Examples#
This page contains some plotting guides for using watex. It is broken up into base, methods, view, and plot utility sections. For more in-depth guide, visit the full user guide.
Most of the data used for the plot examples are real-world geosciences engineering data. However, the scripts implemented for the visualization work with any kind of dataset.
Applications: Step-by-step guide#
These examples show a step-by-step guide for computing the DC-parameters, the mixture learning strategy to predict the permeability coefficient \(k\)
and restoring tensors via the modules watex.methods
and watex.utils.hydroutils
. The feature analyses and visualization are performed using the watex.view
module.
The datasets explanation can be found in watex.datasets
.
Auto-detect the drilling location
EM, DC, and Hydro parameters computing
Fast AMT data processing from Stratagem hardware
Predict FR from DC-Resistivity data
Restoring tensor with noised AMT data
k-prediction from MXS: step-by-step guide
Base assessors & estimators#
Examples concerning the watex.base
module.
Plot Linear Adaptative Neuron Classifier (Adaline)
Plot Sequential Backward Selection (SBS)
Plot Stochastic Linear Adaptative Neuron Classifier
Plot data with missing features
Analyses#
Examples concerning the watex.analysis
module.
Linear discriminant analysis (LDA)
PCA vs Factor Analysis with scedatic noises
Methods#
Examples concerning the watex.methods
module.
Electrical Resistivity Profiling (ERP)
Plot Pseudosection Phase tensors
Plot logging Predictor and target
Plot multiple sites signal recovery
Vertical Electrical Sounding (VES)
Plot utilities#
Examples concerning the watex.utils.plotutils
module.
Plot electrical resistivity profiling (ERP)
Plot feature importance with Randomforest
Plot feature selection with SBS
Plot principal components analysis (PCA) components
Plot pseudo-fracturing index (sfi)
Visualizations#
Examples concerning the watex.view
module.
Plot Receiving Operating Characteristic (ROC)
Plot Regression learning scoring
Plot apparent resistivity curves
Plot bipolar with Principal component analysis (PCA)
Plot dendrogram combined with heatmap
Plot features vs target on histogram plots
Plot multiple categorical feature distributions
Plot robust principal components analysis (PCA)
Plot single learning inspection
Plot single site signal recovery
Plot two dimensional dimensional filtered tensor
Plot two dimensional phase tensors
Plot two dimensional resistivity tensors