def test_one_operation_analyze_analyze():
# given
pipeline, train_data, test_data, node_to_analyze, result_dir = given_data()
requirements = SensitivityAnalysisRequirements(hyperparams_analysis_samples_size=1)
# when
result = OneOperationHPAnalyze(pipeline=pipeline, train_data=train_data, requirements=requirements,
test_data=test_data, path_to_save=result_dir). \
analyze(node=node_to_analyze)
assert type(result) is dict
def run_analysis(pipeline, train_data, test_data):
sa_requirements = SensitivityAnalysisRequirements(
is_visualize=True, is_save_results_to_json=True)
approaches = [
NodeDeletionAnalyze, NodeReplaceOperationAnalyze,
MultiOperationsHPAnalyze
]
result_path = join(default_fedot_data_dir(), 'sensitivity',
f'{PipelineSensitivityAnalysis.__name__}')
PipelineSensitivityAnalysis(pipeline=pipeline,
train_data=train_data,
test_data=test_data,
approaches=approaches,
requirements=sa_requirements,
path_to_save=result_path).analyze()
def __init__(
self,
approaches: Optional[List[Type['NodeAnalyzeApproach']]] = None,
approaches_requirements: SensitivityAnalysisRequirements = None,
path_to_save=None,
log: Log = None):
self.approaches = [NodeDeletionAnalyze, NodeReplaceOperationAnalyze
] if approaches is None else approaches
self.path_to_save = \
join(default_fedot_data_dir(), 'sensitivity', 'nodes_sensitivity') if path_to_save is None else path_to_save
self.log = default_log(__name__) if log is None else log
self.approaches_requirements = \
SensitivityAnalysisRequirements() if approaches_requirements is None else approaches_requirements
def test_pipeline_analysis_analyze(analyze_method):
# given
pipeline, train_data, test_data, node_index, result_dir = given_data()
requirements = SensitivityAnalysisRequirements(hyperparams_analysis_samples_size=1)
# when
non_structure_analyze_result = PipelineAnalysis(pipeline=pipeline,
train_data=train_data,
test_data=test_data,
requirements=requirements,
path_to_save=result_dir).analyze()
# then
assert type(non_structure_analyze_result) is list
assert analyze_method.called
def __init__(self, pipeline: Pipeline, train_data: InputData, test_data: InputData,
requirements: SensitivityAnalysisRequirements = None,
path_to_save=None, log: Log = None):
self._pipeline = pipeline
self._train_data = train_data
self._test_data = test_data
self.problem: Optional[Problem] = None
requirements = SensitivityAnalysisRequirements() if requirements is None else requirements
self.requirements: HyperparamsAnalysisMetaParams = requirements.hp_analysis_meta
self.analyze_method = analyze_method_by_name.get(self.requirements.analyze_method)
self.sample_method = sample_method_by_name.get(self.requirements.sample_method)
self.operation_types = None
self.path_to_save = \
join(default_fedot_data_dir(), 'sensitivity', 'pipeline_sensitivity') \
if path_to_save is None else path_to_save
self.log = default_log(__name__) if log is None else log
def __init__(self,
pipeline: Pipeline,
train_data,
test_data: InputData,
requirements: SensitivityAnalysisRequirements = None,
path_to_save=None,
log: Log = None):
self._pipeline = pipeline
self._train_data = train_data
self._test_data = test_data
self._origin_metric = None
self._requirements = \
SensitivityAnalysisRequirements() if requirements is None else requirements
self._path_to_save = \
join(default_fedot_data_dir(), 'sensitivity', 'nodes_sensitivity') if path_to_save is None else path_to_save
self.log = default_log(__name__) if log is None else log
if not exists(self._path_to_save):
makedirs(self._path_to_save)
def __init__(
self,
pipeline: Pipeline,
train_data: InputData,
test_data: InputData,
approaches: Optional[List[Type[MultiOperationsHPAnalyze]]] = None,
requirements: SensitivityAnalysisRequirements = None,
path_to_save=None,
log: Log = None):
self.pipeline = pipeline
self.train_data = train_data
self.test_data = test_data
self.requirements = \
SensitivityAnalysisRequirements() if requirements is None else requirements
self.approaches = [MultiOperationsHPAnalyze
] if approaches is None else approaches
self.path_to_save = \
join(default_fedot_data_dir(), 'sensitivity', 'pipeline_sa') if path_to_save is None else path_to_save
self.log = default_log(__name__) if log is None else log
def __init__(self, pipeline: Pipeline, train_data: InputData, test_data: InputData,
approaches: Optional[List[Type[NodeAnalyzeApproach]]] = None,
requirements: SensitivityAnalysisRequirements = None,
path_to_save=None, log: Log = None,
nodes_to_analyze: List[Node] = None):
self.pipeline = pipeline
self.train_data = train_data
self.test_data = test_data
self.approaches = approaches
self.requirements = \
SensitivityAnalysisRequirements() if requirements is None else requirements
self.metric = self.requirements.metric
self.log = default_log(__name__) if log is None else log
self.path_to_save = \
join(default_fedot_data_dir(), 'sensitivity', 'nodes_sensitivity') if path_to_save is None else path_to_save
if not nodes_to_analyze:
self.log.message('Nodes to analyze are not defined. All nodes will be analyzed.')
self.nodes_to_analyze = self.pipeline.nodes
else:
self.nodes_to_analyze = nodes_to_analyze
def __init__(self,
pipeline: Pipeline,
train_data,
test_data: InputData,
requirements: SensitivityAnalysisRequirements = None,
path_to_save=None,
log: Log = None):
super().__init__(pipeline, train_data, test_data, path_to_save)
requirements = SensitivityAnalysisRequirements(
) if requirements is None else requirements
self.requirements: HyperparamsAnalysisMetaParams = requirements.hp_analysis_meta
self.analyze_method = analyze_method_by_name.get(
self.requirements.analyze_method)
self.sample_method = sample_method_by_name.get(
self.requirements.sample_method)
self.problem = None
self.operation_type = None
self.data_under_lock: dict = {}
self.path_to_save = \
join(default_fedot_data_dir(), 'sensitivity', 'nodes_sensitivity') if path_to_save is None else path_to_save
self.log = default_log(__name__) if log is None else log