to export as png?

I'd like to import png file, rescale it in Maple (make thumbnail image) and export it again.

I am using 18.1 on windows 7

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]);

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

Way back in Maple 6, the rtable was introduced. You might be more familiar with its three types: Array, Matrix, and Vector. The name rtable is named after "rectangular table", since its entries can be stored contiguously in memory which is important in the case of "hardware" datatypes. This is a key aspect of the external-calling mechanism which allows Maple to use functions from the NAG and CLAPACK external libraries. In essence, the contiguous data portion of a hardware datatype rtable can be passed to a compiled C or Fortran function without any need for copying or preliminary conversion. In such cases, the data structure in Maple is storing its numeric data portion in a format which is also directly accessible within external functions.

You might have noticed that Matrices and Arrays with hardware datatypes (eg. float[8], integer[4], etc) also have an order. The two orders, Fortran_order and C_order, correspond to column-major and row-major storage respectively. The Wikipedia page row-major  explains it nicely.

There is even a help-page which illustrates that the method of accessing entries can affect performance. Since Fortran_order means that the individual entries in any column are contiguous in memory then code which accesses those entries in the same order in which they are stored in memory can perform better. This relates to the fact that computers cache data: blocks of nearby data can be moved from slower main memory (RAM) to very fast cache memory, often as a speculative process which often has very real benefits.

What I'd like to show here is that the relatively small performance improvement (due to matching the entry access to the storage order) when using evalhf can be a more significant improvement when using Maple's Compile command. For procedures which walk all entries of a hardware datatype Matrix or multidimensional Array, to apply a simple operation upon each value, the improvement can involve a significant part of the total computation time.

What makes this more interesting is that in Maple the default order of a float[8] Matrix is Fortran_order, while the default order of a float[8] Array used with the ImageTools package is C_order. It can sometimes pay off, to write your for-do loops appropriately.

If you are walking through all entries of a Fortran_order float[8] Matrix, then it can be beneficial to access entries primarily by walking down each column. By this I mean accessing entries M[i,j] by changing i in ther innermost loop and j in the outermost loop. This means walking the data entries, one at a time as they are stored. Here is a worksheet which illustrates a performance difference of about 30-50% in a Compiled procedure (the precise benefit can vary with platform, size, and what else your machine might be doing that interferes with caching).

Matrixorder.mw

If you are walking through all entries of an m-by-n-by-3 C_order float[8] Array (which is a common structure for a color "image" used by the ImageTools package) then it can be beneficial to access entries A[i,j,k] by changing k in the innermost loop and i in the outermost loop. This means walking the data entries, one at a time as they are stored. Here is a worksheet which illustrates a performance difference of about 30-50% in a Compiled procedure (the precise benefit can vary with platform, size, and what else your machine might be doing that interferes with caching).

Arrayorder.mw


 


 

restart

With the command, subpicture,I take the portion of it that interests me.
How I manage to include this sub-image in another image (img)?

Preview(correctedT)

imgs := GetSubImage(correctedT, 100, 125, 20, 120)
Preview(imgs)

Here's an example exhibited by Nusc, which I have tweaked slightly to make it look more like your mathematica example.

### Reference: http://www.mapleprimes.com/questions/36580-Bifurcation-Diagram

### xexpr is the logistic function to be iterated (we always start off at x=1/2, which will eventually attract).
### [ra,rb] is the range of the parameter.
### acc is the number of points sampled in [ra,rb]

Bifurcation := proc(initialpoint,xexpr,ra,rb,acc)

The complexplot3d command can color by using (complex) argument for the hue, and compute height z by magnitude. So, when rotated to view the x-y plane straight on, it can provide a nice coloring of the argument of whatever complex-valued expression is being plotted.

Another way to obtain a similar plot is to use densityplot (with appropriate values for its scaletorange option) and apply argument to the expression or function being plotted. For some kinds of complex-valued...

Why is it when I read an image a:=ImageTools:-ToGrayscale(ImageTools:-Read("f:/example.bmp")) saved as a bmp saved from the internet and try b:=Threshold(a,0.5,method=above) gives me this error.

Error, (in ImageTools:-Threshold) unable to store 0.107651138030195570e-293+0.522826466871872160e-288*I in a datatype=float[8] rtable

However when I open the bmp in paint and resave the image in either 24 bit 256 color, doesn't really matter, but a format of bmp...

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