Clusters to Terms Mapping

>>> from techminer2.packages.networks.co_occurrence.keywords 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 32:5393',
     'FINANCE 11:1950',
     'FINANCIAL_SERVICE 08:1680',
     'INNOVATION 08:0990',
     'BUSINESS_MODEL 04:1472',
     'BLOCKCHAIN 04:0945',
     'FINANCIAL_SERVICES_INDUSTRIES 03:0949',
     'SURVEYS 03:0484',
     'BANKING 03:0370',
     'MARKETPLACE_LENDING 03:0317',
     'ELECTRONIC_MONEY 03:0305'],
 1: ['FINANCIAL_TECHNOLOGIES 03:0461',
     'CROWDFUNDING 03:0335',
     'SUSTAINABILITY 03:0227',
     'SUSTAINABLE_DEVELOPMENT 03:0227',
     'LITERATURE_REVIEW 02:0560'],
 2: ['FINANCIAL_INSTITUTION 04:0746',
     'COMMERCE 03:0846',
     'FINANCIAL_INCLUSION 03:0590',
     'DIGITAL_TECHNOLOGIES 02:0494']}