Metadata-Version: 2.1
Name: pymatviz
Version: 0.9.2
Summary: A toolkit for visualizations in materials informatics
Author-email: Janosh Riebesell <janosh.riebesell@gmail.com>
License: MIT License
        
        Copyright (c) 2021 Janosh Riebesell
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        The software is provided "as is", without warranty of any kind, express or
        implied, including but not limited to the warranties of merchantability,
        fitness for a particular purpose and noninfringement. In no event shall the
        authors or copyright holders be liable for any claim, damages or other
        liability, whether in an action of contract, tort or otherwise, arising from,
        out of or in connection with the software or the use or other dealings in the
        software.
        
Project-URL: Homepage, https://github.com/janosh/pymatviz
Keywords: chemistry,data visualization,materials discovery,materials informatics,matplotlib,plotly,science
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: matplotlib>=3.6.2
Requires-Dist: numpy<2,>=1.21.0
Requires-Dist: pandas>=2.0.0
Requires-Dist: plotly
Requires-Dist: pymatgen
Requires-Dist: scikit-learn
Requires-Dist: scipy
Provides-Extra: test
Requires-Dist: adjustText; extra == "test"
Requires-Dist: jinja2; extra == "test"
Requires-Dist: kaleido; extra == "test"
Requires-Dist: pdfCropMargins; extra == "test"
Requires-Dist: pytest; extra == "test"
Requires-Dist: pytest-cov; extra == "test"
Requires-Dist: weasyprint; extra == "test"
Provides-Extra: data-src
Requires-Dist: matminer; extra == "data-src"
Requires-Dist: mp_api; extra == "data-src"
Provides-Extra: export-figs
Requires-Dist: kaleido; extra == "export-figs"
Provides-Extra: gh-pages
Requires-Dist: jupyter; extra == "gh-pages"
Requires-Dist: lazydocs; extra == "gh-pages"
Requires-Dist: nbconvert; extra == "gh-pages"
Provides-Extra: df-pdf-export
Requires-Dist: jinja2; extra == "df-pdf-export"
Requires-Dist: pdfCropMargins; extra == "df-pdf-export"
Requires-Dist: weasyprint; extra == "df-pdf-export"
Provides-Extra: auto-text-pos
Requires-Dist: adjustText; extra == "auto-text-pos"

<h1 align="center">
<img src="https://github.com/janosh/pymatviz/raw/main/site/static/favicon.svg" alt="Logo" height="60px">
<br class="hide-in-docs">
pymatviz
</h1>

<h4 align="center" class="toc-exclude">

A toolkit for visualizations in materials informatics.

[![Tests](https://github.com/janosh/pymatviz/actions/workflows/test.yml/badge.svg)](https://github.com/janosh/pymatviz/actions/workflows/test.yml)
[![This project supports Python 3.9+](https://img.shields.io/badge/Python-3.9+-blue.svg?logo=python&logoColor=white)](https://python.org/downloads)
[![PyPI](https://img.shields.io/pypi/v/pymatviz?logo=pypi&logoColor=white)](https://pypi.org/project/pymatviz)
[![PyPI Downloads](https://img.shields.io/pypi/dm/pymatviz?logo=icloud&logoColor=white)](https://pypistats.org/packages/pymatviz)
[![Zenodo](https://img.shields.io/badge/DOI-10.5281/zenodo.10456384-blue?logo=Zenodo&logoColor=white)](https://zenodo.org/records/10456384)

</h4>

<slot name="how-to-cite">

> If you use `pymatviz` in your research, [see how to cite](#how-to-cite-pymatviz).

</slot>

## 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]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-hists.svg
[ptable-lines]: https://github.com/janosh/pymatviz/raw/main/examples/diatomics/homo-nuclear-mace-medium.svg
[ptable-scatters-parity]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-scatters-parity.svg
[ptable-scatters-parabola]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-scatters-parabola.svg
[ptable-heatmap-splits-2]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-heatmap-splits-2.svg
[ptable-heatmap-splits-3]: https://github.com/janosh/pymatviz/raw/main/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.

|           [`plot_phonon_bands(bands_dict)`](pymatviz/phonons.py)           |             [`plot_phonon_dos(doses_dict)`](pymatviz/phonons.py)             |
| :------------------------------------------------------------------------: | :--------------------------------------------------------------------------: |
|                              ![phonon-bands]                               |                                ![phonon-dos]                                 |
| [`plot_phonon_bands_and_dos(bands_dict, doses_dict)`](pymatviz/phonons.py) | [`plot_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]: https://github.com/janosh/pymatviz/raw/main/assets/phonon-bands-mp-2758.svg
[phonon-dos]: https://github.com/janosh/pymatviz/raw/main/assets/phonon-dos-mp-2758.svg
[phonon-bands-and-dos-mp-2758]: https://github.com/janosh/pymatviz/raw/main/assets/phonon-bands-and-dos-mp-2758.svg
[phonon-bands-and-dos-mp-23907]: https://github.com/janosh/pymatviz/raw/main/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).

<https://user-images.githubusercontent.com/30958850/181644052-b330f0a2-70fc-451c-8230-20d45d3af72f.mp4>

## 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]                             |

## Sankey

See [`pymatviz/sankey.py`](pymatviz/sankey.py).

| [`sankey_from_2_df_cols(df_perovskites)`](pymatviz/sankey.py) | [`sankey_from_2_df_cols(df_rand_ints)`](pymatviz/sankey.py) |
| :-----------------------------------------------------------: | :---------------------------------------------------------: |
|             ![sankey-spglib-vs-aflow-spacegroups]             |              ![sankey-from-2-df-cols-randints]              |

## Structure

See [`pymatviz/structure_viz.py`](pymatviz/structure_viz.py). Currently structure plotting is only supported with `matplotlib` in 2d. 3d interactive plots (probably with `plotly`) are on the road map.

| [`plot_structure_2d(mp_19017)`](pymatviz/structure_viz.py) | [`plot_structure_2d(mp_12712)`](pymatviz/structure_viz.py) |
| :--------------------------------------------------------: | :--------------------------------------------------------: |
|  ![struct-2d-mp-19017-Li4Mn0.8Fe1.6P4C1.6O16-disordered]   |        ![struct-2d-mp-12712-Hf9Zr9Pd24-disordered]         |

![matbench-phonons-structures-2d]

## Histograms

See [`pymatviz/histograms.py`](pymatviz/histograms.py).

| [`spacegroup_hist([65, 134, 225, ...], backend="matplotlib")`](pymatviz/histograms.py) | [`spacegroup_hist(["C2/m", "P-43m", "Fm-3m", ...], backend="matplotlib")`](pymatviz/histograms.py) |
| :------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------: |
|                               ![spg-num-hist-matplotlib]                               |                                   ![spg-symbol-hist-matplotlib]                                    |
|   [`spacegroup_hist([65, 134, 225, ...], backend="plotly")`](pymatviz/histograms.py)   |   [`spacegroup_hist(["C2/m", "P-43m", "Fm-3m", ...], backend="plotly")`](pymatviz/histograms.py)   |
|                                 ![spg-num-hist-plotly]                                 |                                     ![spg-symbol-hist-plotly]                                      |
| [`elements_hist(compositions, log=True, bar_values='count')`](pymatviz/histograms.py)  |           [`plot_histogram({'key1': values1, 'key2': values2})`](pymatviz/histograms.py)           |
|                                    ![elements-hist]                                    |                                       ![plot-histogram-ecdf]                                       |

[spg-symbol-hist-plotly]: https://github.com/janosh/pymatviz/raw/main/assets/spg-symbol-hist-plotly.svg
[spg-num-hist-plotly]: https://github.com/janosh/pymatviz/raw/main/assets/spg-num-hist-plotly.svg
[spg-num-hist-matplotlib]: https://github.com/janosh/pymatviz/raw/main/assets/spg-num-hist-matplotlib.svg
[spg-symbol-hist-matplotlib]: https://github.com/janosh/pymatviz/raw/main/assets/spg-symbol-hist-matplotlib.svg
[plot-histogram-ecdf]: https://github.com/janosh/pymatviz/raw/main/assets/plot-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]: https://github.com/janosh/pymatviz/raw/main/assets/density-scatter-plotly.svg
[density-scatter-plotly-blobs]: https://github.com/janosh/pymatviz/raw/main/assets/density-scatter-plotly-blobs.svg
[density-hexbin-with-hist]: https://github.com/janosh/pymatviz/raw/main/assets/density-hexbin-with-hist.svg
[density-hexbin]: https://github.com/janosh/pymatviz/raw/main/assets/density-hexbin.svg
[density-scatter-with-hist]: https://github.com/janosh/pymatviz/raw/main/assets/density-scatter-with-hist.svg
[density-scatter]: https://github.com/janosh/pymatviz/raw/main/assets/density-scatter.svg

## X-Ray Diffraction

See [`pymatviz/xrd.py`](pymatviz/xrd.py).

| [`plot_xrd_pattern(pattern)`](pymatviz/xrd.py) | [`plot_xrd_pattern({key1: patt1, key2: patt2})`](pymatviz/xrd.py) |
| :--------------------------------------------: | :---------------------------------------------------------------: |
|                 ![xrd-pattern]                 |                      ![xrd-pattern-multiple]                      |

[xrd-pattern]: https://github.com/janosh/pymatviz/raw/main/assets/xrd-pattern.svg
[xrd-pattern-multiple]: https://github.com/janosh/pymatviz/raw/main/assets/xrd-pattern-multiple.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]                       |

## Correlation

See [`pymatviz/correlation.py`](pymatviz/correlation.py).

| [`marchenko_pastur(corr_mat, gamma=ncols/nrows)`](pymatviz/correlation.py) | [`marchenko_pastur(corr_mat_significant_eval, gamma=ncols/nrows)`](pymatviz/correlation.py) |
| :------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------: |
|                            ![marchenko-pastur]                             |                            ![marchenko-pastur-significant-eval]                             |

[cumulative-error]: https://github.com/janosh/pymatviz/raw/main/assets/cumulative-error.svg
[cumulative-residual]: https://github.com/janosh/pymatviz/raw/main/assets/cumulative-residual.svg
[error-decay-with-uncert-multiple]: https://github.com/janosh/pymatviz/raw/main/assets/error-decay-with-uncert-multiple.svg
[error-decay-with-uncert]: https://github.com/janosh/pymatviz/raw/main/assets/error-decay-with-uncert.svg
[elements-hist]: https://github.com/janosh/pymatviz/raw/main/assets/elements-hist.svg
[marchenko-pastur-significant-eval]: https://github.com/janosh/pymatviz/raw/main/assets/marchenko-pastur-significant-eval.svg
[marchenko-pastur]: https://github.com/janosh/pymatviz/raw/main/assets/marchenko-pastur.svg
[matbench-phonons-structures-2d]: https://github.com/janosh/pymatviz/raw/main/assets/matbench-phonons-structures-2d.svg
[normal-prob-plot-multiple]: https://github.com/janosh/pymatviz/raw/main/assets/normal-prob-plot-multiple.svg
[normal-prob-plot]: https://github.com/janosh/pymatviz/raw/main/assets/normal-prob-plot.svg
[precision-recall-curve]: https://github.com/janosh/pymatviz/raw/main/assets/precision-recall-curve.svg
[ptable-heatmap-plotly-log]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-heatmap-plotly-log.svg
[ptable-heatmap-plotly-more-hover-data]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-heatmap-plotly-more-hover-data.svg
[ptable-heatmap-ratio]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-heatmap-ratio.svg
[ptable-heatmap]: https://github.com/janosh/pymatviz/raw/main/assets/ptable-heatmap.svg
[residual-vs-actual]: https://github.com/janosh/pymatviz/raw/main/assets/residual-vs-actual.svg
[roc-curve]: https://github.com/janosh/pymatviz/raw/main/assets/roc-curve.svg
[sankey-from-2-df-cols-randints]: https://github.com/janosh/pymatviz/raw/main/assets/sankey-from-2-df-cols-randints.svg
[sankey-spglib-vs-aflow-spacegroups]: https://github.com/janosh/pymatviz/raw/main/assets/sankey-spglib-vs-aflow-spacegroups.svg
[scatter-with-err-bar]: https://github.com/janosh/pymatviz/raw/main/assets/scatter-with-err-bar.svg
[spg-num-sunburst]: https://github.com/janosh/pymatviz/raw/main/assets/spg-num-sunburst.svg
[spg-symbol-sunburst]: https://github.com/janosh/pymatviz/raw/main/assets/spg-symbol-sunburst.svg
[struct-2d-mp-12712-Hf9Zr9Pd24-disordered]: https://github.com/janosh/pymatviz/raw/main/assets/struct-2d-mp-12712-Hf9Zr9Pd24-disordered.svg
[struct-2d-mp-19017-Li4Mn0.8Fe1.6P4C1.6O16-disordered]: https://github.com/janosh/pymatviz/raw/main/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
}
```
