morseframes 0.1.0a2

Morse sequences, reference maps, Morse complexes, and Morse-based persistent homology

MorseFrames

MorseFrames is an experimental C++ and Python library for working with Morse sequences, reference and coreference maps, Morse complexes, and Morse-based persistent homology.

Documentation is available at https://morseframes.readthedocs.io/en/latest/. New readers may want to start with the overview, quick start, and minimal examples. Please see CONTRIBUTING.md for development instructions and CITATION.cff for citation metadata.

The manuscript source for the Morse-frame persistence paper is kept outside this public software repository. When a public preprint or published version is available, the documentation will link to it.

The current codebase contains:

• a header-only C++ core for filtered simplicial complexes;
• several Morse sequence strategies, including saturated, F-Min, F-Max, same-level reduction, plateau-greedy, and flooding variants;
• reference and coreference map construction;
• Morse-reference and Morse-coreference persistence;
• ordinary persistence for validation;
• prime-field coefficients F_p in the Python interface;
• a Python API with a pure-Python fallback and optional nanobind backend;
• an experimental GUDHI-facing adapter for Simplex_tree;
• tests, examples, and reproducible benchmark drivers.

Strategy terminology follows the paper: flooding strategies are filtration-monotone F-sequences, while f-max and f-min are global seed-and-expand F-sequence builders. All exposed strategies keep regular pairs inside one filtration level, so plateaus are handled without perturbing the filtration values.

The GUDHI adapter is included to make future upstream integration easier. It should be considered experimental, but the current native benchmark signal is encouraging: the optimized direct Simplex_tree path is near parity with GUDHI persistent cohomology on the tested flag complexes, and faster on the tested grid plateau complexes for the F-Min, F-Max, and same-level strategies. The generated tables in docs/native_gudhi_*_table.tex record the current numbers and the reproduction commands live in docs/benchmark_reproduction.md.

Build the C++ Tests

cmake -S . -B build
cmake --build build
ctest --test-dir build --output-on-failure

When the C++ GUDHI and Boost headers are available, CMake also builds optional GUDHI adapter tests, examples, and benchmarks. They can be supplied explicitly:

cmake -S . -B build \
  -DMORSEFRAMES_GUDHI_INCLUDE_DIR=/path/to/gudhi/include \
  -DMORSEFRAMES_BOOST_INCLUDE_DIR=/path/to/boost/include

To skip the optional GUDHI tools:

cmake -S . -B build -DMORSEFRAMES_BUILD_GUDHI_TOOLS=OFF

Python Quick Start

The current public alpha is available on PyPI:

python3 -m pip install "morseframes==0.1.0a2"
python3 -c "import morseframes as mf; print(mf.__version__, mf.cpp_backend_available())"

For development from a source checkout, install in editable mode with the test dependency as well. This uses scikit-build-core and nanobind to build the optional native backend:

python3 -m pip install -e ".[dev]"

Example:

import morseframes as mf

complex_ = mf.FilteredComplex.from_simplices([
    ([0], 0.0),
    ([1], 0.0),
    ([0, 1], 1.0),
])

sequence = mf.compute_morse_sequence(complex_, algorithm="f-max")
references = mf.compute_reference_map(complex_, sequence)
diagram = mf.compute_morse_persistence(complex_, sequence, references)

print(diagram.finite_barcode())
print(diagram.essential_barcode())

Prime-field coefficients are available by passing a prime modulus:

diagram = mf.compute_morse_persistence(complex_, algorithm="f-min", modulus=3)

Python Tests

MORSEFRAMES_DISABLE_CPP_BACKEND=1 python3 -m unittest discover -s python/tests -p "test_*.py"
python3 python/examples/quickstart.py

The pure-Python fallback can still be exercised directly from the source tree without building the native backend, or by disabling the backend explicitly:

PYTHONPATH=python python3 -c "import morseframes as mf; print(mf.cpp_backend_available())"
MORSEFRAMES_DISABLE_CPP_BACKEND=1 python3 -m unittest discover -s python/tests -p "test_*.py"

Documentation

Read the Docs is configured through .readthedocs.yaml. The public documentation is available at https://morseframes.readthedocs.io/.

The documentation can also be built locally:

python3 -m pip install -r docs/requirements.txt
sphinx-build -b html docs docs/_build/html

• docs/python_api.md summarizes the public Python API.
• docs/project_overview.rst explains the main objects and computation model.
• docs/minimal_examples.rst gives small copy-paste examples.
• docs/inspecting_morse_data.rst shows how to inspect sequences, maps, Morse complexes, and barcodes.
• docs/strategies.md explains the Morse sequence strategies and terminology.
• docs/python_prime_field_tutorial.md explains persistence over F_p.
• docs/cpp_complex_view_api.md describes the C++ complex-view interface.
• docs/gudhi_contribution_design_note.md summarizes the experimental GUDHI adapter.
• docs/benchmark_reproduction.md explains how to regenerate benchmark tables.
• Generated benchmark table fragments live in docs/*_table.tex; the scripts that regenerate them live in tools/.

Citation

If you use MorseFrames in academic work, please cite it using the metadata in CITATION.cff.

Contributing

Development and testing instructions are collected in CONTRIBUTING.md. Release notes are collected in CHANGELOG.md.

Development note

Parts of the implementation, tests, benchmarks, examples, and documentation were developed with assistance from OpenAI Codex. All mathematical choices, algorithmic design, validation, and released code were reviewed by the authors.

Status

This is research code. The public API is useful for experimentation, but names and interfaces may still change while the paper and GUDHI integration mature.