semvec/pypi-packages huggingface dataset:
mpiFFT4py 1.1.2
mpiFFT4py -- Parallel 3D FFT in Python using MPI for Python

mpiFFT4py
---------

.. image:: https://travis-ci.org/spectralDNS/mpiFFT4py.svg?branch=master
    :target: https://travis-ci.org/spectralDNS/mpiFFT4py
.. image:: https://circleci.com/gh/spectralDNS/mpiFFT4py/tree/master.svg?style=svg
    :target: https://circleci.com/gh/spectralDNS/mpiFFT4py/tree/master
.. image:: https://zenodo.org/badge/51817237.svg
    :target: https://zenodo.org/badge/latestdoi/51817237

Description
-----------
mpiFFT4py performs FFTs in parallel in Python. It is developed to be able to do FFTs in parallel on a three-dimensional computational box (a structured grid), but there are also routines for doing the FFTs on a 2D mesh. It implements both the *slab* and the *pencil* decompositions.

Installation
------------
mpiFFT4py requires *numpy* for basic array oparations, [*pyfftw*](https://github.com/pyfftw/pyFFTW) for efficient FFTs and [*mpi4py*](https://bitbucket.org/mpi4py/mpi4py) for MPI communications. However, if *pyfftw* is not found, then the slower *numpy.fft* is used instead. [*cython*](http://cython.org) is used to optimize a few routines. Install using regular python distutils::

    python setup.py install --prefix="Path on the PYTHONPATH"
  
To install in place do::

    python setup.py build_ext --inplace
    
To install using Anaconda, you may either compile it yourselves using (from the main directory)::

    conda config --add channels conda-forge
    conda build conf/conda
    conda install mpiFFT4py --use-local
    
or use precompiled binaries in the[*conda-forge*](https://anaconda.org/conda-forge/mpifft4py) or the [*spectralDNS*](https://anaconda.org/spectralDNS/mpifft4py) channel on Anaconda cloud::

    conda install -c conda-forge mpifft4py

or::

    conda config --add channels conda-forge
    conda install -c spectralDNS mpifft4py

There are binaries compiled for both OSX and linux, and several versions of Python. Note that the spectralDNS channel contains bleeding-edge versions of the Software, whereas conda-forge is more stable.

Authors
-------
mpiFFT4py is developed by

  * Mikael Mortensen

Licence
-------
mpiFFT4py is licensed under the GNU GPL, version 3 or (at your option) any later version. mpiFFT4py is Copyright (2014-2016) by the authors.

Contact
-------
The latest version of this software can be obtained from

  https://github.com/spectralDNS/mpiFFT4py

Please report bugs and other issues through the issue tracker at:

  https://github.com/spectralDNS/mpiFFT4py/issues
prosody 0.0.5
Python Prosody API: Emotion & Prosody sensitive TTS

#  prosody

Python Prosody API: Emotion & Prosody sensitive TTS

## How To Use
### Installing

Install prosody using pip
```
python -m pip install prosody
```

### Creating a Client

From `prosody_api` package import `Client` class, then create a Client object with your valid username and password.
```python
from prosody.prosody_api import Client

cli = Client('your_id', 'your_password')
```

### Creating a Voice Item

In order to create a Voice item, which is needed for API server to generate actual WAV file, import `Voice` class from `voice_item` package and create an instance of `Voice` class.
There are five public attributes in `Voice` class, two of them are necessary, and the rest is optional.

#### Required Attributes
1. `text`: The text user wants to convert to a WAV file.
2. `actor`: User can choose the actor of generated voice.

#### Optional Attributes
1. `emotion`
2. `prosody`
3. `signature`: Users cannot set an arbitrary signature on their own. After registering the Voice, the server will automatically give a signature.

```python
from prosody.prosody_api import Client
from prosody.voice_item import Voice

# Creating a new client and a new Voice object.
cli = Client('your_id', 'your_password')
new_voice = Voice('안녕하세요', 'lady1')
registered_voice = cli.register_voice(new_voice)

# Updating the Voice object.
registered_voice.text = '반갑습니다'
cli.update_voice(registered_voice)

# Removing the Voice object.
cli.remove_voice(registered_voice)
```

### Generating WAV File
Then, you can call `generate_voice` to create actual WAV file.

```python
cli.generate_voice(registered_voice)
```

## Authors

* **Yuneui Jeong** - *Main contributor* - [laviande22](https://github.com/laviande22)
* **Suwon Shin** - *Boilerplates* - [shh1574](https://github.com/shh1574)