Add ci

.github/workflows/bayesopt_interfaces.yaml

@@ -0,0 +1,57 @@
+on:
+  push:
+  pull_request:
+
+jobs:
+  tests_physbo_interface:
+    name: Run tests for physbo_interface
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        python-version: [3.8]
+        os: [ubuntu-20.04]
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip setuptools
+          pip install pytest
+      - name: Install bayesopt_interfaces
+        run: |
+          pip install ml_interfaces/bayesopt_interfaces
+      - name: Run pytest
+        run: pytest -v ml_interfaces/bayesopt_interfaces/tests/test_physbo_interface.py
+
+  tests_combo_interface:
+    name: Run tests for combo_interface
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-20.04]
+    container:
+        image: python:2.7.18-buster
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip setuptools
+          pip install pytest cython numpy
+      - name: Install combo
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          git clone https://${GITHUB_ACTOR}:${GITHUB_TOKEN}@github.com/tsudalab/combo.git
+          cd combo
+          python setup.py install
+      - name: Install bayesopt_interfaces
+        run: |
+          pip install ml_interfaces/bayesopt_interfaces
+      - name: Run pytest
+        run: |
+          pytest -v ml_interfaces/bayesopt_interfaces/tests/test_combo_interface.py

ml_interfaces/bayesopt_interfaces/.gitignore

@@ -1,2 +1,6 @@
 *.~
-*.pyc
+*.pyc
+examples/data/chosen_actions.csv
+examples/data/result
+tests/data/chosed_actions.csv
+tests/data/result

ml_interfaces/bayesopt_interfaces/bayesopt_if/combo_interface.py

@@ -20,7 +20,7 @@
 
 
 class ComboInterface():
-    def __init__(self, bayesopt, candidates_path='candidates.csv', policy_load_dir='.', policy_save_dir='.', use_saved_policy=False, search_score='PI'):
+    def __init__(self, bayesopt, candidates_path='candidates.csv', policy_load_dir='.', policy_save_dir='.', use_saved_policy=False, visualize=True, search_score='PI'):
         self.data = None
         self.X = None
         self.actions = None
@@ -32,6 +32,7 @@ def __init__(self, bayesopt, candidates_path='candidates.csv', policy_load_dir='
         self.policy_load_dir = policy_load_dir
         self.policy_save_dir = policy_save_dir
         self.use_saved_policy = use_saved_policy
+        self.visualize = visualize
         self.search_mode = 0  # 0: random search, 1: bayes
         self.search_score = search_score  # score: PI, EI, TS
         self.is_write_completed = False
@@ -54,10 +55,11 @@ def start_bayesopt(self):
             self.generate_policy()
 
         # for visualization
-        self.fig, self.ax = plt.subplots(2, 1, tight_layout=True)  # avoid overlap of labels
+        if self.visualize:
+            self.fig, self.ax = plt.subplots(2, 1, tight_layout=True)  # avoid overlap of labels
 
-        # visualize
-        self.visualize()
+            # visualize
+            self.visualize()
 
 
     def load_dataset(self):
@@ -169,7 +171,8 @@ def save_data(self, policy_save_dir='.'):
         self.save_policy(self.policy_save_dir)
         self.save_candidates_and_actions(self.policy_save_dir)  # csv
         self.save_candidates_with_scores(self.policy_save_dir)  # csv
-        self.save_plt(self.policy_save_dir)
+        if self.visualize:
+            self.save_plt(self.policy_save_dir)
 
 
     def save_policy(self, policy_save_dir='.'):

ml_interfaces/bayesopt_interfaces/bayesopt_if/physbo_interface.py

@@ -10,7 +10,7 @@
 
 
 class PhysboInterface(ComboInterface):
-    def __init__(self, candidates_path='candidates.csv', policy_load_dir='.', policy_save_dir='.', use_saved_policy=False, search_score='PI'):
+    def __init__(self, candidates_path='candidates.csv', policy_load_dir='.', policy_save_dir='.', use_saved_policy=False, visualize=True, search_score='PI'):
         self.candidates_path = candidates_path
         self.policy_load_dir = policy_load_dir
         self.policy_save_dir = policy_save_dir
@@ -24,6 +24,7 @@ def __init__(self, candidates_path='candidates.csv', policy_load_dir='.', policy
                          self.policy_load_dir,
                          self.policy_save_dir,
                          self.use_saved_policy,
+                         self.visualize,
                          self.search_score)  # python3 description
 
 

ml_interfaces/bayesopt_interfaces/examples/data/candidates.csv

@@ -0,0 +1,21 @@
+p1,p2,p3,p4,y
+180,0,100,200,
+180,0,200,200,
+180,0,300,200,
+180,0,400,200,
+180,100,100,200,
+180,100,200,200,
+180,100,300,200,
+180,100,400,200,
+180,200,100,200,
+180,200,200,200,
+180,200,300,200,
+180,200,400,200,
+180,300,100,200,
+180,300,200,200,
+180,300,300,200,
+180,300,400,200,
+180,400,100,200,
+180,400,200,200,
+180,400,300,200,
+180,400,400,200,

ml_interfaces/bayesopt_interfaces/examples/data/results.csv

@@ -0,0 +1,21 @@
+y
+0.001
+0.401
+0.398
+0.305
+0.001
+0.352
+0.350
+0.237
+0.350
+0.374
+0.288
+0.262
+0.290
+0.250
+0.245
+0.204
+0.216
+0.129
+0.151
+0.091

ml_interfaces/bayesopt_interfaces/examples/run_combo.py

@@ -0,0 +1,38 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+import os
+import random
+import sys
+
+import combo
+from bayesopt_if.combo_interface import ComboInterface
+
+
+def main():
+    # dir setting
+    candidates_path  = './data/candidates.csv'
+    policy_load_dir = './data/load'
+    policy_save_dir = './data/result'
+
+    # Generate combo
+    ci = ComboInterface(combo, candidates_path, policy_load_dir, policy_save_dir, use_saved_policy=False)
+    ci.start_bayesopt()
+
+    # Write combo operation below
+    ## Following procedure is important for correct generation of result data.
+    ## search -> write(and update -> visualize)
+    for i in range(1):
+        ci.search_next_param_random()
+        ci.write_result(random.random())  # write result
+    for i in range(1):
+        ci.search_next_param_bayes()
+        ci.write_result(random.random())  # write result
+
+    raw_input('Press enter to save and finish\n')
+
+    ci.save_data(policy_save_dir)
+
+
+if __name__ == '__main__':
+    main()

ml_interfaces/bayesopt_interfaces/examples/run_physbo.py

@@ -0,0 +1,50 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import csv
+import os
+import sys
+
+from bayesopt_if.physbo_interface import PhysboInterface
+
+
+def get_data_from_result_list(index):
+    with open('./data/results.csv') as f:
+        reader = csv.reader(f)
+        l = [row for row in reader]
+
+    return float(l[index+1][0])
+
+
+def main():
+    # dir setting
+    candidates_path  = './data/candidates.csv'
+    policy_load_dir = './data/load'
+    policy_save_dir = './data/result'
+
+    # Generate physbo
+    pi = PhysboInterface(candidates_path, policy_load_dir, policy_save_dir, use_saved_policy=False, search_score='EI')
+    pi.start_bayesopt()
+
+    # Procedure of search and register data to PHYSBO
+    # - Following procedure is important for correct generation of result data.
+    # - search -> write (and update -> visualize)
+
+    # Search with Random search for initial step
+    for i in range(3):
+        pi.search_next_param_random()
+        result = get_data_from_result_list(pi.get_next_index())  # get result/evaluation data from experiment. (Result list is used for this test program).
+        pi.write_result(result)  # write result to PHYSBO
+    # Search with Bayesian optimization
+    for i in range(3):
+        pi.search_next_param_bayes()
+        result = get_data_from_result_list(pi.get_next_index())
+        pi.write_result(result)
+
+    input('Press enter to save and finish\n')
+
+    pi.save_data(policy_save_dir)
+
+
+if __name__ == '__main__':
+    main()

ml_interfaces/bayesopt_interfaces/requirements.txt

@@ -1,2 +1,4 @@
 matplotlib
+pandas
 physbo
+pyyaml

ml_interfaces/bayesopt_interfaces/setup.py

@@ -9,7 +9,7 @@ def _requires_from_file(filename):
     version='0.1.0',
     author='Yuki Asano',
     author_email='[email protected]',
-    description='',
+    description='Interface for Bayesian Optimization',
     packages=find_packages(),
     install_requires = _requires_from_file('requirements.txt')
 )

ml_interfaces/bayesopt_interfaces/tests/data/candidates-correct.csv

@@ -0,0 +1,21 @@
+p1,p2,p3,p4,y
+180,0,100,200,0.001
+180,0,200,200,0.401
+180,0,300,200,0.398
+180,0,400,200,0.305
+180,100,100,200,0.001
+180,100,200,200,0.352
+180,100,300,200,0.35
+180,100,400,200,0.237
+180,200,100,200,0.35
+180,200,200,200,0.374
+180,200,300,200,0.288
+180,200,400,200,0.262
+180,300,100,200,0.29
+180,300,200,200,0.25
+180,300,300,200,0.245
+180,300,400,200,0.204
+180,400,100,200,0.216
+180,400,200,200,0.129
+180,400,300,200,0.151
+180,400,400,200,0.091

ml_interfaces/bayesopt_interfaces/tests/test_combo_interface.py

@@ -1,38 +1,52 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
+import csv
+import filecmp
 import os
 import random
 import sys
 
 import combo
 from bayesopt_if.combo_interface import ComboInterface
 
+file_dir = os.path.dirname(__file__)
+data_dir = os.path.join(file_dir, 'data')
 
-def main():
+
+def get_data_from_result_list(index):
+    results_path = os.path.join(data_dir, 'results.csv')
+    with open(results_path) as f:
+        reader = csv.reader(f)
+        l = [row for row in reader]
+
+    return float(l[index+1][0])
+
+
+def test_combo_interface():
     # dir setting
-    candidates_path  = './data/candidates.csv'
-    policy_load_dir = './data/load'
-    policy_save_dir = './data/result'
+    candidates_path  = os.path.join(data_dir, 'candidates.csv')
+    correct_candidates_path = os.path.join(data_dir, 'candidates-correct.csv')
+    policy_load_dir = os.path.join(data_dir, 'load')
+    policy_save_dir = os.path.join(data_dir, 'result')
 
     # Generate combo
-    ci = ComboInterface(combo, candidates_path, policy_load_dir, policy_save_dir, use_saved_policy=False)
+    ci = ComboInterface(combo, candidates_path, policy_load_dir, policy_save_dir, use_saved_policy=False, visualize=False)
     ci.start_bayesopt()
 
     # Write combo operation below
     ## Following procedure is important for correct generation of result data.
     ## search -> write(and update -> visualize)
-    for i in range(1):
+    for i in range(3):
         ci.search_next_param_random()
-        ci.write_result(random.random())  # write result
-    for i in range(1):
+        result = get_data_from_result_list(ci.get_next_index())  # get result/evaluation data from experiment. (Result list is used for this test program).
+        ci.write_result(result)  # write result
+    for i in range(17):
         ci.search_next_param_bayes()
-        ci.write_result(random.random())  # write result
-
-    raw_input('Press enter to save and finish\n')
+        result = get_data_from_result_list(ci.get_next_index())
+        ci.write_result(result)
 
+    #raw_input('Press enter to save and finish\n')
     ci.save_data(policy_save_dir)
 
-
-if __name__ == '__main__':
-    main()
+    assert filecmp.cmp(candidates_path, correct_candidates_path)