https://github.com/pycroscopy/pycroscopy

Scientific analysis of nanoscale materials imaging data
https://github.com/pycroscopy/pycroscopy

afm atom atomic-force-microscopy electron-microscopy fft imaging infrared machine-learning materials-science microscopy raman scanning scanning-probe-microscopy scanning-tunnelling-microscopy signal-processing spectroscopy statistics stem stm visualization

Last synced: 5 months ago
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Scientific analysis of nanoscale materials imaging data

• Host: GitHub
• URL: https://github.com/pycroscopy/pycroscopy
• Owner: pycroscopy
• License: mit
• Created: 2016-06-18T23:12:18.000Z (over 9 years ago)
• Default Branch: main
• Last Pushed: 2025-03-07T22:43:05.000Z (7 months ago)
• Last Synced: 2025-05-15T06:08:17.133Z (5 months ago)
• Topics: afm, atom, atomic-force-microscopy, electron-microscopy, fft, imaging, infrared, machine-learning, materials-science, microscopy, raman, scanning, scanning-probe-microscopy, scanning-tunnelling-microscopy, signal-processing, spectroscopy, statistics, stem, stm, visualization
• Language: Jupyter Notebook
• Homepage: https://pycroscopy.github.io/pycroscopy/about.html
• Size: 354 MB
• Stars: 265
• Watchers: 30
• Forks: 75
• Open Issues: 49
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

          
# pycroscopy

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**pycroscopy** is a [Python](http://www.python.org/) package for generic (domain-agnostic) microscopy data analysis. More specialized or domain-specific analysis routines are contained within some of the other packages within the pycroscopy ecosystem.

Please visit our [homepage](https://pycroscopy.github.io/pycroscopy/about.html) for more information and installation instructions.

If you use pycroscopy for research, we would appreciate if you could cite our [Arxiv paper](https://arxiv.org/abs/1903.09515) titled *"USID and Pycroscopy - Open frameworks for storing and analyzing spectroscopic and imaging data".*

## Examples:

1. **Intro to pycroscopy** - [![Google Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pycroscopy/pycroscopy/blob/main/jupyter_notebooks/Intro_to_Pycroscopy.ipynb)

2. **Image inpainting** - [![Google Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pycroscopy/pycroscopy/blob/main/jupyter_notebooks/Inpainting_example.ipynb)

3. **Denoising with Autoencoders** - [![Google Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pycroscopy/pycroscopy/blob/main/jupyter_notebooks/PycroscopyDenosingAutoencoder.ipynb)

## More examples in the [jupyter_notebooks](jupyter_notebooks/) folder.

## List of Workshops Held

### 2024

- **[Machine Learning in Scanning Transmission Electron Microscopy Workshop 2024, University of Tennessee, Knoville, TN](https://github.com/gduscher/MLSTEM2024)**

### 2023

- **[ML-ElectronMicroscopy-school-2023](https://github.com/SergeiVKalinin/ML-ElectronMicroscopy-2023)**

- **[AutomatedExperiment_Summer2023](https://github.com/SergeiVKalinin/AutomatedExperiment_Summer2023)**

### 2022

- **[FerroSchool Winter 2022 in Calgary](https://github.com/pycroscopy/ferroschool)**

### 2021

- **[Notebooks for MRS2021 tutorial](https://github.com/pycroscopy/MRS2021)**

- **[SPM_ML_School_2021](https://github.com/pycroscopy/SPM_ML_School_2021)**

### 2020  

- **[AISTEM Workshop 2020](https://github.com/pycroscopy/AISTEM_WORKSHOP_2020)**

### 2019  

- **[CNMS ML in MS Workshop 2019](https://github.com/pycroscopy/CNMS_ML_in_MS_Workshop_2019)** 

### 2018  

- **[CNMS ML in MS Workshop 2018](https://github.com/pycroscopy/CNMS_ML_in_MS_Workshop_2018)** 

- **[MM 2018 Workshop](https://github.com/pycroscopy/MM_2018_Workshop)**