Cross-station CCF equivalence + three-archive demo notebook - #4
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Extends the noisepy equivalence evidence from single-station to the cross-station case: CI.PASC (SCEDC) x BK.PKD (NCEDC) x II.PFO (EarthScope), 2022-01-02, three interstation pairs (~150/230/380 km), through real noisepy compute_fft/correlate at a 20 sps target so the Fourier-resample and sub-sample-alignment branches run inside the chain. All three pairs bit-identical (max abs diff 0.0). Two fidelity bugs found and fixed on the way: - segment_interpolate_np was 1 ulp off on ~30% of samples (2e-5 of CCF peak): numba's type unification computes (1 - nfric) in float64 while nfric*sig1[ii] stays float32; the port now encodes those semantics exactly and a reference-loop test locks them down. - preprocess_raw_np force-cast its output to float32; noisepy leaves float64 after resample when the fric branch does not fire. The adapter now keeps the chain's natural dtype (caught by the new sr=20 chain equivalence case). Also fixes the single-station harness, silently broken since the sample-alignment guard landed: both harnesses now snap the day window to the data's sample grid (CI.PASC starts 0.218 samples off midnight) and feed the same snapped window to both paths. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
A week of BHZ noise from CI.PASC (SCEDC S3), BK.PKD (NCEDC S3) and II.PFO (EarthScope S3), obspy-free from fetch through preprocessing, correlated with NoisePy's own compute_fft/correlate. Shows raw hour-long waveforms per archive, single-day vs 7-day stacked CCFs with 3/1.5 km/s moveouts, and a folded record section vs interstation distance. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Pull request overview
Extends the NoisePy numerical-equivalence validation from single-station to cross-station cross-correlation across three S3 archives, and tightens the numpy adapter to reproduce NoisePy/numba mixed-precision behavior and dtype propagation.
Changes:
- Add a new cross-station equivalence harness (
run_xcorr_eval.py) + an integration test wrapper to validate bit-level agreement through real NoisePy FFT/correlation. - Fix two fidelity mismatches in the adapter:
segment_interpolate_npmixed-precision semantics andpreprocess_raw_npoutput dtype preservation (float32 vs float64 depending on branch). - Update the single-station harness to snap day windows to the channel sample grid, and commit new benchmark result JSONs.
Reviewed changes
Copilot reviewed 8 out of 10 changed files in this pull request and generated 4 comments.
Show a summary per file
| File | Description |
|---|---|
| tests/precision/test_xcorr_equivalence.py | Adds integration test invoking the new cross-station harness. |
| tests/precision/test_preprocess_equivalence.py | Adds targeted tests for segment_interpolate_np semantics and exercises the resample branch in chain-equivalence testing. |
| seisfetch/contrib/noisepy_adapter.py | Updates adapter semantics for mixed precision in segment_interpolate_np and preserves natural dtype in preprocess_raw_np. |
| notebooks/README.md | Adds an entry for the new three-archive cross-correlation notebook. |
| benchmarks/results/xcorr_three_archives_2022-01-02.json | Stores cross-station harness results for the three interstation pairs. |
| benchmarks/results/ccf_eval_ci_pasc_2022-01-02.json | Stores updated single-station harness results after window snapping fix. |
| benchmarks/noisepy_eval/run_xcorr_eval.py | New cross-station harness (three archives, three station pairs) using NoisePy compute_fft/correlate. |
| benchmarks/noisepy_eval/run_ccf_eval.py | Adds snap_window() and uses it to align windows across paths for fair comparison. |
| .gitignore | Ignores local cache directories for the evaluation harnesses. |
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| nf32 = np.float32(nfric) | ||
| sig2[1:-1] = (1.0 - np.float64(nf32)) * sig1[2:].astype(np.float64) + ( | ||
| nf32 * sig1[1:-1] | ||
| ).astype(np.float64) |
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Addressed in a258188, with a twist: the suggested plain expression is a trap under numpy 1.x. Value-based casting means a float64 scalar does not upcast a float32 array, so np.float64(...) * float32_array silently runs in float32 there (numpy 2 promotes, so the difference is invisible in this repo's test env — but noisepy pins numpy<2). The now-strict harness caught the 2e-5 CCF divergence immediately. Fixed with np.multiply(..., dtype=np.float64), which forces float64 on every numpy version and drops the intermediate astype copy you flagged. Verified bit-exact vs numba on numpy 1.26.4 and 2.5.1.
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| dt_ns = round(1e9 / seg.sampling_rate) | ||
| day0_ns = int(day0.timestamp() * 1e9) | ||
| start_ns = seg.starttime_ns + round((day0_ns - seg.starttime_ns) / dt_ns) * dt_ns | ||
| start = datetime.fromtimestamp(start_ns / 1e9, tz=timezone.utc) |
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Fixed in a258188: to_epoch_ns() computes exact integer nanoseconds via timedelta floor-division, used by both snap_window and path_b (which had the same timestamp()*1e9 issue).
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| cache.mkdir(parents=True, exist_ok=True) | ||
| f = cache / f"{net}.{sta}.{day}.ms" | ||
| if f.exists(): | ||
| return f.read_bytes() | ||
| kwargs = {} if dc == "earthscope" else {"location": loc, "channel": cha} | ||
| raw = S3OpenClient(datacenter=dc).get_raw(net, sta, day, **kwargs) | ||
| f.write_bytes(raw) | ||
| return raw |
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Fixed in a258188: cache keys now encode datacenter and location/channel (scedc.CI.PASC.00.BHZ.<day>.ms, earthscope.II.PFO.all.<day>.ms); the notebook uses the same scheme.
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| max_abs = float(np.abs(a - b).max()) | ||
| peak = float(np.abs(a).max()) | ||
| corr = float(np.corrcoef(a, b)[0, 1]) | ||
| pair_ok = corr > 0.99999 | ||
| ok &= pair_ok | ||
| results[f"{s}-{r}"] = { | ||
| "max_abs_diff": max_abs, | ||
| "max_abs_rel_to_peak": max_abs / peak if peak else 0.0, | ||
| "waveform_corr": corr, | ||
| "pass": bool(pair_ok), | ||
| } | ||
| print( | ||
| f"{s}-{r}: corr={corr:.9f} max|diff|/peak={max_abs / peak:.2e} " | ||
| f"-> {'PASS' if pair_ok else 'FAIL'}" | ||
| ) |
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Fixed in a258188: all-zero CCFs now raise explicitly, and the pass criterion is max_abs_diff == 0.0 (bit-identity), matching the precision-bank policy that any future drift must be seen and justified. Making it strict paid off immediately — it caught a numpy-1.x casting regression while addressing the comment above.
- snap_window/path_b: exact integer epoch-ns via timedelta division; dt.timestamp()*1e9 exceeds float64's 2**53 integer range and shifted the rounding target by hundreds of ns. - run_xcorr_eval: cache keys now encode datacenter + location/channel so a rerun with different parameters can never silently reuse the wrong bytes (notebook 06 uses the same scheme, re-executed). - Harness pass criterion is now bit-identity (max_abs_diff == 0.0), with an explicit error on all-zero CCFs instead of a ZeroDivisionError. - segment_interpolate_np: dropped the redundant temp copies, but NOT the way Copilot suggested — under numpy 1.x value-based casting a float64 scalar does not upcast a float32 array, so the plain expression silently ran the first product in float32 (2e-5 CCF divergence, caught by the now-strict harness; invisible under numpy 2). np.multiply with dtype=np.float64 forces float64 on every numpy version without an intermediate astype copy. Verified bit-exact vs numba on numpy 1.26.4 and vs the reference loop on numpy 2.5.1. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
January 2022 (93 station-days, 1.1 GB across the three archives). The comparison panel now shows 1 day / 1 week / 1 month: interstation Rayleigh-wave packets emerge cleanly in the month stack on all three pairs, stepping out with distance in the folded record section. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
January-February 2022 (177 station-days, 2 GB across the three archives). The comparison panel now spans 1 day / 1 week / 1 month / 2 months: the interstation Rayleigh-wave packets sharpen and the coda stabilizes between the one- and two-month stacks on all three pairs. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
CI.RPV (Rancho Palos Verdes, SCEDC S3, blank location code) added as a fourth station: the 52-km path across the LA basin produces a dominant symmetric Rayleigh-wave packet visible from a single day of data, and the four-pair record section now shows moveout from 52 to 455 km. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Notebook 06 now demonstrates the full obspy-free path Marine asked for: StationXML fetched from each archive's FDSN station service with seisfetch's raw-HTTP client, parsed and removed with seisfetch.contrib.response (remove_response_np, cross-checked at 7.6e-16 of peak vs obspy on this data), then every station-day converted to ground velocity before the NoisePy correlation chain. A new spectra figure shows all four instruments collapsing onto the same microseism spectrum in physical units. The prose now states explicitly that the bit-identity harness runs at rm_resp=NO and where the response port's own equivalence evidence lives. Fixes a real dirty-metadata bug found on the way: EarthScope II StationXML carries 4-digit fractional seconds, which fromisoformat rejects before Python 3.11 — _parse_iso_utc now normalizes fractions (regression test added). benchmarks/RESULTS.md gains a 'NoisePy equivalence' section rendering the bit-identity JSONs as tables and embedding the two notebook validation figures (HTML inliner learned PNGs). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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What
Extends the noisepy equivalence evidence from single-station to cross-station across three archives, adds an obspy-free instrument-response-removal demonstration end to end, and ships the validation as a notebook + benchmark-page section.
Bit-identity evidence
benchmarks/noisepy_eval/run_xcorr_eval.py: CI.PASC (SCEDC S3) × BK.PKD (NCEDC S3) × II.PFO (EarthScope S3) through real noisepycompute_fft/correlateat a 20 sps target — the Fourier-resample and sub-sample-alignment branches run inside the chain. Bit-identical (max abs diff 0.0) on all three pairs; the pass criterion is now strict bit-identity. Integration test added;benchmarks/RESULTS.md/.htmlgained a "NoisePy equivalence" section with the tables and validation figures.segment_interpolate_npmust replicate numba's mixed-precision type unification — and the fix must usenp.multiply(dtype=np.float64)because numpy 1.x value-based casting silently demotes the float64-scalar product (invisible under numpy 2; caught by the strict harness); (2)preprocess_raw_npno longer force-casts to float32 — noisepy leaves float64 after resample when the fric branch doesn't fire; (3) the single-station harness had been silently broken by the sample-alignment guard — both harnesses now snap day windows to the data's sample grid (integer-exact epoch-ns; archive day files start sub-sample off midnight).Response removal without obspy
notebooks/06_cross_correlation_three_archives.ipynb(executed, committed): four stations (added CI.RPV, 52 km across the LA basin), two months (Jan–Feb 2022, 236 station-days, ~2.3 GB), fully obspy-free — StationXML fetched viaFDSNClient.get_station_textraw HTTP, parsed and removed withseisfetch.contrib.response(cross-checked at 7.6e-16 of peak vsobspy.Trace.remove_responseon this data), every station-day in physical ground velocity before the NoisePy chain. The four response-corrected spectra collapse onto the same microseism spectrum; CCF stacks show 1 day → 1 week → 1 month → 2 months convergence with surface-wave moveouts and a folded record section (52–455 km).Also fixed on the way:
_parse_iso_utcrejects EarthScope II StationXML's 4-digit fractional seconds under Python ≤3.10 — normalized, with a regression test.Review
Copilot review fully addressed (commit a258188, replies on all four threads) — including rejecting one suggestion that was a numpy-1.x casting trap, with the version-stable fix verified bit-exact against numba on numpy 1.26.4 and 2.5.1.
Tests
pytest -m "not integration"), lint green, full CI matrix green (3.9–3.13 + macOS + pymseed-next)🤖 Generated with Claude Code