first draft working and added action

Author: bwheelz36

.github/workflows/build_docs.yml

@@ -0,0 +1,43 @@
+name: build docs
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+
+jobs:
+  deploy:
+    runs-on: ubuntu-20.04
+    permissions:
+      contents: write
+    concurrency:
+      group: ${{ github.workflow }}-${{ github.ref }}
+    steps:
+      - uses: actions/checkout@v3
+
+      - name: Setup Python
+        uses: actions/setup-python@v3
+        with:
+          python-version: '3.10'
+      - name: Install pandoc
+        run: sudo apt-get install -y pandoc
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install sphinx
+          pip install nbsphinx
+          pip install sphinx_rtd_theme
+      - name: Install package
+        run: |
+          pip install -e .
+      - name: build sphinx docs
+        run: |
+          cd docsrc
+          make github
+#      - name: Deploy
+#        uses: peaceiris/actions-gh-pages@v3
+#        if: ${{ github.ref == 'refs/heads/main' }}
+#        with:
+#          github_token: ${{ secrets.GITHUB_TOKEN }}
+#          publish_dir: ./docs

docsrc/code_docs.rst

@@ -0,0 +1,34 @@
+Code Documentation
+==================
+
+This page shows the documentation generated by sphinx automatically scanning our source code
+
+Bayesian Optimization
+---------------------
+
+.. automodule:: bayes_opt.bayesian_optimization
+   :members:
+
+Acquisition function
+--------------------
+
+.. autoclass:: bayes_opt.util.UtilityFunction
+   :members:
+
+Target Space
+------------
+
+.. autoclass:: bayes_opt.target_space.TargetSpace
+   :members:
+
+Domain reduction
+----------------
+
+.. autoclass:: bayes_opt.domain_reduction.SequentialDomainReductionTransformer
+   :members:
+
+Constraints
+-----------
+
+.. autoclass:: bayes_opt.constraint.ConstraintModel
+   :members:

docsrc/constraints.ipynb

@@ -14,7 +14,7 @@
     "2. Expensive constraints - in other situations, you may not know whether or not a given solution violates your constraints until you have explicitly evaluate the objective function there - which is typically an expensive operation. In such situations, it is desirable to **learn** the constrained regions on the fly in order to avoid unnecessary expensive calls to the objective function. The way to handle these situations is described in **2. Advanced Constrained Optimization**\n",
     "\n",
     "\n",
-    "# 1. Simple Constrained Optimization\n",
+    "## 1. Simple Constrained Optimization\n",
     "\n",
     "In situations where you know in advance whether or not a given point violates your constraints, you can normally simply code them directly into the objective function. To demonstrate this, let's start with a standard non-constrained optimization:"
    ]
@@ -161,7 +161,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 2. Advanced Constrained Optimization"
+    "## 2. Advanced Constrained Optimization"
    ]
   },
   {

docsrc/examples.rst

@@ -10,6 +10,4 @@ Examples
    /exploitation_vs_exploration
    /visualization
    /constraints
-   /domain_reduction
-   /Spot
-   /steering_dispersion
+   /domain_reduction