Merge pull request #90 from ChristopherMayes/documentation

Documentation + bugfixes + quality of life upgrades
xopt-org · Feb 9, 2023 · 5b4d9e9 · 5b4d9e9
2 parents 87c7f9b + ae3875c
commit 5b4d9e9
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Showing 25 changed files with 674 additions and 1,012 deletions.
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -25,11 +25,6 @@ jobs:
           channels: conda-forge
           activate-environment: xopt-dev
           environment-file: environment.yml
-
-      - name: flake8
-        shell: bash -l {0}
-        run: |
-          flake8 .
 
       - name: Install Xopt
         shell: bash -l {0}

diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml
@@ -17,7 +17,7 @@ jobs:
       - uses: conda-incubator/setup-miniconda@v2
         with:
           python-version: ${{ matrix.python-version }}
-         miniforge-variant: Mambaforge
+          miniforge-variant: Mambaforge
           channels: conda-forge
           activate-environment: xopt-dev
           environment-file: environment.yml

diff --git a/.github/workflows/formatting.yml b/.github/workflows/formatting.yml
@@ -0,0 +1,32 @@
+name: Formatting
+
+on:
+  push:
+  pull_request:
+  schedule:
+    - cron: '0 0 * * *'  # every day at midnight
+
+jobs:
+  build:
+    runs-on: ${{ matrix.os }}
+    defaults:
+        run:
+          shell: bash
+    strategy:
+      matrix:
+        os: [ubuntu-latest]
+        python-version: [3.9]
+    steps:
+      - uses: actions/checkout@v3
+      - uses: conda-incubator/setup-miniconda@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+          miniforge-variant: Mambaforge
+          channels: conda-forge
+          activate-environment: xopt-dev
+          environment-file: environment.yml
+
+      - name: flake8
+        shell: bash -l {0}
+        run: |
+          flake8 .
diff --git a/docs/examples/bayes_exp/bayesian_exploration.ipynb b/docs/examples/bayes_exp/bayesian_exploration.ipynb
diff --git a/docs/examples/bayes_exp/bayesian_exploration_from_yaml.ipynb b/docs/examples/bayes_exp/bayesian_exploration_from_yaml.ipynb
diff --git a/docs/examples/bayes_exp/benchmarking.ipynb b/docs/examples/bayes_exp/benchmarking.ipynb
diff --git a/docs/examples/bayes_opt/benchmarking.ipynb b/docs/examples/bayes_opt/benchmarking.ipynb
diff --git a/docs/examples/bayes_opt/custom_model.ipynb b/docs/examples/bayes_opt/custom_model.ipynb
diff --git a/docs/examples/bayes_opt/mggpo.ipynb b/docs/examples/bayes_opt/mggpo.ipynb
diff --git a/docs/examples/bayes_opt/upper_confidence_bound_rosenbrock.ipynb b/docs/examples/bayes_opt/upper_confidence_bound_rosenbrock.ipynb
@@ -2,11 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
+   "metadata": {},
    "source": [
     "# Upper Confidence Bound BO\n"
    ]
@@ -20,9 +16,6 @@
      "iopub.status.busy": "2022-07-02T04:15:03.843424Z",
      "iopub.status.idle": "2022-07-02T04:15:04.772187Z",
      "shell.execute_reply": "2022-07-02T04:15:04.771689Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [],
@@ -40,10 +33,7 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%% md\n"
-    }
+    "collapsed": false
    },
    "source": [
     "## Customizing the UpperConfidenceBound Generator\n",
@@ -61,9 +51,6 @@
      "iopub.status.busy": "2022-07-02T04:15:04.774205Z",
      "iopub.status.idle": "2022-07-02T04:15:04.777577Z",
      "shell.execute_reply": "2022-07-02T04:15:04.777331Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [
@@ -106,9 +93,6 @@
      "iopub.status.busy": "2022-07-02T04:15:04.790318Z",
      "iopub.status.idle": "2022-07-02T04:15:04.793274Z",
      "shell.execute_reply": "2022-07-02T04:15:04.793009Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [
@@ -148,9 +132,6 @@
      "iopub.status.busy": "2022-07-02T04:15:04.794652Z",
      "iopub.status.idle": "2022-07-02T04:15:04.805490Z",
      "shell.execute_reply": "2022-07-02T04:15:04.805237Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [
@@ -264,18 +245,15 @@
    "source": [
     "X = Xopt(generator=generator, evaluator=evaluator, vocs=vocs)\n",
     "\n",
-    "for i in range(100):\n",
+    "for i in range(10):\n",
     "    X.step()\n",
     "    print(f\"step {i}: best: {X.data['y'].min()}\")\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%% md\n"
-    }
+    "collapsed": false
    },
    "source": [
     "## View output data"
@@ -291,9 +269,6 @@
      "iopub.status.busy": "2022-07-02T04:15:07.874844Z",
      "iopub.status.idle": "2022-07-02T04:15:07.879906Z",
      "shell.execute_reply": "2022-07-02T04:15:07.879654Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [
@@ -332,19 +307,13 @@
     "ax.set_aspect(\"equal\")"
    ],
    "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
+    "collapsed": false
    }
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%% md\n"
-    }
+    "collapsed": false
    },
    "source": [
     "## Visualize model used by upper confidence bound\n",
@@ -362,9 +331,6 @@
      "iopub.status.busy": "2022-07-02T04:15:07.881359Z",
      "iopub.status.idle": "2022-07-02T04:15:07.936006Z",
      "shell.execute_reply": "2022-07-02T04:15:07.935717Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [
@@ -451,10 +417,7 @@
     "ax = X.data.plot(y=\"y\", logy=True)"
    ],
    "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
+    "collapsed": false
    }
   },
   {
@@ -467,9 +430,6 @@
      "iopub.status.busy": "2022-07-02T04:15:07.937432Z",
      "iopub.status.idle": "2022-07-02T04:15:08.202741Z",
      "shell.execute_reply": "2022-07-02T04:15:08.202032Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [
@@ -509,4 +469,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
diff --git a/tests/generators/bayesian/test_expected_improvement.py b/tests/generators/bayesian/test_expected_improvement.py
@@ -5,20 +5,19 @@
 from xopt.base import Xopt
 
 from xopt.evaluator import Evaluator
-from xopt.generators.bayesian.bayesian_exploration import BayesianExplorationOptions
 from xopt.generators.bayesian.expected_improvement import ExpectedImprovementGenerator
+from xopt.generators.bayesian.upper_confidence_bound import UCBOptions
 
 from xopt.resources.testing import TEST_VOCS_BASE, TEST_VOCS_DATA, xtest_callable
 
 
 class TestExpectedImprovement:
     def test_init(self):
-        ucb_gen = ExpectedImprovementGenerator(TEST_VOCS_BASE)
-        ucb_gen.options.dict()
-        # ucb_gen.options.schema()
+        ei_gen = ExpectedImprovementGenerator(TEST_VOCS_BASE)
+        ei_gen.options.dict()
 
         with pytest.raises(ValueError):
-            ExpectedImprovementGenerator(TEST_VOCS_BASE, BayesianExplorationOptions())
+            ExpectedImprovementGenerator(TEST_VOCS_BASE, UCBOptions())
 
     def test_generate(self):
         gen = ExpectedImprovementGenerator(

diff --git a/tests/generators/bayesian/test_upper_confidence_bound.py b/tests/generators/bayesian/test_upper_confidence_bound.py
@@ -7,7 +7,7 @@
 from xopt.base import Xopt
 
 from xopt.evaluator import Evaluator
-from xopt.generators.bayesian.bayesian_exploration import BayesianExplorationOptions
+from xopt.generators.bayesian.options import BayesianOptions
 from xopt.generators.bayesian.upper_confidence_bound import (
     UpperConfidenceBoundGenerator,
 )
@@ -22,7 +22,7 @@ def test_init(self):
         # ucb_gen.options.schema()
 
         with pytest.raises(ValueError):
-            UpperConfidenceBoundGenerator(TEST_VOCS_BASE, BayesianExplorationOptions())
+            UpperConfidenceBoundGenerator(TEST_VOCS_BASE, BayesianOptions())
 
     def test_generate(self):
         gen = UpperConfidenceBoundGenerator(

diff --git a/tests/generators/test_extremum_seeking.py b/tests/generators/test_extremum_seeking.py
@@ -1,6 +1,7 @@
 import numpy as np
 import pytest
 from pydantic import ValidationError
+
 from xopt import Xopt
 from xopt.evaluator import Evaluator
 from xopt.generators.es.extremumseeking import ExtremumSeekingGenerator

diff --git a/xopt/generator.py b/xopt/generator.py
@@ -4,7 +4,7 @@
 
 import pandas as pd
 
-from xopt.pydantic import XoptBaseModel
+from xopt.pydantic import JSON_ENCODERS, XoptBaseModel
 from xopt.vocs import VOCS
 
 logger = logging.getLogger(__name__)
@@ -15,7 +15,11 @@ class GeneratorOptions(XoptBaseModel):
     Options for the generator.
     """
 
-    pass
+    class Config:
+        arbitrary_types_allowed = True
+        json_encoders = JSON_ENCODERS
+        extra = "forbid"
+        allow_mutation = True
 
 
 _GeneratorOptions = TypeVar("_GeneratorOptions", bound=GeneratorOptions)

diff --git a/xopt/generators/__init__.py b/xopt/generators/__init__.py
@@ -1,32 +1,68 @@
+import warnings
+
 from xopt.errors import XoptError
-from xopt.generators.bayesian.bayesian_exploration import BayesianExplorationGenerator
-from xopt.generators.bayesian.expected_improvement import ExpectedImprovementGenerator
-from xopt.generators.bayesian.mggpo import MGGPOGenerator
-from xopt.generators.bayesian.mobo import MOBOGenerator
-from xopt.generators.bayesian.upper_confidence_bound import (
-    TDUpperConfidenceBoundGenerator,
-    UpperConfidenceBoundGenerator,
-)
 from xopt.generators.es.extremumseeking import ExtremumSeekingGenerator
-
-from xopt.generators.ga import CNSGAGenerator
 from xopt.generators.random import RandomGenerator
-from xopt.generators.scipy.neldermead import NelderMeadGenerator
 
 # add generators here to be registered
 registered_generators = [
-    UpperConfidenceBoundGenerator,
-    MOBOGenerator,
-    BayesianExplorationGenerator,
-    CNSGAGenerator,
     RandomGenerator,
-    NelderMeadGenerator,
-    TDUpperConfidenceBoundGenerator,
-    ExpectedImprovementGenerator,
     ExtremumSeekingGenerator,
-    MGGPOGenerator,
 ]
 
+# generators needing deap
+try:
+    from xopt.generators.ga import CNSGAGenerator
+
+    registered_generators += [CNSGAGenerator]
+
+except ModuleNotFoundError:
+    warnings.warn("WARNING: `deap` not found, CNSGAGenerator is not available")
+
+# generators needing botorch
+try:
+    from xopt.generators.bayesian.bayesian_exploration import (
+        BayesianExplorationGenerator,
+    )
+    from xopt.generators.bayesian.expected_improvement import (
+        ExpectedImprovementGenerator,
+    )
+    from xopt.generators.bayesian.mobo import MOBOGenerator
+    from xopt.generators.bayesian.upper_confidence_bound import (
+        TDUpperConfidenceBoundGenerator,
+        UpperConfidenceBoundGenerator,
+    )
+
+    registered_generators += [
+        UpperConfidenceBoundGenerator,
+        MOBOGenerator,
+        BayesianExplorationGenerator,
+        TDUpperConfidenceBoundGenerator,
+        ExpectedImprovementGenerator,
+    ]
+
+except ModuleNotFoundError:
+    warnings.warn("WARNING: `botorch` not found, Bayesian generators are not available")
+
+# generators requiring deap AND botorch
+try:
+    from xopt.generators.bayesian.mggpo import MGGPOGenerator
+
+    registered_generators += [MGGPOGenerator]
+except ModuleNotFoundError:
+    warnings.warn(
+        "WARNING: `deap` and `botorch` not found, MGGPOGenerator is not " "available"
+    )
+
+try:
+    from xopt.generators.scipy.neldermead import NelderMeadGenerator
+
+    registered_generators += [NelderMeadGenerator]
+
+except ModuleNotFoundError:
+    warnings.warn("WARNING: `scipy` not found, NelderMeadGenerator is not available")
+
+
 generators = {gen.alias: gen for gen in registered_generators}
 generator_default_options = {
     gen.alias: gen.default_options() for gen in registered_generators