About
1. Copyright and license
2. Citing pelicun
3. Logo
4. Acknowledgments
4.1. National Science Foundation
4.2. Contributors
5. Release Notes
5.1. Version 3.0
5.2. Version 2.0
5.3. Version 1.0
User Guide
1. Getting started
1.1. Staying up to date
2. The Pelicun Framework
2.1. Abbreviations
2.2. Introduction to Pelicun
2.3. Overview
2.4. Performance Assessment Workflow
2.5. Response Model
2.6. Performance Model
2.7. Damage Model
2.8. Loss Model
3. Overview of pelicun features
3.1. Saving/loading samples
3.2. Logging support
3.3. Uncertainty quantification
3.4. Assessment types
3.5. Demand simulation
3.6. Damage estimation
3.7. Loss estimation
3.8. Command-line support
3.9. Standalone tools
3.10. Feature overview and examples
4. Damage and loss library
5. Bug reports and feature requests
6. Resources for new python users
7. Examples
7.1. Example 1: Simple loss function.
7.2. Example 2: Damage state validation.
7.3. Example 3: Combining fragility-based damage consequences and loss functions.
8. API Reference
8.1. pelicun
Developer Guide
1. Getting started
1.1. Code of conduct
1.2. How to contribute
2. Setting up a development environment
3. Coding practice
3.1. Code quality assurance
3.2. Unit tests
3.3. Documentation
4. Package architecture
4.1. Overview of files
pelicun
8.
API Reference
8.1.
pelicun
pelicun.tools
pelicun.tools.NNR
pelicun.tools.NNR
Functions
NNR
(target, source, known_values[, ...])