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https://github.com/janosh/pymatviz
A toolkit for visualizations in materials informatics.
https://github.com/janosh/pymatviz
data-visualization machine-learning materials-informatics materials-science matplotlib plotly plots python uncertainty uncertainty-calibration
Last synced: 5 days ago
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A toolkit for visualizations in materials informatics.
- Host: GitHub
- URL: https://github.com/janosh/pymatviz
- Owner: janosh
- License: mit
- Created: 2021-02-21T12:40:34.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-10-18T20:34:09.000Z (17 days ago)
- Last Synced: 2024-10-20T06:11:34.124Z (16 days ago)
- Topics: data-visualization, machine-learning, materials-informatics, materials-science, matplotlib, plotly, plots, python, uncertainty, uncertainty-calibration
- Language: Python
- Homepage: https://janosh.github.io/pymatviz
- Size: 72.8 MB
- Stars: 164
- Watchers: 7
- Forks: 15
- Open Issues: 16
-
Metadata Files:
- Readme: readme.md
- Changelog: changelog.md
- License: license
- Citation: citation.cff
Awesome Lists containing this project
- awesome-materials-informatics - Pymatviz - A toolkit for visualizations in materials informatics. [](https://github.com/janosh/pymatviz) (Software and products)
- best-of-atomistic-machine-learning - GitHub - 30% open · ⏱️ 18.10.2024): (Visualization)
README
pymatviz
A toolkit for visualizations in materials informatics.
[](https://github.com/janosh/pymatviz/actions/workflows/test.yml)
[](https://python.org/downloads)
[](https://pypi.org/project/pymatviz)
[](https://pypistats.org/packages/pymatviz)
[](https://zenodo.org/records/10456384)
> If you use `pymatviz` in your research, [see how to cite](#how-to-cite-pymatviz).
## Installation
```sh
pip install pymatviz
```
## API Docs
See the [/api] page.
[/api]: https://janosh.github.io/pymatviz/api
## Usage
See the Jupyter notebooks under [`examples/`](examples) for how to use `pymatviz`. PRs with additional examples are welcome! 🙏
| | | |
| ---------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------ |
| [mlff_phonons.ipynb](https://github.com/janosh/pymatviz/blob/main/examples/mlff_phonons.ipynb) | [![Open in Google Colab]](https://colab.research.google.com/github/janosh/pymatviz/blob/main/examples/mlff_phonons.ipynb) | [![Launch Codespace]][codespace url] |
| [matbench_dielectric_eda.ipynb](https://github.com/janosh/pymatviz/blob/main/examples/matbench_dielectric_eda.ipynb) | [![Open in Google Colab]](https://colab.research.google.com/github/janosh/pymatviz/blob/main/examples/matbench_dielectric_eda.ipynb) | [![Launch Codespace]][codespace url] |
| [mp_bimodal_e_form.ipynb](https://github.com/janosh/pymatviz/blob/main/examples/mp_bimodal_e_form.ipynb) | [![Open in Google Colab]](https://colab.research.google.com/github/janosh/pymatviz/blob/main/examples/mp_bimodal_e_form.ipynb) | [![Launch Codespace]][codespace url] |
| [matbench_perovskites_eda.ipynb](https://github.com/janosh/pymatviz/blob/main/examples/matbench_perovskites_eda.ipynb) | [![Open in Google Colab]](https://colab.research.google.com/github/janosh/pymatviz/blob/main/examples/matbench_perovskites_eda.ipynb) | [![Launch Codespace]][codespace url] |
| [mprester_ptable.ipynb](https://github.com/janosh/pymatviz/blob/main/examples/mprester_ptable.ipynb) | [![Open in Google Colab]](https://colab.research.google.com/github/janosh/pymatviz/blob/main/examples/mprester_ptable.ipynb) | [![Launch Codespace]][codespace url] |
[Open in Google Colab]: https://colab.research.google.com/assets/colab-badge.svg
[Launch Codespace]: https://img.shields.io/badge/Launch-Codespace-darkblue?logo=github
[codespace url]: https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=340898532
## Periodic Table
See [`pymatviz/ptable/ptable_matplotlib.py`](pymatviz/ptable/ptable_matplotlib.py) and [`pymatviz/ptable/ptable_plotly.py`](pymatviz/ptable/ptable_plotly.py). `matplotlib` supports heatmaps, heatmap ratios, heatmap splits (multiple values per element), histograms, scatter plots and line plots. `plotly` currently only supports heatmaps (PRs to port over other `matplotlib` `ptable` variants to `plotly` are very welcome!). The `plotly` heatmap supports displaying additional data on hover or full interactivity through [Dash](https://plotly.com/dash).
| [`ptable_heatmap(compositions, log=True)`](pymatviz/ptable/ptable_matplotlib.py) | [`ptable_heatmap_ratio(comps_a, comps_b)`](pymatviz/ptable/ptable_matplotlib.py) |
| :--------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------: |
| ![ptable-heatmap] | ![ptable-heatmap-ratio] |
| [`ptable_heatmap_plotly(atomic_masses)`](pymatviz/ptable/ptable_plotly.py) | [`ptable_heatmap_plotly(compositions, log=True)`](pymatviz/ptable/ptable_matplotlib.py) |
| ![ptable-heatmap-plotly-more-hover-data] | ![ptable-heatmap-plotly-log] |
| [`ptable_hists(data, colormap="coolwarm")`](pymatviz/ptable/ptable_matplotlib.py) | [`ptable_lines(data)`](pymatviz/ptable/ptable_matplotlib.py) |
| ![ptable-hists] | ![ptable-lines] |
| [`ptable_scatters(data, colormap="coolwarm")`](pymatviz/ptable/ptable_matplotlib.py) | [`ptable_scatters(data, colormap="coolwarm")`](pymatviz/ptable/ptable_matplotlib.py) |
| ![ptable-scatters-parity] | ![ptable-scatters-parabola] |
| [`ptable_heatmap_splits(2_vals_per_elem, colormap="coolwarm", start_angle=135)`](pymatviz/ptable/ptable_matplotlib.py) | [`ptable_heatmap_splits(3_vals_per_elem, colormap="coolwarm", start_angle=90)`](pymatviz/ptable/ptable_matplotlib.py) |
| ![ptable-heatmap-splits-2] | ![ptable-heatmap-splits-3] |
[ptable-hists]: assets/ptable-hists.svg
[ptable-lines]: assets/homo-nuclear-mace-medium.svg
[ptable-scatters-parity]: assets/ptable-scatters-parity.svg
[ptable-scatters-parabola]: assets/ptable-scatters-parabola.svg
[ptable-heatmap-splits-2]: assets/ptable-heatmap-splits-2.svg
[ptable-heatmap-splits-3]: assets/ptable-heatmap-splits-3.svg
## Phonons
See [`examples/mlff_phonons.ipynb`](https://github.com/janosh/pymatviz/blob/main/examples/mlff_phonons.ipynb) for usage example.
| [`phonon_bands(bands_dict)`](pymatviz/phonons.py) | [`phonon_dos(doses_dict)`](pymatviz/phonons.py) |
| :-------------------------------------------------------------------: | :---------------------------------------------------------------------: |
| ![phonon-bands] | ![phonon-dos] |
| [`phonon_bands_and_dos(bands_dict, doses_dict)`](pymatviz/phonons.py) | [`phonon_bands_and_dos(single_bands, single_dos)`](pymatviz/phonons.py) |
| ![phonon-bands-and-dos-mp-2758] | ![phonon-bands-and-dos-mp-23907] |
[phonon-bands]: assets/phonon-bands-mp-2758.svg
[phonon-dos]: assets/phonon-dos-mp-2758.svg
[phonon-bands-and-dos-mp-2758]: assets/phonon-bands-and-dos-mp-2758.svg
[phonon-bands-and-dos-mp-23907]: assets/phonon-bands-and-dos-mp-23907.svg
### Dash app using `ptable_heatmap_plotly()`
See [`examples/mprester_ptable.ipynb`](https://github.com/janosh/pymatviz/blob/main/examples/mprester_ptable.ipynb).
## Structure
See [`pymatviz/structure_viz/(mpl|plotly).py`](pymatviz/structure_viz/plotly.py). Currently structure plotting is only supported with `matplotlib` in 2d. 3d interactive plots (probably with `plotly`) are on the road map.
| [`structure_2d(mp_19017)`](pymatviz/structure_viz/mpl.py) | [`structure_2d(mp_12712)`](pymatviz/structure_viz/mpl.py) |
| :--------------------------------------------------------------------: | :--------------------------------------------------------------------: |
| ![struct-2d-mp-19017-Li4Mn0.8Fe1.6P4C1.6O16-disordered] | ![struct-2d-mp-12712-Hf9Zr9Pd24-disordered] |
| [`structure_2d_plotly(six_structs)`](pymatviz/structure_viz/plotly.py) | [`structure_3d_plotly(six_structs)`](pymatviz/structure_viz/plotly.py) |
| ![matbench-phonons-structures-2d-plotly] | ![matbench-phonons-structures-3d-plotly] |
[matbench-phonons-structures-2d-plotly]: assets/matbench-phonons-structures-2d-plotly.svg
[matbench-phonons-structures-3d-plotly]: assets/matbench-phonons-structures-3d-plotly.svg
## X-Ray Diffraction
See [`pymatviz/xrd.py`](pymatviz/xrd.py).
| [`xrd_pattern(pattern)`](pymatviz/xrd.py) | [`xrd_pattern({key1: patt1, key2: patt2})`](pymatviz/xrd.py) |
| :---------------------------------------------------------------: | :-----------------------------------------------------------------------------------: |
| ![xrd-pattern] | ![xrd-pattern-multiple] |
| [`xrd_pattern(struct_dict, stack="horizontal")`](pymatviz/xrd.py) | [`xrd_pattern(struct_dict, stack="vertical", title="Custom Title")`](pymatviz/xrd.py) |
| ![xrd-pattern-horizontal-stack] | ![xrd-pattern-vertical-stack] |
[xrd-pattern]: assets/xrd-pattern.svg
[xrd-pattern-multiple]: assets/xrd-pattern-multiple.svg
[xrd-pattern-horizontal-stack]: assets/xrd-pattern-horizontal-stack.svg
[xrd-pattern-vertical-stack]: assets/xrd-pattern-vertical-stack.svg
## Radial Distribution Functions
See [`pymatviz/rdf/plotly.py`](pymatviz/rdf/plotly.py).
| [`rdf_plot(rdf)`](pymatviz/rdf/plotly.py) | [`rdf_plot(rdf, rdf2)`](pymatviz/rdf/plotly.py) |
| :---------------------------------------: | :---------------------------------------------: |
| ![element-pair-rdfs-Na8Nb8O24] | ![element-pair-rdfs-crystal-vs-amorphous] |
[element-pair-rdfs-Na8Nb8O24]: assets/element-pair-rdfs-Na8Nb8O24.svg
[element-pair-rdfs-crystal-vs-amorphous]: assets/element-pair-rdfs-crystal-vs-amorphous.svg
## Coordination
See [`pymatviz/coordination.py`](pymatviz/coordination.py).
| [`coordination_hist(struct_dict)`](pymatviz/coordination.py) | [`coordination_hist(struct_dict, by_element=True)`](pymatviz/coordination.py) |
| :-----------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------: |
| ![coordination-hist-single] | ![coordination-hist-by-structure-and-element] |
| [`coordination_vs_cutoff_line(struct_dict, strategy=None)`](pymatviz/coordination.py) | [`coordination_vs_cutoff_line(struct_dict, strategy=None)`](pymatviz/coordination.py) |
| ![coordination-vs-cutoff-single] | ![coordination-vs-cutoff-multiple] |
[coordination-hist-single]: assets/coordination-hist-single.svg
[coordination-hist-by-structure-and-element]: assets/coordination-hist-by-structure-and-element.svg
[coordination-vs-cutoff-single]: assets/coordination-vs-cutoff-single.svg
[coordination-vs-cutoff-multiple]: assets/coordination-vs-cutoff-multiple.svg
## Sunburst
See [`pymatviz/sunburst.py`](pymatviz/sunburst.py).
| [`spacegroup_sunburst([65, 134, 225, ...])`](pymatviz/sunburst.py) | [`spacegroup_sunburst(["C2/m", "P-43m", "Fm-3m", ...])`](pymatviz/sunburst.py) |
| :----------------------------------------------------------------: | :----------------------------------------------------------------------------: |
| ![spg-num-sunburst] | ![spg-symbol-sunburst] |
## Rainclouds
See [`pymatviz/rainclouds.py`](pymatviz/rainclouds.py).
| [`rainclouds(two_key_dict)`](pymatviz/rainclouds.py) | [`rainclouds(three_key_dict)`](pymatviz/rainclouds.py) |
| :--------------------------------------------------: | :----------------------------------------------------: |
| ![rainclouds-bimodal] | ![rainclouds-trimodal] |
[rainclouds-bimodal]: assets/rainclouds-bimodal.svg
[rainclouds-trimodal]: assets/rainclouds-trimodal.svg
## Sankey
See [`pymatviz/sankey.py`](pymatviz/sankey.py).
| [`sankey_from_2_df_cols(df_perovskites)`](pymatviz/sankey.py) | [`sankey_from_2_df_cols(df_space_groups)`](pymatviz/sankey.py) |
| :-----------------------------------------------------------: | :------------------------------------------------------------: |
| ![sankey-spglib-vs-aflow-spacegroups] | ![sankey-crystal-sys-to-spg-symbol] |
[sankey-spglib-vs-aflow-spacegroups]: assets/sankey-spglib-vs-aflow-spacegroups.svg
[sankey-crystal-sys-to-spg-symbol]: assets/sankey-crystal-sys-to-spg-symbol.svg
## Histograms
See [`pymatviz/histogram.py`](pymatviz/histogram.py).
| [`spacegroup_bar([65, 134, 225, ...], backend="matplotlib")`](pymatviz/histogram.py) | [`spacegroup_bar(["C2/m", "P-43m", "Fm-3m", ...], backend="matplotlib")`](pymatviz/histogram.py) |
| :----------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------: |
| ![spg-num-hist-matplotlib] | ![spg-symbol-hist-matplotlib] |
| [`spacegroup_bar([65, 134, 225, ...], backend="plotly")`](pymatviz/histogram.py) | [`spacegroup_bar(["C2/m", "P-43m", "Fm-3m", ...], backend="plotly")`](pymatviz/histogram.py) |
| ![spg-num-hist-plotly] | ![spg-symbol-hist-plotly] |
| [`elements_hist(compositions, log=True, bar_values='count')`](pymatviz/histogram.py) | [`histogram({'key1': values1, 'key2': values2})`](pymatviz/histogram.py) |
| ![elements-hist] | ![histogram-ecdf] |
[spg-symbol-hist-plotly]: assets/spg-symbol-hist-plotly.svg
[spg-num-hist-plotly]: assets/spg-num-hist-plotly.svg
[spg-num-hist-matplotlib]: assets/spg-num-hist-matplotlib.svg
[spg-symbol-hist-matplotlib]: assets/spg-symbol-hist-matplotlib.svg
[histogram-ecdf]: assets/histogram-ecdf.svg
## Scatter Plots
See [`pymatviz/scatter.py`](pymatviz/scatter.py).
| [`density_scatter_plotly(df, x=x_col, y=y_col, ...)`](pymatviz/scatter.py) | [`density_scatter_plotly(df, x=x_col, y=y_col, ...)`](pymatviz/scatter.py) |
| :------------------------------------------------------------------------: | :------------------------------------------------------------------------: |
| ![density-scatter-plotly] | ![density-scatter-plotly-blobs] |
| [`density_scatter(xs, ys, ...)`](pymatviz/scatter.py) | [`density_scatter_with_hist(xs, ys, ...)`](pymatviz/scatter.py) |
| ![density-scatter] | ![density-scatter-with-hist] |
| [`density_hexbin(xs, ys, ...)`](pymatviz/scatter.py) | [`density_hexbin_with_hist(xs, ys, ...)`](pymatviz/scatter.py) |
| ![density-hexbin] | ![density-hexbin-with-hist] |
[density-scatter-plotly]: assets/density-scatter-plotly.svg
[density-scatter-plotly-blobs]: assets/density-scatter-plotly-blobs.svg
[density-hexbin-with-hist]: assets/density-hexbin-with-hist.svg
[density-hexbin]: assets/density-hexbin.svg
[density-scatter-with-hist]: assets/density-scatter-with-hist.svg
[density-scatter]: assets/density-scatter.svg
## Uncertainty
See [`pymatviz/uncertainty.py`](pymatviz/uncertainty.py).
| [`qq_gaussian(y_true, y_pred, y_std)`](pymatviz/uncertainty.py) | [`qq_gaussian(y_true, y_pred, y_std: dict)`](pymatviz/uncertainty.py) |
| :-------------------------------------------------------------------------: | :-------------------------------------------------------------------------------: |
| ![normal-prob-plot] | ![normal-prob-plot-multiple] |
| [`error_decay_with_uncert(y_true, y_pred, y_std)`](pymatviz/uncertainty.py) | [`error_decay_with_uncert(y_true, y_pred, y_std: dict)`](pymatviz/uncertainty.py) |
| ![error-decay-with-uncert] | ![error-decay-with-uncert-multiple] |
## Cumulative Metrics
See [`pymatviz/cumulative.py`](pymatviz/cumulative.py).
| [`cumulative_error(preds, targets)`](pymatviz/cumulative.py) | [`cumulative_residual(preds, targets)`](pymatviz/cumulative.py) |
| :----------------------------------------------------------: | :-------------------------------------------------------------: |
| ![cumulative-error] | ![cumulative-residual] |
## Classification
See [`pymatviz/relevance.py`](pymatviz/relevance.py).
| [`roc_curve(targets, proba_pos)`](pymatviz/relevance.py) | [`precision_recall_curve(targets, proba_pos)`](pymatviz/relevance.py) |
| :------------------------------------------------------: | :-------------------------------------------------------------------: |
| ![roc-curve] | ![precision-recall-curve] |
[cumulative-error]: assets/cumulative-error.svg
[cumulative-residual]: assets/cumulative-residual.svg
[error-decay-with-uncert-multiple]: assets/error-decay-with-uncert-multiple.svg
[error-decay-with-uncert]: assets/error-decay-with-uncert.svg
[elements-hist]: assets/elements-hist.svg
[matbench-phonons-structures-2d]: assets/matbench-phonons-structures-2d.svg
[normal-prob-plot-multiple]: assets/normal-prob-plot-multiple.svg
[normal-prob-plot]: assets/normal-prob-plot.svg
[precision-recall-curve]: assets/precision-recall-curve.svg
[ptable-heatmap-plotly-log]: assets/ptable-heatmap-plotly-log.svg
[ptable-heatmap-plotly-more-hover-data]: assets/ptable-heatmap-plotly-more-hover-data.svg
[ptable-heatmap-ratio]: assets/ptable-heatmap-ratio.svg
[ptable-heatmap]: assets/ptable-heatmap.svg
[residual-vs-actual]: assets/residual-vs-actual.svg
[roc-curve]: assets/roc-curve.svg
[scatter-with-err-bar]: assets/scatter-with-err-bar.svg
[spg-num-sunburst]: assets/spg-num-sunburst.svg
[spg-symbol-sunburst]: assets/spg-symbol-sunburst.svg
[struct-2d-mp-12712-Hf9Zr9Pd24-disordered]: assets/struct-2d-mp-12712-Hf9Zr9Pd24-disordered.svg
[struct-2d-mp-19017-Li4Mn0.8Fe1.6P4C1.6O16-disordered]: assets/struct-2d-mp-19017-Li4Mn0.8Fe1.6P4C1.6O16-disordered.svg
## How to cite `pymatviz`
See [`citation.cff`](citation.cff) or cite the [Zenodo record](https://zenodo.org/badge/latestdoi/340898532) using the following BibTeX entry:
```bib
@software{riebesell_pymatviz_2022,
title = {Pymatviz: visualization toolkit for materials informatics},
author = {Riebesell, Janosh and Yang, Haoyu and Goodall, Rhys and Baird, Sterling G.},
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, replace with your date of access
version = {0.8.2}, % replace with the version you use
}
```