Friday, November 21st, 2014 at 1:50 pm - - Machining

Sensor readings generally have to be processed before you can use them. Patrick’s explanation of how he filtered the CoffeeMon signal (by picking the maximum value in each time window) suggested that there’s something fishy going on and it would be a mistake to treat the readings as subjected to mere noise.

Here’s a zoomed-in section of my fridge temperature as it rises by about 0.75 degrees an hour, or 12 units of 1/16th of a degree which my Dallas OneWire DS18B20 digital temperature sensor reads at its maximum 12 bits of resolution.

temperrorzoom

The readings don’t jump between more than two levels when the temperature is stable. You’d expect some more random hopping from signal noise.

Indeed, applying a crude Guassian filter doesn’t seem to do much good. This (in green) is the best I got by convolving it with a kernel 32 readings wide (equating to about 25 seconds)

temperrorzoomguass

filteredcont = [ ]   # cont = [ (time, value) ]
k = [math.exp(-n*n/150)  for n in range(-16, 17)]   
sk = sum(k)    # (the 1/150 const chosen for small tail beyond 16 units) 
k = [x/sk  for x in k]
for i in range(16, len(cont) - 16):
    xk = sum(x[1]*kx for x, kx in zip(cont[i-16:i+17], k))
    filteredcont.append((cont[i][0], xk)) 

The filtered version still has steps, but with a rough slope at the change levels. This filter is very expensive, and not any better than the trivially implementable Alpha-beta filter, which smoothed it like so:

temperrorzoomalphabeta

a, b = 0.04, 0.00005  # values picked by experimentation
dt = 0.5
vk, dvk = cont[0][1], 0
cont3 = [ ]
for t, v in cont:
    vk += dvk * dt   # add on velocity
    verr = v - vk    # error measurement
    vk += a * verr   # pull value to measured value
    dvk += (b * verr) / dt  # pull velocity in direction of difference
    cont3.append((t, vk)) 

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Tuesday, November 18th, 2014 at 5:54 pm - - Machining

I have experienced much joy from this hardware hacking. I must have spent a couple hundred pounds on components. The bits arrive in little plastic trays like very expensive chocolate sweeties. There’s always a thrill when you first wire them up and they actually work perfectly. Not only that, you can have fun with them the next day and the day after that, because they have not turned into poop.

I have a few surpluses by now. I got a realtime clock which is 5V, and a microSD card reader which is 3V3; the Jeenodes run on 3.3V and the normal arduinos are 5V, so I can’t easily use either as the controller for datalogger. Some of the more idiot-proof breakout boards have converters on them, so they are safe for either voltage. Adrian has warned me to prepare for the coming of the 1.8V standard everywhere soon. I bought a combined ArduLog-RTC Data Logger, which for the moment is not playing ball.

Meanwhile, I’ve made a rule for the data logging of sensor data. Don’t do it. It’s not an end in itself. Too often people take on projects to collect sensor data and upload it to the internet (it’s Tuesday, so the site must be called Xively) with the idea that anyone else in the world could download it and [rolls eyes] “Do whatever they want with it.”

“Like what?”

“Whatever they want!”

If you can’t think of a single interesting application for your data, why do you think anyone else in the world will be able to? And even if there was anyone in the world who could do something with it, they’re probably the sort of person who’d have their own data which is guaranteed to be lot more interesting to them than yours. There’s a reason we don’t have a CCTV channel of someone else’s back door at night on cable TV.

I’ve formulated a stronger principle:

The value of sensor data is inversely proportional to the product of the time that has ellapsed since it was collected and the distance you are from the subject of the data.

Let’s take a simple case.

Patrick made CoffeeBot by putting the coffee machine onto an electronic weighing scale connected to an Arduino with an ethernet shield that talks to the internet.
coffeebot

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Wednesday, November 12th, 2014 at 11:48 am - - Machining 1 Comment »

I’ve been playing around with some geometric signal processing on the Atmega328-based Arduino kit for my run-time line fitting routine, when it occurred to me that I ought to know if I should be using floats or long_ints as the basis for this system.

Short_ints are only 2bytes with a maximum value of 32767, so you’re always overflowing them and it’s not worth the hassle. Therefore you have to use long_ints, which are 4bytes, the same as a float, so saving precious memory is not a factor in this decision.

Anyways, I woke up this morning and decided I needed some benchmarking.
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Monday, November 10th, 2014 at 10:39 am - - Whipping

It was an expensive London and Cambridge weekend for me and Becka (£99.20 return train ticket each), but the chance to get home on Sunday night directly from the middle of London to the middle of Liverpool in under three hours without needing to be awake beat the plan of car shuttling onto a local train via some backstreet parking spot in St Albans to avoid driving to the centre of London.

You win some, you lose some.

I got a motion for electionleaflets.org to be done properly accepted by the members at the UnlockDemocracy AGM on Saturday. This has the potential to get some professionalism on the situation in time for the next election.

Then I spent 36 hours working and sleeping in the basement of the National Audit Office at the Accountability Hack 2014 on a my project, with Becka getting predictably very bored at times.

The purpose of the project was to learn how to use PDF.js, which Francis told me about the day before.

I thought I had a good chance with it (being as it is completely practical and could be implemented by the Public Accounts Committee right away), but it did not even get an honourable mention. That honour went to Richard whose Parliamentary Bill analyser disclosed how many goats would need to be skinned to print out the Act, among other things. For more details, see my blogpost from six years ago: The vellum has got to go.

povbrain

We met Rob for dinner who had a brain machine on the bookshelf, which Becka was very taken with. I can tell you that someone will be learning how to solder in the next couple of weeks, because that is the only way they are going to get one of their own.

Thursday, November 6th, 2014 at 1:08 am - - Hang-glide

Just when I thought it was over for the summer, there came a chance to go flying at Llangollen. It seems there are more hang-gliding conditions this year than kite-surfing conditions, which is not what I’d hoped.
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Tuesday, November 4th, 2014 at 11:14 am - - Machining 1 Comment »

I’ve begun various arduino experiments here in DoESLiverpool, which necessitated moving closer to Adrian’s desk on account of knowing no electronics, there being bugger all adequate instructions on how to wire anything up.

iotfruit

Oh yes, he says, obviously VCC is standard code for “power in” for that red square in the centre-left of the picture that contains a microSD card and requires 3.3V of power — even though this is nowhere stated and all the other circuits in this kit use 5V.

Whatever.

It’s not much of a standard when this is immediately contradicted by the thin thing on the bottom left of the picture (called a Jeenode) which labels its corresponding power pin “PWR“, and the low-power bluetooth blue board on the middle of the white panel which calls its power pin “VIN” for “voltage in”, and the red “real-time clock” thing above it which labels its power pin “5V“, which is so much better because: (a) it is immediately understandable by the man in the street, (b) it conveys the crucial information about the level of voltage required, and (c) it uses one fewer character when the labels are already too small to read without a magnifying glass which I do not have but should get.

So WhyTF do they use any of those other codes?

Ah, you might say, wouldn’t your logic require sometimes writing “3.3V“, which is four characters?

Well, no, actually, because the thing in the middle with the USB plug has two power pins on it, one called “5V” and the other called “3V3“, so they were forced to be sensible.

Of course, I’ll be proved wrong when I find a peripheral that contains both “VCC” and “VIN” pins.

Don’t get me started on all the other pin names, especially on the different arduino boards on which they’ve failed to mark out these all-important SPI pins that are either pins 11, 12 and 13, or pins 4, 1 and 3, or pins 51, 50 and 52, or you have to look it up on this handy diagram if you have a Jeenode.

I think electronics got off to a bad start from the very beginning when they decided that current flows in the opposite direction to the electrons. From then on it’s been seven human generations of miscodings and mistakes that have been adopted as conventions resulting in something not unlike spelling in the english language — ie you can’t see the problem once you have gotten used to it.

Wednesday, October 29th, 2014 at 8:28 pm - - Machining 2 Comments »

I’m back at work on my SLAM based laser scanner. Failure is not an option. Yet it feels like there is a real risk of it.

One of the steps in the process is to displace all the inertial unit measurements by a small error term in order to minimize the error in the correspondences.

More simply, we have a matrix A of height m and width n (m>n), a column vector b of height n, and we want to fill in the column vector x of height m such that A x = b is almost true.

There is no exact solution, so we look for a least squares answer, where (A x – b)^2 is minimal.

Luckily, there is a function scipy.linalg.lstsq() which does the job.

Let’s consider a simple example of a 3×2 matrix:
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Thursday, October 23rd, 2014 at 4:31 pm - - Machining, University 1 Comment »

I just got myself a new laptop and installed Ubuntu-Linux on it. Scares the hell out of me the speed with which I got it up and running. I am now lost in a sea of code. It’s like walking into a public library after you’d been out in the sticks for a month with only two dog-eared issues of the Reader’s Digest to keep you company. There’s almost too much here. I want to read all of it. And any book or manual you do pick up and spend an hour with means there’s another ten thousand you’ve not picked up that you should have been reading.

Anyways, while doing my apt-cache searching stuff for stuff, I noticed stimfit – Program for viewing and analyzing electophysiological data show up in the search for scipy.

It appears to take datasets of electo-potential readings from a single neuron at every tenth of a milisecond and then fit exponential decay curves [the thick grey line] to selected sections from the (negative) peak to the baseline.

stimfit

A bit like a temperature sequence, eh?

Oh, and it has a funky Python shell built into it to help you automate the analysis functions. What’s not to like?

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Wednesday, October 22nd, 2014 at 3:02 pm - - Weekends

How does anyone hold down a proper job?

OLYMPUS DIGITAL CAMERA
I just got a “Hello world” program working out of a pair of Jeenodes kicking around in the cardboard box left over from the Housahedron project before they migrated to Berlin. Of course, there was no documentation for how to plug in the interface into the Jeenode, and I had to get Adrian’s help.

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Tuesday, October 21st, 2014 at 1:36 pm - - Machining 1 Comment »

To make up for my disorganization with the data collected at my house (in that it got lost, was not frequently sampled enough and didn’t happen over the winter), I got this lovely temperature sequence from megni to analyze for my exponential decay theory which took a reading inside their cottage every 60 seconds.

tempseqraw

My theory is that by fitting exponential decay curves to the data I would get some invariant values relating to the fabric of the building that would change when you improved its insulation characteristics (eg draught-proofing a window).

The first step is to chop of this data into the sections where the temperature is dropping down. It took a while to get some working code, but it came like this:

gw = 30   # half an hour
sampleseqs, sampleseq = [ ], None
for i in range(gw, len(samples):
    vd = samples[i-gw][1] - samples[i][1]  # positive if past temp higher
    if vd >= 0:
        if not sampleseq or vd >= mvd:     # restart seq at bigger difference
            sampleseq = samples[i-gw:i]
            mvd = vd
        sampleseq.append(samples[i])
    elif sampleseq:
        sampleseqs.append(sampleseq)
        sampleseq = None

tempseqrawdeclines
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