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nx_analyst_multi.nx
buildroot/runtime/_hdl_build/nx_analyst_multi.nx
about
nx_analyst_multi.nx -- LIB: MULTI-COLUMN relationship analysis -- the "find patterns" half of the general
data analyst (rung 3). Integer Pearson correlation between two columns + a data-driven strength class +
a KEY-DRIVER finder (which of N candidate columns most correlates with a target). Composes nx_dataframe.
OVERFLOW-AWARE: uses CENTERED sums (subtract the integer mean first) so intermediates stay ~n*V^2 rather
than n^2*V^2 -- safe for moderate n*V (documented bound); i128/normalized scale = the follow-on for very
large streams. license_tier: ORIGINAL
dependencies 2 imports · 4 importers
imports: nx_syscalls.nxnx_dataframe.nx
imported by: nx_analyst_infer.nxnx_analyst_insight.nxnx_analyst_multi_gate.nxnx_analyst_report.nx
structs
| none |
consts
| 10 | const AM_R_DEGENERATE: i64 = 0 - 2000 // sentinel: a column has zero variance -> correlation undefined |
functions
| 14 | func am_pearson_milli(x: *i64, y: *i64, n: i64) -> i64 called by 12: maindb_relrowai_confound_scanai_spearman_millimainai_mine_scan+6 calls 3: sys_mmapdf_meandf_isqrt |
| 43 | func am_covariance(x: *i64, y: *i64, n: i64) -> i64 |
| 56 | func am_class(r_milli: *u8, r: i64, out: *u8) -> i64 |
| 83 | func am_key_driver(target: *i64, cols: *i64, ncol: i64, n: i64, out_idx: *i64, out_r: *i64) -> i64 |