Tag Archives: Non-Fiction

by Ben Trube | August 8, 2016 · 12:05 PM

Dispatches from writing a new fractal book

I spent a lot of the weekend making figures. If a picture is worth 1000 words, then my book would be 500,000 words long. There are a lot of things to consider when making an image for a book:

Since this will be a B&W book, what’s the best gray-scale values to look two-tone without looking faded?
What resolution will work best for the print size, but still work for an eBook (so I don’t have to make two of every picture, hopefully)?
How does the image flow with the text? Does it make it hard to read, or does it illuminate a point the text is making?

This last is the primary goal of pictures. Pictures serve two purposes in my book: to show people pretty images, and to show people how to make pretty images. A lot of the heavier math texts I read can still be very informative if they have good illustrations that make it clear what the writer is trying to say. Still, you don’t want to lean on the pictures too heavily, the text still has to make sense.

My early drafting process has been to write the chapter without illustrations. I insert an [ILLUSTRATE] tag into my text where I think an image would/should go, and then I move on. So far this seems to be working okay. I’m remembering from writing the first fractal book that what I think is a clear explanation and image isn’t always what people actually understand, so I may have to try a few different images, and change the text accordingly.

It probably doesn’t make sense to talk this long about pictures without showing you one, so here is a Minkowski sausage:

Neat, huh?

One other weird quirk of the early going is the feeling that I’ve written this all before. In some ways, this fractal book is the culmination of 5-10 years of thinking about fractals, as well as an intense period of six months research. I have run through the progression of thoughts that make up the first chapters dozens of times in my head, and even though this one of the first times I’m committing them to paper in this particular order, it still feels like something I’ve been doing all along. Probably some of that comes from blogging about fractals, that’s really where this recent and previous interest started.

Last thought of the day is a nice little moment at the library. I was checking out yet another fractal reference, and got to talking with the librarian about the new book, and how I got interested in fractals back in the 6th grade EPP program at school (more than 18 years ago now). Turns out, her son had just recently been part of the same program, and had loved fractals and all of the ways you could use them to make math beautiful. It’s for these kinds of kids and curious adults that I’m writing this book, and it was a nice little encouragement to know that they’re still out there.

Have a good week. I’ll check in when I can.

Squirrel Rant: Mathematical Notation

Since this post veers into very inside baseball territory, let’s start with how we got here.

Have you ever had that book that you had to take with you everywhere? It could be the latest exciting story you were reading, or a really handy reference guide, or something with deep sentimental value. Maybe this book has been a passenger in your car; you take it out to lunch even though you know you’re not going to read it while you eat because you might get sauce on the pages. You just want to pick this book up and hold it, flip through the pages, feel the weight of it as you toss it from hand to hand. Maybe you even… smell the pages. That sort of book.

My latest book of this type is “A Perspective in Theoretical Computer Science: Commemorative Volume for Gift Siromoney“:

I know, it’s cliché. Everyone loves this book and has a copy next to their nightstand.

No? Just me, then? Okay.

Why this book is important is that it is the end of a long trail of looking through references in papers, from a stray mention of Kolam patterns in a L-System book by Przemyslaw Prusinkiewicz to the work of Darrah Chavey, Paulus Gerdes, Marcia Ascher and countless others. This book has some of the best grounding in the computer science behind drawing curved line patterns using context-free and array grammars, and contains images from work in the field. It is perfect because it is obscure and exactly the right book at the right time, even though it was written almost 30 years ago.

Which brings me to mathematical notation.

As a fledging programmer one of the first things they teach you is to use meaningful variable names. A variable is an object that holds a value. So if I’m counting oranges, I might have a variable called numOranges. What I wouldn’t have is a variable called ‘o’. ‘o’ could be anything: orangutans, oscilloscopes, Timothy Olyphants, etc.

Math on the other hand tends to use one letter symbols all the time. You’d think this was okay, because the symbols only ever have one meaning. A ‘+’ symbol is a plus symbol. ‘π’ is pi the number.

Except when π is an iteration symbol, or a time stage symbol. And ‘x’ means multiplication, until you graduate to Algebra where a dot is now multiply and x is a variable. And ‘+’ could mean turn right if we’re talking L-systems.

Math papers in general make an assumption about mathematicians that isn’t always correct. It assumes they can write in a way that can be understood. They understand their field technically, but not in common language, or even readable technical language. Now I’m not picking on the Siromoney book too much. The text is very readable. Some of the paper’s problems come from problems in reproduction. Older books like this one had papers submitted physically and then photocopied into a full book. This was done a typewriter or an early word-processor (courier font is kind of a tip off that we’re looking at a typewriter), so some subscripts and superscripts are incorrect, and some symbols have to be hand-drawn after the paper is typed.

The bigger offenders are the ones who use a symbol without any explanation. I remember after staring at it for a few seconds that ∪ means union, but it might be nice to have some handy definitions at the back or in the text. Defining your terms is often a necessary part of making any proof, or explaining any new concept. It never hurts to make sure your audience is on the same page you are. Especially if you plan to have terms mean something other than their common meaning, like ∪ meaning recursive level, or some such.

For a while now, my goal with this new book has been to take complicated concepts and explain them in ways that make sense to everyone. These papers often do the opposite, take something simple and explain it in a complicated way. Fractals actually aren’t that hard to understand. More and more after reading these papers it feels like I’m translating from some arcane and obscure language, with symbols that change in meaning from one place to another.

It’s confusing, and it doesn’t have to be this way. We can be rigorous AND we can be clear. If you can explain a concept to a 6th grader, then you really understand it.

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Tagged as Math, Non-Fiction, Notation, Research, Writing

by Ben Trube | July 5, 2016 · 12:05 PM

On Research: Dive Deep or Swim Around?

I’m not going to lie. I’m not sure how on point this picture is, but I had to post it for the little red-haired girl.

Just a brief thought today:

When writing a book on diverse subjects, should you read all your sources on one topic then move onto the next, or should you cherry-pick and keep bouncing from one topic to another?

I’ve done a little of both for the expanded edition of Fractals You Can Draw, though my inclination is to go for the cherry-picking or “swimming around” approach. I’ve got a few reasons for this:

Keeps each subject fresher – Spending a week or several reading about one subject can be taxing. I inevitably find myself skimming over passages that I then have to re-read. Reading one topic at a time can give you a solid understanding of the subject matter and helps you better understand concepts as they are presented by different authors. But it can also make you feel like you’re reading the same thing over and over.
Helps you to discover interconnected ideas – With a book that is going to be a survey of different topics, it is important to have a through-line that ties everything together. Reading about a new topic each time can help you to see what’s different about each, and what commonalities they share. And you get some of the same benefit as you would when reading different authors on the same subject; you solidify ideas by seeing them presented from different angles.
Each section is better balanced for research and time – I have a source list that’s currently about 150 papers and 20 or so books. I will not have time to read them all, and I’d like each chapter to be well-balanced in terms of the number of authors and sources. I don’t want to rely too heavily on any one author’s perspective. Since I don’t have infinite time I need to make sure I’m actually covering all the areas I want to write about.
Helps you eliminate topics that don’t fit the theme – If you have better sense of what the whole book is shaping up to be, then you can eliminate sources that don’t fit your book. And reading from diverse sources can change your idea of what the book will be. Something that was going to be a chapter in my first outline is now about 30-40% of the final book.
Gives you new ideas for sources – When you see how ideas connect, you’ll discover new angles and areas to research you hadn’t thought of at the beginning. It’s best to find these topics as early as possible so you can get outlines approved by a publisher (if you have one) and so you can make a better writing and research plan.

So what do you do? Do you dive deep, or float around?

On Research: Trimming the Tree

ResearchBranching

I’m heavy in the middle of the research phase for my new book. I’m trying to read at least one academic paper a night with the goal of having roughly 100 sources for the entire book, and at least 5 sources for each chapter. The trouble is, every time I read a new paper I find five more I want to read. When you’re in deep on a subject, you’re eager to drink up all of these connections and new thoughts as much as you can. There are good reasons for this, the more research you do the better the book you’ll eventually write. But I still have to actually write this book.

Outlines

I wrote an outline for the new expanded edition of Fractals You Can Draw before I entered the research phase. It shaped my initial gathering of material and gave me a good sense of the structure of the book and the kinds of topics I wanted to cover. And now several months later I realize it needs revision. I’ve added some topics, dropped others, and overall have a slightly different feel for what the book will be. The structure is the same, but in my research I’ve found myself fascinated by the different cultural expressions of fractals, sort of an abstract versus practical study all with fractals you can draw by hand, and something that was just a chapter in my original outline is now a whole part of the book.

An outline is a great way to shape your vision initially, and it’s a structure you need to continue to revisit as you get more into the execution. It can remind you of areas you still want to cover but haven’t gotten around to, and it can be a way to shape the new thoughts you’ve been having and see if they fit into the book you still want to write. As the outline matures it can be a good measure for judging the effectiveness of reading new material. Is the new material relevant enough to fit into the existing framework, or will it require a restructuring, and is that restructuring valuable? Some things will fit nicely, others won’t fit neatly but might fit the overall shape of the book, and still others might be for another book entirely. An outline can help divide your sources into these piles.

Source Limitations

I have neither unlimited money nor unlimited time. Practically speaking, my research consists of what I can do on my lunch breaks, off times, and evenings at home. Because of this, I’m more biased in favor of electronic sources, though I do have about two-dozen physical books on my source list as well. I can’t afford to pay for access to expensive databases, meaning some papers are just stuck behind a pay-wall.

Other sources are very informative, but a little hard to cite. Lectures from University classes, unattributed papers from supplemental course work, or images of cool designs from Facebook groups. Often these things aren’t great to use directly, but can point you in the direction of more traditional sources.

It can sound like these limitations are frustrating, but there is a lot of knowledge that is freely accessible, certainly more than you’d be able to read anyway. It might not actually add that much value to your book to spend tons of money on research, if the information can be found for free elsewhere. I’d love to be a world traveler, to go to the regions in India I’m reading about, but for now I’m happy to work from the writing of people who have.

Vision

In addition to writing a book with a bunch of cool fractal designs I have three goals for the book as a whole:

Use fractals to introduce other interesting math subjects. Provide a good overview of fractals and math that leads people to want to learn more.
Show how math and fractals are interconnected across culture and technique (math and art as universal languages).
Choose fractals that can be drawn freehand or with minimal tools (compass, ruler).

Some subjects, like how fractals are used in weather prediction or chip design, are interesting to study but not really on the point of this book. At best they might be a few introductory paragraphs or notes here and there. So it doesn’t make sense to read long papers on how Hilbert Curves are used to organize data-clusters in computers unless I really want to talk about those subjects (which I don’t for this book at least).

Having a good sense of vision can eliminate the temptation for tangents, or for a knowledge dump. You’ll never be able to cover everything, and dropping in a bunch of the random trivia you’ve learned doesn’t make for particularly compelling reading. It’s better to try to say one thing well, than a dozen things poorly. Most academic papers have abstracts or intros that tell you what they’re going to be. If from the intro it doesn’t sound like the paper will contribute much to vision, it’s best to save it for another time.

These are just some of things I’m learning while putting together this book. What else have you learned from long term research projects?