View source: R/dnam_search_index.R
make_si | R Documentation |
Make search index from table of hashed features. Additional details about the hnswlib search index parameters (e..g 'space_val', 'efc_val', 'm_val', and 'ef_val') can be found in the Python package docstrings and ReadMe.
make_si( fh_csv_fpath, si_fname = "new_search_index.pickle", si_dict_fname = "new_index_dict.pickle", threads = 4, space_val = "l2", efc_val = 2000, m_val = 1000, ef_val = 2000 )
fh_csv_fpath |
Name/path of csv (e.g. a table of hashed features) containing data for the index (required, string, "bvaltest.csv", where rows = samples, cols = features). |
si_fname |
Name of new search index file to save (required, string, "new_search_index.pickle") |
si_dict_fname |
Name of new index dictionary, with string labels, to save (required, string, "new_index_dict.pickle"). |
threads |
Number of threads for processing new index (required, int, 4). |
space_val |
Space value for new search index (required, valid string, l2'). |
efc_val |
EFC value for the index (required, int, 2000). |
m_val |
M value for the index (required, int, 1000). |
ef_val |
EF value for the index (required, int, 2000). |
Boolean, TRUE if new search index and dictionary created, FALSE if creating the new search index and dictionary files failed, otherwise NULL.
# fh_csv_fpath <- system.file("extdata", "fhtest", # package = "recountmethylation") # fh_csv_fpath <- file.path(fh_csv_fpath, "bval_fn.csv") # make_si(fh_csv_fpath)
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