semvec/pypi-packages huggingface dataset:
sar-apps 0.0.1
Basic Synthetic Aperature Radar Applications
Requires Python: >=3.8

# SAR Apps
A small module for a few basic Synthetic Aperature Radar Applications for dual channel (Sentinel-1) images using numpy and scipy.

## Overview
A few filters and Detectors are implemented.
### Filters 
- guard window filter
- Polarimteric Whitening
- Mean Square Error Polarimteric Whitening
- Polarimetric Notch Filter
- Polarimetric Match Filter
- Depolarization Ratio Anomaly Detector 
- Normalised Intensity Sum

### Detector
- Sell Averaging Constant False Alarm Rate
- Combined Depolarization Ratio Anomaly Detector

## Installation
To install the library, use pip:

```bash
pip install sar_apps
```
## Contributing
Contributions are welcome! Please submit a pull request with your changes.

## License
This library is licensed under the MIT License. See LICENSE for details.
json-type-hints 1.3
An extension of the standard json library
Requires Python: >=3.10

# json-type-hints
**json-type-hints** is a simple extension of the standard json library intended to help facilitate transferring python objects as json encoded strings. Data types that don't have corresponding json types are preserved by encoding them as dictionaries with `__type__` and `__data__` fields. It encodes and decodes `bytes` and `tuple` by default (replacing the default json library encoding of `tuple` as `list`) and allows adding additional types.

provides `dumps` and `loads` methods
snappy-gpt 0.0.1
Another Wrapper for ESA Snap Graph Processing Tool
Requires Python: >=3.8

# SnappyGPT

Python Module that creates and applies graph processing functions for ESAs SNAP graph processing tool (GPT)

## Requirements

* SNAP must be installed and snappy configured for your python enviroment
* numpy is requiered for utils.py

## Example

```python
from SnappyGPT import utils, GPT

product=utils.read('filename.zip')

preProcessGraph = GPT.Graph()
preProcessGraph.add_calibration(outputImageScaleInDb=True, outputSigmaBand=True)
preProcessGraph.add_thermal_noise_removal()
preProcessGraph.add_topsar_deburst()

processedProduct=preProcessGraph.create_product(product)
```
attribution-analysis 0.1.0
A package for portfolio attribution analysis
Requires Python: >=3.7

# Attribution Analysis

This package provides tools for portfolio attribution analysis, including the Brinson-Fachler (BF) and Brinson-Hood-Beebower (BHB) models.

## Installation

You can install the package using pip:

```
pip install attribution_analysis
```

## Usage

Here's a quick example of how to use the package:

```python
import pandas as pd
from attribution_analysis import attributions

# Your data preparation here...

result = attributions(data, model="BHB", interaction=True)
print(result)
```

For more detailed usage instructions and API documentation, please refer to our documentation.

## License

This project is licensed under the MIT License - see the LICENSE file for details.
siglyser 0.23
Signal processing library

# SigLyser
The signal processing application. \
Provides the following functionality:
1. FFT (fast fourier transform) for time domain data.
2. 3D FFT for time domain data where speed (of engine or any component) is also present.
![3D FFT](images/example.png)

4. Amplitude and RMS (root mean square) of time domain data.



## Project Log
May 2024:\
Included RMS and Amplitude Functionality

April 2024:\
Create the siglyser library after creating the base code in 2018.

## Project Road Map:

1. Documentation for existing functionality
2. Include example data within library
3. develop more examples
4. Time domain signal parsing, analyses, smoothening and standardising.
5. CSV and Excel parsing functionality without using Pandas library
6. App for siglyser (may be a separate python package)
pyui-design 0.0.3
A Python User Interface package
Requires Python: >=3.4

# pyui-design - Python User Interface Design Solution

This is pyui-design package.

This is not UI framework.

This is UI solution for python application.

- CLI
- WEB
- DESKTOP
- MOBILE
- AI
- 

#### 0.0.2 2024/10/17
* Add some defination from other project.

#### 0.0.1 2024/10/17
* Init project.
* Create __pyui-design__ PyPI package name and domain __pyui.design__ .
extractimail 1.1.0
A tool to automatically recollect emails and save attachments.
Requires Python: >=3.6

# Extractimail

## Description

Extractimail is a Python-based utility designed to automatically collect emails from a specified Outlook folder, save attachments with supported extensions, and process them accordingly. It offers an easy installation method and a simple configuration interface for users to set their parameters.

## Features

- **Outlook Integration**: Connects to Outlook and accesses a specified folder.
- **Automatic Setup**: Runs configuration setup automatically upon first use.
- **Email Filtering**: Retrieves emails based on a user-defined date range.
- **Attachment Management**: Saves attachments with supported file extensions (.pdf, .xlsx, .csv).
- **File Processing**: Processes PDF, Excel, and CSV files.
- **User-Friendly Configuration**: Simple graphical interface to set and update configurations.
- **Scheduling**: Allows users to schedule the tool to run automatically at a specified day and time.
- **Easy Installation**: Installable via a single command using `pip`.

## Installation

**Important:** To ensure proper installation and functionality, please install the tool using **Command Prompt** or **PowerShell**. Installing via the terminal in Visual Studio Code (VSCode) may not correctly register the command-line scripts.

Ensure you have **Python 3.6** or higher installed on your machine.

1. **Open Command Prompt or PowerShell:**

   - **Command Prompt:**
     - Press `Win + R`, type `cmd`, and press **Enter**.
     - Alternatively, search for **Command Prompt** in the Start menu.
   - **PowerShell:**
     - Press `Win + R`, type `powershell`, and press **Enter**.
     - Alternatively, search for **PowerShell** in the Start menu.

2. **Install the Tool:**

   ```cmd
   pip install extractimail

After installation, run the command `extractimail --setup` to launch the configuration panel.