Personal Stories

Stories about how you have used Maple, MapleSim and Math in your life or work.

most effective built in operator code award goes to ppl that wrote the code for the union and intercect set operations for maple. Very important simple example below of  one of its applications.

 

When i work with algorithms, probably one of my most primary ports of enquiry (figuratively jeez skynet)  is to set up and if statement triggered to terminate the loop once the operations performed for any further cycles is INDEMPOTENT. this doesnt always mean your output is convergent in every case but it allows you to minimize the amount of time the cpu needs to collect data( ie the point at which it would produce that same set as it did in the last most loop)

 

 

Y := proc (X) local N, S1, `&Sopf;`; if X <> `union`(X, S1[N]) then N := (rand(1 .. NrANGE))(); S1[N] := {K[1](4+N), K[1](5+N), K[1](6+N), K[1](7+N), K[1](8+N), K[1](9+N), K[1](10+N), K[1](11+N), K[1](12+N), K[1](13+N), K[1](14+N), K[1](15+N)}; `&Sopf;` := `union`(X, S1[N]) else  end if end proc

proc (X) local N, S1, `&Sopf;`; if X <> `union`(X, S1[N]) then N := (rand(1 .. NrANGE))(); S1[N] := {K[1](4+N), K[1](5+N), K[1](6+N), K[1](7+N), K[1](8+N), K[1](9+N), K[1](10+N), K[1](11+N), K[1](12+N), K[1](13+N), K[1](14+N), K[1](15+N)}; `&Sopf;` := `union`(X, S1[N]) else  end if end proc

(1)

``

 

Download idempotency.mwidempotency.mw

 

 

Walking into the big blue Maplesoft office on August 3rd was a bit nerve wracking. I had no idea who anyone was, what to expect, or even what I would be doing. As I sat in the front hall waiting for someone to receive me, I remember thinking, “What have I gotten myself into?”. Despite my worries on that first day, interning at Maplesoft has been a great experience! I never knew that I would be able to learn so much about programming and working in a company in such a short amount of time. Although Maple was a programming language that was foreign to me a couple weeks ago, I feel like I’m relatively well versed in it now. Trying to learn a new language in this short timespan hasn’t been easy, but I think that I picked it up quickly, even if I’ve had my fair share of frustrations.

Chaos Game example on Rosetta Code

At Maplesoft, I’ve been contributing to the Rosetta Code project by writing short programs using Maple. The Rosetta Code project is dedicated to creating programming examples for many different tasks in different programming languages. My summer project has been to create solutions using Maple for as many tasks as possible and to post these to Rosetta Code; the goal being to have the list of tasks without Maple implementation shrink with each passing day. It’s nice to feel like I’m leaving a mark in this world, even if it is in such a small corner of the internet.

Flipping Bits example on Rosetta Code/MapleCloud

This internship, of course, came with its share of challenges. During my work on the Rosetta Code project, I posted solutions for a total of 38 tasks. Some of them were easy, but some of them took days to complete. On some days, I felt like I was on top of the world. Everything I made turned out great and I knew exactly how to tackle each problem. Other days were slower. I’ve spent ages just staring at a computer monitor trying to figure out just how on earth I was going to make this machine do what I wanted it to do! The 24 Game task was particularly hard, but also very educational. Through this task, I learned about modules, a concept previously unknown to me. I’m fairly sure that the 24 Game also took me the longest, whereas the Increment a numerical string task took me no time at all. Despite it being easy, the Increment a numerical string task wasn’t particularly fun; a bit of a challenge is required for something to be entertaining, after all. My personal favourite was the Fibonacci n-step number sequences task. It was the first really challenging task I encountered, and for after which the feeling of finally completing a task that I spent so long on, of finally overcoming that mountain, was extremely satisfying. Not all challenges end in satisfaction, however. I often found myself accidentally doing something that made the window freeze. I would close the program, then cry a bit on the inside when I realized I just lost the past half an hour’s worth of unsaved work. Nevertheless, I’m glad I got to face all these obstacles because they have made me more resilient and a better programmer.

The following is the code for the Fibonacci n-step number sequences task

numSequence := proc(initValues :: Array)
	local n, i, values;
n := numelems(initValues);
values := copy(initValues);
for i from (n+1) to 15 do
values(i) := add(values[i-n..i-1]);
end do;
return values;
end proc:
 
initValues := Array([1]):
for i from 2 to 10 do
initValues(i) := add(initValues):
printf ("nacci(%d): %a\n", i, convert(numSequence(initValues), list));
end do:
printf ("lucas: %a\n", convert(numSequence(Array([2, 1])), list));

Maple was a great software to program with and a fairly straightforward language to learn. Having previously programmed in Java, I found Maple similar enough that transitioning wasn’t too difficult. In fact, every once in a while when I didn`t know what to do for a task, I would take a look at the Java example in Rosetta Code and it would point me in a direction or give me some hints. While the two languages are similar, there are still many differences. For example, I liked the fact that in Maple, lists started at an index of 1 rather than 0 and arrays could an arbitrary starting index. Although it was different from what I was used to, I found that it made many things much less confusing. Another thing I liked was that the for loop syntax was very simple. I never once had to run through in my head how many times something would loop for. There were such a wide variety of commands in Maple. There was a command for practically anything, and if you knew that it existed and how to use it, then so much power could be at your fingertips. This is where the help system came in extremely handy. With a single search you might find that the solution to the exact problem you were trying to solve already existed as a Maple command. I always had a help window open when I was using Maple.

Multiplication Tables example on Rosetta Code

Spending my summer coding at Maplesoft has been fun, sometimes challenging, but an overall rewarding experience. Through contributing to the Rosetta Code project, I’ve learned so much about computer programming, and it certainly made the 45 minute drive out to Waterloo worth it!

Yili Xu,
Maplesoft SHAD Intern

Bruce Jenkins is President of Ora Research, an engineering research and advisory service. Maplesoft commissioned him to examine how systems-driven engineering practices are being integrated into the early stages of product development, the results of which are available in a free whitepaper entitled System-Level Physical Modeling and Simulation. In this series of blog posts, Mr. Jenkins discusses the results of his research.

This is the second entry in the series.

My last post, Strategies for accelerating the move to simulation-led, systems-driven engineering, described my firm’s research project to investigate the contemporary state of adoption and application of systems modeling software technologies, and their attendant methods and work processes, in the engineering design of off-highway equipment and mining machinery.

Adoption drivers

In this project, I conducted in-depth, structured but open-ended interviews with some half-dozen expert practitioners at leading manufacturers, including both engineering management and senior discipline leads. These interviews identified the following key technological factors as well as business and competitive issues driving adoption and use of systems modeling tools and methods at current levels:

  • Fuel economy and emissions mandates, powertrain electrification and autonomous operation requirements
  • Software’s ability to drive down product cost of ownership and delivery times
  • Traditional development processes often fail to surface system-level issues until fabrication or assembly, or even until operational deployment
  • Detailed analysis tools such as FEA and CFD focus on behaviors at the component level, and are not optimal for studies of the complete system
  • Engineering departments/groups enjoy greater freedom in systems modeling software selection and purchase decisions than in enterprise-controlled CAD/PDM/PLM decisions
  • Good C/VP-level visibility of systems modeling tools, especially in off-highway equipment

Adoption constraints

At the same time, there was widespread agreement among all the experts interviewed that these tools and methods are not being brought to bear with anywhere near the breadth or depth that practitioner advocates would like, and that they believe would be greatly beneficial to their organizations and industries.

In probing why this is, the interviews revealed an array of factors constraining broader adoption at present. These range from legacy engineering culture issues, through human resource limitations and constraints imposed by business models and corporate cultures, to entrenched shortcomings in how long-established systems modeling software toolsets have been deployed and applied to the product development process:

  • Legacy engineering culture constraints
    • Conservatism of mining machinery product development culture
    • Engineering practices in long-standardized industries grounded in handbook formulas and rules of thumb
    • Perceived lack of time in schedule to do systems modeling
  • Human resource constraints
    • Low availability of engineers with systems modeling skills
    • Shortage of engineers trained in systems thinking
    • Legacy engineering processes compound shortage of systems-thinking engineers
    • Industry downturns put constraints on professional staff development
  • Business-model and corporate-culture constraints
    • Culture of seeking to mitigate cost and risk by staying with legacy designs instead of advancing and innovating the product
    • Corporate awareness of need to innovate in mining machinery gets stifled at engineering level
    • Low C/VP-level visibility of systems modeling tools in mining machinery
  • Engineering organization constraints on innovating/modernizing their systems modeling technology infrastructure
    • Power users wedded to legacy systems modeling tools
    • Weak integration at many/most points of the engineering digital toolset chain
    • Implementing systems modeling software as a sales configuration/costing aid seen as taking too much time

My next post will detail practitioners’ visions, strategies and best practices for accelerating and institutionalizing the implementation and usage of systems modeling tools and practices in their organizations.

You can download the full white paper reporting our findings here.

Bruce Jenkins, Ora Research
oraresearch.com

In order to change Maple for the better, I use to submit SCRs. However, as i was kindly
informed by Bryon (a copy of his e-letter on demand), MaplePrimes are under reconstruction and do not
work properly. At least my three messages sent through the Contact button were lost.
I have  unsuccessfully tried to reach beta.maplesoft.com (see the result of ping in the screen screen.29.08.16.docx).
Please, help me!

Bruce Jenkins is President of Ora Research, an engineering research and advisory service. Maplesoft commissioned him to examine how systems-driven engineering practices are being integrated into the early stages of product development, the results of which are available in a free whitepaper entitled System-Level Physical Modeling and Simulation. In the coming weeks, Mr. Jenkins will discuss the results of his research in a series of blog posts.

This is the first entry in the series.

Discussions of how to bring simulation to bear starting in the early stages of product development have become commonplace today. Driving these discussions, I believe, is growing recognition that engineering design in general, and conceptual and preliminary engineering in particular, face unprecedented pressures to move beyond the intuition-based, guess-and-correct methods that have long dominated product development practices in discrete manufacturing. To continue meeting their enterprises’ strategic business imperatives, engineering organizations must move more deeply into applying all the capabilities for systematic, rational, rapid design development, exploration and optimization available from today’s simulation software technologies.

Unfortunately, discussions of how to simulate early still fixate all too often on 3D CAE methods such as finite element analysis and computational fluid dynamics. This reveals a widespread dearth of awareness and understanding—compounded by some fear, intimidation and avoidance—of system-level physical modeling and simulation software. This technology empowers engineers and engineering teams to begin studying, exploring and optimizing designs in the beginning stages of projects—when product geometry is seldom available for 3D CAE, but when informed engineering decision-making can have its strongest impact and leverage on product development outcomes. Then, properly applied, systems modeling tools can help engineering teams maintain visibility and control at the subsystems, systems and whole-product levels as the design evolves through development, integration, optimization and validation.

As part of my ongoing research and reporting intended to help remedy the low awareness and substantial under-utilization of system-level physical modeling software in too many manufacturing industries today, earlier this year I produced a white paper, “System-Level Physical Modeling and Simulation: Strategies for Accelerating the Move to Simulation-Led, Systems-Driven Engineering in Off-Highway Equipment and Mining Machinery.” The project that resulted in this white paper originated during a technology briefing I received in late 2015 from Maplesoft. The company had noticed my commentary in industry and trade publications expressing the views set out above, and approached me to explore what they saw as shared perspectives.

From these discussions, I proposed that Maplesoft commission me to further investigate these issues through primary research among expert practitioners and engineering management, with emphasis on the off-highway equipment and mining machinery industries. In this research, focused not on software-brand-specific factors but instead on industry-wide issues, I interviewed users of a broad range of systems modeling software products including Dassault Systèmes’ Dymola, Maplesoft’s MapleSim, The MathWorks’ Simulink, Siemens PLM’s LMS Imagine.Lab Amesim, and the Modelica tools and libraries from various providers. Interviewees were drawn from manufacturers of off-highway equipment and mining machinery as well as some makers of materials handling machinery.

At the outset, I worked with Maplesoft to define the project methodology. My firm, Ora Research, then executed the interviews, analyzed the findings and developed the white paper independently of input from Maplesoft. That said, I believe the findings of this project strongly support and validate Maplesoft’s vision and strategy for what it calls model-driven innovation. You can download the white paper here.

Bruce Jenkins, Ora Research
oraresearch.com

Bruce Jenkins is President of Ora Research, an engineering research and advisory service. Maplesoft commissioned him to examine how systems-driven engineering practices are being integrated into the early stages of product development, the results of which are available in a free whitepaper entitled System-Level Physical Modeling and Simulation. In the coming weeks, Mr. Jenkins will discuss the results of his research in a series of blog posts.

This is the first entry in the series.

Discussions of how to bring simulation to bear starting in the early stages of product development have become commonplace today. Driving these discussions, I believe, is growing recognition that engineering design in general, and conceptual and preliminary engineering in particular, face unprecedented pressures to move beyond the intuition-based, guess-and-correct methods that have long dominated product development practices in discrete manufacturing. To continue meeting their enterprises’ strategic business imperatives, engineering organizations must move more deeply into applying all the capabilities for systematic, rational, rapid design development, exploration and optimization available from today’s simulation software technologies.

Unfortunately, discussions of how to simulate early still fixate all too often on 3D CAE methods such as finite element analysis and computational fluid dynamics. This reveals a widespread dearth of awareness and understanding—compounded by some fear, intimidation and avoidance—of system-level physical modeling and simulation software. This technology empowers engineers and engineering teams to begin studying, exploring and optimizing designs in the beginning stages of projects—when product geometry is seldom available for 3D CAE, but when informed engineering decision-making can have its strongest impact and leverage on product development outcomes. Then, properly applied, systems modeling tools can help engineering teams maintain visibility and control at the subsystems, systems and whole-product levels as the design evolves through development, integration, optimization and validation.

As part of my ongoing research and reporting intended to help remedy the low awareness and substantial under-utilization of system-level physical modeling software in too many manufacturing industries today, earlier this year I produced a white paper, “System-Level Physical Modeling and Simulation: Strategies for Accelerating the Move to Simulation-Led, Systems-Driven Engineering in Off-Highway Equipment and Mining Machinery.” The project that resulted in this white paper originated during a technology briefing I received in late 2015 from Maplesoft. The company had noticed my commentary in industry and trade publications expressing the views set out above, and approached me to explore what they saw as shared perspectives.

From these discussions, I proposed that Maplesoft commission me to further investigate these issues through primary research among expert practitioners and engineering management, with emphasis on the off-highway equipment and mining machinery industries. In this research, focused not on software-brand-specific factors but instead on industry-wide issues, I interviewed users of a broad range of systems modeling software products including Dassault Systèmes’ Dymola, Maplesoft’s MapleSim, The MathWorks’ Simulink, Siemens PLM’s LMS Imagine.Lab Amesim, and the Modelica tools and libraries from various providers. Interviewees were drawn from manufacturers of off-highway equipment and mining machinery as well as some makers of materials handling machinery.

At the outset, I worked with Maplesoft to define the project methodology. My firm, Ora Research, then executed the interviews, analyzed the findings and developed the white paper independently of input from Maplesoft. That said, I believe the findings of this project strongly support and validate Maplesoft’s vision and strategy for what it calls model-driven innovation. You can download the white paper here.

Bruce Jenkins, Ora Research
oraresearch.com

A more honest and specific version of lemma 3.

CONGRUENT_FUNCTIONS_OF_THE_FRACTIONAL_PART_OVER_Q_LEMMA_4.mw

Maple Worksheet - Error

Failed to load the worksheet /maplenet/convert/CONGRUENT_FUNCTIONS_OF_THE_FRACTIONAL_PART_OVER_Q_LEMMA_4.mw .

Download CONGRUENT_FUNCTIONS_OF_THE_FRACTIONAL_PART_OVER_Q_LEMMA_4.mw

hello i was just looking back on some stuff i did a few months back and although im aware there is a function for generating the prime subset up to a given number already featured in a package in mape im just curious to know how this one measures up in terms of computational efficiency etc.

 

anyway, this is code, if anyone has the time to give it a try and let me know what they think ie faster more logical way about it any feed back is appreciated cheers.

 

restart;
interface(showassumed = 0, rtablesize = infinity);
with(plots); with(numtheory); with(Statistics); with(LinearAlgebra); with(RandomTools); with(codegen, makeproc); with(combinat); with(Maplets[Elements]);
unprotect(real, rational, integer, complex);
alias(P[In] = CurveFitting[PolynomialInterpolation]); alias(L[In] = CurveFitting[LeastSquares]); alias(R[In] = CurveFitting[RationalInterpolation]); alias(S[In] = CurveFitting[Spline]); alias(B[In] = CurveFitting[BSplineCurve]); alias(L[In] = CurveFitting[ThieleInterpolation], rho = frac); alias(`&Nscr;` = Count); alias(`&Dopf;` = numtheory:-divisors); alias(sigma = numtheory:-sigma); alias(`&Fscr;` = ListTools['Flatten']); alias(`&Sopf;` = seq);
delta := proc (x, y) options operator, arrow; piecewise(x = y, 1, x <> y, 0) end proc;
`&Mopf;` := proc (X, Y) options operator, arrow; map(X, Y) end proc;
`&Cscr;`[S, L] := proc (X) options operator, arrow; convert(X, 'list') end proc;
`&Cscr;`[L, S] := proc (X) options operator, arrow; convert(X, 'set') end proc;
`&Popf;` := proc (N) options operator, arrow; `minus`({`&Sopf;`(k*delta(`&Nscr;`(`&Fscr;`(`&Cscr;`[S, L](`&Mopf;`(`&Cscr;`[S, L], `&Mopf;`(`&Dopf;`, `&Dopf;`(k)))))), 3), k = 1 .. N)}, {0}) end proc;
N -> `minus`({(k delta(&Nscr;(&Fscr;(&Cscr;[S, L]((&Cscr;[S, L])

  &Mopf; (&Dopf; &Mopf; (&Dopf;(k)))))), 3)) &Sopf; (k = 1 .. N)},

  {0})
n[P] := proc (N) options operator, arrow; `&Nscr;`(`&Cscr;`[S, L](`&Popf;`(N)))-1 end proc;



Maple Worksheet - Error

Failed to load the worksheet /maplenet/convert/prime_subset_up_to_N.mw .

Download prime_subset_up_to_N.mw

 

Points on the coordinate plane

(Guidance manual for the 6th class)

Changing the initial coordinates and going through the entire program first, we get a new picture-task

 

    Point_on_co-plane.mws

 

And Another     Coordinate_plane.mws

 

 

 

Points on the coordinate plane

(Guidance manual for the 6th class)

Changing the initial coordinates and going through the entire program first, we get a new picture-task

 

    Point_on_co-plane.mws

 

And Another     Coordinate_plane.mws

 

 

 

Coordinate axis

6th class (in Russia)

Guidance manual for use at lessons (at school)

Coordinate_line_lesson.mws

(It is possible bad English)

 

Coordinate axis

6th class (in Russia)

Guidance manual for use at lessons (at school)

Coordinate_line_lesson.mws

(It is possible bad English)

     I want to understand what the forum rules I break? And why do me constantly interferes Markiyan Hirnyk? A recent example: he removed my comments in the subject  http://www.mapleprimes.com/posts/203796-Equidistant-Surface-

At the beginning of the theme I have provided the text of the program, and then gave a description of the algorithm in words. In removed by Hirnyk examples I have quoted only the formula, because the text of the program has not changed.

I have long known Hirnyk for Russian-speaking forums and personal correspondence. Communication with him for a long time I stopped, because it is extremely unpleasant man, and it seems very angry and envious. In addition, the level of competence is very low and is away from the content of my subject. I am convinced of this. I will not say he is constantly trying to harm me on Russian forums.

     ( Хочу понять, какие правила форума я нарушаю? И почему мне постоянно мешает  Markiyan Hirnyk? Из последних примеров: он удалил мои комментарии в теме http://www.mapleprimes.com/posts/203796-Equidistant-Surface-
В начале темы я предоставил текст программы и потом дал описание алгоритма на словах. В удалённых Hirnyk примерах я привел только формулу, потому что текст программы не изменился.  
Я давно знаю  Hirnyk  по русскоязычным форумам и по личной переписке. Общение я с ним давно прекратил, потому что человек он крайне неприятный, и, похоже, очень злой и завистливый. К тому же уровень его  компетенции весьма невысок и находится в стороне от содержания моих тем. Я в этом убеждён. Не буду говорить, как он пытается постоянно вредить мне на русских форумах. ) 

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