Data analysis and visualization tools¶

Data analysis and visualization tools are essential to understand material response data sets and evaluate the performance of material models. For this reason, HookeAI provides a complete toolkit to streamline the generation of insightful visualizations and provide material-related data analysis.

Key resources¶

Source file/directory	Description
`hookeai/ioput/plots.py`	Wide variety of plotting functions suitable for general visualization of numerical data.
`hookeai/model_architectures/model_prediction.py`	Essential prediction plots for generic time series data.
`hookeai/model_architectures/convergence_plots.py`	Convergence plots with respect to the training data set size, namely the prediction loss and generic time series predictions.
`hookeai/utilities/output_prediction_metrics.py`	Computation and plots of mean predictions metrics for generic time series data.
`hookeai/miscellaneous/materials/compare_material_models.py`	Stress prediction comparison between different material models on given strain-stress data set samples.
`hookeai/miscellaneous/materials/compare_hardening_laws.py`	Comparison of strain hardening laws for elastoplastic material models.
`hookeai/miscellaneous/materials/plot_yield_surface.py`	Visualization of yield surfaces of elastoplastic material models.
`hookeai/user_scripts/synthetic_data/gen_response_dataset.py`	Complete set of plots to describe strain-stress data sets.