Clusters to Terms Mapping

Example

>>> from techminer2.packages.networks.co_occurrence.descriptors import ClustersToTermsMapping
>>> mapping = (
...     ClustersToTermsMapping()
...     #
...     # 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)
{0: ['FINTECH 44:6942',
     'FINANCE 21:3481',
     'INNOVATION 15:2741',
     'TECHNOLOGIES 15:1810',
     'FINANCIAL_TECHNOLOGIES 14:2005',
     'THE_FINANCIAL_INDUSTRY 09:2006',
     'THE_DEVELOPMENT 08:1173',
     'REGULATORS 08:0974',
     'BANKING 07:0851',
     'THE_IMPACT 06:0908',
     'CHINA 06:0673'],
 1: ['FINANCIAL_SERVICE 12:2100',
     'SERVICES 07:1226',
     'INVESTMENT 06:1294',
     'THE_FINANCIAL_SERVICES_INDUSTRY 06:1237',
     'BUSINESS_MODEL 05:1578',
     'BLOCKCHAIN 05:1180'],
 2: ['BANKS 09:1133', 'DATA 07:1086', 'CONSUMERS 07:0925']}