The column map will be more complicated with the need to ingest two
slightly different flat files (_flat_file.csv and _reference_panel.csv)
as discussed in #161 (comment).

I also found myself constantly toggling back and forth between the
separate column_map.tsv and the upload script to figure out how the
columns are being used, so it makes more sense to just hard-code the
column map in the script.

Update column map based on `0906.xlsx_H1_flat_file.csv` in comparison
to the matching Excel file `20240906\ H1N1.xlsx` available on
VIDRL's OneDrive.

Avoid pandas typing issues by just using the Python csv module
to read and write the flat files. Mimics `augur curate` with independent
functions for reading, curating, and writing records.

Doing this in preparation for processing the flat files that includes
human sera measurements. The human serum ids will be parsed the same way
for the flat files to ensure that we use the same standardized id.

Strip the "pool" suffix from the serum strain name, standardize the
egg or cell type, and standardize the serum id.

While looking into this change, I discovered that the strain name used
for the human sera references in H1 and H3 is the egg vaccine strain
regardless of passage annotation. Currently unclear if this is an error
in the flat files or if we've misunderstood the passage annotations for
human sera data. Once we clear this up, we should add some type of
vaccine strain verification so that we can flag mismatches like this
automatically.

In order to include the "assay_date" in the uploaded data, the VIDRL
column needs to be "date" so that it can be parsed within `elife_upload`
as "assay_date".

This is an ugly work around, but it's similar to how cdc_upload handles
the field.¹

¹ <https://github.com/nextstrain/fauna/blob/b133974275ee1ed4e91816c76db6b7616247b6dc/tdb/cdc_upload.py#L58>

Validate records in single flat file. Ensure that the serum
abbreviations map to a single serum strain and all records have the
same test date.

As a side effect, the validated `serum_abbr_map` and `test_date` are
returned to be used for processing the reference panel records in
following commits.

Pull out curation into individual functions that can be shared with the
curation of the _reference_panel.csv file.

Ingests the matching "*_reference_panel.csv" for a provided
"*_flat_file" fstem if the reference panel file exists. The records
parsed from the reference panel file is appended to the same tmp
file that is then passed to elife_upload.py.

This currently includes "extra" records in comparison to Excel files,
where the human sera pool strain is the "test virus" against the other
references. If I strip the `pool` suffix from human sera pool strain,
the measurements are exact duplicates of the measurements for the
matching reference strain. We will need to decide whether or not these
records should be dropped.

Based on comment in Slack¹ that the "e" or "c" suffix in the serum ID
is not a reliable indicator of human serum passage.

¹ <https://bedfordlab.slack.com/archives/C03KWDET9/p1728430958054989?thread_ts=1699914235.686809&cid=C03KWDET9>

Based on meeting with VIDRL, we should only keep homologous titers
for `virus_strain` that includes "pool" suffix. This will act as a proxy
homologous titer for the human serum references. All other virus strains
that include the "pool" suffix are ignored because they are duplicate
data.

Based on meeting with VIDRL, a/b and _1/_2 reference panel files are
created from the same Excel file so they are duplicates while capital
A/B files are separate assays.

So, this changes allows us to check for the a/b and _1/_2 patterns and
ignore the reference panel file if it's a duplicate. This means we
always ingest the a or _1 file but ignore the b and _2 files.