Archive for February 2010

New Spinning Tool: The Nøstepinne

February 22, 2010

We’ve been spinning for a couple of months now. Having produced a few hundred yards of plied yarn, we began to fall prey to a plague of twisted hanks hanging around our home. In case you’re reading this and you don’t know a hank from a ball from a skein (knitters, bear with me), a hank looks like this:

A “ball” can be shaped like, well a ball, or like a round flat-topped cake:

and skein refers to the sausage-like blob of yarn that you’ll get if you buy yarn in a department store or a big craft store like Jo-Ann’s. Ball-shaped balls tend to roll around, to the great amusement of cats and the great frustration of knitters. So I like the cake shape, which doesn’t roll, and also has the advantage of stackability.

Hanks serve well to “set the twist” in your newly plied yarn, and the hank making process also presents an opportunity to count yardage. However,  hanks are nearly impossible to knit from. I would never try. We realized that we needed of a tool for turning our hanks into nice, center-pull balls, like the green cake above. The (cheap) answer: a nøstepinne. This tool’s name comes from Norwegian, and literally means something like “nest stick.” Makes sense. (Spinning tools have the best names in general: distaff, scutching knife, heckles, niddy noddy, weasel. Sounds like midæval torture arsenal to me, and some of these things look like torture implements, too.)

One night Beth and I were talking about what to do about all our nice looking  but inconvenient hanks. Ball winders work great, but they also cost quite a bit, and we’d just dropped a fair bit of coin on our wheel and hand carders. So I said, “We need a nøstepinne!” I don’t know where I learned what a nostepinne is, but I’d heard of them, and I knew they could be used to wind a center pull ball.

I went to work the next day, and when I was eating lunch in the cafeteria, I heard harpsichord and recorder music. We are never treated to early music performances at lunch, so I followed the sound to investigate. Turned out the harpsichord was being played by the man who built it, and he was stationed at the entrance of a craft fair. I wandered through the craft fair, and discovered that one booth sold wood turnings: bowls, rolling pins, and…NØSTEPINNES! I couldn’t believe it. I went into the booth and said, “I’d like that black walnut nøstepinne.”

They seemed surprised that anyone knew was the nøstepinnes were for, let alone a little bearded dude. I asked the man and woman in the booth if they were spinners or knitters, but neither one was. Apparently, the turner had had some requests for the winding sticks at a fair in Maine. So he started turning and selling them.

Check out the excellent ball that Beth spun and wound:

I learned to wind flat stackable yarn balls via some youtube videos and showed Beth the technique, but she is definitely the master now.

The Ben Sweater, or always check your gauge

February 12, 2010

I’ll need to get Beth to take a picture of me outdoors so that I can get a non-backlit photo of my second completed sweater, “the Ben“,  by Nora Gaughan. This one took less than a third as long as my first sweater, thank goodness. The Ben only took me about 7 months, but I wasn’t working on it all the time, and in fact almost 30% of it was knit just on flights to a physics meeting in Australia.

Incidentally, that trip was the only time I’ve ever had knitting needles taken from me by airport security. Bamboo circular needles! Surely pencils are at least as dangerous as bamboo circs, and I’m sure no one would take them away. Even the other passengers thought that the security people didn’t understand the policy. So I think it was a case of one security crew being uninformed rather than an Australia-wide anti-knitting-while-flying phenomenon. I did knit on my first two flights in the country without objection from anyone…

I think the cables show up better in this picture of the sweater parts prior to assembly.

I really like the color of this sweater, which was knit using Berrocco Classic Merino in the “new denim” colorway. The yarn feels pretty nice, and was a very reasonable price for 100% wool. This was the last project I knit with yarn not purchased at a local yarn store (before my fiber snobbery reached its full force.) The only drawback to this worsted weight merino has been that the sweater is far too warm to ever wear in the office. Fortunately, we keep our apartment cold enough to make the sweater pretty comfortable at home.

Features of this sweater that were new for me include the v-neck, and the set-in shoulders (Beth’s Aran sweater had a crew neck and drop shoulders). I love v-neck sweaters. Also, I like sweaters with more shaping. Knitting the set in shoulders was much simpler than I thought it would be. Unfortunately despite having set-in shoulders, this sweater does not look very shaped because it’s a bit too big. I did swatch, but apparently not carefully enough; I didn’t block my swatch, and this sweater is so heavy, it stretches some under its own weight. I know I can’t shrink this sweater to fit, because this yarn felts really well.

I was talking about my fit problems with Rick, one of the owners of our LYS, and he mentioned that Margot (his wife, the other owner) is not at all squeamish about taking scissors to ill fitting sweaters. The idea would be to cut the cuffs off the sleeves, then pick up the stitches at the cut edge and reknit the cuffs to make the sleeves shorter. The same could be done to shorten the body, and I might be able to reseam the edges to make the body slimmer. We’ll see…

In the meantime, the Ben is one of Rhianna’s favorite beds when I’m not wearing it:

Actually it’s one of her favorite beds even when I am wearing it!

Another HDR photo: Hanover UCC Church

February 12, 2010
underexposure
middleexposure
overexposure
TonemappedImage

The previous example of HDR photography resulted in a somewhat surreal looking sky. Photographers using the HDR technique often seek out that appearance. I agree that it looks cool. However, one can also obtain more realistic results, as I tried to do in the above example that I took when I was in graduate school. This church stood across the street from my office in the physics building:

Wilder Hallan HDR image of Wilder Hall, Dartmouth College

The actual church scene didn’t offer the dramatic lighting of the UCLA building at sunset. However, the lighting around the church spanned a wider total dynamic range between the sky and the shadows under the trees. So each exposure of the church is separated by 2 stops, rather than 1.5 as in the previous photo.

The thumbnail images next to the tonemapped church picture above can be clicked to view them more closely. I find the differences to be really striking here. In the darkest exposure (1/100 second), there’s basically no information in the shadows under the trees. Things just look black. Meanwhile, in the brightest exposure (1/6 second) the church almost disappears into the sky because it has been so overexposed. The tonemapped image shows detail in all these areas while remaining more or less realistic in appearance.

How do image histograms work?
The diagram above shows RGB histograms for the three original images, and the histogram for the tonemapped composite below them. The horizontal axes of the histograms indicate brightness or saturation. The black distribution represents brightness; the colored distributions show saturation of each color channel at a given brightness.

So, the left side of each histogram represents the darkest resolvable brightness in a given image. Anything darker would simply look black in that image. The right side represents the brightest resolvable luminosity; anything brighter would appear to be pure white.

The height of the distribution at a given location represents the number of pixels with that brightness (or color saturation for the colored distributions). The vertical lines represent “stops,” or factors-of-two differences in brightness.

You can see from the amount of overlap of the three histograms that they differ by two stops, or a factor of four in brightness. Thus the composite image contains information gleaned from a range of 9 stops, or almost twice the range that could be depicted in a single exposure. The bottom histogram shows how the data from those nine stops has been compressed back down to 5 stops through the tonemapping process.

Okay, enough photo geekery. I think I’ll get back to baking, knitting, and spinning related posts now.

Photo of the Week #10: UCLA in High Dynamic Range

February 10, 2010

click image to view larger

I was at UCLA a few weeks ago for a plasma physics winter school, a week long workshop for grad students and post-docs. In the evenings we had homework sessions on the roof of the physics building, and one evening I took several shots of a building across the street. The above photo is a “tonemapped”, high dynamic range (HDR) image compiled from a stack of three bracketed photos with different exposures.

The light was really amazing because the sun was setting to my left as I was taking the photo. However, I knew that no one exposure could capture both the detail in the clouds, and the details in the shadows on the right side of the picture; the scene had too large a dynamic range. So I took three pictures using the auto exposure bracketing  feature in my camera. These pictures (seen below) were all taken with the aperture set at f/8, but the shutter speeds were 1/6, 1/10, and 1/15.

What is Dynamic Range?

Static dynamic range refers to the difference between brightest and darkest things you can see at the same time without moving your eye around. The static dynamic range of the human eye is generally around 100:1.  So, the dimmest thing you can really see when looking at, say, a campfire is about 100 times dimmer than the fire itself. When talking about photography, differences in brightness are typically discussed in terms of “stops.” A stop is a factor of two difference in brightness. So, a ratio of 100:1 corresponds to about 6 and 1/2 stops (26=64 ; 27=128).

Of course the total dynamic range of your eye is MUCH bigger than that. In total, your eye can resolve an impressive 20 stops, or about a 1,000,000:1 ratio of luminosities (brightnesses). That means if you move your eyes around, they can adapt to see a much wider range of luminosities (just not all at the same time).

My camera, however, can only resolve a modest 5 stops in a single scene (stored as an 8-bit per color channel jpeg file; this post really deserves its geek tag, doesn’t it?). Most cameras have a similar limitation. Consequently, when you look at a photo taken with basically any camera (digital or film), and displayed on a typical monitor or on photo paper, the luminosity information has possibly been heavily truncated. This why skies often look white in photos even though they looked blue in person.

What is Tonemapping?

One way to convey more of the luminosity information from the original scene is by combining multiple exposures into an image that contains a wide dynamic range. The luminosity data can then be compressed to a range that can be displayed in a single scene. That compression process is called tonemapping. In the example above, I took 3 photos, each spanning 5 stops and separated by 1.5 stops and combined them to yield a single photo that retains local contrast information in both the highlights and the shadows. Here are the original images:

While the local contrast information has been better retained everywhere in the tonemapped image, the total dynamic range has not been increased and is still limited by the maximum dynamic ranges of the file format and the display device. I used software called Photomatix Pro to do the tonemapping. The free trial version can make images as large as the one above, or larger ones that have a watermark on them.

Homemade Pita

February 2, 2010

If you’ve never eaten soft, warm pita straight from the oven, frankly I feel bad for you. So, this post will chronicle the results of some experiments I’ve done in home pita baking.

Like many breads, freshly baked pita is so delicious and so different from the room temperature, dry feeling, store bought, plastic-bagged version. On top of the delicious end-product, I enjoy watching the pitas magically puff up while they bake. Have you ever wondered how that pocket gets into the pita?

Well, when they come out of the oven, pitas can be almost spherical, and are filled with a pocket of air. The loaves collapse as they cool, leaving the stuffable pocket in the finished loaf. You can see the puffage in my low-tech time-lapse movie:

These events actually spanned a period of five minutes.

If you want to make pitas from scratch, I highly recommend reading this post by Farmgirl from 2005. Her recipe makes delicious pita, and I’ve achieved a successful puff rate of  at least 70-80% with her recipe. I don’t think I can improve on her recipe at all, without doing Cooks-Illustrated-style experiments involving 50-100 batches.

But a few weeks ago, I got to thinking, “Hmmm, you know, pizza dough is made from almost identical ingredients in almost identical proportions to that pita dough. I wonder if I could make pita from pre-made store-bought pizza dough?” If this worked, it would mean that I could bake fresh pita after work, and still eat at a reasonable hour.

Rising and kneading time account for most of the delay when making any yeast bread. Generally freshly baked bread proves to be totally worth the wait. But sometimes, I don’t have the foresight to know what I want for dinner tomorrow. I think to myself at lunch time that I’d like pita and falafel for dinner. Such was the case one day last week. So I executed my pita-from-pizza-dough experiment. The result: a total success!

I began with some refrigerated, Hannaford-brand whole wheat pizza dough (Hannaford is our regional grocery chain):

I opened the package, divided the dough into 8 parts, covered them with a damp tea towel, and allowed them to warm up to room temperature:Preheat your oven to 500°F. With well floured hands and a well floured board and rolling pin, roll each ball into a 3/16″ (5mm) thick circle. Perfect circles are not important. Uniform and appropriate thickness are important.

Thick, corrugated cardboard or some higher quality hardware store paint stirrers have about the right thickness to make good depth gauges. Just place the sticks on the edges of your board and roll the rolling pin on top of them. When the pita is as thick as the stirring sticks, it will be uniformly the proper thickness. Now that I’m thinking about it, I bet a National Geographic magazine might make a good depth gauge, too. Here are the rolled out proto-pitæ:

Place the dough disks on a piece of aluminum foil. If you have a pizza peel, it will be handy for getting the pitas into the oven. If not, no big deal. The pitas go into the oven sitting on only the foil. No cookie sheets. No baking stones. Just the foil on the oven rack. The bottoms of the pitas harden too quickly on a stone or baking sheet, inhibiting the puffage. Bake the discs, two to four at a time, for 5-7 minutes. You want the insides to be fully baked, but the outsides to still be soft with just a little golden brown coloring.

After the pitas come out, place them into a paper grocery bag, and roll the bag shut, or wrap them in foil. This will keep the loaves soft as they cool.

As you can see, everything worked fine out with the whole wheat dough. However, I repeated the experiment with white-flour pizza dough from Trader Joe’s. Not surprisingly, the white-flour loaves puffed up much higher. Also, I found the first batch of pitas to be a little small. So, I’d recommend dividing the package of dough into only six parts (for a 20 oz package of dough).


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