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Installation

Requirements

  • Python 3.11 or later
  • NumPy >= 1.24.0
  • pandas >= 2.0.0

Optional dependencies:

  • rich: For pretty-printing results

Install from PyPI

Once released, install rthor using pip:

pip install rthor

Or with uv:

uv add rthor

To use our pretty-printing functionality (rthor.print_results) you also need the optional rich dependency:

pip install 'rthor[rich]'
# or with uv
uv add rthor --extra rich

Install from Source

For the latest development version:

git clone https://github.com/MitchellAcoustics/rthor.git
cd rthor
pip install -e .

Or with uv:

git clone https://github.com/MitchellAcoustics/rthor.git
cd rthor
uv pip install -e .

Development Installation

To contribute to rthor, install with development dependencies:

git clone https://github.com/MitchellAcoustics/rthor.git
cd rthor
uv sync --group dev

This installs additional tools for:

  • Testing (pytest, pytest-cov)
  • Documentation (mkdocs, marimo)
  • Linting (ruff, ty)
  • Building (build, twine)
  • Pre-commit hooks (prek)

Set up pre-commit hooks

uv run prek install

This configures hooks for:

  • Code formatting (ruff)
  • Type checking (ty)
  • TOML sorting
  • Markdown linting
  • Trailing whitespace removal

Verify Installation

import rthor
print(rthor.__version__)

# Run a quick test
import numpy as np
matrix = np.array(
    [
        [1.00, 0.90, 0.60, 0.30, 0.60, 0.90],  # Var 1
        [0.90, 1.00, 0.90, 0.60, 0.30, 0.60],  # Var 2
        [0.60, 0.90, 1.00, 0.90, 0.60, 0.30],  # Var 3
        [0.30, 0.60, 0.90, 1.00, 0.90, 0.60],  # Var 4
        [0.60, 0.30, 0.60, 0.90, 1.00, 0.90],  # Var 5
        [0.90, 0.60, 0.30, 0.60, 0.90, 1.00],  # Var 6
    ]
)
result = rthor.test(matrix, order="circular6")
rthor.print_results(result)

                                   RTHOR Test Results
               1 matrix • 6 variables • 72 predictions • 720 permutations
╭──────────────┬────┬───────┬────────────────┬──────────────┬──────────────┬───────────╮
│ Matrix       │    │    CI │ Interpretation │ Significance │    Satisfied │  Violated │
├──────────────┼────┼───────┼────────────────┼──────────────┼──────────────┼───────────┤
│ [1] Matrix 1 │ ✓  │ 1.000 │ Excellent fit  │   p<.05 *    │ 72/72 (100%) │ 0/72 (0%) │
╰──────────────┴────┴───────┴────────────────┴──────────────┴──────────────┴───────────╯
               ℹ️  Higher CI values indicate better fit (range: -1 to +1)

Next Steps