v2.0.0

General

• Special thanks to @riley-brady for supporting me improving the package.
• The python-cmethods package has changed in many ways. Please have a look at the updated README.md and documentation. Please pin version v1.0.3 as long as your code is not v2.0.0 ready.

Breaking changes

• Rework python-cmethods: replace the CMethods class by the new adjust function #48 (@btschwertfeger)

Implemented enhancements

• Optimization for adjust_3d #47
• Find a solution to process large data sets more efficient #6

Full Changelog

v1.0.3

What's Changed

• Fix error when time series includes nan values by @btschwertfeger in #40
• Merge .pylintrc and .coveragerc into pyproject.toml by @btschwertfeger in #44
• Add type checking for parameters of bias correction techniques by @btschwertfeger in #43

Full Changelog: v1.0.2...v1.0.3

v1.0.2

What's Changed

• Clarified difference between stochastic and non-stochastic climate variables in doc and readme by @btschwertfeger in #36
• Fix typos by @btschwertfeger in #38

Full Changelog: v1.0.1...v1.0.2

Release v1.0.1

⚠️ This release contains breaking changes. Please read the release notes carefully.

What is included in python-cmethods v1.0.1?

The following bias correction methods are available:

Scaling-based techniques:

• Linear Scaling cmethods.CMethods.linear_scaling (additive and multiplicative)
• Variance Scaling cmethods.CMethods.variance_scaling (additive)
• Delta (change) Method cmethods.CMethods.delta_method (additive and multiplicative)

Distribution-based techniques:

• Quantile Mapping cmethods.CMethods.quantile_mapping (additive and multiplicative)
• Detrended Quantile Mapping cmethods.CMethods.detrended_quantile_mapping (additive and multiplicative)
• Quantile Delta Mapping cmethods.CMethods.quantile_delta_mapping (additive and multiplicative)

A new documentation at: https://python-cmethods.readthedocs.io/en/stable
PyPI: https://pypi.org/project/python-cmethods/

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What's Changed

• Fixed PyPI repository URL in #16
• Extended the description of quantile mapping with text and images in #20
• Create a Changelog by in #21
• Fixed bug where division lead to nan or inf values by in #33
• Split Quantile Mapping into Quantile Mapping and Detrended Quantile Mapping in #34
• Prepare release by in #35

Full Changelog: v1.0.0...v1.0.1

Release v1.0.0 🎉

⚠️ This release contains breaking changes. Please read the release notes carefully.

What is included in python-cmethods v1.0.0?

The following bias correction methods are available:

Scaling-based techniques:

• Linear Scaling cmethods.CMethods.linear_scaling (additive and multiplicative)
• Variance Scaling cmethods.CMethods.variance_scaling (additive)
• Delta (change) Method cmethods.CMethods.delta_method (additive and multiplicative)

Distribution-based techniques:

• Quantile Mapping cmethods.CMethods.quantile_mapping (additive and multiplicative)
• Quantile Delta Mapping cmethods.CMethods.quantile_delta_mapping (additive and multiplicative)

A new documentation at: https://python-cmethods.readthedocs.io/en/stable
PyPI: https://pypi.org/project/python-cmethods/

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What's Changed

• All bias correction techniques that are applied on 1-dimensional time-series now return the data type np.array. Only the adjust_3d function still returns the data type xarray.core.dataarray.DataArray.
• Moved the content of CMethods.py to __init__.py and adjusted the imports in #14
• Create the documentation in #13
• Move from setup.py to pyproject.toml in #11
• Improved workflows - adding release workflow in #12
• fixed the zero-dimension bug in Variance Scaling
• Extended the examples and added an executable script named biasadjust.py that accepts command-line arguments to bias-adjust time-series climate data based on the passed inputs in #15

Full Changelog: v0.6.3...v1.0.0

Release v0.6.3

Removed the forced grouping to time.month on adjust_3d when no group is specified (i.e., group=None).

This enables the correction of 3-dimensional data sets without a grouping.

Release v0.6.2

Removed the group parameter from quantile_mapping and quantile_delta_mapping since this grouping leads to unrealistic transitions between the selected windows. This, for example leads to high deviations in the mean of monthly transitions if: group="time.mean".

Release v0.6.1

• Fixed zero division error in QDM that occurred when testing with fake precipitation data

Release v0.6

• fixed error when custom exception was raised
• adjusted pyint hints
• extended testing

Release v0.5.4.2

• limitation to additive for variance scaling
• adjusted required dependency versions