Fuzzy trajectories for each subject

Hi Phil,

I have revised the code to include an estimate of the error in the probability distribution of any given image to contain a lens. Each subject image which is being classified now has a distribution of probabilities (to contain a lens), instead of the single probability it used to have. The code makes a Monte-carlo determination of this distribution by updating a large number of probability trajectories for each subject image, and each update makes use of multiple noisy realizations of the agent's confusion matrix.

I have reverted to an old logging.py file, since I did not understand some of the new code that was checked in (I think you got rid of the false negative rates which I wanted to see). Feel free to ignore the logging.py file in this case.

I am still working on the documentation.

Cheers,
Surhud