docstr: Container for dataset metadata and experiment results.
  
  Constructor arguments:
  - The configuration space
  - aslib_directory: directory with a problem instance in the aslib format
docstr_tok: ["Container","for","dataset","metadata","and","experiment","results",".","Constructor","arguments",":","-","The","configuration","space","-","aslib_directory",":","directory","with","a","problem","instance","in","the","aslib","format"]
code: def __init__(self, configuration_space, aslib_directory, logger):
      """Container for dataset metadata and experiment results.
  
      Constructor arguments:
      - The configuration space
      - aslib_directory: directory with a problem instance in the aslib format
      """
  
      self.logger = logger
  
      self.configuration_space = configuration_space
      self.default_configuration_space_dict = (
          configuration_space.get_default_configuration().get_dictionary()
      )
      self.aslib_directory = aslib_directory
  
      aslib_reader = aslib_simple.AlgorithmSelectionProblem(
          self.aslib_directory, self.configuration_space
      )
      self.metafeatures = aslib_reader.metafeatures
      self.algorithm_runs: OrderedDict[
          str, pd.DataFrame
      ] = aslib_reader.algorithm_runs
      self.configurations = aslib_reader.configurations
  
      configurations = dict()
      for algorithm_id in self.configurations:
          configuration = self.configurations[algorithm_id]
          try:
              for key in self.default_configuration_space_dict.keys():
                  if key not in configuration:
                      configuration[
                          key
                      ] = self.default_configuration_space_dict[key]
              configuration = Configuration(
                  configuration_space,
                  values=configuration,
                  allow_inactive_with_values=True,
              )
              configuration = deactivate_inactive_hyperparameters(
                  configuration, configuration_space
              )
              configurations[str(algorithm_id)] = configuration
          except (ValueError, KeyError) as e:
              self.logger.debug("Error reading configurations: %s", e)
  
      self.configurations = configurations
  
imports: from collections import OrderedDict
  import numpy
  import pandas
  from ConfigSpace.configuration_space import Configuration
  from ConfigSpace.util import deactivate_inactive_hyperparameters
  from ..input import aslib_simple
  from ..metafeatures.metafeature import DatasetMetafeatures
label_desc: Use image node_id 1 to create a new MetaBase object from inherited base classes: object with example: obj = MetaBase(configuration_space, aslib_directory, logger)