ctfr 0.1.0.dev4

Efficient toolbox for computing combined time-frequency representations of audio signals.

ctfr

Efficient toolbox for computing combined time-frequency representations of audio signals.

Table of contents

• Documentation
• Installation
  • Using PyPI
  • Development mode
• Citing

---

Documentation

See the ctfr documentation for more information about the package, including usage examples and the API reference.

---

Instalation

Using PyPI

The latest stable release is available on PyPI, and can be installed with the following command:

pip install ctfr

Note that this doesn’t install the plotting dependencies. To install with plotting included, run

pip install ctfr[display]

Development mode

If you want to make changes to ctfr, you can install it in editable mode with development dependencies by cloning or downloading the repository and running:

make dev

or

pip install -e .[dev]

When installing in this mode, Cython is a build dependency. If you have trouble running Cython, see this guide.

Note: When developing, .pyx files need to be recompiled in order for changes in them to take place. This can be done by running

make ext

or

python setup.py build_ext --inplace

---

Citing

If you use ctfr in your work or research, please cite following paper:

To be added.

Also, if you use a speficic combination method, please cite the corresponding paper(s). You can find the references for a specific method by running:

>>> ctfr.cite_method("fls")
M. do V. M. da Costa and L. W. P. Biscainho, “The fast local sparsity method: A low-cost combination of time-frequency representations based on the hoyer sparsity,” Journal of the Audio Engineering Society, vol. 70, no. 9, pp. 698–707, Sep. 2022.