Releases
This is a complete history of cytomulate
releases.
v0.2.0
Welcome to Cytomulate v0.2.0! Hooray! We are not only bringing documentation enhancements, but we are also introducing a new feature for more accurate simulations!
Changes and New Features
- The utilities.univariate_noise_model() method:
Added half_normal option to the noise_distribution parameter
Changed the default noise_distribution to uniform (This is a breaking change because of the benefits to simulated results).
A warning is given when no user-specified noise_distribution is supplied to warn the breaking change
Added the utilities.estimate_noise_model() method to estimate the noise present in the data
Added a built-in estimation procedure to match the amount of zeroes observed in the dataset
Improvements
Added 4 more detailed tutorials on our documentation website
Improved docstrings with more details on key parameters
Updated the lastest references and links
v0.1.1
This is our first maintenance update to be released to v0.1.x, and we are packing in lots of enhancements! All changes are regarding documentations!
Improvements
Added 4 more detailed tutorials on our documentation website
Improved docstrings with more details on key parameters
Updated the lastest references and links
v0.1.0
Our FIRST OFFICIAL RELEASE is here! From now on, all our releases will be supported with our standard support cycle. Here you will find our release notes.
Changes and New Features
Added Command-Line Interface with support for complex simulations
Improved docstrings
Improved documentations with tutorials
From Pre-release
These are listed for documetation reasons for the first official release.
Support for
Emulation Mode
andCreation Mode
Support for complex simulations
Availability on
PyPI
andconda
v0.0.2
This is the first stable pre-release of cytomulate
A fix for critical installation error from v0.0.1.
Availability on
PyPI
andconda
.
v0.0.1
This is official pre-release of cytomulate.
- Introduction of Creation and Emulation mode.
Creation Mode for probabilistic model-based simulation
Emulation Mode for data-based simulation
Support for simulating batches, different cell types, cell differentiations, etc.
Availability on
PyPI
andconda
.