Merge branch 'dev' into main

.github/workflows/python-test.yml

@@ -5,18 +5,18 @@ name: test
 
 on:
   push:
-    branches: [ main, dev ]
+    branches: [ 'main', 'dev', 'dev-*' ]
     tags: [ '*' ]
   pull_request:
-    branches: [ main, dev ]
+    branches: [ 'main', 'dev', 'dev-*' ]
 
 jobs:
   build:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
         os: [ubuntu-latest] # [ubuntu-latest, windows-latest, macos-latest]
-        python-version: [3.8]
+        python-version: ['3.6', '3.7', '3.8', '3.9']
 
     steps:
     - uses: actions/checkout@v2

README.md

@@ -65,8 +65,8 @@ be made to members, instead new members should be created with the modified valu
 easily implement efficient multi-threading, see below!
 
 The trainer automatically constructs `HallOfFame` and `LogBook` objects which keep track of your
-population and offspring. `EaModule` provides defaults for `get_stats_groups` that can be overridden
-if you wish to customize the tracked statistics.
+population and offspring. `EaModule` provides defaults for `get_stats_groups` and `get_progress_stats`
+that can be overridden if you wish to customize the tracked statistics and statistics displayed by tqdm.
 
 
 ### Minimal OneMax Example

requirements.txt

@@ -1,4 +1,5 @@
 pip>=21.0
-numpy>=1.21.0
-tqdm>=4.60.0
+numpy>=1.19
+tqdm>=4
+# ray should be an optional requirement
 ray>=1.6.0

ruck/__init__.py

@@ -32,5 +32,9 @@
 from ruck._train import Trainer
 from ruck._train import yield_population_steps
 
+from ruck._history import HallOfFame
+from ruck._history import Logbook
+from ruck._history import StatsGroup
+
 # functional utils
 from ruck import functional as R

ruck/_history.py

@@ -239,7 +239,6 @@ def __iter__(self):
             yield self[i]
 
 
-
 # ========================================================================= #
 # END                                                                       #
 # ========================================================================= #

ruck/_module.py

@@ -29,6 +29,8 @@
 from typing import Sequence
 from typing import TypeVar
 
+import numpy as np
+
 from ruck._history import StatsGroup
 from ruck._member import Population
 from ruck.util._args import HParamsMixin
@@ -47,12 +49,15 @@ class EaModule(Generic[T], HParamsMixin):
     # OVERRIDABLE DEFAULTS
 
     def get_stats_groups(self) -> Dict[str, StatsGroup[T, Any]]:
-        # additional stats to be recorded
-        return {}
+        # default stats groups
+        return {
+            'fit': StatsGroup(lambda pop: [m.fitness for m in pop], min=np.min, max=np.max, mean=np.mean)
+        }
 
     def get_progress_stats(self) -> Sequence[str]:
         # which stats are included in the progress bar
-        return ('evals', 'fit:max',)
+        # - values added by trainer
+        return ('evals', 'fit:max')
 
     # REQUIRED
 
@@ -62,10 +67,10 @@ def gen_starting_values(self) -> List[T]:
     def generate_offspring(self, population: Population[T]) -> Population[T]:
         raise NotImplementedError
 
-    def select_population(self, population: Population[T], offspring: Population[T]) -> Population[T]:
+    def evaluate_values(self, values: List[T]) -> List[float]:
         raise NotImplementedError
 
-    def evaluate_values(self, values: List[T]) -> List[float]:
+    def select_population(self, population: Population[T], offspring: Population[T]) -> Population[T]:
         raise NotImplementedError
 
 

ruck/_train.py

@@ -130,7 +130,8 @@ def __init__(
     def fit(self, module: EaModule[T]) -> Tuple[Population[T], Logbook[T], HallOfFame[T]]:
         assert isinstance(module, EaModule)
         # history trackers
-        logbook, halloffame = self._create_default_trackers(module)
+        logbook = Logbook('gen', 'evals', **module.get_stats_groups())
+        halloffame = HallOfFame(n_best=self._history_n_best, maximize=True)
         # progress bar and training loop
         with tqdm(total=self._generations, desc='generation', disable=not self._progress, ncols=120) as p:
             for gen, population, offspring, evals in itertools.islice(self._offspring_generator(module), self._generations):
@@ -143,18 +144,6 @@ def fit(self, module: EaModule[T]) -> Tuple[Population[T], Logbook[T], HallOfFam
         # done
         return population, logbook, halloffame.freeze()
 
-    def _create_default_trackers(self, module: EaModule[T]) -> Tuple[Logbook[T], HallOfFame[T]]:
-        halloffame = HallOfFame(
-            n_best=self._history_n_best,
-            maximize=True,
-        )
-        logbook = Logbook(
-            'gen', 'evals',
-            fit=StatsGroup(lambda pop: [m.fitness for m in pop], min=np.min, max=np.max, mean=np.mean),
-            **module.get_stats_groups()
-        )
-        return logbook, halloffame
-
 
 # ========================================================================= #
 # END                                                                       #

setup.py

@@ -48,8 +48,8 @@
     author="Nathan Juraj Michlo",
     author_email="[email protected]",
 
-    version="0.0.1.dev1",
-    python_requires=">=3.8",
+    version="0.1.0",
+    python_requires=">=3.6",
     packages=setuptools.find_packages(),
 
     install_requires=install_requires,
@@ -62,7 +62,10 @@
     classifiers=[
         "License :: OSI Approved :: MIT License",
         "Operating System :: OS Independent",
+        "Programming Language :: Python :: 3.6",
+        "Programming Language :: Python :: 3.7",
         "Programming Language :: Python :: 3.8",
+        "Programming Language :: Python :: 3.9",
         "Intended Audience :: Science/Research",
     ],
 )