Releases: GispoCoding/eis_toolkit
v1.0.0
✨ Available tools
Conversions
- CSV to geodataframe
- Raster to dataframe
Evaluation
- Calculate base metrics (true positive rate, false positive rate, proportion of area)
- Summarize label metrics (for binary classification)
- Summarize probability metrics (for binary classification)
- Plot ROC (receiver operating characteristic) curve
- Plot DET (detection error tradeoff) curve
- Plot precision-recall curve
- Plot calibration curve (reliability curve)
- Plot distribution of predicted probabilities
- Plot confusion matrix
- Plot neural network loss
- Plot neural network accuracy
- Plot prediction area curves
- Plot rate curve
- Score predictions (mae, mse, rmse, r2, accuracy, precision, recall, f1)
Exploratory analysis
- Basic plots (re-exports from Seaborn – barplot, boxplot, ecdfplot, heatmap, histplot, kdeplot, lineplot, pairplot, regplot, scatterplot)
- Chi-square test
- Correlation matrix & plot correlation matrix
- Covariance matrix
- DBSCAN (array & dataframe versions)
- Descriptive statistics (raster & geodataframe versions)
- Evaluate feature importance (for ML model)
- K-means clustering (array & dataframe versions)
- Local Moran's I
- Normality test (array & dataframe versions)
- Plot parallel coordinates
- Compute PCA & plot PCA
Prediction
- Fuzzy overlay (AND, OR, PRODUCT, SUM, GAMMA)
- Train gradient boosting classifier & regressor
- Train random forest classifier & regressor
- Train logistic regression model
- Train MLP classifier & regressor
- ML modeling utility tools: save model, load model, split data, reshape predictions, prepare data for ML, read data for evaluation
- Predict classifier & regressor
Raster processing
- Clip raster
- Create constant raster
- Distance to anomaly
- Extract values from raster
- Reclassify (manual breaks, defined intervals, equal intervals, quantiles, natural breaks, geometric intervals, standard deviation)
- Reproject
- Resample
- Snap
- Unify rasters
- Unique combinations
- Extract window
- Filters
- Focal filter
- Gaussian filter
- Mexican hat filter
- Lee additive noise filter
- Lee multiplicative noise filter
- Lee additive multiplicative noise filter
- Lee enhanced filter
- Gamma filter
- Frost filter
- Kuan filter
- Derivatives
- First order surface derivatives
- Second order surface derivatives
- Classify aspect
Training data tools
- Balance classes (SMOTETomek)
Transformations
- Binarize
- Clip transform
- Min-max scale
- Z-score normalize
- Log transform (ln, log2, log10)
- One-hot encode
- Sigmoid transform
- Winsorize
- CODA transforms
- ALR transform
- Inverse ALR transform
- CLR transform
- Inverse CLR transform
- Single ILR transform
- Single pairwise logratio
- Pairwise logratio
- Single PLR transform
- PLR transform
Vector processing
- Calculate geometry (length for line, area for polygon)
- Cell based association
- Distance computation
- Extract shared lines
- IDW interpolation
- Kriging interpolation
- Rasterize vector
- Reproject vector
- Vector density
Utilities
- Various utilities regrading rasters, vectors, nodata and more. Individual tools/functions not listed here
🌱 Work in progress
- Weights of evidence (calculate weights and calculate responses) – this tool is already included in EIS Toolkit but will undergo some changes in near future
- CNN classifier & regressor models
- Autoencoder for image segmentation
- Mini-Unet for image segmentation
- Data sampler
- Mahalanobis similarity
- Bayesian NN
v0.5.2
v0.5.1
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
v0.5.0
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 (#324)
- Add K-means clustering for raster data (#365)
- Add DBSCAN for raster data (#366)
- Add Confusion matrix plot (#363)
- Add Neural network accuracy and loss plots (#362)
- Add some raster utility tools (#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 (#368)
- Add CLI implementations for many tools
🐞 Fixes
- Fix rasterization of vector label data for ML models called from CLI
- Fix fuzzy sum logic (#381)
🛠️ Other improvements
- Add Criterion parameter to Random Forest models (#345)
- Add nodata handling to Raster to dataframe tool (#364)
- Add max distance parameter to Distance computation and Distance to anomaly (#382)
- Change resampling_method parameter type in Resample raster tool to literal/str (#349)
- Refactor vector -> raster tools: base raster and pixel size + extent to define output raster grid are now available for all of the tools (#375 and #376)
- Refactor validation category. Now called evaluation (#368)
v0.4.0
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
🐞 Fixes
🛠️ Other improvements
- Remove GDAL version restriction (#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.
v0.3.0
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 (#252)
- Surface derivatives (#255)
- Filter and smoothing functions (#289)
- CLI implementations for many tools
🐞 Fixes
- Fix/improve normality test (#267)
- Fix/improve correlation and covariance matrix functions (#268)
- Fix/improve PCA (#269)
🛠️ Other improvements
- Change raster grid check to use only raster metadata/profile instead of raster dataset (#281)
- Added PySAL and ESDA Python packages to repository (#288)
- Minor clean-up PR (#295)
- Small notebook fixes (#296)
- Documentation additions for filter functions (#303)
- Documentation for derivative functions (#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.
v0.2.0-beta
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.
✨ 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
🐞 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.
v0.1.0-beta
EIS Toolkit beta release
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.
Tools included in the release
Conversions
- CSV to dataframe
- Raster to dataframe
Exploratory analysis
- Basic plotting functions from Seaborn (barplot, boxplot, edfcplot, heatmap, histplot, kdeplot, lineplot, pairplot, regplot, scatterplot)
- DBSCAN
- Descriptive statistics (min, max, mean, median, quantiles, standard deviation, relative standard deviation, skew)
- Feature importance evaluation
- K-means clustering
- Plot parallel coordinates
- PCA
- Statistical tests (independence, normality, correlation, covariance)
Prediction
- Fuzzy overlay
- Weights of evidence
Raster processing
- Clip raster
- Create constant raster
- Extract values from raster
- Reproject raster
- Resample raster
- Snap rasters
- Unify rasters
- Extract window from raster
Training data tools
- Balance data (SMOTETomek)
Transformations
- Binarize transform
- Clip transform
- Z-score normalization
- Min-max scaling
- Log transforms (log2, log10, ln)
- Sigmoid transform
- Winsorize
Validation
- Calculate AUC (area under curve)
- Calculate base metrics (true positive rate, proportion of area and false positive rate values)
- Plot correlation matrix
- Plot prediction area curves
- Plot rate curve
Vector processing
- CBA (cell-based association)
- Distance computation
- IDW interpolation
- Kriging interpolation
- Rasterize vector
- Reproject vector
- Vector density
Command-line interface
- Most of the included tools are also available to use from command-line. To get started with this, use the command
eis --helpafter installation. Note that the command-line interface has been primarily designed to be an entry-point for other programs and not for direct use
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.
