mp: removed dead code, add basic example

README.md

@@ -1,9 +1,11 @@
-# Max Value Entropy Search Approximations
+# Variational Entropy Search is Just 1D Regression
 
 Building on this ICML 2025 spotlight paper: [A Unified Framework for Entropy Search and
 Expected Improvement in Bayesian Optimization](https://arxiv.org/pdf/2501.18756)
 
-Collections of toy expertiments for approximating Max Value entropy Search
+Collections of toy expertiments for approximating Max Value entropy Search with variational methods. This simply boils down to fitting a 1D regression model for each and measuring the loss function, the x location with lowest loss is chosen for black box evaluation.
+
+This code is purely for running toy experiments for the researtch paper "Variational Entropy Search is Just 1D Regression"
 
 ![Distribution of Max Values gitven 3 points](scripts/original_data.png)
 
@@ -18,10 +20,15 @@ https://docs.astral.sh/uv/getting-started/installation/
 # install the other dependencies
 uv venv
 uv pip install -e .
+uv run pytest
 ```
 
 # Usage
-This makes the images and animation
+You can run an experiment using these commands
 ```
-uv run pytest
-```
+cd scripts
+python make_1d_benchmark_funs.py  # makes a set of 1D GP sample functions for BO testing 
+python make_1d_bo_animation.py            # applies BO method, and parses the resuls into an animation
+```
+
+![Expected Improvement](scripts/bo_history.gif)

pyproject.toml

@@ -38,9 +38,10 @@ Issues = "https://github.com/graphcore-research/mes"
 [tool.pytest.ini_options]
 minversion = "7.0"
 addopts = "-ra -q"
-testpaths = [
-    "tests",
-]
+testpaths = ["tests"]
+python_files = ["test_*.py", "*_test.py"]
+python_functions = "test_*"
+
 
 [dependency-groups]
 dev = [
@@ -63,7 +64,7 @@ exclude = [
 
 
 [tool.ruff.lint]
-ignore = ["E731"]
+ignore = ["E731"]  # lambda functions can be assigned to variables
 
 
 [tool.ruff.format]