boiling

1. Standing by the stove the other night, waiting for a kettle of water to boil - as it does, starting from the near-silent rattle through the increasing racket, and the whistle starting, and all the other noises that accompany that moment, I had the distinct feeling that I was hearing the big chromatic crescendo at the end of Prokofiev's great D-minor Toccata, one of my favorite piano pieces. It's not that I was fooled - this was not an auditory deja trompé, but something similar - but I've never felt a piece of familiar music so strongly evoked by some random physical event. It was definitely primed by having listened to that piece something like 10 times in the past week. Now whenever I hear that piece, when it gets to the silence at the end before the crescendo, I will think of a boiling kettle.

2. Horrible problems with the paper I've been working on and hoping to have submitted in a matter of days. A big part of the paper - the way that I interpret the data, basically - is a set of relatively simple contrast perception models which I run through the experiment as tests of different hypotheses. I had calibrated these to a set of human thresholds, which I was never quite comfortable with for various reasons, but that's the way I had done it; as a final touch to a figure, I decide to go and generate thresholds estimates for the 'best' model, to plot against the human data, just to show how similar they are, and when I go to do this, the model starts giving me imaginary numbers, which is bad.

By the time I figured out what was wrong - it wasn't really a problem, I was just not using my code properly - I had decided that calibrating the model to the thresholds for my humans was probably a bad idea, because the way I measured the human thresholds was kind of weird, and I could be sure of simulating these properly, so I should just use some standard thresholds. Why not? Nobody is going to argue with a standard CSF. So I plug a standard in and - and I'm going to note here that every time I do something with this model, I have to go and recompute the simulations, which takes hours - and it all goes haywire. The model that 'works', and that's consistent with all these nice facts that I've lined up and made a nice case out of, still works, but depending on how I implement the change in sensitivity, the alternatives either perform horribly - which you'd think is okay, but really doesn't look plausible, just makes it look like I haven't given them a fair chance - or they come out reasonably similar to the favored model.

So, I have to be fair, at the same time that I don't want everything to fall apart. I am certain that things work the way I think they do, and I'm prepared to be wrong, but if I'm wrong then I don't understand how I'm wrong. And building evidence either way progresses in these multi-hour steps in between which I'm sitting here with a stomach ache because I'm afraid that I'm going to wind up with evidence that my experiment isn't actually that good at discriminating these different models.

The problem seems to be in the low-frequency filters; the lowest frequency filter is basically four points in the Fourier domain, and it happens to take up a disproportionately huge amount of image contrast, so the 'not working' models tend to be uniformly low-pass in the simulation, which I know is not fair, because it's all because of that low frequency channel. So I figured that, since these are 'sustained' stimuli, I would be justified in just taking out the lowest few channels and leaving the top 5 or 6 band-pass channels - one thing here being that I'm not willing to go back and redesign everything to the point where we have low-frequency DC-sensitive channels. But then when I just have the mid-to-high frequency channels, the three models are too similar, which I don't like either, and which I know is just because I'm now allowing the low s.f. to get through. And I also know that this version, even though it has the 'standard' CSF, doesn't really because the lowest channels are shut off. So I turned them back on and changed the gain to the CSF, which I realized I had wrong the first time because....

Anyways, you see what I'm doing - changing more than one thing at a time, and making mistakes because I'm rushing it. This just prolongs everything, because every change, or every attempt to figure out what the effects of a change are, and every mistake, takes many hours to evaluate.

Anyways, high irritation and anxiety.