Analysis and post-processing ============================ This section contains recipes that analyze the output of a simulation, for analysis or visualization purposes. .. grid:: 1 2 2 3 :gutter: 1 1 2 3 .. grid-item:: .. card:: PCA/PCovR Visualization for the rattled GaAs training dataset :link: ../examples/gaas-map/gaas-map :link-type: doc :text-align: center :shadow: md .. image:: ../examples/gaas-map/images/thumb/sphx_glr_gaas-map_thumb.png :alt: This example uses rascaline and metatensor to compute structural properties for the structures in a training for a ML model. These are then used with simple dimensionality reduction algorithms (implemented in sklearn and skmatter) to obtain a simplified description of the dataset, that is then visualized using chemiscope. :class: gallery-img .. grid-item:: .. card:: LPR analysis for amorphous silicon dataset :link: ../examples/lpr/lpr :link-type: doc :text-align: center :shadow: md .. image:: ../examples/lpr/images/thumb/sphx_glr_lpr_thumb.png :alt: In this tutorial, we calculate the SOAP descriptors of an amorphous silicon dataset using rascaline, then compute the local prediction rigidity (LPR) for the atoms of a "test" set before and after modifications to the "training" dataset has been made. :class: gallery-img .. grid-item:: .. card:: Generalized Convex Hull construction for the polymorphs of ROY :link: ../examples/roy-gch/roy-gch :link-type: doc :text-align: center :shadow: md .. image:: ../examples/roy-gch/images/thumb/sphx_glr_roy-gch_thumb.png :alt: This notebook analyzes the structures of 264 polymorphs of ROY, from Beran et Al, Chemical Science (2022), comparing the conventional density-energy convex hull with a Generalized Convex Hull (GCH) analysis (see Anelli et al., Phys. Rev. Materials (2018)). It uses features computed with rascaline and uses the directional convex hull function from scikit-matter to make the figure. :class: gallery-img