Censor correction TODO list

[HagaiHargil]

1. Generate a distribution of the number of photon per laser pulse. To that end, simulate a laser signal and distribute all events inside it. This shouldn't take more than an hour using searchsorted.

2. Temporal structure: With the simulated laser pulses, obtain a histogram of the photon arrival times with 16 bins. Most "binary words" should be sparse - a single 1 bit in all 16 bins, representing a lone photon being detected shortly after the laser pulse hit the sample. Two hours.

3. Using the edges of the generated histogram, sum all relevant laser pulses - i.e. the pulses that belong to this specific pixel. This should generate a histogram that expresses the fact that 50 of the laser pulses generated no photons, 25 of them generated one, etc.

4. Now comes the look-up table for our cumulative binary words. The histogram generated in 3 will be compared to that look-up table, and will be replaced by the most suitable entry in that table. To generate this table we need a scikit-learn framework capable of being fed 16 bit words as input, and an integer number corresponding to the number of photons as its output.