semvec/pypi-packages huggingface dataset:
notix 0.0.1
A simple library for showing notifications.
Requires Python: >=3.6

# Notix

Notix is a simple library for showing notifications on Windows using native message boxes. It provides an easy way to display info, warning, and error messages, as well as to ask yes/no questions.

## Features

- Display informational messages
- Display warning messages
- Display error messages
- Ask yes/no questions

## Installation

You can install Notix locally using pip:

pip install -e .

This will install Notix in editable mode, which means that changes made to the source code will be reflected immediately without needing to reinstall the package.

## Usage

Here is an example of how to use Notix:

from notix import mbox

message_box = mbox()

# Show an informational message
message_box.show_info("Hello", "This is an informational message!")

# Show a yes/no question
if message_box.show_question("Confirmation", "Do you want to proceed?"):
    message_box.show_warning("Warning", "You chose to proceed.")
else:
    message_box.show_error("Error", "Operation canceled.")


## User Guide

1. Import the Library: Start by importing the mbox class from the notix module.
2. Create an Instance: Create an instance of the mbox class. This will be used to show messages.
3. Show Messages:
- Use show_info(title, message) to display an informational message.
- Use show_warning(title, message) to show a warning message.
- Use show_error(title, message) to display an error message.
- Use show_question(title, question) to ask a yes/no question. This method returns True for "Yes" and False for "No".

## Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue if you find any bugs or have suggestions for improvements.

## License

This project is licensed under the MIT License. See the LICENSE file for details.

## Author

Sergey Uvarov
Your Email: pop1avplov@example.com
GitHub: [Pop1avok](https://github.com/Pop1avok)
mvtcr 0.2.1.2
mvTCR: A multimodal generative model to learn a unified representation across TCR sequences and scRNAseq data for joint analysis of single-cell immune profiling data

# mvTCR

mvTCR is a multimodal generative model to learn a unified representation across across TCR sequences and scRNAseq data and datasets for joint analysis of single-cell immune profiling data.

- The publication can be found [here](https://www.nature.com/articles/s41467-024-49806-9) 
- GitHub can be found [here](https://github.com/SchubertLab/mvTCR)

### Installation

To install mvTCR follow these steps:
1. Create a [conda](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment) environment: <code>conda create -n mvTCR python=3.10</code>
2. Install mvTCR <code>pip install mvTCR</code>
3. Install [PyTorch](https://pytorch.org/get-started/locally/) e.g. v2.1.2 with the appropriate CUDA version

### Tutorial

Please have a look at our tutorial notebooks found [here](https://github.com/SchubertLab/mvTCR/tree/master/tutorials).

### Bugs and Errors

If you find any bugs or run into errors please report them to our [GitHub](https://github.com/SchubertLab/mvTCR/issues).


#### Reproducibility 

The [reproducibility GitHub](https://github.com/SchubertLab/mvTCR_reproducibility) features experiments and code used in the publication. If you want to reproduce them, please use mvTCR v0.1.3 together with PyTorch v1.8.0 .