semvec/pypi-packages huggingface dataset:
conn2combat 1.0.0
A package for parsing .mat files from CONN first-level ROI-to-ROI analyses and preparing data for COMBAT.
Requires Python: >=3.6

# conn2combat - Extract First Level Data From CONN For Use With COMBAT.

This script is designed to parse .mat files generated from CONN first-level ROI-to_ROI analyses (https://web.conn-toolbox.org/resources) 
and output them in a format that can be used by COMBAT (https://github.com/Jfortin1/ComBatHarmonization). 

Inputs are the CONN analysis directory, an output directory where the outputs should be stored, (optional) a list of ROIs of interest, and (optional) whether outputs should be limited to ROI-to-ROI. 

Outputs consist of one CSV file per subject containing the correlation data for each ROI, and a combined CSV file containing all subjects' data.

## Options

- `-d`, `--conn_directory`: Path to the CONN analysis directory. Required.
- `-o`, `--output_directory`: Path to the directory where the outputs will be saved. Default is the current directory.
- `-r`, `--rois`: List of regions of interest (ROIs) to export. Default is all ROIs.
- `-l`, `--limit`: Limits output to only ROI-to-ROI data (as opposed to ROIs-to-all including atlas and networks).

## Example

```
combat2conn -d /path/to/conn_directory -o /path/to/output_dir -r ROI1 ROI2 ROI3
```

## Requirements

- Python 3.x (tested with python 3.11.11)

## Install as package

1. Install using pip:
    ```
    pip install conn2combat
    ```
2. Process files:
    ```
    python -m combat2conn -d /path/to/conn_directory -o /path/to/output_dir -r ROI1 ROI2 ROI3
    ```

## Run from source 

1. Clone the repository:
    ```
    git clone https://github.com/trevorbryanjackson/CONN_First_Level_Extraction.git
    ```
2. Navigate to the project directory:
    ```
    cd CONN_First_Level_Extraction
    ```
3. Install the required dependencies:
    ```
    pip install -r requirements.txt
    ```
4. Process CONN directory:
    ```
    python conn2combat.py -d /path/to/conn_directory -o /path/to/output_dir -r ROI1 ROI2 ROI3
    ```
smart-reid 0.1.7
With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference CLI.
Requires Python: <=3.12,>=3.8

!pip install onnxruntime-gpu==1.18.0 --index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/
artix-news 0.3.0
Artix News scraper
Requires Python: <4,>=3.5
Keywords: scraping artix news setuptools development

# artix-news
Artix's news CLI. Give to you a fast summary of the new artix changes

![demo](https://i.imgur.com/HEiOr3n.png)


# Install && Usage

``` bash
pip install --user artix-news
```

If installed with pip just call as `artix-news` from command-line.


# Author
Manoel Vilela
turbohtml 0.0.0
Coming soon
Requires Python: >=3.8

An attempt at writing a html5 parser using AI tools.

Current status on html5 treebuilder tests:

~/Projects/turbohtml$ python validate.py
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Tests passed: 282/1756 (16%)