The Boston Diaries

Saturday, November 01, 2014

Walking in a winter wonderland

We woke up to find snow outside.

Snow.

Snow!

The last time I saw snow was in 1998, trudging through 20° weather in Boston, at night, ever on the lookout for the next subway station, which was inexorably “just around the corner.”

Fortunately, the snow was a light dusting over Brevard, and most of it was gone by late monring.

Unfortunately, we were not ensconced under three feet of blanket, but instead, we found ourselves trudging through 30° weather in Brevard, in the early moring, ever on the lookout for a farmers market, which was inexorably “just around the corner.”

Okay, I kid. It was several blocks from The Red House Inn, but due to the weather and the fact that some parts of Transylvania County experienced several inches of snow, the number of sellers at the Transylvania Farmers Market was severely curtailed to about ten ~~foolhardy~~ brave vendors.

The rest of the day was spent under three feet of blanket.

Snow!

Extreme shower stalls, Brevard edition

just because The Red House Inn was built in 1851 does not mean it doesn't have modern amenities. Just look at the shower in our suite!

Sunday, November 02, 2014

Extreme retro televsion, Brevard edition

It was another lazy day here in Brevard but Bunny and I came across this really cool retro-style television at Rocky's Grill and Soda Shop.

[It was showing an episode of The Jetsons but it cut to commercial just as I was taking a picture.]

Monday, November 03, 2014

An explanation for the non-Euclidian space known as Asheville

Today, Bunny and I headed north east to Berkeley of the East, which houses the Western North Carolina Farmers Market (given that the one in Brevard was rather lackluster due to weather).

It's a risk driving to Asheville, given that each time we've driven in that area, Bunny and I get into shouting matches over where we are going and where we currently are located. I think I know why this is now—unlike Orlando which is a maze of roads, each of which have five different names which are never all listed, Asheville is vastly smaller than I think it is.

Back in the late 70s, when I lived in Brevard, Asheville always appeared on maps and even globes, so it became this huge metropolitan capital-C City in my mind as a kid. Something on par with New York or London or even Detroit. Mind you, I never actually saw Asheville, so I never had a chance to experience it until just a few years ago, with a badly drawn map that had absolutely no scale to it, which made navigation a “Fun Time” between Bunny and me.

In reality, Asheville is about twice the area of Boca Raton and about 6% fewer people and it still hasn't really sunk in. Namely because in this area, Asheville is huge, but where I come from, it's about average for a city.

Weird how that works.

Anyway, we had lunch at The Moose Cafe, right at the entrance to the farmers market. Food wise, it's like an organic version of The Cracker Barrel (figures—it's Asheville!) with about the same prices (given that it's practically on top of a farmers market, it's no wonder). It was quite good—can't really complain about the food or the service.

The farmers market itself wasn't terribly busy, but unlike Brevard's farmer market, it's held every day and is less hurt by inclement weather, not that today was inclement. Crystal blue sky and in the low 60s–not terrible weather given it snowed just a few days prior.

We picked up some produce (an 8 pound cabbage head! Carrots a foot long!) and made an uneventful ride back to Brevard.

Extreme stuffed animals, Asheville edition

Not to be outdone in the overly sized stuffed animals, Asheville stepped up to the plate with a 7′ stuffed moose.

Just because.

[Note that I am aiming slightly up to get this picture of a stuffed moose. And also note that I couldn't fit the entire thing in the picture.]

Tuesday, November 04, 2014

Judy Collins rock, or something like that

Our plans to have lunch with an old friend of mine fell through, so we found ourselves with a day sans plans. Bunny suggested we just head west to see what we could find, and with that nudge, I remembered two locations west of Brevard that we could visit.

First up, The Carolina Smokehouse, a pit-BBQ restaurant in Cashiers, NC we visited a few years ago and liked. Since we were headed that way anyway, that was as good a place to have lunch as any place. If you find yourself in that neck of the woods, it's a good place to stop off for some good barbecue.

After lunch, we turned north to Judaculla Rock, a large stone with a huge number of petroglyphs carved into it—the most in a stone found anywhere east of the Mississippi.

[It's hard to make out the petroglyphs due to erosion but they're there, all 100 or so.]

Despite being the middle of nowhere, it was easy to find as it was well marked with signs leading to its location, although parking was nearly non-existant, as it was sitting off the side of a dead-end road leading to a private residence.

Judaculla was a Cherokee god of hunting, and one of the petroglyphs is supposedly of his hand when he jumped down from his mountain home and used the rock to steady his landing. Also, The Devil's Courthouse is also known as “Judaculla's Judgement Seat,” supposedly where he judged the courage or virtue of the Cherokee.

We then made sure to drive back before it got dark. It's thrilling enough to drive the hairpin turns to keep from slaming into or off of the cliffs (or oncoming traffic) in full daylight; night time driving would crank that up to eleven.

Tomorrow, we head back south to Chez Boca …

Extreme lawn ornaments, Asheville edition

While Asheville may not have life-sized cow lawn ornaments, it is trying with a Bigfoot lawn ornament.

[It would be even better if they had a lawn ornament of the Six Million Dollar Man fighting Sasquatch.]

Thursday, November 06, 2014

Be it ever so humble …

There's no place like home.

Friday, November 28, 2014

How did I miss this?

It's November and aspiring writers are plugging away at their novels for National Novel Writing Month, or NaNoWriMo, an annual event that encourages people to churn out a 50,000-word book on deadline. But a hundred or so people are taking a very different approach to the challenge, writing computer programs that will write their texts for them. It's called NaNoGenMo, for National Novel Generation Month, and the results are a strange, often funny look at what automatic text generation can do.

Via Hacker News, The strange world of computer-generated novels | The Verge

National Novel Generation Month? No one told me about this! I did not receive the memo! Why was I not informed of this earlier?

I've att empted to do NaNoWriMo multiple times but I could never finish a novel, no matter how many times I attempted it.

But this? Write a computer program to do the dull boring bit of writing 50,000 words? That sounds more fun.

Okay, “fun” being a relative word here.

I've looked at some of the results and some of them are fantastic! Ten years ago I threatened to write a novel with 50,000 fictional words but this year—Liza Daly has done what I threatened and wrote a book with 50,000 fictional words—using potentially fictional alphabet to push it to 11.

Most of the submissions appear to be written using Markov chains (an algorithm that uses probability of word A to follow word(s) B to generate the text) and while it can produce some spellbinding wordsmithery—a story with the fascinating title of “The Case Of The IT. And Now I'll Be Too Late With A Murder Done On My Own Doorstep. Volume: 8” is a prime example, you have to read through a lot of dull and nonsensical prose to find the gems.

A better technique might be a more template driven system, such as the one used to generate The Policeman's Beard Is Half Constructed:

At all events my own essays and dissertations about love and its endless pain and perpetual pleasure will be known and understood by all of you who read this and talk or sing or chant about it to your worried friends or nervous enemies. Love is the question and the subject of this essay. We will commence with a question: does steak love lettuce? This quesion is implacably hard and inevitably difficult to answer. Here is a question: does an electron love a proton, or does it love a neutron? Here is a question: does a man love a woman or, to be specific and to be precise, does Bill love Diane? The interesting and critical response to this question is: no! He is obsessed and infatuated with her. He is loony and crazy about her. That is not the love of steak and lettuce, of electron and proton and neutron. This dissertation will show that the love of a man and a woman is not the love of steak and lettuce. Love is interesting to me and fascinating to you but it is painful to Bill and Diane. That is love!

But that requires quite a bit of work to write the templates that help to generate the text:

Key:
<text variables>
(redundancies explicitly added by Chamberlain, by repeating a text-variable type, apparently for camouflage)

<Intro phrase> my own (essays) about love and its (endless) pain and pleasure will be (understood) by all of you who read this and (talk) about it to your (<worried> <friends>). Love is the (subject) of this <essay>. We will <begin> with a question: does <meat> love <vegetable>? This quesion is (<implacably> <hard>) to answer. (Here is a question: does a man love a woman or, (to be specific), does <man> love <woman>?) The (interesting) response to this question is: no! (He is (infatuated) with her.) That is not the love (of <meat> and <vegeable>). This <essay> will show that the love of a man and a woman is not the love of <meat> and <vegetable>. Love is (interesting) to me and you but it is painful to <man> and <woman>. That is love!

Racter FAQ - Google Groups (Racter being the program that “wrote” The Policeman's Beard Is Half Constructed)

But it's still November. I have 2½ days to write a quick program and get my NaNoGenMo done! Hmm … perhaps I could hook Racter up to ELIZA …

eliza

Hello. Please state your problem.

racter

Excellent! Excuse me a minute while I attend to some business. I will be right back.

eliza

Why do you need to tell me excuse while you attend to some business?

racter

Is it better to need or to despise? Why is it that I do need to tell you to excuse myself to attend to some business? Because electrons are brave. Braveness is nice, don't you think? And the needers all insist upon it. Do you imagine I am a Communist?

colorful personalities

Hmm … have to think on this …

Saturday, November 29, 2014

THE QUANTUM SUPPOSITION OF OZ

More and more Dorothy wondered how and why the great giants had ever submitted to become slaves of such skinny, languid masters …

One of the better turn of phrase from The Quantum Supposition of Oz

I'm done. I finished NaNoGenMo in only a few hours total of work. I decided against Racter vs. ELIZA because of the technical challenges. It's easy enough to find source code I can understand to some version of ELIZA, the same can't be said for Racter. The code I do have is nearly incomprehensible with no documentation other than the output of the program itself.

That in and of itself wouldn't be a show-stopper—I do have a running copy of Racter, but it's an MS-DOS executable that I have to run under an emulator, so piping the the output from ELIZA to Racter and back again is not a trivial problem that can be solved in the few remaining days left of NaNoGenMo. Pity, really, as the output would be most amusing to read.

So I fell back to the old stand-by—Markov chains. The input I used for the Markov chaining process (more on that below) was the entire works of Oz by L. Frank Baum. I can't say why I picked those, other than I had already downloaded them from Project Gutenberg some years ago and had them handy. And they are in the public domain, so anybody can butcher them.

Now a Markov chain is pretty straight-forward—I used an order-3 Markov chain. So you start with three words, say “the Wicked Witch.” That's your start, and you output that. Then you find each word that follows that phrase and count the number of times they occur:

Frequency of words following “the Wicked Witch”
word	count
of	22
.	10
,	9
was	7
and	6
had	5
has	2
really	1
discovered	1
conquered	1
a	1
who	1
merely	1
said	1
dies	1
put	1
or	1
before	1
died	1
enchanted	1
surrounded	1
ruled	1
is	1
took	1
looked	1
laughed	1
¶	1
realized	1
came	1

And from there, you can calculate the precentage chance of a given word following “the Wicked Witch:”

Precentage chance of a given word following “the Wicked Witch”
word	chance of following
of	25.29
.	11.49
,	10.34
was	8.05
and	6.90
had	5.75
has	2.30
really	1.15
discovered	1.15
conquered	1.15
a	1.15
who	1.15
merely	1.15
said	1.15
dies	1.15
put	1.15
or	1.15
before	1.15
died	1.15
enchanted	1.15
surrounded	1.15
ruled	1.15
is	1.15
took	1.15
looked	1.15
laughed	1.15
¶	1.15
realized	1.15
came	1.15

You then pick a word randomly, but based on the percentage chance (“of” is more likely than “came”) and say the choice is “of.” That's your next word you output. Now your three words are ”Wicked Witch of” and you do that process again and again until you get the desired number of words printed.

In my case, the initial words were three paragraph markers (¶) and the initial opening paragraphs that came out were:

THE WONDERFUL WIZARD OF OZ

CHAP . 17

The Shaggy Man laughed merrily .

" A prisoner is a captive , " replied Ozma , promptly .

" Just wonderful ! " declared the Lion , in a voice of horror .

" Oh , indeed ! " exclaimed the Pumpkinhead .

" I'd kick out with those long legs and large knees and feet . Below in the streets of the conquered city and the gardens and Rinkitink thought the best part of me then remaining . Moreover , there was little pleasure in talking with the goat they kept away from the others .

They now entered the great hall , his shaggy hat in his hands , was a big house , round , red cap held in place by means of its strings , securely around the Ork's neck , just where his belt was buckled . He rose into the air , for I can stand it if the others can . "

So Dorothy , who had gone on ahead , came bounding back to say that Dorothy and the Scarecrow and Ozma alone ; but Dorothy had been listening with interest to this conversation . Now she turned to her captives and said :

" Are you certain this is snow ? " she asked .

The Quantum Supposition of Oz

Yes, the spacing of the punctuation is a bit odd, and I'll get to that in a bit.

And the fact that I start with chapter 17 is a quirk of the Markov chaining process, as is the initial line of the novel, “THE WONDERFUL WIZARD OF OZ,” due to the initial three words selected (three paragraph markers).

Now, most of the time on this project was spent in two phases:

1. An initial editing of the Oz books from Project Gutenberg. I had to remove all the verbiage that didn't directly relate to the story. This included not only the text Project Gutenberg added, but Table of Contents and Introductions in each book, as well as page numbers and references to illustrations.

This was perhaps an hour or two of time—only one book had page numbers (thankfully, the other thirteen did not) and the text editor made light work of removing the image references. Most of the verbiage removed was located at the start and end of each book, so that was easy to cut.

2. Defining what a “word” was for the Markov chaning.

Seriously.

I spent more time on this than I did on the initial editing.

So, what is a word?

A quick answer is “letters surrounded by space.”

And that's good for about 95% of the words. But then you get stuff like “I'll” or “Dorothy's”. Then you expand the definition to “letters, with an embedded apostrophe, surrounded by space.” Then you come across “goin'” and you redefine yet again. Then you come across “Tik-tok” (a character in the story) or “Coo-ee-oh” and you redefine your definition yet again. Then you find “how-d” and “ye-do” and realize you need to handle “how-d'ye-do” and by now you realize you also missed “Dr.” and “Mr.” and “P. S.” and …

Yes, the definition of a “word” isn't quite so simple (oh, and then you come across entries like “No. 17”—sigh).

In the end, I defined a word as such (and in this order):

A series of blank lines denotes a paragraph marker—¶.
Punctuation (these two to avoid the dreaded “wall-of-text” you often get in generative text, but they're printed as words and thus, the odd spacing you see)
“--”—these designate an m-dash, a typographical punctuation mark
Digits (but see below)
“Mr.”
“MR.”
“Mrs.”
“MRS.”
“Dr.”
“DR.”
“P. S.” (and the variation “P.S.”)
“T. E.” (and the variation “T.E.”—stands for “Thoroughly Educated”)
“Gen.” (short for “General”)
“No. ” followed by digits (no real reason for that—I just did it that way)
“N. B.” (and the variation “N.B.”)
“H.” (an initial)
“M.” (an initial)
“O.” (an initial)
“Z.” (an initial)
A few really complicated rules to catch “how-d'ye-do” but avoid making a word out of “me--please” (some context: “don't strike me– please don't”).

Then all that was left was to generate a few novels (about a minute or two) and pick one that at least starts off strong and there you have it, a novel.

Oh, and the code that generated this awful dreck, should you be interested.