Eis-toolkit

Latest version: v1.1.1

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1.1.1

🚀 Performance improvements
- Optimize distance computation (455) (**NOTE**: This optimization affects also `distance_to_anomaly`, `proximity_to_anomaly` and `proximity_computation`)

🐞 Fixes
- Fix missing data closure requirement for CoDA transformations (457)
- Fix plots not being saved correctly when also shown immediately in CLI functions (461)

1.1.0

🐞 Fixes
- Fix issue with winsorize transform when only one percentile was given (450)
- Fix numeric input column checking for Local Moran's I tool (453)

🛠️ Other improvements
- Pin `scipy` version to 1.11.4 to ensure Local Moran's I tool works (451)

1.0.3

✨ New features
- Min-max scaling can be used to scale data inversly (436)
- Added Proximity computation tool (432)
- Added Proximity to anomaly tool (440)
- Added Agterberg-Cheng CI test for Weights of evidence (343)
- Added optimized version of Distance to anomaly tool (requires Windows and to ensure installation of `gdal_array`) (423)

🐞 Fixes
- Fixed transformations tool failing when raster metadata did not have nodata defined (436)
- Fixed PCA tools and updated outputs (446)

🛠️ Other improvements
- Modified/improved Weights of evidence tool (355)
- Removed defaults channel from conda installation instructions (434)
- Added issue templates for new tool requests and bug reports (317)

1.0.2

✨ New features
- Added CLI functions for MLP classifier and regessor (412)
- Added Mask raster tool (413)
- Added CLI function for Mask raster tool (419)

🐞 Fixes
- Fixed Keras model saving and available metrics (412)
- Fixed return data dimension when predicting with Keras regressor model (412)
- Fixed issues with CoDa tools (416 )

🛠️ Other improvements
- Added masking parameter to Unify raster grids tool (417)
- Added band parameter to Descriptive statistics raster too (428)

1.0.1

🐞 Fixes
- Fix unify raster grids copying unwanted raster metadata (402)
- Fix invalid scoring for binary classification models (408)

🛠️ Other improvements
- Reduce number of shown decimals in numeric tool outputs (411)
- Extend documentation (Conda installation) (400)

1.0.0

✨ 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

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