This changes how features are specified to `Targets`,
in a way that will mesh with `parse_alignments`.

Slightly altered specs for `feature_parse_specs` as
described in docs for `Targets`. This allows the
`feature_parse_specs` to also specifying filtering criteria.

Then updated code to better check for correct targets / features
in `feature_parse_specs` in `Targets.__init__`, and removed
redundant code from `Targets.parse_alignment_cs`.

Finally, added the feature parse specs YAML file for the RecA
example and updated the corresponding Jupyter notebook.

Now can pass and get `feature_parse_specs` as a YAML
file or a dict.

Edited `regex` matching to handle custom `cs` '<clip#>' ops.

Instead of writing a script to process the '<clipN>' notation, I
decided to stick with just using tuples to designate features
that have clipping. This makes counting mutations and clipping
easier.

Return columns suffixes `_cs`, `_clip5`, and `_clip3`
in `Targets.parse_alignment_cs`.

…arse into parse_alignment

Previously `Targets.parse_alignment_cs` parsed **all**
features; now it only parses the ones in
`feature_parse_specs`.

Previously the `feature_parse_specs` and the returns
from `parse_alignment_cs` included `target_clip5` and
`target_clip3`. However, this is redundant with the feature-
level clipping information, and so has been removed.

The query clipping is retained as that is not redundant
with feature-level clipping.

Still need to add more rigorous tests.

…arse into parse_alignment

There are new vesions of `pandas` (0.25.1)
and `plotnine` (0.6.0). Use those, and also
update notebooks to have output from these;
in particular the new `pandas` no longer shows
the index in bold in data frames displayed in
Jupyter notebooks.

Only major change is that mutations from ambiguous
are **not** counted as mutations in mutation strings.

Otherwise just streamline code.

Likely has bugs, but general outline is there.

Fixed some formatting, reverted making
`Targets.parse_alignment_cs` private; it's now public
method again. We can re-visit whether to make it public
later.

Simplify the initialization of `Targets`
by modularizing operations like filling the defaults
of `feature_parse_specs` and getting the names of
features to parse in their own methods.

Also, eliminated some redundant parameter checks that
were confusing to read in the code.

Updates to `feature_parse_specs` input to `Targets`,
and docs for `parse_alignments`.

Specifically:

  - `parse_alignments` has different return described and
    can write CSV.

  - Previously there was a single `clip_count` in
    `feature_parse_specs`; now it is `clip5` and `clip3`
    separately. Example notebooks updated to reflect this.

Previously, the `multi_align` option to
`Targets.parse_alignment_cs` was ignored and
secondary alignments were not filtered.

The new `Targets.parse_alignment` is fully implemented
except for the `Targets._parse_single_Alignment` method
it utilizes.

No testing yet.

The new `Targets.parse_alignments` is fully implemented
and tested against `Targets._parse_alignments_csv` and
for consistency in writing CSVs versus returning data frames.

It still needs more testing for correctness of output and
illustrative example.

Also, added a parameter to `Targets` explicitly permittting
the return of mutations / sequences of features with clipping;
otherwise this is disallowed as it can give confusing results.

In addition to minor doc tweaks and slight code
cleaning, implemented testing of `Targets.parse_alignment`
in `test_Targets_parse_alignment.ipynb`.

Fixes this:
#20 (comment)