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etc...

Revert "REL: bump version to 0.8.0"

See merge request !2

This reverts commit b2fcdf0c

Revert "ENH: avoid declaring a new template if the detection is the template itself"

See merge request !1

This reverts commit 392e7f39

With low resampling rate it can happen that a template detects itself with
a very low correlation-coefficient. This patch avoid the creation of an
additional template

Update plotTimeline.sh to also plot gaps in the "scientific" theme if a gap-file "gaps_scan.dat" is given in the results folder. The gap-file is in the format of obspy_scan's --print-gaps optipon. 

(for instance, it avoids inserting catalog events into the combo catalog if
they were actually detected)

(switch b/w transfer-function-based & sos-based filtering)

(i.e. better deal with data masks of Stream/Trace objects)

... as presented in our paper as a post-processing step to reduce the weight of
impulsive waveform features on the cross-correlation coefficient

(but this doesn't include the machine learning itself... this will be provided in due time)

+ some tweaks of the old approach

(particularly to make the Basel script run smooth)

+ set name of the tool to TMT
+ improve descriptions of modules and scripts
+ clean up files in `scripts` dir

New post-processing command line argument plot-FMD
+ overhaul whole FMD plotting routine
+ outsource FMD parameter value estimation into a class
+ helper class to read/write FMD parameter value estimates to/from a json file
   (useful to reload bootstrap estimates based on a large number of iterations
    --> no need to repeat bootstrapping when changing only the plot binning,
          for instance, while the events are the same and the configuration is similar)

Supported Mc estimation methods: MAXC, MBASS, MBS, FIX.
These and more settings can be set up in the last section of `postprocessing.py`
(e.g., the time range, the binning for Mc estimation, the Mc correction factor,
the plot binning, and the bootstrap iterations).