Merge branch 'dev' into main

.github/workflows/python-test.yml

@@ -29,7 +29,7 @@ jobs:
     - name: Install dependencies
       run: |
         python3 -m pip install --upgrade pip
-        python3 -m pip install -r requirements.txt
+        python3 -m pip install -r requirements-all.txt
         python3 -m pip install -r requirements-test.txt
 
     - name: Test with pytest

README.md

@@ -225,9 +225,8 @@ and its object store we can do this efficiently!
 
 from functools import partial
 import numpy as np
-import ray
 from ruck import *
-from ruck.util import *
+from ruck.external.ray import *
 
 
 class OneMaxRayModule(EaModule):

examples/multiobjective.py

@@ -0,0 +1,79 @@
+#
+#  Copyright (c) 2021 Nathan Juraj Michlo
+#
+#  Permission is hereby granted, free of charge, to any person obtaining a copy
+#  of this software and associated documentation files (the "Software"), to deal
+#  in the Software without restriction, including without limitation the rights
+#  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+#  copies of the Software, and to permit persons to whom the Software is
+#  furnished to do so, subject to the following conditions:
+#
+#  The above copyright notice and this permission notice shall be included in
+#  all copies or substantial portions of the Software.
+#
+#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+#  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+#  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+#  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+#  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+#  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+#  SOFTWARE.
+#  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
+
+
+import numpy as np
+from matplotlib import pyplot as plt
+
+from ruck import *
+from ruck.external.deap import select_nsga2
+
+
+class MultiObjectiveMinimalModule(EaModule):
+    """
+    Minimal onemax example
+    - The goal is to flip all the bits of a boolean array to True
+    - Offspring are generated as bit flipped versions of the previous population
+    - Selection tournament is performed between the previous population and the offspring
+    """
+
+    # evaluate unevaluated members
+    def evaluate_values(self, values):
+        return [(y - x**2, x - y**2) for (x, y) in values]
+
+    # generate values in the range [-1, 1]
+    def gen_starting_values(self):
+        return [np.random.random(2) * 2 - 1 for _ in range(100)]
+
+    # randomly offset the members by a small amount
+    def generate_offspring(self, population):
+        return [Member(np.clip(m.value + np.random.randn(2) * 0.05, -1, 1)) for m in population]
+
+    # apply nsga2 to population, which tries to maintain a diverse set of solutions
+    def select_population(self, population, offspring):
+        return select_nsga2(population + offspring, len(population))
+
+
+if __name__ == '__main__':
+    # create and train the population
+    module = MultiObjectiveMinimalModule()
+    pop, logbook, halloffame = Trainer(generations=100, progress=True).fit(module)
+
+    print('initial stats:', logbook[0])
+    print('final stats:', logbook[-1])
+    print('best member:', halloffame.members[0])
+
+    # plot path
+    fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(10, 5))
+    # plot points
+    ax0.set_title('Pareto Optimal Values')
+    ax0.scatter(*zip(*(m.value for m in pop)))
+    ax0.set_xlabel('X')
+    ax0.set_ylabel('Y')
+    # plot pareto optimal solution
+    ax1.set_title('Pareto Optimal Scores')
+    ax1.scatter(*zip(*(m.fitness for m in pop)))
+    ax1.set_xlabel('Distances')
+    ax1.set_ylabel('Smoothness')
+    # display
+    fig.tight_layout()
+    plt.show()

examples/onemax_ray.py

@@ -32,9 +32,8 @@
 
 from functools import partial
 import numpy as np
-import ray
 from ruck import *
-from ruck.util import *
+from ruck.external.ray import *
 
 
 class OneMaxRayModule(EaModule):

examples/traveling_salesman.py

@@ -0,0 +1,100 @@
+#  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
+#  MIT License
+#
+#  Copyright (c) 2021 Nathan Juraj Michlo
+#
+#  Permission is hereby granted, free of charge, to any person obtaining a copy
+#  of this software and associated documentation files (the "Software"), to deal
+#  in the Software without restriction, including without limitation the rights
+#  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+#  copies of the Software, and to permit persons to whom the Software is
+#  furnished to do so, subject to the following conditions:
+#
+#  The above copyright notice and this permission notice shall be included in
+#  all copies or substantial portions of the Software.
+#
+#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+#  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+#  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+#  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+#  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+#  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+#  SOFTWARE.
+#  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
+
+import random
+import numpy as np
+import matplotlib.pyplot as plt
+from ruck import *
+
+
+class TravelingSalesmanModule(EaModule):
+
+    def __init__(self, points, num_individuals: int = 128, closed_path=False):
+        self.num_individuals = int(num_individuals)
+        self.points = np.array(points)
+        self.num_points = len(self.points)
+        self.closed_path = bool(closed_path)
+        # checks
+        assert self.points.ndim == 2
+        assert self.num_points > 0
+        assert self.num_individuals > 0
+
+    # OVERRIDE
+
+    def gen_starting_values(self):
+        values = [np.arange(self.num_points) for _ in range(self.num_individuals)]
+        [np.random.shuffle(v) for v in values]
+        return values
+
+    def generate_offspring(self, population):
+        # there are definitely much better ways to do this
+        return [Member(self._two_opt_swap(random.choice(population).value)) for _ in range(self.num_individuals)]
+
+    def evaluate_values(self, values):
+        # we negate because we want to  minimize dist
+        return [-self._get_dist(v) for v in values]
+
+    def select_population(self, population, offspring):
+        return R.select_tournament(population + offspring, len(population), k=3)
+
+    # HELPER
+
+    def _two_opt_swap(self, idxs):
+        i, j = np.random.randint(0, self.num_points, 2)
+        i, j = min(i, j), max(i, j)
+        nidxs = np.concatenate([idxs[:i], idxs[i:j][::-1], idxs[j:]])
+        return nidxs
+
+    def _get_dist(self, value):
+        if self.closed_path:
+            idxs_from, idxs_to = value, np.roll(value, -1)
+        else:
+            idxs_from, idxs_to = value[:-1], value[1:]
+        # compute dist
+        return np.sum(np.linalg.norm(self.points[idxs_from] - self.points[idxs_to], ord=2, axis=-1))
+
+    def get_plot_points(self, value):
+        idxs = value.value if isinstance(value, Member) else value
+        # handle case
+        if self.closed_path:
+            idxs = np.concatenate([idxs, [idxs[0]]])
+        # get consecutive points
+        xs, ys = self.points[idxs].T
+        return xs, ys
+
+
+if __name__ == '__main__':
+    # determinism
+    random.seed(42)
+    np.random.seed(42)
+    # get points
+    points = np.random.rand(72, 2)
+    # train
+    module = TravelingSalesmanModule(points=points, num_individuals=128, closed_path=False)
+    population, logbook, halloffame = Trainer(generations=1024).fit(module)
+
+    # plot path
+    fig, ax = plt.subplots(1, 1, figsize=(5, 5))
+    ax.plot(*module.get_plot_points(halloffame[0]))
+    plt.show()

requirements-all.txt

@@ -0,0 +1,8 @@
+pip>=21.0
+numpy>=1.19
+tqdm>=4
+
+# requirements needed for examples too
+ray>=1.6.0
+deap>=1.3
+matplotlib>=3

requirements.txt

@@ -1,5 +1,3 @@
 pip>=21.0
 numpy>=1.19
 tqdm>=4
-# ray should be an optional requirement
-ray>=1.6.0

ruck/external/__init__.py

@@ -0,0 +1,23 @@
+#  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
+#  MIT License
+#
+#  Copyright (c) 2021 Nathan Juraj Michlo
+#
+#  Permission is hereby granted, free of charge, to any person obtaining a copy
+#  of this software and associated documentation files (the "Software"), to deal
+#  in the Software without restriction, including without limitation the rights
+#  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+#  copies of the Software, and to permit persons to whom the Software is
+#  furnished to do so, subject to the following conditions:
+#
+#  The above copyright notice and this permission notice shall be included in
+#  all copies or substantial portions of the Software.
+#
+#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+#  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+#  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+#  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+#  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+#  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+#  SOFTWARE.
+#  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~

ruck/external/deap.py

@@ -0,0 +1,77 @@
+#  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
+#  MIT License
+#
+#  Copyright (c) 2021 Nathan Juraj Michlo
+#
+#  Permission is hereby granted, free of charge, to any person obtaining a copy
+#  of this software and associated documentation files (the "Software"), to deal
+#  in the Software without restriction, including without limitation the rights
+#  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+#  copies of the Software, and to permit persons to whom the Software is
+#  furnished to do so, subject to the following conditions:
+#
+#  The above copyright notice and this permission notice shall be included in
+#  all copies or substantial portions of the Software.
+#
+#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+#  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+#  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+#  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+#  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+#  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+#  SOFTWARE.
+#  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
+
+from typing import Optional
+from typing import Tuple
+from ruck.functional import check_selection
+
+
+try:
+    import deap
+except ImportError as e:
+    import warnings
+    warnings.warn('failed to import deap, please install it: $ pip install deap')
+    raise e
+
+# ========================================================================= #
+# deap helper                                                               #
+# ========================================================================= #
+
+
+@check_selection
+def select_nsga2(population, num_offspring: int, weights: Optional[Tuple[float, ...]] = None):
+    """
+    This is hacky... ruck doesn't yet have NSGA2
+    support, but we will add it in future!
+    """
+    # get a fitness value to perform checks
+    f = population[0].fitness
+    # check fitness
+    try:
+        for _ in f: break
+    except:
+        raise ValueError('fitness values do not have multiple values!')
+    # get weights
+    if weights is None:
+        weights = tuple(1.0 for _ in f)
+    # get deap
+    from deap import creator, tools, base
+    # initialize creator
+    creator.create('_SelIdxFitness', base.Fitness, weights=weights)
+    creator.create('_SelIdxIndividual', int, fitness=creator._SelIdxFitness)
+    # convert to deap population
+    idx_individuals = []
+    for i, m in enumerate(population):
+        ind = creator._SelIdxIndividual(i)
+        ind.fitness.values = m.fitness
+        idx_individuals.append(ind)
+    # run nsga2
+    chosen_idx = tools.selNSGA2(individuals=idx_individuals, k=num_offspring)
+    # return values
+    return [population[i] for i in chosen_idx]
+
+
+# ========================================================================= #
+# END                                                                       #
+# ========================================================================= #

ruck/util/_ray.py → ruck/external/ray.py

@@ -28,16 +28,19 @@
 from typing import List
 from typing import Sequence
 
-import ray
-from ray import ObjectRef
-
+try:
+    import ray
+except ImportError as e:
+    import warnings
+    warnings.warn('failed to import ray, please install it: $ pip install ray')
+    raise e
 
 # ========================================================================= #
 # ray                                                                       #
 # ========================================================================= #
 
 
-def ray_map(remote_fn: Callable[[Any], ObjectRef], items: Sequence[Any]) -> List[Any]:
+def ray_map(remote_fn: Callable[[Any], ray.ObjectRef], items: Sequence[Any]) -> List[Any]:
     """
     A simple ray alternative to `map`, input function should be
     a remote function that returns an object reference / future value

ruck/util/__init__.py

@@ -23,8 +23,4 @@
 #  ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
 
 
-from ruck.util._ray import ray_map
-from ruck.util._ray import ray_remote_put
-from ruck.util._ray import ray_remote_puts
-
 from ruck.util._timer import Timer

setup.py

@@ -48,7 +48,7 @@
     author="Nathan Juraj Michlo",
     author_email="[email protected]",
 
-    version="0.2.1",
+    version="0.2.2",
     python_requires=">=3.6",
     packages=setuptools.find_packages(),