129 lines
5.0 KiB
Python
129 lines
5.0 KiB
Python
from movie_filter import MovieFilter
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from relationship_filter import RelationshipFilter
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from rdf_filter import RdfFilter
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from cleaner import PipelineApplier
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from Scripts.DataCleaning.data_output_models.bpe_corpus import BPE_corpus
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from Scripts.DataCleaning.data_output_models.rdf_text_tasks import RDF_text_task_dataset
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from Scripts.DataCleaning.data_output_models.rdf_completation_task import RDF_completation_task_dataset
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from Scripts.DataCleaning.data_output_models.debug_csv import Debug_csv
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import pandas as pd
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RELATIONSHIP_FILTER_LIST = [
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"dbp-dbp:wikiPageUsesTemplate","w3:2000/01/rdf-schema#label","dbp-dbo:abstract",
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"dbp-dbo:wikiPageID","dbp-dbo:wikiPageRevisionID", "dbp-dbo:wikiPageDisambiguates",
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"w3:2002/07/owl#sameAs","dbp-dbp:image","dbp-dbo:wikiPageLength", "w3:2000/01/rdf-schema#comment",
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"dbp-dbo:thumbnail", "foaf:depiction", "w3:1999/02/22-rdf-syntax-ns#type",
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"dbp-dbp:id","dbp-dbp:totalWidth", "w3:ns/prov#wasDerivedFrom", "dbp-dbp:n", "dbp-dbp:alt",
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"dbp-dbo:soundRecording", "dbp-dbp:align", "dbp-dbp:format", "dbp-dbp:n",
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"dbp-dbp:filename", "dbp-dbp:wikt", "foaf:isPrimaryTopicOf", "dbp-dbp:quote", "foaf:homepage",
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"dbp-dbp:wordnet_type", "dbp-dbp:length"
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]
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class Pipeline():
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def __init__(self) -> None:
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self._movie_filter = MovieFilter()
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self._relationship_filter = RelationshipFilter()
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self._rdf_filter = RdfFilter()
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self._pipeline = PipelineApplier()
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self.task_bpe_corpus = BPE_corpus("./Assets/Dataset/Tmp/corpus.txt")
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self.task_rdf_text = RDF_text_task_dataset("./Assets/Dataset/Tmp/rdf_text.csv")
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self.task_rdf_completation = RDF_completation_task_dataset("./Assets/Dataset/Tmp/rdf_completation.csv")
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self._movie_filter.frequency_filter(50,3000)
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self._relationship_filter.frequency_filter(50, 2395627) # from 2718 to 3069
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self._relationship_filter.delete_relationship_uri_by_list(RELATIONSHIP_FILTER_LIST)
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def other_filter(self):
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self._movie_filter.relation_filter("purl:dc/terms/subject",5,100)
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self._movie_filter.relation_filter("dbp-dbo:director",1,100)
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def _get_cleaned_movie_rows(self):
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movie_ids = self._movie_filter.get_movie_id()
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rel_ids = self._relationship_filter.get_relationship_id()
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for RDF in self._rdf_filter.yield_movie_abbreviated_rdfs(movie_ids,rel_ids):
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RDF = self._pipeline.drop_na_from_dataset(RDF)
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RDF = self._pipeline.regex_on_objects(RDF)
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RDF = self._pipeline.rdf_add_special_token(RDF)
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if RDF.empty:
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continue
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yield RDF
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def execute_task_bpe_corpus(self):
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for RDF in self._get_cleaned_movie_rows():
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RDF = self._pipeline.rebuild_by_movie(RDF)
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RDF = RDF[["Triple","Abstract"]]
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self.task_bpe_corpus.write_from_df(RDF)
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self._end_file_handler()
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def execute_tasks_rdf_text(self):
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for RDF in self._get_cleaned_movie_rows():
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RDF = self._pipeline.rebuild_by_movie(RDF)
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self.task_rdf_text.write(RDF)
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self._end_file_handler()
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def execute_task_rdf_completation(self):
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for RDF in self._get_cleaned_movie_rows():
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RDF["Triple"] = self._pipeline.build_triple(RDF)
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self.task_rdf_completation.write(RDF[["MovieID","Triple"]])
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self._end_file_handler()
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def _end_file_handler(self):
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self.task_bpe_corpus.close()
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self.task_rdf_text.close()
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self.task_rdf_completation.close()
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def execute_all_task(self):
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for RDF in self._get_cleaned_movie_rows():
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completation_RDF = RDF.copy()
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completation_RDF["Triple"] = self._pipeline.build_triple(completation_RDF)
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self.task_rdf_completation.write(completation_RDF[["MovieID","Triple"]])
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RDF = self._pipeline.rebuild_by_movie(RDF)
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self.task_rdf_text.write(RDF)
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self.task_bpe_corpus.write_from_df(RDF[["Triple","Abstract"]])
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self._end_file_handler()
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def use_toy_dataset(self):
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# CHOOSEN MOVIE:
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# The Dark Knight : 117248
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# Inception : 147074
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# The Avengers : 113621
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# Cast Away : 1123
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# The Departed : 117586
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# American Psycho : 90177
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# Avatar : 71587
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# Django Unchained : 138952
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# Spirited Away : 144137
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# Knives Out : 148025
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movie_list = [117248, 147074, 113621, 1123, 117586, 90177, 71587, 138952, 144137, 148025]
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self._movie_filter.MOVIE_FILTER = pd.DataFrame({"MovieID": movie_list})
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def generate_csv_debug_file(self, debug_path:str):
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debug_csv = Debug_csv(debug_path)
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for RDF in self._get_cleaned_movie_rows():
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debug_csv.write(RDF)
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debug_csv.close()
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pipe = Pipeline()
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pipe.use_toy_dataset()
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pipe.other_filter()
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# pipe.execute_all_task()
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pipe.generate_csv_debug_file("Assets/Dataset/Tmp/debug.csv") |