semvec/pypi-packages huggingface dataset:
quake-inverse-squareroot 0.0.4
A Python port from Quake 3's fast inverse square root algorithm

# quake 3's fastest inverse square root

This module is a port from Quake 3's inverse square root algorithm.

## Installation

1. Get yourself a C compiler (like gcc, clang or msvc)
2. Run `python setup.py install`
3. Enjoy!

## Build

1. Get yourself a C compiler (like gcc, clang or msvc)
2. Run `python setup.py build bdist_wheel sdist`
3. Check the `dist` folder for the wheel and source distribution

## Documentation

`quake_inverse_sq.coarse_inv_sqrt(number: float) -> float`  
This is fastest inverse square root algorithm. It is not as accurate as the `quake_inverse_sq.fined_inv_sqrt` function, but it is much faster. It is implemented from this [wikipedia](https://en.wikipedia.org/wiki/Fast_coarse_inv_sqrt)  
  
`quake_inverse_sq.fined_inv_sqrt(number: float) -> float`
This is the original inverse square root algorithm. It is more accurate than the `quake_inverse_sq.coarse_inv_sqrt` function, but it is slower. It is implemented from `math.h`
pyrusgeom 0.1.2
A package for handling geometry and math in SS2D
Requires Python: >=3.7

# PyrusGeom
## Geom2D | Soccer Math

PyrusGeom is a Python library for dealing with math and geometry in SS2D.


# Installation

Use pip or build to install PyrusGeom.  
x.x.x = release version  
*test pypi* release:
```Bash
pip install -i https://test.pypi.org/simple/ pyrusgeom==x.x.x
```
*pypi* release:
```Bash
pip install pyrusgeom==x.x.x
```
download and use the released tar file:
```Bash
python -m pip install pyrusgeom-x.x.x.tar.gz
```
or use the git repository
```sh
git clone https://github.com/Cyrus2D/PyrusGeom.git
python -m build
python -m pip install dist/pyrusgeom-x.x.x.tar.gz
```

# Usage

for importing you can use this options

import the desired class
```python
from pyrusgeom.vector_2d import Vector2D # for Vector2D
from pyrusgeom.polygon_2d import Polygon2D # for Polygon2D
```
Or use a Wildcard import like
```python
from pyrusgeom.soccer_math import *
from pyrusgeom.geom_2d import *
```

Examples

```python
vec_1 = Vector2D() # create Vector with default value.
vec_2 = Vector2D(20,30) # create Vector with 20 , 30 value directly.
line_1 = Line2D(vec1,vec2) # create line from 2 points.
circle_1 = Circle2D(3,3,5) # create circle with center point and radius value.
print(circle_1.intersection(line_1)) #  calculate the intersection with straight line.
```

# Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## TODO
triangulation | 
delaunay_triangulation | 
composite_region_2d | 
voronoi_diagram | 
circluar import | 
remaining eq,hash,reverse |
etc
oceansdb 0.8.15
Subsample ocean climatologies and reference data
Requires Python: >=3.7
Keywords: WOA,World Ocean Atlas,climatology,oceanography,ETOPO,temperature,salinity,bathymetry,CARS

========
OceansDB
========

.. image:: https://zenodo.org/badge/52222122.svg
   :target: https://zenodo.org/badge/latestdoi/52222122

.. image:: https://readthedocs.org/projects/oceansdb/badge/?version=latest
    :target: http://oceansdb.readthedocs.org/en/latest/?badge=latest
         :alt: Documentation Status

.. image:: https://img.shields.io/travis/castelao/oceansdb.svg
        :target: https://travis-ci.org/castelao/oceansdb

.. image:: https://img.shields.io/pypi/v/oceansdb.svg
        :target: https://pypi.python.org/pypi/oceansdb


Package to subsample, or interpolate, climatologies like WOA to any coordinates.

This package started with functions to obtain climatological values to compare with measured data, allowing a quality control check by comparison. It hence needed to work for any coordinates requested. I split these functionalities from `CoTeDe <http://cotede.castelao.net>`_ into this standalone package to allow more people to use it for other purposes.

* Free software: 3-clause BSD style license - see LICENSE.rst  
* Documentation: https://oceansdb.readthedocs.io.

Features
--------

- If the database files are not localy available, automatically download it.

- Extract, or interpolate if necessary, climatologic data on requested coordinates;

  - Can request a single point, a profile or a section;

  - Ready to handle -180 to 180 or 0 to 360 coordinate system;

- Ready to use with:

  - World Ocean Atlas (WOA)

  - CSIRO Atlas Regional Seas (CARS)

  - ETOPO (topography)

Quick howto use
---------------

Inside python:

.. code-block:: python

    >>> import oceansdb
    >>> with oceansdb.WOA() as db:

Find out what is available:

.. code-block:: python

    >>>     db.keys()

Average temperature at one point:

.. code-block:: python

    >>>     t = db['sea_water_temperature'].extract(var='mean', doy=136.875, depth=0, lat=17.5, lon=-37.5)

A profile of salinity:

.. code-block:: python

    >>>     t = db['sea_water_salinity'].extract(var='mean', doy=136.875, depth=[0, 10, 15, 18], lat=17.5, lon=-37.5)

A full depth section of temperature:

.. code-block:: python

    >>>     t = db['sea_water_temperature'].extract(var='mean', doy=136.875, lat=17.48, lon=[-39, -37.5, -35.2])

Using CARS instead of WOA:

.. code-block:: python

    >>> with oceansdb.CARS() as db:
    >>>     t = db['sea_water_temperature'].extract(var='mean', doy=136.875, lat=17.48, lon=[-39, -37.5, -35.2], depth=[0,10,120,280])

Or to get topography for one point from the 1 min arc resolution:

.. code-block:: python

    >>> with oceansdb.ETOPO(resolution='1min') as db:
    >>>     h = db['topography'].extract(lat=17.5, lon=0)
dictmsgr 0.2
Single-thread dict-based messenger inspired by the Robot Operation System.
Requires Python: >=3.7
Keywords: dict,messenger

# dictmsgr

Dict Messenger inspired by Robot Operation System, publish topic by setting item to a dict-like `Context` object. Callback subscription can be registered to be used in a single thread. The callback function should have signature `callback(ctx, msg)` and will be called when `Context.__setitem__()` is fired. This dict is designed to function like a project-wide globals() that you can read&write. '/' is used to specify multi-level nested dict keys.

`pip install dictmsgr`