diff --git a/requirements.txt b/requirements.txt index e69de29..7cf115b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -0,0 +1,8 @@ +pytest~=6.2.5 +setuptools==58.2.0 +numpy~=1.26.4 +pydot~=1.4.2 +empy~=3.3.4 +lark~=1.1.1 +scipy~=1.12.0 +scikit-learn~=1.4.0 \ No newline at end of file diff --git a/src/InteractionQuery/InteractionQuery/query_node.py b/src/InteractionQuery/InteractionQuery/query_node.py deleted file mode 100644 index b18cde9..0000000 --- a/src/InteractionQuery/InteractionQuery/query_node.py +++ /dev/null @@ -1,4 +0,0 @@ -import rclpy -from rclpy.node import Node - -from interaction_msgs.srv import Query \ No newline at end of file diff --git a/src/InteractionQuery/InteractionQuery/regular.py b/src/InteractionQuery/InteractionQuery/regular.py deleted file mode 100644 index 7349859..0000000 --- a/src/InteractionQuery/InteractionQuery/regular.py +++ /dev/null @@ -1,12 +0,0 @@ -class RegularQuery: - def __init__(self, regular, episode): - self.regular = int(regular) - self.counter = episode - - def query(self): - - if self.counter % self.regular == 0 and self.counter != 0: - return True - - else: - return False diff --git a/src/InteractionQuery/setup.cfg b/src/InteractionQuery/setup.cfg deleted file mode 100644 index 1c40041..0000000 --- a/src/InteractionQuery/setup.cfg +++ /dev/null @@ -1,4 +0,0 @@ -[develop] -script_dir=$base/lib/InteractionQuery -[install] -install_scripts=$base/lib/InteractionQuery diff --git a/src/ObjectiveFunctions/package.xml b/src/ObjectiveFunctions/package.xml deleted file mode 100644 index 9806cd4..0000000 --- a/src/ObjectiveFunctions/package.xml +++ /dev/null @@ -1,18 +0,0 @@ - - - - ObjectiveFunctions - 0.0.0 - TODO: Package description - niko - TODO: License declaration - - ament_copyright - ament_flake8 - ament_pep257 - python3-pytest - - - ament_python - - diff --git a/src/ObjectiveFunctions/setup.cfg b/src/ObjectiveFunctions/setup.cfg deleted file mode 100644 index 2c66535..0000000 --- a/src/ObjectiveFunctions/setup.cfg +++ /dev/null @@ -1,4 +0,0 @@ -[develop] -script_dir=$base/lib/ObjectiveFunctions -[install] -install_scripts=$base/lib/ObjectiveFunctions diff --git a/src/Optimizers/setup.cfg b/src/Optimizers/setup.cfg deleted file mode 100644 index 588328d..0000000 --- a/src/Optimizers/setup.cfg +++ /dev/null @@ -1,4 +0,0 @@ -[develop] -script_dir=$base/lib/Optimizers -[install] -install_scripts=$base/lib/Optimizers diff --git a/src/RepresentationModels/resource/RepresentationModels b/src/RepresentationModels/resource/RepresentationModels deleted file mode 100644 index e69de29..0000000 diff --git a/src/RepresentationModels/setup.cfg b/src/RepresentationModels/setup.cfg deleted file mode 100644 index 4b0d329..0000000 --- a/src/RepresentationModels/setup.cfg +++ /dev/null @@ -1,4 +0,0 @@ -[develop] -script_dir=$base/lib/RepresentationModels -[install] -install_scripts=$base/lib/RepresentationModels diff --git a/src/RepresentationModels/setup.py b/src/RepresentationModels/setup.py deleted file mode 100644 index a2bbff0..0000000 --- a/src/RepresentationModels/setup.py +++ /dev/null @@ -1,25 +0,0 @@ -from setuptools import find_packages, setup - -package_name = 'RepresentationModels' - -setup( - name=package_name, - version='0.0.0', - packages=find_packages(exclude=['test']), - data_files=[ - ('share/ament_index/resource_index/packages', - ['resource/' + package_name]), - ('share/' + package_name, ['package.xml']), - ], - install_requires=['setuptools'], - zip_safe=True, - maintainer='niko', - maintainer_email='nikolaus.feith@unileoben.ac.at', - description='TODO: Package description', - license='TODO: License declaration', - tests_require=['pytest'], - entry_points={ - 'console_scripts': [ - ], - }, -) diff --git a/src/RepresentationModels/test/test_copyright.py b/src/RepresentationModels/test/test_copyright.py deleted file mode 100644 index 97a3919..0000000 --- a/src/RepresentationModels/test/test_copyright.py +++ /dev/null @@ -1,25 +0,0 @@ -# Copyright 2015 Open Source Robotics Foundation, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from ament_copyright.main import main -import pytest - - -# Remove the `skip` decorator once the source file(s) have a copyright header -@pytest.mark.skip(reason='No copyright header has been placed in the generated source file.') -@pytest.mark.copyright -@pytest.mark.linter -def test_copyright(): - rc = main(argv=['.', 'test']) - assert rc == 0, 'Found errors' diff --git a/src/RepresentationModels/test/test_flake8.py b/src/RepresentationModels/test/test_flake8.py deleted file mode 100644 index 27ee107..0000000 --- a/src/RepresentationModels/test/test_flake8.py +++ /dev/null @@ -1,25 +0,0 @@ -# Copyright 2017 Open Source Robotics Foundation, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from ament_flake8.main import main_with_errors -import pytest - - -@pytest.mark.flake8 -@pytest.mark.linter -def test_flake8(): - rc, errors = main_with_errors(argv=[]) - assert rc == 0, \ - 'Found %d code style errors / warnings:\n' % len(errors) + \ - '\n'.join(errors) diff --git a/src/RepresentationModels/test/test_pep257.py b/src/RepresentationModels/test/test_pep257.py deleted file mode 100644 index b234a38..0000000 --- a/src/RepresentationModels/test/test_pep257.py +++ /dev/null @@ -1,23 +0,0 @@ -# Copyright 2015 Open Source Robotics Foundation, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from ament_pep257.main import main -import pytest - - -@pytest.mark.linter -@pytest.mark.pep257 -def test_pep257(): - rc = main(argv=['.', 'test']) - assert rc == 0, 'Found code style errors / warnings' diff --git a/src/interaction_msgs/srv/Query.srv b/src/interaction_msgs/srv/Query.srv index a543115..2d2ccc2 100644 --- a/src/interaction_msgs/srv/Query.srv +++ b/src/interaction_msgs/srv/Query.srv @@ -1,3 +1,6 @@ +# MODES: random:=0, regular:=1, improvement:=2 +uint16 modes + # random query float32 threshold @@ -7,9 +10,9 @@ uint16 current_episode # improvement query # float32 threshold -uint16 period +# uint16 frequency uint16 last_queried_episode -float32[] rewards +float32[] last_rewards --- bool interaction \ No newline at end of file diff --git a/src/InteractionQuery/InteractionQuery/__init__.py b/src/interaction_objective_function/interaction_objective_function/__init__.py similarity index 100% rename from src/InteractionQuery/InteractionQuery/__init__.py rename to src/interaction_objective_function/interaction_objective_function/__init__.py diff --git a/src/RepresentationModels/package.xml b/src/interaction_objective_function/package.xml similarity index 93% rename from src/RepresentationModels/package.xml rename to src/interaction_objective_function/package.xml index 0a5f94f..122c14e 100644 --- a/src/RepresentationModels/package.xml +++ b/src/interaction_objective_function/package.xml @@ -1,7 +1,7 @@ - RepresentationModels + interaction_objective_function 0.0.0 TODO: Package description niko diff --git a/src/InteractionQuery/resource/InteractionQuery b/src/interaction_objective_function/resource/interaction_objective_function similarity index 100% rename from src/InteractionQuery/resource/InteractionQuery rename to src/interaction_objective_function/resource/interaction_objective_function diff --git a/src/interaction_objective_function/setup.cfg b/src/interaction_objective_function/setup.cfg new file mode 100644 index 0000000..e6a1bf3 --- /dev/null +++ b/src/interaction_objective_function/setup.cfg @@ -0,0 +1,4 @@ +[develop] +script_dir=$base/lib/interaction_objective_function +[install] +install_scripts=$base/lib/interaction_objective_function diff --git a/src/Optimizers/setup.py b/src/interaction_objective_function/setup.py similarity index 92% rename from src/Optimizers/setup.py rename to src/interaction_objective_function/setup.py index a038bdf..27798b8 100644 --- a/src/Optimizers/setup.py +++ b/src/interaction_objective_function/setup.py @@ -1,6 +1,6 @@ from setuptools import find_packages, setup -package_name = 'Optimizers' +package_name = 'interaction_objective_function' setup( name=package_name, diff --git a/src/InteractionQuery/test/test_copyright.py b/src/interaction_objective_function/test/test_copyright.py similarity index 100% rename from src/InteractionQuery/test/test_copyright.py rename to src/interaction_objective_function/test/test_copyright.py diff --git a/src/InteractionQuery/test/test_flake8.py b/src/interaction_objective_function/test/test_flake8.py similarity index 100% rename from src/InteractionQuery/test/test_flake8.py rename to src/interaction_objective_function/test/test_flake8.py diff --git a/src/InteractionQuery/test/test_pep257.py b/src/interaction_objective_function/test/test_pep257.py similarity index 100% rename from src/InteractionQuery/test/test_pep257.py rename to src/interaction_objective_function/test/test_pep257.py diff --git a/src/ObjectiveFunctions/ObjectiveFunctions/__init__.py b/src/interaction_optimizers/interaction_optimizers/__init__.py similarity index 100% rename from src/ObjectiveFunctions/ObjectiveFunctions/__init__.py rename to src/interaction_optimizers/interaction_optimizers/__init__.py diff --git a/src/interaction_optimizers/interaction_optimizers/acquisition_function/__init__.py b/src/interaction_optimizers/interaction_optimizers/acquisition_function/__init__.py new file mode 100644 index 0000000..fa31491 --- /dev/null +++ b/src/interaction_optimizers/interaction_optimizers/acquisition_function/__init__.py @@ -0,0 +1,4 @@ +from .confidence_bounds import ConfidenceBounds +from .probability_of_improvement import ProbabilityOfImprovement +from .expected_improvement import ExpectedImprovement +from .preference_expected_improvement import PreferenceExpectedImprovement diff --git a/src/interaction_optimizers/interaction_optimizers/acquisition_function/confidence_bounds.py b/src/interaction_optimizers/interaction_optimizers/acquisition_function/confidence_bounds.py new file mode 100644 index 0000000..2c5c232 --- /dev/null +++ b/src/interaction_optimizers/interaction_optimizers/acquisition_function/confidence_bounds.py @@ -0,0 +1,31 @@ + +import numpy as np + + +class ConfidenceBounds: + def __init__(self, nr_weights, nr_samples=100, beta=1.2, seed=None, lower_bound=-1.0, upper_bound=1.0): + self.nr_weights = nr_weights + self.nr_samples = nr_samples + self.beta = beta # if beta negative => lower confidence bounds + self.lower_bound = lower_bound + self.upper_bound = upper_bound + self.seed = seed + + def __call__(self, gauss_process, _, seed=None): + # if seed is set for whole experiment + if self.seed is not None: + seed = self.seed + + # random generator + rng = np.random.default_rng(seed) + + # sample from the surrogate + x_test = rng.uniform(self.lower_bound, self.upper_bound, size=(self.nr_samples, self.nr_weights)) + mu, sigma = gauss_process.predict(x_test, return_std=True) + + # upper/lower confidence bounds + cb = mu + self.beta * sigma + + # get the best result and return it + idx = np.argmax(cb) + return x_test[idx, :] diff --git a/src/interaction_optimizers/interaction_optimizers/acquisition_function/expected_improvement.py b/src/interaction_optimizers/interaction_optimizers/acquisition_function/expected_improvement.py new file mode 100644 index 0000000..8bfb579 --- /dev/null +++ b/src/interaction_optimizers/interaction_optimizers/acquisition_function/expected_improvement.py @@ -0,0 +1,37 @@ + +import numpy as np +from scipy.stats import norm + + +class ExpectedImprovement: + def __init__(self, nr_weights, nr_samples=100, kappa=0.0, seed=None, lower_bound=-1.0, upper_bound=1.0): + self.nr_weights = nr_weights + self.nr_samples = nr_samples + self.kappa = kappa + self.lower_bound = lower_bound + self.upper_bound = upper_bound + self.seed = seed + + def __call__(self, gauss_process, x_observed, seed=None): + # if seed is set for whole experiment + if self.seed is not None: + seed = self.seed + + # random generator + rng = np.random.default_rng(seed) + + # get the best so far observed y + mu = gauss_process.predict(x_observed) + y_best = max(mu) + + # sample from surrogate + x_test = rng.uniform(self.lower_bound, self.upper_bound, size=(self.nr_samples, self.nr_weights)) + mu, sigma = gauss_process.predict(x_test, return_std=True) + + # expected improvement + z = (mu - y_best - self.kappa) / sigma + ei = (mu - y_best - self.kappa) * norm.cdf(z) + sigma * norm.pdf(z) + + # get the best result and return it + idx = np.argmax(ei) + return x_test[idx, :] diff --git a/src/interaction_optimizers/interaction_optimizers/acquisition_function/preference_expected_improvement.py b/src/interaction_optimizers/interaction_optimizers/acquisition_function/preference_expected_improvement.py new file mode 100644 index 0000000..bffcef3 --- /dev/null +++ b/src/interaction_optimizers/interaction_optimizers/acquisition_function/preference_expected_improvement.py @@ -0,0 +1,93 @@ + +import numpy as np +from scipy.stats import norm + + +class PreferenceExpectedImprovement: + def __init__(self, nr_dims, initial_variance, update_variance, nr_samples=100, + kappa=0.0, lower_bound=None, upper_bound=None, seed=None, fixed_dims=None): + self.nr_dims = nr_dims + + self.initial_variance = initial_variance + self.update_variance = update_variance + + self.nr_samples = nr_samples + self.kappa = kappa + + if lower_bound is None: + self.lower_bound = [-1.] * self.nr_dims + else: + self.lower_bound = lower_bound + + if upper_bound is None: + self.upper_bound = [1.] * self.nr_dims + else: + self.upper_bound = upper_bound + + self.seed = seed + + # initial proposal distribution + self.proposal_mean = np.zeros((nr_dims, 1)) + self.proposal_cov = np.diag(np.ones((nr_dims,)) * self.initial_variance) + + # fixed dimension for robot experiment + self.fixed_dims = fixed_dims + + def rejection_sampling(self, seed=None): + rng = np.random.default_rng(seed) + + samples = np.empty((0, self.nr_dims)) + while samples.shape[0] < self.nr_samples: + # sample from the multi variate gaussian distribution + sample = np.zeros((1, self.nr_dims)) + for i in range(self.nr_dims): + if i in self.fixed_dims: + sample[0, i] = self.fixed_dims[i] + else: + check = False + while not check: + sample[0, i] = rng.normal(self.proposal_mean[i], self.proposal_cov[i, i]) + if self.lower_bound[i] <= sample[0, i] <= self.upper_bound[i]: + check = True + + samples = np.append(samples, sample, axis=0) + + return samples + + def __call__(self, gauss_process, x_observed, seed=None): + # if seed is set for whole experiment + if self.seed is not None: + seed = self.seed + + # get the best so far observed y + mu = gauss_process.predict(x_observed) + y_best = max(mu) + + # sample from surrogate + x_test = self.rejection_sampling(seed) + mu, sigma = gauss_process.predict(x_test, return_std=True) + + # expected improvement + z = (mu - y_best - self.kappa) / sigma + ei = (mu - y_best - self.kappa) * norm.cdf(z) + sigma * norm.pdf(z) + + # get the best result and return it + idx = np.argmax(ei) + return x_test[idx, :] + + def update_proposal_model(self, preference_mean, preference_bool): + cov_diag = np.ones((self.nr_dims,)) * self.initial_variance + cov_diag[preference_bool] = self.update_variance + + preference_cov = np.diag(cov_diag) + + preference_mean = preference_mean.reshape(-1, 1) + + posterior_mean = np.linalg.inv(np.linalg.inv(self.proposal_cov) + np.linalg.inv(preference_cov))\ + .dot(np.linalg.inv(self.proposal_cov).dot(self.proposal_mean) + + np.linalg.inv(preference_cov).dot(preference_mean)) + + posterior_cov = np.linalg.inv(np.linalg.inv(self.proposal_cov) + np.linalg.inv(preference_cov)) + + self.proposal_mean = posterior_mean + self.proposal_cov = posterior_cov diff --git a/src/interaction_optimizers/interaction_optimizers/acquisition_function/probability_of_improvement.py b/src/interaction_optimizers/interaction_optimizers/acquisition_function/probability_of_improvement.py new file mode 100644 index 0000000..d4ccb2e --- /dev/null +++ b/src/interaction_optimizers/interaction_optimizers/acquisition_function/probability_of_improvement.py @@ -0,0 +1,37 @@ + +import numpy as np +from scipy.stats import norm + + +class ProbabilityOfImprovement: + def __init__(self, nr_weights, nr_samples=100, kappa=0.0, seed=None, lower_bound=-1.0, upper_bound=1.0): + self.nr_weights = nr_weights + self.nr_samples = nr_samples + self.kappa = kappa + self.lower_bound = lower_bound + self.upper_bound = upper_bound + self.seed = seed + + def __call__(self, gauss_process, x_observed, seed=None): + # if seed is set for whole experiment + if self.seed is not None: + seed = self.seed + + # random generator + rng = np.random.default_rng(seed) + + # get the best so far observed y + mu = gauss_process.predict(x_observed) + y_best = max(mu) + + # sample from surrogate + x_test = rng.uniform(self.lower_bound, self.upper_bound, size=(self.nr_samples, self.nr_weights)) + mu, sigma = gauss_process.predict(x_test, return_std=True) + + # probability of improvement + z = (mu - y_best - self.kappa) / sigma + pi = norm.cdf(z) + + # get the best result and return it + idx = np.argmax(pi) + return x_test[idx, :] diff --git a/src/interaction_optimizers/interaction_optimizers/bayesian_optimization_node.py b/src/interaction_optimizers/interaction_optimizers/bayesian_optimization_node.py new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/src/interaction_optimizers/interaction_optimizers/bayesian_optimization_node.py @@ -0,0 +1 @@ + diff --git a/src/Optimizers/Optimizers/__init__.py b/src/interaction_optimizers/interaction_optimizers/optimizers/__init__.py similarity index 100% rename from src/Optimizers/Optimizers/__init__.py rename to src/interaction_optimizers/interaction_optimizers/optimizers/__init__.py diff --git a/src/interaction_optimizers/interaction_optimizers/optimizers/bayesian_optimization.py b/src/interaction_optimizers/interaction_optimizers/optimizers/bayesian_optimization.py new file mode 100644 index 0000000..b58e90d --- /dev/null +++ b/src/interaction_optimizers/interaction_optimizers/optimizers/bayesian_optimization.py @@ -0,0 +1,137 @@ + +import numpy as np +from sklearn.gaussian_process import GaussianProcessRegressor +from sklearn.gaussian_process.kernels import Matern, RBF, ExpSineSquared + +from ..acquisition_function import ConfidenceBounds +from ..acquisition_function import ProbabilityOfImprovement +from ..acquisition_function import ExpectedImprovement +from ..acquisition_function import PreferenceExpectedImprovement + +from sklearn.exceptions import ConvergenceWarning +import warnings + +warnings.filterwarnings('ignore', category=ConvergenceWarning) + + +class BayesianOptimization: + def __init__(self, nr_steps, nr_dimensions, nr_policy_parameters, seed=None, + fixed_dimensions=None, lower_bound=None, upper_bound=None, + acquisition_function_name="EI", kernel_name="Matern", + **kwargs): + + self.nr_steps = nr_steps + self.nr_dimensions = nr_dimensions + self.nr_policy_parameters = nr_policy_parameters + self.nr_weights = nr_policy_parameters * nr_dimensions + + if lower_bound is None: + self.lower_bound = [-1.] * self.nr_weights + else: + self.lower_bound = lower_bound + + if upper_bound is None: + self.upper_bound = [-1.] * self.nr_weights + else: + self.upper_bound = upper_bound + + self.seed = seed + self.fixed_dimensions = fixed_dimensions + + self.x_observed = None + self.y_observed = None + self.best_reward = None + self.episode = 0 + + self.gauss_process = None + self.n_restarts_optimizer = kwargs.get('n_restarts_optimizer', 5) + + + + # region Kernel + length_scale = kwargs.get('length_scale', 1.0) + + if kernel_name == "Matern": + nu = kwargs.get('nu', 1.5) + self.kernel = Matern(nu=nu, length_scale=length_scale) + + elif kernel_name == "RBF": + self.kernel = RBF(length_scale=length_scale) + + elif kernel_name == "ExpSineSquared": + periodicity = kwargs.get('periodicity', 1.0) + self.kernel = ExpSineSquared(length_scale=length_scale, periodicity=periodicity) + + else: + raise NotImplementedError("This kernel is not implemented!") + # endregion + + # region Acquisitionfunctions + if 'nr_samples' in kwargs: + nr_samples = kwargs['nr_samples'] + else: + nr_samples = 100 + + if acquisition_function_name == "CB": + beta = kwargs.get('beta', 1.2) + self.acquisition_function = ConfidenceBounds(self.nr_weights, nr_samples=nr_samples, beta=beta, seed=seed, + lower_bound=lower_bound, upper_bound=upper_bound) + + elif acquisition_function_name == "PI": + kappa = kwargs.get('kappa', 0.0) + self.acquisition_function = ProbabilityOfImprovement(self.nr_weights, nr_samples=nr_samples, kappa=kappa, + seed=seed, lower_bound=lower_bound, + upper_bound=upper_bound) + elif acquisition_function_name == "EI": + kappa = kwargs.get('kappa', 0.0) + self.acquisition_function = ExpectedImprovement(self.nr_weights, nr_samples=nr_samples, kappa=kappa, + seed=seed, lower_bound=lower_bound, upper_bound=upper_bound) + elif acquisition_function_name == "PEI": + kappa = kwargs.get('kappa', 0.0) + + initial_variance = kwargs.get('initial_variance', None) + update_variance = kwargs.get('update_variance', None) + + if initial_variance is None or update_variance is None: + raise ValueError("Initial_variance and update_variance has to be provided in PEI!") + + self.acquisition_function = PreferenceExpectedImprovement(self.nr_weights, initial_variance, + update_variance, nr_samples=nr_samples, + kappa=kappa, lower_bound=lower_bound, + upper_bound=upper_bound, seed=seed, + fixed_dims=fixed_dimensions) + else: + raise NotImplementedError("This acquisition function is not implemented!") + # endregion + + self.reset() + + def reset(self): + self.gauss_process = GaussianProcessRegressor(self.kernel, n_restarts_optimizer=self.n_restarts_optimizer) + self.best_reward = np.empty((1, 1)) + self.x_observed = np.zeros((1, self.nr_weights), dtype=np.float64) + self.y_observed = np.zeros((1, 1), dtype=np.float64) + self.episode = 0 + + def next_observation(self): + x_next = self.acquisition_function(self.gauss_process, self.x_observed, seed=self.seed) + return x_next + + def add_observation(self, y_new, x_new): + if self.episode == 0: + self.x_observed[0, :] = x_new + self.y_observed[0] = y_new + self.best_reward[0] = np.max(self.y_observed) + else: + self.x_observed = np.vstack((self.x_observed, np.around(x_new, decimals=8))) + self.y_observed = np.vstack((self.y_observed, y_new)) + self.best_reward = np.vstack((self.best_reward, np.max(self.y_observed))) + + self.gauss_process.fit(self.x_observed, self.y_observed) + self.episode += 1 + + def get_best_result(self): + y_max = np.max(self.y_observed) + idx = np.argmax(self.y_observed) + x_max = self.x_observed[idx, :] + return y_max, x_max, idx diff --git a/src/Optimizers/package.xml b/src/interaction_optimizers/package.xml similarity index 94% rename from src/Optimizers/package.xml rename to src/interaction_optimizers/package.xml index 9ed5d14..404340c 100644 --- a/src/Optimizers/package.xml +++ b/src/interaction_optimizers/package.xml @@ -1,7 +1,7 @@ - Optimizers + interaction_optimizers 0.0.0 TODO: Package description niko diff --git a/src/ObjectiveFunctions/resource/ObjectiveFunctions b/src/interaction_optimizers/resource/interaction_optimizers similarity index 100% rename from src/ObjectiveFunctions/resource/ObjectiveFunctions rename to src/interaction_optimizers/resource/interaction_optimizers diff --git a/src/interaction_optimizers/setup.cfg b/src/interaction_optimizers/setup.cfg new file mode 100644 index 0000000..397420e --- /dev/null +++ b/src/interaction_optimizers/setup.cfg @@ -0,0 +1,4 @@ +[develop] +script_dir=$base/lib/interaction_optimizers +[install] +install_scripts=$base/lib/interaction_optimizers diff --git a/src/ObjectiveFunctions/setup.py b/src/interaction_optimizers/setup.py similarity index 94% rename from src/ObjectiveFunctions/setup.py rename to src/interaction_optimizers/setup.py index c232c91..0d735f4 100644 --- a/src/ObjectiveFunctions/setup.py +++ b/src/interaction_optimizers/setup.py @@ -1,6 +1,6 @@ from setuptools import find_packages, setup -package_name = 'ObjectiveFunctions' +package_name = 'interaction_optimizers' setup( name=package_name, diff --git a/src/ObjectiveFunctions/test/test_copyright.py b/src/interaction_optimizers/test/test_copyright.py similarity index 100% rename from src/ObjectiveFunctions/test/test_copyright.py rename to src/interaction_optimizers/test/test_copyright.py diff --git a/src/ObjectiveFunctions/test/test_flake8.py b/src/interaction_optimizers/test/test_flake8.py similarity index 100% rename from src/ObjectiveFunctions/test/test_flake8.py rename to src/interaction_optimizers/test/test_flake8.py diff --git a/src/ObjectiveFunctions/test/test_pep257.py b/src/interaction_optimizers/test/test_pep257.py similarity index 100% rename from src/ObjectiveFunctions/test/test_pep257.py rename to src/interaction_optimizers/test/test_pep257.py diff --git a/src/RepresentationModels/RepresentationModels/__init__.py b/src/interaction_query/interaction_query/__init__.py similarity index 100% rename from src/RepresentationModels/RepresentationModels/__init__.py rename to src/interaction_query/interaction_query/__init__.py diff --git a/src/InteractionQuery/InteractionQuery/improvement.py b/src/interaction_query/interaction_query/improvement_query.py similarity index 99% rename from src/InteractionQuery/InteractionQuery/improvement.py rename to src/interaction_query/interaction_query/improvement_query.py index 416a832..014e7a1 100644 --- a/src/InteractionQuery/InteractionQuery/improvement.py +++ b/src/interaction_query/interaction_query/improvement_query.py @@ -1,3 +1,4 @@ + class ImprovementQuery: def __init__(self, threshold, period, last_query, rewards): self.threshold = threshold diff --git a/src/interaction_query/interaction_query/query_node.py b/src/interaction_query/interaction_query/query_node.py new file mode 100644 index 0000000..13a1b25 --- /dev/null +++ b/src/interaction_query/interaction_query/query_node.py @@ -0,0 +1,71 @@ +#!/usr/bin/env python3 +import rclpy +from rclpy.node import Node + +from .random_query import RandomQuery +from .regular_query import RegularQuery +from .improvement_query import ImprovementQuery + +from interaction_msgs.srv import Query + + +class QueryNode(Node): + def __init__(self): + super().__init__('query_node') + self.query_service = self.create_service(Query, 'user_query', self.query_callback) + + self.get_logger().info('Query node started!') + + def check_random_request(self, req): + t = req.threshold + if 0 < t <= 1: + return True + else: + self.get_logger().error('Invalid random request in user query!') + + def check_regular_request(self, req): + f = req.frequency + if f > 0: + return True + else: + self.get_logger().error('Invalid regular request in user query!') + + def check_improvement_request(self, req): + t = req.threshold + f = req.frequency + last_rewards = req.last_rewards + if 0 < t <= 1 and f > 0 and isinstance(last_rewards, list): + return True + else: + self.get_logger().error('Invalid improvement request in user query!') + + def query_callback(self, request, response): + mode = response.mode + query_obj = None + if mode == 0: + if self.check_random_request(request): + query_obj = RandomQuery(request.threshold) + elif mode == 1: + if self.check_regular_request(request): + query_obj = RegularQuery(request.frequency, request.current_episode) + elif mode == 2: + if self.check_improvement_request(request): + query_obj = ImprovementQuery(request.threshold, request.frequency, + request.last_queried_episode, request.last_rewards) + else: + self.get_logger().error('Invalid query mode!') + + if query_obj is not None: + response.interaction = query_obj.query() + return response + + +def main(args=None): + rclpy.init(args=args) + node = QueryNode() + rclpy.spin(node) + rclpy.shutdown() + + +if __name__ == '__main__': + main() diff --git a/src/InteractionQuery/InteractionQuery/random.py b/src/interaction_query/interaction_query/random_query.py similarity index 100% rename from src/InteractionQuery/InteractionQuery/random.py rename to src/interaction_query/interaction_query/random_query.py diff --git a/src/interaction_query/interaction_query/regular_query.py b/src/interaction_query/interaction_query/regular_query.py new file mode 100644 index 0000000..80c380d --- /dev/null +++ b/src/interaction_query/interaction_query/regular_query.py @@ -0,0 +1,12 @@ +class RegularQuery: + def __init__(self, frequency, episode): + self.frequency = int(frequency) + self.counter = episode + + def query(self): + + if self.counter % self.frequency == 0 and self.counter != 0: + return True + + else: + return False diff --git a/src/InteractionQuery/package.xml b/src/interaction_query/package.xml similarity index 83% rename from src/InteractionQuery/package.xml rename to src/interaction_query/package.xml index 0e664ec..bdffdd2 100644 --- a/src/InteractionQuery/package.xml +++ b/src/interaction_query/package.xml @@ -1,12 +1,15 @@ - InteractionQuery + interaction_query 0.0.0 TODO: Package description root TODO: License declaration + interaction_msgs + rclpy + ament_copyright ament_flake8 ament_pep257 diff --git a/src/Optimizers/resource/Optimizers b/src/interaction_query/resource/interaction_query similarity index 100% rename from src/Optimizers/resource/Optimizers rename to src/interaction_query/resource/interaction_query diff --git a/src/interaction_query/setup.cfg b/src/interaction_query/setup.cfg new file mode 100644 index 0000000..a593405 --- /dev/null +++ b/src/interaction_query/setup.cfg @@ -0,0 +1,4 @@ +[develop] +script_dir=$base/lib/interaction_query +[install] +install_scripts=$base/lib/interaction_query diff --git a/src/InteractionQuery/setup.py b/src/interaction_query/setup.py similarity index 86% rename from src/InteractionQuery/setup.py rename to src/interaction_query/setup.py index 74212fe..06c55ac 100644 --- a/src/InteractionQuery/setup.py +++ b/src/interaction_query/setup.py @@ -1,6 +1,6 @@ from setuptools import find_packages, setup -package_name = 'InteractionQuery' +package_name = 'interaction_query' setup( name=package_name, @@ -20,6 +20,7 @@ setup( tests_require=['pytest'], entry_points={ 'console_scripts': [ + 'query_n = interaction_query.query_node:main', ], }, ) diff --git a/src/Optimizers/test/test_copyright.py b/src/interaction_query/test/test_copyright.py similarity index 100% rename from src/Optimizers/test/test_copyright.py rename to src/interaction_query/test/test_copyright.py diff --git a/src/Optimizers/test/test_flake8.py b/src/interaction_query/test/test_flake8.py similarity index 100% rename from src/Optimizers/test/test_flake8.py rename to src/interaction_query/test/test_flake8.py diff --git a/src/Optimizers/test/test_pep257.py b/src/interaction_query/test/test_pep257.py similarity index 100% rename from src/Optimizers/test/test_pep257.py rename to src/interaction_query/test/test_pep257.py