semvec/pypi-packages huggingface dataset:
wam-api 0.0.1
This package allows users to input time (UT) and satellite locations and output the density value based on various WAM outputs.
Requires Python: >=3.8

# Usage
The purpose of this README is to show the user how to install the WAM_Interpolate pip package <br>
and how to get the interpolated density at the given datetime, latitude, longitude, and altitude.

```
#from a high level, we want this all put into a pip-installable package with a call sequence like the following:
from wam_api import WAMInterpolator
foo = WAMInterpolator() # <-- as a class/object
dt = datetime(2024, 5, 11, 18, 12, 22)
lat, lon, alt = -33.4, -153.24, 550.68  # degrees north, degrees east, km
my_density = foo.get_density(dt, lat, lon, alt)
```
bg-refseq-accession-file-utils 0.1.0
Collection of Python modules for reading and writing tab-delimited RefSeq accession files.
Requires Python: >=3.6
Keywords: bg_refseq_accession_file_utils

==============================
BG RefSeq Accession File Utils
==============================

Collection of Python modules for reading and writing the tab-delimited RefSeq accession files.



Features
--------

* RefSeqAccessionFileParser class for reading the RefSeq accession files
* RefSeqAccessionFileWriter class for writing the RefSeq accession files
* RefSeqAccessionRecord class for representing the RefSeq accession records

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.1.0 (2024-10-19)
------------------

* First release on PyPI.
tpall 0.3
Quelques classes pour le TP de l'UE Automates, Langages et Logique
Requires Python: >=3.10

# tpall 


Quelques classes pour le TP de l'UE Automates, Langages et Logique :
 - `tpall.af.AFD` : Automate Fini Déterministe ;
 - `tpall.af.AFN` : Automate Fini Non-déterministe ;
 - `tpall.re.{EnsembleVide, Epsilon, Lettre, Somme, Concat, Etoile}` : Expressions Rationnelles.

Visualisation des automates à l'aide de `graphviz` par la méthode `dessine()`.

Visualisation des expressions rationnelles à l'aide de `svgling.arbre(e)`.

Génération d'expressions rationnelles à partir de chaînes de caractères à l'aide de `tpall.re.analyse`.

Décomposition d'expressions rationnelles par pattern matching.
bg-review-file-utils 0.1.0
Collection of Python modules for reading and writing tab-delimited review files.
Requires Python: >=3.6
Keywords: bg_review_file_utils

====================
BG Review File Utils
====================

Collection of Python modules for reading and writing tab-delimited review files.



Features
--------

* ReviewParser class for reading tab-delimited review files
* ReviewWriter class for writing tab-delimited review files
* ReviewRecord class for representing review records

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.1.0 (2024-10-16)
------------------

* First release on PyPI.
DriniChlor 0.0.3
An engineering tool for measurements and analyzes the necessary chlorine level for disinfecting water, depending on measured values for DO, temperature, and NTU.
Requires Python: >=3.6

# Engineering Tool for Water Quality Monitoring

This project is an engineering tool developed in Python using the Tkinter and Matplotlib libraries to create a graphical interface for monitoring and analyzing chlorine, temperature, dissolved oxygen (DO), and turbidity (NTU) in water. The system simulates measurements and analyzes the necessary chlorine level for disinfecting water, depending on measured values for DO, temperature, and NTU.

## Main Components

### Sensor Class
- Represents a sensor that reads randomly generated values for the main variables (e.g., chlorine, DO, temperature).
- Contains methods to calculate the chlorine level based on:
  - DO level
  - Temperature
  - The difference in NTU between the inlet and outlet.

### EngineeringTool Class
- Contains the graphical interface where the user can manually enter values for NTU and temperature.
- The use of graphs allows for the visualization of the read data, along with predictions and differences between various chlorine levels.

## Graphs and Analysis
- The tool creates graphs that show the relationships between chlorine and DO, temperature, as well as NTU, illustrating the differences and averages of chlorine levels.
- Predictions of future chlorine levels are based on historical data collected by the sensor.

This tool can be used to simulate and analyze the effectiveness of water disinfection with chlorine, based on important parameters such as temperature and dissolved oxygen. Its functionality offers an experimental approach that can be useful for research laboratories or scientific studies related to water quality and disinfection.

## Installation

1. Ensure that Python and the Tkinter and Matplotlib libraries are installed on your system.
2. Download or clone this repository to your computer.
3. Run the file `engineering_tool.py`.

```bash
python engineering_tool.py
modifiedstemmer 0.0.11
A modified Porter stemmer for verbs and other additional rules.
Requires Python: >=3.6

### What is stemming?

Stemming is a technique in Natural Language Processing that reduces various inflected forms of a word to a single invariant root form. This root form, known as the stem, may or may not be identical to the word's morphological root.

### What is it good for?

Stemming is highly useful in various applications, with query expansion in information retrieval being a prime example. For instance, in a search engine, if a user searches for "cat," it would be beneficial for the search to return documents containing the word "cats" as well. This won't happen unless both the query and the document index undergo stemming. Essentially, stemming reduces the specificity of queries, enabling the retrieval of more relevant results, though this involves a trade-off.

### What type of stemmer is this?

modifiedstemmer is a suffix-stripping stemmer, which means it transforms words into stems by applying a predetermined sequence of changes to the word's suffix. Other stemmers may function differently, such as by using a lookup table to map inflected forms to their roots or by employing clustering techniques to group various forms around a central form. Each approach comes with its own set of pros and cons. modifiedstemmer, specifically, is a modified version of the original Porter stemmer and includes more comprehensive rules for handling verbs and suffixes.

### How do I use it?

Using the modifiedstemmer is straightforward. Simply import the stemmer, create an instance, and use it to stem words:

```python

from mod_stemmer import modifiedstemmer
my_stemmer = modifiedstemmer.stemmer()
print(my_stemmer.stem('consistency'))

```

This process will convert the word 'consistent' to its stem form.
filefrag 0.0.2
examine fragments of files in the filesystem
Requires Python: >=3.8

# filefrag

Python library to get FIE and command line tool

## Install

See [the video](https://asciinema.org/a/681791) for a demo including installing
from source, but you can install with pip:

```sh
pip install filefrag
```

## Usage

Run `pyfilefrag` on the command line. See `--help` for details. It has
`--verbose`, and `--json` outputs for your parsing pleasure.

To use the library, just call filefrag.FileMap('/path/whatever') to build a map
of the extents in the file using ioctl’s interface. Then you can poke about in
the guts of a file:

* ⛓️‍💥 inspect fragmentation
* 🔍 find out where data is on your physical drive
* 🟰 compare extents between paths
* 📔 use them as dict keys
* 🕳️ check files for holes, like before and after hole punching
* ✅ verify your deduplication strategy, write your own stats tool
* 💩 dump file layouts to json (`print(f"{filemap:j}"`)
* ⚠️ break your disk because you believed the outputs of this alpha release!

Comes with a Device class to do comparisons, so it ought to work with fragments
in files on different mountpoints, bind mounts and so on (unfortunately not
snap’s FUSE mounts; they’re far too abstract and piped in via a socket)

## Example

```python
from filefrag import FileMap

mapping = FileMap('/usr/bin/bash')

print(mapping)
print(extents)
```
EnviroChlor 0.0.0
An engineering tool for measurements and analyzes the necessary chlorine level for disinfecting water, depending on measured values for DO, temperature, and NTU.
Requires Python: >=3.6

# Engineering Tool for Water Quality Monitoring

This project is an engineering tool developed in Python using the Tkinter and Matplotlib libraries to create a graphical interface for monitoring and analyzing chlorine, temperature, dissolved oxygen (DO), and turbidity (NTU) in water. The system simulates measurements and analyzes the necessary chlorine level for disinfecting water, depending on measured values for DO, temperature, and NTU.

## Main Components

### Sensor Class
- Represents a sensor that reads randomly generated values for the main variables (e.g., chlorine, DO, temperature).
- Contains methods to calculate the chlorine level based on:
  - DO level
  - Temperature
  - The difference in NTU between the inlet and outlet.

### EngineeringTool Class
- Contains the graphical interface where the user can manually enter values for NTU and temperature.
- The use of graphs allows for the visualization of the read data, along with predictions and differences between various chlorine levels.

## Graphs and Analysis
- The tool creates graphs that show the relationships between chlorine and DO, temperature, as well as NTU, illustrating the differences and averages of chlorine levels.
- Predictions of future chlorine levels are based on historical data collected by the sensor.

This tool can be used to simulate and analyze the effectiveness of water disinfection with chlorine, based on important parameters such as temperature and dissolved oxygen. Its functionality offers an experimental approach that can be useful for research laboratories or scientific studies related to water quality and disinfection.

## Installation

1. Ensure that Python and the Tkinter and Matplotlib libraries are installed on your system.
2. Download or clone this repository to your computer.
3. Run the file `engineering_tool.py`.

```bash
python engineering_tool.py
fidA 0.1.1
A Python package for FID-A processing based on the MATLAB code by Jamie Near

# fidA

**fidA** is a Python package for processing Free Induction Decay (FID) data, inspired by the FID-A MATLAB code by Jamie Near.

## Authors

- **Colleen Bailey**, Sunnybrook Research Institute
- **Ira Yao**

## Table of Contents

- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Importable Classes and Functions](#importable-classes-and-functions)
- [Publishing as a Python Package](#publishing-as-a-python-package)
- [Running Tests](#running-tests)
- [License](#license)
- [Acknowledgments](#acknowledgments)

## Features

- **Data Import/Export**:
  - Load FID data from various formats (e.g., Bruker).
  - Read and write LCModel coordinate files.
  - Write data in LCModel `.RAW` format.

- **Processing Functions**:
  - Phase correction (zero and first-order).
  - Frequency alignment and shifting.
  - Averaging and median filtering of scans.
  - Exponential line broadening filter.
  - Zero-padding for spectral resolution enhancement.
  - Automatic referencing of ppm values.

- **Peak Fitting**:
  - Fit single or multiple peaks using Lorentzian or Gaussian models.
  - Estimate peak parameters like amplitude, full width at half maximum (FWHM), and chemical shift.

- **Visualization**:
  - Plot spectra with customizable parameters.
  - Ridge plots for comparing multiple spectra.

## Installation

You can install `fidA` from PyPI (once it's published) or from the source code.

### From PyPI (Not yet available)

```bash
pip install fidA