A Python package for EM data analysis
Project description
Description
This project provides a useful tool for analyzing electron microscopy data.
More specifically, the morph_analysis.py module offers various functions that iteratively analyze several morphological properties of networks (such as porosity, tortuosity, fractal dimension, etc.) obtained from in-situ measurement movies. This module is highly valuable as it facilitates the investigation of how specific properties evolve over time, thereby reducing the time required for data analysis.
Features
- Normalization for a better image contrast (optional)
- Scalebar calibration
- ROI selection
- Plotting a specific property value as a function of time
- Generating a .csv file for a subsequent analysis with other programs (such as curve fitting)
- Provides images and corresponding tables for the segmentation measurements
Installation
EM_data_analysis requires Python 3.6 or above.
Installation using pip (recommended):
pip install EM_data_analysis
Usage
Create an empty directory (will be used to store all the frames created from the movie). Then, simply input the path of the movie, the directory created to store the frames, frame rate and the time length.
from EM_data_analysis import morph_analysis as ma
ma.Network_analysis("path-of-the-movie", "path-of-the-directory", frame-rate, time-length)
The movie format must be explicit and could be in AVI or MP4 format.
Contributions
EM_data_analysis is created by Mattia Lizzano
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file EM_data_analysis-1.0.3.tar.gz.
File metadata
- Download URL: EM_data_analysis-1.0.3.tar.gz
- Upload date:
- Size: 2.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
aa64b9176c0f2b1e14807c227516e31ebfef0145546e93d16d0b108d4618f0c1
|
|
| MD5 |
003a9e63ec84bd292f249f69dbe7d1f5
|
|
| BLAKE2b-256 |
169cae5c031a593dfc6608acdbc8deb4262c3bf22550d561405f83b66b195547
|
File details
Details for the file EM_data_analysis-1.0.3-py3-none-any.whl.
File metadata
- Download URL: EM_data_analysis-1.0.3-py3-none-any.whl
- Upload date:
- Size: 2.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
51e8651e63c2083ef7cb6307760c1d08750f75e8d6a7ff3e6cd290aa41e4c538
|
|
| MD5 |
1202f054df4d77106b4a17d4279b91d0
|
|
| BLAKE2b-256 |
e1d8581a2398835619b61fe266d6df63d044bd5fcedd2b986b61fd568fc58dc1
|