Add support for faceting by both subject ID and antigen-isotype in `plot_predicted_curve()`

[Kwan-Jenny]

Description
This issue proposes extending the plot_predicted_curve() function to support dual-axis faceting: by participant ID (rows) and by antigen-isotype (columns) using facet_grid() instead of facet_wrap(). This update is based on advisor feedback during the 07.30.2025 meeting and is intended to improve visualization of antibody response dynamics across both subjects and antigen-isotype combinations.

Motivation

• Users need to compare IgG and IgA response patterns within the same individual.

• This layout will make it easier to examine temporal correlation between isotypes and identify heterogeneity in immune response patterns.

• Builds on recent support for multiple ID faceting and enhances interpretability of individual-level plots.

Planned Changes

• Refactor internal faceting logic from facet_wrap() to facet_grid() when multiple antigen-isotype combinations are provided.

• Add argument(s) (e.g. facet_by_isotype = TRUE) to toggle this behavior.

• Maintain backward compatibility with current single-axis faceting.

• Update visual examples and test cases for:

  • One subject with multiple antigen-isotypes

  • Multiple subjects with multiple antigen-isotypes

Related Tasks

• Expand test-plot_predicted_curve.R to cover the new dual-axis faceting scenario.

• Add new test example(s) for 2×2 and 3×2 facet grids.

• Update examples-plot_predicted_curve.R to demonstrate the new functionality.

• Revise plot_predicted_curve() documentation to include usage of dual faceting.

Background
This feature was discussed during the July 30th check-in meeting with Dr. Kristen Aiemjoy and Dr. Ezra Morrison. Kristen specifically suggested allowing side-by-side comparison of IgG and IgA curves for the same subject to assist with evaluating correlation in response timing across isotypes.