# Grower Skill Tree Feature Measurement
The `capability-feature-measurement` crate provides a suite of traits and data structures for measuring and evaluating tree-like configurations. Ideal for applications requiring in-depth analyses of node-based data structures, it allows developers to statistically analyze parameters such as tree depth, breadth, density, sub-branch ordering, and more. This crate is versatile, catering to various tree-like structures, including custom skeletons, and offers the capacity to juxtapose actual versus expected configuration outcomes.
## Key Features
- **Complexity Measurement**: Determines the overall complexity category (`Simple`, `Balanced`, `Complex`) the tree might belong to.
- **Depth and Breadth Analysis**: Measures maximum depth and node child distribution across the structure.
- **Density Evaluation**: Assists in understanding leaf density and variant distribution among tree nodes.
- **Weighted Branching and Symmetry**: Evaluates child node counts against mean and variance-based expectations; measures balance or asymmetry.
- **Level-specific Metrics**: Captures aggregate node statistics at defined levels and highlights potential skips.
## Usage
To use this crate, implement the specified traits for your data structures (e.g., `Skeleton`, `StringSkeleton`) that represent tree configurations. Each implementation facilitates precise measurements, ensuring conformity or highlighting discrepancies with expected behaviors or configurations.
Add the crate to your `Cargo.toml`:
```toml
[dependencies]
capability-feature-measurement = "0.1.0"
```
Implement the necessary traits from the crate to enhance your data structures with tree measurement capabilities, thereby aiding in tree configuration analysis applications.
---
*This README.md file was generated by an AI model and may not be 100% accurate, however, it should be pretty good.*