Graph Centrality

[jeffreyyancey]

Title: Add graph centrality algorithms for computing central and median nodes

Description:

This pull request introduces new algorithms to compute the central and median nodes in a weighted graph. It includes the implementation of the Floyd-Warshall algorithm for all-pairs shortest paths and functions to calculate eccentricity and harmonic closeness centrality. The code is well-documented, includes comprehensive type hints, and contains doctests for various graph scenarios to ensure correctness.

• [X] Add an algorithm?
• [ ] Fix a bug or typo in an existing algorithm?
• [X] Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
• [X] Documentation change?

Checklist:

• [X] I have read CONTRIBUTING.md.
• [X] This pull request is all my own work -- I have not plagiarized.
• [X] I know that pull requests will not be merged if they fail the automated tests.
• [X] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• [X] All new Python files are placed inside an existing directory.
• [X] All filenames are in all lowercase characters with no spaces or dashes.
• [X] All functions and variable names follow Python naming conventions.
• [X] All function parameters and return values are annotated with Python type hints.
• [X] All functions have doctests that pass the automated testing.
• [X] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• [ ] If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

Commit:

Initial commit: Implement graph centrality algorithms for weighted graphs

• Added core functionality to compute central and median nodes in a weighted graph using:
  • Floyd-Warshall algorithm for calculating all-pairs shortest paths
  • Eccentricity for determining the central node
  • Harmonic closeness centrality for determining the median node
• Developed utility functions to handle graph data and validate positive edge weights
• Included extensive doctests to verify functionality across various graph types:
  • Single-node, disconnected, fully connected, cyclic, and directed acyclic graphs (DAGs)
• Improved code modularity and readability by refactoring functions
• Enforced code style and consistency with ruff and black formatting
• Documented the algorithmic approach, complexity, and example applications in the module docstring