semvec/pypi-packages huggingface dataset:
pyexops 0.1.39
Um simulador Python de Sistemas Exoplanetários para curvas de luz e velocidades radiais.
Requires Python: >=3.8
Keywords: exoplanets transit simulation light curve radial velocity photometry dask astronomy

# pyExopS (Python Exoplanetary Systems Simulator)

`pyExopS` is a Python-based simulator designed to generate realistic observational data for exoplanetary systems. It aims to provide a flexible and extensible platform for studying phenomena like planetary transits, stellar activity, and various observational systematics.

## Features

-   **Realistic Star Model:** Includes quadratic limb darkening and dynamic stellar spots (umbra and penumbra).
-   **Planet Model:** Customizable orbiting planets with definable physical and orbital parameters.
-   **Advanced PSF Modeling:** Supports Gaussian, Moffat, Airy Disk, Elliptical Gaussian, and Combined Point Spread Functions to simulate realistic instrumental and atmospheric blurring.
-   **Noise Injection:** Injects Poisson (photon) noise and Gaussian (readout) noise for true-to-life data.
-   **Photometry Methods:** Implements various photometric extraction techniques:
    -   Simple Aperture Photometry (SAP)
    -   Optimal Photometry
    -   PSF Fitting Photometry
    -   Simplified Difference Imaging Photometry (DIP)
-   **Data Conditioning:** Includes a PDCSAP-like detrending algorithm to remove instrumental and astrophysical systematics from light curves while preserving transit signals.
-   **Variable Cadence:** Allows simulation of observations with non-uniform time sampling (e.g., high cadence during transit, low cadence out-of-transit).
-   **Parallel Processing:** Leverages Dask for efficient parallel computation across multicore CPUs, NVIDIA GPUs (Dask-CUDA), or distributed clusters.

## Installation

You can install `pyExopS` using pip:

```bash
pip install pyexops
graphex 3.5.10
Python package for creating and manipulating graphs and networks
Requires Python: >=3.11
Keywords: Networks, Graph Theory, Mathematics, network, graph, discrete mathematics, math

Graphex
=======

.. image:: https://img.shields.io/pypi/v/graphex.svg
   :target: https://pypi.org/project/graphex/

.. image:: https://img.shields.io/pypi/l/graphex.svg
   :target: https://github.com/taylortech75/graphex/blob/main/LICENSE.txt

.. image:: https://img.shields.io/pypi/pyversions/graphex.svg
   :target: https://pypi.org/project/graphex/

.. image:: https://img.shields.io/github/labels/taylortech75/graphex/good%20first%20issue?color=green&label=contribute
   :target: https://github.com/taylortech75/graphex/contribute

**Graphex** is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

Resources
---------

- **Website (including documentation):** https://networkx.org
- **Mailing list:** https://groups.google.com/forum/#!forum/networkx-discuss
- **Source:** https://github.com/taylortech75/graphex
- **Bug reports:** https://github.com/taylortech75/graphex/issues
- **Report a security vulnerability:** https://tidelift.com/security
- **Tutorial:** https://networkx.org/documentation/latest/tutorial.html
- **GitHub Discussions:** https://github.com/taylortech75/graphex/discussions
- **Discord (Scientific Python):** https://discord.com/invite/vur45CbwMz

Simple Example
--------------

Find the shortest path between two nodes in an undirected graph:

.. code:: pycon

    >>> import graphex as nx
    >>> G = nx.Graph()
    >>> G.add_edge("A", "B", weight=4)
    >>> G.add_edge("B", "D", weight=2)
    >>> G.add_edge("A", "C", weight=3)
    >>> G.add_edge("C", "D", weight=4)
    >>> nx.shortest_path(G, "A", "D", weight="weight")
    ['A', 'B', 'D']

Install
-------

Install the latest released version of Graphex:

.. code:: shell

    pip install graphex

Install with all optional dependencies:

.. code:: shell

    pip install graphex[default]

For additional details, please see the `installation guide <https://networkx.org/documentation/stable/install.html>`_.

Bugs
----

Please report any bugs `here <https://github.com/taylortech75/graphex/issues>`_.
Even better, fork the repository on `GitHub <https://github.com/taylortech75/graphex>`_ and create a pull request (PR).
We welcome all contributions, big or small, and we will help you make the PR if you're new to `git`.
Just ask on the issue and/or see the `contributor guide <https://networkx.org/documentation/latest/developer/contribute.html>`_.

License
-------

Released under the `3-clause BSD license <https://github.com/taylortech75/graphex/blob/main/LICENSE.txt>`_::

    Copyright (c) 2004–2025, graphex Developers
    Tomas Olson <tomasolson42@gmail.com>
cgen 2025.1
C/C++ source generation from an AST
Requires Python: >=3.10

cgen: An Abstract Syntax Tree for C, in Python
----------------------------------------------

.. image:: https://gitlab.tiker.net/inducer/cgen/badges/main/pipeline.svg
    :alt: Gitlab Build Status
    :target: https://gitlab.tiker.net/inducer/cgen/commits/main
.. image:: https://github.com/inducer/cgen/actions/workflows/ci.yml/badge.svg
    :alt: Github Build Status
    :target: https://github.com/inducer/cgen/actions/workflows/ci.yml
.. image:: https://badge.fury.io/py/cgen.svg
    :alt: Python Package Index Release Page
    :target: https://pypi.org/project/cgen/

cgen offers a simple abstract syntax tree for C and related languages
(C++/CUDA/OpenCL) to allow structured code generation from Python.
To represent mathematical expressions, cgen can be used with `pymbolic
<https://github.com/inducer/pymbolic>`__.

Places on the web related to cgen:

* `Python package index <https://pypi.org/project/cgen>`__ (download releases)
* `Documentation <https://documen.tician.de/cgen>`__ (read how things work)
* `Github <https://github.com/inducer/cgen>`__ (get latest source code, file bugs)

cgen is licensed under the liberal `MIT license
<https://en.wikipedia.org/wiki/MIT_License>`__ and free for commercial, academic,
and private use. All of cgen's dependencies can be automatically installed from
the package index after using::

    pip install cgen