Filter*ByAlignmentConfidenceJob: better alignment plots

[Icemole]

The alignment plots were previously useless when dealing with values outside of the disposed range, such as when aligning with NNs (negative alignment scores). Now the X axis range entirely depends on the distribution.

Also added a custom plot for the recording alignment scores, since the Y axis label was wrong (it said "segments" instead of "recordings").

Notes:

1. The previous plots would be irreproducible. However, for me this is not an issue due to the "cosmetic" nature of the change.
2. If the job is not triggered with remove_dnf_alignments=True (which is the recommended value anyway, and only set to False for retrocompatibility purposes), the graph might look bad (e.g. X axis extending from 0 to 1e+36, one big bar at [0, 200] and then nothing else). However, since I use NN-based alignments, it does already look bad to me for most of my filterings (just one histogram bar at 0 and then an empty graph), so I believe this would already be an improvement. To circumvent this, the user should set remove_dnf_alignments=True.
3. To fix (2), we can think of setting remove_dnf_alignments=True by default always. The alignments that did not finish aren't in the alignment caches anyway, so these being included here only pollutes the plot. What do you think?

[michelwi]

Do we not have a separate Job to plot alignment scores that is much more versatile and configurable?

i6_core/mm/alignment.py

Line 429 in b19149e

class PlotAlignmentJob(Job):

So instead of changing the suboptimal plotting function of the filter jobs to something slightly-less-but-still-not-so-good , I would just disregard the plots they produce and use the dedicated plotting job..?

Maybe instead if this PR, add a parameter filter_list to the PlotAlignmentJob and use the self.out_kept_recordings