Package: pymatviz
pymatvizA toolkit for visualizations in materials informatics.If you usepymatvizin your research,see how to cite.🔨   Installationpipinstallpymatviz💡   API DocsSee the/apipage.📙   UsageSee the Jupyter notebooks underexamples/for how to usepymatviz. PRs with additional examples are welcome! 🙏matbench_dielectric_eda.ipynbmp_bimodal_e_form.ipynbmatbench_perovskites_eda.ipynbmprester_ptable.ipynbPeriodic TableSeepymatviz/ptable.py. Heatmaps of the periodic table can be plotted both withmatplotlibandplotly.plotlysupports displaying additional data on hover or full interactivity throughDash.ptable_heatmap(compositions, log=True)ptable_heatmap_ratio(comps_a, comps_b)ptable_heatmap_plotly(atomic_masses)ptable_heatmap_plotly(compositions, log=True)Nested Periodic TableSeepymatviz/ptable.py. Plot histogram plots and scatter plots nested within periodic table.ptable_hists(data, colormap="coolwarm"ptable_scatters(data, colormap="coolwarm"|||PhononsSeepymatviz/phonons.py.plot_phonon_bands(bands_dict)plot_phonon_dos(doses_dict)plot_phonon_bands_and_dos(bands_dict, doses_dict)Dash app usingptable_heatmap_plotly()Seeexamples/mprester_ptable.ipynb.https://user-images.githubusercontent.com/30958850/181644052-b330f0a2-70fc-451c-8230-20d45d3af72f.mp4SunburstSeepymatviz/sunburst.py.spacegroup_sunburst([65, 134, 225, ...])spacegroup_sunburst(["C2/m", "P-43m", "Fm-3m", ...])SankeySeepymatviz/sankey.py.sankey_from_2_df_cols(df_perovskites)sankey_from_2_df_cols(df_rand_ints)StructureSeepymatviz/structure_viz.py. Currently structure plotting is only supported withmatplotlibin 2d. 3d interactive plots (probably withplotly) are on the road map.plot_structure_2d(mp_19017)plot_structure_2d(mp_12712)HistogramsSeepymatviz/histograms.py.spacegroup_hist([65, 134, 225, ...], backend="matplotlib")spacegroup_hist(["C2/m", "P-43m", "Fm-3m", ...], backend="matplotlib")spacegroup_hist([65, 134, 225, ...], backend="plotly")spacegroup_hist(["C2/m", "P-43m", "Fm-3m", ...], backend="plotly")elements_hist(compositions, log=True, bar_values='count')Parity PlotsSeepymatviz/parity.py.density_scatter(xs, ys, ...)density_scatter_with_hist(xs, ys, ...)density_hexbin(xs, ys, ...)density_hexbin_with_hist(xs, ys, ...)scatter_with_err_bar(xs, ys, yerr, ...)residual_vs_actual(y_true, y_pred, ...)Uncertainty CalibrationSeepymatviz/uncertainty.py.qq_gaussian(y_true, y_pred, y_std)qq_gaussian(y_true, y_pred, y_std: dict)error_decay_with_uncert(y_true, y_pred, y_std)error_decay_with_uncert(y_true, y_pred, y_std: dict)Cumulative Error & ResidualSeepymatviz/cumulative.py.cumulative_error(preds, targets)cumulative_residual(preds, targets)Classification MetricsSeepymatviz/relevance.py.roc_curve(targets, proba_pos)precision_recall_curve(targets, proba_pos)CorrelationSeepymatviz/correlation.py.marchenko_pastur(corr_mat, gamma=ncols/nrows)marchenko_pastur(corr_mat_significant_eval, gamma=ncols/nrows)📖   How to citepymatvizYou can cite theZenodo recordusing the following BibTeX entry:@software{riebesell_pymatviz_2022,title={Pymatviz: visualization toolkit for materials informatics},author={Riebesell, Janosh},date={2022-10-01},year={2022},doi={10.5281/zenodo.7486816},url={https://github.com/janosh/pymatviz},note={10.5281/zenodo.7486816 - https://github.com/janosh/pymatviz},urldate={2023-01-01},%optional,replacewithyourdateofaccessversion={0.7.1}, % replace with the version you use}