Recent Releases of muvi
muvi - Release Notes for Version 0.1.4
Summary
This release includes enhancements, bug fixes, and new features to improve functionality and usability. Key updates involve fixing renaming issues after reordering, updating plotting defaults, adding new functionalities, and addressing bugs.
New Features
muvi.pl.missingness_overview: Added a function to provide an overview of missing data.
Changes and Improvements
- Allow Factor Sorting by R2 and Renaming by Enrichment Significance: Enhanced factor sorting and renaming capabilities.
- Set Default Renaming to False: Adjusted default to set renaming to false for better control.
- Redefine
n_factorsas Number of Uninformed Factors: Updated definition for accuracy.
Bug Fixes
- Fix Renaming After Reordering: Resolved issues with renaming operations post-reordering.
- Fix Variance Explained Grouped: Fixed unwanted reordering with grouped variance explanation calculations.
- Python
Published by arberqoku over 1 year ago
muvi - Version 0.1.3
Skip normalization for Bernoulli likelihood.
- Python
Published by arberqoku almost 2 years ago
muvi - Version 0.1.2
Release Summary
New Features and Enhancements
Data Handling:
- Deduplicate Indices: Remove duplicate indices to ensure data integrity.
- Data Merging and Normalization: Implement methods for merging (union/intersection) and normalizing data.
- Flexibility in Masks and Samples: Improve handling of missing/extra features in prior masks and allow redundant samples in covariates.
- Integration with
adataandmdata: Updatefrom_adataandfrom_mdatamethods, including support forobs_keyto load observations fromobsmif required.
Plotting and Visualization:
- Group Plots: Introduce group plots to facilitate visual analysis of grouped data.
Model Loading:
- CPUUnpickler: Add
CPUUnpicklerto load models trained on GPU, enabling model compatibility across different hardware setups.
- CPUUnpickler: Add
Feature Set Enhancements:
- Posterior Feature Sets: Allow computing and exporting posterior feature sets using kneed.
Miscellaneous:
- TensorDict: Add
tensordictsupport for more efficient mini-batching. - ASCII Representation: Add ASCII representations of data for better readability and debugging.
- TensorDict: Add
- Python
Published by arberqoku almost 2 years ago