stability_label_algorithm/modules/dataset_generator/dataset_generator.py
def generate_dataset_sample(self, custom_dataset_name: Optional[str] = None, include_ground_truth: bool = True,
                                sample_size: int = 1000, verbose: bool = True) -> Dataset:
        """
        Generate a Dataset, where the number of DatasetItems for each number of items in the knowledge base is
        specified. For example, if there are 4 Queryables in the ArgumentationSystem, then a knowledge base can contain
        either 0, 1, or 2 (=4/2) items. If, for example, sample_size = 10 then for each knowledge base size 10
        ArgumentationTheories are generated, so the total number of DatasetItems is 30.

        :param custom_dataset_name: Optional, name of the Dataset. Otherwise a name based on the timestamp is chosen.
        :param include_ground_truth: Boolean indicating if the ground truth should be computed. Note: this takes time!
        :param sample_size: Number of DatasetItems for each number of items in the knowledge base.
        :param verbose: Boolean indicating if information should be printed.
        :return: The resulting Dataset.
        """
        timestamp = datetime.now().strftime('%Y%m%d-%H%M%S%f')

        # Store argumentation system
        argumentation_system_name = self._get_argumentation_system_name(timestamp)
        write_argumentation_system(self.argumentation_system, argumentation_system_name)

        # Compute and store dataset
        dataset_name = self._get_dataset_name(custom_dataset_name, argumentation_system_name, timestamp)
        argumentation_theory_dataset = DatasetGenerator._generate_argumentation_theory_dataset_sample(
            dataset_name, self.argumentation_system, argumentation_system_name, sample_size, verbose)
        DatasetJsonWriter().write_to_json(argumentation_theory_dataset)
        if not include_ground_truth:
            return argumentation_theory_dataset

        # Compute and store annotated dataset if required
        raise NotImplementedError('Moet nog!')

        Generate a Dataset, where the number of DatasetItems for each number of items in the knowledge base is
        specified. For example, if there are 4 Queryables in the ArgumentationSystem, then a knowledge base can contain
        either 0, 1, or 2 (=4/2) items. If, for example, sample_size = 10 then for each knowledge base size 10
        ArgumentationTheories are generated, so the total number of DatasetItems is 30.

        :param custom_dataset_name: Optional, name of the Dataset. Otherwise a name based on the timestamp is chosen.
        :param include_ground_truth: Boolean indicating if the ground truth should be computed. Note: this takes time!
        :param sample_size: Number of DatasetItems for each number of items in the knowledge base.
        :param verbose: Boolean indicating if information should be printed.
        :return: The resulting Dataset.
        
Generate a Dataset, where the number of DatasetItems for each number of items in the knowledge base is
specified. For example, if there are 4 Queryables in the ArgumentationSystem, then a knowledge base can contain
either 0, 1, or 2 (=4/2) items. If, for example, sample_size = 10 then for each knowledge base size 10
ArgumentationTheories are generated, so the total number of DatasetItems is 30.
Generate a Dataset where the number of DatasetItems for each number of items in the knowledge base is specified . For example if there are 4 Queryables in the ArgumentationSystem then a knowledge base can contain either 0 1 or 2 ( = 4 / 2 ) items . If for example sample_size = 10 then for each knowledge base size 10 ArgumentationTheories are generated so the total number of DatasetItems is 30 .
def generate_dataset_sample(self, custom_dataset_name: Optional[str] = None, include_ground_truth: bool = True,
                                sample_size: int = 1000, verbose: bool = True) -> Dataset:
        timestamp = datetime.now().strftime('%Y%m%d-%H%M%S%f')
        argumentation_system_name = self._get_argumentation_system_name(timestamp)
        write_argumentation_system(self.argumentation_system, argumentation_system_name)
        dataset_name = self._get_dataset_name(custom_dataset_name, argumentation_system_name, timestamp)
        argumentation_theory_dataset = DatasetGenerator._generate_argumentation_theory_dataset_sample(
            dataset_name, self.argumentation_system, argumentation_system_name, sample_size, verbose)
        DatasetJsonWriter().write_to_json(argumentation_theory_dataset)
        if not include_ground_truth:
            return argumentation_theory_dataset
        raise NotImplementedError('Moet nog!')
def generate_dataset_sample ( self , custom_dataset_name : Optional [ str ] = None , include_ground_truth : bool = True , sample_size : int = 1000 , verbose : bool = True ) -> Dataset : timestamp = datetime . now ( ) . strftime ( '%Y%m%d-%H%M%S%f' ) argumentation_system_name = self . _get_argumentation_system_name ( timestamp ) write_argumentation_system ( self . argumentation_system , argumentation_system_name ) dataset_name = self . _get_dataset_name ( custom_dataset_name , argumentation_system_name , timestamp ) argumentation_theory_dataset = DatasetGenerator . _generate_argumentation_theory_dataset_sample ( dataset_name , self . argumentation_system , argumentation_system_name , sample_size , verbose ) DatasetJsonWriter ( ) . write_to_json ( argumentation_theory_dataset ) if not include_ground_truth : return argumentation_theory_dataset raise NotImplementedError ( 'Moet nog!' )
Generate a Dataset, where the number of DatasetItems for each number of items in the knowledge base is
specified.
Generate a Dataset where the number of DatasetItems for each number of items in the knowledge base is specified .
"""
        Generate a Dataset, where the number of DatasetItems for each number of items in the knowledge base is
        specified. For example, if there are 4 Queryables in the ArgumentationSystem, then a knowledge base can contain
        either 0, 1, or 2 (=4/2) items. If, for example, sample_size = 10 then for each knowledge base size 10
        ArgumentationTheories are generated, so the total number of DatasetItems is 30.

        :param custom_dataset_name: Optional, name of the Dataset. Otherwise a name based on the timestamp is chosen.
        :param include_ground_truth: Boolean indicating if the ground truth should be computed. Note: this takes time!
        :param sample_size: Number of DatasetItems for each number of items in the knowledge base.
        :param verbose: Boolean indicating if information should be printed.
        :return: The resulting Dataset.
        """ # Store argumentation system # Compute and store dataset # Compute and store annotated dataset if required
The resulting Dataset.
The resulting Dataset .
self
custom_dataset_name
Optional[str]
Optional, name of the Dataset. Otherwise a name based on the timestamp is chosen.
Optional name of the Dataset . Otherwise a name based on the timestamp is chosen .
include_ground_truth
bool
Boolean indicating if the ground truth should be computed. Note: this takes time!
Boolean indicating if the ground truth should be computed . Note : this takes time!
sample_size
int
Number of DatasetItems for each number of items in the knowledge base.
Number of DatasetItems for each number of items in the knowledge base .
verbose
bool
Boolean indicating if information should be printed.
Boolean indicating if information should be printed .