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Transition from setup.py to pyproject.toml
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* Move static package configuration from setup.py to pyproject.toml
  - Minimal changes were made to the configuration, so it still lists
    Python 2.7 as the minimum version, though it hasn't been tested what
the minimum version of Python is that can install the package with a
pyproject.toml file and no setup.py.
  - Drop the `future` dependency since it is not needed with Python 3.
* Merge long description content in setup.py into README.rst
* Capture development dependencies listed in setup.py in
  requirements-dev.txt
* Save change log which was in long description in setup.py in its own
  file, CHANGES.rst.
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wshanks committed Mar 15, 2024
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211 changes: 1 addition & 210 deletions setup.py → CHANGES.rst
100755 → 100644
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#!/usr/bin/env python
# -*- coding: utf-8 -*-

import os
import sys

# Common options for distutils/setuptools's setup():
setup_options = dict(
name='uncertainties',
version='3.1.7',
author='Eric O. LEBIGOT (EOL)',
author_email='eric.lebigot@normalesup.org',
url='http://uncertainties-python-package.readthedocs.io/',
license='Revised BSD License',
description=('Transparent calculations with uncertainties on the'
' quantities involved (aka error propagation);'
' fast calculation of derivatives'),
long_description='''\
Overview
========
``uncertainties`` allows **calculations** such as (2 +/- 0.1)*2 = 4 +/-
0.2 to be **performed transparently**. Much more complex mathematical
expressions involving numbers with uncertainties can also be evaluated
directly.
The ``uncertainties`` package **takes the pain and complexity out**
of uncertainty calculations.
**Detailed information** about this package can be found on its `main
website`_.
Basic examples
==============
.. code-block:: python
>>> from uncertainties import ufloat
>>> x = ufloat(2, 0.25)
>>> x
2.0+/-0.25
>>> square = x**2 # Transparent calculations
>>> square
4.0+/-1.0
>>> square.nominal_value
4.0
>>> square.std_dev # Standard deviation
1.0
>>> square - x*x
0.0 # Exactly 0: correlations taken into account
>>> from uncertainties.umath import * # sin(), etc.
>>> sin(1+x**2)
-0.95892427466313845+/-0.2836621854632263
>>> print (2*x+1000).derivatives[x] # Automatic calculation of derivatives
2.0
>>> from uncertainties import unumpy # Array manipulation
>>> random_vars = unumpy.uarray([1, 2], [0.1, 0.2])
>>> print random_vars
[1.0+/-0.1 2.0+/-0.2]
>>> print random_vars.mean()
1.50+/-0.11
>>> print unumpy.cos(random_vars)
[0.540302305868+/-0.0841470984808 -0.416146836547+/-0.181859485365]
Main features
=============
- **Transparent calculations with uncertainties**: **no or little
modification of existing code** is needed. Similarly, the Python_ (or
IPython_) shell can be used as **a powerful calculator** that
handles quantities with uncertainties (``print`` statements are
optional, which is convenient).
- **Correlations** between expressions are correctly taken into
account. Thus, ``x-x`` is exactly zero, for instance (most
implementations found on the web yield a non-zero uncertainty for
``x-x``, which is incorrect).
- **Almost all mathematical operations** are supported, including most
functions from the standard math_ module (sin,...). Comparison
operators (``>``, ``==``, etc.) are supported too.
- Many **fast operations on arrays and matrices** of numbers with
uncertainties are supported.
- **Extensive support for printing** numbers with uncertainties
(including LaTeX support and pretty-printing).
- Most uncertainty calculations are performed **analytically**.
- This module also gives access to the **derivatives** of any
mathematical expression (they are used by error
propagation theory, and are thus automatically calculated by this
module).
Installation or upgrade
=======================
Installation instructions are available on the `main web site
<http://uncertainties-python-package.readthedocs.io/en/latest/index.html#installation-and-download>`_
for this package.
Contact
=======
Please send **feature requests, bug reports, or feedback** to
`Eric O. LEBIGOT (EOL)`_.
Version history
===============

Expand Down Expand Up @@ -247,102 +132,8 @@
- 1.0.9: ``correlations()`` renamed more appropriately as
``covariance_matrix()``.

.. _Python: http://docs.python.org/tutorial/interpreter.html
.. _IPython: http://ipython.readthedocs.io/en/stable/
.. _NumPy: http://numpy.scipy.org/
.. _math: http://docs.python.org/library/math.html
.. _PEP 8: http://www.python.org/dev/peps/pep-0008/
.. _error propagation theory: http://en.wikipedia.org/wiki/Propagation_of_uncertainty
.. _Eric O. LEBIGOT (EOL): mailto:eric.lebigot@normalesup.org
.. _PayPal: https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=4TK7KNDTEDT4S
.. _main website: http://uncertainties-python-package.readthedocs.io/
.. _code updater: http://uncertainties-python-package.readthedocs.io/en/latest/index.html#migration-from-version-1-to-version-2
.. _formatting: http://uncertainties-python-package.readthedocs.io/en/latest/user_guide.html#printing''',
classifiers=[
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Other Audience',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: BSD License',
'Operating System :: OS Independent',
'Programming Language :: Python',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Programming Language :: Python :: 3.11',
'Programming Language :: Python :: 3.12',
'Programming Language :: Python :: Implementation :: Jython',
'Programming Language :: Python :: Implementation :: PyPy',
'Topic :: Education',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Mathematics',
'Topic :: Scientific/Engineering :: Physics',
'Topic :: Software Development',
'Topic :: Software Development :: Libraries',
'Topic :: Software Development :: Libraries :: Python Modules',
'Topic :: Utilities'
],

keywords=[
'error propagation', 'uncertainties', 'uncertainty calculations',
'standard deviation', 'derivatives', 'partial derivatives',
'differentiation'
],

# Files are defined in MANIFEST (which is automatically created by
# python setup.py sdist bdist_wheel):
packages=[
'uncertainties', 'uncertainties.unumpy', 'uncertainties.lib1to2',
'uncertainties.lib1to2.fixes'
],

# The code runs with both Python 2 and Python 3:
options={"bdist_wheel": {"universal": True}}
)

# The best available setup() is used (some users do not have
# setuptools):
try:
from setuptools import setup

# Some setuptools-specific options can be added:

addtl_setup_options = dict(

project_urls={
'Documentation':
'https://uncertainties-python-package.readthedocs.io/',
'Source': 'https://github.com/lebigot/uncertainties'
},

install_requires=['future'],

tests_require=['nose', 'numpy'],

# Optional dependencies install using:
# `easy_install uncertainties[optional]`
extras_require={
'optional': ['numpy'],
'docs': ['sphinx'],
}
)

# easy_install uncertainties[tests] option:
addtl_setup_options['extras_require']['tests'] = (
addtl_setup_options['tests_require'])

# easy_install uncertainties[all] option: all dependencies are
# gathered
addtl_setup_options['extras_require']['all'] = set(
sum(addtl_setup_options['extras_require'].values(), []))

setup_options.update(addtl_setup_options)

except ImportError:
from distutils.core import setup

# End of setup definition
.. _formatting: http://uncertainties-python-package.readthedocs.io/en/latest/user_guide.html#printing

setup(**setup_options)
102 changes: 89 additions & 13 deletions README.rst
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Expand Up @@ -13,31 +13,101 @@ uncertainties
.. image:: https://img.shields.io/github/actions/workflow/status/lmfit/uncertainties/python-package.yml?logo=github%20actions
:target: https://github.com/lmfit/uncertainties/actions/workflows/python-package.yml

This is the ``uncertainties`` Python package, which performs **transparent
calculations with uncertainties** (aka "error propagation"):
``uncertainties`` allows **calculations** such as (2 +/- 0.1)*2 = 4 +/-
0.2 to be **performed transparently**. Much more complex mathematical
expressions involving numbers with uncertainties can also be evaluated
directly.

The ``uncertainties`` package **takes the pain and complexity out**
of uncertainty calculations.

**Detailed information** about this package can be found on its `main
website`_.

Basic examples
--------------

.. code-block:: python
>>> from uncertainties import ufloat
>>> from uncertainties.umath import * # sin(), etc.
>>> x = ufloat(1, 0.1) # x = 1+/-0.1
>>> print(2*x)
2.00+/-0.20
>>> sin(2*x) # In a Python shell, "print" is optional
0.9092974268256817+/-0.08322936730942848
This package also **automatically calculates derivatives of arbitrary functions**:
>>> x = ufloat(2, 0.25)
>>> x
2.0+/-0.25
>>> square = x**2 # Transparent calculations
>>> square
4.0+/-1.0
>>> square.nominal_value
4.0
>>> square.std_dev # Standard deviation
1.0
>>> (2*x+1000).derivatives[x]
>>> square - x*x
0.0 # Exactly 0: correlations taken into account
>>> from uncertainties.umath import * # sin(), etc.
>>> sin(1+x**2)
-0.95892427466313845+/-0.2836621854632263
>>> print (2*x+1000).derivatives[x] # Automatic calculation of derivatives
2.0
The main documentation is available at
https://uncertainties.readthedocs.io/.
>>> from uncertainties import unumpy # Array manipulation
>>> random_vars = unumpy.uarray([1, 2], [0.1, 0.2])
>>> print random_vars
[1.0+/-0.1 2.0+/-0.2]
>>> print random_vars.mean()
1.50+/-0.11
>>> print unumpy.cos(random_vars)
[0.540302305868+/-0.0841470984808 -0.416146836547+/-0.181859485365]
Main features
-------------

- **Transparent calculations with uncertainties**: **no or little
modification of existing code** is needed. Similarly, the Python_ (or
IPython_) shell can be used as **a powerful calculator** that
handles quantities with uncertainties (``print`` statements are
optional, which is convenient).

- **Correlations** between expressions are correctly taken into
account. Thus, ``x-x`` is exactly zero, for instance (most
implementations found on the web yield a non-zero uncertainty for
``x-x``, which is incorrect).

- **Almost all mathematical operations** are supported, including most
functions from the standard math_ module (sin,...). Comparison
operators (``>``, ``==``, etc.) are supported too.

- Many **fast operations on arrays and matrices** of numbers with
uncertainties are supported.

- **Extensive support for printing** numbers with uncertainties
(including LaTeX support and pretty-printing).

- Most uncertainty calculations are performed **analytically**.

- This module also gives access to the **derivatives** of any
mathematical expression (they are used by `error
propagation theory`_, and are thus automatically calculated by this
module).


Installation or upgrade
-----------------------

Installation instructions are available on the `main web site
<http://uncertainties-python-package.readthedocs.io/en/latest/index.html#installation-and-download>`_
for this package.



Git branches
------------

The ``release`` branch is the latest stable release. It should pass the tests.


``master*`` branches in the Github repository are bleeding-edge, and do not
necessarily pass the tests. The ``master`` branch is the latest, relatively
stable versions (while other ``master*`` branches are more experimental).
Expand Down Expand Up @@ -67,3 +137,9 @@ History
This package was created back around 2009 by `Eric O. LEBIGOT <https://github.com/lebigot>`_.

Ownership of the package was taken over by the `lmfit GitHub organization <https://github.com/lmfit>`_ in 2024.

.. _Python: http://docs.python.org/tutorial/interpreter.html
.. _IPython: http://ipython.readthedocs.io/en/stable/
.. _math: http://docs.python.org/library/math.html
.. _error propagation theory: http://en.wikipedia.org/wiki/Propagation_of_uncertainty
.. _main website: http://uncertainties-python-package.readthedocs.io/
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