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- builtins.object
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- Experiment
class Experiment(builtins.object) |
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Experiment(experiment_name: str = None, data: pandas.core.frame.DataFrame = None, samplers: list = [], metrics: list = [], ground_truth: str = None, snapshot_interval: int = -1, n_threads: int = 1, seed: int = 42)
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Methods defined here:
- __init__(self, experiment_name: str = None, data: pandas.core.frame.DataFrame = None, samplers: list = [], metrics: list = [], ground_truth: str = None, snapshot_interval: int = -1, n_threads: int = 1, seed: int = 42)
- Initialize self. See help(type(self)) for accurate signature.
- evaluate(self, plot=False, plot_labels=None)
- run(self)
- run_sampler(self, approximator: structure_learning.approximators.approximator.Approximator)
- Run a specific sampler.
Parameters:
sampler: The sampler instance to run.
- save(self, filename: str, compression='gzip')
- Saves the Graph object to a file.
Parameters:
filename (str): Path to the output file.
- to_yaml(self, yaml_file: str)
- Save experiment configuration to a YAML file.
Parameters:
yaml_file (str): Path to the YAML file where the configuration will be saved.
Class methods defined here:
- from_yaml(yaml_file: str, data: pandas.core.frame.DataFrame, ground_truth: str = None)
- Load experiment configuration from a YAML file.
Parameters:
yaml_file (str): Path to the YAML file containing experiment configuration.
- load(filename: str, compression='gzip')
- Loads a Graph object from a file.
Parameters:
filename (str): Path to the input file.
Returns:
Graph: Loaded Graph object.
Data descriptors defined here:
- __dict__
- dictionary for instance variables
- __weakref__
- list of weak references to the object
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