Metadata-Version: 2.3
Name: arpespythontools
Version: 1.2.2
Summary: Explore, analyze, visualize Angle Resolved Photoemission Spectroscopy (ARPES) data.
Home-page: https://pranabdas.github.io/arpespythontools/
License: MIT
Keywords: arpes,condensed-matter-physics,data-analysis,materials-science,matplotlib,photoelectron-spectroscopy,python,surface-science
Author: Pranab Das
Requires-Python: >=3.10,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Provides-Extra: lint
Provides-Extra: notebook
Requires-Dist: astropy (>=6.1.7)
Requires-Dist: autopep8 (>=2.3.1) ; extra == "lint"
Requires-Dist: jupyterlab (>=4.3.4) ; extra == "notebook"
Requires-Dist: matplotlib (>=3.10.0)
Requires-Dist: numpy (>=2.2.1)
Requires-Dist: psutil (>=6.1.1)
Requires-Dist: scipy (>=1.15.0)
Project-URL: Documentation, https://pranabdas.github.io/arpespythontools/docs/
Project-URL: Repository, https://github.com/pranabdas/arpespythontools
Description-Content-Type: text/markdown

<h1 align="center">ARPES Python Tools</h1>

<p align="center">
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  <a href="https://github.com/pranabdas/arpespythontools/blob/master/LICENSE"><img src="https://img.shields.io/github/license/sourcerer-io/hall-of-fame.svg?colorB=A31F34"></a>
  <a href="https://pypi.org/project/arpespythontools/#history"><img src="https://img.shields.io/github/v/release/pranabdas/arpespythontools.svg" alt="Latest Release"/></a>
  <a href="https://pypi.org/project/arpespythontools/"><img src="https://img.shields.io/pypi/pyversions/arpespythontools" alt="Supported Python versions"/></a>
</p>

This python library helps you load, analyze and visualize ARPES data.

## Quick start

Install latest stable version:
```console
pip install --upgrade arpespythontools
```

Import and start using:

```python
import arpespythontools as arp

data, energy, angle = arp.load_ses_spectra("sample_spectrum.txt")
data_k, e_bin, k = arp.k_conv(data, energy, angle, 16.67)
```

Please find the detailed documentation here: https://pranabdas.github.io/arpespythontools/

