semvec/pypi-packages huggingface dataset:
reticle-analysis 0.1.0
Reticle pipeline
License: MIT
Requires Python: >=3.8

# Python-Fiji-Pipeline
This Library includes code related Reticle pipeline workflow.


----- Reticle Pipeline -----

This pipeline includes the following steps:

1. Difference of Gauss. [32 bits] 
-> process_stack(file_path,sigma1,sigma2)  

2. Calculate Binary mask of the step 1 (DoG). [16 bits]
-> process_dog_stack(file_path) 

3. Remove Outliers.  [16 bits]
-> apply_median_filter(file_path, size) 

4. Normalize result of Binary Mask. [32 bits]
-> normalizar_stack(Binarymask_file_path,original_file_path)  

5. Calculate Regions of interest (ROIS), F0, log2(pixel/F0). 
In this step paralellism cpu code is added. [32 bits]
-> process_stack_rois(file_path,roi_size,frame_range)
microSWIFTtelemetry 0.3.7
microSWIFTtelemetry: Python-based functionality for pulling telemetry from the microSWIFT wave buoy.
License: MIT
Requires Python: >=3.7



microSWIFTtelemetry
===================
Python-based functionality for pulling telemetry from the microSWIFT wave buoy.

.. _README: https://github.com/SASlabgroup/microSWIFTtelemetry/blob/main/README.md

License
=======
``microSWIFTtelemetry`` is licensed under the terms of the MIT license. See the file
"LICENSE" for information on the history of this software, terms & conditions
for usage, and a DISCLAIMER OF ALL WARRANTIES.

All trademarks referenced herein are property of their respective holders.

Copyright (c) 2022--, Jacob Davis, University of Washington
ai-yardstick 0.0.1
A CLI tool for running and managing LLM evaluations
License: MIT
Requires Python: >=3.9

# ai-yardstick

[![PyPI](https://img.shields.io/pypi/v/ai-yardstick.svg)](https://pypi.org/project/ai-yardstick/)
[![Changelog](https://img.shields.io/github/v/release/kevinschaul/ai-yardstick?include_prereleases&label=changelog)](https://github.com/kevinschaul/ai-yardstick/releases)
[![Tests](https://github.com/kevinschaul/ai-yardstick/actions/workflows/test.yml/badge.svg)](https://github.com/kevinschaul/ai-yardstick/actions/workflows/test.yml)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/kevinschaul/ai-yardstick/blob/master/LICENSE)

A CLI tool for running and managing LLM evaluations

See [my own evals](https://github.com/kevinschaul/llm-evals/)

## Installation

Install this tool using `pip`:
```bash
pip install ai-yardstick
```
## Usage

Create a new eval with:
```bash
ai-yardstick create EVAL_NAME
```

Then edit prompts.csv, models.csv and tests.csv with your test cases.

Run an eval with:
```bash
ai-yardstick run path/to/config.yaml
```

For help, run:
```bash
ai-yardstick --help
```
You can also use:
```bash
python -m llm_evals_cli --help
```
## Development

To contribute to this tool, first checkout the code. Then create a new virtual environment:
```bash
cd ai-yardstick
python -m venv venv
source venv/bin/activate
```
Now install the dependencies and test dependencies:
```bash
pip install -e '.[test]'
```
To run the tests:
```bash
python -m pytest
```