semvec/pypi-packages huggingface dataset:
brisket 0.1.2
Fast Cython-powered one-hot encoding for DNA sequences
License: MIT
Requires Python: <4.0,>=3.9
Keywords: bioinformatics, dna, one-hot-encoding, cython, genomics

# brisket

Fast cython powered 1 hot encoding for DNA sequences.

## Installation

```bash
$ pip install brisket
```

## Usage

```python
import numpy as np
from brisket import encode_seq

# Encode a DNA sequence to one-hot format
dna_sequence = "ATCG"
encoded = encode_seq(dna_sequence)

print(encoded)
# Output: 2D numpy array with shape (4, seq_length) - PyTorch convention
# [[1 0 0 0]  # A channel: positions 0, 1, 2, 3
#  [0 0 1 0]  # C channel: positions 0, 1, 2, 3
#  [0 0 0 1]  # G channel: positions 0, 1, 2, 3
#  [0 1 0 0]] # T channel: positions 0, 1, 2, 3

# The encoding uses channels-first format:
# - Row 0 = A channel, Row 1 = C channel, Row 2 = G channel, Row 3 = T channel
# - Each row represents one nucleotide type across all positions
# - Each column represents one position in the sequence

# Invalid characters (not A, T, C, G) result in all-zero columns
encoded_with_n = encode_seq("ATCGN")  # Last column will be [0 0 0 0]

```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`brisket` was created by Natalie Gill and Sean Whalen. It is licensed under the terms of the MIT license.

## Credits

`brisket` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
muse2csv 1.0.0
Convert GE MUSE ECG XML exports to CSV format
License: MIT
Requires Python: >=3.8

# muse2csv
### Convert GE MUSE XML ECG exports to CSV format

`muse2csv` is a lightweight Python library that converts ECG data exported from the GE MUSE Resting ECG System (in XML format) into CSV (Comma Separated Values) format, compatible with Excel or similar tools and many programming languages.

## Installation

Install directly from PyPI:

```bash
pip install muse2csv
```

Or install locally from source:

```bash
git clone https://github.com/nagyl1999/muse2csv.git
cd muse2csv
pip install .
```

## Usage

An example is provided in the `examples` folder.

```python
from muse2csv.converter import muse_to_csv
import pandas as pd
import matplotlib.pyplot as plt

muse_export = "examples/anonim_pac_xml_export.txt"
wfdb_filename = "patient001_ecg"

lead_names = ['I', 'II', 'III', 'aVR', 'aVL', 'aVF', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6']

muse_to_csv(muse_export, wfdb_filename)

df = pd.read_csv(f'{wfdb_filename}.csv', sep=';')

df[lead_names].plot(subplots=True, figsize=(12, 8), sharex=True, legend=False)

annotations = df[df['QRS'] != '.']

plt.gcf().axes[0].scatter(
    annotations['Time'].index,
    annotations['I'].values,
    color='red',
    marker='*',
    zorder=5
)

plt.show()
```
muse2wfdb 1.4.0
Convert GE MUSE ECG XML exports to WFDB format
License: MIT
Requires Python: >=3.8

# muse2wfdb
### Convert GE MUSE XML ECG exports to WFDB format

`muse2wfdb` is a lightweight Python library that converts ECG data exported from the GE MUSE Resting ECG System (in XML format) into WFDB (WaveForm DataBase) format, compatible with PhysioNet tools and the wfdb Python package.

## Installation

Install directly from PyPI:

```bash
pip install muse2wfdb
```

Or install locally from source:

```bash
git clone https://github.com/nagyl1999/muse2wfdb.git
cd muse2wfdb
pip install .
```

## Usage

An example is provided in the `examples` folder.

```python
from muse2wfdb.converter import muse_to_wfdb
import wfdb

muse_export = "examples/anonim_pac_xml_export.txt"
wfdb_filename = "patient001_ecg"

annotations = muse_to_wfdb(muse_export, wfdb_filename, ['Age: 75', 'Dx: 316998'])

record = wfdb.rdrecord(wfdb_filename)
annotation = None

if annotations:
    annotation = wfdb.rdann(wfdb_filename, 'atr')

wfdb.plot_wfdb(record=record, annotation=annotation, title="MUSE exported ECG")
```
whatsapp-utils-fapi 0.3.0
whatsapp_utils_fapi
License: MIT
Requires Python: >=3.11

# WhatsApp Utils

A Python package for handling WhatsApp audio messages with Azure AI services integration.

## Features

- Send and receive WhatsApp audio messages
- Speech-to-text conversion using Azure Cognitive Services
- Text-to-speech conversion using Azure Cognitive Services
- AI-powered responses using Azure OpenAI

## Installation

```bash
python -m build
pip install whatsapp_utils_FAPI
whatsapp-utils-FAPI 0.2.0
whatsapp_utils_FAPI
License: MIT
Requires Python: >=3.11

# WhatsApp Utils

A Python package for handling WhatsApp audio messages with Azure AI services integration.

## Features

- Send and receive WhatsApp audio messages
- Speech-to-text conversion using Azure Cognitive Services
- Text-to-speech conversion using Azure Cognitive Services
- AI-powered responses using Azure OpenAI

## Installation

```bash
python -m build
pip install whatsapp_utils_FAPI