semvec/pypi-packages huggingface dataset:
swotted 1.0.2a2
A tensor decomposition model extracting temporal phenotypes
Requires Python: <4.0,>=3.8

# SWoTTeD : An Extension of Tensor Decomposition to Temporal Phenotyping

This repository contains the implementation of **SWoTTeD** (**S**liding **W**ind**o**w for **T**emporal **Te**nsor **D**ecomposition)
  
![Illustration of SwoTTeD Decomposition](./sliding_window_temporal_phenotyping.png)


### Authors

* Hana Sebia, Inria, [AIstroSight](https://team.inria.fr/aistrosight/)
* Thomas Guyet, Inria, [AIstroSight](https://team.inria.fr/aistrosight/)
* Mike Rye, Inria, [AIstroSight](https://team.inria.fr/aistrosight/)

### Overview

***SWoTTeD*** is a tensor decomposition framework to extract temporal phenotypes from structured data. Most recent decomposition models allow extracting phenotypes that only describe snapshots of typical profiles, also called daily phenotypes. However, ***SWoTTeD*** extends the notion of daily phenotype into temporal phenotype describing an arrangement of features over a time window.

The capabilities of the SWoTTeD model are illustrated in the [example notebook](./notebooks/SWoTTeD_module_example.ipynb).


This code implements the SWoTTeD as a [PyTorch Lightning](http://lightning.ai) module that you can embed in you own architecture. The `SWoTTeD` module enables:
* to discover phenotypes through the decomposition of a *3D tensor* (with dimensions: patients, features and time). To deal with patient' data having different duration, the dataset is a collection of pathways (2D matrices);
* to project new patient pathways on discovered phenotypes;
* to predict next events in a pathways.

More documentation about this project and how to use the model is available here: [https://hsebia.gitlabpages.inria.fr/swotted/](https://hsebia.gitlabpages.inria.fr/swotted/).

### How to install

The `pyproject.toml` is the project configuration file for [poetry](https://python-poetry.org/) which enables to create and set up a virtual environment suitable to run ***SWoTTeD***.

```bash
git clone https://gitlab.inria.fr/hsebia/swotted

## In case of the use of poetry
poetry install
poetry shell
```
dstructlib 1.0.0
Data Structures Collections: BST and Linked Lists.
Requires Python: >=3.6

# DS Collections

## Overview

**DS Collections** is a Python package that provides efficient and easy-to-use implementations of fundamental data structures. It currently includes:

- **Singly Linked List**: A simple linked list where each node points to the next.
- **Doubly Linked List**: A more advanced linked list with both forward and backward traversal.
- **Binary Search Tree (BST)**: A binary tree for efficient searching, insertion, and deletion operations.

This package is designed for developers, students, and anyone learning about data structures or needing these implementations in their projects.

---

## Features

- **Singly Linked List**
  - Add, delete, and traverse nodes.
  - Efficient memory usage for linear data.

- **Doubly Linked List**
  - Supports bidirectional traversal.
  - Add or delete nodes at any position.

- **Binary Search Tree**
  - Allows duplicate or unique keys.
  - Includes functions for insertion, deletion, and traversal.

---

## Installation

You can install the package locally or through PyPI (if uploaded):

```bash
pip install ds_collections
ocxtools 1.5.3
Python utility CLI for working with 3Docx models.
Requires Python: <4.0,>=3.10

# ocxtools
> ### A python CLI to work with 3Docx models.

``ocxtools`` is a configurable Python CLI shell with pluggable subcommands. The CLI combines features from [``click``](https://click.palletsprojects.com/en/8.1.x/),
[``click-shell``](https://click-shell.readthedocs.io/en/latest/), [``typer``](https://typer.tiangolo.com/) and [``Rich``](https://rich.readthedocs.io/en/stable/introduction.html)
with emphasis on **Typer** and **Rich** to make a good-looking CLI.

## Installation

install from pypi:
````commandline
pip install ocxtools
````

# Usage
## The main CLI

````commandline

             ,----..
            /   /   \    ,----..   ,--,     ,--,
           /   .     :  /   /   \  |'. \   / .`|
          .   /   ;.  \|   :     : ; \ `\ /' / ;
         .   ;   /  ` ;.   |  ;. / `. \  /  / .'          ______   ___    ___   _     _____
         ;   |  ; \ ; |.   ; /--`   \  \/  / ./          |      | /   \  /   \ | |   / ___/
         |   :  | ; | ';   | ;       \  \.'  /     _____ |      ||     ||     || |  (   \_
         .   |  ' ' ' :|   : |        \  ;  ;     |     ||_|  |_||  O  ||  O  || |___\__  |
         '   ;  \; /  |.   | '___    / \  \  \    |_____|  |  |  |     ||     ||     /  \ |
          \   \  ',  / '   ; : .'|  ;  /\  \  \            |  |  |     ||     ||     \    |
           ;   :    /  '   | '/  :./__;  \  ;  \           |__|   \___/  \___/ |_____|\___|
            \   \ .'   |   :    / |   : / \  \  ;
             `---`      \   \ .'  ;   |/   \  ' |
                         `---`    `---'     `--`

Version: 1.1.0
Copyright (c) 2024. OCX Consortium (https://3docx.org)

Starting ocxtools...
ocxtools >: help

Documented commands (type help <topic>):
========================================
clear  docker  validate  version

Undocumented commands:
======================
exit  help  quit


ocxtools >:

````
## Shell Completion
Command completion is not supported on Windows installations.

## Sub-commands
### [docker](readme/docker.md)

### [validate](readme/validate.md)

# Changelog
[Changelog](CHANGELOG.md)

## API

The API documentation is autogenerated using ``sphinx`` and the Read The Docs theme:

https://ocxstandard.github.io/ocxtools/
Twilly 0.0.3
A library to calculate real estate returns, taxes, stamp duty, and admin fees
Requires Python: >=3.6

# Twilly

`twilly` is a Python library designed to streamline real estate operations, including sending notifications and calculating earnings for administrators when a property is sold. The library integrates with Twilio's messaging API to send WhatsApp notifications.

## Features

- Automated Notifications: Notify administrators via WhatsApp whenever a property is sold.
- Earnings Calculation: Automatically calculate administrative earnings based on the property price.
- Twilio Integration: Seamless integration with Twilio's API for secure and reliable messaging.

## Installation

You can install `twilly` using `pip`:

```bash
pip install twilly