v3.0

• The architecture was redesigned to better support interactive calculation and provide a low-level integration across all supported methods. This is the first release with the new architecture. Frequent updates are planned to provide additional examples, tests, and bugfixes in the next few months.

• New assessment module introduced to replace control module:

  • Provides a high-level access to models and their methods
  • Integrates all types of assessments into a uniform approach
  • Most of the methods from the earlier control module were moved to the model module

• Decoupled demand, damage, and loss calculations:

  • Fragility functions and consequence functions are stored in separate files. Added new methods to the db module to prepare the corresponding data files and re-generated such data for FEMA P58 and Hazus earthquake assessments. Hazus hurricane data will be added in a future release.
  • Decoupling removed a large amount of redundant data from supporting databases and made the use of HDF and json files for such data unnecessary. All data are stored in easy-to-read csv files.
  • Assessment workflows can include all three steps (i.e., demand, damage, and loss) or only one or two steps. For example, damage estimates from one analysis can drive loss calculations in another one.

• Integrated damage and loss calculation across all methods and components:

  • This includes phenomena such as collapse, including various collapse modes, and irreparable damage.
  • Cascading damages and other interdependencies between various components can be introduced using a damage process file.
  • Losses can be driven by damages or demands. The former supports the conventional damage->consequence function approach, while the latter supports the use of vulnerability functions. These can be combined within the same analysis, if needed.
  • The same loss component can be driven by multiple types of damages. For example, replacement can be triggered by either collapse or irreparable damage.

• Introduced Options in the configuration file and in the base module:

  • These options handle settings that concern pelicun behavior;
  • general preferences that might affect multiple assessment models;
  • and settings that users would not want to change frequently.
  • Default settings are provided in a default_config.json file. These can be overridden by providing any of the prescribed keys with a user-defined value assigned to them in the configuration file for an analysis.

• Introduced consistent handling of units. Each csv table has a standard column to describe units of the data in it. If the standard column is missing, the table is assumed to use SI units.

• Introduced consistent handling of pandas MultiIndex objects in headers and indexes. When tabular data is stored in csv files, MultiIndex objects are converted to simple indexes by concatenating the strings at each level and separating them with a -. This facilitates post-processing csv files in pandas without impeding post-processing those files in non-Python environments.

• Updated the DL_calculation script to support the new architecture. Currently, only the config file input is used. Other arguments were kept in the script for backwards compatibility; future updates will remove some of those arguments and introduce new ones.

• The log files were redesigned to provide more legible and easy-to-read information about the assessment.