semvec/pypi-packages huggingface dataset:
ConCat-LS 1.0.0
Repository for ConCat: a simple and intuitive method for English lexical substitution.
Requires Python: >=3.6
Keywords: lexical substitution, lexical semantics, word representation, natural language processing

# *Lexical Substitution is not Synonym Substitution: On the Importance of Producing Contextually Relevant Word Substitutes*

![ConCat](concat.png "ConCat")

## Software
In this repository, you will find the following files:

- `lex_sub.py`: class code for our ConCat method
- `data`: all data for reproducing our results, including the benchmark datasets
fastdataing 1.0.6
Read themo info from lammps output file or log file

### Common fast data processing methods

> A collection of frequently employed functions!

#### Smooth

```
import fastdataing.fastdataing as fd
```

- fd.smooth_MIS(x,y,factor=300): 
  - smooth data
- fd.smooth_SF(x,y,factors=[5,3]): 
  - smooth data

### files processing

```
import fastdataing.files as ff

files = ff.get_files(directory="./",suffix="py")
print(files)
```

- get_files(directory, suffix): 
  - Read files with the same suffix in the folder and save them as a list

### plot figs

```
import fastdataing.fastdataing as fd
import matplotlib.pyplot as plt
fig = fd.add_fig()
ax = fd.add_ax(fig)
plt.show()
```

- add_fig(figsize=(10,8)): 
  - add a canvas, return ax

### Figure Processing

```
import fastdataing.figure as ff
```



- fig2ico(png_file,ico_file=False):
  - convert png to ico file
- fig2binary(fig_file, binary_file=False, threshold=128):
  - convert fig to binary image
- binary2dxf(binary_image_file,dxf_file=False):
  - convert binary to dxf format

### ...
glimix-core 3.1.14
Fast inference over mean and covariance parameters for Generalised Linear Mixed Models
Requires Python: ~=3.10
Keywords: glmm, lmm

# glimix-core

[![Documentation](https://readthedocs.org/projects/glimix-core/badge/?version=latest)](https://glimix-core.readthedocs.io/en/latest/?badge=latest)

Fast inference over mean and covariance parameters for Generalised Linear Mixed
Models.

It implements the mathematical tricks of
[FaST-LMM](https://github.com/MicrosoftGenomics/FaST-LMM) for the special case
of Linear Mixed Models with a linear covariance matrix and provides an
interface to perform inference over millions of covariates in seconds.
The Generalised Linear Mixed Model inference is implemented via Expectation
Propagation and also makes use of several mathematical tricks to handle large
data sets with thousands of samples and millions of covariates.

## Install

Via [pip](https://pypi.python.org/pypi/pip):

```bash
pip install glimix-core
```

## Usage

Here it is a very simple example to get you started:

```python
>>> from numpy import array, ones
>>> from numpy_sugar.linalg import economic_qs_linear
>>> from glimix_core.lmm import LMM
>>>
>>> X = array([[1, 2], [3, -1], [1.1, 0.5], [0.5, -0.4]], float)
>>> QS = economic_qs_linear(X, False)
>>> X = ones((4, 1))
>>> y = array([-1, 2, 0.3, 0.5])
>>> lmm = LMM(y, X, QS)
>>> lmm.fit(verbose=False)
>>> lmm.lml()
-2.2726234086180557
```

We  also provide an extensive [documentation](http://glimix-core.readthedocs.org/) about the library.

## Authors

* [Danilo Horta](https://github.com/horta)

## License

This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/glimix-core/master/LICENSE.md).
kivymd-admin 0.0.1
A command-line tool for managing KivyMD projects.
Requires Python: >=3.7

# KivyMD Helper Scripts 🛠️

This repository contains a set of helper scripts designed to streamline the development of KivyMD applications. These scripts assist in creating template applications, structuring files, and setting up a development environment conducive for KivyMD.

## Table of Contents 📑

- [Features](#features) 🌟
- [Prerequisites](#prerequisites) 🔍
- [Installation](#installation) ⚙️
- [Usage](#usage) 🚀
- [Script Descriptions](#script-descriptions) 📝
- [Contributing](#contributing) 👥
- [License](#license) 📜

## Features 🌟

1. **Template Creation**: Generate basic templates for KivyMD applications, allowing you to kickstart your project.
2. **File Structuring**: Organize your files in a recommended structure, ensuring maintainability and clarity.
3. **KivyMD Setup**: Quick setup scripts for KivyMD dependencies and configurations.

## Prerequisites 🔍

Before using these scripts, ensure you have the following installed:

- Python (>= 3.7) 🐍
- pip 📦
- Kivy 🎨
- KivyMD 📱

## Installation ⚙️

1. Clone this repository:
   ```bash
   git clone https://github.com/yourusername/kivymd-helper-scripts.git
   ```
2. Navigate to the repository directory:
    ```bash
    cd kivymd-helper-scripts
    ```
3. (Optional) Create a virtual environment to keep dependencies managed:
    ```bash
    python -m venv venv
    source venv/bin/activate
    ```
    On Windows, use `venv\Scripts\activate`
4. Install the required dependencies:

    ```bash
    pip install -r requirements.txt
    ```

## Usage 🚀
To use a script, run it with Python:

## Script Descriptions 📝

1. **create_template.py**: Generates a basic KivyMD application template. Use the `--name` option to specify the app's name.
2. **structure_files.py**: Organizes your project files. Ensure you're in the project's root directory before executing.
3. **setup_kivymd.py**: Sets up necessary dependencies and configurations for KivyMD. 

## Contributing 👥

If you find any bugs, have suggestions or want to improve these scripts, feel free to create an issue or pull request.

## License 📜

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
exordiumx 0.2.0
A custom VSCode-style logger for Python
Requires Python: >=3.6

# Exordium

Exordium is a custom VSCode-style logger for Python, providing colorful and informative log messages.

## Installation

You can install Exordium using pip:

```
pip install exordium
```

Or directly from the GitHub repository:

```
pip install git+https://github.com/ExoticCitron/exordium.git
```

## Usage

Here's a simple example of how to use Exordium:

```python
from exordium import get_logger

logger = get_logger(__name__)

logger.info("This is an info message")
logger.debug("This is a debug message")
logger.warning("This is a warning message")
logger.success("This is a success message")
logger.error("This is an error message")
logger.critical("This is a critical message")
```

## License

This project is licensed under the MIT License - see the LICENSE file for details.
demonstrable-whisperx-service 3.0.0
A standalone service for transcribing audio files using WhisperX
Requires Python: <3.11,>=3.10.15

===========================================
Demonstrable Transcription WhisperX Service
===========================================

WhisperX has onerous dependency requirements, and is trick to correctly install. This service
provides a simple API for transcribing audio files using WhisperX, and is intended to be installed
in an isolated environment with a specific Python interpreter.

The package is intended to be used and invoked through demonstrable-transcription, which provides a
command-line interface for interacting with the service.