Merge branch 'release/0.4.0'

.readthedocs.yml

@@ -0,0 +1,25 @@
+# .readthedocs.yml
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Build documentation in the docs/ directory with Sphinx
+sphinx:
+  configuration: docs/source/conf.py
+
+# Build documentation with MkDocs
+#mkdocs:
+#  configuration: mkdocs.yml
+
+# Optionally build your docs in additional formats such as PDF
+formats:
+  - pdf
+
+# Optionally set the version of Python and requirements required to build your docs
+python:
+  version: 3.7
+  install:
+    - requirements: docs/requirements.txt
+  system_packages: true

.travis.yml

@@ -5,6 +5,7 @@ language: python
 python:
  - "3.6"
  - "3.7"
+ - "3.8"
 
 # Install dependencies into Travis-CI's virtualenv
 install:

CHANGELOG.md

@@ -0,0 +1,39 @@
+# LEAP CHANGES BY VERSION
+
+Being a terse compilation by version of changes.
+
+## 0.4.0, 9/19/2020
+
+* Significantly added to online [documentation](https://leap-gmu.readthedocs.io/en/latest/index.html)
+* Major code reorganization
+    * exception management for `Individual` has been moved to `RobustIndividual`
+    * `DistributedIndividual` now inherits from `RobustIndividual`
+    * `core.py` has been broken out to separate modules
+        * `Individual` and `RobustIndividual` now in `individual.py`
+        * representation specific entities moved to new sub-packages, `binary_rep`
+          and `real_rep`
+        * `Representation` now in `representation.py`
+        * `Decoder` now in `decoder.py`
+    * documentation, doctests, examples, Jupyter notebooks, and unit tests updated accordingly 
+* added ability to pass ancillary information during evaluation, such as UUIDs
+  that could be used to name output files and directories, yet do not have a 
+  direct impact on fitness
+
+## 0.3.1
+
+* Apply `Representation` consistently throughout LEAP, particulary the top-level monolithic functions
+* Added probe to `leap_ec.distributed.asynchronous.stead_state()` to take regular snapshots of the population
+
+## 0.3
+
+* fix how non-viable individuals sort themselves when compared since the prior method of comparing math.nan to math.nan yielded non-ideal behavior 
+* minor maintenance tweaks
+
+## 0.2
+
+* changed package name to `leap_ec` from `leap` to mitigate pypi namespace collisions
+* minor maintenance tweaks
+
+## 0.1
+
+* first major "mature" release of LEAP

README.md

@@ -51,7 +51,7 @@ algorithm.
 
 Here's an example that applies a genetic algorithm variant to solve the 
 `MaxOnes` optimization problem.  It uses bitflip mutation, uniform crossover, 
-and binary tournament selection:
+and binary tournament_selection selection:
 
 ```Python
 from leap_ec.algorithm import generational_ea
@@ -66,7 +66,7 @@ ea = generational_ea(generations=100, pop_size=pop_size,
                      ),
 
                      # The operator pipeline
-                     pipeline=[ops.tournament,                     # Select parents via tournament selection
+                     pipeline=[ops.tournament_selection,                     # Select parents via tournament_selection selection
                                ops.clone,                          # Copy them (just to be safe)
                                ops.mutate_bitflip,                 # Basic mutation: defaults to a 1/L mutation rate
                                ops.uniform_crossover(p_swap=0.4),  # Crossover with a 40% chance of swapping each gene