Installation¶

PyMixEF supports CPython 3.11, 3.12, and 3.13. The core installation depends only on NumPy and SciPy.

Install from PyPI¶

Create or activate a virtual environment, then install the published package:

python -m pip install --upgrade pip
python -m pip install pymixef

Confirm which interpreter and package version you are using:

python -c "import sys, pymixef; print(sys.executable); print(pymixef.__version__)"
pymixef --version

The distribution name and import name are both lowercase pymixef; the project and documentation use the display name PyMixEF.

Choose optional features¶

Extras keep the numerical core small while making complete workflows easy to install.

Install command	Adds	Choose it when
`pip install pymixef`	NumPy, SciPy, CLI, core models	Your inputs are mappings or NumPy-compatible arrays
`pip install "pymixef[data]"`	pandas, Polars, PyArrow, xarray adapters	You exchange data through dataframe or labeled-array ecosystems
`pip install "pymixef[plot]"`	Matplotlib	You will create plots in scripts
`pip install "pymixef[notebooks]"`	JupyterLab, kernel, notebook validation, Matplotlib	You will run the ten tutorials
`pip install "pymixef[report]"`	Markdown, PDF, and Word report dependencies	You will call `render_report` beyond plain HTML
`pip install "pymixef[validation]"`	pandas and statsmodels	You will run comparison/validation workflows
`pip install "pymixef[docs]"`	Sphinx documentation toolchain	You will build this documentation
`pip install "pymixef[dev]"`	tests, build, typing, lint, release tools	You will contribute to the package

Extras can be combined:

python -m pip install "pymixef[data,notebooks,report,validation]"

Install from a source checkout¶

An editable install reflects local source changes immediately:

git clone https://github.com/kkusima/PyMixEF.git
cd PyMixEF
python -m venv .venv
source .venv/bin/activate
python -m pip install -e ".[dev,notebooks,docs]"

On Windows PowerShell, activate with:

.\.venv\Scripts\Activate.ps1
python -m pip install -e ".[dev,notebooks,docs]"

Verify the installation¶

This smoke test exercises import, formula compilation, the LMM backend, and the structured convergence result:

import pymixef

data = {
    "y": [1.0, 1.4, 2.0, 1.2, 1.8, 2.3],
    "time": [0, 1, 2, 0, 1, 2],
    "subject": ["A", "A", "A", "B", "B", "B"],
}

result = pymixef.fit("y ~ time + (1 | subject)", data, method="reml")
print(result.summary())
assert result.convergence.trustworthy

Offline behavior and packaged resources¶

The library itself is fully offline and emits no telemetry. The wheel includes the py.typed marker, the versioned ModelIR JSON schema, and the stable warning catalog. Documentation links and package installation naturally require network access unless you use local copies or a package mirror.

Troubleshooting¶

No matching distribution found: Confirm that the active interpreter is CPython 3.11–3.13 and update pip. If a package index or mirror has not synchronized yet, install from the canonical source checkout.
A dataframe type is not recognized: Install the data extra and verify that the dataframe library is available in the same environment as PyMixEF.
PDF or Word report export fails: Install the report extra. Markdown and HTML have a smaller dependency path.
A notebook kernel cannot import PyMixEF: Install pymixef[notebooks] into that kernel’s environment, then select that environment from Jupyter’s kernel menu.
A method is unavailable even though installation succeeded: Installation and capability are separate. Query pymixef capabilities or consult the analysis matrix; unsupported methods are refused explicitly rather than silently replaced.

Next¶

Continue to the five-minute quickstart, or go directly to choosing an analysis.