From b53b8ea997d363c4f1fca1197683391e0872dad3 Mon Sep 17 00:00:00 2001
From: Chang-SHAO <101379630+Chang-SHAO@users.noreply.github.com>
Date: Thu, 4 Jul 2024 00:54:20 +0800
Subject: [PATCH 1/2] Add files via upload

---
 pypop7/optimizers/ds/test_powel.py | 14 ++++++++++++++
 1 file changed, 14 insertions(+)
 create mode 100644 pypop7/optimizers/ds/test_powel.py

diff --git a/pypop7/optimizers/ds/test_powel.py b/pypop7/optimizers/ds/test_powel.py
new file mode 100644
index 000000000..c050ed6c0
--- /dev/null
+++ b/pypop7/optimizers/ds/test_powel.py
@@ -0,0 +1,14 @@
+def test_optimize():
+    import numpy  # engine for numerical computing
+    from pypop7.benchmarks.base_functions import rosenbrock  # function to be minimized
+    from pypop7.optimizers.ds.powell import POWELL
+    problem = {'fitness_function': rosenbrock,  # to define problem arguments
+               'ndim_problem': 2,
+               'lower_boundary': -5.0 * numpy.ones((2,)),
+               'upper_boundary': 5.0 * numpy.ones((2,))}
+    options = {'max_function_evaluations': 5000,  # to set optimizer options
+               'seed_rng': 2022}
+    powel = POWELL(problem, options)  # to initialize the black-box optimizer class
+    results = powel.optimize()  # to run its optimization/evolution process
+    assert results['n_function_evaluations'] == 5000
+    assert results['best_so_far_y'] < 1.0

From 774c1aa94607577c01deeb3776bd06bd65d779f8 Mon Sep 17 00:00:00 2001
From: Chang-SHAO <101379630+Chang-SHAO@users.noreply.github.com>
Date: Thu, 4 Jul 2024 00:59:35 +0800
Subject: [PATCH 2/2] Add files via upload

---
 pypop7/optimizers/ds/test_cs.py  | 14 ++++++++++++++
 pypop7/optimizers/ds/test_gps.py | 14 ++++++++++++++
 pypop7/optimizers/ds/test_hj.py  | 14 ++++++++++++++
 pypop7/optimizers/ds/test_nm.py  | 14 ++++++++++++++
 4 files changed, 56 insertions(+)
 create mode 100644 pypop7/optimizers/ds/test_cs.py
 create mode 100644 pypop7/optimizers/ds/test_gps.py
 create mode 100644 pypop7/optimizers/ds/test_hj.py
 create mode 100644 pypop7/optimizers/ds/test_nm.py

diff --git a/pypop7/optimizers/ds/test_cs.py b/pypop7/optimizers/ds/test_cs.py
new file mode 100644
index 000000000..a006bdacb
--- /dev/null
+++ b/pypop7/optimizers/ds/test_cs.py
@@ -0,0 +1,14 @@
+def test_optimize():
+    import numpy  # engine for numerical computing
+    from pypop7.benchmarks.base_functions import rosenbrock  # function to be minimized
+    from pypop7.optimizers.ds.cs import CS
+    problem = {'fitness_function': rosenbrock,  # to define problem arguments
+               'ndim_problem': 2,
+               'lower_boundary': -5.0 * numpy.ones((2,)),
+               'upper_boundary': 5.0 * numpy.ones((2,))}
+    options = {'max_function_evaluations': 5000,  # to set optimizer options
+               'seed_rng': 2022}
+    cs = CS(problem, options)  # to initialize the black-box optimizer class
+    results = cs.optimize()  # to run its optimization/evolution process
+    assert results['n_function_evaluations'] == 5000
+    assert results['best_so_far_y'] < 1.0
diff --git a/pypop7/optimizers/ds/test_gps.py b/pypop7/optimizers/ds/test_gps.py
new file mode 100644
index 000000000..27df808fd
--- /dev/null
+++ b/pypop7/optimizers/ds/test_gps.py
@@ -0,0 +1,14 @@
+def test_optimize():
+    import numpy  # engine for numerical computing
+    from pypop7.benchmarks.base_functions import rosenbrock  # function to be minimized
+    from pypop7.optimizers.ds.gps import GPS
+    problem = {'fitness_function': rosenbrock,  # to define problem arguments
+               'ndim_problem': 2,
+               'lower_boundary': -5.0 * numpy.ones((2,)),
+               'upper_boundary': 5.0 * numpy.ones((2,))}
+    options = {'max_function_evaluations': 5000,  # to set optimizer options
+               'seed_rng': 2022}
+    gps = GPS(problem, options)  # to initialize the black-box optimizer class
+    results = gps.optimize()  # to run its optimization/evolution process
+    assert results['n_function_evaluations'] == 5000
+    assert results['best_so_far_y'] < 10.0
diff --git a/pypop7/optimizers/ds/test_hj.py b/pypop7/optimizers/ds/test_hj.py
new file mode 100644
index 000000000..124a97245
--- /dev/null
+++ b/pypop7/optimizers/ds/test_hj.py
@@ -0,0 +1,14 @@
+def test_optimize():
+    import numpy  # engine for numerical computing
+    from pypop7.benchmarks.base_functions import rosenbrock  # function to be minimized
+    from pypop7.optimizers.ds.hj import HJ
+    problem = {'fitness_function': rosenbrock,  # to define problem arguments
+               'ndim_problem': 2,
+               'lower_boundary': -5.0 * numpy.ones((2,)),
+               'upper_boundary': 5.0 * numpy.ones((2,))}
+    options = {'max_function_evaluations': 5000,  # to set optimizer options
+               'seed_rng': 2022}
+    hj = HJ(problem, options)  # to initialize the black-box optimizer class
+    results = hj.optimize()  # to run its optimization/evolution process
+    assert results['n_function_evaluations'] == 5000
+    assert results['best_so_far_y'] < 1.0
diff --git a/pypop7/optimizers/ds/test_nm.py b/pypop7/optimizers/ds/test_nm.py
new file mode 100644
index 000000000..c12ca28d5
--- /dev/null
+++ b/pypop7/optimizers/ds/test_nm.py
@@ -0,0 +1,14 @@
+def test_optimize():
+    import numpy  # engine for numerical computing
+    from pypop7.benchmarks.base_functions import rosenbrock  # function to be minimized
+    from pypop7.optimizers.ds.nm import NM
+    problem = {'fitness_function': rosenbrock,  # to define problem arguments
+               'ndim_problem': 2,
+               'lower_boundary': -5.0 * numpy.ones((2,)),
+               'upper_boundary': 5.0 * numpy.ones((2,))}
+    options = {'max_function_evaluations': 5000,  # to set optimizer options
+               'seed_rng': 2022}
+    nm = NM(problem, options)  # to initialize the black-box optimizer class
+    results = nm.optimize()  # to run its optimization/evolution process
+    assert results['n_function_evaluations'] == 5000
+    assert results['best_so_far_y'] < 1.0