Pelicun

- Changes affecting backwards compatibility

- **Remove "bldg" from repair consequence output filenames**: The increasing scope of Pelicun now covers simulations for transportation and water networks. Hence, labeling repair consequence outputs as if they were limited to buildings no longer seems appropriate. The `bldg` label was dropped from the following files: `DV_bldg_repair_sample`,`DV_bldg_repair_stats`,`DV_bldg_repair_grp`, `DV_bldg_repair_grp_stats`, `DV_bldg_repair_agg`, `DV_bldg_repair_agg_stats`.

- Deprecation warnings

- **Remove `Bldg` from repair settings label in DL configuration file**: Following the changes above, we dropped `Bldg` from `BldgRepair` when defining settings for repair consequence simulation in a configuration file. The previous version (i.e., `BldgRepair`) will keep working until the next major release, but we encourage everyone to adopt the new approach and simply use the `Repair` keyword there.

- New features

- **Location-specific damage processes**: This new feature is useful when you want damage to a component type to induce damage in another component type at the same location only. For example, damaged water pipes on a specific story can trigger damage in floor covering only on that specific story. Location-matching is performed automatically without you having to define component pairs for every location using the following syntax: `'1_CMP.A-LOC', {'DS1': 'CMP.B_DS1'}` , where DS1 of `CMP.A` at each location triggers DS1 of `CMP.B` at the same location.

- **New `custom_model_dir` argument for `DL_calculation`**: This argument allows users to prepare custom damage and loss model files in a folder and pass the path to that folder to an auto-population script through `DL_calculation`. Within the auto-population script, they can reference only the name of the files in that folder. This provides portability for simulations that use custom models and auto population, such as some of the advanced regional simualtions in [SimCenter's R2D Tool](https://simcenter.designsafe-ci.org/research-tools/r2dtool/).

- **Extend Hazus EQ auto population sripts to include water networks**: Automatically recognize water network assets and map them to archetypes from the Hazus Earthquake technical manual.

- **Introduce `convert_units` function**: Provide streamlined unit conversion using the pre-defined library of units in Pelicun. Allows you to convert a variable from one unit to another using a single line of simple code, such as
`converted_height = pelicun.base.convert_units(raw_height, unit='m', to_unit='ft')`
While not as powerful as some of the Python packages dedicated to unit conversion (e.g., [Pint](https://pint.readthedocs.io/en/stable/)), we believe the convenience this function provides for commonly used units justifies its use in several cases.

- Architectural and code updates

- **Split `model.py` into subcomponents**: The `model.py` file was too large and its contents were easy to refactor into separate modules. Each model type has its own python file now and they are stored under the `model` folder.

- **Split the `RandomVariable` class into specific classes**: It seems more straightforward to grow the list of supported random variables by having a specific class for each kind of RV. We split the existing large `RandomVariable` class in `uq.py` leveraging inheritance to minimize redundant code.

- **Automatic code formatting**: Further improve consistency in coding style by using [black](https://black.readthedocs.io/en/stable/) to review and format the code when needed.

- **Remove `bldg` from variable and class names**: Following the changes mentioned earlier, we dropped `bldg` from lables where the functionality is no longer limited to buildings.

- **Introduce `calibrated` attribute for demand model**: This new attribute will allow users to check if a model has already been calibrated to the provided empirical data.

- Several other minor improvements; see commit messages for details.

- Dependencies

- Ceiling raised for `pandas`, supporting version 2.0 and above up until 3.0.

* Changes that might affect backwards compatibility:

* Unit information is included in every output file. If you parse Pelicun outputs and did not anticipate a Unit entry, your parser might need an update.

* Decision variable types in the repair consequence outputs are named using CamelCase rather than all capitals to be consistent with other parts of the codebase. For example, we use "Cost" instead of "COST". This might affect post-processing scripts.

* For clarity, "ea" units were replaced with "unitless" where appropriate. There should be no practical difference between the calculations due to this change. Interstory drift ratio demand types are one example.

* Weighted component block assignment is no longer supported. We recommend using more versatile multiple component definitions (see new feature below) to achieve the same effect.

* Damage functions (i.e., assign quantity of damage as a function of demand) are no longer supported. We recommend using the new multilinear CDF feature to develop theoretically equivalent but more efficient models.

* New multilinear CDF Random Variable allows using the multilinear approximation of any CDF in the tool.

* Capacity adjustment allows adjusting (scaling or shifting) default capacities (i.e., fragility curves) with factors specific to each Performance Group.

* Support for multiple definitions of the same component at the same location-direction. This feature facilitates adding components with different block sizes to the same floor or defining multiple tenants on the same floor, each with their own set of components.

* Support for cloning demands, that is, taking a provided demand dataset, creating a copy and considering it as another demand. For example, you can provide results of seismic response in the X direction and automatically prepare a copy of them to represent results in the Y direction.

* Added a comprehensive suite of more than 140 unit tests that cover more than 93% of the codebase. Tests are automatically executed after every commit using GitHub Actions and coverage is monitored through `Codecov.io`. Badges at the top of the Readme show the status of tests and coverage. We hope this continuous integration facilitates editing and extending the existing codebase for interested members of the community.

* Completed a review of the entire codebase using `flake8` and `pylint` to ensure PEP8 compliance. The corresponding changes yielded code that is easier to read and use. See guidance in Readme on linting and how to ensure newly added code is compliant.

* Models for estimating Environmental Impact (i.e., embodied carbon and energy) of earthquake damage as per FEMA P-58 are included in the DL Model Library and available in this release.

* "ListAllDamageStates" option allows you to print a comprehensive list of all possible damage states for all components in the columns of the DMG output file. This can make parsing the output easier but increases file size. By default, this option is turned off and only damage states that affect at least one block are printed.

* Damage and Loss Model Library

* A collection of parameters and metadata for damage and loss models for performance based engineering. The library is available and updated regularly in the DB_DamageAndLoss GitHub Repository.

* This and future releases of Pelicun have the latest version of the library at the time of their release bundled with them.

* DL_calculation tool

* Support for combination of built-in and user-defined databases for damage and loss models.

* Results are now also provided in standard SimCenter `JSON` format besides the existing `CSV` tables. You can specify the preferred format in the configuration file under Output/Format. The default file format is still CSV.

* Support running calculations for only a subset of available consequence types.

* Several error and warning messages added to provide more meaningful information in the log file when something goes wrong in a simulation.

* Update dependencies to more recent versions.

* The online documentation is significantly out of date. While we are working on an update, we recommend using the documentation of the [DL panel in SimCenter's PBE Tool](https://nheri-simcenter.github.io/PBE-Documentation/common/user_manual/usage/desktop/PBE/Pelicun.html) as a resource.

* Calculation settings are now assessment-specific. This allows you to use more than one assessments in an interactive calculation and each will have its own set of options, including log files.

* The uq module was decoupled from the others to enable standalone uq calculations that work without having an active assessment.

* A completely redesigned DL_calculation.py script that provides decoupled demand, damage, and loss assessment and more flexibility when setting up each of those when pelicun is used with a configuration file in a larger workflow.

* Two new examples that use the DL_calculation.py script and a json configuration file were added to the example folder.

* A new example that demonstrates a detailed interactive calculation in a Jupyter notebook was added to the following DesignSafe project: https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-3411v5 This project will be extended with additional examples in the future.

* Unit conversion factors moved to an external file (settings/default_units) to make it easier to add new units to the list. This also allows redefining the internal units through a complete replacement of the factors. The internal units continue to follow the SI system.

* Substantial improvements in coding style using flake8 and pylint to monitor and help enforce PEP8.

* Several performance improvements made calculations more efficient, especially for large problems, such as regional assessements or tall buildings investigated using the FEMA P-58 methodology.

* Several bugfixes and a large number of minor changes that make the engine more robust and easier to use.

* Update recommended Python version to 3.10 and other dependencies to more recent versions.

* 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.

* Support EDPs with more than 3 characters and/or a variable in their name. For example, SA_1.0 or SA_T1
* Support fitting normal distribution to raw EDP data (lognormal was already available)
* Extract key settings to base.py to make them more accessible for users.
* Minor bug fixes mostly related to hurricane storm surge assessment

* Extend the uq module to support:
* More efficient sampling, especially when most of the random variables in the model are either independent or perfectly correlated.
* More accurate and more efficient fitting of multivariate probability distributions to raw EDP data.
* Arbitrary marginals (beyond the basic Normal and Lognormal) for joint distributions.
* Latin Hypercube Sampling
* Introduce external auto-population scripts and provide an example for hurricane assessments.
* Add a script to help users convert HDF files to CSV (HDF_to_CSV.py under tools)
* Use unique and standardized attribute names in the input files
* Migrate to the latest version of Python, numpy, scipy, and pandas (see setup.py for required minimum versions of those tools).
* Bug fixes and minor improvements to support user needs:
* Add 1.2 scale factor for EDPs controlling non-directional Fragility Groups.
* Remove dependency on scipy's truncnorm function to avoid long computation times due to a bug in recent scipy versions.