From 0d131d0c70063f0e6508b91cba7304ae371d8466 Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Tue, 26 Sep 2023 11:52:38 -0500 Subject: [PATCH 01/13] enable xopt init from yaml file --- .../generators/bayesian/test_custom_model.py | 4 +- tests/generators/bayesian/test_high_level.py | 18 +- .../bayesian/test_model_constructor.py | 106 +++---- tests/generators/test_rcds.py | 4 +- tests/test_io.py | 2 +- tests/test_pydantic.py | 269 +++++++++--------- tests/test_utils.py | 2 +- tests/test_xopt.py | 44 +-- xopt/base.py | 51 +++- xopt/evaluator.py | 2 +- xopt/generator.py | 6 +- .../generators/bayesian/bayesian_generator.py | 17 +- xopt/generators/bayesian/models/standard.py | 6 +- xopt/generators/bayesian/multi_fidelity.py | 6 +- xopt/generators/bayesian/time_dependent.py | 4 +- xopt/generators/bayesian/turbo.py | 3 +- xopt/generators/rcds/rcds.py | 3 +- xopt/numerical_optimizer.py | 2 +- xopt/pydantic.py | 149 +++++----- 19 files changed, 378 insertions(+), 320 deletions(-) diff --git a/tests/generators/bayesian/test_custom_model.py b/tests/generators/bayesian/test_custom_model.py index 7b217756..5eacdf16 100644 --- a/tests/generators/bayesian/test_custom_model.py +++ b/tests/generators/bayesian/test_custom_model.py @@ -80,9 +80,7 @@ class ConstraintPrior(torch.nn.Module): def forward(self, X): return X.squeeze(dim=-1) ** 2 - gp_constructor = StandardModelConstructor( - mean_modules={"c": ConstraintPrior()} - ) + gp_constructor = StandardModelConstructor(mean_modules={"c": ConstraintPrior()}) generator = ExpectedImprovementGenerator( vocs=my_vocs, gp_constructor=gp_constructor ) diff --git a/tests/generators/bayesian/test_high_level.py b/tests/generators/bayesian/test_high_level.py index 5a271527..ccd8e34f 100644 --- a/tests/generators/bayesian/test_high_level.py +++ b/tests/generators/bayesian/test_high_level.py @@ -125,10 +125,13 @@ def test_restart_torch_inline_serialization(self): assert X2.generator.vocs.variable_names == ["x1", "x2"] assert X2.generator.numerical_optimizer.n_restarts == 1 assert np.allclose( - X2.generator.data[X2.vocs.all_names].to_numpy(), - X.data[X.vocs.all_names].to_numpy() + X2.generator.data[X2.vocs.all_names].to_numpy(), + X.data[X.vocs.all_names].to_numpy(), + ) + assert ( + X.generator.model.state_dict().__str__() + == X2.generator.model.state_dict().__str__() ) - assert X.generator.model.state_dict().__str__() == X2.generator.model.state_dict().__str__() X2.step() @@ -171,7 +174,10 @@ def test_restart_torch_serialization(self): X2.generator.data[X2.vocs.all_names].to_numpy(), X.data[X.vocs.all_names].to_numpy(), ) - assert X.generator.model.state_dict().__str__() == X2.generator.model.state_dict().__str__() + assert ( + X.generator.model.state_dict().__str__() + == X2.generator.model.state_dict().__str__() + ) X2.step() @@ -218,10 +224,10 @@ def test_restart(self): X2.step() - @pytest.fixture(scope='module', autouse=True) + @pytest.fixture(scope="module", autouse=True) def clean_up(self): yield - files = ['dump.yml', 'mobo_model.pt', 'dump_inline.yml'] + files = ["dump.yml", "mobo_model.pt", "dump_inline.yml"] for f in files: if os.path.exists(f): os.remove(f) diff --git a/tests/generators/bayesian/test_model_constructor.py b/tests/generators/bayesian/test_model_constructor.py index e963e9a2..a9ec3729 100644 --- a/tests/generators/bayesian/test_model_constructor.py +++ b/tests/generators/bayesian/test_model_constructor.py @@ -34,7 +34,7 @@ def test_standard(self): constructor = StandardModelConstructor() constructor.build_model( - test_vocs.variable_names, test_vocs.output_names, test_data + test_vocs.variable_names, test_vocs.output_names, test_data ) constructor.build_model_from_vocs(test_vocs, test_data) @@ -47,7 +47,7 @@ def test_duplicate_keys(self): constructor = StandardModelConstructor() constructor.build_model( - test_vocs.variable_names, test_vocs.output_names, test_data + test_vocs.variable_names, test_vocs.output_names, test_data ) model = constructor.build_model_from_vocs(test_vocs, test_data) @@ -61,13 +61,13 @@ def test_custom_model(self): with pytest.raises(ValidationError): StandardModelConstructor( - vocs=test_vocs, covar_modules=deepcopy(custom_covar)["y1"] + vocs=test_vocs, covar_modules=deepcopy(custom_covar)["y1"] ) # test custom covar module constructor = StandardModelConstructor(covar_modules=deepcopy(custom_covar)) model = constructor.build_model( - test_vocs.variable_names, test_vocs.output_names, test_data + test_vocs.variable_names, test_vocs.output_names, test_data ) assert isinstance(model.models[0].covar_module.base_kernel, PeriodicKernel) @@ -132,9 +132,9 @@ def test_serialization(self): def test_model_saving(self): my_vocs = VOCS( - variables={"x": [0, 1]}, - objectives={"y": "MAXIMIZE"}, - constraints={"c": ["LESS_THAN", 0]}, + variables={"x": [0, 1]}, + objectives={"y": "MAXIMIZE"}, + constraints={"c": ["LESS_THAN", 0]}, ) # specify a periodic kernel for each output (objectives and constraints) @@ -142,7 +142,7 @@ def test_model_saving(self): gp_constructor = StandardModelConstructor(covar_modules=covar_modules) generator = ExpectedImprovementGenerator( - vocs=my_vocs, gp_constructor=gp_constructor + vocs=my_vocs, gp_constructor=gp_constructor ) # define training data to pass to the generator @@ -151,7 +151,7 @@ def test_model_saving(self): train_c = 2.0 * torch.sin(2 * 3.14 * train_x + 0.25) training_data = pd.DataFrame( - {"x": train_x.numpy(), "y": train_y.numpy(), "c": train_c} + {"x": train_x.numpy(), "y": train_y.numpy(), "c": train_c} ) generator.add_data(training_data) @@ -176,7 +176,7 @@ def test_model_saving(self): loaded_generator = ExpectedImprovementGenerator.model_validate_json(dump) assert isinstance( - loaded_generator.gp_constructor.covar_modules["y"], ScaleKernel + loaded_generator.gp_constructor.covar_modules["y"], ScaleKernel ) # clean up @@ -191,7 +191,7 @@ def test_model_saving(self): gp_constructor = StandardModelConstructor(covar_modules=covar_modules) generator = ExpectedImprovementGenerator( - vocs=my_vocs, gp_constructor=gp_constructor + vocs=my_vocs, gp_constructor=gp_constructor ) # define training data to pass to the generator @@ -200,7 +200,7 @@ def test_model_saving(self): train_c = 2.0 * torch.sin(2 * 3.14 * train_x + 0.25) training_data = pd.DataFrame( - {"x": train_x.numpy(), "y": train_y.numpy(), "c": train_c} + {"x": train_x.numpy(), "y": train_y.numpy(), "c": train_c} ) generator.add_data(training_data) @@ -218,7 +218,7 @@ def test_model_saving(self): # create generator from file saved_options["vocs"] = my_vocs.model_dump() loaded_generator = ExpectedImprovementGenerator.model_validate_json( - json.dumps(saved_options) + json.dumps(saved_options) ) for name, val in loaded_generator.gp_constructor.covar_modules.items(): assert isinstance(val, ScaleKernel) @@ -236,9 +236,9 @@ def test_train_model(self): test_data = deepcopy(TEST_VOCS_DATA) test_pts = torch.tensor( - pd.DataFrame( - TEST_VOCS_BASE.random_inputs(5, include_constants=False) - ).to_numpy() + pd.DataFrame( + TEST_VOCS_BASE.random_inputs(5, include_constants=False) + ).to_numpy() ) test_covar_modules = [] @@ -248,7 +248,7 @@ def test_train_model(self): # prepare custom covariance module covar_module = PolynomialKernel(power=1, active_dims=[0]) * PolynomialKernel( - power=1, active_dims=[1] + power=1, active_dims=[1] ) scaled_covar_module = ScaleKernel(covar_module) @@ -263,21 +263,21 @@ def test_train_model(self): # train model with StandardModelConstructor gp_constructor = StandardModelConstructor(covar_modules=test_covar1) constructed_model = gp_constructor.build_model_from_vocs( - test_vocs, test_data + test_vocs, test_data ).models[0] # build initial model explicitly for comparison train_X = torch.cat( - ( - torch.tensor(test_data["x1"]).reshape(-1, 1), - torch.tensor(test_data["x2"]).reshape(-1, 1), - ), - dim=1, + ( + torch.tensor(test_data["x1"]).reshape(-1, 1), + torch.tensor(test_data["x2"]).reshape(-1, 1), + ), + dim=1, ) train_Y = torch.tensor(test_data["y1"]).reshape(-1, 1) if test_covar2: covar_module = PolynomialKernel( - power=1, active_dims=[0] + power=1, active_dims=[0] ) * PolynomialKernel(power=1, active_dims=[1]) scaled_covar_module = ScaleKernel(covar_module) covar2 = scaled_covar_module @@ -285,27 +285,27 @@ def test_train_model(self): covar2 = None input_transform = Normalize( - test_vocs.n_variables, bounds=torch.tensor(test_vocs.bounds) + test_vocs.n_variables, bounds=torch.tensor(test_vocs.bounds) ) benchmark_model = SingleTaskGP( - train_X, - train_Y, - input_transform=input_transform, - outcome_transform=Standardize(1), - covar_module=covar2, - likelihood=GaussianLikelihood(noise_prior=GammaPrior(1.0, 10.0)), + train_X, + train_Y, + input_transform=input_transform, + outcome_transform=Standardize(1), + covar_module=covar2, + likelihood=GaussianLikelihood(noise_prior=GammaPrior(1.0, 10.0)), ) init_mll = ExactMarginalLogLikelihood( - benchmark_model.likelihood, benchmark_model + benchmark_model.likelihood, benchmark_model ) fit_gpytorch_mll(init_mll) assert torch.allclose( - benchmark_model.train_inputs[0], constructed_model.train_inputs[0] + benchmark_model.train_inputs[0], constructed_model.train_inputs[0] ) assert torch.allclose( - benchmark_model.train_targets, constructed_model.train_targets + benchmark_model.train_targets, constructed_model.train_targets ) with torch.no_grad(): @@ -313,7 +313,7 @@ def test_train_model(self): benchmark_prediction = benchmark_model.posterior(test_pts).mean assert torch.allclose( - constructed_prediction, benchmark_prediction, rtol=1e-3 + constructed_prediction, benchmark_prediction, rtol=1e-3 ) def test_train_from_scratch(self): @@ -342,7 +342,7 @@ def test_func(input_dict): # prepare custom covariance module covar_module = PolynomialKernel(power=1, active_dims=[0]) * PolynomialKernel( - power=1, active_dims=[1] + power=1, active_dims=[1] ) scaled_covar_module = ScaleKernel(covar_module) @@ -352,7 +352,7 @@ def test_func(input_dict): # construct BAX generator generator = ExpectedImprovementGenerator( - vocs=vocs, gp_constructor=gp_constructor + vocs=vocs, gp_constructor=gp_constructor ) # define test points @@ -389,7 +389,7 @@ def test_func(input_dict): # construct generator with all points generator = ExpectedImprovementGenerator( - vocs=vocs, gp_constructor=gp_constructor + vocs=vocs, gp_constructor=gp_constructor ) # create input points @@ -402,12 +402,12 @@ def test_func(input_dict): # make sure models have exactly the same data points assert torch.allclose( - benchmark_model.models[0].train_inputs[0], - generated_model.models[0].train_inputs[0], + benchmark_model.models[0].train_inputs[0], + generated_model.models[0].train_inputs[0], ) assert torch.allclose( - benchmark_model.models[0].train_targets, - generated_model.models[0].train_targets, + benchmark_model.models[0].train_targets, + generated_model.models[0].train_targets, ) with torch.no_grad(): @@ -431,16 +431,16 @@ def test_heteroskedastic(self): # validate against botorch HeteroskedasticSingleTaskGP train_x, train_y, train_yvar = get_training_data( - test_vocs.variable_names, "y1", test_data + test_vocs.variable_names, "y1", test_data ) bmodel = HeteroskedasticSingleTaskGP( - train_x, - train_y, - train_yvar, - input_transform=get_input_transform( - test_vocs.variable_names, test_vocs.variables - ), - outcome_transform=Standardize(1), + train_x, + train_y, + train_yvar, + input_transform=get_input_transform( + test_vocs.variable_names, test_vocs.variables + ), + outcome_transform=Standardize(1), ) mll = ExactMarginalLogLikelihood(bmodel.likelihood, bmodel) fit_gpytorch_mll(mll) @@ -451,16 +451,16 @@ def test_heteroskedastic(self): posterior = model.posterior(test_x.unsqueeze(1)) bposterior = bmodel.posterior(test_x.unsqueeze(1)) assert torch.allclose( - posterior.mean[..., 0].flatten(), bposterior.mean.flatten() + posterior.mean[..., 0].flatten(), bposterior.mean.flatten() ) assert torch.allclose( - posterior.variance[..., 0].flatten(), bposterior.variance.flatten() + posterior.variance[..., 0].flatten(), bposterior.variance.flatten() ) @pytest.fixture(autouse=True) def clean_up(self): yield - files = ['test.yml', 'covar_modules_y.pt', 'covar_modules_c.pt'] + files = ["test.yml", "covar_modules_y.pt", "covar_modules_c.pt"] for f in files: if os.path.exists(f): os.remove(f) diff --git a/tests/generators/test_rcds.py b/tests/generators/test_rcds.py index b5600730..4ac89fda 100644 --- a/tests/generators/test_rcds.py +++ b/tests/generators/test_rcds.py @@ -10,10 +10,10 @@ def f_RCDS_minimize(input_dict): p = [] for i in range(2): - p.append(input_dict[f'p{i}']) + p.append(input_dict[f"p{i}"]) obj = np.linalg.norm(p) - outcome_dict = {'f': obj} + outcome_dict = {"f": obj} return outcome_dict diff --git a/tests/test_io.py b/tests/test_io.py index 0a67767d..94660ed7 100644 --- a/tests/test_io.py +++ b/tests/test_io.py @@ -16,7 +16,7 @@ def test_options_to_dict(self): generator = RandomGenerator(vocs=TEST_VOCS_BASE) X = Xopt(generator=generator, evaluator=evaluator, vocs=TEST_VOCS_BASE) print(X.model_dump_json()) - print(X.to_json(base_key='bk')) + print(X.to_json(base_key="bk")) def test_state_to_dict(self): evaluator = Evaluator(function=dummy) diff --git a/tests/test_pydantic.py b/tests/test_pydantic.py index b3ccb84e..2d4cf020 100644 --- a/tests/test_pydantic.py +++ b/tests/test_pydantic.py @@ -4,7 +4,7 @@ from typing import Optional, Union import pytest -from pydantic import BaseModel, ConfigDict, Field, SerializeAsAny, field_validator +from pydantic import BaseModel, ConfigDict, Field, field_validator, SerializeAsAny from pydantic.json import custom_pydantic_encoder from xopt.pydantic import ( @@ -37,15 +37,15 @@ class TestJsonEncoders: misc_class = MiscClass() @pytest.mark.parametrize( - ("fn",), - [ - (misc_fn,), - pytest.param(misc_class.misc_method, marks=pytest.mark.xfail(strict=True)), - (misc_class.misc_static_method,), - pytest.param( - misc_class.misc_cls_method, marks=pytest.mark.xfail(strict=True) - ), - ], + ("fn",), + [ + (misc_fn,), + pytest.param(misc_class.misc_method, marks=pytest.mark.xfail(strict=True)), + (misc_class.misc_static_method,), + pytest.param( + misc_class.misc_cls_method, marks=pytest.mark.xfail(strict=True) + ), + ], ) def test_function_type(self, fn): encoder = {FunctionType: JSON_ENCODERS[FunctionType]} @@ -58,17 +58,17 @@ def test_function_type(self, fn): assert fn == callable_from_str @pytest.mark.parametrize( - ("fn",), - [ - pytest.param( - misc_class.misc_static_method, marks=pytest.mark.xfail(strict=True) - ), - pytest.param(misc_fn, marks=pytest.mark.xfail(strict=True)), - (misc_class.misc_method,), - pytest.param( - misc_class.misc_cls_method, marks=pytest.mark.xfail(strict=True) - ), - ], + ("fn",), + [ + pytest.param( + misc_class.misc_static_method, marks=pytest.mark.xfail(strict=True) + ), + pytest.param(misc_fn, marks=pytest.mark.xfail(strict=True)), + (misc_class.misc_method,), + pytest.param( + misc_class.misc_cls_method, marks=pytest.mark.xfail(strict=True) + ), + ], ) def test_method_type(self, fn): encoder = {MethodType: JSON_ENCODERS[MethodType]} @@ -81,13 +81,13 @@ def test_method_type(self, fn): assert fn == callable @pytest.mark.parametrize( - ("fn",), - [ - (misc_class.misc_static_method,), - (misc_fn,), - (misc_class.misc_method,), - (misc_class.misc_cls_method,), - ], + ("fn",), + [ + (misc_class.misc_static_method,), + (misc_fn,), + (misc_class.misc_method,), + (misc_class.misc_cls_method,), + ], ) def test_full_encoder(self, fn): json_encoder = partial(custom_pydantic_encoder, JSON_ENCODERS) @@ -101,14 +101,14 @@ class TestSignatureValidateAndCompose: misc_class = MiscClass() @pytest.mark.parametrize( - ("args", "kwargs"), - [ - pytest.param((5, 2, 1), {"x": 2}, marks=pytest.mark.xfail(strict=True)), - pytest.param((), ({"y": 2}), marks=pytest.mark.xfail(strict=True)), - pytest.param((2,), ({"x": 2}), marks=pytest.mark.xfail(strict=True)), - ((), ({"x": 2})), - ((), {}), - ], + ("args", "kwargs"), + [ + pytest.param((5, 2, 1), {"x": 2}, marks=pytest.mark.xfail(strict=True)), + pytest.param((), ({"y": 2}), marks=pytest.mark.xfail(strict=True)), + pytest.param((2,), ({"x": 2}), marks=pytest.mark.xfail(strict=True)), + ((), ({"x": 2})), + ((), {}), + ], ) def test_validate_kwarg_only(self, args, kwargs): def run(*, x: int = 4): @@ -116,7 +116,7 @@ def run(*, x: int = 4): signature_model = validate_and_compose_signature(run, *args, **kwargs) assert all( - [kwargs[kwarg] == getattr(signature_model, kwarg) for kwarg in kwargs] + [kwargs[kwarg] == getattr(signature_model, kwarg) for kwarg in kwargs] ) # run @@ -125,20 +125,20 @@ def run(*, x: int = 4): run(*args, **kwargs) @pytest.mark.parametrize( - ("args", "kwargs"), - [ - pytest.param( - ( - 5, - 3, - 2, - ), - {"x": 1}, - marks=pytest.mark.xfail(strict=True), + ("args", "kwargs"), + [ + pytest.param( + ( + 5, + 3, + 2, ), - ((2, 1, 0), {}), - ((), {}), - ], + {"x": 1}, + marks=pytest.mark.xfail(strict=True), + ), + ((2, 1, 0), {}), + ((), {}), + ], ) def test_validate_var_positional(self, args, kwargs): def run(*args): @@ -153,22 +153,22 @@ def run(*args): run(*args) @pytest.mark.parametrize( - ("args", "kwargs"), - [ - pytest.param((5,), {"x": 2}, marks=pytest.mark.xfail(strict=True)), - ((), {"x": 2, "y": 3}), - pytest.param((), {}, marks=pytest.mark.xfail(strict=True)), + ("args", "kwargs"), + [ + pytest.param((5,), {"x": 2}, marks=pytest.mark.xfail(strict=True)), + ((), {"x": 2, "y": 3}), + pytest.param((), {}, marks=pytest.mark.xfail(strict=True)), + ( ( - ( - 2, - 4, - ), - {}, + 2, + 4, ), - ((2,), {"y": 4, "extra": True}), - ((2,), {"y": 4}), - ((2,), {"y": 4, "z": 3}), - ], + {}, + ), + ((2,), {"y": 4, "extra": True}), + ((2,), {"y": 4}), + ((2,), {"y": 4, "z": 3}), + ], ) def test_validate_full_sig(self, args, kwargs): def run(x, y, z=4, *args, **kwargs): @@ -181,64 +181,64 @@ def run(x, y, z=4, *args, **kwargs): run(*args, **kwargs) @pytest.mark.parametrize( - ("args", "kwargs"), - [ - pytest.param((5, 1), {"y": 2}, marks=pytest.mark.xfail(strict=True)), + ("args", "kwargs"), + [ + pytest.param((5, 1), {"y": 2}, marks=pytest.mark.xfail(strict=True)), + ( ( - ( - 2, - 4, - ), - {}, + 2, + 4, ), - ((5,), {"y": 2}), - ], + {}, + ), + ((5,), {"y": 2}), + ], ) def test_validate_classmethod(self, args, kwargs): signature_model = validate_and_compose_signature( - self.misc_class.misc_cls_method, *args, **kwargs + self.misc_class.misc_cls_method, *args, **kwargs ) args, kwargs = signature_model.build() self.misc_class.misc_cls_method(*args, **kwargs) @pytest.mark.parametrize( - ("args", "kwargs"), - [ - pytest.param((5, 1), {"y": 2}, marks=pytest.mark.xfail(strict=True)), + ("args", "kwargs"), + [ + pytest.param((5, 1), {"y": 2}, marks=pytest.mark.xfail(strict=True)), + ( ( - ( - 2, - 4, - ), - {}, + 2, + 4, ), - ((5,), {"y": 2}), - ], + {}, + ), + ((5,), {"y": 2}), + ], ) def test_validate_staticmethod(self, args, kwargs): signature_model = validate_and_compose_signature( - self.misc_class.misc_static_method, *args, **kwargs + self.misc_class.misc_static_method, *args, **kwargs ) args, kwargs = signature_model.build() self.misc_class.misc_static_method(*args, **kwargs) @pytest.mark.parametrize( - ("args", "kwargs"), - [ - pytest.param((5, 1), {"y": 2}, marks=pytest.mark.xfail(strict=True)), + ("args", "kwargs"), + [ + pytest.param((5, 1), {"y": 2}, marks=pytest.mark.xfail(strict=True)), + ( ( - ( - 2, - 4, - ), - {}, + 2, + 4, ), - ((5,), {"y": 2}), - ], + {}, + ), + ((5,), {"y": 2}), + ], ) def test_validate_bound_method(self, args, kwargs): signature_model = validate_and_compose_signature( - self.misc_class.misc_method, *args, **kwargs + self.misc_class.misc_method, *args, **kwargs ) args, kwargs = signature_model.build() @@ -250,18 +250,18 @@ class TestCallableModel: misc_class = MiscClass() @pytest.mark.parametrize( - ("fn", "args", "kwargs"), - [ - (misc_fn, (5,), {"y": 2}), - (misc_class.misc_cls_method, (5,), {"y": 2}), - (misc_class.misc_static_method, (5,), {"y": 2}), - pytest.param( - misc_class.misc_method, - (5,), - {"y": 2}, - marks=pytest.mark.xfail(strict=True), - ), - ], + ("fn", "args", "kwargs"), + [ + (misc_fn, (5,), {"y": 2}), + (misc_class.misc_cls_method, (5,), {"y": 2}), + (misc_class.misc_static_method, (5,), {"y": 2}), + pytest.param( + misc_class.misc_method, + (5,), + {"y": 2}, + marks=pytest.mark.xfail(strict=True), + ), + ], ) def test_construct_callable(self, fn, args, kwargs): json_encoder = partial(custom_pydantic_encoder, JSON_ENCODERS) @@ -272,23 +272,23 @@ def test_construct_callable(self, fn, args, kwargs): callable(*args, **kwargs) @pytest.mark.parametrize( - ("fn", "args", "kwargs"), - [ - pytest.param(misc_fn, (5,), {"y": 2}, marks=pytest.mark.xfail(strict=True)), - pytest.param( - misc_class.misc_cls_method, - (5,), - {"y": 2}, - marks=pytest.mark.xfail(strict=True), - ), - pytest.param( - misc_class.misc_static_method, - (5,), - {"y": 2}, - marks=pytest.mark.xfail(strict=True), - ), - (misc_class.misc_method, (5,), {"y": 2}), - ], + ("fn", "args", "kwargs"), + [ + pytest.param(misc_fn, (5,), {"y": 2}, marks=pytest.mark.xfail(strict=True)), + pytest.param( + misc_class.misc_cls_method, + (5,), + {"y": 2}, + marks=pytest.mark.xfail(strict=True), + ), + pytest.param( + misc_class.misc_static_method, + (5,), + {"y": 2}, + marks=pytest.mark.xfail(strict=True), + ), + (misc_class.misc_method, (5,), {"y": 2}), + ], ) def test_bound_callables(self, fn, args, kwargs): json_encoder = partial(custom_pydantic_encoder, JSON_ENCODERS) @@ -324,6 +324,7 @@ def test_serialize_loader(self): # tests to verify v2 behavior remains same (for things that changed from v1) + class DummyObj: pass @@ -332,7 +333,7 @@ class Dummy(BaseModel): default_obj: DummyObj = Field(DummyObj()) model_config = ConfigDict(arbitrary_types_allowed=True) - @field_validator('default_obj') + @field_validator("default_obj") def validate_obj(cls, value): assert isinstance(value, DummyObj) return value @@ -341,15 +342,15 @@ def validate_obj(cls, value): # Test subclass model resolution order # we want behavior like v1 had https://github.com/pydantic/pydantic/issues/1932 class Parent(BaseModel): - a1: str = 'a1' + a1: str = "a1" class Child1(Parent): - name: str = 'child1' + name: str = "child1" class Child2(Parent): - name: str = 'child2' + name: str = "child2" class Container(BaseModel): @@ -364,12 +365,12 @@ def test_object_init(self): def test_subclass_init(self): c1 = Container() - print('c1', c1.model_dump()) + print("c1", c1.model_dump()) c2 = Container(obj=Child2()) - print('c2', c2.model_dump()) + print("c2", c2.model_dump()) # doesn't resolve child1 - c3 = Container(**{'obj': {'a1': 'a1', 'name': 'child1'}}) + c3 = Container(**{"obj": {"a1": "a1", "name": "child1"}}) print(type(c3.obj), type(c3.obj2), c3) # works - c4 = Container(**{'obj2': {'a1': 'a1', 'name': 'child1'}}) + c4 = Container(**{"obj2": {"a1": "a1", "name": "child1"}}) print(type(c4.obj), type(c4.obj2), c4) diff --git a/tests/test_utils.py b/tests/test_utils.py index fa8d4b0e..1217ab9c 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -17,7 +17,7 @@ class MockBaseModel(BaseModel): - model_config = ConfigDict(arbitrary_types_allowed=True, extra='forbid') + model_config = ConfigDict(arbitrary_types_allowed=True, extra="forbid") device: torch.device diff --git a/tests/test_xopt.py b/tests/test_xopt.py index 41a7afed..5418f3bc 100644 --- a/tests/test_xopt.py +++ b/tests/test_xopt.py @@ -65,12 +65,21 @@ def dummy(x): X = Xopt.from_yaml(YAML) assert X.vocs.variables == {"x1": [0, 3.14159], "x2": [0, 3.14159]} + X = Xopt(YAML) + assert X.vocs.variables == {"x1": [0, 3.14159], "x2": [0, 3.14159]} + + with pytest.raises(ValueError): + Xopt(YAML, 1) + + with pytest.raises(ValueError): + Xopt(YAML, my_kwarg=1) + def test_evaluate_data(self): evaluator = Evaluator(function=xtest_callable) generator = RandomGenerator(vocs=deepcopy(TEST_VOCS_BASE)) xopt = Xopt( - generator=generator, evaluator=evaluator, vocs=deepcopy(TEST_VOCS_BASE) + generator=generator, evaluator=evaluator, vocs=deepcopy(TEST_VOCS_BASE) ) # test evaluating data w/o constants specified @@ -101,8 +110,10 @@ def test_str_method(self): val = str(xopt) assert "Data size: 2" in val - assert "vocs:\n constants:\n cnt1: 1.0\n constraints:\n c1:\n - " \ - "GREATER_THAN\n - 0.5\n objectives:\n" in val + assert ( + "vocs:\n constants:\n cnt1: 1.0\n constraints:\n c1:\n - " + "GREATER_THAN\n - 0.5\n objectives:\n" in val + ) def test_function_checking(self): def f(x, a=True): @@ -115,8 +126,8 @@ def g(x, a=True): return False vocs = VOCS( - variables={"x": [0, 2 * math.pi]}, - objectives={"f": "MINIMIZE"}, + variables={"x": [0, 2 * math.pi]}, + objectives={"f": "MINIMIZE"}, ) # init with generator and evaluator @@ -147,9 +158,9 @@ def test_submit_bad_data(self): generator = DummyGenerator(vocs=deepcopy(TEST_VOCS_BASE)) evaluator = Evaluator(function=xtest_callable) X = Xopt( - generator=generator, - evaluator=evaluator, - vocs=deepcopy(TEST_VOCS_BASE), + generator=generator, + evaluator=evaluator, + vocs=deepcopy(TEST_VOCS_BASE), ) with pytest.raises(ValueError): X.evaluate_data(pd.DataFrame({"x1": [0.0, 5.0], "x2": [-3.0, 1.0]})) @@ -158,15 +169,15 @@ def test_add_data(self): generator = DummyGenerator(vocs=deepcopy(TEST_VOCS_BASE)) evaluator = Evaluator(function=xtest_callable) X = Xopt( - generator=generator, - evaluator=evaluator, - vocs=deepcopy(TEST_VOCS_BASE), + generator=generator, + evaluator=evaluator, + vocs=deepcopy(TEST_VOCS_BASE), ) assert X.generator.data is None X.add_data(pd.DataFrame({"x1": [0.0, 1.0], "x2": [0.0, 1.0]})) assert ( - len(X.generator.data) == 2 + len(X.generator.data) == 2 ), f"len(X.generator.data) = {len(X.generator.data)}" def test_asynch(self): @@ -266,6 +277,7 @@ def test_dump_w_exploded_cols(self): X.dump_state() import os + os.remove(X.dump_file) def test_checkpointing(self): @@ -273,7 +285,7 @@ def test_checkpointing(self): generator = RandomGenerator(vocs=deepcopy(TEST_VOCS_BASE)) X = Xopt( - generator=generator, evaluator=evaluator, vocs=deepcopy(TEST_VOCS_BASE) + generator=generator, evaluator=evaluator, vocs=deepcopy(TEST_VOCS_BASE) ) X.dump_file = "test_checkpointing.yaml" @@ -295,7 +307,7 @@ def test_random_evaluate(self): generator = RandomGenerator(vocs=deepcopy(TEST_VOCS_BASE)) xopt = Xopt( - generator=generator, evaluator=evaluator, vocs=deepcopy(TEST_VOCS_BASE) + generator=generator, evaluator=evaluator, vocs=deepcopy(TEST_VOCS_BASE) ) # fixed seed for deterministic results @@ -304,10 +316,10 @@ def test_random_evaluate(self): assert np.isclose(xopt.data["x1"].iloc[0], 0.488178) assert len(xopt.data) == 3 - @pytest.fixture(scope='module', autouse=True) + @pytest.fixture(scope="module", autouse=True) def clean_up(self): yield - files = ['test_checkpointing.yaml'] + files = ["test_checkpointing.yaml"] for f in files: if os.path.exists(f): os.remove(f) diff --git a/xopt/base.py b/xopt/base.py index 202ed1aa..e22e757e 100644 --- a/xopt/base.py +++ b/xopt/base.py @@ -1,6 +1,6 @@ import json import logging -from typing import Dict, List, Union, Optional +from typing import Dict, List, Optional, Union import numpy as np import pandas as pd @@ -27,8 +27,12 @@ class Xopt(XoptBaseModel): """ vocs: VOCS = Field(description="VOCS object for Xopt") - generator: SerializeAsAny[Generator] = Field(description="generator object for Xopt") - evaluator: SerializeAsAny[Evaluator] = Field(description="evaluator object for Xopt") + generator: SerializeAsAny[Generator] = Field( + description="generator object for Xopt" + ) + evaluator: SerializeAsAny[Evaluator] = Field( + description="evaluator object for Xopt" + ) strict: bool = Field( True, description="flag to indicate if exceptions raised during evaluation " @@ -46,23 +50,26 @@ class Xopt(XoptBaseModel): description="flag to indicate that torch models should be serialized " "when dumping", ) - serialize_inline: bool = Field(False, description="flag to indicate if torch models" - " should be stored inside main config file") + serialize_inline: bool = Field( + False, + description="flag to indicate if torch models" + " should be stored inside main config file", + ) - @field_validator("vocs", mode='before') + @field_validator("vocs", mode="before") def validate_vocs(cls, value): if isinstance(value, dict): value = VOCS(**value) return value - @field_validator("evaluator", mode='before') + @field_validator("evaluator", mode="before") def validate_evaluator(cls, value): if isinstance(value, dict): value = Evaluator(**value) return value - @field_validator("generator", mode='before') + @field_validator("generator", mode="before") def validate_generator(cls, value, info: FieldValidationInfo): if isinstance(value, dict): name = value.pop("name") @@ -74,7 +81,7 @@ def validate_generator(cls, value, info: FieldValidationInfo): return value - @field_validator("data", mode='before') + @field_validator("data", mode="before") def validate_data(cls, v, info: FieldValidationInfo): if isinstance(v, dict): try: @@ -95,6 +102,22 @@ def n_data(self): else: return len(self.data) + def __init__(self, *args, **kwargs): + """ + Initialize Xopt. + """ + if len(args) == 1: + if len(kwargs) > 0: + raise ValueError("cannot specify yaml string and kwargs for Xopt init") + super().__init__(**yaml.safe_load(args[0])) + elif len(args) > 1: + raise ValueError( + "arguments to Xopt must be either a single yaml string " + "or a keyword arguments passed directly to pydantic" + ) + else: + super().__init__(**kwargs) + def step(self): """ run one optimization cycle @@ -207,9 +230,13 @@ def random_evaluate(self, n_samples=1, seed=None, **kwargs): def dump_state(self, **kwargs): """dump data to file""" if self.dump_file is not None: - output = json.loads(self.json(serialize_torch=self.serialize_torch, - serialize_inline=self.serialize_inline, - **kwargs)) + output = json.loads( + self.json( + serialize_torch=self.serialize_torch, + serialize_inline=self.serialize_inline, + **kwargs, + ) + ) with open(self.dump_file, "w") as f: yaml.dump(output, f) logger.debug(f"Dumped state to YAML file: {self.dump_file}") diff --git a/xopt/evaluator.py b/xopt/evaluator.py index 891f09fa..a6cb6bd0 100644 --- a/xopt/evaluator.py +++ b/xopt/evaluator.py @@ -48,7 +48,7 @@ class Evaluator(XoptBaseModel): model_config = ConfigDict(arbitrary_types_allowed=True) - @model_validator(mode='before') + @model_validator(mode="before") def validate_all(cls, values): f = get_function(values["function"]) kwargs = values.get("function_kwargs", {}) diff --git a/xopt/generator.py b/xopt/generator.py index dc614db5..0655c23b 100644 --- a/xopt/generator.py +++ b/xopt/generator.py @@ -14,7 +14,9 @@ class Generator(XoptBaseModel, ABC): name: ClassVar[str] = Field(description="generator name") vocs: VOCS = Field(description="generator VOCS", exclude=True) - data: Optional[pd.DataFrame] = Field(None, description="generator data", exclude=True) + data: Optional[pd.DataFrame] = Field( + None, description="generator data", exclude=True + ) supports_batch_generation: ClassVar[bool] = Field( default=False, description="flag that describes if this " @@ -31,7 +33,7 @@ class Generator(XoptBaseModel, ABC): _is_done = False - @field_validator("data", mode='before') + @field_validator("data", mode="before") def validate_data(cls, v): if isinstance(v, dict): try: diff --git a/xopt/generators/bayesian/bayesian_generator.py b/xopt/generators/bayesian/bayesian_generator.py index 84927857..09a6fa15 100644 --- a/xopt/generators/bayesian/bayesian_generator.py +++ b/xopt/generators/bayesian/bayesian_generator.py @@ -13,9 +13,10 @@ from botorch.sampling import get_sampler, SobolQMCNormalSampler from botorch.utils.multi_objective.box_decompositions import DominatedPartitioning from gpytorch import Module -from pydantic import Field, SerializeAsAny, field_validator +from pydantic import Field, field_validator, SerializeAsAny from pydantic_core.core_schema import FieldValidationInfo from torch import Tensor + from xopt.generator import Generator from xopt.generators.bayesian.base_model import ModelConstructor from xopt.generators.bayesian.custom_botorch.constrained_acqusition import ( @@ -80,18 +81,18 @@ class BayesianGenerator(Generator, ABC): ) n_candidates: int = 1 - @field_validator("model", mode='before') + @field_validator("model", mode="before") def validate_torch_modules(cls, v): if isinstance(v, str): - if v.startswith('base64:'): + if v.startswith("base64:"): v = decode_torch_module(v) elif os.path.exists(v): v = torch.load(v) return v - @field_validator("gp_constructor", mode='before') + @field_validator("gp_constructor", mode="before") def validate_gp_constructor(cls, value): - print(f'Verifying model {value}') + print(f"Verifying model {value}") constructor_dict = {"standard": StandardModelConstructor} if value is None: value = StandardModelConstructor() @@ -111,7 +112,7 @@ def validate_gp_constructor(cls, value): return value - @field_validator("numerical_optimizer", mode='before') + @field_validator("numerical_optimizer", mode="before") def validate_numerical_optimizer(cls, value): optimizer_dict = {"grid": GridOptimizer, "LBFGS": LBFGSOptimizer} if value is None: @@ -131,7 +132,7 @@ def validate_numerical_optimizer(cls, value): raise ValueError(f"{value} not found") return value - @field_validator("turbo_controller", mode='before') + @field_validator("turbo_controller", mode="before") def validate_turbo_controller(cls, value, info: FieldValidationInfo): """note default behavior is no use of turbo""" optimizer_dict = { @@ -163,7 +164,7 @@ def validate_turbo_controller(cls, value, info: FieldValidationInfo): ) return value - @field_validator("computation_time", mode='before') + @field_validator("computation_time", mode="before") def validate_computation_time(cls, value): if isinstance(value, dict): value = pd.DataFrame(value) diff --git a/xopt/generators/bayesian/models/standard.py b/xopt/generators/bayesian/models/standard.py index f04de360..ad4f7525 100644 --- a/xopt/generators/bayesian/models/standard.py +++ b/xopt/generators/bayesian/models/standard.py @@ -11,13 +11,13 @@ from gpytorch.likelihoods import GaussianLikelihood from gpytorch.priors import GammaPrior from pydantic import ConfigDict, Field, field_validator +from pydantic_core.core_schema import FieldValidationInfo from torch.nn import Module from xopt.generators.bayesian.base_model import ModelConstructor from xopt.generators.bayesian.models.prior_mean import CustomMean from xopt.generators.bayesian.utils import get_input_transform, get_training_data from xopt.pydantic import decode_torch_module -from pydantic_core.core_schema import FieldValidationInfo DECODERS = {"torch.float32": torch.float32, "torch.float64": torch.float64} MIN_INFERRED_NOISE_LEVEL = 1e-4 @@ -40,14 +40,14 @@ class StandardModelConstructor(ModelConstructor): model_config = ConfigDict(arbitrary_types_allowed=True, validate_assignment=True) - @field_validator("covar_modules", "mean_modules", mode='before') + @field_validator("covar_modules", "mean_modules", mode="before") def validate_torch_modules(cls, v): if not isinstance(v, dict): raise ValueError("must be dict") else: for key, val in v.items(): if isinstance(val, str): - if val.startswith('base64:'): + if val.startswith("base64:"): v[key] = decode_torch_module(val) elif os.path.exists(val): v[key] = torch.load(val) diff --git a/xopt/generators/bayesian/multi_fidelity.py b/xopt/generators/bayesian/multi_fidelity.py index 59a40ef3..5e1c836e 100644 --- a/xopt/generators/bayesian/multi_fidelity.py +++ b/xopt/generators/bayesian/multi_fidelity.py @@ -23,9 +23,7 @@ class MultiFidelityGenerator(MOBOGenerator): name = "multi_fidelity" - fidelity_parameter: Literal["s"] = Field( - "s", description="fidelity parameter name" - ) + fidelity_parameter: Literal["s"] = Field("s", description="fidelity parameter name") cost_function: Callable = Field( lambda x: x + 1.0, description="callable function that describes the cost " @@ -39,7 +37,7 @@ class MultiFidelityGenerator(MOBOGenerator): Assumes a fidelity parameter [0,1] """ - @field_validator("vocs", mode='before') + @field_validator("vocs", mode="before") def validate_vocs(cls, v: VOCS): v.variables["s"] = [0, 1] v.objectives["s"] = ObjectiveEnum("MAXIMIZE") diff --git a/xopt/generators/bayesian/time_dependent.py b/xopt/generators/bayesian/time_dependent.py index 8877be5d..bf1011dd 100644 --- a/xopt/generators/bayesian/time_dependent.py +++ b/xopt/generators/bayesian/time_dependent.py @@ -5,7 +5,7 @@ import pandas as pd import torch from botorch.acquisition import FixedFeatureAcquisitionFunction -from pydantic import Field, PositiveFloat, field_validator +from pydantic import Field, field_validator, PositiveFloat from xopt.generators.bayesian.bayesian_generator import BayesianGenerator from xopt.generators.bayesian.models.time_dependent import TimeDependentModelConstructor @@ -24,7 +24,7 @@ class TimeDependentBayesianGenerator(BayesianGenerator, ABC): description="constructor used to generate model", ) - @field_validator("gp_constructor", mode='before') + @field_validator("gp_constructor", mode="before") def validate_gp_constructor(cls, value): constructor_dict = {"time_dependent": TimeDependentModelConstructor} if value is None: diff --git a/xopt/generators/bayesian/turbo.py b/xopt/generators/bayesian/turbo.py index 75fd0a52..22b73cf1 100644 --- a/xopt/generators/bayesian/turbo.py +++ b/xopt/generators/bayesian/turbo.py @@ -5,8 +5,9 @@ import torch from botorch.models import ModelListGP -from pydantic import ConfigDict, Field, PositiveFloat, PositiveInt from pandas import DataFrame +from pydantic import ConfigDict, Field, PositiveFloat, PositiveInt + from xopt.pydantic import XoptBaseModel from xopt.vocs import VOCS diff --git a/xopt/generators/rcds/rcds.py b/xopt/generators/rcds/rcds.py index 3951093d..3917cd61 100644 --- a/xopt/generators/rcds/rcds.py +++ b/xopt/generators/rcds/rcds.py @@ -428,8 +428,7 @@ class RCDSGenerator(Generator): _rcds: RCDS = None _generator = None - model_config = ConfigDict(arbitrary_types_allowed=True, - validate_assignment=True) + model_config = ConfigDict(arbitrary_types_allowed=True, validate_assignment=True) def __init__(self, **kwargs): super().__init__(**kwargs) diff --git a/xopt/numerical_optimizer.py b/xopt/numerical_optimizer.py index 23229536..36c4f213 100644 --- a/xopt/numerical_optimizer.py +++ b/xopt/numerical_optimizer.py @@ -2,7 +2,7 @@ import torch from botorch.optim import optimize_acqf -from pydantic import ConfigDict, Field, PositiveInt, field_validator +from pydantic import ConfigDict, Field, field_validator, PositiveInt from pydantic_core.core_schema import FieldValidationInfo from torch import Tensor diff --git a/xopt/pydantic.py b/xopt/pydantic.py index c8698dc6..d80d7509 100644 --- a/xopt/pydantic.py +++ b/xopt/pydantic.py @@ -2,7 +2,6 @@ import inspect import io import json -import yaml import logging import os.path import typing @@ -16,8 +15,17 @@ import orjson import pandas as pd import torch.nn -from pydantic import BaseModel, ConfigDict, create_model, Field, field_serializer, field_validator, \ - model_serializer, model_validator +import yaml +from pydantic import ( + BaseModel, + ConfigDict, + create_model, + Field, + field_serializer, + field_validator, + model_serializer, + model_validator, +) from pydantic.v1.json import custom_pydantic_encoder from pydantic_core.core_schema import FieldValidationInfo, SerializationInfo @@ -56,19 +64,19 @@ # Pydantic v2 will by default serialize submodels as annotated types, dropping subclass attributes -def recursive_serialize(v, base_key="", serialize_torch=False, - serialize_inline: bool = False - ) -> dict: +def recursive_serialize( + v, base_key="", serialize_torch=False, serialize_inline: bool = False +) -> dict: for key in list(v): if isinstance(v[key], dict): v[key] = recursive_serialize(v[key], key, serialize_torch, serialize_inline) elif isinstance(v[key], torch.nn.Module): if serialize_torch: if serialize_inline: - v[key] = 'base64:' + encode_torch_module(v[key]) + v[key] = "base64:" + encode_torch_module(v[key]) else: v[key] = process_torch_module( - module=v[key], name="_".join((base_key, key)) + module=v[key], name="_".join((base_key, key)) ) else: del v[key] @@ -110,14 +118,18 @@ def recursive_deserialize(v: dict) -> dict: return v -def orjson_dumps(v: BaseModel, *, base_key="", serialize_torch=False, - serialize_inline=False - ) -> str: +def orjson_dumps( + v: BaseModel, *, base_key="", serialize_torch=False, serialize_inline=False +) -> str: # TODO: move away from borrowing pydantic v1 encoder preset json_encoder = partial(custom_pydantic_encoder, JSON_ENCODERS) - return orjson_dumps_custom(v, default=json_encoder, base_key=base_key, - serialize_torch=serialize_torch, - serialize_inline=serialize_inline) + return orjson_dumps_custom( + v, + default=json_encoder, + base_key=base_key, + serialize_torch=serialize_torch, + serialize_inline=serialize_inline, + ) def orjson_dumps_custom(v: BaseModel, *, default, base_key="", **kwargs) -> str: @@ -126,7 +138,7 @@ def orjson_dumps_custom(v: BaseModel, *, default, base_key="", **kwargs) -> str: def orjson_dumps_except_root(v: BaseModel, *, base_key="", **kwargs) -> dict: - """ Same as above but start at fields of root model, instead of model itself """ + """Same as above but start at fields of root model, instead of model itself""" dump = v.model_dump() encoded_dump = recursive_serialize(dump, base_key=base_key, **kwargs) return encoded_dump @@ -150,20 +162,22 @@ def process_torch_module(module, name): def encode_torch_module(module): import base64 import gzip + buffer = io.BytesIO() # 5 supported since 3.8 torch.save(module, buffer, pickle_protocol=5) module_bytes = buffer.getbuffer().tobytes() cb = gzip.compress(module_bytes, compresslevel=9) encoded_bytes = base64.standard_b64encode(cb) - return encoded_bytes.decode('ascii') + return encoded_bytes.decode("ascii") def decode_torch_module(modulestr: str): import base64 import gzip - assert modulestr.startswith('base64:') - base64str = modulestr.split('base64:', 1)[1] + + assert modulestr.startswith("base64:") + base64str = modulestr.split("base64:", 1)[1] decoded = base64.standard_b64decode(base64str) decompressed = gzip.decompress(decoded) bytestream = io.BytesIO(decompressed) @@ -172,9 +186,9 @@ def decode_torch_module(modulestr: str): class XoptBaseModel(BaseModel): - model_config = ConfigDict(arbitrary_types_allowed=True, extra='forbid') + model_config = ConfigDict(arbitrary_types_allowed=True, extra="forbid") - @field_validator("*", mode='before') + @field_validator("*", mode="before") def validate_files(cls, value, info: FieldValidationInfo): if isinstance(value, str): if os.path.exists(value): @@ -186,7 +200,7 @@ def validate_files(cls, value, info: FieldValidationInfo): # Note that this function still returns a dict, NOT a string. Pydantic will handle # final serialization of basic types in Rust. - @model_serializer(mode='plain', when_used='json') + @model_serializer(mode="plain", when_used="json") def serialize_json(self, sinfo: SerializationInfo) -> dict: return orjson_dumps_except_root(self) @@ -231,25 +245,25 @@ class CallableModel(BaseModel): callable: Callable signature: BaseModel - model_config = ConfigDict(arbitrary_types_allowed=True, extra='forbid') + model_config = ConfigDict(arbitrary_types_allowed=True, extra="forbid") - @model_serializer(mode='plain', when_used='json', return_type='str') + @model_serializer(mode="plain", when_used="json", return_type="str") def serialize(self): return orjson_dumps(self) - @model_validator(mode='before') + @model_validator(mode="before") def validate_all(cls, values): callable = values.pop("callable") if not isinstance( - callable, - ( - str, - Callable, - ), + callable, + ( + str, + Callable, + ), ): raise ValueError( - "Callable must be object or a string. Provided %s", type(callable) + "Callable must be object or a string. Provided %s", type(callable) ) # parse string to callable @@ -300,19 +314,19 @@ def __call__(self, *args, **kwargs): class ObjLoader( - BaseModel, - Generic[ObjType], + BaseModel, + Generic[ObjType], ): model_config = ConfigDict(arbitrary_types_allowed=True) object: Optional[ObjType] = None loader: CallableModel = None object_type: Optional[type] = None - @model_serializer(mode='plain', when_used='json', return_type='str') + @model_serializer(mode="plain", when_used="json", return_type="str") def serialize_json(self) -> str: return orjson_dumps(self) - @model_validator(mode='before') + @model_validator(mode="before") def validate_all(cls, values): # In v1, could access type_ to get resolved inner type # See https://stackoverflow.com/questions/75165745 @@ -342,10 +356,10 @@ def validate_all(cls, values): if callable.callable is not obj_type: raise ValueError( - "Provided loader of type %s. ObjLoader parameterized for \ + "Provided loader of type %s. ObjLoader parameterized for \ %s", - callable.callable.__name__, - obj_type, + callable.callable.__name__, + obj_type, ) # opt for obj type @@ -375,30 +389,30 @@ def load(self, store: bool = False): # For testing class ObjLoaderMinimal( - BaseModel, - Generic[ObjType], + BaseModel, + Generic[ObjType], ): model_config = ConfigDict(arbitrary_types_allowed=True) object: Optional[ObjType] = None object_type: Optional[type] = None - @model_validator(mode='before') + @model_validator(mode="before") def validate_all(cls, values): - print('model validator before: ', values) + print("model validator before: ", values) annotation = cls.model_fields["object"].annotation inner_types = typing.get_args(annotation) obj_type = inner_types[0] - print(f'{obj_type=}') + print(f"{obj_type=}") return {"object_type": obj_type} - @model_validator(mode='after') + @model_validator(mode="after") def validate_print(cls, values): - print('model validator after: ', values) + print("model validator after: ", values) return values - @field_serializer('object_type', when_used='json') + @field_serializer("object_type", when_used="json") def serialize_object_type(self, x): - print('object_type serializer', x) + print("object_type serializer", x) if x is None: return x return f"{x.__module__}.{x.__name__}" @@ -406,9 +420,8 @@ def serialize_object_type(self, x): # COMMON BASE FOR EXECUTORS class BaseExecutor( - BaseModel, - Generic[ObjType], - + BaseModel, + Generic[ObjType], ): model_config = ConfigDict(arbitrary_types_allowed=True) @@ -427,11 +440,11 @@ class BaseExecutor( # and kwargs executor: Optional[ObjType] = None - @model_serializer(mode='plain', when_used='json', return_type='str') + @model_serializer(mode="plain", when_used="json", return_type="str") def serialize_json(self) -> str: return orjson_dumps(self) - @model_validator(mode='before') + @model_validator(mode="before") def validate_all(cls, values): # TODO: better solution, since type_ is no longer available executor_type = typing.get_args(cls.model_fields["executor"].annotation)[0] @@ -452,9 +465,9 @@ def validate_all(cls, values): getattr(executor_type, submit_callable) except AttributeError: raise ValueError( - "Executor type %s has no submit method %s.", - executor_type.__name__, - submit_callable, + "Executor type %s has no submit method %s.", + executor_type.__name__, + submit_callable, ) # VALIDATE MAP CALLABLE AGAINST EXECUTOR TYPE @@ -468,9 +481,9 @@ def validate_all(cls, values): getattr(executor_type, map_callable) except AttributeError: raise ValueError( - "Executor type %s has no map method %s.", - executor_type.__name__, - map_callable, + "Executor type %s has no map method %s.", + executor_type.__name__, + map_callable, ) # VALIDATE SHUTDOWN CALLABLE AGAINST EXECUTOR TYPE @@ -484,9 +497,9 @@ def validate_all(cls, values): getattr(executor_type, shutdown_callable) except AttributeError: raise ValueError( - "Executor type %s has no shutdown method %s.", - executor_type.__name__, - shutdown_callable, + "Executor type %s has no shutdown method %s.", + executor_type.__name__, + shutdown_callable, ) # Compose loader utility @@ -527,8 +540,8 @@ def shutdown(self) -> None: # NormalExecutor with no context handling on submission and executor persistence class NormalExecutor( - BaseExecutor[ObjType], - Generic[ObjType], + BaseExecutor[ObjType], + Generic[ObjType], ): model_config = ConfigDict(arbitrary_types_allowed=True) @@ -542,8 +555,8 @@ def validate_executor(cls, v, info: FieldValidationInfo): else: if not isinstance(v, (info.data["executor_type"],)): raise ValueError( - "Provided executor is not instance of %s", - info.data["executor_type"].__name__, + "Provided executor is not instance of %s", + info.data["executor_type"].__name__, ) return v @@ -626,9 +639,9 @@ def rpartial(func, *args): if bind is not None: if not isinstance(bind, (bound_class,)): raise ValueError( - "Provided bind %s is not instance of %s", - bind, - bound_class.__qualname__, + "Provided bind %s is not instance of %s", + bind, + bound_class.__qualname__, ) if is_bound and isinstance(callable, (FunctionType,)) and bind is None: @@ -737,7 +750,7 @@ def validate_and_compose_signature(callable: Callable, *args, **kwargs): pydantic_fields[key] = (type(value), value) model = create_model( - f"Kwargs_{callable.__qualname__}", __base__=SignatureModel, **pydantic_fields + f"Kwargs_{callable.__qualname__}", __base__=SignatureModel, **pydantic_fields ) return model() From 18c867757cfa1c1cfbd96a2720e186fa785c503d Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Wed, 27 Sep 2023 13:35:01 -0500 Subject: [PATCH 02/13] start fixes to cnsga for yaml dumping --- xopt/generators/ga/cnsga.py | 67 +++++++++++-------------------------- 1 file changed, 19 insertions(+), 48 deletions(-) diff --git a/xopt/generators/ga/cnsga.py b/xopt/generators/ga/cnsga.py index 1cbe6795..7078c466 100644 --- a/xopt/generators/ga/cnsga.py +++ b/xopt/generators/ga/cnsga.py @@ -2,11 +2,11 @@ import logging import os import random -from typing import Dict, List +from typing import Dict, List, Optional import pandas as pd from deap import algorithms as deap_algorithms, base as deap_base, tools as deap_tools -from pydantic import ConfigDict, confloat, Field +from pydantic import ConfigDict, confloat, Field, PrivateAttr import xopt.utils from xopt.generator import Generator @@ -34,25 +34,21 @@ class CNSGAGenerator(Generator): None, description="Population file to load (CSV format)" ) output_path: str = Field(None, description="Output path for population files") + _children: List[Dict] = PrivateAttr([]) + _offspring: Optional[pd.DataFrame] = PrivateAttr(None) + population: Optional[pd.DataFrame] = Field(None) model_config = ConfigDict(extra="allow") def __init__(self, **kwargs): super().__init__(**kwargs) - # Internal data structures - self.children = ( - [] - ) # list of unevaluated inputs. This should be a list of dicts. - self.population = None # The latest population data (fully evaluated) - self.offspring = None # Newly evaluated data, but not yet added to population - self._loaded_population = ( None # use these to generate children until the first pop is made ) # DEAP toolbox (internal) - self.toolbox = cnsga_toolbox(self.vocs, selection="auto") + self._toolbox = cnsga_toolbox(self.vocs, selection="auto") if self.population_file is not None: self.load_population_csv(self.population_file) @@ -63,31 +59,6 @@ def __init__(self, **kwargs): # if data is not None: # self.population = cnsga_select(data, n_pop, vocs, self.toolbox) - def old__init__( - self, - vocs, - *, - n_pop, - data=None, - crossover_probability=0.9, - mutation_probability=1.0, - ): - self._vocs = vocs # TODO: use proper options - self.n_pop = n_pop - self.crossover_probability = crossover_probability - self.mutation_probability = mutation_probability - - # Internal data structures - self.children = [] # unevaluated inputs. This should be a list of dicts. - self.population = None # The latest population (fully evaluated) - self.offspring = None # Newly evaluated data, but not yet added to population - - # DEAP toolbox (internal) - self.toolbox = cnsga_toolbox(vocs, selection="auto") - - if data is not None: - self.population = cnsga_select(data, n_pop, vocs, self.toolbox) - def create_children(self) -> List[Dict]: # No population, so create random children if self.population is None: @@ -103,28 +74,28 @@ def create_children(self) -> List[Dict]: inputs = cnsga_variation( pop, self.vocs, - self.toolbox, + self._toolbox, crossover_probability=self.crossover_probability, mutation_probability=self.mutation_probability, ) return inputs.to_dict(orient="records") def add_data(self, new_data: pd.DataFrame): - self.offspring = pd.concat([self.offspring, new_data]) + self._offspring = pd.concat([self._offspring, new_data]) # Next generation - if len(self.offspring) >= self.n_pop: - candidates = pd.concat([self.population, self.offspring]) + if len(self._offspring) >= self.n_pop: + candidates = pd.concat([self.population, self._offspring]) self.population = cnsga_select( - candidates, self.n_pop, self.vocs, self.toolbox + candidates, self.n_pop, self.vocs, self._toolbox ) if self.output_path is not None: self.write_offspring() self.write_population() - self.children = [] # reset children - self.offspring = None # reset offspring + self._children = [] # reset children + self._offspring = None # reset offspring def generate(self, n_candidates) -> list[dict]: """ @@ -133,10 +104,10 @@ def generate(self, n_candidates) -> list[dict]: """ # Make sure we have enough children to fulfill the request - while len(self.children) < n_candidates: - self.children.extend(self.create_children()) + while len(self._children) < n_candidates: + self._children.extend(self.create_children()) - return [self.children.pop() for _ in range(n_candidates)] + return [self._children.pop() for _ in range(n_candidates)] def write_offspring(self, filename=None): """ @@ -144,7 +115,7 @@ def write_offspring(self, filename=None): Similar to write_population """ - if self.offspring is None: + if self._offspring is None: logger.warning("No offspring to write") return @@ -152,7 +123,7 @@ def write_offspring(self, filename=None): filename = f"{self.name}_offspring_{xopt.utils.isotime(include_microseconds=True)}.csv" filename = os.path.join(self.output_path, filename) - self.offspring.to_csv(filename, index_label="xopt_index") + self._offspring.to_csv(filename, index_label="xopt_index") def write_population(self, filename=None): """ @@ -178,7 +149,7 @@ def load_population_csv(self, filename): pop = pd.read_csv(filename, index_col="xopt_index") self._loaded_population = pop # This is a list of dicts - self.children = self.vocs.convert_dataframe_to_inputs( + self._children = self.vocs.convert_dataframe_to_inputs( pop[self.vocs.variable_names], include_constants=False ).to_dict(orient="records") logger.info(f"Loaded population of len {len(pop)} from file: {filename}") From d187cd08f4754bea927689d6e722e6e90e7f2b17 Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Wed, 27 Sep 2023 13:35:57 -0500 Subject: [PATCH 03/13] mpi fixes + addition tests --- tests/test_mpi.py | 65 ++++++++++++++++++++++++++++++++++++++++++ xopt/mpi/run.py | 72 +++++++++++++++++++++++++---------------------- 2 files changed, 104 insertions(+), 33 deletions(-) create mode 100644 tests/test_mpi.py diff --git a/tests/test_mpi.py b/tests/test_mpi.py new file mode 100644 index 00000000..1de8a123 --- /dev/null +++ b/tests/test_mpi.py @@ -0,0 +1,65 @@ +import yaml + +from xopt.mpi.run import run_mpi + + +class TestMPI: + def test_mpi(self): + YAML = """ + max_evaluations: 5 + evaluator: + function: xopt.resources.test_functions.tnk.evaluate_TNK + function_kwargs: + a: 999 + max_workers: 2 + + generator: + name: random + + vocs: + variables: + x1: [0, 3.14159] + x2: [0, 3.14159] + objectives: {y1: MINIMIZE, y2: MINIMIZE} + constraints: + c1: [GREATER_THAN, 0] + c2: [LESS_THAN, 0.5] + constants: {a: dummy_constant} + + """ + + # run batched mode + run_mpi(yaml.safe_load(YAML), 0, False, None) + + # run asynch mode + run_mpi(yaml.safe_load(YAML), 0, True, None) + + def test_with_cnsga(self): + YAML = """ + max_evaluations: 10 + generator: + name: cnsga + population_size: 64 + + evaluator: + function: xopt.resources.test_functions.tnk.evaluate_TNK + function_kwargs: + sleep: 0 + random_sleep: 0.1 + + vocs: + variables: + x1: [0, 3.14159] + x2: [0, 3.14159] + objectives: {y1: MINIMIZE, y2: MINIMIZE} + constraints: + c1: [GREATER_THAN, 0] + c2: [LESS_THAN, 0.5] + constants: {a: dummy_constant} + """ + + # run batched mode + run_mpi(yaml.safe_load(YAML), 0, False, None) + + # run asynch mode + run_mpi(yaml.safe_load(YAML), 0, True, None) diff --git a/xopt/mpi/run.py b/xopt/mpi/run.py index a6ec1d4e..503d6958 100644 --- a/xopt/mpi/run.py +++ b/xopt/mpi/run.py @@ -17,41 +17,23 @@ mpi_rank = comm.Get_rank() mpi_size = comm.Get_size() -""" -Xopt MPI driver +logger = logging.getLogger("xopt") -Basic usage: -mpirun -n 4 python -m mpi4py.futures -m xopt.mpi.run xopt.yaml +def run_mpi(config, verbosity, asynch, logfile): + """ + Xopt MPI driver + Basic usage: -""" + mpirun -n 4 python -m mpi4py.futures -m xopt.mpi.run xopt.yaml -if __name__ == "__main__": - logger = logging.getLogger("xopt") - - # ARGS = 'xopt.in'.split() - - parser = argparse.ArgumentParser(description="Configure xopt") - parser.add_argument("input_file", help="input_file") - - parser.add_argument("--logfile", "-l", help="Log file to write to") - - parser.add_argument("--verbose", "-v", action="count", help="Show more log output") - parser.add_argument( - "--asynch", "-a", action="store_true", help="Use asynchronous execution" - ) - - args = parser.parse_args() - print(args) - - infile = args.input_file - assert os.path.exists(infile), f"Input file does not exist: {infile}" + """ level = "WARN" - if args.verbose: - iv = args.verbose + if verbosity: + iv = verbosity if iv == 1: level = "WARN" elif iv == 2: @@ -61,20 +43,18 @@ set_handler_with_logger(level=level) - if args.logfile: + if logfile: set_handler_with_logger(file=args.logfile, level=level) # logger.info(xopt_logo) # logger.info('_________________________________') logger.info(f"Parallel execution with {mpi_size} workers") - config = yaml.safe_load(infile) - - if args.asynch: + if asynch: logger.info("Enabling async mode") - X = AsynchronousXopt.model_validate(config) + X = AsynchronousXopt(**config) else: - X = Xopt.model_validate(config) + X = Xopt(**config) print(X) sys.stdout.flush() @@ -84,3 +64,29 @@ X.evaluator.executor = executor X.evaluator.max_workers = mpi_size X.run() + + +if __name__ == "__main__": + # ARGS = 'xopt.in'.split() + + parser = argparse.ArgumentParser(description="Configure xopt") + parser.add_argument("input_file", help="input_file") + + parser.add_argument("--logfile", "-l", help="Log file to write to") + + parser.add_argument("--verbose", "-v", action="count", help="Show more log output") + parser.add_argument( + "--asynch", "-a", action="store_true", help="Use asynchronous execution" + ) + + args = parser.parse_args() + print(args) + + input_file = args.input_file + log_file = args.logfile + verbosity = args.verbose + asynch = args.asynch + + assert os.path.exists(input_file), f"Input file does not exist: {input_file}" + + run_mpi(yaml.safe_load(input_file), verbosity, log_file, asynch) From de3a8bd75a81e68f74f1148ddc45b0189db90738 Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Wed, 27 Sep 2023 13:44:09 -0500 Subject: [PATCH 04/13] formatting --- tests/test_mpi.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_mpi.py b/tests/test_mpi.py index 1de8a123..5505f57c 100644 --- a/tests/test_mpi.py +++ b/tests/test_mpi.py @@ -40,13 +40,13 @@ def test_with_cnsga(self): generator: name: cnsga population_size: 64 - + evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK function_kwargs: sleep: 0 random_sleep: 0.1 - + vocs: variables: x1: [0, 3.14159] From 864741f432e12e3f8d45d0989f5b47cd38e8d7a1 Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Wed, 27 Sep 2023 15:34:48 -0500 Subject: [PATCH 05/13] fix error with file inputs --- tests/test_mpi.py | 17 +++++++++++++++++ xopt/mpi/run.py | 2 +- 2 files changed, 18 insertions(+), 1 deletion(-) diff --git a/tests/test_mpi.py b/tests/test_mpi.py index 5505f57c..cd9dc86d 100644 --- a/tests/test_mpi.py +++ b/tests/test_mpi.py @@ -1,3 +1,6 @@ +import os + +import pytest import yaml from xopt.mpi.run import run_mpi @@ -34,6 +37,12 @@ def test_mpi(self): # run asynch mode run_mpi(yaml.safe_load(YAML), 0, True, None) + # test with file + with open("test.yml", "w") as f: + yaml.dump(yaml.safe_load(YAML), f) + + run_mpi(yaml.safe_load(open("test.yml")), 0, False, None) + def test_with_cnsga(self): YAML = """ max_evaluations: 10 @@ -63,3 +72,11 @@ def test_with_cnsga(self): # run asynch mode run_mpi(yaml.safe_load(YAML), 0, True, None) + + @pytest.fixture(scope="module", autouse=True) + def clean_up(self): + yield + files = ["test.yml"] + for f in files: + if os.path.exists(f): + os.remove(f) diff --git a/xopt/mpi/run.py b/xopt/mpi/run.py index 503d6958..09590d2e 100644 --- a/xopt/mpi/run.py +++ b/xopt/mpi/run.py @@ -89,4 +89,4 @@ def run_mpi(config, verbosity, asynch, logfile): assert os.path.exists(input_file), f"Input file does not exist: {input_file}" - run_mpi(yaml.safe_load(input_file), verbosity, log_file, asynch) + run_mpi(yaml.safe_load(open(input_file)), verbosity, log_file, asynch) From fdef0b8652b0863e537b9d02d89a086a9edf5d75 Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Sat, 30 Sep 2023 14:50:13 -0500 Subject: [PATCH 06/13] fix validation issues in xopt base class and cnsga generator --- tests/generators/ga/test_cnsga.py | 30 +++++++++++++-- tests/test_xopt.py | 30 +++++++++++++++ xopt/base.py | 62 ++++++++++++++++--------------- xopt/generators/ga/cnsga.py | 36 +++++++++--------- xopt/vocs.py | 4 +- 5 files changed, 112 insertions(+), 50 deletions(-) diff --git a/tests/generators/ga/test_cnsga.py b/tests/generators/ga/test_cnsga.py index ce77af9c..fb9e779b 100644 --- a/tests/generators/ga/test_cnsga.py +++ b/tests/generators/ga/test_cnsga.py @@ -16,10 +16,34 @@ def test_cnsga(): def test_cnsga_from_yaml(): - X = Xopt.from_yaml(TEST_YAML) + YAML = """ + max_evaluations: 5 + dump_file: null + data: null + generator: + name: cnsga + population_size: 64 + population_file: null # Bad + + evaluator: + function: xopt.resources.test_functions.tnk.evaluate_TNK + function_kwargs: + sleep: 0 + random_sleep: 0.1 + + vocs: + variables: + x1: [0, 3.14159] + x2: [0, 3.14159] + objectives: {y1: MINIMIZE, y2: MINIMIZE} + constraints: + c1: [GREATER_THAN, 0] + c2: [LESS_THAN, 0.5] + constants: {a: dummy_constant} + """ + + X = Xopt(YAML) # Patch in generator - X.generator = CNSGAGenerator(vocs=X.vocs) - X.max_evaluations = 5 X.run() assert len(X.data) == 5 assert all(~X.data["xopt_error"]) diff --git a/tests/test_xopt.py b/tests/test_xopt.py index 5418f3bc..937ea9c2 100644 --- a/tests/test_xopt.py +++ b/tests/test_xopt.py @@ -7,6 +7,8 @@ import numpy as np import pandas as pd import pytest +from pydantic import ValidationError + from xopt.asynchronous import AsynchronousXopt from xopt.base import Xopt from xopt.errors import XoptError @@ -43,6 +45,8 @@ def dummy(x): # init with yaml YAML = """ + dump_file: null + data: null evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK function_kwargs: @@ -74,6 +78,32 @@ def dummy(x): with pytest.raises(ValueError): Xopt(YAML, my_kwarg=1) + def test_bad_vocs(self): + # test with bad vocs + YAML = """ + evaluator: + function: xopt.resources.test_functions.tnk.evaluate_TNK + function_kwargs: + a: 999 + + generator: + name: random + + vocs: + variables: + x1: [0, 3.14159] + x2: [0, 3.14159] + objectives: {y1: MINIMIZE, y2: MINIMIZE} + constraints: + c1: [GREATER_THAN, 0] + c2: [LESS_THAN, 0.5] + constants: {a: dummy_constant} + bad_val: 5 + + """ + with pytest.raises(ValidationError): + Xopt(YAML) + def test_evaluate_data(self): evaluator = Evaluator(function=xtest_callable) generator = RandomGenerator(vocs=deepcopy(TEST_VOCS_BASE)) diff --git a/xopt/base.py b/xopt/base.py index e22e757e..b9395417 100644 --- a/xopt/base.py +++ b/xopt/base.py @@ -1,12 +1,13 @@ import json import logging -from typing import Dict, List, Optional, Union +from typing import Dict, List, Optional, Union, Any import numpy as np import pandas as pd import yaml from pandas import DataFrame -from pydantic import Field, field_validator, FieldValidationInfo, SerializeAsAny +from pydantic import Field, field_validator, FieldValidationInfo, SerializeAsAny, \ + ValidationError, model_validator from xopt import _version from xopt.evaluator import Evaluator, validate_outputs @@ -36,7 +37,7 @@ class Xopt(XoptBaseModel): strict: bool = Field( True, description="flag to indicate if exceptions raised during evaluation " - "should stop Xopt", + "should stop Xopt", ) dump_file: Optional[str] = Field( None, description="file to dump the results of the evaluations" @@ -48,19 +49,34 @@ class Xopt(XoptBaseModel): serialize_torch: bool = Field( False, description="flag to indicate that torch models should be serialized " - "when dumping", + "when dumping", ) serialize_inline: bool = Field( False, description="flag to indicate if torch models" - " should be stored inside main config file", + " should be stored inside main config file", ) - @field_validator("vocs", mode="before") - def validate_vocs(cls, value): - if isinstance(value, dict): - value = VOCS(**value) - return value + @model_validator(mode="before") + @classmethod + def validate_model(cls, data: Any): + if isinstance(data, dict): + # validate vocs + if isinstance(data["vocs"], dict): + data["vocs"] = VOCS(**data["vocs"]) + + # validate generator + if isinstance(data["generator"], dict): + name = data["generator"].pop("name") + generator_class = get_generator(name) + data["generator"] = generator_class.model_validate( + {**data["generator"], "vocs": data["vocs"]}) + elif isinstance(data["generator"], str): + generator_class = get_generator(data["generator"]) + + data["generator"] = generator_class.model_validate({"vocs": data["vocs"]}) + + return data @field_validator("evaluator", mode="before") def validate_evaluator(cls, value): @@ -69,18 +85,6 @@ def validate_evaluator(cls, value): return value - @field_validator("generator", mode="before") - def validate_generator(cls, value, info: FieldValidationInfo): - if isinstance(value, dict): - name = value.pop("name") - generator_class = get_generator(name) - value = generator_class.model_validate({**value, "vocs": info.data["vocs"]}) - elif isinstance(value, str): - generator_class = get_generator(value) - value = generator_class.model_validate({"vocs": info.data["vocs"]}) - - return value - @field_validator("data", mode="before") def validate_data(cls, v, info: FieldValidationInfo): if isinstance(v, dict): @@ -158,13 +162,13 @@ def run(self): self.step() def evaluate_data( - self, - input_data: Union[ - pd.DataFrame, - List[Dict[str, float]], - Dict[str, List[float]], - Dict[str, float], - ], + self, + input_data: Union[ + pd.DataFrame, + List[Dict[str, float]], + Dict[str, List[float]], + Dict[str, float], + ], ) -> pd.DataFrame: """ Evaluate data using the evaluator and wait for results. diff --git a/xopt/generators/ga/cnsga.py b/xopt/generators/ga/cnsga.py index 7078c466..3dc2a1e3 100644 --- a/xopt/generators/ga/cnsga.py +++ b/xopt/generators/ga/cnsga.py @@ -30,10 +30,11 @@ class CNSGAGenerator(Generator): mutation_probability: confloat(ge=0, le=1) = Field( 1.0, description="Mutation probability" ) - population_file: str = Field( + population_file: Optional[str] = Field( None, description="Population file to load (CSV format)" ) - output_path: str = Field(None, description="Output path for population files") + output_path: Optional[str] = Field(None, description="Output path for population " + "files") _children: List[Dict] = PrivateAttr([]) _offspring: Optional[pd.DataFrame] = PrivateAttr(None) population: Optional[pd.DataFrame] = Field(None) @@ -81,21 +82,22 @@ def create_children(self) -> List[Dict]: return inputs.to_dict(orient="records") def add_data(self, new_data: pd.DataFrame): - self._offspring = pd.concat([self._offspring, new_data]) - - # Next generation - if len(self._offspring) >= self.n_pop: - candidates = pd.concat([self.population, self._offspring]) - self.population = cnsga_select( - candidates, self.n_pop, self.vocs, self._toolbox - ) - - if self.output_path is not None: - self.write_offspring() - self.write_population() - - self._children = [] # reset children - self._offspring = None # reset offspring + if new_data is not None: + self._offspring = pd.concat([self._offspring, new_data]) + + # Next generation + if len(self._offspring) >= self.n_pop: + candidates = pd.concat([self.population, self._offspring]) + self.population = cnsga_select( + candidates, self.n_pop, self.vocs, self._toolbox + ) + + if self.output_path is not None: + self.write_offspring() + self.write_population() + + self._children = [] # reset children + self._offspring = None # reset offspring def generate(self, n_candidates) -> list[dict]: """ diff --git a/xopt/vocs.py b/xopt/vocs.py index 2648ccfb..a73a282f 100644 --- a/xopt/vocs.py +++ b/xopt/vocs.py @@ -61,7 +61,9 @@ class VOCS(XoptBaseModel): description="observation names tracked alongside objectives and constraints", ) - model_config = ConfigDict(validate_assignment=True, use_enum_values=True) + model_config = ConfigDict( + validate_assignment=True, use_enum_values=True, extra="forbid" + ) @classmethod def from_yaml(cls, yaml_text): From 2b07505ce9a31cc3d22b951ab87b1bb1c653a45e Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Sat, 30 Sep 2023 14:55:54 -0500 Subject: [PATCH 07/13] formatting, remove n_raw_samples --- .../bayesian/test_upper_confidence_bound.py | 2 +- tests/generators/ga/test_cnsga.py | 7 ++-- xopt/base.py | 38 +++++++++++-------- .../bayesian/upper_confidence_bound.py | 2 +- xopt/generators/ga/cnsga.py | 5 ++- xopt/mpi/run.py | 1 - xopt/numerical_optimizer.py | 17 +-------- 7 files changed, 33 insertions(+), 39 deletions(-) diff --git a/tests/generators/bayesian/test_upper_confidence_bound.py b/tests/generators/bayesian/test_upper_confidence_bound.py index b1a73481..fe9f21c8 100644 --- a/tests/generators/bayesian/test_upper_confidence_bound.py +++ b/tests/generators/bayesian/test_upper_confidence_bound.py @@ -2,8 +2,8 @@ import numpy as np import pandas as pd -import torch import pytest +import torch from xopt.base import Xopt from xopt.evaluator import Evaluator diff --git a/tests/generators/ga/test_cnsga.py b/tests/generators/ga/test_cnsga.py index fb9e779b..0b52305e 100644 --- a/tests/generators/ga/test_cnsga.py +++ b/tests/generators/ga/test_cnsga.py @@ -2,7 +2,6 @@ from xopt.evaluator import Evaluator from xopt.generators.ga.cnsga import CNSGAGenerator from xopt.resources.test_functions.tnk import evaluate_TNK, tnk_vocs -from xopt.resources.testing import TEST_YAML def test_cnsga(): @@ -23,14 +22,14 @@ def test_cnsga_from_yaml(): generator: name: cnsga population_size: 64 - population_file: null # Bad - + population_file: null + evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK function_kwargs: sleep: 0 random_sleep: 0.1 - + vocs: variables: x1: [0, 3.14159] diff --git a/xopt/base.py b/xopt/base.py index b9395417..210cc1a4 100644 --- a/xopt/base.py +++ b/xopt/base.py @@ -1,13 +1,18 @@ import json import logging -from typing import Dict, List, Optional, Union, Any +from typing import Any, Dict, List, Optional, Union import numpy as np import pandas as pd import yaml from pandas import DataFrame -from pydantic import Field, field_validator, FieldValidationInfo, SerializeAsAny, \ - ValidationError, model_validator +from pydantic import ( + Field, + field_validator, + FieldValidationInfo, + model_validator, + SerializeAsAny, +) from xopt import _version from xopt.evaluator import Evaluator, validate_outputs @@ -37,7 +42,7 @@ class Xopt(XoptBaseModel): strict: bool = Field( True, description="flag to indicate if exceptions raised during evaluation " - "should stop Xopt", + "should stop Xopt", ) dump_file: Optional[str] = Field( None, description="file to dump the results of the evaluations" @@ -49,12 +54,12 @@ class Xopt(XoptBaseModel): serialize_torch: bool = Field( False, description="flag to indicate that torch models should be serialized " - "when dumping", + "when dumping", ) serialize_inline: bool = Field( False, description="flag to indicate if torch models" - " should be stored inside main config file", + " should be stored inside main config file", ) @model_validator(mode="before") @@ -70,11 +75,14 @@ def validate_model(cls, data: Any): name = data["generator"].pop("name") generator_class = get_generator(name) data["generator"] = generator_class.model_validate( - {**data["generator"], "vocs": data["vocs"]}) + {**data["generator"], "vocs": data["vocs"]} + ) elif isinstance(data["generator"], str): generator_class = get_generator(data["generator"]) - data["generator"] = generator_class.model_validate({"vocs": data["vocs"]}) + data["generator"] = generator_class.model_validate( + {"vocs": data["vocs"]} + ) return data @@ -162,13 +170,13 @@ def run(self): self.step() def evaluate_data( - self, - input_data: Union[ - pd.DataFrame, - List[Dict[str, float]], - Dict[str, List[float]], - Dict[str, float], - ], + self, + input_data: Union[ + pd.DataFrame, + List[Dict[str, float]], + Dict[str, List[float]], + Dict[str, float], + ], ) -> pd.DataFrame: """ Evaluate data using the evaluator and wait for results. diff --git a/xopt/generators/bayesian/upper_confidence_bound.py b/xopt/generators/bayesian/upper_confidence_bound.py index 9d3ff21c..c94d4c21 100644 --- a/xopt/generators/bayesian/upper_confidence_bound.py +++ b/xopt/generators/bayesian/upper_confidence_bound.py @@ -20,7 +20,7 @@ class UpperConfidenceBoundGenerator(BayesianGenerator): __doc__ = """Implements Bayesian Optimization using the Upper Confidence Bound acquisition function""" - @field_validator("vocs", mode='before') + @field_validator("vocs", mode="before") def validate_vocs_without_constraints(cls, v): if v.constraints: warnings.warn( diff --git a/xopt/generators/ga/cnsga.py b/xopt/generators/ga/cnsga.py index 3dc2a1e3..62f847ad 100644 --- a/xopt/generators/ga/cnsga.py +++ b/xopt/generators/ga/cnsga.py @@ -33,8 +33,9 @@ class CNSGAGenerator(Generator): population_file: Optional[str] = Field( None, description="Population file to load (CSV format)" ) - output_path: Optional[str] = Field(None, description="Output path for population " - "files") + output_path: Optional[str] = Field( + None, description="Output path for population " "files" + ) _children: List[Dict] = PrivateAttr([]) _offspring: Optional[pd.DataFrame] = PrivateAttr(None) population: Optional[pd.DataFrame] = Field(None) diff --git a/xopt/mpi/run.py b/xopt/mpi/run.py index 09590d2e..3011c28d 100644 --- a/xopt/mpi/run.py +++ b/xopt/mpi/run.py @@ -8,7 +8,6 @@ from mpi4py.futures import MPICommExecutor from xopt import AsynchronousXopt - # from mpi4py.futures import MPIPoolExecutor from xopt.base import Xopt from xopt.log import set_handler_with_logger diff --git a/xopt/numerical_optimizer.py b/xopt/numerical_optimizer.py index 36c4f213..b55922e0 100644 --- a/xopt/numerical_optimizer.py +++ b/xopt/numerical_optimizer.py @@ -2,8 +2,7 @@ import torch from botorch.optim import optimize_acqf -from pydantic import ConfigDict, Field, field_validator, PositiveInt -from pydantic_core.core_schema import FieldValidationInfo +from pydantic import ConfigDict, Field, PositiveInt from torch import Tensor from xopt.pydantic import XoptBaseModel @@ -22,10 +21,6 @@ def optimize(self, function, bounds, n_candidates=1): class LBFGSOptimizer(NumericalOptimizer): name: str = Field("LBFGS", frozen=True) - n_raw_samples: PositiveInt = Field( - 20, - description="number of raw samples used to seed optimization", - ) n_restarts: PositiveInt = Field( 20, description="number of restarts during acquistion function optimization" ) @@ -33,14 +28,6 @@ class LBFGSOptimizer(NumericalOptimizer): model_config = ConfigDict(validate_assignment=True) - @field_validator("n_restarts") - def validate_num_restarts(cls, v: int, info: FieldValidationInfo): - if v > info.data["n_raw_samples"]: - raise ValueError( - "num_restarts cannot be greater than number of " "raw_samples" - ) - return v - def optimize(self, function, bounds, n_candidates=1): assert isinstance(bounds, Tensor) if len(bounds) != 2: @@ -49,7 +36,7 @@ def optimize(self, function, bounds, n_candidates=1): acq_function=function, bounds=bounds, q=n_candidates, - raw_samples=self.n_raw_samples, + raw_samples=self.n_restarts, num_restarts=self.n_restarts, options={"maxiter": self.max_iter}, ) From e182f9dae302c8219fa0e1a1d038cdad70113749 Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Sat, 30 Sep 2023 15:03:44 -0500 Subject: [PATCH 08/13] fix tests --- tests/generators/bayesian/test_bax.py | 5 ----- tests/generators/bayesian/test_bayesian_exploration.py | 3 --- tests/generators/bayesian/test_expected_improvement.py | 3 --- tests/generators/bayesian/test_high_level.py | 5 ----- tests/generators/bayesian/test_multi_fidelity.py | 1 - tests/generators/bayesian/test_upper_confidence_bound.py | 4 ---- 6 files changed, 21 deletions(-) diff --git a/tests/generators/bayesian/test_bax.py b/tests/generators/bayesian/test_bax.py index c890d702..7fca2ca3 100644 --- a/tests/generators/bayesian/test_bax.py +++ b/tests/generators/bayesian/test_bax.py @@ -115,7 +115,6 @@ def test_generate(self): vocs=test_vocs, algorithm=alg, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.data = TEST_VOCS_DATA @@ -128,7 +127,6 @@ def test_generate(self): vocs=test_vocs, algorithm=alg, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.data = TEST_VOCS_DATA @@ -143,7 +141,6 @@ def test_cuda(self): ) if torch.cuda.is_available(): - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.data = TEST_VOCS_DATA @@ -158,7 +155,6 @@ def test_in_xopt(self): vocs=TEST_VOCS_BASE, algorithm=alg, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 xopt = Xopt(generator=gen, evaluator=evaluator, vocs=TEST_VOCS_BASE) @@ -174,7 +170,6 @@ def test_file_saving(self): gen = BaxGenerator( vocs=TEST_VOCS_BASE, algorithm=alg, algorithm_results_file="test" ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 xopt = Xopt(generator=gen, evaluator=evaluator, vocs=TEST_VOCS_BASE) diff --git a/tests/generators/bayesian/test_bayesian_exploration.py b/tests/generators/bayesian/test_bayesian_exploration.py index 0c73b729..b6515ddb 100644 --- a/tests/generators/bayesian/test_bayesian_exploration.py +++ b/tests/generators/bayesian/test_bayesian_exploration.py @@ -20,7 +20,6 @@ def test_generate(self): gen = BayesianExplorationGenerator( vocs=ele, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA @@ -34,7 +33,6 @@ def test_generate(self): gen = BayesianExplorationGenerator( vocs=ele, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA @@ -47,7 +45,6 @@ def test_generate(self): def test_in_xopt(self): evaluator = Evaluator(function=xtest_callable) gen = BayesianExplorationGenerator(vocs=TEST_VOCS_BASE) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA diff --git a/tests/generators/bayesian/test_expected_improvement.py b/tests/generators/bayesian/test_expected_improvement.py index 5e3c838f..39cfd067 100644 --- a/tests/generators/bayesian/test_expected_improvement.py +++ b/tests/generators/bayesian/test_expected_improvement.py @@ -20,7 +20,6 @@ def test_generate(self): gen = ExpectedImprovementGenerator( vocs=TEST_VOCS_BASE, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA @@ -38,7 +37,6 @@ def test_generate_w_overlapping_objectives_constraints(self): gen = ExpectedImprovementGenerator( vocs=test_vocs, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA @@ -51,7 +49,6 @@ def test_in_xopt(self): gen = ExpectedImprovementGenerator( vocs=TEST_VOCS_BASE, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 diff --git a/tests/generators/bayesian/test_high_level.py b/tests/generators/bayesian/test_high_level.py index ccd8e34f..d2af21ae 100644 --- a/tests/generators/bayesian/test_high_level.py +++ b/tests/generators/bayesian/test_high_level.py @@ -48,7 +48,6 @@ def test_constrained_mobo(self): numerical_optimizer: name: LBFGS n_restarts: 1 - n_raw_samples: 2 evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK @@ -74,7 +73,6 @@ def test_mobo(self): numerical_optimizer: name: LBFGS n_restarts: 2 - n_raw_samples: 2 evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK vocs: @@ -100,7 +98,6 @@ def test_restart_torch_inline_serialization(self): numerical_optimizer: name: LBFGS n_restarts: 1 - n_raw_samples: 2 evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK vocs: @@ -148,7 +145,6 @@ def test_restart_torch_serialization(self): numerical_optimizer: name: LBFGS n_restarts: 1 - n_raw_samples: 2 evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK vocs: @@ -193,7 +189,6 @@ def test_restart(self): numerical_optimizer: name: LBFGS n_restarts: 1 - n_raw_samples: 2 evaluator: function: xopt.resources.test_functions.tnk.evaluate_TNK diff --git a/tests/generators/bayesian/test_multi_fidelity.py b/tests/generators/bayesian/test_multi_fidelity.py index 4fd16d16..6771d23c 100644 --- a/tests/generators/bayesian/test_multi_fidelity.py +++ b/tests/generators/bayesian/test_multi_fidelity.py @@ -98,7 +98,6 @@ def test_generation(self): generator = MultiFidelityGenerator(vocs=vocs) generator.numerical_optimizer.n_restarts = 1 - generator.numerical_optimizer.n_raw_samples = 1 generator.add_data(data) diff --git a/tests/generators/bayesian/test_upper_confidence_bound.py b/tests/generators/bayesian/test_upper_confidence_bound.py index fe9f21c8..d5921a10 100644 --- a/tests/generators/bayesian/test_upper_confidence_bound.py +++ b/tests/generators/bayesian/test_upper_confidence_bound.py @@ -22,7 +22,6 @@ def test_generate(self): gen = UpperConfidenceBoundGenerator( vocs=TEST_VOCS_BASE, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA @@ -44,7 +43,6 @@ def test_cuda(self): if torch.cuda.is_available(): gen.use_cuda = True - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA @@ -58,7 +56,6 @@ def test_generate_w_overlapping_objectives_constraints(self): gen = UpperConfidenceBoundGenerator( vocs=test_vocs, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 gen.data = TEST_VOCS_DATA @@ -71,7 +68,6 @@ def test_in_xopt(self): gen = UpperConfidenceBoundGenerator( vocs=TEST_VOCS_BASE, ) - gen.numerical_optimizer.n_raw_samples = 1 gen.numerical_optimizer.n_restarts = 1 gen.n_monte_carlo_samples = 1 From e77fa0461aba78bb1edc6c98ab4eb4e6f4cf1a1e Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Sun, 1 Oct 2023 12:10:09 -0500 Subject: [PATCH 09/13] refactoring yaml and dumping methods --- docs/examples/cnsga/cnsga_tnk.ipynb | 2 +- tests/test_xopt.py | 2 +- xopt/base.py | 35 +++++++++++++++++++---------- xopt/mpi/run.py | 3 ++- 4 files changed, 27 insertions(+), 15 deletions(-) diff --git a/docs/examples/cnsga/cnsga_tnk.ipynb b/docs/examples/cnsga/cnsga_tnk.ipynb index 99e3f40f..ab96b2ac 100644 --- a/docs/examples/cnsga/cnsga_tnk.ipynb +++ b/docs/examples/cnsga/cnsga_tnk.ipynb @@ -274,7 +274,7 @@ "\n", "\"\"\"\n", "\n", - "X = Xopt.from_yaml(YAML)\n", + "X = Xopt(YAML)\n", "X" ] }, diff --git a/tests/test_xopt.py b/tests/test_xopt.py index 937ea9c2..26ae42af 100644 --- a/tests/test_xopt.py +++ b/tests/test_xopt.py @@ -304,7 +304,7 @@ def test_dump_w_exploded_cols(self): ) data = explode_all_columns(data) X.add_data(data) - X.dump_state() + X.dump() import os diff --git a/xopt/base.py b/xopt/base.py index 210cc1a4..fad92f23 100644 --- a/xopt/base.py +++ b/xopt/base.py @@ -203,7 +203,8 @@ def evaluate_data( self.add_data(new_data) # dump data to file if specified - self.dump_state() + if self.dump_file is not None: + self.dump() return new_data @@ -239,19 +240,29 @@ def random_evaluate(self, n_samples=1, seed=None, **kwargs): result = self.evaluate_data(random_inputs) return result - def dump_state(self, **kwargs): + def yaml(self, **kwargs): + """serialize first then dump to yaml string""" + output = json.loads( + self.json( + serialize_torch=self.serialize_torch, + serialize_inline=self.serialize_inline, + **kwargs, + ) + ) + return yaml.dump(output) + + def dump(self, file: str = None, **kwargs): """dump data to file""" - if self.dump_file is not None: - output = json.loads( - self.json( - serialize_torch=self.serialize_torch, - serialize_inline=self.serialize_inline, - **kwargs, - ) + fname = file if file is not None else self.dump_file + + if fname is None: + raise ValueError( + "no dump file specified via argument or in `dump_file` attribute" ) - with open(self.dump_file, "w") as f: - yaml.dump(output, f) - logger.debug(f"Dumped state to YAML file: {self.dump_file}") + else: + with open(fname, "w") as f: + f.write(self.yaml(**kwargs)) + logger.debug(f"Dumped state to YAML file: {fname}") def dict(self, **kwargs) -> Dict: """handle custom dict generation""" diff --git a/xopt/mpi/run.py b/xopt/mpi/run.py index 3011c28d..93690a93 100644 --- a/xopt/mpi/run.py +++ b/xopt/mpi/run.py @@ -8,6 +8,7 @@ from mpi4py.futures import MPICommExecutor from xopt import AsynchronousXopt + # from mpi4py.futures import MPIPoolExecutor from xopt.base import Xopt from xopt.log import set_handler_with_logger @@ -75,7 +76,7 @@ def run_mpi(config, verbosity, asynch, logfile): parser.add_argument("--verbose", "-v", action="count", help="Show more log output") parser.add_argument( - "--asynch", "-a", action="store_true", help="Use asynchronous execution" + "--async", "-a", action="store_true", help="Use asynchronous execution" ) args = parser.parse_args() From 6ae8dbcad1cf1602eedf3719a2de170cb4bf4981 Mon Sep 17 00:00:00 2001 From: Ryan Roussel Date: Mon, 2 Oct 2023 14:03:04 -0500 Subject: [PATCH 10/13] update asynchronous CL interface keyword --- xopt/mpi/run.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/xopt/mpi/run.py b/xopt/mpi/run.py index 93690a93..c13de5c4 100644 --- a/xopt/mpi/run.py +++ b/xopt/mpi/run.py @@ -76,7 +76,7 @@ def run_mpi(config, verbosity, asynch, logfile): parser.add_argument("--verbose", "-v", action="count", help="Show more log output") parser.add_argument( - "--async", "-a", action="store_true", help="Use asynchronous execution" + "--asynchronous", "-a", action="store_true", help="Use asynchronous execution" ) args = parser.parse_args() From 5171cb787addc98bf2c9c267fc34718394fdc384 Mon Sep 17 00:00:00 2001 From: Christopher Mayes <31023527+ChristopherMayes@users.noreply.github.com> Date: Mon, 2 Oct 2023 15:47:29 -0700 Subject: [PATCH 11/13] Working parallel notebook. Try tests. --- docs/examples/basic/xopt_parallel.ipynb | 1877 +++++------------------ scripts/execute_notebooks.bash | 2 +- xopt/mpi/run.py | 15 +- 3 files changed, 404 insertions(+), 1490 deletions(-) diff --git a/docs/examples/basic/xopt_parallel.ipynb b/docs/examples/basic/xopt_parallel.ipynb index 6bb40c51..695c3054 100644 --- a/docs/examples/basic/xopt_parallel.ipynb +++ b/docs/examples/basic/xopt_parallel.ipynb @@ -19,19 +19,13 @@ "metadata": {}, "outputs": [], "source": [ - "from xopt import Xopt" + "from xopt import AsynchronousXopt as Xopt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:22:40.867616Z", - "iopub.status.busy": "2022-07-02T03:22:40.867297Z", - "iopub.status.idle": "2022-07-02T03:22:41.538758Z", - "shell.execute_reply": "2022-07-02T03:22:41.538424Z" - }, "pycharm": { "name": "#%%\n" } @@ -73,12 +67,6 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:22:41.813692Z", - "iopub.status.busy": "2022-07-02T03:22:41.813504Z", - "iopub.status.idle": "2022-07-02T03:22:41.829500Z", - "shell.execute_reply": "2022-07-02T03:22:41.829220Z" - }, "pycharm": { "name": "#%%\n" } @@ -90,27 +78,52 @@ "\n", " Xopt\n", "________________________________\n", - "Version: 1.1.2+31.g422c5a9.dirty\n", + "Version: 2.0a1+193.g6ae8dbca.dirty\n", "Data size: 0\n", "Config as YAML:\n", - "xopt: {asynch: true, strict: false, dump_file: null, max_evaluations: 1000}\n", - "generator: {name: cnsga, population_size: 64, crossover_probability: 0.9, mutation_probability: 1.0,\n", - " population_file: null, output_path: temp}\n", + "dump_file: null\n", "evaluator:\n", " function: xopt.resources.test_functions.tnk.evaluate_TNK\n", + " function_kwargs:\n", + " raise_probability: 0\n", + " random_sleep: 0.1\n", + " sleep: 0\n", " max_workers: 1\n", - " function_kwargs: {sleep: 0, random_sleep: 0.1, raise_probability: 0}\n", " vectorized: false\n", + "generator:\n", + " crossover_probability: 0.9\n", + " mutation_probability: 1.0\n", + " name: cnsga\n", + " output_path: temp\n", + " population: null\n", + " population_file: null\n", + " population_size: 64\n", + "is_done: false\n", + "max_evaluations: 1000\n", + "serialize_inline: false\n", + "serialize_torch: false\n", + "strict: true\n", "vocs:\n", - " variables:\n", - " x1: [0.0, 3.14159]\n", - " x2: [0.0, 3.14159]\n", + " constants:\n", + " a: dummy_constant\n", " constraints:\n", - " c1: [GREATER_THAN, 0.0]\n", - " c2: [LESS_THAN, 0.5]\n", - " objectives: {y1: MINIMIZE, y2: MINIMIZE}\n", - " constants: {a: dummy_constant}\n", - " linked_variables: {x9: x1}\n" + " c1:\n", + " - GREATER_THAN\n", + " - 0.0\n", + " c2:\n", + " - LESS_THAN\n", + " - 0.5\n", + " objectives:\n", + " y1: MINIMIZE\n", + " y2: MINIMIZE\n", + " observables: []\n", + " variables:\n", + " x1:\n", + " - 0.0\n", + " - 3.14159\n", + " x2:\n", + " - 0.0\n", + " - 3.14159\n" ] }, "execution_count": 3, @@ -121,9 +134,8 @@ "source": [ "# Make a proper input file.\n", "YAML = \"\"\"\n", - "xopt:\n", - " asynch: True\n", - " max_evaluations: 1000\n", + "\n", + "max_evaluations: 1000\n", "\n", "generator:\n", " name: cnsga\n", @@ -144,7 +156,6 @@ " constraints:\n", " c1: [GREATER_THAN, 0]\n", " c2: [LESS_THAN, 0.5]\n", - " linked_variables: {x9: x1}\n", " constants: {a: dummy_constant}\n", "\n", "\"\"\"\n", @@ -156,12 +167,6 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:22:41.831298Z", - "iopub.status.busy": "2022-07-02T03:22:41.831164Z", - "iopub.status.idle": "2022-07-02T03:22:50.614427Z", - "shell.execute_reply": "2022-07-02T03:22:50.613438Z" - }, "pycharm": { "name": "#%%\n" } @@ -171,7 +176,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "96.5 ms ± 16.8 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "100 ms ± 17.5 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], @@ -185,12 +190,6 @@ "cell_type": "code", "execution_count": 5, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:22:50.618389Z", - "iopub.status.busy": "2022-07-02T03:22:50.618099Z", - "iopub.status.idle": "2022-07-02T03:24:45.937568Z", - "shell.execute_reply": "2022-07-02T03:24:45.936851Z" - }, "pycharm": { "name": "#%%\n" } @@ -200,8 +199,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 6.94 s, sys: 225 ms, total: 7.16 s\n", - "Wall time: 1min 50s\n" + "CPU times: user 11.1 s, sys: 207 ms, total: 11.3 s\n", + "Wall time: 1min 58s\n" ] } ], @@ -225,12 +224,6 @@ "cell_type": "code", "execution_count": 6, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:24:45.942081Z", - "iopub.status.busy": "2022-07-02T03:24:45.941750Z", - "iopub.status.idle": "2022-07-02T03:24:45.945061Z", - "shell.execute_reply": "2022-07-02T03:24:45.944538Z" - }, "pycharm": { "name": "#%%\n" } @@ -244,12 +237,6 @@ "cell_type": "code", "execution_count": 7, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:24:45.948030Z", - "iopub.status.busy": "2022-07-02T03:24:45.947835Z", - "iopub.status.idle": "2022-07-02T03:24:45.974579Z", - "shell.execute_reply": "2022-07-02T03:24:45.974116Z" - }, "pycharm": { "name": "#%%\n" } @@ -259,8 +246,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 3.86 s, sys: 294 ms, total: 4.15 s\n", - "Wall time: 12.9 s\n" + "CPU times: user 4.55 s, sys: 313 ms, total: 4.86 s\n", + "Wall time: 14 s\n" ] }, { @@ -278,7 +265,7 @@ "%%time\n", "X = Xopt(YAML)\n", "\n", - "with ProcessPoolExecutor() as executor:\n", + "with ProcessPoolExecutor(max_workers=N_CPUS) as executor:\n", " X.evaluator.executor = executor\n", " X.evaluator.max_workers = N_CPUS\n", " X.run()\n", @@ -302,12 +289,6 @@ "cell_type": "code", "execution_count": 8, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:24:45.976904Z", - "iopub.status.busy": "2022-07-02T03:24:45.976686Z", - "iopub.status.idle": "2022-07-02T03:24:45.979272Z", - "shell.execute_reply": "2022-07-02T03:24:45.978947Z" - }, "pycharm": { "name": "#%%\n" } @@ -321,12 +302,6 @@ "cell_type": "code", "execution_count": 9, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:24:45.981047Z", - "iopub.status.busy": "2022-07-02T03:24:45.980915Z", - "iopub.status.idle": "2022-07-02T03:25:11.072275Z", - "shell.execute_reply": "2022-07-02T03:25:11.071480Z" - }, "pycharm": { "name": "#%%\n" } @@ -336,8 +311,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 4.3 s, sys: 192 ms, total: 4.49 s\n", - "Wall time: 11.3 s\n" + "CPU times: user 4.77 s, sys: 176 ms, total: 4.95 s\n", + "Wall time: 11.4 s\n" ] }, { @@ -353,10 +328,9 @@ ], "source": [ "%%time\n", - "\n", "X = Xopt(YAML)\n", "\n", - "with ThreadPoolExecutor() as executor:\n", + "with ThreadPoolExecutor(max_workers=N_CPUS) as executor:\n", " X.evaluator.executor = executor\n", " X.evaluator.max_workers = N_CPUS\n", " X.run()\n", @@ -382,12 +356,6 @@ "cell_type": "code", "execution_count": 10, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:25:11.076355Z", - "iopub.status.busy": "2022-07-02T03:25:11.076087Z", - "iopub.status.idle": "2022-07-02T03:25:11.364582Z", - "shell.execute_reply": "2022-07-02T03:25:11.364010Z" - }, "pycharm": { "name": "#%%\n" } @@ -397,1025 +365,140 @@ "name": "stdout", "output_type": "stream", "text": [ - "xopt: {asynch: true, strict: false, dump_file: null, max_evaluations: 1000}\n", - "generator: {name: cnsga, population_size: 64, crossover_probability: 0.9, mutation_probability: 1.0,\n", - " population_file: null, output_path: temp}\n", + "data: null\n", + "dump_file: null\n", "evaluator:\n", " function: xopt.resources.test_functions.tnk.evaluate_TNK\n", + " function_kwargs:\n", + " raise_probability: 0\n", + " random_sleep: 0.1\n", + " sleep: 0\n", " max_workers: 1\n", - " function_kwargs: {sleep: 0, random_sleep: 0.1, raise_probability: 0}\n", " vectorized: false\n", + "generator:\n", + " crossover_probability: 0.9\n", + " mutation_probability: 1.0\n", + " name: cnsga\n", + " output_path: temp\n", + " population: null\n", + " population_file: null\n", + " population_size: 64\n", + "is_done: false\n", + "max_evaluations: 1000\n", + "serialize_inline: false\n", + "serialize_torch: false\n", + "strict: true\n", "vocs:\n", - " variables:\n", - " x1: [0.0, 3.14159]\n", - " x2: [0.0, 3.14159]\n", + " constants:\n", + " a: dummy_constant\n", " constraints:\n", - " c1: [GREATER_THAN, 0.0]\n", - " c2: [LESS_THAN, 0.5]\n", - " objectives: {y1: MINIMIZE, y2: MINIMIZE}\n", - " constants: {a: dummy_constant}\n", - " linked_variables: {x9: x1}\n" + " c1:\n", + " - GREATER_THAN\n", + " - 0.0\n", + " c2:\n", + " - LESS_THAN\n", + " - 0.5\n", + " objectives:\n", + " y1: MINIMIZE\n", + " y2: MINIMIZE\n", + " observables: []\n", + " variables:\n", + " x1:\n", + " - 0.0\n", + " - 3.14159\n", + " x2:\n", + " - 0.0\n", + " - 3.14159\n" ] } ], "source": [ "X = Xopt(YAML)\n", - "X.yaml('test.yaml') # Write this input to file\n", + "X.dump('test.yaml') # Write this input to file\n", "!cat test.yaml" ] }, { "cell_type": "code", "execution_count": 11, - "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:25:11.367100Z", - "iopub.status.busy": "2022-07-02T03:25:11.366919Z", - "iopub.status.idle": "2022-07-02T03:25:42.081626Z", - "shell.execute_reply": "2022-07-02T03:25:42.081073Z" - }, - "pycharm": { - "name": "#%%\n" - } - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Namespace(input_file='test.yaml', logfile='xopt.log', verbose=2)\n", - "Parallel execution with 10 workers\n", - "Initializing Xopt object\n", - "Initializing generator cnsga,\n", + "Namespace(input_file='test.yaml', logfile='xopt.log', verbose=2, asynchronous=True)\n", + "Parallel execution with 8 workers\n", + "Enabling async mode\n", + "Initialized generator cnsga\n", "Created toolbox with 2 variables, 2 constraints, and 2 objectives.\n", " Using selection algorithm: nsga2\n", - "Initializing Xopt object\n", - "Xopt object initialized\n", - "Enabling async mode\n", "\n", " Xopt\n", "________________________________\n", - "Version: 1.1.2+31.g422c5a9.dirty\n", + "Version: 2.0a1+193.g6ae8dbca.dirty\n", "Data size: 0\n", "Config as YAML:\n", - "xopt: {asynch: true, strict: false, dump_file: null, max_evaluations: 1000}\n", - "generator: {name: cnsga, population_size: 64, crossover_probability: 0.9, mutation_probability: 1.0,\n", - " population_file: null, output_path: temp}\n", + "dump_file: null\n", "evaluator:\n", " function: xopt.resources.test_functions.tnk.evaluate_TNK\n", + " function_kwargs:\n", + " raise_probability: 0\n", + " random_sleep: 0.1\n", + " sleep: 0\n", " max_workers: 1\n", - " function_kwargs: {sleep: 0, random_sleep: 0.1, raise_probability: 0}\n", " vectorized: false\n", + "generator:\n", + " crossover_probability: 0.9\n", + " mutation_probability: 1.0\n", + " name: cnsga\n", + " output_path: temp\n", + " population: null\n", + " population_file: null\n", + " population_size: 64\n", + "is_done: false\n", + "max_evaluations: 1000\n", + "serialize_inline: false\n", + "serialize_torch: false\n", + "strict: true\n", "vocs:\n", - " variables:\n", - " x1: [0.0, 3.14159]\n", - " x2: [0.0, 3.14159]\n", + " constants:\n", + " a: dummy_constant\n", " constraints:\n", - " c1: [GREATER_THAN, 0.0]\n", - 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"Running Xopt step\n", - "Running Xopt step\n", - "Running Xopt step\n", - "Running Xopt step\n", - "Running Xopt step\n", - "Running Xopt step\n", "Xopt is done. Max evaluations 1000 reached.\n", - "--------------------------------------------------------------------------\n", - "A system call failed during shared memory initialization that should\n", - "not have. It is likely that your MPI job will now either abort or\n", - "experience performance degradation.\n", - "\n", - " Local host: ChristophersMBP\n", - " System call: unlink(2) /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T//ompi.ChristophersMBP.501/pid.15991/1/vader_segment.ChristophersMBP.501.89fb0001.4\n", - " Error: No such file or directory (errno 2)\n", - "--------------------------------------------------------------------------\n", - "CPU times: user 180 ms, sys: 53.8 ms, total: 233 ms\n", - "Wall time: 14.8 s\n" + "CPU times: user 237 ms, sys: 84.1 ms, total: 321 ms\n", + "Wall time: 19.9 s\n" ] } ], "source": [ "%%time\n", - "!mpirun -n {N_CPUS} python -m mpi4py.futures -m xopt.mpi.run -vv --logfile xopt.log test.yaml" + "!mpirun -n 8 python -m mpi4py.futures -m xopt.mpi.run -vv --logfile xopt.log test.yaml" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:25:42.084193Z", - "iopub.status.busy": "2022-07-02T03:25:42.083890Z", - "iopub.status.idle": "2022-07-02T03:25:42.352867Z", - "shell.execute_reply": "2022-07-02T03:25:42.352305Z" - }, "pycharm": { "name": "#%%\n" } @@ -1425,16 +508,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Running Xopt step\n", - "2022-08-18T11:45:27-0700 - xopt.base - INFO - Xopt is done. Max evaluations 1000 reached.\n" + "2023-10-02T15:43:05-0700 - xopt - INFO - Parallel execution with 8 workers\n", + "2023-10-02T15:43:05-0700 - xopt - INFO - Enabling async mode\n", + "2023-10-02T15:43:05-0700 - xopt.generator - INFO - Initialized generator cnsga\n", + "2023-10-02T15:43:05-0700 - xopt.generators.ga.cnsga - INFO - Created toolbox with 2 variables, 2 constraints, and 2 objectives.\n", + "2023-10-02T15:43:05-0700 - xopt.generators.ga.cnsga - INFO - Using selection algorithm: nsga2\n", + "2023-10-02T15:43:22-0700 - xopt.base - INFO - Xopt is done. Max evaluations 1000 reached.\n" ] } ], @@ -1458,28 +537,11 @@ "cell_type": "code", "execution_count": 13, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:25:42.355681Z", - "iopub.status.busy": "2022-07-02T03:25:42.355267Z", - "iopub.status.idle": "2022-07-02T03:25:43.283065Z", - "shell.execute_reply": "2022-07-02T03:25:43.282658Z" - }, "pycharm": { "name": "#%%\n" } }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-08-18 11:45:28,982 - distributed.diskutils - INFO - Found stale lock file and directory '/var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-o2x19bac', purging\n", - "2022-08-18 11:45:28,982 - distributed.diskutils - INFO - Found stale lock file and directory '/var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-pkfm2l0b', purging\n", - "2022-08-18 11:45:28,982 - distributed.diskutils - INFO - Found stale lock file and directory '/var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-2pe9ydgc', purging\n", - "2022-08-18 11:45:28,982 - distributed.diskutils - INFO - Found stale lock file and directory '/var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-3ol1dgla', purging\n", - "2022-08-18 11:45:28,982 - distributed.diskutils - INFO - Found stale lock file and directory '/var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-37kim0g2', purging\n" - ] - }, { "data": { "text/html": [ @@ -1487,7 +549,7 @@ "
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\n", - " Comm: tcp://127.0.0.1:54856\n", + " Comm: tcp://127.0.0.1:52516\n", " \n", " Workers: 5\n", @@ -1599,7 +663,7 @@ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1644,7 +708,7 @@ "
\n", - " Comm: tcp://127.0.0.1:54896\n", + " Comm: tcp://127.0.0.1:52529\n", " \n", " Total threads: 2\n", @@ -1607,7 +671,7 @@ "
\n", - " Dashboard: http://127.0.0.1:54897/status\n", + " Dashboard: http://127.0.0.1:52532/status\n", " \n", " Memory: 12.80 GiB\n", @@ -1615,13 +679,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:54861\n", + " Nanny: tcp://127.0.0.1:52519\n", "
\n", - " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-nlturonv\n", + " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-vr2u8v0f\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1689,7 +753,7 @@ "
\n", - " Comm: tcp://127.0.0.1:54899\n", + " Comm: tcp://127.0.0.1:52530\n", " \n", " Total threads: 2\n", @@ -1652,7 +716,7 @@ "
\n", - " Dashboard: http://127.0.0.1:54900/status\n", + " Dashboard: http://127.0.0.1:52534/status\n", " \n", " Memory: 12.80 GiB\n", @@ -1660,13 +724,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:54863\n", + " Nanny: tcp://127.0.0.1:52520\n", "
\n", - " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-wu2vuab_\n", + " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-lctgep94\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1734,7 +798,7 @@ "
\n", - " Comm: tcp://127.0.0.1:54902\n", + " Comm: tcp://127.0.0.1:52538\n", " \n", " Total threads: 2\n", @@ -1697,7 +761,7 @@ "
\n", - " Dashboard: http://127.0.0.1:54903/status\n", + " Dashboard: http://127.0.0.1:52540/status\n", " \n", " Memory: 12.80 GiB\n", @@ -1705,13 +769,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:54862\n", + " Nanny: tcp://127.0.0.1:52521\n", "
\n", - " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-c67xq0c9\n", + " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-v2zyshjr\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1779,7 +843,7 @@ "
\n", - " Comm: tcp://127.0.0.1:54891\n", + " Comm: tcp://127.0.0.1:52531\n", " \n", " Total threads: 2\n", @@ -1742,7 +806,7 @@ "
\n", - " Dashboard: http://127.0.0.1:54892/status\n", + " Dashboard: http://127.0.0.1:52535/status\n", " \n", " Memory: 12.80 GiB\n", @@ -1750,13 +814,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:54860\n", + " Nanny: tcp://127.0.0.1:52522\n", "
\n", - " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-l9dnpx62\n", + " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-az6s0cco\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1828,7 +892,7 @@ "" ], "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -1847,12 +911,6 @@ "cell_type": "code", "execution_count": 14, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:25:43.284966Z", - "iopub.status.busy": "2022-07-02T03:25:43.284824Z", - "iopub.status.idle": "2022-07-02T03:26:09.934574Z", - "shell.execute_reply": "2022-07-02T03:26:09.934255Z" - }, "pycharm": { "name": "#%%\n" } @@ -1862,8 +920,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 4.25 s, sys: 559 ms, total: 4.81 s\n", - "Wall time: 12.5 s\n" + "CPU times: user 4.01 s, sys: 487 ms, total: 4.5 s\n", + "Wall time: 12.3 s\n" ] }, { @@ -1903,12 +961,6 @@ "cell_type": "code", "execution_count": 15, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:09.936350Z", - "iopub.status.busy": "2022-07-02T03:26:09.936234Z", - "iopub.status.idle": "2022-07-02T03:26:09.937984Z", - "shell.execute_reply": "2022-07-02T03:26:09.937719Z" - }, "pycharm": { "name": "#%%\n" } @@ -1922,12 +974,6 @@ "cell_type": "code", "execution_count": 16, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:09.939421Z", - "iopub.status.busy": "2022-07-02T03:26:09.939321Z", - "iopub.status.idle": "2022-07-02T03:26:09.949961Z", - "shell.execute_reply": "2022-07-02T03:26:09.949359Z" - }, "pycharm": { "name": "#%%\n" } @@ -1956,86 +1002,68 @@ " \n", " \n", " \n", - " \n", - " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -2048,113 +1076,95 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", "
\n", - " Comm: tcp://127.0.0.1:54890\n", + " Comm: tcp://127.0.0.1:52539\n", " \n", " Total threads: 2\n", @@ -1787,7 +851,7 @@ "
\n", - " Dashboard: http://127.0.0.1:54893/status\n", + " Dashboard: http://127.0.0.1:52542/status\n", " \n", " Memory: 12.80 GiB\n", @@ -1795,13 +859,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:54859\n", + " Nanny: tcp://127.0.0.1:52523\n", "
\n", - " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-worker-space/worker-eerlov4r\n", + " Local directory: /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-ta6kq5di\n", "
x1x2ax9y1y2c1c2some_arrayxopt_runtimexopt_error
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60.9769782.405552dummy_constant0.9769780.9769782.4055525.6417763.858635[1, 2, 3]0.03803920.2579541.0682570.2579541.0682570.2873600.3815030.040074False
70.4557402.939118dummy_constant0.4557400.4557402.9391187.9238555.951254[1, 2, 3]0.07459930.5487802.4533660.5487802.4533665.4130533.8180190.089152False
110.2320460.367798dummy_constant0.2320460.2320460.367798-0.7195460.089277[1, 2, 3]0.03671842.8994912.9860532.8994912.98605316.22631311.9380140.066158False
81.4944652.718696dummy_constant1.4944651.4944652.7186968.6434075.911574[1, 2, 3]0.05816350.2985410.9716180.2985410.9716180.0274430.2630100.067451False
..................
9980.8012000.637918dummy_constantNaN0.8012000.6379180.0723220.109743[1, 2, 3]0.0379579960.5280900.8117880.5280900.8117880.0359490.0980010.009233False
10060.4801760.997499dummy_constantNaN0.4801760.9974990.1630260.247899[1, 2, 3]0.0081769970.5028970.8257540.5028970.8257540.0130070.1061240.137924False
9891.2725880.147963dummy_constantNaN1.2725880.1479630.6691240.720823[1, 2, 3]0.1911399980.1849370.9813100.1849370.9813100.0958740.3309240.115444False
10020.5838170.787997dummy_constantNaN0.5838170.7879970.0330470.089968[1, 2, 3]0.0714449991.0318650.7887521.0318650.7887520.7394140.3662580.000516False
9970.8753230.596263dummy_constantNaN0.8753230.5962630.2206980.150134[1, 2, 3]0.10514010000.3626750.9637520.3626750.963752-0.0262110.2339240.055614False
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\n", + "

1000 rows × 8 columns

\n", "" ], "text/plain": [ - " x1 x2 a x9 y1 y2 \\\n", - "10 2.471422 0.488736 dummy_constant 2.471422 2.471422 0.488736 \n", - "6 0.976978 2.405552 dummy_constant 0.976978 0.976978 2.405552 \n", - "7 0.455740 2.939118 dummy_constant 0.455740 0.455740 2.939118 \n", - "11 0.232046 0.367798 dummy_constant 0.232046 0.232046 0.367798 \n", - "8 1.494465 2.718696 dummy_constant 1.494465 1.494465 2.718696 \n", - "... ... ... ... ... ... ... \n", - "998 0.801200 0.637918 dummy_constant NaN 0.801200 0.637918 \n", - "1006 0.480176 0.997499 dummy_constant NaN 0.480176 0.997499 \n", - "989 1.272588 0.147963 dummy_constant NaN 1.272588 0.147963 \n", - "1002 0.583817 0.787997 dummy_constant NaN 0.583817 0.787997 \n", - "997 0.875323 0.596263 dummy_constant NaN 0.875323 0.596263 \n", + " x1 x2 y1 y2 c1 c2 \\\n", + "8 2.716443 0.577442 2.716443 0.577442 6.810310 4.918616 \n", + "2 0.257954 1.068257 0.257954 1.068257 0.287360 0.381503 \n", + "3 0.548780 2.453366 0.548780 2.453366 5.413053 3.818019 \n", + "4 2.899491 2.986053 2.899491 2.986053 16.226313 11.938014 \n", + "5 0.298541 0.971618 0.298541 0.971618 0.027443 0.263010 \n", + "... ... ... ... ... ... ... \n", + "996 0.528090 0.811788 0.528090 0.811788 0.035949 0.098001 \n", + "997 0.502897 0.825754 0.502897 0.825754 0.013007 0.106124 \n", + "998 0.184937 0.981310 0.184937 0.981310 0.095874 0.330924 \n", + "999 1.031865 0.788752 1.031865 0.788752 0.739414 0.366258 \n", + "1000 0.362675 0.963752 0.362675 0.963752 -0.026211 0.233924 \n", "\n", - " c1 c2 some_array xopt_runtime xopt_error \n", - "10 5.446776 3.886633 [1, 2, 3] 0.011140 False \n", - "6 5.641776 3.858635 [1, 2, 3] 0.038039 False \n", - "7 7.923855 5.951254 [1, 2, 3] 0.074599 False \n", - "11 -0.719546 0.089277 [1, 2, 3] 0.036718 False \n", - "8 8.643407 5.911574 [1, 2, 3] 0.058163 False \n", - "... ... ... ... ... ... \n", - "998 0.072322 0.109743 [1, 2, 3] 0.037957 False \n", - "1006 0.163026 0.247899 [1, 2, 3] 0.008176 False \n", - "989 0.669124 0.720823 [1, 2, 3] 0.191139 False \n", - "1002 0.033047 0.089968 [1, 2, 3] 0.071444 False \n", - "997 0.220698 0.150134 [1, 2, 3] 0.105140 False \n", + " xopt_runtime xopt_error \n", + "8 0.001578 False \n", + "2 0.040074 False \n", + "3 0.089152 False \n", + "4 0.066158 False \n", + "5 0.067451 False \n", + "... ... ... \n", + "996 0.009233 False \n", + "997 0.137924 False \n", + "998 0.115444 False \n", + "999 0.000516 False \n", + "1000 0.055614 False \n", "\n", - "[1000 rows x 11 columns]" + "[1000 rows x 8 columns]" ] }, "execution_count": 16, @@ -2170,12 +1180,6 @@ "cell_type": "code", "execution_count": 17, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:09.951480Z", - "iopub.status.busy": "2022-07-02T03:26:09.951390Z", - "iopub.status.idle": "2022-07-02T03:26:09.961699Z", - "shell.execute_reply": "2022-07-02T03:26:09.961455Z" - }, "pycharm": { "name": "#%%\n" } @@ -2204,13 +1208,10 @@ " 		x1x2ax9y1y2c1c2some_arrayxopt_runtimexopt_errorfeasible_c1
90.5476231.169586dummy_constant0.5476230.5476231.1695860.5928540.450613[1, 2, 3]0.11082320.2579541.0682570.2579541.0682570.2873600.3815030.040074FalseTrueTrueTrue
260.9800030.426040dummy_constant0.9800030.9800030.4260400.0457610.235873[1, 2, 3]0.08144150.2985410.9716180.2985410.9716180.0274430.2630100.067451FalseTrueTrueTrue
180.9227110.491246dummy_constant0.9227110.9227110.4912460.0900820.178761[1, 2, 3]0.171685200.5028970.9886820.5028970.9886820.1984440.2388180.046855FalseTrueTrueTrue
660.4324591.093330dummy_constant0.4324590.4324591.0933300.2856680.356603[1, 2, 3]0.087319250.7617180.9945070.7617180.9945070.6204760.3130330.155186FalseTrueTrueTrue
720.5048301.092646dummy_constant0.5048300.5048301.0926460.3686250.351253[1, 2, 3]0.009447390.9248120.5973080.9248120.5973080.3089620.1899340.122035FalseTrueTrue..................
10001.0486560.099549dummy_constantNaN1.0486560.0995490.1039460.461385[1, 2, 3]0.0149059950.5028470.8344520.5028470.8344520.0225100.1118660.125600FalseTrueTrueTrue
9980.8012000.637918dummy_constantNaN0.8012000.6379180.0723220.109743[1, 2, 3]0.0379579960.5280900.8117880.5280900.8117880.0359490.0980010.009233FalseTrueTrueTrue
10060.4801760.997499dummy_constantNaN0.4801760.9974990.1630260.247899[1, 2, 3]0.0081769970.5028970.8257540.5028970.8257540.0130070.1061240.137924FalseTrueTrueTrue
10020.5838170.787997dummy_constantNaN0.5838170.7879970.0330470.089968[1, 2, 3]0.0714449980.1849370.9813100.1849370.9813100.0958740.3309240.115444FalseTrueTrueTrue
9970.8753230.596263dummy_constantNaN0.8753230.5962630.2206980.150134[1, 2, 3]0.1051409991.0318650.7887521.0318650.7887520.7394140.3662580.000516FalseTrueTrue
\n", - "

439 rows × 14 columns

\n", + "

474 rows × 11 columns

\n", "
" ], "text/plain": [ - " x1 x2 a x9 y1 y2 \\\n", - "9 0.547623 1.169586 dummy_constant 0.547623 0.547623 1.169586 \n", - "26 0.980003 0.426040 dummy_constant 0.980003 0.980003 0.426040 \n", - "18 0.922711 0.491246 dummy_constant 0.922711 0.922711 0.491246 \n", - "66 0.432459 1.093330 dummy_constant 0.432459 0.432459 1.093330 \n", - "72 0.504830 1.092646 dummy_constant 0.504830 0.504830 1.092646 \n", - "... ... ... ... ... ... ... \n", - "1000 1.048656 0.099549 dummy_constant NaN 1.048656 0.099549 \n", - "998 0.801200 0.637918 dummy_constant NaN 0.801200 0.637918 \n", - "1006 0.480176 0.997499 dummy_constant NaN 0.480176 0.997499 \n", - "1002 0.583817 0.787997 dummy_constant NaN 0.583817 0.787997 \n", - "997 0.875323 0.596263 dummy_constant NaN 0.875323 0.596263 \n", - "\n", - " c1 c2 some_array xopt_runtime xopt_error feasible_c1 \\\n", - "9 0.592854 0.450613 [1, 2, 3] 0.110823 False True \n", - "26 0.045761 0.235873 [1, 2, 3] 0.081441 False True \n", - "18 0.090082 0.178761 [1, 2, 3] 0.171685 False True \n", - "66 0.285668 0.356603 [1, 2, 3] 0.087319 False True \n", - "72 0.368625 0.351253 [1, 2, 3] 0.009447 False True \n", - "... ... ... ... ... ... ... \n", - "1000 0.103946 0.461385 [1, 2, 3] 0.014905 False True \n", - "998 0.072322 0.109743 [1, 2, 3] 0.037957 False True \n", - "1006 0.163026 0.247899 [1, 2, 3] 0.008176 False True \n", - "1002 0.033047 0.089968 [1, 2, 3] 0.071444 False True \n", - "997 0.220698 0.150134 [1, 2, 3] 0.105140 False True \n", + " x1 x2 y1 y2 c1 c2 xopt_runtime \\\n", + "2 0.257954 1.068257 0.257954 1.068257 0.287360 0.381503 0.040074 \n", + "5 0.298541 0.971618 0.298541 0.971618 0.027443 0.263010 0.067451 \n", + "20 0.502897 0.988682 0.502897 0.988682 0.198444 0.238818 0.046855 \n", + "25 0.761718 0.994507 0.761718 0.994507 0.620476 0.313033 0.155186 \n", + "39 0.924812 0.597308 0.924812 0.597308 0.308962 0.189934 0.122035 \n", + ".. ... ... ... ... ... ... ... \n", + "995 0.502847 0.834452 0.502847 0.834452 0.022510 0.111866 0.125600 \n", + "996 0.528090 0.811788 0.528090 0.811788 0.035949 0.098001 0.009233 \n", + "997 0.502897 0.825754 0.502897 0.825754 0.013007 0.106124 0.137924 \n", + "998 0.184937 0.981310 0.184937 0.981310 0.095874 0.330924 0.115444 \n", + "999 1.031865 0.788752 1.031865 0.788752 0.739414 0.366258 0.000516 \n", "\n", - " feasible_c2 feasible \n", - "9 True True \n", - "26 True True \n", - "18 True True \n", - "66 True True \n", - "72 True True \n", - "... ... ... \n", - "1000 True True \n", - "998 True True \n", - "1006 True True \n", - "1002 True True \n", - "997 True True \n", + " xopt_error feasible_c1 feasible_c2 feasible \n", + "2 False True True True \n", + "5 False True True True \n", + "20 False True True True \n", + "25 False True True True \n", + "39 False True True True \n", + ".. ... ... ... ... \n", + "995 False True True True \n", + "996 False True True True \n", + "997 False True True True \n", + "998 False True True True \n", + "999 False True True True \n", "\n", - "[439 rows x 14 columns]" + "[474 rows x 11 columns]" ] }, "execution_count": 17, @@ -2468,12 +1423,6 @@ "cell_type": "code", "execution_count": 18, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:09.963345Z", - "iopub.status.busy": "2022-07-02T03:26:09.963213Z", - "iopub.status.idle": "2022-07-02T03:26:10.293817Z", - "shell.execute_reply": "2022-07-02T03:26:10.293540Z" - }, "pycharm": { "name": "#%%\n" } @@ -2481,7 +1430,7 @@ "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -2489,7 +1438,7 @@ "metadata": { "image/png": { "height": 432, - "width": 434 + "width": 474 } }, "output_type": "display_data" @@ -2505,12 +1454,6 @@ "cell_type": "code", "execution_count": 19, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:10.295507Z", - "iopub.status.busy": "2022-07-02T03:26:10.295345Z", - "iopub.status.idle": "2022-07-02T03:26:10.342537Z", - "shell.execute_reply": "2022-07-02T03:26:10.342244Z" - }, "pycharm": { "name": "#%%\n" } @@ -2518,7 +1461,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -2526,7 +1469,7 @@ "metadata": { "image/png": { "height": 432, - "width": 440 + "width": 446 } }, "output_type": "display_data" @@ -2542,12 +1485,6 @@ "cell_type": "code", "execution_count": 20, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:10.344200Z", - "iopub.status.busy": "2022-07-02T03:26:10.344081Z", - "iopub.status.idle": "2022-07-02T03:26:10.386366Z", - "shell.execute_reply": "2022-07-02T03:26:10.386051Z" - }, "pycharm": { "name": "#%%\n" } @@ -2555,7 +1492,7 @@ "outputs": [ { "data": { - "image/png": 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", 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NGJfLb1vaiXaHtr3u6Yf9Rcs35JL6xbvcbWPZ2o25/Lal+crPnsgNdVMzbcKIstUBAABQFFMqymi//fbLySefnCS58847dzut4tZbb83Gja885J599tndVl9/MWvK6Iys6VhIM7KmKmdNOSTJKw/7J1xzdy6/belOIyW2PeyfcM3dWbR8Q2E1b2/R8g2pm/vQXrf2XN/QnLq5D5WtDgAAgCIJHLrg5ptvTkVFRSoqKnLllVfu8pxLL700SdLS0pK/+Zu/SWvrjnPy161bl7//+79PkgwfPjwXXXRRWWvuj2qqK3ND3dRUVbbvdq6qHJQbz5mamurKHn/Yb2hqySX1i9PcsrVd5ze3bM0l9YvTYLFLAACglxuwUyoeeOCBPPnkk23/vm7durbXTz75ZG6++eYdzj///PM71c9b3/rWvPe97828efPywx/+MKeccko++tGP5pBDDslvfvObXHXVVVm5cmWS5Itf/GIOOOCATvUz0E2bMCL1F07f7bSEbUbWVOXGc6bm6PEjOv2wf9+cmYVNr5i/ZM1ew45XW9/QnNuXPJ3Z08cVUgMAAEA5DNjA4Rvf+Ea+9a1v7fLYL37xi/ziF7/Y4WedDRyS5Jvf/GY2btyYH//4x7n77rtz991373B80KBB+fSnP52LL764033wSuhw35yZuX3J06lfuCKPbTc9YvKo2tTNODRnTTmkLSzoDQ/79QtXdrLdCoEDAADQqw3YwKE7DR06NAsWLMh3v/vd3HzzzXnkkUfypz/9Ka95zWty/PHH58Mf/nCOOeaYni6zX6iprszs6eMye/q4ve420dMP+43NrZ3aXSNJHlu7MY3Nrd26iwYAAEBHVJRKpVJPF0F5rV69OmPHjk2SrFq1KmPGjOnhinpeY3NrJl3x0063X/a5t3X5Yf/5TU05+qo7O93+4cv/IgftV92lGgAAAMr1zGjRSAakzV1cdLGr7ZNkWBfXgRhWXZk1LzTml0+uy5oXGrtcDwAAQJFMqWBAKuJhv6uGVg3OpFG1nZpWMaRyUCZf8dNsPzypIsmfjdk/X33vlIw/cFiX6wMAAOgKIxwYkLY97HfG5FG1ha2dUDejc2tBbGnZmlfPhSoleWT1iznp2nvzuR/9tsu1AQAAdIXAgQGrsw/7dTMOLayGWVNGZ2RNVWHX2+abv3hK6AAAAPQogQMDVmce9kfWVOWsKYcUVkNNdWVuqJuaqsri/yh+8xdP5al1mwu/LgAAQHsIHBiwOvqwX1U5KDeeMzU1BazfsL1pE0ak/sLpZRnp8NF5jxR+TQAAgPYQODCgtfdhf2RNVb5z0fQcPX5E2eq4b87MXH32kZn8qrUlXv3vHfHI6j91sTIAAIDOsUsFA962h/3blzyd+oUr8th2u0ZMHlWbuhmH5qwphxQ+suHVaqorM3v6uMyePi6Nza3Z3NSSYdWV2dDQnGO/9PNOXbOUZM0LjRl9wNBiiwUAANgLgQNk9w/7Re1G0VFDqwa39b1yZUOXrrVyfYPAAQAA6HYCB3iV7R/2e4NxI2t6tD0AAEBnWMMBernRBwxNRSfbVvy/9gAAAN1N4AB9wOjhQzrZTtgAAAD0DIED9AHVlZ2b4jGknVt+AgAAFM3TCPRyjc2t+cO6zi0c+eS6hjQ2txZcEQAAwN4JHKCX29zUUkj7xubWPL+pSQABAAB0C7tUQC83rLprf0wXPPp0vver1Vm2dmPbzyaNqk3djHGZNWV0arp4fQAAgF0xwgF6uaFVgzNpVG2n2g4eVJErf/TYDmFDkixbuzGX37Y0J1xzdxYt31BEmQAAADsQOEAfUDdjXKfatW4t7fH4+obm1M19aJehgykYAABAVxhLDX3ArCmj85WfPZH1Dc2FX7u5ZWsuqV+c++bMTJLMX7Im9QtXmoIBAAB0iREO0AfUVFfmhrqpqSrTNpfrG5rzj3f+Pidcc3cuv22pKRgAAECXCRygj5g2YUTqL5yekTVVezxv8KCKTl3/G/f/ca8jKPY0BQMAAGB7AgfoQ6ZNGJH75szM1WcfmcmvWkhy8qjaXHnmG/a6bsPutLfVtikYDV3crhMAAOjfTMaGPqamujKzp4/L7Onj0tjcms1NLRlcUZHWUilbXm7NlT/6bdlrWN/QnNuXPJ3Z0zu3mCUAAND/CRygj2poatnlAo/dpX7hCoEDAACwWwIH6IMWLd+QS+oXl2XXivZ6bO3GNDa3ZmjV4B6rAQAA6L0EDtDHLFq+IXVzH0pzy9aeLiWbm1oEDgAAwC5ZNBL6kIamllxSv7hXhA1JMqxaZgkAAOyawAH6kPlL1vToNIrtTR5Va3QDAACwWwIH6EPqF67s6RLa1M04tKdLAAAAejGBA/QRjc2tPbIbxa6MrKnKWVMO6ekyAACAXkzgAH3E5qaWLrW/f87M3D9nZpfrqKoclBvPmZoa6zcAAAB7IHCAPqKrCzQeOKw6Y0fsm0mjajt9jZE1VfnORdNz9PgRXaoFAADo/wQO0EcMrRrc6bBg+wUe62aM69Q1Zk0ZnfvmzBQ2AAAA7SJwgD6ks2HB9gs8zpoyOiNrqjrUfmRNVa46+42mUdAvrHmhMb98cl3WvNDY06UAAPRrnh6gD5k1ZXS+8rMnOrQ15qsXeKyprswNdVNTN/ehNLds3Wt7azbQ12zY3JznNm3JwfsNyYhhr4RrT63bnL+dtySPrn4xpe3OrUjyZ2P2z1ffOyXjDxzW9vPG5tas29yU5JXpSLaABQDoOE8Q0IcUFRZMmzAi9RdOzyX1i/cYXoysqcqN50w1jYJe77mNW3LVj5flp0ufSdN2fzaqKwdl9PAh+eO6l3bZrpTkkdUv5qRr7805Mw7NhIP2zY33/DHPbWra4bzX7j8kFx9/WN599NgMqqjI5qaWDKuuFEQAAOxBRalUKu39NPqy1atXZ+zYsUmSVatWZcyYMT1cEV21aPmGQsKChqaW3L7k6dQvXJHHtttyc/Ko2tTNODRnTTnEyAZ6vW89+FSu/OFv0x1/mQ2qSLZu19GkUbWpmzEus6aM9mcFAOizyvXMKHAYAAQO/VPRYUFjc6vf2tLnfOvBp/KZH/62p8vIyJqq3FA3NdMmGA0EAPQ95Xpm9OsY6KNqqisze/q4zJ4+rpCwYGjVYEEDfcpzG7fkyl4QNiTJ+obm1M19KPUXThc6AAD8P3apgH5gaNXgHLSfhe0YWK768bJumUbRXs0tW3NJ/eI0NLX0dCkAAL2CwAGAPumnS5/p6RJ2sr6hObcvebqnywAA6BUEDgD0ORs2N++wG0VvUr9wRU+XAADQKwgcAOhzntu0padL2K3H1m5MY3NrT5cBANDjBA4A9DkH7zekp0vYo83WcQAAEDgA0PeMGFaV6sre+1fYsA5sSQsA0F/13m9rALAHb3vja3u6hF2aPKrWjjEAABE4ANBHXX76pFT0dBG7UDfj0J4uAQCgVxA4ANAnHVw7JFf+5Rt6uowdjKypyllTDunpMgAAegWBAwB91nlvGZ/P/uUb2jXSYfTwoWUdEVFVOSg3njM1NdZvAABIkvhWBECfdt5bxuftb3xtrv7x4/np0rXZ0rK17diQykF52xtH5bLTj8jBta/sbLHmhcasXN+QcSNrMvqAofnWg0/lyh/+NqUu1DCypio3njM1R48f0cV3AwDQf1SUSqWufMeiD1i9enXGjh2bJFm1alXGjBnTwxUBlM+Gzc15btOWHLzfkIwYVtWuNs9t3LLLwKJqUHLqG0fl0lMn5sE/bEj9whV5bO3GtuOTR9WmbsahOWvKIUY2AAB9VrmeGX07AqBfGTGsqt1BwzYH1w7JP753SpIpuw0sxh84LLOnj0tjc2s2N7VkWHWl3SgAAPZA4AAA29lbYDG0arCgAQCgHSwaCQAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAZdbY3JrnNzWlsbm1p0sBAOg2lT1dAAD0Rw1NLZm/ZE3qF67MsrUb234+aVRt6maMy6wpo1NT7a9hAKD/8k0HAAq2aPmGXFK/OOsbmnc6tmztxlx+29J85WdP5Ia6qZk2YUQPVAgAUH6mVABAgRYt35C6uQ/tMmzY3vqG5tTNfSiLlm/opsoAALqXwAEACtLQ1JJL6henuWVru85vbtmaS+oXp6GppcyVAQB0P4EDABRk/pI1ex3Z8GrrG5pz+5Kny1QRAEDPETgAQEHqF67sZLsVBVcCANDzBA4AUIDG5tYddqPoiMfWbrRlJgDQ7wgcAKAAm7u4DkNX2wMA9DYCBwAowLDqru003dX2AAC9jcABAAowtGpwJo2q7VTbyaNqM7RqcMEVAQD0LIEDABSkbsa4TrY7tOBKAAB6nsABAAoya8rojKyp6lCbkTVVOWvKIWWqCACg5wgcAKAgNdWVufrsN2ZQRfvOr6oclBvPmZoa6zcAAP2QwAEACvKtB5/K/6r/r2wt7f3ckTVV+c5F03P0+BHlLwwAoAf4lQoAFOBbDz6Vz/zwt+0+/+ITDxM2AAD9mhEOANBFz23ckis7EDYkyRd+/Hie27ilTBUBAPQ8gQMAdNFVP16Wdsyi2EEpydU/frwc5QAA9AoCBwDoop8ufaaT7dYWXAkAQO8hcACALtiwuTlNLVs71XZLy9Zs2NxccEUAAL2DwAEAuuC5TV1bh6Gr7QEAeiuBAwB0wcH7DenR9gAAvZXAAQC6YMSwqlRXdu6v0yGVgzJiWFXBFQEA9A4CBwDoore98bWdbDeq4EoAAHoPgQMAdNHlp09KRQfbVCS57PQjylEOAECvIHAAgC46uHZIrvzLN3SozWfPekMOrrV+AwDQfwkcAKAA571lfD77l2/Y60iHiiSfO+sNOfeY8d1QFQBAz6ns6QIAoL847y3j8/Y3vjZX//jx/HTp2mxp2dp2bEjloLztjaNy2elHGNkAAAwIAgcAKNDBtUPyj++dkmRKNmxuznObtuTg/YbYjQIAGHAEDgBQJiOGVQkaAIAByxoOAAAAQOEEDgAAAEDhBA4AAABA4QQOAAAAQOEEDgAAAEDhBA4AAABA4QQOAAAAQOEEDgAAAEDhBA4AAABA4QQOAFBma15ozC+fXJc1LzT2dCkAAN2msqcLAID+6Kl1m/O385bk0dUvprTdzyuS/NmY/fPV907J+AOH9VR5AABlZ4QDABTscz/6bU669t488qqwIUlKSR5Z/WJOuvbefO5Hv+2J8gAAuoXAAQAK9Lkf/Tbf/MVT7Tr3m794SugAAPRbAgcAKMhT6za3O2zY5pu/eCpPrdu81/Mam1vz/KamNDa3dugYAEBPsYYDABTkb+ct6VS7j857JPM/fOxOP29oasn8JWtSv3Bllq3d2PbzSaNq8z+PGp2KUkW+v3j1TsfqZozLrCmjU1Nd/r/mG5tbs7mpJcOqKzO0anDZ+wMA+g6BAwAU5NHVL3aq3SOr/7TTzxYt35BL6hdnfUPzTseWrd2Yz/1o404/33bs8tuW5is/eyI31E3NtAkjOlXTnuwpCOnOsIPd2xYEDa6oSGupJBACoEf4NgAABVjzQuNOC0S2V+n/tR99wNAkr4QNdXMfSnPL1k7Xs76hOXVzH0r9hdMLDR32FoSUO+xg97YFQbf8ckV+98ymnY6//jX75dy3HCoQAqDbWMMBAAqwcn1Dl9r/7Ldrk7zy0HhJ/eIuhQ3bNLdszSX1i9PQ1NLlayX/HYTsKmzY3rawY9HyDYX0y94tWr4hJ1xzdy6/bekuw4Yk+d2zm3L5bUtzwjV3+38DQLcQOABAAcaNrOlS+6/e9fu231Dv7YG+I9Y3NOf2JU93+TodDUKKDjvYvfYGQdsIhADoLgIHACjA6AOGpqIL7f/U2JLblzyd+oUrC6tpm/qFK7p8jc4EIUWFHexeZ0fECIQA6A4CBwAoyJ+N2b9L7W/55VM7LMJYlMfWbuzylpmdDUKKCDvYva6MiBEIAVBuAgcAKMhX3zulS+0f383c+yJs7sJvshubWzsdhBQRdrB7XR0RIxACoJwEDgBQkPEHDsv7jh7T02Xs0rAu7ErQlbCiiPbsWleCoG0EQgCUk8ABAAp0xZlv7FL7I167X0GV/LfJo2oztGpwp9t3Jawooj27VlSQIxACoFwEDgBQoK482CfJOcccWlAl/61uRteuObRqcCaNqu1U266GHexeUUGOQAiAchE4AECB1rzQ2KX208aPyMiaqoKqSUbWVOWsKYd0+Tp1M8Z1sl3xAQqv6EoQtI1ACIByEjgkWblyZS699NJMmjQpNTU1GTFiRKZNm5Zrr702L730UiF9PPbYY/nIRz6SI488MrW1tamqqspBBx2UmTNn5vrrr8+mTeVbKAyA7rNyfUOX2q/b1JQb6qamqrLrf0VXVQ7KjedMTU0Bv8GeNWV0h4OQosIOdq+zQdB/txcIAVA+Az5wWLBgQf7sz/4s1113XR5//PG89NJLeeGFF/Lwww/n7/7u7/LmN785f/zjH7vUx3XXXZc///M/zz//8z9n6dKl2bRpU15++eWsW7cu99xzTz7+8Y/nyCOPzKOPPlrQuwKgp4wbWdPl9tMmjEj9hdO7NNJhZE1VvnPR9Bw9fkSX6tmmprqyQ0FIkWEHu9eZIGgbgRAA5TagA4dHHnkk7373u/Piiy9m2LBhueqqq/Lggw/mrrvuygc+8IEkye9+97ucccYZ2bx5c6f6+P73v59LL700LS0tqaqqysc+9rEsWLAgDz30UL773e/muOOOS5KsWLEib3vb2/Liiy8W9v4A6H6jDxiaik62rfh/7ZNk2oQRuW/OzFx99pGZ/Kph85NH1eYzZ07OZ86cvMtjV599ZO6bM7OwsGGb9gYhRYcd7F5Hg6BtBEIAdIeKUqlU6ukiesrMmTNzzz33pLKyMvfdd1+OOeaYHY5/+ctfzpw5c5Ikn/3sZ3PFFVd0uI8jjzwyS5cuTZLccccdOeOMM3Y6513velduvfXWJK+Mhvj4xz/e4X72ZPXq1Rk7dmySZNWqVRkzpndu2QbQX5z1zw/kkdUdD5CnjBme+R8+dpfHGptbs7mpJcOqK3eac7+nY+XQ0NSS25c8nfqFK/LYdtsyTh5Vm7oZh+asKYd4kO1mi5ZvyCX1i7O+oXmv546sqcqN50wVCAHQplzPjAM2cHj44Yczbdq0JMnFF1+cG2+8cadztm7dmje+8Y1ZtmxZDjjggDz77LPZZ5992t3Hxo0bs//++ydJ3vzmN2fx4sW7PO/RRx/Nn//5nyd5JXz4wQ9+0NG3s0cCB4Du9dS6zTnp2ns73O6eS0/M+AOHlaGi8unusGMg29t/621B0C2/fCqPP7Pz2lBHvGa/nPuW8QIhAHZSrmfGAfu3zfz589teX3DBBbs8Z9CgQTn33HPzqU99Ki+88ELuueeenHLKKe3uo7n5v3/LcNhhh+32vNe97nVtr5uamtp9fQB6p/EHDstfHzs+3/zFU+1uc+Fx4/tc2JC8slOCoKF8GppaMn/JmtQvXJll240mmTSqNnUzxmXWlNFt4UFNdWVmTx+X2dPHtYUTgysq0loqCYQA6BEDdg2H+++/P0lSU1OTqVOn7va8E088se31Aw880KE+DjzwwIwY8cpwxT0tPPmHP/yh7fXEiRM71AcAvdMVZ74hf33s+Hade+Fx4/Ppd7yhvAXR5yxaviEnXHN3Lr9t6Q5hQ5IsW7sxl9+2NCdcc3cWLd+wU9uhVYNz0H7VGTGsKgftVy1sAKBHDNjAYdmyZUmSww8/PJWVux/occQRR+zUpiM++MEPJkn+67/+Kz/5yU92ec7nP//5JMngwYNz0UUXdbgPAHqnK858Q+659MRMGTN8p4UkK/LKmg33XHqisIGdLFq+IXVzH9rrmgzrG5pTN/ehXYYOANDTBuSUii1btmTdunVJste5KQcccEBqamrS0NCQVatWdbivyy+/PL/61a9y55135uyzz86HP/zhnHzyyTnwwAPzxz/+MTfccEPuvffeDB48OP/0T/+USZMmdbiP1atX7/H42rVrO3xNAIox/sBhbQtBrnmhMSvXN2TcyJq23Sjg1RqaWnJJ/eI0t2xt1/nNLVtzSf3i3DdnprUZAOhVBuTfSps2/fdCSsOG7X2+7LbAoTNbYw4bNiw/+clPcvPNN+eLX/xirrvuulx33XU7nPPOd74zc+bMyfTp0zt8/SRti3sA0LuNPmCooIG9mr9kTbt2m9je+obm3L7k6cyePq5MVQFAxw3IKRVbtmxpe11Vtee9xJOkuro6SdLY2Nip/n71q1/l3/7t33a7jsOdd96Zb33rW9m4ceMujwMAA0f9wpWdbLei4EoAoGsGZOAwZMiQttfb7ySxO9t2jhg6tOO/lfrBD36Qk046KT//+c9z5JFH5rbbbsv69evT3NycP/zhD7n66qvz8ssv54Ybbshb3vKWPPPMMx3uY9WqVXv8Z9GiRR2+JgDQ/RqbW3daILK9Hlu7MY3NrQVXBACdNyCnVOy3335tr9szTaKhoSFJ+6ZfbO/ZZ5/N+eefn6amprzhDW/Igw8+mJqamrbjhx12WD71qU9l2rRpOeWUU/Lb3/42H/nIR/Lv//7vHeqnqD1SAYCetbmppcvt7UgBQG8xYEc4HHjggUn2vuDiCy+80BY4dHSthHnz5rW1veyyy3YIG7Z38skn5+STT06S3HrrrXnhhRc61A8A0D8M6+Kij11tDwBFGpCBQ5K23SCefPLJtLTs/rcJjz/++E5t2mv7bTTf/OY37/HcqVOnJkm2bt2aJ554okP9AEBPaWxuzfObmgzlL8jQqsGZNKq2U20nj6o1ugGAXmXAxuDHHXdc7r///jQ0NGTx4sW73SHi3nvvbXt97LHHdqiPysr//s+7p1AjSV5++eVdtgOA3qahqSXzl6xJ/cKVO6w3MGlUbepmjMusKaNtz9gFdTPG5fLblnai3aFlqAYAOm/AjnCYNWtW2+ubbrppl+ds3bo1t9xyS5Jk+PDhmTlzZof6mDBhQtvr+++/f4/n3nfffUmSioqKjB8/vkP9AEB3WbR8Q0645u5cftvSnRY3XLZ2Yy6/bWlOuObuLFq+oYcq7PtmTRmdkTV730VreyNrqnLWlEPKVBEAdM6ADRymTZuW448/Pkkyd+7c/PKXv9zpnOuuu65tWsTf/u3fZp999tnh+M0335yKiopUVFTkyiuv3Kn9GWeckYqKiiTJVVddlTVr1uyylq9//ev51a9+lSSZMWNGRo4c2en3BQDlsmj5htTNfSjrG/a8w9P6hubUzX1I6NBJNdWVuaFuaqoq2/c1rapyUG48Z6pRJQD0OgM2cEiSr371qxk6dGhaWlpy6qmn5gtf+EIWLlyYu+++OxdffHHmzJmTJJk4cWI+8YlPdPj6RxxxRC644IIkyZo1a/KmN70pV199de6///4sWbIkP/rRj/L+978/F198cZJk8ODBufrqq4t7gwBQkIamllxSvzjNLVvbdX5zy9ZcUr84DV3cdWGgmjZhROovnL7XkQ4ja6rynYum5+jxI7qpMgBovwEdhb/pTW/K9773vdTV1WXjxo257LLLdjpn4sSJWbBgwQ5baXbE1772tTQ0NOR73/tenn/++Vx++eW7PK+mpiZf//rXc9JJJ3WqHwAop/lL1ux1ZMOrrW9ozu1Lns7s6ePKVFX/Nm3CiNw3Z2ZuX/J06heuyGPbTWGZPKo2dTMOzVlTDjGyAYBea8D/DXXmmWfm0UcfzVe/+tUsWLAgq1evTlVVVQ4//PD8z//5P/PhD384++67b6evX11dnXnz5uXiiy/OzTffnIULF2bNmjVpampKbW1tXv/61+cv/uIv8sEPfjBjxowp8J0BQHHqF67sZLsV3R44bNjcnOc2bcnB+w3JiGEdWwuht6mprszs6eMye/q4NDa3ZnNTS4ZVV9qNAoA+oaJUKpV6ugjKa/Xq1Rk7dmySZNWqVYINADqksbk1k674aafbL/vc28r+gPzcxi256sfL8tOlz6Rpu2kf1ZWD8rY3vjaXnz4pB9cOKWsNANBXleuZcUCv4QAA7N3mLq7D0NX2e/OtB5/K9Kvvyu1Lnt4hbEiSppatuX3J05l+9V351oNPlbUOAGBHA35KBQCwZ8O6uEZAV9vvybcefCqf+eFv93peKWk777y3jC9bPQDAfzPCAQDYo6FVgzNpVG2n2k4eVVu26RTPbdySK9sRNmzvyh/+Ns9t3FKWegCAHQkcAIC9qpvRuYUf62YcWnAl/+2qHy9LRxeiKiW5+sePl6McAOBVBA4AwF7NmjI6I2s6tuPDyJqqnDXlkDJVlPx06TOdbLe24EoAgF0ROAAAe1VTXZkb6qamqrJ9Xx2qKgflxnOmpqZM6zds2Ny80wKR7bWlZWs2bG4uuCIA4NUEDgBAu0ybMCL1F07f60iHkTVV+c5F03P0+BFlq+W5TV1bh6Gr7QGAvbNLBQDQbtMmjMh9c2bm9iVPp37hijy2dmPbscmjalM349CcNeWQso1s2Obg/Yb0aHsAYO8EDgBAh9RUV2b29HGZPX1cGptbs7mpJcOqK8u2G8WujBhWlerKQZ2aVjGkclBGDOvYehQAQMeZUgEAdNrQqsE5aL/qbg0btnnbG1/byXajCq4EANgVgQMA0CddfvqkVHSwTUWSy04/ohzlAACvInAAAPqkg2uH5Mq/fEOH2nz2rDfk4FrrNwBAdxA4AAB91nlvGZ/P/uUb9jrSoSLJ5856Q849Znw3VAUAJBaNBAD6uPPeMj5vf+Nrc/WPH89Pl67Nlu0WkhxSOShve+OoXHb6EUY2AEA3EzgAAH3ewbVD8o/vnZJkSjZsbs5zm7bk4P2G2I0CAHqQwAEA6FdGDKsSNABAL2ANBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcJXd0ckLL7yQ5cuXZ9CgQTn88MMzbNiwdrV78cUXc/vttydJzj333HKWCAAAABSorCMcHn300Zxyyik5+OCDc/TRR2fq1KkZOXJkzjrrrDz66KN7bb969eqcf/75+eu//utylgkAAAAUrGyBwz333JNjjz02P//5z9Pa2ppSqZRSqZSXX345d9xxR4466qh8/vOfT6lU2uu12nMOAAAA0HuUZUrFiy++mPe9731paGhIkhx11FE56aST0tTUlHvvvTePPvpoWlpacuWVV+ZXv/pVvv/976e6urocpQAAAAA9oCyBwze+8Y08++yzqaioyD/90z/lb/7mb3Y4vmDBgnz4wx/OihUrcscdd+S0007Lj370o+y3337lKAcAAADoZmWZUnHHHXekoqIi73nPe3YKG5LkjDPOyH/913/ltNNOS6lUyv3335+TTz45GzZsKEc5AAAAQDcrS+Dw29/+Nkny/ve/f7fnHHDAAVmwYEE+8IEPpFQqZfHixTnxxBPzzDPPlKMkAAAAoBuVJXB48cUXkyRjxozZc+eDBuVf/uVf8vd///cplUp57LHHcsIJJ2TVqlXlKAsAAADoJmUJHPbdd98kyZ/+9Kd2nf+FL3whX/jCF1IqlfKHP/whxx9/fJ588slylAYAAAB0g7IEDocddliS5JFHHml3m7//+7/PP//zPydJVq1alRNOOCG/+c1vylEeAAAAUGZlCRymTp2aUqmUn/70px1q96EPfSg333xzBg0alGeffTbnn39+OcoDAAAAyqwsgcPJJ5+cJPm///f/Zs2aNR1qe8455+R73/te9tlnn7z88svlKA8AgH6isbk1z29qSmNza0+XAsCrVJbjoqeffnqqqqrS3Nycq666Kl/72tc61P6d73xnfvjDH+ad73xnXnrppXKUCABAH9XQ1JL5S9akfuHKLFu7se3nk0bVpm7GuMyaMjo11WX5mgtAB5Tlk3i//fbL/Pnzs379+uyzzz6dusapp56au+66q8PTMgAA6L8WLd+QS+oXZ31D807Hlq3dmMtvW5qv/OyJ3FA3NdMmjOiBCgHYpqJUKpV6ugjKa/Xq1Rk7dmySVxbk3Nt2pQAAvdGi5RtSN/ehNLds3eu5VZWDUn/hdKEDQDuU65mxLGs47MoXv/jFrF27tru6AwCgH2loaskl9YvbFTYkSXPL1lxSvzgNTS1lrgyA3em2wOGyyy7LoYcemjPPPDPz589PS4sPfwAA2mf+kjW7nEaxJ+sbmnP7kqfLVBEAe9NtgUOStLS05Mc//nHe9a53ZfTo0bn00kvz29/+tjtLAACgD6pfuLKT7VYUXAkA7dVtgcNvfvObfPSjH82BBx6YUqmU559/Ptdff33+7M/+LDNmzMi//uu/ZtOmTd1VDgAAfURjc+sOu1F0xGNrN9oyE6CHdFvg8IY3vCFf+cpXsmbNmtx6660588wzM3jw4JRKpTz88MP5X//rf2XUqFE577zzcu+993ZXWQAA9HKbu7gOQ1fbA9A53TqlIkkqKysza9as3H777Vm9enWuueaaTJo0KaVSKS+99FLq6+vz1re+NYcffniuvvrqrFmzprtLBACgFxlW3bWd3LvaHoDO6fbAYXsHH3xwLr300ixdujQLFy7MBz/4wdTW1qZUKuWPf/xjPv3pT2f8+PE5/fTT8x//8R95+eWXe7JcAAB6wNCqwZk0qrZTbSePqs3QqsEFVwRAe/Ro4LC9adOm5cYbb8zatWtzyy235LWvfW1KpVJaW1vzn//5n3n3u9+d0aNH55Of/KTtNQEABpi6GeM62e7QgisBoL16TeCQJE899VS+9KUv5Yorrsizzz6bioqKJEmpVEqpVMq6devy5S9/OYcffni+8pWv9HC1AAB0l1lTRmdkTVWH2oysqcpZUw4pU0UA7E2PBw6NjY2pr6/PySefnMMPPzyf+9zn8tRTT6VUKuWII47Itddem2effTZ33nln3ve+96WysjKNjY35u7/7u9TX1/d0+QAAdIOa6srcUDc1VZXt+/paVTkoN54zNTXWbwDoMRWlUqnUEx3/8pe/zE033ZTvf//7bdthlkql7Lvvvnn3u9+diy66KG95y1t2avfUU0/lXe96V37961/nTW96UxYvXtzdpfc5q1evztixY5Mkq1atypgxY3q4IgCAzlm0fEMuqV+c9Q3Nuz1nZE1Vbjxnao4eP6IbKwPou8r1zNitke+29Rluuumm/P73v0/ySsiQJFOnTs1FF12U2bNnZ7/99tvtNcaPH58vfvGLOe200/LEE090S90AAPQO0yaMyH1zZub2JU+nfuGKPLZ2Y9uxyaNqUzfj0Jw15RAjGwB6gW77JD7jjDPys5/9LFu3bm0LGYYPH57Zs2fnAx/4QP78z/+83deaMGFCkuSll14qpLaVK1fmn/7pn7JgwYKsXLky1dXVOfzww/Pud787H/rQh7LvvvsW0k+S3Hnnnamvr88DDzyQtWvXprKyMq95zWvyZ3/2Zzn55JNzzjnnZNiwYYX1BwDQ39RUV2b29HGZPX1cGptbs7mpJcOqK+1GAdDLdNuUikGD/nu+3QknnJCLLroof/VXf5UhQ4Z0+FpPP/10Zs+enYqKitx9991dqmvBggV5//vfnxdffHGXx1//+tfnxz/+cQ477LAu9fPCCy/kggsuyO23377H8379619nypQpXerr1UypAAAAYHf6/JSKgw8+OOedd14uuuii/I//8T+6dK1DDjkk99xzT5dreuSRR/Lud787L730UoYNG5ZPfepTmTlzZhobGzNv3rz867/+a373u9/ljDPOyMMPP9zpkQcvvvhiTjnllLb1Js4444y8973vzeGHH57W1tasWLEiDz/8cH7wgx90+T0BAABAb9BtIxxaWlpSWdm75tLNnDkz99xzTyorK3PfffflmGOO2eH4l7/85cyZMydJ8tnPfjZXXHFFp/o599xz8+1vfzuVlZWpr6/Pe97znl2eVyqV0traWvh/JyMcAAAA2J1yPTN227aYvS1sePjhh9tGSVx44YU7hQ1J8olPfCKTJk1KkvzjP/5jXn755Q7388ADD+Tb3/52kuQf/uEfdhs2JElFRUWv++8EAAAAndFtgUNvM3/+/LbXF1xwwS7PGTRoUM4999wkr6zB0JlpHP/8z/+cJBk2bFg+8YlPdLg9AAAA9EUDNnC4//77kyQ1NTWZOnXqbs878cQT214/8MADHeqjubm5bZHIt7/97W1rQLS0tGTFihVZuXJlmpt3v4c0AAAA9FUDNnBYtmxZkuTwww/f4zSGI444Yqc27fXII49ky5YtSZJjjjkmzzzzTC644IIMHz4848ePz6GHHpr9998/p59+eh588MFOvAsAAADonQbkggFbtmzJunXrkmSvi2EccMABqampSUNDQ1atWtWhfh577LEd+jzyyCPb+t3+5z/5yU/yn//5n7nuuuvy0Y9+tEN9JK8s8LEna9eu7fA1AQB6k8bm1mxuasngioq0lkoZVl2ZoVWDe7osAPZgQAYOmzZtanvdnq0utwUOmzdv7lA/GzZsaHv92c9+Nk1NTXnHO96RK6+8Mm984xvz4osv5j/+4z/yyU9+Mhs3bszHP/7xvP71r8/b3/72DvWzbTVRAID+pKGpJfOXrMktD67I757dtNPx1792v5x7zKGZNWV0aqoH5NdagF5tQE6p2DbNIUmqqqr2en51dXWSpLGxsUP9NDQ0tL1uamrKmWeemdtvvz1Tp05NdXV1Dj744FxyySVZsGBBBg0alFKplDlz5qSbdioFAOi1Fi3fkBOuuTuX37Z0l2FDkvzumU25/LalOeGau7No+YZdngNAzxmQgcOQIUPaXrdn0campqYkydChQzvdT5J8+ctfzqBBO/8nP+644/LOd74zSbJ06dIsXbq0Q/2sWrVqj/8sWrSoQ9cDAOhJi5ZvSN3ch7K+oX2La69vaE7d3IeEDgC9zIAce7bffvu1vW7PNIltIxXaM/1id/1MmDAhr3/963d77mmnnZYf/OAHSZKHH344Rx55ZLv72ds6FAAAfUVDU0suqV+c5patHWrX3LI1l9Qvzn1zZppeAdBLDNgRDgceeGCSvS+4+MILL7QFDh1dK2H78/cWCmx/7nPPPdehfgAA+ov5S9a0e2TDq61vaM7tS54uuCIAOmtABg5JMmnSpCTJk08+mZaWlt2e9/jjj+/Upr3e8IY3tL1ubW3d47nbH9/TNp0AAP1Z/cKVXWy/oqBKAOiqARs4HHfccUlemS6xePHi3Z537733tr0+9thjO9THoYcemnHjxiVJ/vCHP+zx3O2Pjx49ukP9AAD0B43NrVm2dmOXrvHY2o1pbN7zL3oA6B4DNnCYNWtW2+ubbrppl+ds3bo1t9xyS5Jk+PDhmTlzZof7ede73pUkefbZZ/Pggw/u9rxbb7217fXxxx/f4X4AAPq6zU27H3XaE9cBoGsGbOAwbdq0tgf7uXPn5pe//OVO51x33XVZtmxZkuRv//Zvs88+++xw/Oabb05FRUUqKipy5ZVX7rKfj370o227Vfzv//2/d9gqc5v6+vrcc889SZIzzjjDIpAAwIA0rKDFHou6DgBdM2ADhyT56le/mqFDh6alpSWnnnpqvvCFL2ThwoW5++67c/HFF2fOnDlJkokTJ+YTn/hEp/oYN25cPve5zyVJFi9enGnTpuVb3/pWFi9enJ///Of58Ic/nPPPPz9JUltbm+uvv76Q9wYA0NcMrRqcSaNqu3SNyaNqM7RqcEEVAdAVAzr+fdOb3pTvfe97qaury8aNG3PZZZftdM7EiROzYMGCHba47Ki/+7u/y4YNG/KlL30pjz32WFvAsL2DDz448+fPz//4H/+j0/0AAPR1dTPG5fLblnah/aEFVgNAVwzoEQ5JcuaZZ+bRRx/Nxz72sUycODH77rtvhg8fnqOOOipf+tKX8utf/zqHH354l/v5whe+kF/84hc555xzMn78+FRXV2f//ffP0Ucfnc9//vN54okncswxxxTwjgAA+q5ZU0ZnZE1Vp9qOrKnKWVMOKbgiADqrolQqlXq6CMpr9erVGTt2bJJk1apV1ogAAHq1Rcs3pG7uQ2lu2druNlWVg/Kdi6bn6PEjylgZQP9UrmfGAT/CAQCA3mXahBGpv3B6u0c6jKypEjYA9EIDeg0HAAB6p2kTRuS+OTNz+5Knc8uDT+XxZzftdM4Rr90v5x4zPmdNOSQ1dqYA6HV8MgMA0CvVVFdm9vRxmT19XBqbW7O5qSWDKyrSWiplWHWl3SgAejmBAwAAvd7QqsECBoA+xhoOAAAAQOEEDgAAAEDhBA4AAABA4QQOAAAAQOEEDgAA9EuNza15flNTGptbe7oUgAHJLhUAAPQbDU0tmb9kTeoXrsyytRvbfj5pVG3qZozLrCmjU1PtKzBAd/BpCwBAv7Bo+YZcUr846xuadzq2bO3GXH7b0nzlZ0/khrqpmTZhRA9UCDCwmFIBAECft2j5htTNfWiXYcP21jc0p27uQ1m0fEM3VQYwcAkcAADo0xqaWnJJ/eI0t2xt1/nNLVtzSf3iNDS1lLkygIFN4AAAQJ82f8mavY5seLX1Dc25fcnTZaoIgETgAABAH1e/cGUn260ouJId2SUDGOgsGgkAQJ/V2Ny6w24UHfHY2o1pbG7N0KrBhdVjlwyA/+bTDgCAPmtzF9dh2NzUUljgYJcMgB2ZUgEAQJ81rIujBbrafhu7ZADsTOAAAECfNbRqcCaNqu1U28mjagsZ3WCXDIBdEzgAANCn1c0Y18l2hxbSv10yAHZN4AAAQJ82a8rojKyp6lCbkTVVOWvKIYX031t3yQDoaQIHAAD6tJrqytxQNzVVle37altVOSg3njO1kN0iitglA6C/EjgAANDnTZswIvUXTt/rSIeRNVX5zkXTc/T4YnaJKGKXDID+yraYAAD0C9MmjMh9c2bm9iVPp37hijy23ciDyaNqUzfj0Jw15ZBCRjZs01t2yQDojXzCAQDQb9RUV2b29HGZPX1cGptbs7mpJcOqKwvZjWJXtu2S0ZlpFUXtkgHQW5lSAQBAv9HY3JrnNzWlsbk1Q6sG56D9qsv+UN/Tu2QAvcf2n0EY4QAAQB/X0NSS+UvWpH7hyh1GGkwaVZu6GeMya8roQqdRvNqsKaPzlZ890aGtMYvcJQPoWT39GdSbVZRKpVJPF0F5rV69OmPHjk2SrFq1KmPGjOnhigAAirFo+YZcUr94jw/7I/bdJ19815/l+P9xUNlGOyxaviF1cx9Kc8vWvZ5bVTmo0IUrgZ7Tns+gkTVV+cf3TMkRo2rLOsWrK8r1zChwGAAEDgBAf9SRh/xtyvkbx/Y+eNx4zlRhA/QDnfkMSnrnyAeBA50mcAAA+puGppaccM3dHZrGsL2RNVW5oW5qpk0o9sG/oamlW3fJAHpGVz+DkvJ9DnVGuZ4ZfdoBANDnzF+ypktf9Nc3NKdu7kOpv3B6oV/2u3uXDKBndPUzKCnf51BvYpcKAAD6nPqFK7t8jeaWrbmkfnEamloKqGhn3bVLBtD9ivgMSsr/OdTTBA4AAPQpjc2tO6wE3xXrG5pz+5KnC7kWMDAU+RmU9O/PIYEDAAB9yuaCfxNYv3BFodcD+reiP4OS/vs5JHAAAKBPGVbwoouPrd2YxubWQq8J9F9FfwYl/fdzSOAAAECfMrRqcCaNqi30muX4jSXQP5XjMyjpn59DAgcAAPqcuhnjCr1eOX5jCfRfRX8GJf3zc0jgAABAnzNryuiMrKkq5FqTR9XaSQLokCI/g5L++zkkcAAAoM+pqa7MDXVTU1XZ9a+zdTMOLaAiYCAp8jMo6b+fQwIHAAD6pGkTRqT+wuld+i3jyJqqnDXlkAKrAgaKIj6Dkv79OSRwAACgz5o2YUTumzMzV599ZGqHdGz+86CK5MZzpqamH86bBrrH9p9BkzuxkGRV5aB+/TnUP98VAAADRk11ZaaM3T8bt3RshfetpaSmH86ZBrpXTXVlZk8fl9nTx6WxuTWbm1ry+NqN+ej3lmR9Q/Nu242sqcqN50zN0eNHdGO13csIBwAA+rwP3vKrTrZbXHAlwEA2tGpwDtqvOsdPPGi3Ix8mj6rN1WcfmfvmzOzXYUNihAMAAP3A6j9t6WS7xoIrAXjFrkY+DKuu7Je7UeyOEQ4AAPRpf3huc4+2B9ibbSMfBlLYkAgcAADo4554ZlOPtgdg1wQOAAD0aRNfu1+Ptgdg1wQOAAD0aa87eFiPtgdg1wQOAAD0eWOGD+lku6EFVwLANgIHAAD6vK+fe1Qn200tuBIAthE4AADQ500+ZP+c/sbXdqjNGUe+NpMP2b9MFQEgcAAAoF/4Wt3UdocOZxz52vyf9xvdAFBOlT1dAAAAFOVrdVPz2NMv5oO3LM7qPzXudHzM8KH5+rlTjWwA6AYCBwAA+pXJh+yfBz751iTJH57bnCee2ZSJr93PbhQA3UzgAABAv/W6g4cJGgB6iDUcAAAAgMIJHAAAAIDCCRwAAACAwgkcAAAAgMIJHAAAAIDCCRwAAACAwgkcAAAAgMIJHAAAAIDCCRwAAACAwgkcAAAAgMIJHAAAAIDCCRwAAACAwgkcAAAAgMIJHAAAAIDCCRwAAACAwgkcAAAAgMIJHAAAAIDCCRwAAACAwgkcAAAAgMIJHAAAgH6vsbk1z29qSmNza0+XAgNGZU8XAAAAUA4NTS2Zv2RN6heuzLK1G9t+PmlUbepmjMusKaNTU+2RCMrFny4AAKDfWbR8Qy6pX5z1Dc07HVu2dmMuv21pvvKzJ3JD3dRMmzCiByqE/s+UCgAAoF9ZtHxD6uY+tMuwYXvrG5pTN/ehLFq+oZsqg4FF4AAAAPQbDU0tuaR+cZpbtrbr/OaWrbmkfnEamlrKXBkMPAIHAACg35i/ZM1eRza82vqG5ty+5OkyVQQDl8ABAADoN+oXruxkuxUFVwIIHAAAgH6hsbl1h90oOuKxtRttmQkFEzgAAAD9wuYursPQ1fbAjgQOAABAvzCsurJH2wM7EjgAAAD9wtCqwZk0qrZTbSePqs3QqsEFVwQDm8ABAADoN+pmjOtku0MLrgQQOAAAAP3GrCmjM7KmqkNtRtZU5awph5SpooGnsbk1z29qsggnMUkJAADoN2qqK3ND3dTUzX0ozS1b93p+VeWg3HjO1NRYv6FLGppaMn/JmtQvXLnDTiGTRtWmbsa4zJoy2n/jAcgIBwAAoF+ZNmFE6i+cvteRDiNrqvKdi6bn6PEjuqmy/mnR8g054Zq7c/ltS3falnTZ2o25/LalOeGau7No+YYeqpCeInAAAAD6nWkTRuS+OTNz9dlHZvKrFpKcPKo2V599ZO6bM1PY0EWLlm9I3dyHsr6heY/nrW9oTt3ch4QOA4wxLQAAQL9UU12Z2dPHZfb0cWlsbs3mppYMq660G0VBGppackn94nZNXUmS5patuaR+ce6bM9P0igHCCAcAAKDfG1o1OAftVy1sKND8JWv2OrLh1dY3NOf2JU+XqSJ6G4EDAAAAHVa/cGUn260ouBJ6K4EDAAAAHdLY3LrTApHt9djajbbMHCAEDgAAAHTI5qaWHm1P3yBwAAAAoEOGdXHRx662p28QOAAAANAhQ6sGZ9Krthttr8mjai3eOUAIHAAAAOiwuhnjOtnu0IIrobcSOAAAANBhs6aMzsiaqg61GVlTlbOmHFKmiuhtBA4AAAB0WE11ZW6om5qqyvY9VlZVDsqN50xNjfUbBgyBAwAAAJ0ybcKI1F84fa8jHUbWVOU7F03P0eNHdFNl9AaiJQAAADpt2oQRuW/OzNy+5OnUL1yRx9ZubDs2eVRt6mYcmrOmHGJkwwDk/zgAAABdUlNdmdnTx2X29HFpbG7N5qaWDKuutBvFACdwAAAAoDBDqwYLGkhiDQcAAACgDAQOAAAAQOEEDgAAAEDhBA4AAABA4QQOAABAv9bY3JrnNzWlsbm1p0uBAcUuFQAAQL/T0NSS+UvWpH7hyixbu7Ht55NG1aZuxrjMmjI6NdUeh6Cc/AkDAAD6lUXLN+SS+sVZ39C807Flazfm8tuW5is/eyI31E3NtAkjeqBCGBhMqQAAAPqNRcs3pG7uQ7sMG7a3vqE5dXMfyqLlG7qpMhh4BA4AAEC/0NDUkkvqF6e5ZWu7zm9u2ZpL6henoamlzJXBwCRwAAAA+oX5S9bsdWTDq61vaM7tS54uU0UwsAkcAACAfqF+4cpOtltRcCVAInAAAAD6gcbm1h12o+iIx9ZutGUmlIHAAQAA6PM2d3Edhq62B3YmcAAAAPq8YdWVPdoe2JnAAQAA6POGVg3OpFG1nWo7eVRthlYNLrgiQOAAAAD0C3UzxnWy3aEFVwIkAgcAAKCfmDVldEbWVHWozciaqpw15ZAyVQQDm8ABAADoF2qqK3ND3dRUVbbvMaeqclBuPGdqaqzfAGUhcAAAAPqNaRNGpP7C6Xsd6TCypirfuWh6jh4/opsqg4FHlAcAAPQr0yaMyH1zZub2JU+nfuGKPLZ2Y9uxyaNqUzfj0Jw15RAjG6DM/AkDAAD6nZrqysyePi6zp49LY3NrNje1ZFh1pd0ooBsJHAAAgH5taNVgQQP0AGs4JFm5cmUuvfTSTJo0KTU1NRkxYkSmTZuWa6+9Ni+99FJZ+ly7dm2GDx+eioqKVFRU5KSTTipLPwAAANATBvwIhwULFuT9739/XnzxxbafvfTSS3n44Yfz8MMP5xvf+EZ+/OMf57DDDiu034985CM79AkAAAD9yYAe4fDII4/k3e9+d1588cUMGzYsV111VR588MHcdddd+cAHPpAk+d3vfpczzjgjmzdvLqzfH/3oR/mP//iPHHzwwYVdEwAAAHqTAR04fPSjH81LL72UysrK/OxnP8tll12WY445Jm9961vz9a9/Pddcc02S5PHHH89XvvKVQvrcvHlz/uZv/iZJcu211xZyTQAAAOhtBmzg8PDDD+eee+5Jklx44YU55phjdjrnE5/4RCZNmpQk+cd//Me8/PLLXe73sssuy6pVqzJz5sycc845Xb4eAAAA9EYDNnCYP39+2+sLLrhgl+cMGjQo5557bpLkhRdeaAsoOmvRokX5P//n/6Sqqio33HBDl64FAAAAvdmADRzuv//+JElNTU2mTp262/NOPPHEttcPPPBAp/traWnJBz/4wWzdujV///d/n9e//vWdvhYAAAD0dgN2l4ply5YlSQ4//PBUVu7+P8MRRxyxU5vOuPbaa/PII4/kda97XS677LJOX2dXVq9evcfja9euLbQ/AAAA2JsBGThs2bIl69atS5KMGTNmj+cecMABqampSUNDQ1atWtWp/v74xz/mc5/7XJLka1/7WoYMGdKp6+zO2LFjC70eAAAAdNWAnFKxadOmttfDhg3b6/k1NTVJ0umtMS+++OI0NjbmPe95T0499dROXQMAAAD6kgE7wmGbqqqqvZ5fXV2dJGlsbOxwX7fcckvuvPPO1NbW5vrrr+9w+/bY28iLtWvXZtq0aWXpGwAAAHZlQAYO209paG5u3uv5TU1NSZKhQ4d2qJ9169blE5/4RJLkqquuyqhRozrUvr32Ni0EAAAAutuAnFKx3377tb1uzzSJhoaGJO2bfrG9j3/841m3bl2OOuqofOhDH+pYkQAAANCHDdgRDgceeGDWrVu31x0eXnjhhbbAoSOLMz799NP59re/nSR561vfmu9///t7PP+5557LvHnzkiQTJkzI9OnT290XAAAA9DYDMnBIkkmTJuX+++/Pk08+mZaWlt1ujfn444/v0Ka9tp+qcc011+z1/GXLluV973tfkuS8884TOAAAANCnDcgpFUly3HHHJXllusTixYt3e969997b9vrYY48te10AAADQHwzYwGHWrFltr2+66aZdnrN169bccsstSZLhw4dn5syZ7b7++PHjUyqV9vrPNieeeGLbz26++eZOvScAAADoLQZs4DBt2rQcf/zxSZK5c+fml7/85U7nXHfddVm2bFmS5G//9m+zzz777HD85ptvTkVFRSoqKnLllVeWvWYAAADoKwbsGg5J8tWvfjXHHntsGhsbc+qpp+ayyy7LzJkz09jYmHnz5uXrX/96kmTixIlt21sCAAAAezegA4c3velN+d73vpe6urps3Lgxl1122U7nTJw4MQsWLNhhK00AAABgzwbslIptzjzzzDz66KP52Mc+lokTJ2bffffN8OHDc9RRR+VLX/pSfv3rX+fwww/v6TIBAACgT6kobb9yIf3S6tWrM3bs2CTJqlWrMmbMmB6uCAAAgN6iXM+MA36EAwAAAFA8gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBQ5KVK1fm0ksvzaRJk1JTU5MRI0Zk2rRpufbaa/PSSy916dobN27MvHnz8oEPfCBvfvObM3z48FRVVeWggw7KSSedlGuvvTZ/+tOfinkjAAAA0EtUlEqlUk8X0ZMWLFiQ97///XnxxRd3efz1r399fvzjH+ewww7r8LV/8pOf5Oyzz05TU9Mez3vNa16Tf/u3f8vMmTM73Ed7rF69OmPHjk2SrFq1KmPGjClLPwAAwM4am1uzuaklw6orM7RqcE+XAzsp1zNjZSFX6aMeeeSRvPvd785LL72UYcOG5VOf+lRmzpyZxsbGzJs3L//6r/+a3/3udznjjDPy8MMPZ9iwYR26/vr169PU1JRBgwbllFNOydve9rb8+Z//eYYPH57Vq1fnO9/5Tr73ve/l2WefzTve8Y784he/yJQpU8rzZgEAgG7T0NSS+UvWpH7hyixbu7Ht55NG1aZuxrjMmjI6NdUD+nGMAWBAj3CYOXNm7rnnnlRWVua+++7LMcccs8PxL3/5y5kzZ06S5LOf/WyuuOKKDl3/e9/7Xu6+++5cdtllGTdu3C7P+f/+v/8v//t//+8kyVvf+tbcddddnXgne2aEAwAAdJ9FyzfkkvrFWd/QvNtzRtZU5Ya6qZk2YUQ3Vga7Vq5nxgEbODz88MOZNm1akuTiiy/OjTfeuNM5W7duzRvf+MYsW7YsBxxwQJ599tnss88+hddy9NFH51e/+lUGDRqU5557LiNHjiz0+gIHAADoHouWb0jd3IfS3LJ1r+dWVQ5K/YXThQ70uHI9Mw7YRSPnz5/f9vqCCy7Y5TmDBg3KueeemyR54YUXcs8995SllpNOOinJKwHH8uXLy9IHAABQXg1NLbmkfnG7woYkaW7ZmkvqF6ehqaXMlUHPGLCBw/33358kqampydSpU3d73oknntj2+oEHHihLLdsvKjlo0ID9XwIAAH3a/CVr9jiNYlfWNzTn9iVPl6ki6FkDdpWSZcuWJUkOP/zwVFbu/j/DEUccsVObot17771JksrKyhx++OEdbr969eo9Hl+7dm2n6gIAANqvfuHKTrZbkdnTd73mG/RlAzJw2LJlS9atW5cke52bcsABB6SmpiYNDQ1ZtWpV4bUsWLAgjz76aJLktNNOS21tbYevsW2uDQAA0DMam1t32I2iIx5buzGNza22zKTfGZDj9zdt2tT2uj1bXdbU1CRJNm/eXGgdGzZsyN/8zd8kSQYPHpzPf/7zhV4fAADoHpu7uA5DV9tDbzRgRzhsU1VVtdfzq6urkySNjY2F1dDa2pr3v//9WbFiRZLkH/7hH/KmN72pU9fa28iLtWvXtu3IAQAAFG9YddcerbraHnqjAXlXDxkypO11c/PeF3XZtqjj0KFDC6vhQx/6UH76058mSc4444x8+tOf7vS1bHMJAAA9a2jV4EwaVdupaRWTR9WaTkG/NCCnVOy3335tr9szTaKhoSFJ+6ZftMenPvWpfP3rX0+SHHfccfn3f//3DB7sAwYAAPqyuhmdW/ixbsahBVcCvcOADByGDBmSAw88MMned3h44YUX2gKHIhZn/NKXvpQvfvGLSZI3v/nNueOOOwodOQEAAPSMWVNGZ2TN3qdsb29kTVXOmnJImSqCnjUgA4ckmTRpUpLkySefTEvL7hdoefzxx3dq01lf+9rX8slPfrLtWv/5n/+Z/fffv0vXBAAAeoea6srcUDc1VZXte8yqqhyUG8+ZmhrrN9BPDdjA4bjjjkvyynSJxYsX7/a8e++9t+31scce2+n+vv3tb+fDH/5wkuSwww7LnXfe2TbKAgAA6B+mTRiR+gun73Wkw8iaqnznouk5evyIbqoMut+ADRxmzZrV9vqmm27a5Tlbt27NLbfckiQZPnx4Zs6c2am+br311lxwwQUplUoZM2ZM7rrrrhxyiGFTAADQH02bMCL3zZmZq88+MpNH1e5wbPKo2lx99pG5b85MYQP93oAduzNt2rQcf/zxuf/++zN37tycd955OeaYY3Y457rrrsuyZcuSJH/7t3+bffbZZ4fjN998cy644IIkyWc+85lceeWVO/Xzs5/9LO973/vS2tqagw8+OHfeeWfGjx9flvcEAAD0DjXVlZk9fVxmTx+XxubWbG5qybDqyn6zG0V/fE8Ub8AGDkny1a9+Nccee2waGxtz6qmn5rLLLsvMmTPT2NiYefPmte0kMXHixHziE5/o8PUXLlyYs88+O83Nzdlnn31y/fXX5+WXX87SpUt322bMmDEZPnx4Z98SAADQywytGtwvHsobmloyf8ma1C9cucP2n5NG1aZuxrjMmjLaehTsYEDfDW9605vyve99L3V1ddm4cWMuu+yync6ZOHFiFixYsMNWmu3105/+NC+99FKS5OWXX8773//+vba56aabcv7553e4LwAAgHJZtHxDLqlfnPUNzTsdW7Z2Yy6/bWm+8rMnckPd1EybYKoIrxiwazhsc+aZZ+bRRx/Nxz72sUycODH77rtvhg8fnqOOOipf+tKX8utf/zqHH354T5cJAADQIxYt35C6uQ/tMmzY3vqG5tTNfSiLlm/opsro7SpKpVKpp4ugvFavXp2xY8cmSVatWpUxY8b0cEUAAEBf0NDUkhOuuXuvYcP2RtZU5b45M02v6EPK9cw44Ec4AAAAsGvzl6zpUNiQvDLS4fYlT5epIvoSgQMAAAC7VL9wZSfbrSi4EvoigQMAAAA7aWxu3WE3io54bO3GNDa3FlwRfY3AAQAAgJ1sbmrp0fb0fQIHAAAAdjKsi4s+drU9fZ/AAQAAgJ0MrRqcSaNqO9V28qjaDK0aXHBF9DUCBwAAAHapbsa4TrY7tOBK6IsEDgAAAOzSrCmjM7KmqkNtRtZU5awph5SpIvoSgQMAAAC7VFNdmRvqpqaqsn2PjlWVg3LjOVNTY/0GInAAAABgD6ZNGJH6C6fvdaTDyJqqfOei6Tl6/IhuqozeTuwEAADAHk2bMCL3zZmZ25c8nfqFK/LY2o1txyaPqk3djENz1pRDjGxgB+4GAAAA9qqmujKzp4/L7Onj0tjcms1NLRlWXWk3CnZL4AAAAECHDK0aLGhgr6zhAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFE7gAAAAABRO4AAAAAAUTuAAAAAAFK6ypwug/FpaWtper127tgcrAQAAoLfZ/jlx++fHrhI4DADPP/982+tp06b1YCUAAAD0Zs8//3zGjx9fyLVMqQAAAAAKV1EqlUo9XQTltWXLlvzmN79Jkhx00EGprDSwZaBZu3Zt2+iWRYsWZdSoUT1cEX2Z+4kiuZ8okvuJIrmfKEpfuJdaWlraRsYfeeSRGTJkSCHX9eQ5AAwZMiRHH310T5dBLzFq1KiMGTOmp8ugn3A/UST3E0VyP1Ek9xNF6c33UlHTKLZnSgUAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQOIEDAAAAUDiBAwAAAFA4gQMAAABQuIpSqVTq6SIAAACA/sUIBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIHAAAAoHACBwAAAKBwAgcAAACgcAIH6ENWrlyZSy+9NJMmTUpNTU1GjBiRadOm5dprr81LL73UpWtv3Lgx8+bNywc+8IG8+c1vzvDhw1NVVZWDDjooJ510Uq699tr86U9/KuaN0CuU837anbVr12b48OGpqKhIRUVFTjrppLL0Q/frzvvpzjvvzPnnn5/DDz88NTU12X///TNx4sT81V/9VW644YZs3ry50P7oft1xPz322GP5yEc+kiOPPDK1tbVtf+fNnDkz119/fTZt2lRIP3S/5557LnfccUeuuOKKvP3tb8+BBx7Y9vfO+eefX5Y+582bl9NOOy2jRo3KkCFDMn78+JxzzjlZuHBhWfqj+3TX/dRvv4uXgD7hjjvuKO2///6lJLv85/Wvf33pD3/4Q6eu/eMf/7hUXV2922tv++c1r3lN6ec//3nB74yeUM77aU/e9a537dDPiSeeWHgfdL/uup82bNhQOuuss/b6WfXrX/+662+KHtMd99O1115bqqys3ON9dOihh5YeeeSRgt4V3WlP/1/PO++8QvtqbGwsveMd79htf4MGDSp97nOfK7RPuld33E/9+bu4EQ7QBzzyyCN597vfnRdffDHDhg3LVVddlQcffDB33XVXPvCBDyRJfve73+WMM87o1G/21q9fn6ampgwaNCinnXZarr/++vz85z/Pf/3Xf+WHP/xh3vOe9yRJnn322bzjHe/IkiVLinx7dLNy30+786Mf/Sj/8R//kYMPPriwa9Lzuut+evHFF3PKKafk9ttvT5KcccYZ+fa3v51f/vKXeeCBB/Kd73wnH/3oRzNmzJhC3hc9ozvup+9///u59NJL09LSkqqqqnzsYx/LggUL8tBDD+W73/1ujjvuuCTJihUr8ra3vS0vvvhiYe+P7jd27NiceuqpZbv+hRdemDvuuCNJMnPmzMyfPz+LFi3K3Llz87rXvS5bt27NFVdckW984xtlq4HuU677qV9/F+/pxAPYu5NOOqmUpFRZWVl68MEHdzp+zTXXtCWfn/3sZzt8/Xnz5pUuvvji0ooVK3Z7zj/90z+19fHWt761w33Qe5T7ftqVTZs2lcaOHVtKUrrllluMcOhHuut+Ouecc9r6mTdv3m7P27p1a+nll1/udD/0rO64n974xje2XeOOO+7Y5TnvfOc728657rrrOtUPPeeKK64o/ehHPyo988wzpVKpVFq+fHlZRjjcc889bdc988wzSy0tLTscf/7550vjxo0rJSkdcMABpRdeeKGwvuk+3XE/9efv4gIH6OUWLVrU9uFy8cUX7/Kc1tbW0qRJk9r+Qmtubi5LLUcddVTb8MB169aVpQ/Kq6fup4985COlJKWZM2eWSqWSwKGf6K776f7772/r58orr+xq2fRS3XE/vfjii219vPnNb97teY888kjbee9617s61Ae9T7kCh9NPP72UpDR48ODSqlWrdnnOv/3bv7X1fe211xbWNz2nXPdTe/TF7+KmVEAvN3/+/LbXF1xwwS7PGTRoUM4999wkyQsvvJB77rmnLLVsW+Bv69atWb58eVn6oLx64n5atGhR/s//+T+pqqrKDTfc0KVr0bt01/30z//8z0mSYcOG5ROf+ESH29M3dMf91Nzc3Pb6sMMO2+15r3vd69peNzU1dagPBobNmzfnrrvuSpKccsopu53O9c53vjO1tbVJkltvvbXb6qN/6ovfxQUO0Mvdf//9SZKamppMnTp1t+edeOKJba8feOCBstSy/ZeuQYN8fPRF3X0/tbS05IMf/GC2bt2av//7v8/rX//6Tl+L3qc77qfm5ua2dRve/va3Z9iwYUleubdWrFiRlStX7vAQSd/VHffTgQcemBEjRiRJ/vjHP+72vD/84Q9trydOnNihPhgYFi1a1Pa9aPt78tWqqqoyY8aMtjYvv/xyt9RH/9QXv4v3jSphAFu2bFmS5PDDD09lZeVuzzviiCN2alO0e++9N0lSWVmZww8/vCx9UF7dfT9de+21eeSRR/K6170ul112WaevQ+/UHffTI488ki1btiRJjjnmmDzzzDO54IILMnz48IwfPz6HHnpo9t9//5x++ul58MEHO/Eu6C266/Ppgx/8YJLkv/7rv/KTn/xkl+d8/vOfT5IMHjw4F110UYf7oP/b/t7b/p7clW3HW1pa8vvf/76sddG/9cXv4gIH6MW2bNmSdevWJcleV14/4IADUlNTkyRZtWpV4bUsWLAgjz76aJLktNNOaxseSN/R3ffTH//4x3zuc59Lknzta1/LkCFDOnUdeqfuup8ee+yxHfo88sgjc/PNN6ehoWGHn//kJz/J8ccfn3/8x3/s0PXpHbrz8+nyyy/PX/zFXyRJzj777Fx66aX5yU9+kocffjjf+973ctJJJ+UHP/hBBg8enH/6p3/KpEmTOtwH/d/2997e7tmxY8fush10RF/9Li5wgF5s06ZNba+3DSPek21fwIrcyjBJNmzYkL/5m79J8spve7b95oe+pbvvp4svvjiNjY15z3veU9YtyegZ3XU/bdiwoe31Zz/72axbty7veMc78qtf/SpbtmzJs88+m6997Wupra3N1q1b8/GPf3y3v7Wm9+rOz6dhw4blJz/5Sf71X/81Y8aMyXXXXZfTTz8906ZNy3vf+97ce++9eec735lf/OIX+dCHPtTh6zMwdOSe3Xa/JsV/R2Ng6MvfxQUO0IttG0acvDIHcG+qq6uTJI2NjYXV0Nramve///1ZsWJFkuQf/uEf8qY3vamw69N9uvN+uuWWW3LnnXemtrY2119/fYfb0/t11/20/UiGpqamnHnmmbn99tszderUVFdX5+CDD84ll1ySBQsWZNCgQSmVSpkzZ05KpVKH+qFndfffd7/61a/yb//2b7tdx+HOO+/Mt771rWzcuLFT16f/68g9u+1+TYr9jsbA0Ne/iwscoBfbfgh6exZF27aQzNChQwur4UMf+lB++tOfJknOOOOMfPrTny7s2nSv7rqf1q1b17aTwFVXXZVRo0Z1qD19Q3fdT6+eivPlL395lwtlHXfccXnnO9+ZJFm6dGmWLl3aoX7oWd35990PfvCDnHTSSfn5z3+eI488MrfddlvWr1+f5ubm/OEPf8jVV1+dl19+OTfccEPe8pa35JlnnulwH/R/Hblnt1/or8jvaAwMff27uMABerH99tuv7XV7huBt+01ge4ajtsenPvWpfP3rX0/yypf5f//3f8/gwYMLuTbdr7vup49//ONZt25djjrqKMOR+7Huup+272fChAl73OnktNNOa3v98MMPd6gfelZ33U/PPvtszj///DQ1NeUNb3hDHnzwwcyaNSsjRozIPvvsk8MOOyyf+tSn8qMf/SgVFRX57W9/m4985CMdezMMCB25Z7cfqVXUdzQGhv7wXXz3SwADPW7IkCE58MADs27duqxevXqP577wwgttf6FtvzhRZ33pS1/KF7/4xSTJm9/85txxxx1S+T6uO+6np59+Ot/+9reTJG9961vz/e9/f4/nP/fcc5k3b16SVx4mp0+f3u6+6Fnd9fm0/fkdWZjtueee61A/9Kzuup/mzZvX1vayyy7bYW799k4++eScfPLJufPOO3PrrbfmhRdeyAEHHNChvujftv88Wr16dY466qjdnrv9QpFFfEdjYOgv38UFDtDLTZo0Kffff3+efPLJtLS07HarsMcff3yHNl3xta99LZ/85CfbrvWf//mf2X///bt0TXqHct9P2w8rveaaa/Z6/rJly/K+970vSXLeeecJHPqY7vh8esMb3tD2urW1dY/nbn98T9sq0jt1x/20/VaGb37zm/d47tSpU3PnnXdm69ateeKJJ3w+sYPJkye3vd7+ntyVbcf70laG9Kz+9F3clAro5Y477rgkrwzHW7x48W7P27Yvb5Ice+yxne7v29/+dj784Q8nSQ477LDceeedOfDAAzt9PXqX7r6f6N+643469NBDM27cuCTJH/7whz2eu/3x0aNHd6gfel533E/bhxgtLS17PPfll1/eZTtIkqOPPrptscjt78lXa25uzsKFC3dqA7vT376LCxygl5s1a1bb65tuummX52zdujW33HJLkmT48OGZOXNmp/q69dZbc8EFF6RUKmXMmDG56667csghh3TqWvRO5b6fxo8fn1KptNd/tjnxxBPbfnbzzTd36j3Rc7rr8+ld73pXklfm3z/44IO7Pe/WW29te3388cd3uB96VnfcTxMmTGh7ff/99+/x3Pvuuy9JUlFRkfHjx3eoH/q//fbbLyeffHKSV3Y12d1UoFtvvbVtt5Ozzz672+qjb+qX38VLQK93/PHHl5KUKisrSw8++OBOx6+55ppSklKS0mc+85mdjt900017PF4qlUr/+Z//WaqqqiolKR188MGlxx9/vOB3QW/RHffT3mxrf+KJJ3aqPb1Hd9xPK1asKA0ZMqSUpDR16tTS5s2bdzrn29/+dtt1zjjjjK6+LXpIue+nZcuWlSoqKkpJSqNHjy6tXr16l3X8y7/8S9t1jjnmmK6+LXrY8uXL2/5/nnfeee1q057PprvuuqvtnL/8y78stbS07HD8+eefL40bN66UpDR8+PDShg0buvhO6A3KdT/11+/ixodBH/DVr341xx57bBobG3Pqqafmsssuy8yZM9PY2Jh58+a1rV47ceLEtu0IO2LhwoU5++yz09zcnH322SfXX399Xn755T1uKzdmzJgMHz68s2+JHlTu+4mBpTvup3HjxuVzn/tc5syZk8WLF2fatGmZM2dO3vjGN+bFF1/MrbfemhtvvDFJUltbm+uvv76w90f3Kvf9dMQRR+SCCy7IN7/5zaxZsyZvetOb8tGPfjTHH3989ttvv6xatSrz5s3Ld7/73STJ4MGDc/XVVxf6Him/Bx54IE8++WTbv69bt67t9ZNPPrnTiLrzzz+/U/289a1vzXvf+97MmzcvP/zhD3PKKafkox/9aA455JD85je/yVVXXZWVK1cmSb74xS9aeLSP6o77qV9/F+/pxANonx/+8Iel2tratnT01f9MnDix9Pvf/36XbfeWqn7mM5/Z7XV3989NN91U3jdMWZXzfmqPbe2NcOgfuut++uQnP9n22+ld/XPwwQfv8rfi9C3lvp+2bNlSes973rPXv+dqampK3/nOd8r4TimX8847r0PfaXalvZ9NL730Uun000/f7bUHDRrU6b8r6R26437qz9/FreEAfcSZZ56ZRx99NB/72McyceLE7Lvvvhk+fHiOOuqofOlLX8qvf/1rKx/Tbu4nitRd99MXvvCF/OIXv8g555yT8ePHp7q6Ovvvv3+OPvrofP7zn88TTzyRY445poB3RE8q9/1UXV2defPm5ec//3nOPffcTJw4MTU1NamsrMyIESNyzDHH5NOf/nQef/zxzJ49u8B3Rn80dOjQLFiwIN/5zndyyimn5OCDD05VVVXGjh2b2bNn54EHHsiVV17Z02VCj6kolbZbvQsAAACgAEY4AAAAAIUTOAAAAACFEzgAAAAAhRM4AAAAAIUTOAAAAACFEzgAAAAAhRM4AAAAAIUTOAAAAACFEzgAAAAAhRM4AAAAAIUTOAAAAACFEzgAAAAAhRM4AAAAAIUTOAAAAACFEzgAAAAAhRM4AAAAAIUTOAAAAACFq+zpAgAAelJLS0t+85vfZNGiRXn44YezaNGiPPbYY2ltbU2SLF++POPHj+/ZIgGgDxI4AAAD2lVXXZUrr7yyp8sAgH7HlAoAYEArlUptr4cMGZIZM2bkda97XQ9WBAD9g8ABABjQjjnmmNx4441ZvHhxNm3alF/+8pc57rjjerosAOjzTKkAAAa00047radLAIB+yQgHAKBPevnll/Pa1742FRUVefvb377X85cuXZqKiopUVFTk6quv7oYKAWBgEzgAAH3SPvvsk3PPPTdJ8rOf/Sxr1qzZ4/nf/OY3kySDBw/OeeedV/b6AGCgEzgAAH3WRRddlCTZunVrbrnllt2e9/LLL6e+vj5Jcuqpp2b06NHdUh8ADGQCBwCgz5o4cWJOOOGEJMlNN9202/PuuOOOPP/880mSCy+8sFtqA4CBTuAAAPRp20Y5/P73v88vfvGLXZ6zLYw48MADc+aZZ3ZbbQAwkAkcAIA+7a/+6q8yfPjwJLse5fDss8/mJz/5SZKkrq4uVVVV3VkeAAxYAgcAoE8bOnRoZs+enST5/ve/n4aGhh2Of/vb305LS0uS5K//+q+7vT4AGKgEDgBAn/eBD3wgSbJp06b8x3/8xw7Hto16OProo3PkkUd2e20AMFAJHACAPm/KlCmZOnVqkh2nVTz00EN57LHHkhjdAADdTeAAAPQL2xaPvPfee/PHP/4xyX+HD0OHDs373ve+HqsNAAYigQMA0C/Mnj07++67b0qlUr71rW+lsbEx8+bNS5K8853vzP7779/DFQLAwCJwAAD6hdra2rz73e9OknzrW9/KD37wg7z44otJkgsvvLAnSwOAAUngAAD0G9umVaxYsSJz5sxJkkyYMCEnnXRSD1YFAANTZU8XAABQlGOPPTaTJk3KsmXL8swzzyRJLrjgglRUVOy2zebNm/ODH/xgh589+eSTba9/8IMf5MADD2z79ylTpmTKlCnFFg4A/VBFqVQq9XQRAABFue6663LppZcmSQYNGpSnnnoqY8eO3e35Tz31VCZMmNDu63/mM5/JlVde2dUyAaDfM6UCAOhXzjnnnLbXp5xyyh7DBgCgfEypAAD6ld/85jdtr//6r/96r+ePHz8+BnwCQPGMcAAA+pVvfvObSZKRI0fmrLPO6uFqAGDgEjgAAP3GU089lX//939P8spikdXV1T1cEQAMXBaNBAD6tDVr1uSll17K8uXL88lPfjK//v/buWMbhmEYioIsBa3g3ku58AqawZt5Ai+gYVKn/4CQ+K5kxfoB5PNUa63mnLVt2+r1AOC1/HAAAH7acRx13/fX7LousQEAFhMcAIC/0Huvfd9rjFHnea5eBwBez0kFAAAAEOdpJAAAABAnOAAAAABxggMAAAAQJzgAAAAAcYIDAAA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" ] @@ -2563,7 +1500,7 @@ "metadata": { "image/png": { "height": 432, - "width": 454 + "width": 526 } }, "output_type": "display_data" @@ -2592,12 +1529,6 @@ "cell_type": "code", "execution_count": 21, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:10.388162Z", - "iopub.status.busy": "2022-07-02T03:26:10.388050Z", - "iopub.status.idle": "2022-07-02T03:26:10.390409Z", - "shell.execute_reply": "2022-07-02T03:26:10.389941Z" - }, "pycharm": { "name": "#%%\n" } @@ -2613,12 +1544,6 @@ "cell_type": "code", "execution_count": 22, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:10.391901Z", - "iopub.status.busy": "2022-07-02T03:26:10.391800Z", - "iopub.status.idle": "2022-07-02T03:26:10.478191Z", - "shell.execute_reply": "2022-07-02T03:26:10.477824Z" - }, "pycharm": { "name": "#%%\n" } @@ -2627,7 +1552,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 22, @@ -2636,7 +1561,7 @@ }, { "data": { - "image/png": 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", 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" ] @@ -2679,28 +1604,14 @@ "cell_type": "code", "execution_count": 23, "metadata": { - "execution": { - "iopub.execute_input": "2022-07-02T03:26:10.479957Z", - "iopub.status.busy": "2022-07-02T03:26:10.479845Z", - "iopub.status.idle": "2022-07-02T03:26:11.537891Z", - "shell.execute_reply": "2022-07-02T03:26:11.537191Z" - }, "pycharm": { "name": "#%%\n" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "rm: dask-worker-space: No such file or directory\n" - ] - } - ], + "outputs": [], "source": [ "# Cleanup\n", - "!rm -r dask-worker-space\n", + "#!rm -r dask-worker-space\n", "!rm -r temp\n", "!rm xopt.log*\n", "!rm test.yaml" @@ -2709,7 +1620,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3.9.13 ('xopt-dev2')", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2723,7 +1634,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.9.18" }, "vscode": { "interpreter": { diff --git a/scripts/execute_notebooks.bash b/scripts/execute_notebooks.bash index 785b809c..b57bf87d 100755 --- a/scripts/execute_notebooks.bash +++ b/scripts/execute_notebooks.bash @@ -2,7 +2,7 @@ NOTEBOOKS=$(find . -type f -name "*.ipynb" -not -path '*/.*') -SKIP="parallel" +SKIP="Xparallel" echo $NOTEBOOKS diff --git a/xopt/mpi/run.py b/xopt/mpi/run.py index c13de5c4..9c69345e 100644 --- a/xopt/mpi/run.py +++ b/xopt/mpi/run.py @@ -20,7 +20,7 @@ logger = logging.getLogger("xopt") -def run_mpi(config, verbosity, asynch, logfile): +def run_mpi(config, verbosity=None, asynchronous=True, logfile=None): """ Xopt MPI driver @@ -50,7 +50,7 @@ def run_mpi(config, verbosity, asynch, logfile): # logger.info('_________________________________') logger.info(f"Parallel execution with {mpi_size} workers") - if asynch: + if asynchronous: logger.info("Enabling async mode") X = AsynchronousXopt(**config) else: @@ -76,17 +76,20 @@ def run_mpi(config, verbosity, asynch, logfile): parser.add_argument("--verbose", "-v", action="count", help="Show more log output") parser.add_argument( - "--asynchronous", "-a", action="store_true", help="Use asynchronous execution" + "--asynchronous", "-a", action="store_true", help="Use asynchronous execution", + default=True ) args = parser.parse_args() print(args) input_file = args.input_file - log_file = args.logfile + logfile = args.logfile verbosity = args.verbose - asynch = args.asynch + asynchronous = args.asynchronous assert os.path.exists(input_file), f"Input file does not exist: {input_file}" - run_mpi(yaml.safe_load(open(input_file)), verbosity, log_file, asynch) + config = yaml.safe_load(open(input_file)) + + run_mpi(config, verbosity=verbosity, logfile=logfile, asynchronous=asynchronous) From c125353c010c87657acb36da5544f715558e033c Mon Sep 17 00:00:00 2001 From: Christopher Mayes <31023527+ChristopherMayes@users.noreply.github.com> Date: Mon, 2 Oct 2023 15:52:52 -0700 Subject: [PATCH 12/13] black --- xopt/mpi/run.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/xopt/mpi/run.py b/xopt/mpi/run.py index 9c69345e..15e0af23 100644 --- a/xopt/mpi/run.py +++ b/xopt/mpi/run.py @@ -76,8 +76,11 @@ def run_mpi(config, verbosity=None, asynchronous=True, logfile=None): parser.add_argument("--verbose", "-v", action="count", help="Show more log output") parser.add_argument( - "--asynchronous", "-a", action="store_true", help="Use asynchronous execution", - default=True + "--asynchronous", + "-a", + action="store_true", + help="Use asynchronous execution", + default=True, ) args = parser.parse_args() @@ -91,5 +94,5 @@ def run_mpi(config, verbosity=None, asynchronous=True, logfile=None): assert os.path.exists(input_file), f"Input file does not exist: {input_file}" config = yaml.safe_load(open(input_file)) - + run_mpi(config, verbosity=verbosity, logfile=logfile, asynchronous=asynchronous) From 950044170c60d21c99d0d4a914237e16759b1988 Mon Sep 17 00:00:00 2001 From: Christopher Mayes <31023527+ChristopherMayes@users.noreply.github.com> Date: Mon, 2 Oct 2023 16:04:49 -0700 Subject: [PATCH 13/13] CNSGA notebook --- docs/examples/cnsga/cnsga_tnk.ipynb | 280 +++++++++++++++++++++------- docs/examples/cnsga/test.csv | 65 ------- 2 files changed, 217 insertions(+), 128 deletions(-) delete mode 100644 docs/examples/cnsga/test.csv diff --git a/docs/examples/cnsga/cnsga_tnk.ipynb b/docs/examples/cnsga/cnsga_tnk.ipynb index ab96b2ac..30be3252 100644 --- a/docs/examples/cnsga/cnsga_tnk.ipynb +++ b/docs/examples/cnsga/cnsga_tnk.ipynb @@ -100,8 +100,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: total: 5.02 s\n", - "Wall time: 5.02 s\n" + "CPU times: user 1.92 s, sys: 17.1 ms, total: 1.94 s\n", + "Wall time: 1.94 s\n" ] } ], @@ -175,8 +175,10 @@ "outputs": [ { "data": { - "text/plain": "
", - "image/png": 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" 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", + "text/plain": [ + "
" + ] }, "metadata": {}, "output_type": "display_data" @@ -240,7 +242,56 @@ "outputs": [ { "data": { - "text/plain": "\n Xopt\n________________________________\nVersion: 2.0a1+84.g3b769dc3.dirty\nData size: 0\nConfig as YAML:\ndump_file: null\nevaluator:\n function: !!python/name:xopt.resources.test_functions.tnk.evaluate_TNK ''\n function_kwargs:\n raise_probability: 0.1\n random_sleep: 0\n sleep: 0\n max_workers: 1\n vectorized: false\ngenerator:\n _loaded_population: !!python/object:pandas.core.frame.DataFrame\n _flags:\n allows_duplicate_labels: true\n _metadata: []\n _mgr: !!python/object/apply:pandas.core.internals.managers.BlockManager\n - !!python/tuple\n - !!python/object/apply:pandas._libs.internals._unpickle_block\n - !!python/object/apply:numpy.core.multiarray._reconstruct\n args:\n - &id001 !!python/name:numpy.ndarray ''\n - !!python/tuple\n - 0\n - !!binary |\n Yg==\n state: !!python/tuple\n - 1\n - !!python/tuple\n - 1\n - 64\n - !!python/object/apply:numpy.dtype\n args:\n - b1\n - false\n - true\n state: !!python/tuple\n - 3\n - '|'\n - null\n - null\n - null\n - -1\n - -1\n - 0\n - false\n - !!binary |\n AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\n AAAAAAAAAA==\n - !!python/object/apply:builtins.slice\n - 3\n - 4\n - 1\n - 2\n - !!python/object/apply:pandas._libs.internals._unpickle_block\n - !!python/object/apply:numpy.core.multiarray._reconstruct\n args:\n - *id001\n - !!python/tuple\n - 0\n - !!binary |\n Yg==\n state: !!python/tuple\n - 1\n - !!python/tuple\n - 8\n - 64\n - &id007 !!python/object/apply:numpy.dtype\n args:\n - f8\n - false\n - true\n state: !!python/tuple\n - 3\n - <\n - null\n - null\n - null\n - -1\n - -1\n - 0\n - false\n - !!binary |\n 5G5qgBGR4z+tVFWdVdXoP61UVZ1V1eg/rVRVnVXV6D+tVFWdVdXoP61UVZ1V1eg/Hzb9jWrX6D9T\n bBiqEbHwP0REfpNLaeg/RER+k0tp6D9ERH6TS2noP0REfpNLaeg/RER+k0tp6D9CqkNOBzHPPz10\n +8tS0t4/PXT7y1LS3j89dPvLUtLeP5ufy1S+au4/+hFDuel97D/GnHquxCDpP8aceq7EIOk/5mE3\n 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the iterables. Stops when the shortest iterable is exhausted.'\n __name__: map\n mate: !!python/object/apply:functools.partial\n args:\n - &id006 !!python/name:deap.tools.crossover.cxSimulatedBinaryBounded ''\n state: !!python/tuple\n - *id006\n - !!python/tuple []\n - eta: 20.0\n low: &id009 !!python/tuple\n - !!python/object/apply:numpy.core.multiarray.scalar\n - *id007\n - !!binary |\n AAAAAAAAAAA=\n - !!python/object/apply:numpy.core.multiarray.scalar\n - *id007\n - !!binary |\n AAAAAAAAAAA=\n up: &id010 !!python/tuple\n - !!python/object/apply:numpy.core.multiarray.scalar\n - *id007\n - !!binary |\n boYb8PkhCUA=\n - !!python/object/apply:numpy.core.multiarray.scalar\n - *id007\n - !!binary |\n boYb8PkhCUA=\n - __doc__: \"Executes a simulated binary crossover that modify in-place the input\\n\\\n \\ individuals. The simulated binary crossover expects :term:`sequence`\\n\\\n \\ individuals of floating point numbers.\\n\\n :param ind1: The first\\\n \\ individual participating in the crossover.\\n :param ind2: The second\\\n \\ individual participating in the crossover.\\n :param eta: Crowding degree\\\n \\ of the crossover. A high eta will produce\\n children resembling\\\n \\ to their parents, while a small eta will\\n produce solutions\\\n \\ much more different.\\n :param low: A value or a :term:`python:sequence`\\\n \\ of values that is the lower\\n bound of the search space.\\n\\\n \\ :param up: A value or a :term:`python:sequence` of values that is the\\\n \\ upper\\n bound of the search space.\\n :returns: A tuple\\\n \\ of two individuals.\\n\\n This function uses the :func:`~random.random`\\\n \\ function from the python base\\n :mod:`random` module.\\n\\n .. note::\\n\\\n \\ This implementation is similar to the one implemented in the\\n \\\n \\ original NSGA-II C code presented by Deb.\\n \"\n __name__: mate\n mutate: !!python/object/apply:functools.partial\n args:\n - &id008 !!python/name:deap.tools.mutation.mutPolynomialBounded ''\n state: !!python/tuple\n - *id008\n - !!python/tuple []\n - eta: 20.0\n indpb: 0.5\n low: *id009\n up: *id010\n - __doc__: \"Polynomial mutation as implemented in original NSGA-II algorithm\\\n \\ in\\n C by Deb.\\n\\n :param individual: :term:`Sequence `\\\n \\ individual to be mutated.\\n :param eta: Crowding degree of the mutation.\\\n \\ A high eta will produce\\n a mutant resembling its parent,\\\n \\ while a small eta will\\n produce a solution much more different.\\n\\\n \\ :param low: A value or a :term:`python:sequence` of values that\\n \\\n \\ is the lower bound of the search space.\\n :param up:\\\n \\ A value or a :term:`python:sequence` of values that\\n is\\\n \\ the upper bound of the search space.\\n :returns: A tuple of one individual.\\n\\\n \\ \"\n __name__: mutate\n select: !!python/object/apply:functools.partial\n args:\n - &id011 !!python/name:deap.tools.emo.selNSGA2 ''\n state: !!python/tuple\n - *id011\n - !!python/tuple []\n - {}\n - __doc__: \"Apply NSGA-II selection operator on the *individuals*. Usually,\\\n \\ the\\n size of *individuals* will be larger than *k* because any individual\\n\\\n \\ present in *individuals* will appear in the returned list at most once.\\n\\\n \\ Having the size of *individuals* equals to *k* will have no effect\\\n \\ other\\n than sorting the population according to their front rank.\\\n \\ The\\n list returned contains references to the input *individuals*.\\\n \\ For more\\n details on the NSGA-II operator see [Deb2002]_.\\n\\n :param\\\n \\ individuals: A list of individuals to select from.\\n :param k: The\\\n \\ number of individuals to select.\\n :param nd: Specify the non-dominated\\\n \\ algorithm to use: 'standard' or 'log'.\\n :returns: A list of selected\\\n \\ individuals.\\n\\n .. [Deb2002] Deb, Pratab, Agarwal, and Meyarivan,\\\n \\ \\\"A fast elitist\\n non-dominated sorting genetic algorithm for multi-objective\\n\\\n \\ optimization: NSGA-II\\\", 2002.\\n \"\n __name__: select\nmax_evaluations: 6400\nserialize_torch: false\nstrict: false\nvocs:\n constants:\n a: dummy_constant\n constraints:\n c1:\n - GREATER_THAN\n - 0.0\n c2:\n - LESS_THAN\n - 0.5\n objectives:\n y1: MINIMIZE\n y2: MINIMIZE\n observables: []\n variables:\n x1:\n - 0.0\n - 3.14159\n x2:\n - 0.0\n - 3.14159\n" + "text/plain": [ + "\n", + " Xopt\n", + "________________________________\n", + "Version: 2.0a1+195.gc125353c.dirty\n", + "Data size: 0\n", + "Config as YAML:\n", + "dump_file: null\n", + "evaluator:\n", + " function: xopt.resources.test_functions.tnk.evaluate_TNK\n", + " function_kwargs:\n", + " raise_probability: 0.1\n", + " random_sleep: 0\n", + " sleep: 0\n", + " max_workers: 1\n", + " vectorized: false\n", + "generator:\n", + " crossover_probability: 0.9\n", + " mutation_probability: 1.0\n", + " name: cnsga\n", + " output_path: .\n", + " population: null\n", + " population_file: test.csv\n", + " population_size: 64\n", + "max_evaluations: 6400\n", + "serialize_inline: false\n", + "serialize_torch: false\n", + "strict: false\n", + "vocs:\n", + " constants:\n", + " a: dummy_constant\n", + " constraints:\n", + " c1:\n", + " - GREATER_THAN\n", + " - 0.0\n", + " c2:\n", + " - LESS_THAN\n", + " - 0.5\n", + " objectives:\n", + " y1: MINIMIZE\n", + " y2: MINIMIZE\n", + " observables: []\n", + " variables:\n", + " x1:\n", + " - 0.0\n", + " - 3.14159\n", + " x2:\n", + " - 0.0\n", + " - 3.14159\n" + ] }, "execution_count": 11, "metadata": {}, @@ -297,7 +348,9 @@ "outputs": [ { "data": { - "text/plain": "64" + "text/plain": [ + "64" + ] }, "execution_count": 12, "metadata": {}, @@ -305,7 +358,7 @@ } ], "source": [ - "len(X.generator.children)" + "len(X.generator._children)" ] }, { @@ -319,24 +372,11 @@ }, "outputs": [ { - "ename": "OSError", - "evalue": "[Errno 22] Invalid argument: '.\\\\cnsga_offspring_2023-09-06T16:51:58.610319-05:00.csv'", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mOSError\u001B[0m Traceback (most recent call last)", - "File \u001B[1;32m:1\u001B[0m\n", - "File \u001B[1;32m~\\Documents\\GitHub\\Xopt\\xopt\\base.py:132\u001B[0m, in \u001B[0;36mXopt.run\u001B[1;34m(self)\u001B[0m\n\u001B[0;32m 126\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\n\u001B[0;32m 127\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mXopt is done. \u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[0;32m 128\u001B[0m \u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mMax evaluations \u001B[39m\u001B[38;5;132;01m{\u001B[39;00m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mmax_evaluations\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m reached.\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[0;32m 129\u001B[0m )\n\u001B[0;32m 130\u001B[0m \u001B[38;5;28;01mbreak\u001B[39;00m\n\u001B[1;32m--> 132\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mstep\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n", - "File \u001B[1;32m~\\Documents\\GitHub\\Xopt\\xopt\\base.py:117\u001B[0m, in \u001B[0;36mXopt.step\u001B[1;34m(self)\u001B[0m\n\u001B[0;32m 114\u001B[0m new_samples \u001B[38;5;241m=\u001B[39m pd\u001B[38;5;241m.\u001B[39mDataFrame(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mgenerator\u001B[38;5;241m.\u001B[39mgenerate(n_generate))\n\u001B[0;32m 116\u001B[0m \u001B[38;5;66;03m# Evaluate data\u001B[39;00m\n\u001B[1;32m--> 117\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mevaluate_data\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnew_samples\u001B[49m\u001B[43m)\u001B[49m\n", - "File \u001B[1;32m~\\Documents\\GitHub\\Xopt\\xopt\\base.py:150\u001B[0m, in \u001B[0;36mXopt.evaluate_data\u001B[1;34m(self, input_data)\u001B[0m\n\u001B[0;32m 147\u001B[0m \u001B[38;5;66;03m# explode any list like results if all of the output names exist\u001B[39;00m\n\u001B[0;32m 148\u001B[0m new_data \u001B[38;5;241m=\u001B[39m explode_all_columns(new_data)\n\u001B[1;32m--> 150\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43madd_data\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnew_data\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 152\u001B[0m \u001B[38;5;66;03m# dump data to file if specified\u001B[39;00m\n\u001B[0;32m 153\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mdump_state()\n", - "File \u001B[1;32m~\\Documents\\GitHub\\Xopt\\xopt\\base.py:174\u001B[0m, in \u001B[0;36mXopt.add_data\u001B[1;34m(self, new_data)\u001B[0m\n\u001B[0;32m 172\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m 173\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mdata \u001B[38;5;241m=\u001B[39m new_data\n\u001B[1;32m--> 174\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mgenerator\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43madd_data\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnew_data\u001B[49m\u001B[43m)\u001B[49m\n", - "File \u001B[1;32m~\\Documents\\GitHub\\Xopt\\xopt\\generators\\ga\\cnsga.py:127\u001B[0m, in \u001B[0;36mCNSGAGenerator.add_data\u001B[1;34m(self, new_data)\u001B[0m\n\u001B[0;32m 122\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mpopulation \u001B[38;5;241m=\u001B[39m cnsga_select(\n\u001B[0;32m 123\u001B[0m candidates, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mn_pop, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mvocs, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mtoolbox\n\u001B[0;32m 124\u001B[0m )\n\u001B[0;32m 126\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39moutput_path \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[1;32m--> 127\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mwrite_offspring\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 128\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mwrite_population()\n\u001B[0;32m 130\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mchildren \u001B[38;5;241m=\u001B[39m [] \u001B[38;5;66;03m# reset children\u001B[39;00m\n", - "File \u001B[1;32m~\\Documents\\GitHub\\Xopt\\xopt\\generators\\ga\\cnsga.py:159\u001B[0m, in \u001B[0;36mCNSGAGenerator.write_offspring\u001B[1;34m(self, filename)\u001B[0m\n\u001B[0;32m 156\u001B[0m filename \u001B[38;5;241m=\u001B[39m \u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;132;01m{\u001B[39;00m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mname\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m_offspring_\u001B[39m\u001B[38;5;132;01m{\u001B[39;00mxopt\u001B[38;5;241m.\u001B[39mutils\u001B[38;5;241m.\u001B[39misotime(include_microseconds\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m)\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m.csv\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[0;32m 157\u001B[0m filename \u001B[38;5;241m=\u001B[39m os\u001B[38;5;241m.\u001B[39mpath\u001B[38;5;241m.\u001B[39mjoin(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39moutput_path, filename)\n\u001B[1;32m--> 159\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moffspring\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mto_csv\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfilename\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mindex_label\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mxopt_index\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m)\u001B[49m\n", - "File \u001B[1;32m~\\mambaforge\\envs\\xopt-dev\\lib\\site-packages\\pandas\\core\\generic.py:3772\u001B[0m, in \u001B[0;36mNDFrame.to_csv\u001B[1;34m(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, decimal, errors, storage_options)\u001B[0m\n\u001B[0;32m 3761\u001B[0m df \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(\u001B[38;5;28mself\u001B[39m, ABCDataFrame) \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mto_frame()\n\u001B[0;32m 3763\u001B[0m formatter \u001B[38;5;241m=\u001B[39m DataFrameFormatter(\n\u001B[0;32m 3764\u001B[0m frame\u001B[38;5;241m=\u001B[39mdf,\n\u001B[0;32m 3765\u001B[0m header\u001B[38;5;241m=\u001B[39mheader,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 3769\u001B[0m decimal\u001B[38;5;241m=\u001B[39mdecimal,\n\u001B[0;32m 3770\u001B[0m )\n\u001B[1;32m-> 3772\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mDataFrameRenderer\u001B[49m\u001B[43m(\u001B[49m\u001B[43mformatter\u001B[49m\u001B[43m)\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mto_csv\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 3773\u001B[0m \u001B[43m \u001B[49m\u001B[43mpath_or_buf\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3774\u001B[0m \u001B[43m \u001B[49m\u001B[43mlineterminator\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mlineterminator\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3775\u001B[0m \u001B[43m \u001B[49m\u001B[43msep\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43msep\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3776\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoding\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mencoding\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3777\u001B[0m \u001B[43m \u001B[49m\u001B[43merrors\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43merrors\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3778\u001B[0m \u001B[43m \u001B[49m\u001B[43mcompression\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mcompression\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3779\u001B[0m \u001B[43m \u001B[49m\u001B[43mquoting\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mquoting\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3780\u001B[0m \u001B[43m \u001B[49m\u001B[43mcolumns\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mcolumns\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3781\u001B[0m \u001B[43m \u001B[49m\u001B[43mindex_label\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mindex_label\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3782\u001B[0m \u001B[43m \u001B[49m\u001B[43mmode\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mmode\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3783\u001B[0m \u001B[43m \u001B[49m\u001B[43mchunksize\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mchunksize\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3784\u001B[0m \u001B[43m \u001B[49m\u001B[43mquotechar\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mquotechar\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3785\u001B[0m \u001B[43m \u001B[49m\u001B[43mdate_format\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mdate_format\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3786\u001B[0m \u001B[43m \u001B[49m\u001B[43mdoublequote\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mdoublequote\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3787\u001B[0m \u001B[43m \u001B[49m\u001B[43mescapechar\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mescapechar\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3788\u001B[0m \u001B[43m \u001B[49m\u001B[43mstorage_options\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mstorage_options\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 3789\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n", - "File \u001B[1;32m~\\mambaforge\\envs\\xopt-dev\\lib\\site-packages\\pandas\\io\\formats\\format.py:1186\u001B[0m, in \u001B[0;36mDataFrameRenderer.to_csv\u001B[1;34m(self, path_or_buf, encoding, sep, columns, index_label, mode, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, errors, storage_options)\u001B[0m\n\u001B[0;32m 1165\u001B[0m created_buffer \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mFalse\u001B[39;00m\n\u001B[0;32m 1167\u001B[0m csv_formatter \u001B[38;5;241m=\u001B[39m CSVFormatter(\n\u001B[0;32m 1168\u001B[0m path_or_buf\u001B[38;5;241m=\u001B[39mpath_or_buf,\n\u001B[0;32m 1169\u001B[0m lineterminator\u001B[38;5;241m=\u001B[39mlineterminator,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 1184\u001B[0m formatter\u001B[38;5;241m=\u001B[39m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mfmt,\n\u001B[0;32m 1185\u001B[0m )\n\u001B[1;32m-> 1186\u001B[0m \u001B[43mcsv_formatter\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msave\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m created_buffer:\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;28;01massert\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(path_or_buf, StringIO)\n", - "File \u001B[1;32m~\\mambaforge\\envs\\xopt-dev\\lib\\site-packages\\pandas\\io\\formats\\csvs.py:240\u001B[0m, in \u001B[0;36mCSVFormatter.save\u001B[1;34m(self)\u001B[0m\n\u001B[0;32m 236\u001B[0m \u001B[38;5;250m\u001B[39m\u001B[38;5;124;03m\"\"\"\u001B[39;00m\n\u001B[0;32m 237\u001B[0m \u001B[38;5;124;03mCreate the writer & save.\u001B[39;00m\n\u001B[0;32m 238\u001B[0m \u001B[38;5;124;03m\"\"\"\u001B[39;00m\n\u001B[0;32m 239\u001B[0m \u001B[38;5;66;03m# apply compression and byte/text conversion\u001B[39;00m\n\u001B[1;32m--> 240\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m \u001B[43mget_handle\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 241\u001B[0m \u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mfilepath_or_buffer\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 242\u001B[0m \u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmode\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 243\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoding\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mencoding\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 244\u001B[0m \u001B[43m \u001B[49m\u001B[43merrors\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43merrors\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 245\u001B[0m \u001B[43m \u001B[49m\u001B[43mcompression\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcompression\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 246\u001B[0m \u001B[43m \u001B[49m\u001B[43mstorage_options\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mstorage_options\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 247\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m \u001B[38;5;28;01mas\u001B[39;00m handles:\n\u001B[0;32m 248\u001B[0m \u001B[38;5;66;03m# Note: self.encoding is irrelevant here\u001B[39;00m\n\u001B[0;32m 249\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mwriter \u001B[38;5;241m=\u001B[39m csvlib\u001B[38;5;241m.\u001B[39mwriter(\n\u001B[0;32m 250\u001B[0m handles\u001B[38;5;241m.\u001B[39mhandle,\n\u001B[0;32m 251\u001B[0m lineterminator\u001B[38;5;241m=\u001B[39m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mlineterminator,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 256\u001B[0m quotechar\u001B[38;5;241m=\u001B[39m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mquotechar,\n\u001B[0;32m 257\u001B[0m )\n\u001B[0;32m 259\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_save()\n", - "File \u001B[1;32m~\\mambaforge\\envs\\xopt-dev\\lib\\site-packages\\pandas\\io\\common.py:859\u001B[0m, in \u001B[0;36mget_handle\u001B[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001B[0m\n\u001B[0;32m 854\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(handle, \u001B[38;5;28mstr\u001B[39m):\n\u001B[0;32m 855\u001B[0m \u001B[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001B[39;00m\n\u001B[0;32m 856\u001B[0m \u001B[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001B[39;00m\n\u001B[0;32m 857\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m ioargs\u001B[38;5;241m.\u001B[39mencoding \u001B[38;5;129;01mand\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mb\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;129;01min\u001B[39;00m ioargs\u001B[38;5;241m.\u001B[39mmode:\n\u001B[0;32m 858\u001B[0m \u001B[38;5;66;03m# Encoding\u001B[39;00m\n\u001B[1;32m--> 859\u001B[0m handle \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mopen\u001B[39;49m\u001B[43m(\u001B[49m\n\u001B[0;32m 860\u001B[0m \u001B[43m \u001B[49m\u001B[43mhandle\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 861\u001B[0m \u001B[43m \u001B[49m\u001B[43mioargs\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmode\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 862\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoding\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mioargs\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mencoding\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 863\u001B[0m \u001B[43m \u001B[49m\u001B[43merrors\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43merrors\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 864\u001B[0m \u001B[43m \u001B[49m\u001B[43mnewline\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\n\u001B[0;32m 865\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 866\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m 867\u001B[0m \u001B[38;5;66;03m# Binary mode\u001B[39;00m\n\u001B[0;32m 868\u001B[0m handle \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mopen\u001B[39m(handle, ioargs\u001B[38;5;241m.\u001B[39mmode)\n", - "\u001B[1;31mOSError\u001B[0m: [Errno 22] Invalid argument: '.\\\\cnsga_offspring_2023-09-06T16:51:58.610319-05:00.csv'" + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 9.72 s, sys: 92.1 ms, total: 9.81 s\n", + "Wall time: 9.82 s\n" ] } ], @@ -357,8 +397,10 @@ "outputs": [ { "data": { - "text/plain": "
", - "image/png": 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" + "image/png": 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", + "text/plain": [ + "
" + ] }, "metadata": {}, "output_type": "display_data" @@ -380,7 +422,9 @@ "outputs": [ { "data": { - "text/plain": "64" + "text/plain": [ + "6400" + ] }, "execution_count": 15, "metadata": {}, @@ -410,7 +454,18 @@ "outputs": [ { "data": { - "text/plain": "[]" + "text/plain": [ + "['cnsga_population_2023-10-02T16:04:06.441768-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:06.537684-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:06.631702-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:06.726169-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:06.820353-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:06.918867-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:07.017250-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:07.116332-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:07.212575-07:00.csv',\n", + " 'cnsga_population_2023-10-02T16:04:07.310986-07:00.csv']" + ] }, "execution_count": 16, "metadata": {}, @@ -427,16 +482,27 @@ "cell_type": "code", "execution_count": 17, "metadata": { - "tags": [], "ExecuteTime": { "end_time": "2023-09-06T21:52:00.295436300Z", "start_time": "2023-09-06T21:52:00.280436100Z" - } + }, + "tags": [] }, "outputs": [ { "data": { - "text/plain": "[]" + "text/plain": [ + "['cnsga_offspring_2023-10-02T16:04:06.440781-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:06.536785-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:06.630800-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:06.725309-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:06.819553-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:06.917943-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:07.016399-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:07.115494-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:07.211766-07:00.csv',\n", + " 'cnsga_offspring_2023-10-02T16:04:07.310142-07:00.csv']" + ] }, "execution_count": 17, "metadata": {}, @@ -459,15 +525,24 @@ }, "outputs": [ { - "ename": "IndexError", - "evalue": "list index out of range", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mIndexError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[1;32mIn[18], line 2\u001B[0m\n\u001B[0;32m 1\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mxopt\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mutils\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m read_xopt_csv\n\u001B[1;32m----> 2\u001B[0m pop_df \u001B[38;5;241m=\u001B[39m read_xopt_csv(\u001B[43mpop_files\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;241;43m-\u001B[39;49m\u001B[38;5;241;43m1\u001B[39;49m\u001B[43m]\u001B[49m)\n\u001B[0;32m 3\u001B[0m pop_df\u001B[38;5;241m.\u001B[39mplot\u001B[38;5;241m.\u001B[39mscatter(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mx1\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mx2\u001B[39m\u001B[38;5;124m\"\u001B[39m, marker\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mo\u001B[39m\u001B[38;5;124m\"\u001B[39m, color\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mred\u001B[39m\u001B[38;5;124m\"\u001B[39m, alpha\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m1\u001B[39m)\n", - "\u001B[1;31mIndexError\u001B[0m: list index out of range" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "offspring_df = read_xopt_csv(*offspring_files[-10:])\n", "offspring_df.plot.scatter(\"x1\", \"x2\", marker=\".\", color=\"black\", alpha=.1)" @@ -506,11 +602,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(6400, 6349)" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "all_offspring = read_xopt_csv(*offspring_files) \n", "len(all_offspring), len(all_offspring.drop_duplicates())" @@ -518,7 +625,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -537,9 +644,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "df = pd.DataFrame(X.generator.generate(1000))\n", "\n", @@ -562,9 +690,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'y1': 1, 'y2': 1, 'c1': 0.9, 'c2': 0.5}" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Notice that this returns `some_array`\n", "evaluate_TNK({'x1':1, 'x2':1})" @@ -572,7 +711,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -585,9 +724,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "6400" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from xopt import Xopt\n", "\n", @@ -628,21 +778,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plot_population(X)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -664,7 +818,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.16" + "version": "3.9.18" } }, "nbformat": 4, diff --git a/docs/examples/cnsga/test.csv b/docs/examples/cnsga/test.csv deleted file mode 100644 index 24682c8a..00000000 --- a/docs/examples/cnsga/test.csv +++ /dev/null @@ -1,65 +0,0 @@ -xopt_index,x1,x2,y1,y2,c1,c2,xopt_runtime,xopt_error,xopt_error_str -251,0.8435368241252594,0.48943425077733627,0.8435368241252594,0.48943425077733627,0.004045474744415183,0.11812918458670565,1.3000000000040757e-05,False, -832,0.8435368241252594,0.48943425077733627,0.8435368241252594,0.48943425077733627,0.004045474744415183,0.11812918458670565,1.4700000000367197e-05,False, 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