Insights module and SHAPInsight

.lockfiles/py310-dev.lock

@@ -8,7 +8,7 @@ anyio==4.4.0
     # via
     #   httpx
     #   jupyter-server
-appnope==0.1.4 ; platform_system == 'Darwin'
+appnope==0.1.4 ; sys_platform == 'darwin'
     # via ipykernel
 argon2-cffi==23.1.0
     # via jupyter-server
@@ -84,7 +84,9 @@ click==8.1.7
     #   pydoclint
     #   streamlit
 cloudpickle==3.0.0
-    # via dask
+    # via
+    #   dask
+    #   shap
 colorama==0.4.6
     # via
     #   click
@@ -230,6 +232,8 @@ idna==3.7
     #   httpx
     #   jsonschema
     #   requests
+imageio==2.36.1
+    # via scikit-image
 imagesize==1.4.1
     # via sphinx
 importlib-metadata==7.1.0
@@ -238,7 +242,7 @@ importlib-metadata==7.1.0
     #   opentelemetry-api
 iniconfig==2.0.0
     # via pytest
-intel-openmp==2021.4.0 ; platform_system == 'Windows'
+intel-openmp==2021.4.0 ; sys_platform == 'win32'
     # via mkl
 interface-meta==1.3.0
     # via formulaic
@@ -344,10 +348,14 @@ kiwisolver==1.4.5
     # via matplotlib
 latexcodec==3.0.0
     # via pybtex
+lazy-loader==0.4
+    # via scikit-image
 license-expression==30.3.0
     # via cyclonedx-python-lib
 lifelines==0.29.0
     # via ngboost
+lime==0.2.0.1
+    # via shap
 linear-operator==0.5.2
     # via
     #   botorch
@@ -370,6 +378,7 @@ matplotlib==3.9.1
     # via
     #   baybe (pyproject.toml)
     #   lifelines
+    #   lime
     #   seaborn
     #   types-seaborn
 matplotlib-inline==0.1.7
@@ -386,7 +395,7 @@ mdurl==0.1.2
     # via markdown-it-py
 mistune==3.0.2
     # via nbconvert
-mkl==2021.4.0 ; platform_system == 'Windows'
+mkl==2021.4.0 ; sys_platform == 'win32'
     # via torch
 mmh3==5.0.1
     # via e3fp
@@ -424,6 +433,7 @@ nest-asyncio==1.6.0
 networkx==3.3
     # via
     #   mordredcommunity
+    #   scikit-image
     #   torch
 ngboost==0.5.1
     # via baybe (pyproject.toml)
@@ -436,7 +446,9 @@ notebook-shim==0.2.4
     #   jupyterlab
     #   notebook
 numba==0.60.0
-    # via scikit-fingerprints
+    # via
+    #   scikit-fingerprints
+    #   shap
 numpy==1.26.4
     # via
     #   baybe (pyproject.toml)
@@ -449,7 +461,9 @@ numpy==1.26.4
     #   e3fp
     #   formulaic
     #   h5py
+    #   imageio
     #   lifelines
+    #   lime
     #   matplotlib
     #   mordredcommunity
     #   ngboost
@@ -465,44 +479,47 @@ numpy==1.26.4
     #   pyro-ppl
     #   rdkit
     #   scikit-fingerprints
+    #   scikit-image
     #   scikit-learn
     #   scikit-learn-extra
     #   scipy
     #   seaborn
+    #   shap
     #   streamlit
+    #   tifffile
     #   types-seaborn
     #   xarray
     #   xyzpy
-nvidia-cublas-cu12==12.1.3.1 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cublas-cu12==12.1.3.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via
     #   nvidia-cudnn-cu12
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-cuda-cupti-cu12==12.1.105 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cuda-cupti-cu12==12.1.105 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cuda-nvrtc-cu12==12.1.105 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cuda-nvrtc-cu12==12.1.105 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cuda-runtime-cu12==12.1.105 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cuda-runtime-cu12==12.1.105 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cudnn-cu12==8.9.2.26 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cudnn-cu12==8.9.2.26 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cufft-cu12==11.0.2.54 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cufft-cu12==11.0.2.54 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-curand-cu12==10.3.2.106 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-curand-cu12==10.3.2.106 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cusolver-cu12==11.4.5.107 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cusolver-cu12==11.4.5.107 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-cusparse-cu12==12.1.0.106 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-cusparse-cu12==12.1.0.106 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-nccl-cu12==2.20.5 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-nccl-cu12==2.20.5 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
-nvidia-nvjitlink-cu12==12.5.82 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-nvjitlink-cu12==12.5.82 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via
     #   nvidia-cusolver-cu12
     #   nvidia-cusparse-cu12
-nvidia-nvtx-cu12==12.1.105 ; platform_machine == 'x86_64' and platform_system == 'Linux'
+nvidia-nvtx-cu12==12.1.105 ; platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
 onnx==1.16.1
     # via
@@ -566,6 +583,7 @@ packaging==24.1
     #   jupyterlab
     #   jupyterlab-server
     #   jupytext
+    #   lazy-loader
     #   matplotlib
     #   mordredcommunity
     #   nbconvert
@@ -576,7 +594,9 @@ packaging==24.1
     #   plotly
     #   pyproject-api
     #   pytest
+    #   scikit-image
     #   setuptools-scm
+    #   shap
     #   sphinx
     #   streamlit
     #   tox
@@ -592,6 +612,7 @@ pandas==2.2.2
     #   pandas-flavor
     #   scikit-fingerprints
     #   seaborn
+    #   shap
     #   streamlit
     #   xarray
     #   xyzpy
@@ -612,8 +633,10 @@ pexpect==4.9.0 ; sys_platform != 'emscripten' and sys_platform != 'win32'
 pillow==10.4.0
     # via
     #   baybe (pyproject.toml)
+    #   imageio
     #   matplotlib
     #   rdkit
+    #   scikit-image
     #   streamlit
 pip==24.1.2
     # via pip-api
@@ -784,13 +807,17 @@ s3transfer==0.10.4
     # via boto3
 scikit-fingerprints==1.9.0
     # via baybe (pyproject.toml)
+scikit-image==0.25.0
+    # via lime
 scikit-learn==1.5.1
     # via
     #   baybe (pyproject.toml)
     #   gpytorch
+    #   lime
     #   ngboost
     #   scikit-fingerprints
     #   scikit-learn-extra
+    #   shap
     #   skl2onnx
 scikit-learn-extra==0.3.0
     # via baybe (pyproject.toml)
@@ -805,11 +832,14 @@ scipy==1.14.0
     #   formulaic
     #   gpytorch
     #   lifelines
+    #   lime
     #   linear-operator
     #   ngboost
     #   scikit-fingerprints
+    #   scikit-image
     #   scikit-learn
     #   scikit-learn-extra
+    #   shap
 sdaxen-python-utilities==0.1.5
     # via e3fp
 seaborn==0.13.2
@@ -822,6 +852,8 @@ setuptools==71.1.0
     #   setuptools-scm
 setuptools-scm==8.1.0
     # via baybe (pyproject.toml)
+shap==0.46.0
+    # via baybe (pyproject.toml)
 six==1.16.0
     # via
     #   asttokens
@@ -833,6 +865,8 @@ six==1.16.0
     #   rfc3339-validator
 skl2onnx==1.17.0
     # via baybe (pyproject.toml)
+slicer==0.0.8
+    # via shap
 smart-open==7.0.5
     # via e3fp
 smmap==5.0.1
@@ -889,7 +923,7 @@ sympy==1.13.1
     # via
     #   onnxruntime
     #   torch
-tbb==2021.13.0 ; platform_system == 'Windows'
+tbb==2021.13.0 ; sys_platform == 'win32'
     # via mkl
 tenacity==8.5.0
     # via
@@ -902,6 +936,8 @@ terminado==0.18.1
     #   jupyter-server-terminals
 threadpoolctl==3.5.0
     # via scikit-learn
+tifffile==2024.12.12
+    # via scikit-image
 tinycss2==1.3.0
     # via nbconvert
 tokenize-rt==6.1.0
@@ -950,9 +986,11 @@ tox-uv==1.9.1
 tqdm==4.66.4
     # via
     #   huggingface-hub
+    #   lime
     #   ngboost
     #   pyro-ppl
     #   scikit-fingerprints
+    #   shap
     #   xyzpy
 traitlets==5.14.3
     # via
@@ -970,7 +1008,7 @@ traitlets==5.14.3
     #   nbclient
     #   nbconvert
     #   nbformat
-triton==2.3.1 ; python_full_version < '3.12' and platform_machine == 'x86_64' and platform_system == 'Linux'
+triton==2.3.1 ; python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'
     # via torch
 typeguard==2.13.3
     # via
@@ -1013,7 +1051,7 @@ virtualenv==20.26.3
     # via
     #   pre-commit
     #   tox
-watchdog==4.0.1 ; platform_system != 'Darwin'
+watchdog==4.0.1 ; sys_platform != 'darwin'
     # via streamlit
 wcwidth==0.2.13
     # via prompt-toolkit

CHANGELOG.md

@@ -10,6 +10,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   the corresponding parameter/target column labels
 
 ### Added
+- Optional `insights` dependency group
+- SHAP explanations via the new `SHAPInsight` class
 - `allow_missing` and `allow_extra` keyword arguments to `Objective.transform`
 - Example for a traditional mixture
 - `add_noise_to_perturb_degenerate_rows` utility

CONTRIBUTORS.md

@@ -30,3 +30,5 @@
   `scikit-fingerprints` support
 - Fabian Liebig (Merck KGaA, Darmstadt, Germany):\
   Benchmarking structure and persistence capabilities for benchmarking results
+- Alexander Wieczorek (Swiss Federal Institute for Materials Science and Technology, Dübendorf, Switzerland):\
+  SHAP explainers for insights

README.md

@@ -30,10 +30,15 @@
 The **Bay**esian **B**ack **E**nd (**BayBE**) is a general-purpose toolbox for Bayesian Design
 of Experiments, focusing on additions that enable real-world experimental campaigns.
 
-Besides functionality to perform a typical recommend-measure loop, BayBE's highlights are:
-- ✨ Custom parameter encodings: Improve your campaign with domain knowledge
+## 🔋 Batteries Included
+Besides its core functionality to perform a typical recommend-measure loop, BayBE
+offers a range of ✨**built‑in features**✨ crucial for real-world use cases.
+The following provides a non-comprehensive overview:
+
+- 🛠️ Custom parameter encodings: Improve your campaign with domain knowledge
 - 🧪 Built-in chemical encodings: Improve your campaign with chemical knowledge
 - 🎯 Single and multiple targets with min, max and match objectives
+- 🔍 Insights: Easily analyze feature importance and model behavior
 - 🎭 Hybrid (mixed continuous and discrete) spaces
 - 🚀 Transfer learning: Mix data from multiple campaigns and accelerate optimization
 - 🎰 Bandit models: Efficiently find the best among many options in noisy environments (e.g. A/B Testing)
@@ -296,7 +301,8 @@ The available groups are:
 - `lint`: Required for linting and formatting.
 - `mypy`: Required for static type checking.
 - `onnx`: Required for using custom surrogate models in [ONNX format](https://onnx.ai).
-- `polars`: Required for optimized search space construction via [Polars](https://docs.pola.rs/)
+- `polars`: Required for optimized search space construction via [Polars](https://docs.pola.rs/).
+- `insights`: Required for built-in model and campaign analysis (e.g. using [SHAP](https://shap.readthedocs.io/)).
 - `simulation`: Enabling the [simulation](https://emdgroup.github.io/baybe/stable/_autosummary/baybe.simulation.html) module.
 - `test`: Required for running the tests.
 - `benchmarking`: Required for running the benchmarking module.

baybe/_optional/info.py

@@ -25,11 +25,13 @@ def exclude_sys_path(path: str, /):  # noqa: DOC402, DOC404
 # Individual packages
 with exclude_sys_path(os.getcwd()):
     FLAKE8_INSTALLED = find_spec("flake8") is not None
+    LIME_INSTALLED = find_spec("lime") is not None
     ONNX_INSTALLED = find_spec("onnxruntime") is not None
     POLARS_INSTALLED = find_spec("polars") is not None
     PRE_COMMIT_INSTALLED = find_spec("pre_commit") is not None
     PYDOCLINT_INSTALLED = find_spec("pydoclint") is not None
     RUFF_INSTALLED = find_spec("ruff") is not None
+    SHAP_INSTALLED = find_spec("shap") is not None
     SKFP_INSTALLED = find_spec("skfp") is not None  # scikit-fingerprints
     STREAMLIT_INSTALLED = find_spec("streamlit") is not None
     XYZPY_INSTALLED = find_spec("xyzpy") is not None
@@ -44,6 +46,7 @@ def exclude_sys_path(path: str, /):  # noqa: DOC402, DOC404
 
 # Information on whether all required packages for certain functionality are available
 CHEM_INSTALLED = SKFP_INSTALLED
+INSIGHTS_INSTALLED = SHAP_INSTALLED and LIME_INSTALLED
 LINT_INSTALLED = all(
     (
         FLAKE8_INSTALLED,

baybe/_optional/insights.py

@@ -0,0 +1,16 @@
+"""Optional import for the insights subpackage."""
+
+from baybe.exceptions import OptionalImportError
+
+try:
+    import shap
+except ModuleNotFoundError as ex:
+    raise OptionalImportError(
+        "Explainer functionality is unavailable because 'insights' is not installed."
+        " Consider installing BayBE with 'insights' dependency, e.g. via "
+        "`pip install baybe[insights]`."
+    ) from ex
+
+__all__ = [
+    "shap",
+]