pattern – dave's blog of art and programming

Warping a 4 shaft table loom

The next stop on my exploration of loom technology for the weavingcodes project (after building a frame loom and learning tablet weaving) has been learning how to use a 4 shaft table loom. This has been kind of daunting to me, as it’s a much more modern weaving device than I’ve been working with up to now (frame looms and tablet weaving can be considered to be both neolithic digital tech). I also couldn’t really figure out much from books on the warping techniques, as it’s difficult to get the idea through images – so I had to just kind of jump in and try it.

I decided to use the double weave draft plan to start with from my last post – partly as I want to try this technique, but also it’s pretty simple warp threading for a first attempt.

The next step was to choose the material. A while back I bought 200gms of good quality 8/2ne cotton/linen mix which I’ve been saving for something like this. In order to calculate the amount of fabric the yarn will produce you can wrap it lightly around a ruler:

This yarn is about 10 threads per centimetre, so we can use that to figure out roughly how many warp threads (or ‘ends’) to use – I decided on 160 ends in total (so ~16cm wide) comprised of the two alternating colours. I wound out two sets of 80 threads over a couple of metres, doing both colours at once to make it easier. I then attached each one to the back roller and wound them in a bit – this would have worked better later if I had used more bundles of fewer threads.

You can see in the picture I’ve also bolted a “raddle” (thing with nails) on the back beam of the loom to help space out the warp threads – this is important later on. Now we come to the heddles. The threading chart is what programs this part of the loom, which in turn forms a fixed instruction set of pattern possibilities for the weave. You can see the 4 levers that operate the frames in the photo above – these essentially give us 4 bits per weft of information. 2 of the 16 possibilities are invalid – as all frames raised or lowered doesn’t provide a working fabric. Using different sequences of these 14 combinations for each weft thread, the possibilities become mathematically huge – even with a fixed warp like this.

Reading the frames and warp colours from the chart to provide a sequence, you hook each warp end through the eye of the heddle – this was the most time consuming part of the process.

Once that is done, the reed – which is attached to the beater and used to pack down and keep the fabric evenly spaced, is threaded (or “sleyed”). The reed I used was a bit too course so I used two threads per gap – this could have done with being a bit more as it turned out.

With all this done the warp ends can be attached to the front roller and the whole warp can be wound on through the heddles and back again to check the tension. Of course in practice (and as it was my first time) it actually involved a lot of tangles and swearing, and two broken warp threads, fairly easily knotted back together. The raddle was essential in helping untangle the warp threads, but I also had to fiddle around with the tension a lot, retying the knots attaching them to the rollers and using plenty of sticks (it seems you can never have too many sticks when warping a loom). This is a test that the warp is threaded correctly, with all black threads (frames 2 and 4) lifted – phew!

After that we could try a little test weaving, going freestyle on the heddles.

It turns out the reed is a little too wide, meaning it’s stretching the warp out as the woven fabric finds it’s true width – switching to a new one is possible without needing to do the heddles again, so we’ll see how it goes. Compared with tablet weaving, this is far more mechanised and efficient in terms of fabric production, but the flipside to that is that you lose a lot of flexibility, and the loom is less responsive to particular material properties like this.

Coding with threads: Frame loom

After writing the 4 shaft loom simulation the next job was to try weaving the structures with real threads. Would I be able to replicate the predicted patterns and structures? Ellen warned me that the meander weave would result in unstable fabric, but it would depend on the nature of the material used so was worth trying. Originally I planned to warp up the Harris loom but I need to work up to that as it’s a big and complex job, so I quickly built a frame loom with some bits of wood and nails at 5mm intervals to hold the warp in place.

Here you can see it set up with the all important first ‘shed’ (name given to the gap between subsets of warp theads), which defines the order of the threads. I packed the warp too tightly and messily so this was important – luckily as the yarn colours alternate so it made it easy to make.

Here I’m sleying the shafts using threads to pick up the warp as defined by the simulation toggle buttons. The threads (which form heddles) are tied on to wooden poles which are pulled in different combinations during weaving. This is the approach we saw on the warp weighted looms in Copenhagen, I’m not sure if it’s usually used on frame looms – it was cumbersome but much faster than counting threads manually each time. It’s important to use thinner threads than the warp, but you need to put quite a bit of tension on them so they need to be strong. There is something very appropriate in the context of this project about coding threads with threads in this way.

Here it is finished and ready to start weaving. I numbered the shafts with pencil but it’s actually very obvious based on the order they are attached so I never used them. Following the lift plan from the simulation was quite easy, thinking about the pattern more than the combinations of numbers – as I went on I could tell where I was based on the nature of the shed, keeping an eye on the rhythm of the warp threads picked up. Also the parts where I need to lift 3 and leave 1 was really tricky – not helped by the fact that the resulting weft was difficult to see at that point.

In relation to livecoding, I was surprised to the extent that improvisation is required when weaving even based on a predefined pattern. There is a lot of reasoning required in response to issues of structure that cannot be defined ahead of time. You need to respond to the interactions of the materials and the loom itself, the most obvious problem you need to think about and solve ‘live’ is the selvedge – the edges of the fabric. In order to keep the weave from falling apart you need to ‘tweak’ the first and last warp thread based on which weft yarn colour thread you are using. The different weft threads also need to go over/under each other in a suitable manner which interacts with this. This will be important to include in the simulation properly, but this will only give an early indication of problematic decisions, rather than a failsafe solution.

Here’s a closeup of the meander pattern compared to the simulation. The yarn is cheap and a bit fuzzy, but hopefully you can see the structure – the differences are interesting. I’m not sure how this will distort further when I remove it from the loom and the tension is gone.

Here are some more freestyle patterns, the boxy ones turned out to be more stable than the meanders – it’s really satisfying to see them emerge from the abstract set of rules that you work with to lift the shafts, not unlike graphics programming. Which of the 4 shafts to lift can be thought of like 4 bit opcodes with different ordering resulting in indirect pattern shifts.

There are three types of limitation that I’d like to note and think about (especially in terms of incorporating them in a programming language). One is the selvedge, as I mentioned earlier – another is floats, which cause the problems on the meander pattern (long threads not incorporated into the fabric). The third is more subtle, some sequences of sheds cause problems when packing down the weft, for example if you are not too careful you can cause the ordering of the weft colours to be disrupted in some situations.

Dyadic device: a 4 shaft loom simulation.

On the train back from the Sheffield codingweaves workshops back in October I wrote a quick browser program to attempt to further understand the relationship between structure and pattern in weaving – which I’ve put online here. This works in the inverse of how we’ve been writing weaving simulation programs so far. Instead of defining the pattern you want directly, you are describing the set up of a 4 shaft loom – so the warp threads that each of 4 shafts pick up in the top row of toggle boxes, then which shafts are picked up for each weft thread as the fabric is woven on the right.

This involved writing a program that is based closely on how a loom functions – for example calculating a shed (the gap between ordered warp thread) by folding over each shaft in turn and or-ing each warp thread to calculate which ones are picked up. This really turns out to be the core of the algorithm – here’s a snippet:

;; 'or's two lists together:
;; (list-or (list 0 1 1 0) (list 0 0 1 1)) => (list 0 1 1 1)
(define (list-or a b)
  (map2
   (lambda (a b)
     (if (or (not (zero? a)) (not (zero? b))) 1 0))
   a b))

;; calculate the shed, given a lift plan position counter
;; shed is 0/1 for each warp thread: up/down
(define (loom-shed l lift-counter)
  (foldl
   (lambda (a b)
     (list-or a b))
   (build-list (length (car (loom-heddles l))) (lambda (a) 0))
   (loom-heddles-raised l lift-counter)))

I’ve become quite obsessed with this program, spending quite a lot of time with it trying to understand how the loom setup corresponds to the patterns. Here are some example weaves that you can try. Colour wise, in all these examples the order is fixed – both the warp and the weft alternate light/dark yarns.

This is tabby or plain weave – the simplest and strongest weave (used for sails and hard wearing fabric). The striped pattern is a result of this alternating colour order.

Basket weave – doubling the plain weave, results in a zigzag pattern.

This is called 2×2 twill, the structure provides a stretchy fabric, often used for clothes. Notice that the pattern in the same as the basket weave even though the structure is different – this is a hint at how structure and pattern are linked in strange ways (it gets much more complex than this of course).

I’ve become very interested in this threading pattern for the shafts as it results in lots of interesting patterns. This is an example of connected boxes.

A slight shift and we can obtain meanders, an important motif of the kairotic project. It turns out this is a highly unstable structure due to the length of the ‘floats’ – the threads spending too long without being incorporated back into the weave. More on that later on.

Here’s a more freeform weave where I switch patterns between different types by changing the lift order. Much like music, it’s possible to switch patterns in a nice way that doesn’t interrupt the flow.

Next up is building a real loom to try these patterns out in thread form.

Egglab – pattern generation obsession

I’m putting the final pieces together for the release of the all new Project Nightjar game (due in the run up to Easter, of course!) and the automatic pattern generation has been a focus right up to this stage. The challenge I like most about citizen science is that along with all the ‘normal’ game design creative restrictions (is it fun? will it work on the browser?) you also have to satisfy the fairly whopping constraints of the science itself, determining which decisions impact on the observations you are making – and being sure that they will be robust to peer review in the context of publication – I never had to worry about that with PlayStation games 🙂

With this game, similar to the last two, we want to analyse people’s ability to recognise types of pattern in a background image. Crucially, this is a completely different perception process from recognition of a learned pattern (a ‘search image’), so we don’t want to be generating the same exact egg each time from the same description – we don’t want people to ‘learn’ them. This also makes sense in the natural context of course, in that an individual bird’s eggs will not be identical, due to there being many many additional non-deterministic processes happening that create the pattern.

The base images we are using are wrapped Perlin noise at different scales, and with different thresholds applied. These are then rotated and combined with each other and plain colours with the browser’s built in composite operations. Ideally we would generate the noise each time we need it with a different random seed to make them all unique, but this is way too slow for HTML5 Canvas to do (pixel processing in Javascript is still painful at this scale). To get around this we pre-render a set of variations of noise images, the genetic program picks one of four scales, and one of two thresholds (and one without threshold) and we randomly pick a new variation of this each time we render the egg. The image at the top shows the variation that happens across 6 example programs. Below are some of the noise images we’re using:

Visualising egg pattern genomes

A couple of screenshots from the upcoming Project Nightjar citizen science game – the genetic programming pattern generator is now working in a simple test framework, and even with myself as the only player at the moment, it’s gradually producing eggs that are harder and harder to find against one of the background images from the field site in South Africa. Today I’ve been working on a viewer for the pattern genome itself, which displays all the base images and the operations and intermediate steps as it builds up the final image. Unlike any natural form of genetics, genetic programming is all about growing trees of functions connected together, and here we are interested in combining simple images using HTML5 canvas’s composite operations to make complex patterns.

This will be useful for debugging mutations, where the sub-trees are jumbled up, but as we’re building a citizen science game, we’re also going to be exposing as much as possible about how it’s working – from the game mechanics like this to the underlying camouflage theories we’ll be testing. If you recognise the graph drawing algorithm, I’ve been plundering a long forgotten project: fastbreeder.