Merge branch 'master' of https://github.com/Helmholtz-AI-Energy/propu…

…late

.github/workflows/python-test.yml

@@ -0,0 +1,55 @@
+name: Python test
+
+on: [push]
+
+jobs:
+    build:
+        runs-on: ubuntu-latest
+        steps:
+            - uses: actions/checkout@v3
+            - name: Set up MPI
+              uses: mpi4py/setup-mpi@v1
+              with:
+                mpi: 'openmpi'
+            - name: Set up Python
+              uses: actions/setup-python@v4
+              with:
+                  python-version: '3.9'
+            - name: Install dependencies
+              run: |
+                  python -m pip install --upgrade pip
+                  pip install ruff pytest pytest-cov
+                  pip install coverage-badge
+                  pip install -r requirements.txt
+                  pip install .
+            - name: Lint with ruff
+              run: |
+                  # stop the build if there are Python syntax errors or undefined names
+                  ruff --output-format=github --select=E9,F63,F7,F82 --target-version=py39 .
+                  # default set of ruff rules with GitHub Annotations
+                  ruff --output-format=github --target-version=py39 .
+            - name: Test with pytest
+              run: |
+                pytest --cov=propulate
+                coverage-badge -fo coverage.svg
+
+            - name: Verify Changed files
+              uses: tj-actions/verify-changed-files@v16
+              id: verify-changed-files
+              with:
+                files: coverage.svg
+
+            - name: Commit files
+              if: steps.verify-changed-files.outputs.files_changed == 'true'
+              run: |
+                git config --local user.email "github-actions[bot]@users.noreply.github.com"
+                git config --local user.name "github-actions[bot]"
+                git add coverage.svg
+                git commit -m "Updated coverage.svg"
+
+            - name: Push changes
+              if: steps.verify-changed-files.outputs.files_changed == 'true'
+              uses: ad-m/github-push-action@master
+              with:
+                github_token: ${{ secrets.github_token }}
+                branch: ${{ github.ref }}

README.md

@@ -12,6 +12,7 @@
 [![OpenSSF Best Practices](https://www.bestpractices.dev/projects/7785/badge)](https://www.bestpractices.dev/projects/7785)
 [![](https://img.shields.io/badge/Contact-marie.weiel%40kit.edu-orange)](mailto:[email protected])
 [![Documentation Status](https://readthedocs.org/projects/propulate/badge/?version=latest)](https://propulate.readthedocs.io/en/latest/?badge=latest)
+![](./coverage.svg)
 
 # **Click [here](https://www.scc.kit.edu/en/aboutus/16956.php) to watch our 3 min introduction video!** 
 

propulate/propagators/cmaes.py

@@ -1,6 +1,5 @@
-import copy
 import random
-from typing import List, Dict, Union, Tuple
+from typing import List, Dict, Tuple
 
 import numpy as np
 

propulate/propagators/pso.py

@@ -127,8 +127,8 @@ def _prepare_data(
             else:
                 particles.append(make_particle(individual))
                 logging.warning(
-                    f"Got Individual instead of Particle. If this is on purpose, you can ignore this warning. "
-                    f"Converted the Individual to Particle. Continuing."
+                    "Got Individual instead of Particle. If this is on purpose, you can ignore this warning. "
+                    "Converted the Individual to Particle. Continuing."
                 )
 
         own_p = [

pyproject.toml

@@ -0,0 +1,29 @@
+[tool.ruff]
+select = ["E", "F"]
+ignore = ["E501"]
+
+exclude = [
+    ".bzr",
+    ".direnv",
+    ".eggs",
+    ".git",
+    ".git-rewrite",
+    ".hg",
+    ".mypy_cache",
+    ".nox",
+    ".pants.d",
+    ".pytype",
+    ".ruff_cache",
+    ".svn",
+    ".tox",
+    ".venv",
+    "__pypackages__",
+    "_build",
+    "buck-out",
+    "build",
+    "dist",
+    "node_modules",
+    "venv",
+]
+
+line-length = 88

requirements.txt

@@ -1,7 +1,6 @@
 cycler==0.11.0
 deepdiff>=5.8.0
 kiwisolver==1.4.2
-matplotlib==3.2.1
 mpi4py==3.0.3
 numpy
 ordered-set==4.1.0

setup.cfg

@@ -30,14 +30,13 @@ install_requires =
 	cycler #==0.11.0
 	deepdiff #==5.8.0
 	kiwisolver #==1.4.2
-	matplotlib #==3.2.1
 	mpi4py #==3.0.3
 	numpy #==1.22.3
 	ordered-set #==4.1.0
 	pyparsing #==3.0.7
 	python-dateutil #==2.8.2
 	six #==1.16.0
-    	colorlog
+    colorlog
 
 # The usage of test_requires is discouraged, see `Dependency Management` docs
 # tests_require = pytest; pytest-cov
@@ -102,7 +101,8 @@ exclude =
     dist
     .eggs
     docs/conf.py
-max-line-length = 250
+max-line-length = 88
+extend-ignore = E203, E501
 
 [semantic_release]
 branch = "release"

tests/test_cmaes.py

@@ -0,0 +1,60 @@
+import random
+import tempfile
+from typing import Dict
+from operator import attrgetter
+
+import numpy as np
+
+from propulate import Propulator
+from propulate.propagators import CMAPropagator, BasicCMA
+
+
+def sphere(params: Dict[str, float]) -> float:
+    """
+    Sphere function: continuous, convex, separable, differentiable, unimodal
+
+    Input domain: -5.12 <= x, y <= 5.12
+    Global minimum 0 at (x, y) = (0, 0)
+
+    Parameters
+    ----------
+    params: dict[str, float]
+            function parameters
+    Returns
+    -------
+    float
+        function value
+    """
+    return np.sum(np.array(list(params.values())) ** 2)
+
+
+def test_PSO():
+    """
+    Test single worker using Propulator to optimize sphere using a PSO propagator.
+    """
+    rng = random.Random(42)  # Separate random number generator for optimization.
+    limits = {
+        "a": (-5.12, 5.12),
+        "b": (-5.12, 5.12),
+    }
+    with tempfile.TemporaryDirectory() as checkpoint_path:
+        # Set up evolutionary operator.
+
+        adapter = BasicCMA()
+        propagator = CMAPropagator(adapter, limits, rng=rng)
+
+        # Set up propulator performing actual optimization.
+        propulator = Propulator(
+            loss_fn=sphere,
+            propagator=propagator,
+            generations=10,
+            checkpoint_path=checkpoint_path,
+            rng=rng,
+        )
+
+        # Run optimization and print summary of results.
+        propulator.propulate()
+        propulator.summarize()
+        best = min(propulator.population, key=attrgetter("loss"))
+
+        assert best.loss < 10.0

tests/test_propulator_sphere.py

@@ -0,0 +1,73 @@
+import random
+import tempfile
+from typing import Dict
+from operator import attrgetter
+import logging
+
+import numpy as np
+
+from propulate import Propulator
+from propulate.utils import get_default_propagator, set_logger_config
+
+
+def sphere(params: Dict[str, float]) -> float:
+    """
+    Sphere function: continuous, convex, separable, differentiable, unimodal
+
+    Input domain: -5.12 <= x, y <= 5.12
+    Global minimum 0 at (x, y) = (0, 0)
+
+    Parameters
+    ----------
+    params: dict[str, float]
+            function parameters
+    Returns
+    -------
+    float
+        function value
+    """
+    return np.sum(np.array(list(params.values())) ** 2)
+
+
+def test_Propulator():
+    """
+    Test single worker using Propulator to optimize sphere.
+    """
+    rng = random.Random(42)  # Separate random number generator for optimization.
+    limits = {
+        "a": (-5.12, 5.12),
+        "b": (-5.12, 5.12),
+    }
+    with tempfile.TemporaryDirectory() as checkpoint_path:
+        set_logger_config(
+            level=logging.INFO,
+            log_file=checkpoint_path + "/propulate.log",
+            log_to_stdout=True,
+            log_rank=False,
+            colors=True,
+        )
+        # Set up evolutionary operator.
+        propagator = get_default_propagator(  # Get default evolutionary operator.
+            pop_size=4,  # Breeding pool size
+            limits=limits,  # Search-space limits
+            mate_prob=0.7,  # Crossover probability
+            mut_prob=9.0,  # Mutation probability
+            random_prob=0.1,  # Random-initialization probability
+            rng=rng,  # Random number generator
+        )
+
+        # Set up propulator performing actual optimization.
+        propulator = Propulator(
+            loss_fn=sphere,
+            propagator=propagator,
+            generations=10,
+            checkpoint_path=checkpoint_path,
+            rng=rng,
+        )
+
+        # Run optimization and print summary of results.
+        propulator.propulate()
+        propulator.summarize()
+        best = min(propulator.population, key=attrgetter("loss"))
+
+        assert best.loss < 0.8

tests/test_pso.py

@@ -0,0 +1,69 @@
+import random
+import tempfile
+from typing import Dict
+from operator import attrgetter
+
+import numpy as np
+
+from propulate import Propulator
+from propulate.propagators import Conditional
+from propulate.propagators.pso import BasicPSO, InitUniformPSO
+
+
+def sphere(params: Dict[str, float]) -> float:
+    """
+    Sphere function: continuous, convex, separable, differentiable, unimodal
+
+    Input domain: -5.12 <= x, y <= 5.12
+    Global minimum 0 at (x, y) = (0, 0)
+
+    Parameters
+    ----------
+    params: dict[str, float]
+            function parameters
+    Returns
+    -------
+    float
+        function value
+    """
+    return np.sum(np.array(list(params.values())) ** 2)
+
+
+def test_PSO():
+    """
+    Test single worker using Propulator to optimize sphere using a PSO propagator.
+    """
+    rng = random.Random(42)  # Separate random number generator for optimization.
+    limits = {
+        "a": (-5.12, 5.12),
+        "b": (-5.12, 5.12),
+    }
+    with tempfile.TemporaryDirectory() as checkpoint_path:
+        # Set up evolutionary operator.
+
+        pso_propagator = BasicPSO(
+            0.729,
+            1.49334,
+            1.49445,
+            0,  # MPI rank TODO fix when implemented proper MPI parallel tests
+            limits,
+            rng,
+        )
+        init = InitUniformPSO(limits, rng=rng, rank=0)
+        propagator = Conditional(1, pso_propagator, init)  # TODO MPIify
+
+        # Set up propulator performing actual optimization.
+        propulator = Propulator(
+            loss_fn=sphere,
+            propagator=propagator,
+            generations=10,
+            checkpoint_path=checkpoint_path,
+            rng=rng,
+        )
+
+        # Run optimization and print summary of results.
+        propulator.propulate()
+        propulator.summarize()
+        best = min(propulator.population, key=attrgetter("loss"))
+
+        assert best.loss < 30.0

tutorials/cmaes_example.py

@@ -8,7 +8,7 @@
 from propulate import Propulator
 from propulate.propagators import BasicCMA, ActiveCMA, CMAPropagator
 from propulate.utils import set_logger_config
-from function_benchmark import *
+from function_benchmark import get_function_search_space
 
 
 if __name__ == "__main__":