tem-staining-comparison
A Python package to generate synthetic images of ferritin rings and perform spectral analysis
Science Score: 49.0%
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Repository
A Python package to generate synthetic images of ferritin rings and perform spectral analysis
Basic Info
Statistics
- Stars: 0
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- Open Issues: 1
- Releases: 2
Metadata Files
README.md
TEM staining comparison
This repository contains code used to generate synthetic data and perform spectral analysis for the paper Systematic Comparison of Commercial Uranyl-Alternative Stains for Negative- and Positive-Staining Transmission Electron Microscopy of Organic Specimens by Vera M. Kissling, Stephanie Eitner, Davide Bottone, Gea Cereghetti, and Peter Wick (under review)
Installation
The tem-staining package can be installed directly from this repository. We recommend installing it in a fresh environment.
pip install tem-staining@git+https://github.com/dv-bt/tem-staining-comparison
Usage
The functions in the synthetic_data module can be used to generate synthetic images of ferritin rings. A random state can also be set to obtain reproducible results.
```python
from temstaining.syntheticdata import generateferritinrings
import cv2
image, ringcenters = generateferritinrings( imagewidth=1024, arealfraction=0.3, backgroundvalue=80, randomstate=12743672, pixelsize=0.3e-9, )
cv2.imwrite("example_image.png", image) ```
Notebooks
The repository includes the notebooks used to generate synthetic data and perform spectral analysis, as well as the raw and processed data. To run the notebooks and repoduce the results, navigate to the notebooks directory and install the virtual environment from the environment.yml file:
bash
conda env create -f environment.yml
Acknowledgements
This work was financed by the MetrINo project (23.00360, 22HLT04). The project received funding from the European Partnership on Metrology, co-financed by the European Union's Horizon Europe Research and Innovation Programme and SERI (REF-1131-52104)
Owner
- Login: dv-bt
- Kind: user
- Repositories: 2
- Profile: https://github.com/dv-bt
GitHub Events
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- Release event: 3
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Dependencies
- numpy >=2
- opencv-python >=4.10
- scipy >=1.14