Processing, Programming

Cantor’s Snowflake

The Koch snowflake is a famous fractal.

The Koch Snowflake fractal

So is the Cantor set.

The Cantor set

Less famous, maybe, is Cantor dust, a version of the Cantor set made with squares instead of lines, which apparently earned it a much cooler name.

But as far as I know, we have no Cantor snowflake.

Since it’s Christmas, and since, in the odd quiet moments between holiday noise, Daniel Shiffman’s Nature of Code has been keeping me company, I wondered if we could make a Cantor snowflake.

Here’s what I came up with.

cantor-snowflake

As a bonus, it contains the Koch snowflake inside of it! I didn’t expect that.

I also rendered a Cantor snowflake PDF, which has a couple extra generations. It could make a nice bookmark.

Here’s the sourcecode, which is also running on openprocessing:

void setup() {
  size(1450, 300);

  background(255);
  noStroke();
  fill(0);

  cantorSnowflake(0, height/2, 140, 280);
}

void cantorSnowflake(float x, float y, float length, float sideStep) {
  if (length < 0.1) return;

  pushMatrix();

  hexagon(x, y, length);

  translate(sideStep, 0);

  for (int i = 0; i < 6; i++) {
    PVector point = vector(i * THIRD_PI, length * 2 / 3);
    cantorSnowflake(point.x, point.y, length / 3, sideStep);
  }

  popMatrix();
}

void hexagon(float centerX, float centerY, float length) {
  translate(centerX, centerY);

  beginShape();
  for (int i = 0; i < 6; i++) {
    hexPoint(vector(i * THIRD_PI, length));
  }
  endShape(CLOSE);
}

void hexPoint(PVector v) {
  vertex(v.x, v.y);
}

PVector vector(float rads, float length) {
  return new PVector(cos(rads) * length, sin(rads) * length);
}

Happy Christmas!

Standard
Programming

ERMAHGERD, the Gem

I just published my first “official” gem, ermahgerd, and what an auspicious way start my gem-author career! ERMAHGERD, I’M A RERL RERBER PRERGRERMAHR!

It’s (currently) totally based on J Miller Design’s translator, but there are some bits I’d like to tweak. We’ll see, it’s just for fun.

Get started with ERMAHGERD:

$ gem install ermahgerd
$ irb
ruby-1.9.3-p0 :001 > require 'ermahgerd'
 => true 
ruby-1.9.3-p0 :002 > Ermahgerd.translate("Goosebumps, my favorite books!")
 => "GERSBERMS, MAH FRAVRIT BERKS!" 
Standard
Programming

Rails 3: Selectively Override Email Recipients

It’s a common thing, in your test environments, to intercept out-going email, and stuff it in some dumpster out back, so you don’t bother your users. We do this at SeeClickFix, and we’re upgrading to Rails 3, so I went searching for the new way to do this, and found Rob Aldred’s handy post on the subject.

So we deployed our Rails 3 branch to a test environment & unleashed our QA staff on it, but they all knew that they’d never get email from that environment, so they never checked for them. Which was a problem, because all the email were broken in QA. Oops.

It’d be nice to only dump certain messages (the ones to your normal users) and let through others (the ones to your QA staff). Can we do this? Let’s see.

ActionMailer::Base lets you register an interceptor, and every time it’s about to send an email, it’ll call your interceptor’s #delivering_email method with the email as an argument. All the examples I found register a class as an interceptor, with #delivering_email implemented as a class method, like this:

class FooInterceptor
  def self.delivering_email(message)
    message.to = "dump@example.com"
  end
end

ActionMailer::Base.register_interceptor(FooInterceptor)

Now that’s fine, but why pass a class with a class method? Why not an object with an instance method? Especially since a class is just an object, an instance of Class. Will ActionMailer::Base#register_interceptor do something funny with its argument? Try to call #new on it? Who knows?

I tried this just to see if it would work:

class FooBarRecipient
  def delivering_email(message)
    message.to = "dump@example.com"
  end
end

ActionMailer::Base.register_interceptor(FooBarRecipient.new)

And it does! Nice job, register_interceptor, not doing anything funky with it. Thanks!

This means we can create an interceptor object with a whitelist:

class WhitelistInterceptor

  def initialize(whitelist)
    @whitelist = whitelist
  end

  def delivering_email(message)
    message.to = Array(message.to).map { |address|
      if @whitelist.include?(address)
        address
      else
        "dump@example.com"
      end
    }
  end

end

Of course that’s really basic – you probably want to allow all email sent to your domain, for instance. And maybe you want the messages to be tagged somehow, so you can tell which test environment a message came from, so you give the WhitelistInterceptor the Rails environment to add as a message header. But that’s the idea. And my favorite part is that the class has no Rails dependencies, so it’s trivial to test.

Is there any reason not to do this?

Standard
Functional Programming

Disable Your Links, or Gate Your Functions?

It’s pretty common to disable links and buttons that cause updates, so those updates don’t happen twice, and re-enable them when the update has finished.

At work, our app’s links are usually wired to javascript functions that use jQuery to scrape the form data and post it to web services via ajax. We normally disable links and buttons something like this:

var updateLink = $('#updateLink');  // Find the link.
updateLink.click(function() {       // When it's clicked...
   updateLink.disable();            // disable it...
   ajax({
      data: getFormData(),          // ... & send the form data
      url: 'http://someWebService', // to some web service.
      success: function(results) {  // When the service
         if (results.hasErrors) {   // finishes,
            showErrors(results);    // show any errors,
            updateLink.enable();    // and enable the link
         }                          // so they can try again.
      }
   });
});

We added those enable() and disable() functions to jQuery — they just add or remove the disabled attribute from whatever they’re called on. But it seems Firefox doesn’t support disabled on anchor tags, like IE8 does, so we couldn’t stop the repeat-calls that way.

We got to thinking, what if the link always called its javascript function, but the function could turn itself off after the first call, and back on after a successful ajax post? That led to this:

function makeGated(fn) {
   var open = true;
   var gate = {
      open: function() { open = true; }
      shut: function() { open = false; }
   };

   return function() {
      if (open) {
         fn(gate);
      }
   };
}

makeGated takes your function, and wraps it in another function, a gate function (it “makes your function a gated function”). When you call the function it creates, it will only call your function if the gate is open — which it is, at first. But then, your function can decide whether to close the gate (that’s why the gate is passed to your function). You could use it like this:

var updateLink = $('#updateLink');  // Find the link.
updateLink.click(
   makeGated(function(gate) {       // When it's clicked...
      gate.shut();                  // shut the gate...
      ajax({
         data: getFormData(),       // ...same as before...
         url: 'http://someWebService',
         success: function(results) {
            if (results.hasErrors) {
               showErrors(results);
               gate.open();  // Open the gate
                             // so they can try again.
            }
         }
      });
   }));

We dropped this in, and it worked pretty much as expected: you can click all you want, and the update will only fire once; when the update completes, it’ll turn back on.

The downside? Since it doesn’t disable the link, the user has no idea what’s going on. In fact, since the closed-gate function finishes so quickly, it seems like the button’s not doing anything at all, which might even make it look broken.

So we chucked it, and hid the links instead. It’s not as nifty, and it’s not reusable, but it’s clear enough for both end-users and programmers who don’t grok higher-order functions. Even when you have a nice, flexible language, and can make a sweet little hack, it doesn’t mean the dumb approach won’t sometimes win out.

Standard
Programming

Array.prototype.toString

This is one of my favorite javascript tricks, because of its effort-to-payoff ratio.

Problem: the default Array.prototype.toString hides any nested structure.

[1, 2, 3, 4, 5].toString(); //-> "1, 2, 3, 4, 5"
[1, 2, [3, 4], 5].toString(); //-> "1, 2, 3, 4, 5"

Solution: override Array.prototype.toString.

Array.prototype.toString = function() {
    return '[' + this.join(', ') + ']';
};

[1, 2, 3, 4, 5].toString(); //-> "[1, 2, 3, 4, 5]"
[1, 2, [3, 4], 5].toString(); //-> "[1, 2, [3, 4], 5]"
Standard
Tools

Firebug and Monaco, on Windows

I’ve been running Firebug at work for a long time, it’s a really solid tool. A while ago, I started using a Monaco.ttf for Windows. I think it looks much better on my Ubuntu system, but it’s nice to have on Vista.

Firebug was apparently written for the Mac, because it uses Monaco all over the place. That would be very nice, but on Windows, a bold Monaco is a wider Monaco.  This makes the line number gutters uneven, and makes the screen flash when you scroll through text:

I finally got irritated enough to google it, and I found this post by Thomas Scholz (it’s in German, here’s Google’s translation).

The details: Firebug’s CSS files are located in its extension directory, which is probably someplace like this:

  • Vista: C:\Users\{USERNAME}\AppData\Roaming\Mozilla\Firefox\Profiles\{alphanumerics}.default\extensions\firebug@software.joehewitt.com\skin\classic
  • XP: C:\Documents and Settings\{USERNAME}\Application Data\Mozilla Firefox\Profiles\extensions\firebug@software.joehewitt.com\skin\classic

Search-and-replace the Monaco away, and restart Firefox.

Standard
Functional Programming, Programming

Clojure Changing My Mind

As good as Processing is, it’s still java. I’ve slowly been learning clojure, and trying to use it with Processing, via clj-processing. While the clojure docs and the book are both good, I’m still in that flounder-around stage, trying out tiny experiments to understand how things work.

I wanted a function to make saw-step sequences: (1 2 3 2 1 2 3 2 …). You give it the low bound, the high bound, and the step-size. For example:

  • (saw-step 1 4 1) gives (1 2 3 4 3 2 1 2 3 4 3 ...)
  • (saw-step 0 15 5) gives (0 5 10 15 10 5 0 5 ...)
  • (saw-step 0 5 2) gives (0 2 4 5 3 1 0 2 4 5 ...)

I’ve coded this kind of thing up in ruby, javascript, or java a dozen times, though it’s usually inside a loop, not returning a list. Something like this:

var min = 3;
var max = 7;
var step = 2;

var n = min;
while(shouldContinue()) {
    doSomethingWith(n);
    n += step;
    if (n+step > max || n-step < min) {
        step *= -1;  // turn around
    }
}

My first try in clojure took a similar tack. I never got it right, but it was something like this:

(defn saw-step
  [min max step-size]
    (let [step (ref step-size)]
      (iterate
       (fn [x]
         (if (or ( min (- x @step)))
           (dosync (alter step -)))
         (+ @step x))
         min)))

It’s a disaster — the parentheses don’t even match — but you get the gist. I was trying to cram the same imperative algorithm into clojure: keep some mutable state, add step to it, and when you reach the edges, mutate step to change direction. I kept getting bugs where it would go one step beyond the edge, or it would start working its way back from one edge, only to turn around again, and bounce against the edge forever.

I gave up and went to bed, but a few days later, I had better luck.

(defn saw-step
  [min max step]
     (cycle
      (into (vec (range min max step)) ; vec, so (into) adds to end
	    (for [x
		  (iterate #(- % step) max)
		  :while (> x min)] x))))

The first not-entirely-wrong step I made was to try breaking the list of numbers I wanted into two parts: the going-up numbers, and the coming-down numbers. (0 2 4 5 3 1) is just (0 2 4) + (5 3 1). The (range min max step) part gives you the going-ups, and the (for [x (iterate ...) stuff is the going-downs, as a list comprehension.

(One mistake I made was trying (range max min step) for the going-downs, which yields an empty list; another was using (iterate dec max), which never ends, because it keeps decrementing into the negatives. I found my way out with the list comprehension, but I bet there’s a better way.)

Once you have those two lists, you can use into to add each item from the second list to the first, giving you (0 2 4 5 3 1). That goes into cycle for a lazy, infinite sequence.

The solution’s not too bad: a saw-step is a cycle of the going-ups, followed by the going-downs. The code looks about that way.

(It occurred to me after that I could always use a default step of 1, and pipe the result through a scaling map. That would give me the bounds I wanted, with the extra benefit of evenly-spaced steps. Maybe I’ll remove step later.)

Alan Perlis said, “A language that doesn’t affect the way you think about programming, is not worth knowing.” He also said, “The only difference(!) between Shakespeare and you was the size of his idiom list – not the size of his vocabulary.”  Clojure’s changing my mind, a bit at a time.

Standard
Functional Programming, Programming

A JavaScript War Story

What follows is an account from the author’s experience. Some details have been changed for the usual reasons, and a poor memory has fuzzed out the rest.

UPDATE: it turns out the technique described below is known as debouncing. What an awesome name!

My last job was for a company that made case-management software. With this software, you could track all kinds of data about your case: you could categorize it, sub-categorize it, say where and when it happened, note whether it was still open, track who was responsible…all kinds of stuff, great for data fiends.

One of our customers’ favorite features was the reports, and they were pretty spiffin’. But, not being ones to rest on our laurels, we were adding pivot-table reports, so you could count the number of cases, grouped by any criteria you wanted. The input screen let the customer pick their pivot criterion, and which criteria they wanted as columns, for sub-counts. We struggled to name these UI fields — something lucid, something explanatory, something evocative — something to make them understand what kind of report they were in for. After a while, we decided to just show them: when they changed their pivot criterion, we’d run some javascript to render a skeleton report, same as the real report, but minus the data. It would save them time, and save our servers.

The javascript was pretty involved. It had to generate the same HTML as we did for the pivot table, which meant it had to know (or make up) values for each criterion, like all the case categories and sub-categories, and which sub-categories belonged to which categories. And we let the customers pivot on up to THREE, count ‘em, different criteria. And it had to happen each time the user picked different pivot criteria. It took a few tricks, but we got it working. It ran slowly, maybe a few seconds, but it was quick enough, probably, especially once we threw in a little “please wait” spinner. Then we realized we needed to re-render whenever the window resized.

No biggie, I thought, and I quickly added window.onResize(reportPreview);. It worked great, except it re-rendered the report with every pixel-wide movement of the mouse, as the window was dragged to new widths and heights. Calling a function, one that runs for a few seconds, a hundred times in the time it took to widen the browser an inch, meant a locked browser. It meant “time to get more coffee,” and after, “time to fix the bug.”

I knew we could delay calling reportPreview, but we only wanted to delay it when the window was being resized — when the user changed the columns, there was no reason to wait. I was sure window.setTimeout() would do what we needed, but I didn’t want to muck up reportPreview() with it.

I’d been reading The Little Schemer lately, and noticing some striking similarities between javascript and scheme: first-class functions, and higher-order functions that take functions as arguments, and return other functions as values. It was fun reading, with its strange teacher-student dialog style. The material was better than brainteasers, and I knew it would make me a better programmer down the road, but I didn’t think of it as relevant to the day-job, as…applicable.

Then I realized higher-order functions were a way out of this. I could write a function, delay, that would wrap one long-running, slow-poke function in another function: an intermediary that you could call as many times a second as you wanted, but it would only call the slow-poke once things had settled down. delay would let us keep setTimeout out of reportPreview. Something like this:

function delay(millis, slowPoke) {
    var timeoutId = undefined;

    // This is the intermediary.  Call it lots, it won't hurt.
    return function() {
        if (timeoutId) {  // If we're waiting...
            clearTimeout(timeoutId); // re-start the clock.
        }
        timeoutId = window.setTimeout(slowPoke, millis);
    }
}

The first time you call the intermediary, it tells the window to call slowPoke after a bit, but every time you call it after that, it starts the clock over. It’s like when you’re in a five-minute time-out, and you start acting up after only three, so your mom says “Ok, buster, another five minutes.”

var fiveMinutes = 5 * 60 * 1000;
var screamAndShout = delay(fiveMinutes, function() {
    getBackToPlaying();
});

screamAndShout(); // Aw nuts, I'm in time-out.

// I'll be good for as long as I can, but...
screamAndShout(); // dang, five MORE minutes!

Once delay was in place, running reportPreview when the window was resized was no problem.

function reportPreview() {
    // recursion, DOM manipulation, insanity...
}
columnPicker.onChange(reportPreview);
window.onResize(delay(100, reportPreview));

After testing, we found that delaying it for 100 milliseconds made all the difference in the world.

Do you have a war story? Share it, and start the healing: tell a short one in the comments, or link to a longer one on your own damn blog.

Standard
Functional Programming, Programming

Higher-Order Functions and Function Composition, with Processing

I was looking for a good way to illustrate functional composition and higher order functions, and thought that something could be done with Processing, a java-based graphics tool. Among other things, Processing exposes raw pixel data for the images it renders, and you can update the pixels programatically, providing a simple kind of image filtering.

For example, here’s some code that converts a color image to grayscale. Just like with HTML, colors are represented1 as 3 channels (red, green, blue), and each channel has 255 increments. A gray pixel has equal amounts of red, green, and blue, so if you get the overall brightness of a pixel, and set its color to that much red, green, and blue, it should turn the image gray.

PImage img = loadImage("tattoo.jpg");
size(img.width, img.height);  // set the window size
image(img, 0, 0);  // render the image at x:y = 0:0

loadPixels(); // load the image's pixels into an array
for (int i = 0; i < pixels.length; i++) {
    // get the color for this pixel
    color c = pixels[i];

    // get its brightness
    float bright = brightness(c);

    // Change its color to its grayscale equivalent
    pixels[i] = color(bright, bright, bright);
}
updatePixels();  // render the new pixels to the screen

Here’s the original image:

the original image

…and here’s the filtered version:

the image in grayscale

You can define a bunch of routines like this, each looping through the pixels the same way, but adjusting the colors differently. But if you can separate the pixel-changing part from the pixel-looping part, then you can swap in ANY pixel-changing routine, giving you a flexible image filtering system.

The pixel-changing code is essentially a function that turns one pixel’s color into a new color, and the pixel-looping code uses it to replace each pixel’s original color. The pixel-changing function could be described like this:

color transform(color c) {
    ...
}

Many modern programming languages support first-class functions, which are a natural way to model this. Processing uses a form of Java, which doesn’t have first-class functions, but we can wrap the functions in a class, giving us an object called a functor. I called this one ColorTrans, for “color transformer”.

abstract class ColorTrans {
    public abstract color transform(color c);
}

The ColorTrans class’ only method, transform, is our pixel-changing function. We can re-write the loop from before to use a ColorTrans filter, and while we’re at it, we’ll move it into a method that takes the filename as a parameter, too.

void filterImage(String path, ColorTrans filter) {
    PImage img = loadImage(path);
    size(img.width, img.height);
    image(img, 0, 0);

    loadPixels();
    for (int i = 0; i < pixels.length; i++) {
        // use the filter parameter
        pixels[i] = filter.transform(pixels[i]);
    }
    updatePixels();
}

We can easily recreate the grayscale filter from earlier as a ColorTrans.

ColorTrans grayscale = new ColorTrans() {
    color transform(color c) {
        float bright = brightness(c);
        return color(bright, bright, bright);
    }
};

filterImage("tattoo.jpg", grayscale);

Another really easy filter to write is an inverter. If a pixel has R:100, G:30, B:255, an inverter will return the color R:(255-100), G:(255-30), B:(255-255), or R:155, G:225, B:0.

ColorTrans invert = new ColorTrans() {
    color transform(color c) {
        return color(255 - red(c),
                     255 - green(c),
                     255 - blue(c));
    }
};

filterImage("tattoo.jpg", invert);

The image produced by an inverter is like a film negative.

inverted, like a negative

Now we begin to see the benefits of keeping the-parts-that-change separate from the-parts-that-don’t: we can easily define and swap in new filters. This is one of the big parts of higher-order programming: writing routines that are configured by passing in functions (or functors, in this case) to do part of the work.

Manufacturing a ColorTrans

A useful kind of filter is one that increases (or decreases) the color on one channel: add some red, or remove some green. This kind of filter is easy to create:

ColorTrans aFifthMoreRed = new ColorTrans() {
    color transform(color c) {
    	return color(red(c) * 1.2, green(c), blue(c));
    }
};

This filter will increase the amout of red in the image by 20%. But 20% is a pretty arbitrary number; it’d be better if we could tell the filter how much to increase the red by. Generally, you’d add an “amount” parameter to the transform method, but then filterImage would have to know that this ColorTrans object takes an extra parameter. It’s kind of nice having filterImage treat all ColorTrans objects the same, just passing in the color.

Instead, we can make a method that builds ColorTrans objects: we tell it how much to increase the red by, and it builds a ColorTrans that does it for us.

ColorTrans ampRed(final float amount) {
    return new ColorTrans() {
        color transform(color c) {
            color(red(c) * amount, green(c), blue(c));
        }
    };
}

ColorTrans aQuarterMoreRed = ampRed(1.25);
ColorTrans aThirdLessRed = ampRed(2/3);
ColorTrans noRedAtAll = ampRed(0);

(If you’re curious why amount is final, the short answer is “because the compiler says so,” but there’s a better answer2.)

This is pretty nice, because we can use this inside an animation loop, animating the amount of color amplification.

float theta = 0.0;

void setup() {
    filterImage("tattoo.jpg", noChange);
}

void draw() {
    float ampRedAmount = sin(theta) * 1.2;
    filterImage("tattoo.jpg", ampRed(ampRedAmount));
    theta += 0.1;
}

[Here's where I'd link to the applet, nicely hosted somewhere, if I had a hosting service that allowed applets. I'll try to find a place to put all the code, so you can try it yourself.]

Processing calls setup to initialize the animation, and calls draw once per “tick”, to advance the animation. Here, in each frame of the animation, a new ColorTrans is constructed by ampRed, with the amount tied to the sine wave function, oscillating between 0 and 1.2. When viewed, the amount of red in the image swells and falls, and back again3.

This is another big part of higher-order programming: writing functions that build other functions, based on some arguments. Combined with routines that take functions as arguments, it’s a handy way to break down some problems. If done well, the routines that take functions as arguments, and the functions that build those functions, can become a sort of mini-language, a fluent interface, or almost an embedded DSL.

Plugging filters together – filter composition

This is where it gets fun. Suppose you’ve created an ampBlue that works just like ampRed, and now you want to filter an image with both of them. One approach might be something like this:

void draw() {
    filterImage("tattoo.jpg", ampRed(sin(theta) * 1.2));
    filterImage("tattoo.jpg", ampBlue(cos(theta) * 1.2));
}

Using the sine and cosine functions, the image should pulse nicely through reds and blues. The only problem is that it doesn’t really work, because filterImage loads the image fresh from the filesystem each time, so you only get the effect of the ampBlue filter. So how can we apply multiple filters?

We plug them together. We want a filter that does the work of two other filters, and we want it to look like any other filter, so filterImage won’t know the difference. To get this, we can add a method to ColorTrans that returns a new ColorTrans, which calls first the one, and then the other.

class ColorTrans {
    ...
    public ColorTrans then(final ColorTrans applySecond) {
        final ColorTrans applyFirst = this;
        return new ColorTrans() {
	    color transform(color c) {
	        return applySecond(applyFirst(c));
	    }
	};
    }
}

filterImage("tattoo.jpg", grayscale.then(invert));

first grayscaled, then inverted

Combining filters becomes a matter of chaining them together through then. The red-and-blue example becomes:

void draw() {
   filterImage("tattoo.jpg",
        ampRed(sin(theta) * 1.2).then(
            ampBlue(cos(theta) * 1.2)));
}

Processing does it kind of this way, too

If you look at the source for Processing, in PImage.java on line 619, you’ll find code that looks kind of like this:

  public void filter(int kind) {
    loadPixels();

    switch (kind) {
      case BLUR: ...
      case GRAY: ...
      case INVERT: ...
      case POSTERIZE: ...
      case RGB: ...
      case THRESHOLD: ...
      case ERODE: ...
      case DILATE: ...
    }
    updatePixels();  // mark as modified
  }

It basically does just what I’ve been doing, except the operations are hard-coded into the source, rather than being separated behind a class interface. The filters aren’t composable directly, though you can call a number of them in a row:

filter(INVERT);
filter(THRESHOLD);
filter(DILATE);

One benefit of this approach is that it’s easy to see, line-by-line, exactly what’s happening. I’d bet it beats the pants off of the ColorTrans version in benchmarks, too. But filters aren’t composeable, and it’s certainly not extendable. When you’re doing computation-intensive graphics, every bit of speed is important; when you’re illustrating a programming idea, it’s not. Decide for yourself which is more important for your needs.

____________________________________


1. It may seem weird, if you know Java, that the parameter’s type is color — it’s not a java primitive, but it doesn’t follow the normal classname conventions. It’s just the way Processing does it. You can read more about the color constructor in the Processing reference. [back]


2. Taken from the AnonymousInnerClasses page on the Portland Patterns Repository, 2009-04-30:

AnonymousInnerClasses can also be used to create something like closures in the JavaLanguage. However they do not “close over” the lexical environment so they aren’t TrueClosures. (They can capture the value of local variables, but they do not have access to the variable binding so they can’t change the original variable. Which Java makes quite clear by only allowing InnerClasses to refer to local variables that have been declared final (so no-one can change them)).

[back]


3. The noChange filter returns the same color it was given — an identity function. filterImage is called inside setup only so the window size is set correctly, since setting the size inside draw has no effect. And theta is just a Greek letter often used for angles and trigonometry.[back]

Standard
Functional Programming, Learning, Programming, Software Thinking

Heading to the Int’l Lisp Conf, 2009

My next step on the road to lisp is at the International Lisp Conference in Cambridge, MA, this March.

A lot of people are surprised to hear I’m interested in Lisp, but I’ve been studying scheme informally for about 3 years, reading SICP, and finishing The Little Schemer last year. I’ve been interested in clojure for about 18 months, especially after seeing Rich Hickey talk about it last March.  Now I’m studying it in earnest with Stu Halloway’s Programming Clojure.

I don’t use lisps of any sort at work, so it’s not a “practical” language to study like, say, C# is.  But that’s short-term thinking.  Learning lisp is plenty practical, if you’re looking longer-term — even if it’s only three years out.  Learning lisp teaches you about some of the core issues of programming.

I like learning lisp because it’s a window into the workings of programming languages, being so close to the AST.  I want to learn more about meta-programming with macros, hygienic or not.

And for the record, the functional techniques in The Little Schemer have improved my Ruby, JavaScript, and C# in some really solid ways. Functional programming is making its way to the rest of the programming world, and lisp does functional programming.

If you’ll be at the conference, I’d love to hear from you.

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