Preparing for release.

Author: amogorkon

.gitignore

@@ -1,8 +1,9 @@
 .hypothesis
+.git
 .cache/*
 __pycache__
 .ipynb_checkpoints/
-_config.yml
+.pytest_cache
 DEV*
 TODO-fuzzy
 box

.pytest_cache/README.md

@@ -0,0 +1,8 @@
+# pytest cache directory #
+
+This directory contains data from the pytest's cache plugin,
+which provides the `--lf` and `--ff` options, as well as the `cache` fixture.
+
+**Do not** commit this to version control.
+
+See [the docs](https://docs.pytest.org/en/latest/cache.html) for more information.

.pytest_cache/v/cache/lastfailed

@@ -0,0 +1 @@
+{}

.pytest_cache/v/cache/nodeids

@@ -0,0 +1,59 @@
+[
+  "test_functionality.py::test_array",
+  "test_functionality.py::test_value",
+  "test_functionality.py::test_rating",
+  "test_units.py::Test_Functions::test_R",
+  "test_units.py::Test_Functions::test_S",
+  "test_units.py::Test_Functions::test_alpha",
+  "test_units.py::Test_Functions::test_alpha_2",
+  "test_units.py::Test_Functions::test_bounded_linear",
+  "test_units.py::Test_Functions::test_bounded_sigmoid",
+  "test_units.py::Test_Functions::test_constant",
+  "test_units.py::Test_Functions::test_gauss",
+  "test_units.py::Test_Functions::test_inv",
+  "test_units.py::Test_Functions::test_linear",
+  "test_units.py::Test_Functions::test_moderate",
+  "test_units.py::Test_Functions::test_noop",
+  "test_units.py::Test_Functions::test_normalize",
+  "test_units.py::Test_Functions::test_rectangular",
+  "test_units.py::Test_Functions::test_sigmoid",
+  "test_units.py::Test_Functions::test_simple_sigmoid",
+  "test_units.py::Test_Functions::test_singleton",
+  "test_units.py::Test_Functions::test_trapezoid",
+  "test_units.py::Test_Functions::test_triangular",
+  "test_units.py::Test_Functions::test_triangular_sigmoid",
+  "test_units.py::Test_Hedges::test_minus",
+  "test_units.py::Test_Hedges::test_plus",
+  "test_units.py::Test_Hedges::test_very",
+  "test_units.py::Test_Combinators::test_MAX",
+  "test_units.py::Test_Combinators::test_MIN",
+  "test_units.py::Test_Combinators::test_bounded_sum",
+  "test_units.py::Test_Combinators::test_einstein_product",
+  "test_units.py::Test_Combinators::test_einstein_sum",
+  "test_units.py::Test_Combinators::test_gamma_op",
+  "test_units.py::Test_Combinators::test_hamacher_product",
+  "test_units.py::Test_Combinators::test_hamacher_sum",
+  "test_units.py::Test_Combinators::test_lambda_op",
+  "test_units.py::Test_Combinators::test_lukasiewicz_AND",
+  "test_units.py::Test_Combinators::test_lukasiewicz_OR",
+  "test_units.py::Test_Combinators::test_product",
+  "test_units.py::Test_Domain::test_basics",
+  "test_units.py::Test_Set::test_complement",
+  "test_units.py::Test_Set::test_eq",
+  "test_units.py::Test_Set::test_normalized",
+  "test_units.py::Test_Set::test_sub_super_set",
+  "test_units.py::Test_Rules::test_rescale",
+  "test_units.py::Test_Truth::test_fairly_false_and_very_true",
+  "test_units.py::Test_Truth::test_true_and_false",
+  "test_units.py::Test_Truth::test_very_false_and_fairly_true",
+  "fuzzy/classes.py::fuzzy.classes.Domain",
+  "fuzzy/combinators.py::fuzzy.combinators.simple_disjoint_sum",
+  "fuzzy/functions.py::fuzzy.functions.bounded_linear",
+  "fuzzy/functions.py::fuzzy.functions.bounded_sigmoid",
+  "fuzzy/functions.py::fuzzy.functions.constant",
+  "fuzzy/functions.py::fuzzy.functions.linear",
+  "fuzzy/functions.py::fuzzy.functions.simple_sigmoid",
+  "fuzzy/functions.py::fuzzy.functions.singleton",
+  "fuzzy/functions.py::fuzzy.functions.triangular_sigmoid",
+  "fuzzy/rules.py::fuzzy.rules.round_partial"
+]

CONTRIBUTING.md

@@ -0,0 +1,2 @@
+If you want to contribute, you can do so by pull requests on github or by posting issues.
+Format style should follow PEP8. 

Dockerfile

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2017 Anselm Kiefner
+Copyright (c) 2017-2019 Anselm Kiefner
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

LICENSE

@@ -0,0 +1,25 @@
+
+name: fuzzylogic
+description: Fuzzy Logic for Python 3
+license: MIT
+url: https://github.com/amogorkon/fuzzylogic
+version: 0.1.1
+author: Anselm Kiefner
+author_email: fuzzylogic-pypi@anselm.kiefner.de
+python_requires: >3.6
+
+keywords: [fuzzy logic]
+classifiers:::[
+	Development Status :: 4 - Beta
+	Intended Audience :: Developers
+	Intended Audience :: Education
+	Intended Audience :: Manufacturing
+	Intended Audience :: Science/Research
+	Natural Language :: English
+	License :: OSI Approved :: MIT License
+	Operating System :: OS Independent
+	Programming Language :: Python :: 3 :: Only
+	Topic :: Scientific/Engineering :: Artificial Intelligence
+	Topic :: Scientific/Engineering :: Mathematics
+	Topic :: Scientific/Engineering :: Information Analysis
+]:::

META.stay

@@ -1,6 +1,5 @@
 # fuzzy - Fuzzy Logic for Python 3
-
-Thanks to hypothesis unit tests, I'm pretty confident that things should work out of the box in most cases. This is the third or fourth time I rebuilt this library from scratch to find the sweet spot between ease of use (beautiful is better than ugly!), testability (simple is better than complex!) and potential to optimize for performance (practicality beats purity!). 
+This is the fourth time I rebuilt this library from scratch to find the sweet spot between ease of use (beautiful is better than ugly!), testability (simple is better than complex!) and potential to optimize for performance (practicality beats purity!). 
 
 ### Why a new library?
 The first time I was confronted with fuzzy logic, I fell in love with the concept, but after reading books and checking out libraries etc. I found it frustrating how most people make fuzzy logic appear complicated, hard to handle and incorporate in code.
@@ -12,14 +11,14 @@ Finally, most education on the subject emphasize sets and membership functions,
 So, the idea is to have four main parts that work together: domains, sets, functions and rules. You start modelling your system by defining your domain of interest. Then you think about where your interesting points are in that domain and look for a function that might do what you want. In general, fuzzy.functions map any value to [0,1], that's all. Then simply wrap your function in a Set and assign this to the domain in question. Once assigned, you can plot that set and see if it actually looks how you imagined. Now that you have one or more sets, you also can start to combine them with set operations &, |, ~, etc. It's fairly straight forward.
 Finally, use the Rules to map input domain to output domain to actually control stuff.
 
-### Warning: Magic!
+### Warning: Magic
 To make it possible to write fuzzy logic in the most pythonic and simplest way imaginable, it was necessary to employ some magic tricks that normally are discouraged, but at least there's no black magic involved (aka meta-programming etc.), so things are easy to debug if there is a problem. Most notably:
-* all functions are recursive closures (which makes it kinda hard to serialize things, if you want to do that)
+* all functions are recursive closures (which makes it kinda hard to serialize things, if you really want to do that)
 * Set uses a lot of dunder functions to implement their logic, which can be a bit daunting at first glance
 * Domain and Set uses an assignment trick to make it possible to instantiate Set() without passing domain and name over and over (yet still be explicit, just not the way one would normally expect). This also allows to call sets as Domain.attributes, which also normally shouldn't be possible (since they are technically not attributes). However, this allows interesting things like dangling sets (sets without domains) that can be freely combined with other sets to avoid cluttering of domain-namespaces and just have the resulting set assigned to a domain to work with. 
 
 
-Check the notebook for working examples and documentation.
+Check the Showcase notebook for working examples and documentation.
 
 Have fun!
 - Anselm Kiefner