sun, 14-feb-2010, 17:02

Drawn bow

Drawing my bow

Today I made a bow from a board. I started with a 1x3 piece of red oak, and ended up with the bow seen in silhouette in the photo on the right. It’s an American flatbow, similar to what many Native American tribes (including some Inuit) used. In mine, the upper and lower limbs don’t have quite the same shape and it has a lower draw weight than I had planned on, but I think it was a good first attempt at bow-making.

The hardest part is finding a board that has straight grain lines running all the way down the face of the board. You cut and smooth the sides first (it’s about 1½” wide at the handle and gently tapers to ½” at the tips) then begin tapering the limbs (full thickness at the handle, gently tapering to ½” at the tips). After each thinning the bow is drawn slightly further up a tillering board (a piece of wood with notches cut into it to hold the string) and the shape is evaluated to make sure it’s bending the way you want. My mistake was in thinning the wrong limb too much without making similar changes to the other half of the bow. Once I realized this, I had to remove a bunch of material off the now-thicker limb and wound up with a bow that is easier to draw than intended. Since I haven’t actually shot an arrow from a bow since high school, a light drawing bow is probably a good idea until I’m ready for something more powerful. This one is reasonably easy for me to pull, and shoots sticks very smoothly.

Tools used: I used a rip saw to cut the board to rough dimension, smoothed the saw cuts with a wooden jack plane, made the initial taper with a drawknife, and did the majority of the remaining adjustments with a coffin smoother, an adjustable mouth block plane and a handled cabinet scraper. Probably should have used the scraper more and the hand planes less. Volumes 1 and 4 of The Traditional Bowyer’s Bible were invaluable, and I think I could have used the other two volumes too, if I’d had them. There’s a ton of information in those books for both the beginner, and advanced bowyer. In addition to volumes 2 and 3, I need some real arrows, a target, and more wood for more bows!

tags: bow  bowyer  woodworking 
sun, 31-jan-2010, 16:41

Utility area doors

Utility area doors

We’ve been wanting to let the kittens into the rest of the house for several weeks now, but when we got close to letting them downstairs we realized they could get into all sorts of trouble in the utility area in the bathroom where the water heater, pump, and washing machine are. Worse, if they got in there, they could climb around behind the shower and tub surround and we’d have no way of getting them out.

So I built the doors you can see in the photo. They’re made from clear pine. I’d originally planned on using “pocket-screw technology,” on the doors, but when driving the pocket screws from the back of the rails into the styles, they cracked the styles. I wound up using glue and dowels instead, and they seem solid. I was a little worried because the doors were so large, but they’re flat and slide easily in the tracks I made.

The image looks a little warped because it's a series of photos that are joined together using the AutoStitch iPhone app. It's a pretty good alternative when you don't have a wide angle lens.

Today was the first day the kittens came downstairs (except once when Jenson escaped), and things seemed to go well. Nika and Piper have been spending nights with all of us, so they’re used to the kittens. Buddy and Deuce mostly seemed afraid. Koidern and Kiva were both very interested, and spent the whole time cautiously following the kittens around. After an hour or so we put the kittens back upstairs to let everyone relax. I opened up the gates again this afternoon and captured this video of Kiva’s interaction with Tallys (and a little of Jenson). Tallys is the one rolling around on the floor in front of the heater, seemingly trying to play with Kiva’s feet.

The music (which was playing on the stereo as I recorded the video on my iPhone) is from Four Tet's latest record.

tags: dogs  Jenson  kittens  Kiva  Tallys 
sun, 31-jan-2010, 13:40

I recently saw a pair of blog posts showing how to make heatmaps with straight R and with ggplot2. Basketball doesn’t really interest me, so I figured I’d attempt to do the same thing for the 2010 Oakland Athletics 40-man roster. Results are at the bottom of the post.

First, I needed to get the 40-man roster:

$ w3m -dump "http://oakland.athletics.mlb.com/team/roster_40man.jsp?c_id=oak" > 40man

Then trim it down so it’s just a listing of the player’s names.

Next, get the baseball data bank (BDB) database from http://baseball-databank.org/, convert and insert it into a PostgreSQL database using mysql2pgsql.perl.

A Python script reads the names from the roster, and dumps a CSV file of the batting and pitching data for the past two seasons for the players passed in.

$ cat 40man_names | ./get_two-year_batter_stats.py

The batting data looks like this:

            name  , age,   g,    ba,   obp,   slg,   ops,  rc,   hrr,    kr,   bbr
Daric Barton (1B) ,  25, 194, 0.238, 0.342, 0.365, 0.707,  73, 0.017, 0.173, 0.134
Travis Buck (RF)  ,  27,  74, 0.223, 0.289, 0.392, 0.682,  28, 0.035, 0.202, 0.073
Chris Carter (LF) ,  28,  13, 0.261, 0.320, 0.261, 0.581,   1, 0.000, 0.360, 0.080
...

I’ve used the counting stats in the BDB to calculate batting average (ba), on-base percentage (obp), slugging percentage (slg), OPS (on-base percentage + slugging percentage), runs created (rc), home run rate (hrr), strikeout rate (kr) and walks rate (bbr).

And the pitching data:

            name   , age,  g,      ip,  w, l,    sv,    wp,    lp,    wf,   era,    k9,   bb9,   hr9
Brett Anderson (P) ,  22,  30, 175.33, 11,  11,   0,  0.37,  0.37,  0.00,  4.06,  7.70,  2.36,  1.03
Andrew Bailey (P)  ,  26,  68,  83.33,  6,   3,  26,  0.09,  0.04,  0.04,  1.84,  9.83,  2.92,  0.54
Jerry Blevins (P)  ,  27,  56,  60.00,  1,   3,   0,  0.02,  0.05, -0.04,  3.75,  8.70,  3.30,  0.60
...

Here I’ve calculated innings pitched (ip), winning percentage (wp), losing percentage (lp), win frequency (wf), earned run average (era), strikeouts per nine innings (k9), walks per nine (bb9), and home runs given up per nine innings (hr9). All these stats are for the last two Major League seasons.

Finally, generate the heat maps in R. For batting statistics:

library(ggplot2)
mlb <- read.csv('batting.csv')
mlb$name <- with(mlb, reorder(name, ops))
mlb.m <- melt(mlb)
mlb.m <- ddply(mlb.m, .(variable), transform, rescale = rescale(value))
(p <- ggplot(mlb.m, aes(variable, name)) +
+   geom_tile(aes(fill = rescale), colour = "white") +
+   scale_fill_gradient(low = "gold", high = "darkgreen"))
base_size <- 14
p + theme_grey(base_size = base_size) + labs(x = "", y = "") +
+   scale_x_discrete(expand = c(0, 0)) + scale_y_discrete(expand = c(0, 0)) +
+   opts(legend.position = "none", axis.ticks = theme_blank(),
+   axis.text.x = theme_text(size = base_size * 0.8, angle = 0, hjust = 0.5, colour = "black"),
+   axis.text.y = theme_text(size = base_size * 0.8, lineheight = 0.9, colour="black", hjust = 1))
    

Pitching statistics are the same, except the third line (where I order the data frame) is:

mlb$name <- with(mlb, reorder(name, 1/(era+0.1)))
    

The results:

A’s batting heatmap, ordered by OPS

A’s pitching heatmap, ordered by ERA

You have to keep the number of games (or innings pitched for pitchers) in mind when you look at these charts. I don’t even know who some of those guys are, probably because they’ve only barely played in the majors. It might make some sense to split the pitching plot into plots for starters and relievers, but I’d need a good way to determine a pitcher’s status (innings pitched divided by games beyond some threshold, perhaps?).

As for the A’s, I like their pitching, but have serious doubts about their offense. I sure hope some of the younger guys on this chart start reaching their power potential because having Jack Cust as your only offensive weapon doesn’t bode well for the team scoring runs.


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