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import random
from .helper_classes import RDFTriples, KB2Data
random.seed(42)
[docs]
class LPGen:
def __init__(self, kb_path, storage_dir=None, max_num_lps=1000, depth=3, max_child_length=20, refinement_expressivity=0.2,
downsample_refinements=True, sample_fillers_count=10, num_sub_roots=50, min_num_pos_examples=1):
"""
Args
- kb_path: path to the owl file representing the knowledge base/ontology
- storage_dir: directory in which to store the data to be generated. Not the directory needs not to exists, it would be created automatically
- max_num_lps: the maximum number of learning problems to store
- depth, max_child_length, refinement_expressivity, sample_fillers_count, num_sub_roots all refer to the size of the data (learning problems) to be generated
- downsample_refinements: whether to downsample refinements in ExpressRefinement. If refinement_expressivity<1, this must be set to True
"""
self.triple_gen = RDFTriples(kb_path=kb_path, storage_dir=storage_dir)
self.lp_gen = KB2Data(path=kb_path, storage_dir=storage_dir, max_num_lps=max_num_lps, depth=depth,
max_child_length=max_child_length, refinement_expressivity=refinement_expressivity,
downsample_refinements=downsample_refinements, sample_fillers_count=sample_fillers_count, num_sub_roots=num_sub_roots, min_num_pos_examples=min_num_pos_examples)
[docs]
def generate(self):
self.triple_gen.export_triples()
self.lp_gen.generate_descriptions().save_data()