Eis-toolkit

Minor fix release 2 for EIS Toolkit 1.0 release candidate

✨ New features
- Added CLI tool for CBA (391)

🐞 Fixes
- Minor fixes/modifications for CBA (391)

🛠️ Other improvements
- Enabled JSON str outputs in CLI again (394)

Minor fix release for EIS Toolkit 1.0 release candidate

✨ New features
- Added CLI tools for evaluation tools (Summarize label metrics binary, Summarize probability metrics, Plot ROC curve, Plot DET curve, Plot precision recall curve, Plot calibration curve, Plot predicted probability distribution and Score predictions) (387)

🐞 Fixes
- Fix result prints for some CLI functions (390)
- Fix nodata masking for ML models run through CLI

🛠️ Other improvements
- Separated CLI functions for classifier and regressor predicting and testing (prev. called evaluate) (390)
- Added classification threshold parameter for predicting with a classifier (390)

EIS Toolkit 1.0 release candidate

This release is the final beta release which serves as a release candidate for the 1.0 release that will be done soon. Bug fixes and minor adjustments may be still made before the 1.0 release.

✨ New features

- Add Distance to anomaly (https://github.com/GispoCoding/eis_toolkit/pull/324)
- Add K-means clustering for raster data (https://github.com/GispoCoding/eis_toolkit/pull/365)
- Add DBSCAN for raster data (https://github.com/GispoCoding/eis_toolkit/pull/366)
- Add Confusion matrix plot (https://github.com/GispoCoding/eis_toolkit/pull/363)
- Add Neural network accuracy and loss plots (https://github.com/GispoCoding/eis_toolkit/pull/362)
- Add some raster utility tools (https://github.com/GispoCoding/eis_toolkit/pull/371)
- Add many evaluation tools: Summarize label metrics binary, Summarize probability metrics, Plot ROC curve, Plot DET curve, Plot precision recall curve, Plot calibration curve, Plot predicted probability distribution and Score predictions (https://github.com/GispoCoding/eis_toolkit/pull/368)
- Add CLI implementations for many tools

🐞 Fixes
- Fix rasterization of vector label data for ML models called from CLI
- Fix fuzzy sum logic (https://github.com/GispoCoding/eis_toolkit/pull/381)

🛠️ Other improvements

- Add Criterion parameter to Random Forest models (https://github.com/GispoCoding/eis_toolkit/pull/345)
- Add nodata handling to Raster to dataframe tool (https://github.com/GispoCoding/eis_toolkit/pull/364)
- Add max distance parameter to Distance computation and Distance to anomaly (https://github.com/GispoCoding/eis_toolkit/pull/382)
- Change resampling_method parameter type in Resample raster tool to literal/str (https://github.com/GispoCoding/eis_toolkit/pull/349)
- Refactor vector -> raster tools: base raster and pixel size + extent to define output raster grid are now available for all of the tools (https://github.com/GispoCoding/eis_toolkit/pull/375 and https://github.com/GispoCoding/eis_toolkit/pull/376)
- Refactor validation category. Now called evaluation (https://github.com/GispoCoding/eis_toolkit/pull/368)

EIS Toolkit beta release 4

EIS Toolkit's beta release includes most of the basic tools required to conduct mineral prospectivity mapping with Python. Note that this is a beta release and more tools will be added in the upcoming months, and existing tools will be optimized and refined.


✨ New features

- Local Moran's I (https://github.com/GispoCoding/eis_toolkit/pull/305)
- Raster reclassification tools (https://github.com/GispoCoding/eis_toolkit/pull/197)
- CLI implementations for many tools


🐞 Fixes

- Fix/improve normality test (https://github.com/GispoCoding/eis_toolkit/pull/323)
- Fix WofE generalized cumulative weights (https://github.com/GispoCoding/eis_toolkit/pull/326)


🛠️ Other improvements

- Remove GDAL version restriction (https://github.com/GispoCoding/eis_toolkit/pull/330)


Roadmap
The first non-beta release of EIS Toolkit is planned for April 2024. All the planned tools should be implemented by then and requested new additions from Toolkit testers considered as much as possible. For planned tools, refer to the wiki page of this repository.

The first release of EIS QGIS Plugin, which serves a graphical user-interface for EIS Toolkit, should also happen in April 2024.

EIS Toolkit beta release 3

EIS Toolkit's beta release includes most of the basic tools required to conduct mineral prospectivity mapping with Python. Note that this is a beta release and more tools will be added in the upcoming months, and existing tools will be optimized and refined.


✨ New features

- MLP classifier and regressor (https://github.com/GispoCoding/eis_toolkit/pull/252)
- Surface derivatives (https://github.com/GispoCoding/eis_toolkit/pull/255)
- Filter and smoothing functions (https://github.com/GispoCoding/eis_toolkit/pull/289)
- CLI implementations for many tools


🐞 Fixes

- Fix/improve normality test (https://github.com/GispoCoding/eis_toolkit/pull/267)
- Fix/improve correlation and covariance matrix functions (https://github.com/GispoCoding/eis_toolkit/pull/268)
- Fix/improve PCA (https://github.com/GispoCoding/eis_toolkit/pull/269)


🛠️ Other improvements

- Change raster grid check to use only raster metadata/profile instead of raster dataset (https://github.com/GispoCoding/eis_toolkit/pull/281)
- Added PySAL and ESDA Python packages to repository (https://github.com/GispoCoding/eis_toolkit/pull/288)
- Minor clean-up PR (https://github.com/GispoCoding/eis_toolkit/pull/295)
- Small notebook fixes (https://github.com/GispoCoding/eis_toolkit/pull/296)
- Documentation additions for filter functions (https://github.com/GispoCoding/eis_toolkit/pull/303)
- Documentation for derivative functions (https://github.com/GispoCoding/eis_toolkit/pull/301)


Roadmap
The first non-beta release of EIS Toolkit is planned for April 2024. All the planned tools should be implemented by then and requested new additions from Toolkit testers considered as much as possible. For planned tools, refer to the wiki page of this repository.

The first release of EIS QGIS Plugin, which serves a graphical user-interface for EIS Toolkit, should also happen in April 2024.

EIS Toolkit beta release 2

EIS Toolkit's beta release includes most of the basic tools required to conduct mineral prospectivity mapping with Python. Note that this is a beta release and more tools will be added in the upcoming months, and existing tools will be optimized and refined.

:sparkles: New features

- Unique grid conditions (86)
- One-hot encoding (224)
- Extract shared lines (241)
- Coda transforms (244)
- Calculate geometry (248)
- Logistic regression (210)
- Random forest classifier and regressor (210)
- Gradient boosting classifier and regressor (210)
- Various modeling functions (split data, get cross-validator, load/save model, evaluate model, predict with model) (210)


🚀 Performance improvements

- Optimize IDW (226)
- Optimize distance computation (230)


🐞 Fixes

- Fix invalid CLI imports (distance computation, descriptive statistics) (223)
- Fix several issues with example notebooks (225)
- Fixed issue related to type checking in check_minmax_position function (242)
- Fixed two minor issues with Chi-square test (249)
- Corrections to raster exporting in CBA (250)

🛠️ Other improvements
- Added nodata handling (dropping) in Descriptive statistics (245)
- Miscellaneous ci and documentation additions (256)
- Update fuzzy overlay docs (258)

Roadmap

The first non-beta release of EIS Toolkit is planned for April 2024. All the planned tools should be implemented by then and requested new additions from Toolkit testers considered as much as possible. For planned tools, refer to the wiki page of this repository.

The first release of EIS QGIS Plugin, which serves a graphical user-interface for EIS Toolkit, should also happen in April 2024.