address issues 20 and 22

[dantzert]

This pull request introduces several enhancements and refactors to the testing infrastructure, package metadata, and example data scripts for the modpods project. The main focus is on expanding and standardizing support for multiple optimization methods (Bayesian, Differential Evolution, and Dual Annealing) across all test suites, updating package metadata for PyPI compatibility, and providing a reproducible data-fetching script for USGS Delaware River data.

Testing and Optimization Methods:

• Refactored all test scripts (test_bayesian.py, test_integrated.py, test_camels.py, and tests/test_modpods.py) to systematically test and compare multiple optimization methods (bayesian, differential_evolution, and dual_annealing) instead of only compass search or Bayesian optimization. Tests now report and compare R² scores across all methods. [1] [2] [3] [4] [5] [6]
• Updated test fixtures in tests/test_modpods.py to provide models trained with each optimizer, and added corresponding validation tests. [1] [2] [3]
• Improved test output for easier comparison of optimization performance, including best/worst method and improvement statistics. [1] [2] [3]

Package Metadata and Build System:

• Added and updated pyproject.toml and modpods.egg-info files to specify dependencies, Python version, project metadata, and build configuration for PyPI distribution. [1] [2] [3] [4]

Data and Documentation:

• Added a new script testing_data/pull_usgs_delaware.py that fetches and processes USGS Delaware River gauge height data for testing, including data normalization and plotting. The script demonstrates reproducible data fetching without committing large files to the repository.
• Updated IDEA.md to reference enhancements tracked in the project’s GitHub issues.

Minor/Other:

• Adjusted file paths for test data in test_camels.py to ensure correct loading from the tests/data directory.
• Added a backup file modpods.py.bak (purpose not specified).
• Minor updates to egg-info index files.

These changes collectively improve the robustness, maintainability, and reproducibility of the modpods package and its test suite.