Characterization of raw data: image of adc vs col

[manuelakuhn]

@Wunderer wants to create an "image" of the raw data but instead of using raw vs col she wants to use adc vs col.
How does that work?

We would like to modify the "image" method of raw so that it has dimensions
x = columns (as before)
y = ADCs (so only 7 rows, not 14xx)
This amounts to generating a new histogram (one for each coarse, each fine, each gain for both sample & reset)
when I copy the raw/image.py routine, and replace plt.imshow(data) by a plt.hist2d(self._data["ADC'], self._data["col"], .) I get an error that 'self' is not defined ... so I can't trivially do this myself yet.

or worded as algorithm: for either sample/reset, and for either coarse/fine/gain (having 6 separate plots created is fine)

• build a 2d histogram with columns as X and ADC number as Y
• display the histogram (ideally with a color bar, and labeling)