semvec/pypi-packages huggingface dataset:
drt-sdk-core 0.0.3
Core components of the Dharitri Python SDK.
Requires Python: >=3.8

# drt-sdk-py-core

Core components of the Dharitri Python SDK.

## Distribution
 
 - GitHub: `git+https://git@github.com/DharitriOne/drt-sdk-py-core.git@v{Version}#egg=drt_sdk_core`
 - [PyPi](https://pypi.org/user/xfactor.toml/)

## Documentation

[docs.dharitri.com](https://docs.dharitri.com/sdk-and-tools/moapy/moapy/)

## Development setup

### Virtual environment

Create a virtual environment and install the dependencies:

```
python3 -m venv ./venv
source ./venv/bin/activate
pip install -r ./requirements.txt --upgrade
```

Install development dependencies, as well:

```
pip install -r ./requirements-dev.txt --upgrade
```

Above, `requirements.txt` should mirror the **dependencies** section of `pyproject.toml`.

If using VSCode, restart it or follow these steps:
 - `Ctrl + Shift + P`
 - _Select Interpreter_
 - Choose `./venv/bin/python`.

### Tests

Run the tests as follows:

```
pytest .
```

### Linting

First, install [`pyright`](https://github.com/microsoft/pyright) as follows:

```
npm install --global pyright
```

Run `pyright`:

```
pyright
```

Run `flake8`:

```
flake8 drt_sdk_core
```
EM-data-analysis 1.1.1
A Python package for EM data analysis
Requires Python: >=3.6

# 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):
```bash
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 and the directory created to store the frames.

```python
from EM_data_analysis import morph_analysis as ma

ma.Network_analysis("path-of-the-movie", "path-of-the-directory") 
```


The movie format must be explicit and could be in AVI or MP4 format.

# Contributions
`EM_data_analysis` is created by Mattia Lizzano, Giorgio Divitini and the Electron Microscopy and Nanoscopy group of Italian Institute of Technology (IIT)