116 lines
17 KiB
Plaintext
116 lines
17 KiB
Plaintext
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é($j³1 ã óœ — d Z ddlmZ ddlZddlZddlmZ ddlmZ ddl Z
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ddl Z ed« Z
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d
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d„Zdd„Zdd „Zdd
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„Zd „ Zed k( r e« yy)ud _analyze_varisol.py — analyse inject_variable_isolation output.
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Reads /mnt/d/Resonance_Engine/traj/varisol_<RUN_ID>/injections.jsonl
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Outputs the four tests Claude Desktop specified:
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1. S/N test — peak_delta_asym / pre_std_asym per (var, quantile)
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2. Directionality — does sign(response) flip with sign(strength)?
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3. Stress symmetry — stress_xx vs yy isotropic vs anisotropic
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4. Control test — mid_price near-zero check
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Plus per-variable signature table aggregated over reps.
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Plus the new test enabled by adding calibration runs:
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5. Calibration regression — is each variable response explained by
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amplitude alone (does it fall on the raw-strength response curve)?
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If yes → variable is "just amplitude". If no → variable has structure.
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Usage:
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python3 _analyze_varisol.py latest
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python3 _analyze_varisol.py <RUN_ID>
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startswithÚexists)ÚargÚpÚrunss ú+/mnt/d/Resonance_Engine/_analyze_varisol.pyÚfind_runr s• € Ø
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|||-|||,|.dšœ« �Œ} t « |j= |d›z dœ¬�« t dž|d›z › �« t dŸ« y ) Né r z=== analyzing z ===
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z meta.jsonzrun_id=Úrun_idz
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started=Úwall_iso_startz
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variables=Ú variablesz
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quantiles=Ú quantilesz
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str_cap=Ústr_capzcalibration_strengths=Úcalibration_strengthsz
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n_repeats=Ú n_repeatsz total=Ún_total_injectionszbaseline_clean_stats.jsonz === verified-stable baseline ===z baseline_anchor_asym = Úbaseline_anchor_asymz.3fz asymmetry: mean=r6 z std=r7 z.4fz coherence: mean=r8 Ú
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coherence_stdz stress_xy: mean=Ústress_xy_meanz.6fÚ
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stress_xy_stdz vel_mean : mean=Ú
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vel_mean_meanÚ vel_mean_stdz n=Únzloaded z injection records (r0 Úvariablez variable, Ú calibrationz calibration)
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z==== TEST 1: SIGNAL/NOISE (peak_asym_delta / pre_asym_std) ===z<18r9 z>10r4 z>12z
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sn(mean3reps)z>17u peak_Δasymz>14Ú
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halflife_sz>13)r1 r9 r4 )Ú asymmetry_snÚmean)Úasymmetry_peak_deltark )Úasymmetry_halflife_srk )Úsn_meanÚ peak_meanÚ
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halflife_meanr1 rn g @z BELOW NOISEr& z>+12.5fz>17.3fro z>+14.4frp z zQ (S/N < 2.0 = below the noise floor; that variable at that quantile is poison.)
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zL=== TEST 2: DIRECTIONALITY (does response sign flip with strength sign?) ===Ú q01_strengthu
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q01_peakÎ”Ú q99_strengthu
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q99_peakΔÚverdictz>20Úq01Úq99r rl Ú directionalz scalar/nulluJ === TEST 3: STRESS SYMMETRY (xx vs yy peak — isotropic if ratio→1) ===ziso_ratio(mean)z>18Ústress_xy_peak)rt Úq50ru rI Ústress_xy_peak_deltagš™™™™™é?Ú isotropicg à?Ú anisotropicÚmixedz>18.3fz>+17.6fzE=== TEST 4: CONTROL (mid_price should produce near-zero response) ===Ú mid_pricerj z mid_price z : strength=z+.5fz sn=u peakΔ=z+.4fu Interpretation: SN should track strength (small strength → small SN). If mid_price q50 has SN>>2.0, the encoding is wrong.
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zN=== TEST 5: CALIBRATION REGRESSION (lattice impulse response vs amplitude) ===)ry rk )Ú asym_peakÚasym_snÚxy_peakÚhalfu asym_peakΔr u xy_peakΔz>+12.4fr~ z>12.3fr€ z>+14.6fr� é é z
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asym_peak = z * strength + u R²=u → calibration slope: z (asym units per unit strength)zG PER-VARIABLE EXCESS RESPONSE (observed_peak - calibration_predicted):Ú predictedÚobservedÚresidualz rel_excess%g�íµ ÷Æ°>éd Únanz>+13.1fuÕ
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Interpretation: |relative excess| < 20% → variable response is explained by amplitude alone (no special structure). |excess| > 50% → variable has a signature beyond pure amplitude (interesting/worth using).z no calibration records found
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z8
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=== PER-VARIABLE SUMMARY (q99 vs q01, mean of reps) ===Úq99_snÚq01_snÚyesÚnoz>+14.5fz>10.2f)r1 Ús99Úp99Úsn99Ús01Úp01Úsn01rv z_aggregated.csvF)Úindexzaggregated CSV: z
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=== DONE ===) Úlenr Úargvr ÚprintÚnamer r Ú read_textrJ r r# rT ÚsumÚcopyÚgroupbyÚaggÚ reset_indexÚ sort_valuesÚiterrowsÚemptyÚfloatÚilocrk ÚnpÚsignÚvaluesÚpolyfitÚabsr Úto_csv)/r ÚrunÚmetaÚbase_pÚbrM ÚdfÚvar_dfÚcal_dfÚgrpÚ_rO Úsn_strr) Úsubrt ru r� r� r‘ rŽ rs ÚqÚssÚisoÚxyr4 ÚsnÚpeakÚcal_grpr, r ÚcoefÚr2_numÚr2_denÚr2ÚslopeÚ interceptÚstÚpredÚobsÚresidÚrelÚ summary_rowsr’ r� Údirecs/ r ÚmainrÈ \ s¢ € Ü œSŸX™X› ¨Ò*Œ#�(‰(�1Š+°€CÜ
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