Terms to Cluster Mapping

Example

>>> from techminer2.packages.networks.co_occurrence.descriptors import TermsToClustersMapping
>>> mapping = (
...     TermsToClustersMapping()
...     #
...     # FIELD:
...     .having_terms_in_top(20)
...     .having_terms_ordered_by("OCC")
...     .having_term_occurrences_between(None, None)
...     .having_term_citations_between(None, None)
...     .having_terms_in(None)
...     #
...     # COUNTERS:
...     .using_term_counters(True)
...     #
...     # NETWORK:
...     .using_clustering_algorithm_or_dict("louvain")
...     .using_association_index("association")
...     #
...     # DATABASE:
...     .where_root_directory_is("example/")
...     .where_database_is("main")
...     .where_record_years_range_is(None, None)
...     .where_record_citations_range_is(None, None)
...     .where_records_match(None)
...     #
...     .run()
... )
>>> from pprint import pprint
>>> pprint(mapping)
{'BANKING 07:0851': 0,
 'BANKS 09:1133': 2,
 'BLOCKCHAIN 05:1180': 1,
 'BUSINESS_MODEL 05:1578': 1,
 'CHINA 06:0673': 0,
 'CONSUMERS 07:0925': 2,
 'DATA 07:1086': 2,
 'FINANCE 21:3481': 0,
 'FINANCIAL_SERVICE 12:2100': 1,
 'FINANCIAL_TECHNOLOGIES 14:2005': 0,
 'FINTECH 44:6942': 0,
 'INNOVATION 15:2741': 0,
 'INVESTMENT 06:1294': 1,
 'REGULATORS 08:0974': 0,
 'SERVICES 07:1226': 1,
 'TECHNOLOGIES 15:1810': 0,
 'THE_DEVELOPMENT 08:1173': 0,
 'THE_FINANCIAL_INDUSTRY 09:2006': 0,
 'THE_FINANCIAL_SERVICES_INDUSTRY 06:1237': 1,
 'THE_IMPACT 06:0908': 0}

Example

>>> mapping = (
...     TermsToClustersMapping()
...     #
...     # FIELD:
...     .having_terms_in_top(20)
...     .having_terms_ordered_by("OCC")
...     .having_term_occurrences_between(None, None)
...     .having_term_citations_between(None, None)
...     .having_terms_in(None)
...     #
...     # COUNTERS:
...     .using_term_counters(False)
...     #
...     # NETWORK:
...     .using_clustering_algorithm_or_dict("louvain")
...     .using_association_index("association")
...     #
...     # DATABASE:
...     .where_root_directory_is("example/")
...     .where_database_is("main")
...     .where_record_years_range_is(None, None)
...     .where_record_citations_range_is(None, None)
...     .where_records_match(None)
...     #
...     .run()
... )
>>> from pprint import pprint
>>> pprint(mapping)
{'BANKING': 0,
 'BANKS': 2,
 'BLOCKCHAIN': 1,
 'BUSINESS_MODEL': 1,
 'CHINA': 0,
 'CONSUMERS': 2,
 'DATA': 2,
 'FINANCE': 0,
 'FINANCIAL_SERVICE': 1,
 'FINANCIAL_TECHNOLOGIES': 0,
 'FINTECH': 0,
 'INNOVATION': 0,
 'INVESTMENT': 1,
 'REGULATORS': 0,
 'SERVICES': 1,
 'TECHNOLOGIES': 0,
 'THE_DEVELOPMENT': 0,
 'THE_FINANCIAL_INDUSTRY': 0,
 'THE_FINANCIAL_SERVICES_INDUSTRY': 1,
 'THE_IMPACT': 0}