semvec/pypi-packages huggingface dataset:
fftl 2025.1.1
Generalised FFTLog for integral transforms
Requires Python: >=3.8
Keywords: FFTLog, Hankel transform, Laplace transform, Stieltjes transform, integral transform

*FFTL* — generalised FFTLog for Python
======================================

The *FFTL* package for Python contains a routine to calculate integral
transforms of the type *ã(k) = ∫ a(r) T(kr) dr* for arbitrary kernels *T*.  It
uses a modified FFTLog [2] method of Hamilton [1] to efficiently compute the
transform on logarithmic input and output grids.

The package supports any array implementation such as Numpy, JAX, Torch, dask,
etc. as long as it provides a reasonable set of standard Array API functions
(e.g. `log()`, `exp()`, `linspace()`, etc.) and Fast Fourier Transforms
(`fft.rfft()` and `fft.irfft()`).

Besides the generalised FFTLog algorithm, the package also provides a number of
standard integral transforms.


Installation
------------

Install with pip:

    pip install fftl

The package only requires `numpy` and `scipy`.

For development, it is recommended to clone the GitHub repository, and perform
an editable pip installation.


Usage
-----

The core functionality of the package is provided by the [`fftl`] module.  The
[`fftl.transform()`] routine computes the generalised FFTLog integral transform
for a given kernel.  For convenience, the module provides a number of
[standard integral transforms].

[`fftl`]: https://fftl.readthedocs.io/latest/fftl.html
[`fftl.transform()`]: https://fftl.readthedocs.io/latest/fftl.html#fftl.transform
[standard integral transforms]: https://fftl.readthedocs.io/latest/transforms.html


User manual
-----------

* [Generalised FFTLog][`fftl`]
* [Standard Integral Transforms][standard integral transforms]


References
----------

1.  Hamilton A. J. S., 2000, MNRAS, 312, 257 (astro-ph/9905191)
2.  Talman J. D., 1978, J. Comp. Phys., 29, 35
pylywsdxx 2.8.3
A Python3 class to interrogate Xiaomi Mijia LYWSD* sensors.
Requires Python: >=3.9


[![License](https://img.shields.io/github/license/mausy5043/pylywsdxx)](LICENSE)
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# pylywsdxx

This is a Python3 library to allow interrogation of Xiaomi Mijia LYWSD* sensors via Bluetooth Low Energy (BLE).

**Note**: This is an unofficial project, and is in no way supported or endorsed by Xiaomi.

## Requirements

This module requires [`bluepy3`](https://pypi.org/project/bluepy3/) which should be installed automagically when using the installation instructions below.

Development of this package is done in Python 3.12. The package is considered forwards compatible at least upto Python 3.12 and probably also beyond. Backwards compatibility is not guaranteed; if it works on Python 3.9 or before consider yourself lucky. [Python versions that are end-of-life](https://devguide.python.org/versions/) are not supported.

The package has been extensively tested on a Raspberry Pi 3 Model B+ (aarch64) with Debian GNU Linux 12 /w Python 3.11.*.


## Installation

```
pip install pylywsdxx
```

## Usage

```
import pylywsdxx as pyly

mac = "A4:C1:38:0D:EA:D0"

device2 = pyly.Lywsd02(mac)
data2 = device2.data
print(f"Temperature: {data2.temperature}˚C")

device3 = pyly.Lywsd03(mac)
data3 = device3.data
print(f"Temperature: {data3.temperature}˚C")
```

Please note that this module has completely and intentionally broken backwards compatibility with previous
and existing versions of `lywsd02` and `lywsd03mmc` and with v1.* versions of itself.

## Acknowledgements

Based on previous work stolen from Mikhail Baranov (`h4`) : [lywsd02](https://github.com/h4/lywsd02)
and Duncan Barclay (`uduncanu`) : [lywsd03mmc](https://github.com/uduncanu/lywsd03mmc)


## Disclaimer & License
As of September 2024 `pylywsdxx` is distributed under [AGPL-3.0-or-later](LICENSE).
logicalpy 1.2.1
A library providing basic functionalities for manipulating propositional logic
Requires Python: >=3.9
Keywords: formal logic, logic, propositional logic

# LogicalPy

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[![License](https://img.shields.io/github/license/Cubix1729/logicalpy)](https://github.com/Cubix1729/logicalpy/blob/master/LICENSE)
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LogicalPy is a Python library providing basic functionalities for manipulating propositional logic.

## Description

The library allows to work with classical propositional logic formulae.
The main features include:

 - The construction of logical formulae either directly or from a string
 - The visualisation of truth tables
 - The implementation of semantic notions: satisfiability, entailment...
 - The conversion to normal forms (NNF, CNF, or DNF)
 - The implementation of a Hilbert-style proof system
 - Automated theorem proving with the resolution procedure

The library also supports LaTeX code generation for most of its functionalities.

For the complete documentation, see [https://cubix1729.github.io/logicalpy/](https://cubix1729.github.io/logicalpy/).

## Installation

With pip:
```
pip install logicalpy
```

Note that the library needs a Python version higher than 3.9.

## Contributing

If you want to contribute to this project, you can open an issue to report a bug or request a feature,
or make a pull request.
See [CONTRIBUTING.md](./CONTRIBUTING.md) for detailed contribution guidelines.

## License

This project is licensed under the MIT license.