odd number

A simulation of the Poisson process, built using Processing.

The process models random events occuring in continuous time given that:

1. Events occur on their own
2. The average rate of events happening remains constant
3. Future events have nothing to do with ones which have happened

A process has average rate such as per minute. Number of events in t minutes is the discrete random variable X, where . The time you have to wait between events follows an exponential distribution .

The simulation works by obtaining a waiting time between each event, through making independent observations on the random variable . We can do this by solving:

where u is a random observation on the uniform distribution U(0,1). With the exponention distribution this means solving

which ends up with

Each time an event is fired, t is recalculated.

Western brands converted to Arabic in Abu Dhabi

Here’s the binomial distribution 80′s style. Each click generates a series of n independent Bernoulli trials resulting in a random variable Y which is the number of successes. The probability function of Y is:

where

This painting is derived from a finite projective plane of order 3.

Number of points and lines . Each line is incident with n+1=4 points, each point is incident with four lines. The projective plane corresponds to this cyclic block design which has thirteen varieties arranged in thirteen blocks of size 4.

There are small, persistent landslides from these cliffs every few minutes. Sometimes they can’t be seen, but you can hear the hissing noise. This is the result.

The beach has many blocks of stone containing fossillised shells. Lots of these stones have live barnacles and limpets firmly attached. It’s hard to tell what they think of their ancestors, but not that much seems to have changed over time.

I did two pictures today, but the other one looked a bit funny. It had pencil scribbles unfortunately near where you’d expect wibbly stuff.

Here’s the unfunny, serious, watercoloury one. I think the blue added at the end sorted things out a bit.

I’ve just signed up for a new course, Applications in Probability.

The word “probability” has a contrary provenance. Wikipedia says:

According to Richard Jeffrey, “Before the middle of the seventeenth century, the term ‘probable’ (Latin probabilis) meant approvable, and was applied in that sense, univocally, to opinion and to action. A probable action or opinion was one such as sensible people would undertake or hold, in the circumstances.

The most obvious example of chance as the subject of a piece of work is Duchamp’s Three Standard Stoppages: three one metre long threads are dropped onto pieces of cloth, which are then chopped up according to where the threads have fallen. Duchamp wrote the instructions of the work’s making on the side of the box – the process of its creation was as important as the resulting artefact. Maybe it’s not a readymade, but an unreadymade.

Any work that incorporates real-world processes is invoking chance – but not necessarily in the plain sense of randomness, or as a subject in itself. If there is something as obvious as the roll of dice, then it’s about unlocking and making visible the natural processes which are the subject.

Process art employs natural forces, and its practitioners seem to have a passing interest in chance and serendipity.

Generative art uses randomness, often as a seed for the algorithmic process, either at the start or within each iteration. But I don’t think chance is (normally) its subject – rather, it’s a conveniently available unspecified event to be exploited.

Chance sits at a particular meeting point between knowledge and ignorance. We can say something quantitive about an outcome, especially over a long period of time if it involves repeating the same event. If it’s equally likely outcomes, then this quantity can be worked out by counting (the theoretical approach). Or we can establish the probability of outcomes from empirical observation, and accumulation of data.

But if we need probability, then we either can’t have knowledge of all the factors contributing to an outcome, or there are simply too many factors to calculate effectively. Probability and chance are admissions of failure – we don’t know what’s going to happen, but we can say how many times something might happen as opposed to not.

Whatever, it’s apparent that predictions and their relationship to outcomes are at the heart of human interests, from gambling to the enlivening possibility of failure in a performance. I’m unsure of its validity as an area of artistic exploration though. Maybe it’s simply a tool to be employed.

I went to Abu Dhabi recently. Here’s the view looking from the flat where we were staying:

The light changed all the time – so the detail on the buildings in the distance came and went.

Here’s one from the public beach – a slightly more careful approach: