# History

## v0.1.0-alpha

This is the initial release of **foxes** - ready for testing.

So far not many models have been transferred from the Fraunhofer IWES in-house predecessor *flappy*, they will be added in the following versions. Also optimization is not yet included. We are just getting started here!

Enjoy - we are awaiting comments and issues, thanks for testing.

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.1.0](https://github.com/FraunhoferIWES/foxes/commits/v0.1.0)

## v0.1.1-alpha

- New code style, created by *black*
- Small fixes, discovered by *flake8*
- Tests now via *pytest* instead of *unittest*
- Introducing github workflow for automatic testing

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.1.1](https://github.com/FraunhoferIWES/foxes/commits/v0.1.1)

## v0.1.2-alpha

- Adding support for Python 3.9, 3.10

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.1.2](https://github.com/FraunhoferIWES/foxes/commits/v0.1.2)

## v0.1.3-alpha

- Adding docu: [https://fraunhoferiwes.github.io/foxes.docs/index.html](https://fraunhoferiwes.github.io/foxes.docs/index.html)

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.1.3](https://github.com/FraunhoferIWES/foxes/commits/v0.1.3)

## v0.1.4-alpha

- Fixes
  - Static data: Adding missing data `wind_rotation.nc` to manifest
- Models
  - New wake model added: `TurbOParkWake` from Orsted
  - New turbine type added: `PCtSingleFiles`, reads power and thrust curves from two separate files
  - New turbulence intensity wake model added: `IECTI2019`/`Frandsen` and `IECTI2005`

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.1.4](https://github.com/FraunhoferIWES/foxes/commits/v0.1.4)

## v0.2.0-alpha

- Core
  - Introducing the concept of runners
- Opt
  - New sub package: `foxes.opt`, install by `pip install foxes[opt]`. This introduces the capability to run wind farm optimizations. As examples layout optimization for simple cases are given, see below.
- Models
  - New turbine model: `Thrust2Ct`, calculates ct from thrust values
  - New turbine type: `NullType`, a turbine type with only rotor diameter and hub height data
  - Renamed `PCtSingleFiles` into `PCtTwoFiles`
- Output
  - New output: `WindRoseOutput`, providing a plotly figure that shows a rose-type histogram
  - New output: `AmbientWindRoseOutput`, providing rose-type plotly figures of ambient data (no wake calculation involved)
- Algorithms
  - Improved `Downwind`: Now with option for ambient runs (no wakes)
- Utils
  - New utility: `show_plotly_fig`, opens a window that shows a plotly figure (instead of browser)
  - New runners: `DefaultRunner`, `DaskRunner`. The latter features parallel runs via dask
- Examples
  - Introducing two sub-folders of examples: `foxes` and `foxes.opt`
  - New example: `wind_rose`, calculation of wind rose states data
  - New example: `layout_single_state`, wind farm layout optimization for a single wind state
  - New example: `layout_wind_rose`, wind farm layout optimization for wind rose states
- Notebooks
  - New notebook: `layout_opt.ipynb`, demonstrating a simple layout optimization case

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.2.0](https://github.com/FraunhoferIWES/foxes/commits/v0.2.0)

## v0.2.1-alpha

- Input:
  - New input: `MultiHeightStates` and `MultiHeightTimeseries`, for input data at several height levels, e.g. WRF results at one point
- Output:
  - New output: `FarmResultsEval`, calculates sum, mean, min, max over states or turbines for the whole wind farm. Also calculates capacity, efficiency, yield, P75, P90.
  - New output: `ResultsWriter`, writes farm results or pandas data to csv file
  - Renaming: `AmbientRosePlotOutput` is now called `StatesRosePlotOutput`
- Notebooks:
  - New notebook: `multi_height.ipynb`, demonstrating the usage of multi-height wind input data

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.2.1](https://github.com/FraunhoferIWES/foxes/commits/v0.2.1)

## v0.2.2-alpha

- Bug fixes
  - Bug fixed in `MultiHeightStates` for wind veer cases

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.2.2](https://github.com/FraunhoferIWES/foxes/commits/v0.2.2)

## v0.2.3-alpha

- Input states
  - Improved: `SingleStateStates` now supports profiles
- Turbine models
  - New model `PowerMask`: Derates or boosts a turbine
- Examples
  - New: `power_mask`, demonstrates derating and boost
- Utils
  - New: `cubic_roots`, solves a cubic equation
- Output
  - New: `StateTurbineMap`, creates heat maps for state-turbine data
  - New: `TurbineTypeCurves`, creates power and thrust curve plots
  - Improved: `FarmLayoutOutput` now supports scatter color by variable
- Documentation
  - Adding forgotten `foxes.opt` to API
- Notebooks:
  - Now including results as colored layout plots
  - New notebook: `wind_rose.ipynb`, demonstrating how to calculate wind roses
  - New notebook: `power_mask.ipynb`, showing derating and boost via a power mask

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.2.3](https://github.com/FraunhoferIWES/foxes/commits/v0.2.3)

## v0.2.4-alpha

- Bug fixes
  - Hotfix for bug in `TurbineTypeCurves` output

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.2.4](https://github.com/FraunhoferIWES/foxes/commits/v0.2.4)

## v0.2.5-alpha

- Core:
  - New: `ExtendedStates`, allows for adding point data models to states
- Input:
  - Improved: `FieldDataNC`, now with support for spatially uniform variables
- Turbine types:
  - New: `WsRho2PCtTwoFiles`, air density dependent power and ct curves
- Turbine models:
  - New: `SectorManagement`, sets variables by range rules on other variables
- Point models:
  - New: `SetUniformData`, set uniform variables (optionally state dependent)
- Examples:
  - New: `sector_management`, demonstrates how to model wind sector management
- Notebooks:
  - New: `sector_man.ipynb`, demonstrates how to model wind sector management
  - New: `data.ipynb`, lists and shows the static data
- Bug fixes:
  - Fix for bug with option `col_models` in farm layout from csv

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.2.5](https://github.com/FraunhoferIWES/foxes/commits/v0.2.5)

## v0.2.6-alpha

- Output:
  - Improved: `FarmResultsEval` can now handle NaN data in Einstein sums
  - Improved: `ResultsWriter` can now also write turbine names 
- Turbine models:
  - New: `TableFactors`, multiplies variables with data from a two dimensional table
  - New: `YAW2YAWM`, calculates yaw deltas from absolute yaw and wind direction
  - New `YAWM2YAW`, calculates absolute yaw from yaw deltas and wind direction
  - Generalized: `kTI`, now includes optional offset `kb`
- Turbine types:
  - Changed: Now yaw correction of `P` and `CT` switched on by default
- Point models:
  - New: `TKE2TI`, calculates turbulence intensity from TKE
- Wake models:
  - New: `PorteAgel`, calculates wakes based on the Bastankhah PorteAgel 2016 wake model
- Wake frames:
  - New: `YawedWake`, bends wakes in yawed conditions
- Wake superposition models:
  - Improved: `LinearSuperposition`, now includes options for lower/higher limits of total wake deltas
- Examples:
  - New: `compare_wakes`, compares wake models along horizontal lines
  - New: `yawed_wake`, demonstrates wake bending by yawing a rotor
- Notebooks:
 - New: `yawed_wake.ipynb`, demonstrates wake bending by yawing a rotor
- Bug fixes:
  - Fix for bug with `ExtendedStates`, now it is actually working
  - Fix for bug with wake width in `CrespoHernandezTIWake`
  - Fix for bug with YAW and WD when using the `YAWM2YAW` turbine model
  - Fix for bug in `TurbOPark` wake model, double counting constant offset in sigma

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.2.6](https://github.com/FraunhoferIWES/foxes/commits/v0.2.6)

## v0.3.0-alpha

- Core:
  - Models now with simplified structure, reduces memory load during calculations
- Algorithms:
  - New: `Iterative`, iterative wind farm calculation until convergence has been reached
- Input:
  - Improved: `FieldDataNC` now accepts xarray Dataset or file pattern str as input
  - New: `ShearedProfile`, Vertical WS profile can be determined with shear exponent
- Output:
  - Improved: `FlowPlots2D` replacing horizontal/vertical --> xy, xz, yz, more intuitive
- Wake models:
  - New: `TurbOParkIX`, integrates wake corrected TI along centreline for wake width sigma.
- Wake frames:
  - Improved: All yawed wake frames now also support centreline data integration
- Notebooks:
  - New: `overview.ipynb`, summarizes the setup steps
- Bug fixes:
  - Fix for bug in `TurbOPark` wake model: Brackets in Eq. (4) were wrong 
  - Fix for bug with long streamlines

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.3.0](https://github.com/FraunhoferIWES/foxes/commits/v0.3.0)

## v0.3.1-alpha

- Input states:
  - Improved: `FieldDataNC` now supports states subset selection
- Wake frames:
  - Improved: `Streamlines` now with maximal length option
- Turbine models:
  - New: `Calculator`, simple variable calculation via user function
- Opt:
  - Now two abstract problems in core: `FarmOptProblem` and `FarmVarsProblem`, the latter invokes the `SetFarmVars` turbine model 
  - New opt problem: `RegularLayoutOptProblem`, searches for a regular grid layout
  - New opt problem: `GeomRegGrids`, finds regular grid layout by purely geometrical means (no wind farm calculation)
  - New opt problem: `GeomLayout`, turbine positioning based on xy variables, also purely geometrical
  - New opt problem: `GeomLayoutGridded`, a purely geometrical optimization on a gridded background
- Examples:
  - New in `foxes.opt`: Example `layout_regular_grid`, demonstrates regular grid layout optimization
  - New in `foxes.opt`: Example `geom_reggrids`, purely geometrical regular layout optimization
- Utils:
  - New functions for shape file handling: `read_shp`, `shp2csv`, `read_shp_polygons`
  
**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.3.1](https://github.com/FraunhoferIWES/foxes/commits/v0.3.1)

## v0.3.2-alpha

- Bug fixes:
  - Fix for bug in `FarmResultsEval` that affected time range calculations under Windows
  - Bug fixes for `FarmResultsEval` with time series data
    
**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.3.2](https://github.com/FraunhoferIWES/foxes/commits/v0.3.2)

## v0.3.3-alpha

- Utils:
  - Now `geopandas_helpers` can handle interior areas
    
**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.3.3](https://github.com/FraunhoferIWES/foxes/commits/v0.3.3)

## v0.3.4-alpha

- Installation:
  - `foxes` now supports Python 3.11
- Input:
  - New layout input option: `add_from_df`, adding turbines from a pandas DataFrame
  - New interface to [windIO](https://github.com/IEAWindTask37/windIO) case yaml files
- Turbine types:
  - New turbine type `CpCtFile`, reads CP and CT data from file or pandas DataFrame
  - New turbine type `CpCtFromTwo`, reads CP and CT data from two files or pandas DataFrames
  - Improved: Turbine types now calculate `P_nominal` as maximum, if not explicitely given
- Constants:
  - Introducing `P_UNITS`, used in turbine types and output evaluation
- States:
  - Bug fixed in `FieldDataNC` with loading multiple files
- Core:
  - Improved `DataCalcModel`: Now cleaner treatment of runs with `progress_bar=False`. Also now slimmer for `distributed` scheduler

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.3.4](https://github.com/FraunhoferIWES/foxes/commits/v0.3.4)

## v0.3.5-alpha

- General:
  - Moving identifier-type entries from `foxes.variables` to `foxes.constants`
- Models:
  - New wake superposition model `ProductSuperposition`, computing factorized wake deltas
  - New turbine model: `RotorCentreCalc`, calculates data at rotor centre, irrespective of rotor model
- Bug fixes:
  - Bug fixed that caused problems when restarting the `SectorManagement` turbine model, e.g. for flow plots
- Documentation:
  - Completely new style, fixing issues with incomplete API entries

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.3.5](https://github.com/FraunhoferIWES/foxes/commits/v0.3.5)

## v0.4.0

- Models:
  - Improved: New option to specify wake growth variable name, such that multiple `kTI` models could be used, resulting in different `k`'s for different wake models
  - New turbine model: `LookupTable`, interpolates data based on a multi-dimensional lookup table
- Utils:
  - Improved `DaskRunner`: Now supports clusters that run the Slurm queueing system
- Examples:
  - New: `timeseries_slurm`, shows how to run foxes on a HPC with Slurm queueing system
- Optimization:
  - Improved: `foxes.opt` is now able to optimize for flow variables (at selected points in space) in addition to turbine variables
- Documentation:
  - Improved API docu, now based on `python-apigen`

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.4.0](https://github.com/FraunhoferIWES/foxes/commits/v0.4.0)

## v0.4.1

- Algorithms:
  - Improved: `Iterative` now iterates through outer loop instead of within chunk
- Models:
  - New wake frame: `Timelines`, propagates wakes for spatially uniform time series
- Tests:
  - New test: `consistency/iterative`, checks if iterative algorithm gives same result
- Examples:
  - New example: `timelines`, demonstrates the usage of the `Timelines` wake frame
  - Improved: All examples were update for the correct usage of the `DaskRunner`
- Notebooks:
  - New notebook: `timelines.ipynb`, showing how to use the `Timelines` wake frame in a notebook
- Data:
  - New states data `timeseries_100.csv.gz`, a short timeseries with timestep 1 min, varying wind direction only
- Output:
  - Improved: `FlowPlots2D` now has the optional argument `runner`, for computing plots with the chosen parallelization settings

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.4.1](https://github.com/FraunhoferIWES/foxes/commits/v0.4.1)

## v0.4.2

- Bug fixes:
  - Fix of bug that slowed down `TurbOParkIX` by considering all TI wakes instead of only source turbine wake during integration
  - Fix of bug that prevented plotly wind roses to be shown in the documentation
  - Fix in docu that excluded the algorithm models from the API
- Output:
  - New: `Animator`, creates animations based on generators that yield lists of artists
- Examples:
  - Improved: `timelines` now includes turbine REWS signal in animations
- Notebooks:
  - Improved: `timelines.ipynb` now includes turbine REWS signal in animations

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.4.2](https://github.com/FraunhoferIWES/foxes/commits/v0.4.2)

## v0.4.3

- Output:
  - Improved: `RosePlotOutput` and `StatesRosePlotOutput` now optionally return the binned data
- Models:
  - New vertical profile: `DataProfile`, data based profile from file or pandas DataFrame
  - Improved ti superposition: Now supporting n-th power superposition
  - Improved wake model `TurbOParkIX`: New option for consideration of all wakes in ti integral
- Bug fixes:
  - Fixed bug with `windio` input that resulted in wrong wind rose weights
  - Fixed bug with `FlowPlots2D` with value bounds in contour plots

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.4.3](https://github.com/FraunhoferIWES/foxes/commits/v0.4.3)

## v0.4.4

- Testing automated publishing to PyPi via workflow

## v0.4.5

- Models:
  - New rotor model: `LevelRotor`, calculates the REWS from different height levels
  - New turbine type: `WsTI2PCtFromTwo`, reads turbulence-dependent ct- and power curves

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.4.5](https://github.com/FraunhoferIWES/foxes/commits/v0.4.5)

## v0.5

- Dependencies:
  - Dropping support for Python 3.7, due to `netcdf4` dependency
- Core:
  - Simplified model initialization/finalization. Removing the `keep_models` idea, instead all models are now kept in the algorithm's idata memory until finalization. Adding a new model now mostly requires that the `sub_models` and the `load_data` functions are overloaded, if applicable. The `initialize` and `finalize` only need to be addressed explicitly in non-standard cases.
- Algorithms:
  - New algorithm: `Sequential`, step wise evaluation of states for simulation environments that do not support chunking
  - Improved: `Iterative` now supports under-relaxation of parameters
- Output:
  - New sub package: `output.flow_plots_2d` is now a package instead of a module
- Models:
  - This version introduces induction models for modelling blockage effects.
  - New induction model: `RHB`, the classic Rankine-half-body model.
- Examples:
  - New example: `sequential`, demonstrating the usage of the sequential algorithm
  - New example: `induction_RHB`, showing the Rankine-half-body model for blockage
- Notebooks:
  - New notebook: `blockage.ipynb`, demonstrating how to apply the RHB induction model to a wind farm

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.5](https://github.com/FraunhoferIWES/foxes/commits/v0.5)

## v0.5.1

- Dependencies:
  - The `windio` package is now an optional dependency, to be installed by hand if needed. This is due to windio being not available at conda-forge
- Notebooks:
  - New notebook: `sequential.ipynb`, creating an animation showing state-by-state wake propagation

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.5.1](https://github.com/FraunhoferIWES/foxes/commits/v0.5.1)

## v0.5.2

- Algorithms:
  - Improved `Downwind`: Now optional arguments that allow calculation of subsets in calc_farm and calc_points, e.g. a selection of states
- Output:
  - New output: `PointCalculator`, a wrapper for the calc_points function of the algorithm
  - New output: `SliceData`, creating arrays, DataFrames or Datasets from 2D slices
  - Improved `FlowPlots2D`: Completely refactored, data based on `SliceData`. New option for creating figures for subsets of states only.
- Vertical profiles:
  - Now optional support for `ustar` input data instead of reference data
- Turbine types:
  - Fix for `Cp`-based models with interpolation within sparse input data
- Wake models:
  - Renaming: `BastankhahWake` class now called `Bastankhah2014`. Models in the model book are also renamed from `Bastankhah` to `Bastankhah2014`
  - Renaming: `PorteAgelWake` class now called `Bastankhah2016`. Models in the model book are also renamed from `PorteAgel` to `Bastankhah2016`
  - Renaming: `RHB` class now called `RankineHalfBody`
  - Fix: `RankineHalfBody` no longer shows a jump at the rotor disc, but a small region of constant deficit instead
  - New default values: `Bastankhah2014` now has default value `sbeta_factor=0.2` (previously 0.25). Models with the previous value are available in the model book as `Bastankhah025` etc.
- Wake superpositions:
  - Restructured: Now simplified classes for WS or TI superposition only (less general but simpler), e.g. `WSLinear` or `TIQuadratic`, etc. Also in the model book the models are now called `ws_linear` or `ti_quadratic`, etc.

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.5.2](https://github.com/FraunhoferIWES/foxes/commits/v0.5.2)

## v0.5.2.1

- Bug fixes:
  - Bugs fixed that messed up the colorbar and the title in animations
- Notebooks:
  - Improved animations in `timelines.ipynb` and `sequential.ipynb`

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.5.2.1](https://github.com/FraunhoferIWES/foxes/commits/v0.5.2.1)

## v0.6

- Dependencies:
  - Replacing dependency on `plotly` by dependency on `windrose`, since the latter is lighter
- Core:
  - This version introduces `AxialInductionModel` classes, computing the axial induction factor `a(ct)`
- Wake models:
  - Reformulating `beta` in terms of induction in `Bastankhah2014` and `CrespoHernandez`
  - New default: `Bastankhah2014`, `Bastankhah2016`, `TurbOPark` and `TurbOParkIX` now with default axial induction model `Madsen`
  - New induction wake models: `Rathmann`, `SelfSimilar` and `SelfSimilar2020`, for blockage modelling
  - Introducing `WakeMirror` wrapper around wake models, modelling wake reflection from ground or horizontal plane via virtual mirrored turbines
- Wake frames:
  - Renaming `Streamlines` to `Streamlines2D`, no changes in model book names
- Axial induction models:
  - New induction model: `BetzAxialInduction`, the classic `a = 0.5(1 - sqrt(1-ct))` relation. In the model book this is called `Betz`.
  - New induction model: `MadsenAxialInduction`, a third-order polynomial approximation of `a(ct)`. In the model book this is called `Madsen`.
- Output:
  - Improved: `FlowPlots2D` now includes an option for indicating the rotor disk by a colored line
  - Improved: `RosePlotOutput` no longer depends on `plotly`, but on the new utility `TabWindroseAxes`
- Utils:
  - New: `TabWindroseAxes`, a derivative of `windrose.WindroseAxes` for input data that is based on bins with weights (and not timeseries)
- Notebooks:
  - New: `blockage_comparison.ipynb`, comparing four turbine induction models
- Bug fixes:
  - Fix for bug in `Streamlines2D` when used in combination with `WakeMirror`
- Tests:
  - Fresh `flappy` v0.6.2 test data for all Bastankhah and CrespoHernandez wakes, also without the `sbeta` limitation

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.6](https://github.com/FraunhoferIWES/foxes/commits/v0.6)

## v0.6.1

- Input:
  - New ambient states: `TabStates`, single tab-file input
- Data
  - New static data: `winds100.tab`, an example tab file
- Examples:
  - New example: `tab_file`, demonstrating the usage of the `TabStates`
- Bug fixes:
  - Bug fixed for `RankineHalfBody` turbine induction model that produced wrong results for wind directions unequal 270 degrees

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.6.1](https://github.com/FraunhoferIWES/foxes/commits/v0.6.1)

## v0.6.2

- Models:
  - New partial wakes model: `PartialCentre`, evaluating wake deltas at the rotor centre point only
- Inputs:
  - New farm layout input: `add_random`, adds turbines at random positions, respecting a minimal distance
  - New states creation: `random_timseries_data`, creates uniform random timeseries data
- Utils:
  - New function `random_xy_square`, generates random xy positions with minimal distance
- Examples:
  - New example: `random_timeseries`, computes a random farm in a random timeseries. Both sizes are defined by user input

**Full Changelog**: [https://github.com/FraunhoferIWES/foxes/commits/v0.6.2](https://github.com/FraunhoferIWES/foxes/commits/v0.6.2)