code wiki / _hdl_build / nx_sim_sensitivity_gate.nx
nx_sim_sensitivity_gate.nx
buildroot/runtime/_hdl_build/nx_sim_sensitivity_gate.nx
about
nx_sim_sensitivity_gate.nx -- climb the RESULTS-ROBUSTNESS axis with global SENSITIVITY ANALYSIS
(NASA-STD-7009 Results Robustness; ASME V&V / FDA expect it). Variance-based Sobol first-order indices via the
Saltelli pick-freeze Monte-Carlo estimator: S_i = Var(E[y|x_i]) / Var(y) = the fraction of output variance
explained by input i. Sim: y = 3*x1 + 4*x2 + 0*x3 (3 independent centered-uniform inputs). Analytic indices:
S1=a^2 v1/Var=360/1000, S2=b^2 v2/Var=640/1000, S3=0 (x3 irrelevant). The MC estimator must recover these,
rank x2>x1, sum to ~1 (additive=no interactions), and the irrelevant x3 must score ~0 (liar-kill: a
non-influential input cannot be assigned influence). Deterministic PRNG. GREEN iff 6/6. license_tier: ORIGINAL
dependencies 1 imports · 0 importers
imports: nx_syscalls.nx
imported by: nobody (leaf or entry point)
call flow from main pre-order; caps 40 nodes / depth 6 declared; ↻ = already shown
structs
| none |
consts
| none |
functions
| 10 | func g_w(s: *u8) -> i64 { var n: i64=0; while s[n]!=(0 as u8){n=n+1} sys_write(1,s,n); return 0 } |
| 11 | func g_n(v: i64) -> i64 { var m: i64=v; if m<0{g_w("-");m=0-m} let t:*u8=sys_mmap(24); var k:i64=0; if m==0{t[0]=48 as u8;k=1}; while m>0{t[k]=(48+(m%10)) as u8;m=m/10;k=k+1}; var i:i64=0; let o:*u8=sys_mmap(24); while i<k{o[i]=t[k-1-i];i=i+1}; sys_write(1,o,k); return 0 } |
| 12 | func g_row(id: *u8, ok: i64, pass: *i64) -> i64 { g_w(" "); g_w(id); g_w(": "); if ok==1 { g_w("OK\n"); pass[0]=pass[0]+1 } else { g_w("FAIL\n") } return 0 } |
| 13 | func iabs(x: i64) -> i64 { if x<0 { return 0-x } return x } called by 1: main |
| 14 | func xrng(s: *i64) -> i64 { var x: i64=s[0]; x = x ^ (x << 13); x = x ^ (x >> 7); x = x ^ (x << 17); s[0]=x; return x } called by 1: rpos |
| 15 | func rpos(s: *i64) -> i64 { let v: i64=xrng(s); return v & 0x3FFFFFFFFFFFFFFF } |
| 16 | func samp(s: *i64, R: i64) -> i64 { return (rpos(s)%(2*R+1)) - R } // centered uniform on [-R,R] |
| 17 | func ymodel(x1: i64, x2: i64, x3: i64) -> i64 { return 3*x1 + 4*x2 + 0*x3 } called by 1: main |
| 19 | func main() -> i64 |