Merge pull request #5 from jungtaekkim/0.2.0

0.2.0
jungtaekkim · Mar 12, 2024 · 3df1f31 · 3df1f31
2 parents 5eaf53d + dbb1196
commit 3df1f31
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diff --git a/.github/workflows/pytest.yml b/.github/workflows/pytest.yml
@@ -7,24 +7,22 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - '3.6'
           - '3.7'
           - '3.8'
           - '3.9'
           - '3.10'
           - '3.11'
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
       - uses: actions/setup-python@v2
         with:
           python-version: ${{ matrix.python-version }}
-      - name: Install dependencies
+      - name: Install this project and its dependencies
         run: |
-          python -m pip install --upgrade pip setuptools
-          pip install pytest
-          pip install scipy
+          pip install --upgrade pip
+          pip install .[dev]
+          pip list
       - name: Run pytest
         run: |
-          pip install .
           pytest
diff --git a/LICENSE b/LICENSE
@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2019-2023 Jungtaek Kim
+Copyright (c) 2019-2024 Jungtaek Kim
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

diff --git a/README.md b/README.md
@@ -1,9 +1,9 @@
 <p align="center">
-<img src="https://github.com/jungtaekkim/bayeso/blob/main/docs/_static/assets/logo_bayeso_capitalized.svg" width="400" />
+<img src="https://raw.githubusercontent.com/jungtaekkim/bayeso/main/docs/_static/assets/logo_bayeso_capitalized.svg" width="400" />
 </p>
 
 # BayesO Benchmarks: Benchmark Functions for Bayesian Optimization
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7577331.svg)](https://doi.org/10.5281/zenodo.7577331)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7577330.svg)](https://doi.org/10.5281/zenodo.7577330)
 [![Build Status](https://github.com/jungtaekkim/bayeso-benchmarks/actions/workflows/pytest.yml/badge.svg)](https://github.com/jungtaekkim/bayeso-benchmarks/actions/workflows/pytest.yml)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
@@ -21,42 +21,36 @@ You can choose one of three installation options.
 To install the released version in PyPI repository, command it.
 
 ```shell
-$ pip install bayeso-benchmarks
+pip install bayeso-benchmarks
 ```
 
 * Using source code (for developer installation)
 
-To install `bayeso-benchmarks` from source code, command
+To install `bayeso-benchmarks` from source code, command the following in the `bayeso-benchmarks` root.
 
 ```shell
-$ pip install .
+pip install .
 ```
-in the `bayeso-benchmarks` root.
 
 * Using source code (for editable development mode)
 
-To use editable development mode, command
+To use editable development mode, command the following in the `bayeso-benchmarks` root.
 
 ```shell
-$ pip install -r requirements.txt
-$ python setup.py develop
+pip install -e .
 ```
-in the `bayeso-benchmarks` root.
+
+If you want to install the packages required for development, you can simply add `[dev]`.
+For example, `pip install .[dev]` or `pip install -e .[dev]`.
 
 * Uninstallation
 
 If you would like to uninstall `bayeso-benchmarks`, command it.
 
 ```shell
-$ pip uninstall bayeso-benchmarks
+pip uninstall bayeso-benchmarks
 ```
 
-## Required Packages
-Mandatory pacakges are inlcuded in `requirements.txt`.
-The following `requirements` files include the package list, the purpose of which is described as follows.
-
-* `requirements-dev.txt`: It is for developing the `bayeso-benchmarks` package.
-
 ## Simple Example
 A simple example on Branin function is shown below.
 ```python
@@ -71,5 +65,17 @@ Y = obj_fun.output(X)
 Y_noise = obj_fun.output_gaussian_noise(X)
 ```
 
+## Citation
+```
+@misc{KimJ2023software,
+    author={Kim, Jungtaek},
+    title={{BayesO Benchmarks}: Benchmark Functions for {Bayesian} Optimization},
+    doi={10.5281/zenodo.7577330},
+    url={https://github.com/jungtaekkim/bayeso-benchmarks},
+    howpublished={\url{https://doi.org/10.5281/zenodo.7577330}},
+    year={2023}
+}
+```
+
 ## License
 [MIT License](LICENSE)
diff --git a/bayeso_benchmarks/__init__.py b/bayeso_benchmarks/__init__.py
@@ -1,10 +1,10 @@
 #
-# author: Jungtaek Kim (jtkim@postech.ac.kr)
-# last updated: January 6, 2023
+# author: Jungtaek Kim (jungtaek.kim.mail@gmail.com)
+# last updated: January 27, 2023
 #
 
 
-__version__ = '0.1.7'
+__version__ = '0.2.0'
 
 
 from bayeso_benchmarks.inf_dim_ackley import Ackley

diff --git a/bayeso_benchmarks/benchmark_base.py b/bayeso_benchmarks/benchmark_base.py
@@ -1,5 +1,5 @@
 #
-# author: Jungtaek Kim (jtkim@postech.ac.kr)
+# author: Jungtaek Kim (jungtaek.kim.mail@gmail.com)
 # last updated: December 13, 2022
 #
 

diff --git a/bayeso_benchmarks/four_dim_colville.py b/bayeso_benchmarks/four_dim_colville.py
@@ -42,7 +42,4 @@ def __init__(self, seed=None):
         global_minimum = 0.0
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Colville, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_ackley.py b/bayeso_benchmarks/inf_dim_ackley.py
@@ -40,7 +40,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Ackley, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_cosines.py b/bayeso_benchmarks/inf_dim_cosines.py
@@ -33,7 +33,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Cosines, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_griewank.py b/bayeso_benchmarks/inf_dim_griewank.py
@@ -39,7 +39,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Griewank, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_levy.py b/bayeso_benchmarks/inf_dim_levy.py
@@ -45,7 +45,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Levy, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_rastrigin.py b/bayeso_benchmarks/inf_dim_rastrigin.py
@@ -37,7 +37,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Rastrigin, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_rosenbrock.py b/bayeso_benchmarks/inf_dim_rosenbrock.py
@@ -37,7 +37,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Rosenbrock, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_sphere.py b/bayeso_benchmarks/inf_dim_sphere.py
@@ -36,7 +36,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Sphere, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/inf_dim_zakharov.py b/bayeso_benchmarks/inf_dim_zakharov.py
@@ -42,7 +42,4 @@ def __init__(self, dim_problem, seed=None):
 
         function = lambda bx: fun_target(bx, dim_problem)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
-        except:
-            super(Zakharov, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, dim_problem=dim_problem, seed=seed)
diff --git a/bayeso_benchmarks/one_dim_constant.py b/bayeso_benchmarks/one_dim_constant.py
@@ -43,7 +43,4 @@ def __init__(self,
         global_minimum = constant
         function = lambda bx: fun_target(bx, dim_bx, constant)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Constant, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/one_dim_gramacyandlee2012.py b/bayeso_benchmarks/one_dim_gramacyandlee2012.py
@@ -1,6 +1,6 @@
 #
-# author: Jungtaek Kim (jtkim@postech.ac.kr)
-# last updated: February 8, 2021
+# author: Jungtaek Kim (jungtaek.kim.mail@gmail.com)
+# last updated: August 4, 2023
 #
 
 import numpy as np
@@ -28,12 +28,9 @@ def __init__(self, seed=None):
         assert bounds.shape[1] == 2
 
         global_minimizers = np.array([
-            [0.54856405],
+            [0.54856344],
         ])
-        global_minimum = -0.86901113
+        global_minimum = -0.8690111350
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(GramacyAndLee2012, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/one_dim_linear.py b/bayeso_benchmarks/one_dim_linear.py
@@ -47,7 +47,4 @@ def __init__(self,
             global_minimum = slope * bounds[0, 1]
         function = lambda bx: fun_target(bx, dim_bx, slope)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Linear, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/one_dim_step.py b/bayeso_benchmarks/one_dim_step.py
@@ -58,7 +58,4 @@ def __init__(self,
         global_minimum = np.min(step_values)
         function = lambda bx: fun_target(bx, dim_bx, steps, step_values)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Step, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/six_dim_hartmann6d.py b/bayeso_benchmarks/six_dim_hartmann6d.py
@@ -1,6 +1,6 @@
 #
-# author: Jungtaek Kim (jtkim@postech.ac.kr)
-# last updated: February 8, 2021
+# author: Jungtaek Kim (jungtaek.kim.mail@gmail.com)
+# last updated: August 4, 2023
 #
 
 import numpy as np
@@ -54,12 +54,9 @@ def __init__(self, seed=None):
         assert bounds.shape[1] == 2
 
         global_minimizers = np.array([
-            [0.20169, 0.150011, 0.476874, 0.275332, 0.311652, 0.6573],
+            [0.20168949, 0.15001068, 0.47687397, 0.27533242, 0.3116516, 0.65730054],
         ])
-        global_minimum = -3.322368
+        global_minimum = -3.3223680115
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Hartmann6D, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/three_dim_hartmann3d.py b/bayeso_benchmarks/three_dim_hartmann3d.py
@@ -1,6 +1,6 @@
 #
-# author: Jungtaek Kim (jtkim@postech.ac.kr)
-# last updated: February 8, 2021
+# author: Jungtaek Kim (jungtaek.kim.mail@gmail.com)
+# last updated: August 4, 2023
 #
 
 import numpy as np
@@ -51,12 +51,9 @@ def __init__(self, seed=None):
         assert bounds.shape[1] == 2
 
         global_minimizers = np.array([
-            [0.114614, 0.555649, 0.852547],
+            [0.11458889, 0.55564889, 0.85254698],
         ])
-        global_minimum = -3.86278
+        global_minimum = -3.8627797874
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Hartmann3D, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/two_dim_beale.py b/bayeso_benchmarks/two_dim_beale.py
@@ -34,7 +34,4 @@ def __init__(self, seed=None):
         global_minimum = 0.0
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Beale, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/two_dim_bohachevsky.py b/bayeso_benchmarks/two_dim_bohachevsky.py
@@ -34,7 +34,4 @@ def __init__(self, seed=None):
         global_minimum = 0.0
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Bohachevsky, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/two_dim_branin.py b/bayeso_benchmarks/two_dim_branin.py
@@ -1,6 +1,6 @@
 #
-# author: Jungtaek Kim (jtkim@postech.ac.kr)
-# last updated: February 8, 2021
+# author: Jungtaek Kim (jungtaek.kim.mail@gmail.com)
+# last updated: August 4, 2023
 #
 
 import numpy as np
@@ -53,10 +53,7 @@ def __init__(self,
             [np.pi, 2.275],
             [9.42478, 2.475],
         ])
-        global_minimum = 0.3978874
+        global_minimum = 0.3978873577
         function = lambda bx: fun_target(bx, dim_bx, a, b, c, r, s, t)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Branin, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/two_dim_bukin6.py b/bayeso_benchmarks/two_dim_bukin6.py
@@ -34,7 +34,4 @@ def __init__(self, seed=None):
         global_minimum = 0.0
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(Bukin6, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
diff --git a/bayeso_benchmarks/two_dim_dejong5.py b/bayeso_benchmarks/two_dim_dejong5.py
@@ -1,6 +1,6 @@
 #
-# author: Jungtaek Kim (jtkim@postech.ac.kr)
-# last updated: February 8, 2021
+# author: Jungtaek Kim (jungtaek.kim.mail@gmail.com)
+# last updated: August 4, 2023
 #
 
 import numpy as np
@@ -48,10 +48,7 @@ def __init__(self, seed=None):
             [-32.0400369, -31.9824982],
             [-31.98255954, -32.04163256],
         ])
-        global_minimum = 0.9980038
+        global_minimum = 0.9980038378
         function = lambda bx: fun_target(bx, dim_bx)
 
-        try:
-            super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
-        except:
-            super(DeJong5, self).__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)
+        super().__init__(dim_bx, bounds, global_minimizers, global_minimum, function, seed=seed)