Pyviscous

Latest version: v2.2.1

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2.2.1

Release Highlights

This release introduces several enhancements to elevate the overall quality and usability of the code:
1. **Improved Formatting:**
The code has undergone refinements in formatting to enhance readability and maintain consistency.
2. **Real Case Study: Bow at Banff**
A new real case study, **Bow at Banff**, has been added to provide a practical example, offering users valuable context for application and understanding.
3. **Sensitivity Index Adjustment:**
Sensitivity index results are now enforced to be one when exceeding one. This adjustment aims to improve the accuracy and reliability of sensitivity analyses.
4. **Expanded n_components Range:**
The range of `n_components` has been expanded from [2, 9] to [1, 9], providing users with increased flexibility in configuring the model.
5. **Additional Input Arguments:**
Two optional input arguments, Model Selection Criteria (MSC) and verbose, have been introduced to the `viscous` function, offering users more control and customization.

These updates collectively contribute to a more robust and user-friendly code. We encourage users to explore the new features and provide feedback for ongoing improvements.

2.2.0

This release includes the improved handling of the marginal densities of the Gaussian Mixture Copula Model (GMCM). It also includes better treatments for kmeans related errors in GMCM parameter initialization.

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