Merge pull request #126 from takeno1995/main

add PIMS

package/samplers/gp_pims/LICENCE

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+MIT License
+
+Copyright (c) 2024 Shion TAKENO
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

package/samplers/gp_pims/README.md

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+---
+author: Shion TAKENO
+title: Gaussian-Process Probability of Improvement from Maximum of Sample Path Sampler
+description: This sampler searches for each trial based on Probability of Improvement from Maximum of Sample Path using Gaussian process.
+tags: [sampler, Gaussian process]
+optuna_versions: [3.6.1]
+license: MIT License
+---
+
+<!--
+This is an example of the frontmatters.
+All columns must be string.
+You can omit quotes when value types are not ambiguous.
+For tags, a package placed in
+- package/samplers/ must include the tag "sampler"
+- package/visualilzation/ must include the tag "visualization"
+- package/pruners/ must include the tag "pruner"
+respectively.
+
+---
+author: Optuna team
+title: My Sampler
+description: A description for My Sampler.
+tags: [sampler, 2nd tag for My Sampler, 3rd tag for My Sampler]
+optuna_versions: [3.6.1]
+license: "MIT License"
+---
+-->
+
+## Class or Function Names
+
+- PIMSSampler
+
+## Installation
+
+```shell
+$ pip install -r requirements.txt
+```
+
+## Example
+
+Please see example.py.
+
+## Others
+
+### Reference
+
+Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi,
+Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds,
+Proceedings of the 41st International Conference on Machine Learning, PMLR 235:47510-47534, 2024.
+
+### Bibtex
+
+```
+
+@InProceedings{pmlr-v235-takeno24a,
+  title = 	 {Posterior Sampling-Based {B}ayesian Optimization with Tighter {B}ayesian Regret Bounds},
+  author =       {Takeno, Shion and Inatsu, Yu and Karasuyama, Masayuki and Takeuchi, Ichiro},
+  booktitle = 	 {Proceedings of the 41st International Conference on Machine Learning},
+  pages = 	 {47510--47534},
+  year = 	 {2024},
+  editor = 	 {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix},
+  volume = 	 {235},
+  series = 	 {Proceedings of Machine Learning Research},
+  month = 	 {21--27 Jul},
+  publisher =    {PMLR},
+  pdf = 	 {https://raw.githubusercontent.com/mlresearch/v235/main/assets/takeno24a/takeno24a.pdf},
+  url = 	 {https://proceedings.mlr.press/v235/takeno24a.html}
+}
+
+```

package/samplers/gp_pims/__init__.py

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+from .sampler import PIMSSampler
+
+
+__all__ = ["PIMSSampler"]

package/samplers/gp_pims/example.py

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+from __future__ import annotations
+
+import numpy as np
+import optuna
+import optunahub
+
+
+def f(x: np.ndarray) -> float:
+    return -np.sin(3 * np.sum(x**2)) - np.sum(x**2) ** 2 + 0.7 * np.sum(x**2)
+
+
+if __name__ == "__main__":
+    mod = optunahub.load_module(
+        package="samplers/gp_pims",
+    )
+
+    PIMSSampler = mod.PIMSSampler
+
+    def objective(trial: optuna.Trial) -> float:
+        x = trial.suggest_float("x", 0, 1)
+        y = trial.suggest_float("y", 0, 1)
+        return f(np.asarray([x, y]))
+
+    search_space = {
+        "x": optuna.distributions.FloatDistribution(0, 1),
+        "y": optuna.distributions.FloatDistribution(0, 1),
+    }
+
+    kernel_bounds = np.array([[1e-3, 1e-3], [1e3, 1e3]])
+    sampler = PIMSSampler(search_space=search_space, kernel_bounds=kernel_bounds)
+    study = optuna.create_study(sampler=sampler, direction="maximize")
+    # study = optuna.create_study(sampler=sampler)
+    study.optimize(objective, n_trials=20)
+    # optuna.visualization.plot_optimization_history(study)
+
+    fig = optuna.visualization.plot_optimization_history(study)
+    fig.write_image("optuna_history.png")

package/samplers/gp_pims/requirements.txt

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+contourpy==1.1.0
+cycler==0.11.0
+Cython==3.0.0
+decorator==5.1.1
+fonttools==4.42.0
+GPy==1.13.1
+importlib-resources==6.0.1
+kiwisolver==1.4.4
+matplotlib==3.7.2
+numpy==1.26.3
+packaging==23.1
+paramz==0.9.6
+Pillow==10.0.0
+pyparsing==3.0.9
+python-dateutil==2.8.2
+scipy==1.11.1
+six==1.16.0
+zipp==3.16.2