Laser beam GIF

GIF made with Processing, animated with CSS.

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GIF of Music

What’s greater? The gift of music or that GIFs don’t have music?
harmonica

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Harry Horstman of Mount Sproatt

When I first read The Mysterious Harry Hortsman I was immediately drawn to this so-called “illusive” character who mined and otherwise occupied the area nearly a hundred years ago.

On a warm sunny October afternoon I set out to summit Sproatt. I took one of the easier bush whacking routes next to Sproatt Creek up around back just in time to snap a couple pics and return for supper. Simply stunning looking back across Whistler valley into Garibaldi Provincial Park.

Whistler_from_Sproatt

On the way down I decided to take a straighter shot avoiding some of the larger hazards such as cliffs and avalanche shoots overgrown with near-impassable alder trees. I have hiked every inch of Sproatt in the past 20 years, or so I thought. On cutting across the hill I walked over and barely noticed a site of an old cabin. Reduced to a level dirt floor with an outline of decaying logs, the site had bits of single plate glass and other debris.

Harry_Hortman_Cabin

After some closer inspection I uncovered an old frying pan that felt a bit spooky considering it’s mention in Harry Hortsman’s story.

Harry_Hortman_Frying_Pan

This site seems to be a bit lower in elevation than the reported cabin Harry Hortsman had at the 5300 foot level, which I still have yet to find.

Was this another cabin of Harry’s or possibly the residence of another miner or illusive character of years past?

Selfie_from_Sproatt

It’s getting dark and colder quickly. My thoughts are of all the mysterious people that have roamed these woods.

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How Guessing Football Works

Guessing Football

A quick post to explain a bit about how guessingfootball.com works.

The site was built for myself as a fun project to see how accurate I could get a machine to pick football games.
This after years of failing to successfully do so myself.

It was conceived many years ago and half-built in different forms on different technologies but abandoned each time before completion.

This year, in time for the NFL season, I managed to build it out using Python and Django, taking advantage of HTML5’s localstorage to store user picks.

This is how it predicts games:

  1. Grab a random score from a list of all the scores in the last two years with the frequency it occurs. 21, 17, 10 etc. are very common so they get picked more often. Do the same for the opponent.
  2. Are they the same? If so, throw one of the scores away and get a new one. Ties happen but are rare.
  3. Look at the scores and check their variance to the team’s computed mean. Basically, if the score fits within an acceptable range, keep it, if not throw it away and pick another. The computed mean is a weighted average of points-for and points-against. Meaning a teams recent scores influence the process more than a score a long time ago.
  4. Finally, a check is performed to see that the probability of these scores happening isn’t too far fetched. 5-2 for instance.
  5. Once the week is complete, look back and reflect. See where the biggest mistakes happened and lightly factor that into the next round of picks. All final scores are then added into the pool and the oldest week removed. Repeat.

That’s it. No rumour mill. No injuries or QB controversies. I know what you’re thinking… “Surely I could do better”. Well I say give it a try! (and don’t call me Shirley.)

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