semvec/pypi-packages huggingface dataset:
qdr 1.0.1
Manage your tasks directly from the terminal using markdown
License: MIT
Requires Python: >=3.12
Keywords: cli, markdown, task-manager, terminal

<div align="center">

<img src="https://raw.githubusercontent.com/spec-driven/quadro/main/docs/assets/logo_light_transparent.svg" alt="Quadro Logo" width="120">

# Quadro

Terminal-native • Markdown-powered • AI-ready

**Task management for the AI generation**

[![PyPI](https://img.shields.io/pypi/v/qdr?style=flat-square&color=green)](https://pypi.org/project/qdr/)
[![Python](https://img.shields.io/badge/python-3.12+-green?style=flat-square)](https://www.python.org)
[![Documentation](https://img.shields.io/badge/docs-quadro-green?style=flat-square)](https://spec-driven.github.io/quadro/)

</div>

---

**The problem:**

You're building with an AI assistant. You explain what you want in chat. Next session,
your AI forgot. You explain again. Or you just start coding without planning and fix
issues as they come up.

<br>

**What Quadro is:**

A task manager that stores tasks as markdown files in your repo. Your AI can read them
through MCP.

You write down what you want to build. Your AI sees it. No copy-paste between sessions.
When you plan first, you catch problems early. Your AI makes better suggestions because
it knows what you're trying to do.

<br>

**This might work for you if:**

- You code with an AI assistant
- You want to plan your work instead of figuring it out while coding
- You need your AI to remember what you're building across sessions
- You prefer terminal tools and keeping everything in git

<br>

---

<div align="center">

<h3>You plan. Quadro stores it. Your AI reads it.</h3>

<a href="https://spec-driven.github.io/quadro/">
  <img src="https://img.shields.io/badge/Get_started-→-CCFF00?style=for-the-badge&labelColor=000000" alt="Get started">
</a>

</div>
interpax 0.3.12
Interpolation and function approximation with JAX
License: MIT
Requires Python: >=3.10
Keywords: interpolation spline cubic fourier approximation


########
interpax
########
|License| |DOI| |Issues| |Pypi|

|Docs| |UnitTests| |Codecov|

interpax is a library for interpolation and function approximation using JAX.

Includes methods for nearest neighbor, linear, and several cubic interpolation schemes
in 1d, 2d, and 3d, as well as Fourier interpolation for periodic functions in
1d and 2d.

Coming soon:
- Spline interpolation for rectilinear grids in N-dimensions
- RBF interpolation for unstructured data in N-dimensions
- Smoothing splines for noisy data


Installation
============

interpax is installable with `pip`:

.. code-block:: console

    pip install interpax



Usage
=====

.. code-block:: python

    import jax.numpy as jnp
    import numpy as np
    from interpax import interp1d

    xp = jnp.linspace(0, 2 * np.pi, 100)
    xq = jnp.linspace(0, 2 * np.pi, 10000)
    f = lambda x: jnp.sin(x)
    fp = f(xp)

    fq = interp1d(xq, xp, fp, method="cubic")
    np.testing.assert_allclose(fq, f(xq), rtol=1e-6, atol=1e-5)


For full details of various options see the `API documentation <https://interpax.readthedocs.io/en/latest/api.html>`__


.. |License| image:: https://img.shields.io/github/license/f0uriest/interpax?color=blue&logo=open-source-initiative&logoColor=white
    :target: https://github.com/f0uriest/interpax/blob/master/LICENSE
    :alt: License

.. |DOI| image:: https://zenodo.org/badge/706703896.svg
    :target: https://zenodo.org/doi/10.5281/zenodo.10028967
    :alt: DOI

.. |Docs| image:: https://img.shields.io/readthedocs/interpax?logo=Read-the-Docs
    :target: https://interpax.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation

.. |UnitTests| image:: https://github.com/f0uriest/interpax/actions/workflows/unittest.yml/badge.svg
    :target: https://github.com/f0uriest/interpax/actions/workflows/unittest.yml
    :alt: UnitTests

.. |Codecov| image:: https://codecov.io/github/f0uriest/interpax/graph/badge.svg?token=MB11I7WE3I
    :target: https://codecov.io/github/f0uriest/interpax
    :alt: Coverage

.. |Issues| image:: https://img.shields.io/github/issues/f0uriest/interpax
    :target: https://github.com/f0uriest/interpax/issues
    :alt: GitHub issues

.. |Pypi| image:: https://img.shields.io/pypi/v/interpax
    :target: https://pypi.org/project/interpax/
    :alt: Pypi
quadax 0.2.11
Numerical quadrature with JAX
License: MIT
Requires Python: >=3.10
Keywords: integration quadrature gauss kronrod tanh sinh romberg adaptive


########
quadax
########
|License| |DOI| |Issues| |Pypi|

|Docs| |UnitTests| |Codecov|

quadax is a library for numerical quadrature and integration using JAX.

- ``vmap``-able, ``jit``-able, differentiable.
- Scalar or vector valued integrands.
- Finite or infinite domains with discontinuities or singularities within the domain of integration.
- Globally adaptive Gauss-Kronrod and Clenshaw-Curtis quadrature for smooth integrands (similar to ``scipy.integrate.quad``)
- Adaptive tanh-sinh quadrature for singular or near singular integrands.
- Quadrature from sampled values using trapezoidal and Simpsons methods.

Coming soon:

- Custom JVP/VJP rules (currently AD works by differentiating the loop which isn't the most efficient.)
- N-D quadrature (cubature)
- QMC methods
- Integration with weight functions
- Sparse grids (maybe, need to play with data structures and JAX)

Installation
============

quadax is installable with `pip`:

.. code-block:: console

    pip install quadax



Usage
=====

.. code-block:: python

    import jax.numpy as jnp
    import numpy as np
    from quadax import quadgk

    fun = lambda t: t * jnp.log(1 + t)

    epsabs = epsrel = 1e-5 # by default jax uses 32 bit, higher accuracy requires going to 64 bit
    a, b = 0, 1
    y, info = quadgk(fun, [a, b], epsabs=epsabs, epsrel=epsrel)
    assert info.err < max(epsabs, epsrel*abs(y))
    np.testing.assert_allclose(y, 1/4, rtol=epsrel, atol=epsabs)


For full details of various options see the `API documentation <https://quadax.readthedocs.io/en/latest/api.html>`__


.. |License| image:: https://img.shields.io/github/license/f0uriest/quadax?color=blue&logo=open-source-initiative&logoColor=white
    :target: https://github.com/f0uriest/quadax/blob/master/LICENSE
    :alt: License

.. |DOI| image:: https://zenodo.org/badge/709132830.svg
    :target: https://zenodo.org/doi/10.5281/zenodo.10035983
    :alt: DOI

.. |Docs| image:: https://img.shields.io/readthedocs/quadax?logo=Read-the-Docs
    :target: https://quadax.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation

.. |UnitTests| image:: https://github.com/f0uriest/quadax/actions/workflows/unittest.yml/badge.svg
    :target: https://github.com/f0uriest/quadax/actions/workflows/unittest.yml
    :alt: UnitTests

.. |Codecov| image:: https://codecov.io/github/f0uriest/quadax/graph/badge.svg?token=MB11I7WE3I
    :target: https://codecov.io/github/f0uriest/quadax
    :alt: Coverage

.. |Issues| image:: https://img.shields.io/github/issues/f0uriest/quadax
    :target: https://github.com/f0uriest/quadax/issues
    :alt: GitHub issues

.. |Pypi| image:: https://img.shields.io/pypi/v/quadax
    :target: https://pypi.org/project/quadax/
    :alt: Pypi