[MODEL] Update data model to include longitudinal pheno data when sessions exist in TSV

[alyssadai]

Changes proposed in this pull request:

• Created subclasses of the "Session" class -> PhenotypicSession and ImagingSession
• Updated logic for bagel pheno command to populate attributes for every session that exists in the input phenotypic TSV
• Updated the existing tests to check at the appropriate level of depth in the output JSONLD files for variables
• Regenerated the reference example_synthetic JSON and JSONLD following the new session-level phenotypic model
• Updated the bagel bids command tests to look at only imaging sessions in the output
• Added example17 which includes no phenotypic sessions (session_id column) in the phenotypic TSV (but this is currently not tested by any tests)

Checklist

• PR has an interpretable title with a prefix ([ENH], [FIX], [REF], [TST], [CI], [MNT], [INF], [MODEL], [DOC]) (see https://neurobagel.org/contributing/pull_requests for more info)
• PR links to GitHub issue with mention Closes #XXXX
• Tests pass
• Checks pass

For new features:

• Tests have been added

For bug fixes:

• There is at least one test that would fail under the original bug conditions.

[github-actions]

Pull Request Test Coverage Report for Build 7184951017

• 70 of 70 (100.0%) changed or added relevant lines in 4 files are covered.
• 2 unchanged lines in 1 file lost coverage.
• Overall coverage increased (+0.004%) to 99.69%

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Files with Coverage Reduction	New Missed Lines	%
bagel/tests/conftest.py	2	88.57%

Totals
Change from base Build 7177602160:	0.004%
Covered Lines:	1286
Relevant Lines:	1290

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💛 - Coveralls

[surchs]

what an excellent example of pair programming 👯

🧑‍🍳