sklearn -> scikit-learn

v1.0.2

Change branch name in publish action

Version 1.0

This is a major version update of MELD, and it will break backwards compatibility with previous workflows due to a significant change in nomenclature accompanying our revised manuscript forthcoming in Nature Biotechnology.

You can find an up-to-date version of our article on BioRxiv with the revised language. The main difference is that we have dropped the "RES" and "EES" language for a more rigorous probabilistic interpretation inspired by an update to the algorithm made during the review process.

The output of meld.MELD().fit_transform is now referred to as the sample_densities and is the output of a kernel density estimation of each sample over that cell similarity graph. We then calculate the ratio of these densities using meld.utils.normalize_densities to calculate sample_likelihoods.

This framework reflects the interpretation of the MELD algorithm as a kernel density estimation over a graph. The tutorial and documentation have also been updated.

v0.3 - Bugfix

Fixes get_cmap import on init

Trigger PyPI release

Merge pull request #39 from KrishnaswamyLab/dburkhardt-patch-1

Update version.py

Revised MELD package to accompany revision

This update implements the changes described in the revised version of the manuscript (v3 on BioRxiv).

• The meld.MELD() function now calculateds the EES using the new heat filter and provides a kernel density estimate of each sample over the data graph
• the meld.MELD() function can take in data and build a graph using the Graphtools package
• You only need to pass sample labels and the RES and cell number normalization happens automatically
• Updated parameters and comparison helper scripts

MELD v0.2.3

• Getting coverage to 100%
• Adding support for multidimensional RES
• Improving normalization in spectrogram clustering