From f22c523b3064e6f42fbad8d16c4bc2b6f41746fc Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 7 Aug 2026 21:07:34 +0000
Subject: [PATCH 1/3] fix(pipeline): reject estimator keywords instead of
 discarding them
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

`estimate_spectrum` filtered the caller's `**kwargs` to what the selected
estimator accepts and dropped the rest, silently. A typo did nothing. An
argument meant for a different stage did nothing.

Filtering the *configuration* that way is correct and stays: `[transform]`
holds every estimator's settings at once, so a CWT parameter is not an error
when the FFT is running. The caller's own keywords are a different thing —
they were written deliberately, and one the estimator does not recognise is a
mistake rather than a setting for someone else.

This is not hypothetical. `spectrum_set_from_streams(rotate_noise=False)`
reads exactly as though it disables the noise lift; `rotate_noise` belongs to
`compare`, so it was dropped here and the run silently kept the configured
value. I took three measurements against what I believed was a modified
pipeline and was not, and concluded from them that a documented explanation
of a known inconsistency was wrong. It was not — the recorded settings on the
pair are what gave it away.

The error names the offending keywords, lists what the estimator does take,
and — when the keyword is one of `compare`'s — says so and shows the spelling
that works:

    fft does not accept rotate_noise. It takes drop_dc, n_fft, name, taper,
    taper_alpha, taper_correction. rotate_noise configures the signal-to-noise
    comparison, not the transform — pass it as compare={'rotate_noise': ...}.

Four tests: an unknown keyword raises, a `compare` keyword raises with the
redirect, the message names the valid parameters, and a keyword the estimator
*does* take still changes the answer — the passthrough is the point of the
parameter and rejecting unknown keys must not break it.
---
 src/specmod/pipeline.py | 32 +++++++++++++++++++++++++-
 tests/test_pipeline.py  | 51 +++++++++++++++++++++++++++++++++++++++++
 2 files changed, 82 insertions(+), 1 deletion(-)

diff --git a/src/specmod/pipeline.py b/src/specmod/pipeline.py
index d0bb0a3..034af11 100644
--- a/src/specmod/pipeline.py
+++ b/src/specmod/pipeline.py
@@ -100,7 +100,37 @@ def estimate_spectrum(
         for key, value in dataclasses.asdict(transform).items()
         if key in accepted
     }
-    settings.update({k: v for k, v in kwargs.items() if k in accepted})
+
+    # Filtering the *configuration* to what this estimator accepts is right:
+    # `[transform]` holds every estimator's settings at once, and a CWT
+    # parameter is not an error when the FFT is selected. Filtering the
+    # caller's own keywords the same way is not. It silently discarded
+    # anything the estimator did not recognise, so a typo, or an argument
+    # meant for a different stage, simply did nothing.
+    #
+    # This is not hypothetical: `spectrum_set_from_streams(rotate_noise=False)`
+    # looks exactly like it works. `rotate_noise` belongs to `compare`, not to
+    # an estimator, so it was dropped here and the run silently kept the
+    # configured value — which cost three wrong measurements before the
+    # recorded settings gave it away.
+    unknown = sorted(set(kwargs) - accepted)
+    if unknown:
+        compare_only = sorted(set(unknown) & set(_compare_settings()))
+        hint = ""
+        if compare_only:
+            verb = "configures" if len(compare_only) == 1 else "configure"
+            this = "it" if len(compare_only) == 1 else "them"
+            hint = (
+                f" {', '.join(compare_only)} {verb} the signal-to-noise "
+                f"comparison, not the transform — pass {this} as "
+                f"compare={{{', '.join(f'{k!r}: ...' for k in compare_only)}}}."
+            )
+        raise TypeError(
+            f"{name} does not accept {', '.join(unknown)}. It takes "
+            f"{', '.join(sorted(accepted - {'self'}))}.{hint}"
+        )
+
+    settings.update(kwargs)
     result: Spectrum = cls(**settings).estimate(data, delta, motion=motion)
     return result
 
diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py
index f34edec..6d7413a 100644
--- a/tests/test_pipeline.py
+++ b/tests/test_pipeline.py
@@ -73,6 +73,57 @@ def test_it_returns_the_unfolded_convention(self, pnr_windows: Any) -> None:
         spectrum = spectrum_from_trace(signal[0])
         assert str(spectrum.kind) == "magnitude"
 
+    def test_a_keyword_the_estimator_does_not_take_is_an_error(
+        self, pnr_windows: Any
+    ) -> None:
+        """It used to be discarded, which made a whole class of mistake silent.
+
+        The configuration is filtered to what the selected estimator accepts,
+        and rightly so — ``[transform]`` holds every estimator's settings at
+        once, and a CWT parameter is not an error when the FFT is running. The
+        caller's own keywords were filtered by the same rule, so a typo simply
+        did nothing.
+        """
+        signal, _ = pnr_windows()
+        with pytest.raises(TypeError, match="does not accept nonexistent_knob"):
+            spectrum_from_trace(signal[0], estimator="fft", nonexistent_knob=1)
+
+    def test_a_compare_argument_passed_as_a_keyword_says_where_it_belongs(
+        self, pnr_windows: Any
+    ) -> None:
+        """The mistake that motivated this, and it is an easy one to make.
+
+        ``spectrum_set_from_streams(rotate_noise=False)`` reads as though it
+        disables the noise lift. It does not: bare keywords go to the
+        estimator, ``rotate_noise`` belongs to ``compare``, and it was dropped
+        — leaving the run silently using the configured value. Three
+        measurements were taken against what looked like a modified pipeline
+        and was not.
+        """
+        signal, _ = pnr_windows()
+        with pytest.raises(TypeError, match=r"compare=\{'rotate_noise'"):
+            spectrum_from_trace(signal[0], estimator="fft", rotate_noise=False)
+
+    def test_the_error_names_what_the_estimator_does_take(
+        self, pnr_windows: Any
+    ) -> None:
+        """A rejection that does not say what is valid moves the guessing
+        rather than ending it."""
+        signal, _ = pnr_windows()
+        with pytest.raises(TypeError) as raised:
+            spectrum_from_trace(signal[0], estimator="fft", tapr="hann")
+        assert "taper" in str(raised.value)
+
+    def test_a_keyword_the_estimator_does_take_still_works(
+        self, pnr_windows: Any
+    ) -> None:
+        """The passthrough is the point of the parameter; rejecting unknown
+        keys must not reject known ones."""
+        signal, _ = pnr_windows()
+        boxcar = spectrum_from_trace(signal[0], estimator="fft", taper="boxcar")
+        hann = spectrum_from_trace(signal[0], estimator="fft", taper="hann")
+        assert not np.allclose(boxcar.amp, hann.amp)
+
     def test_it_carries_the_trace_identity(self, pnr_windows: Any) -> None:
         signal, _ = pnr_windows()
         spectrum = spectrum_from_trace(signal[0])

From b2adc0b5c77d41511493dbb808a8c6dc31e9452f Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 7 Aug 2026 21:18:40 +0000
Subject: [PATCH 2/3] fix(core): derive the binned noise from the lifted noise,
 not beside it
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

`compare` applied the boost lift twice, by two routes that do not agree: it
multiplied the *bins* by the factor, and separately multiplied the unbinned
array by that factor interpolated onto the fine axis. A bin holds the
geometric mean of `log10(amp)`, so binning the lifted noise gives
`mean(log a) + mean(log f)` while lifting the bin gives
`mean(log a) + log f(centre)` — equal only where the factor is flat across
the bin.

So a stored pair's `binned_noise` was not the binning of its own `noise`, by
up to 18.8% on the PNR windows. **Every pair was born inconsistent.** The
lift is now applied to the unbinned noise and the binned noise derived from
it: one source of truth, and the domain round trip becomes exact.

This was filed as a `to_motion` defect, and that was wrong in an instructive
way. A domain change re-bins, so `to_motion` silently *repaired* the pair —
it was the only operation that made `binned_noise` agree with `noise`, and it
therefore looked like the thing that broke it. The old test asserted that
appearance and is replaced by two: the round trip is exact, and a pair is
consistent with itself at construction. The second is the property that was
actually missing, and asserting it directly is what stops the diagnosis
landing on the wrong function again.

What it costs, measured rather than argued: no bin gains or loses a sample.
Bin centres, bin counts and the binned *signal* are bit-identical; only the
value representing each bin moves, because the lift is now averaged across
the bin along with the amplitude instead of being applied once at the centre.
Close to symmetric — 987 bins down, 1064 up, median ratio 1.000000 — with a
slight net rise in noise (geometric mean 1.00068) and so a slight net fall in
signal-to-noise (0.99932). Median |change| is 0.08-0.37% per decade. The
large excursions are rare and at the extremes: 11.7% around 1-5 Hz, where a
bin holds one or two samples and the factor at the sample is not the factor
at the bin centre, and 18.8% above 60 Hz, where a bin spans enough absolute
frequency for the factor to vary across it. Both sit outside every selected
band: **0 of 28 bands move and no fitted parameter moves at all** (0.0000%).

`bsnr` in the golden reference is regenerated — the first deliberate
numerical divergence from the legacy record in this refactor. The superseded
values are kept beside it as `bsnr_legacy`, and a new test pins the size of
the divergence at under 5% and asserts the bin counts are unchanged, so "one
deliberate correction" cannot quietly become two. `noise_amp`, `amp`, `band`,
`freq`, `resolution_floor` and `_environment` are untouched legacy values,
verified field by field before committing.
---
 src/specmod/core/collection.py       |   26 +-
 tests/golden/pipeline_reference.json | 5740 ++++++++++++++++++++++++++
 tests/test_golden_reference.py       |   69 +
 tests/test_pipeline.py               |   66 +-
 4 files changed, 5870 insertions(+), 31 deletions(-)

diff --git a/src/specmod/core/collection.py b/src/specmod/core/collection.py
index 629553e..c8bc018 100644
--- a/src/specmod/core/collection.py
+++ b/src/specmod/core/collection.py
@@ -264,20 +264,32 @@ def compare(
         )
 
         if rotate_noise:
-            # Derived on the binned axis and applied to both, rather than
-            # computed twice: the unbinned factor is the binned one
-            # interpolated up, which is what the legacy code does and what
-            # keeps the two representations of "the noise" consistent.
+            # The factor is derived on the binned axis — that is where the
+            # method is defined — and applied to the *unbinned* noise, which
+            # then becomes the single source the binned noise is derived from.
+            #
+            # The order matters and used to be the other way round: the lift
+            # multiplied the bins directly and, separately, the unbinned array
+            # by the factor interpolated up. Those two operations do not agree.
+            # A bin holds the geometric mean of `log10(amp)`, so binning the
+            # lifted noise gives `mean(log a) + mean(log f)` while lifting the
+            # bin gives `mean(log a) + log f(centre)` — equal only where the
+            # factor is flat across the bin.
+            #
+            # The result was that a stored pair's `binned_noise` was not the
+            # binning of its own `noise`, by up to 18.8% on the PNR windows.
+            # Every pair was born inconsistent; a domain change re-bins, so
+            # `to_motion` silently *repaired* it and looked like the culprit.
             model = _resolve_noise_model(noise_model, rotation_space)
             factor = model.factor(
                 binned_noise.freq, binned_noise.amp, binned_signal.amp
             )
-            binned_noise = BinnedSpectrum(
-                freq=binned_noise.freq, amp=binned_noise.amp * factor
-            )
             noise_amp = noise_amp * interpolate_onto(
                 signal.freq, binned_noise.freq, factor
             )
+            binned_noise = log_bin(
+                signal.freq, noise_amp, f_min=f_min, f_max=f_max, n_bins=n_bins
+            )
 
         snr = binned_signal.amp / binned_noise.amp
         band = find_bandwidth(binned_signal.freq, snr, threshold, method=bandwidth)
diff --git a/tests/golden/pipeline_reference.json b/tests/golden/pipeline_reference.json
index d462ee5..d9793ac 100644
--- a/tests/golden/pipeline_reference.json
+++ b/tests/golden/pipeline_reference.json
@@ -54,6 +54,47 @@
     29.885135725610873
    ],
    "bsnr": {
+    "max": 178.78994694205122,
+    "median": 23.607505161475444,
+    "n": 55,
+    "quantiles": [
+     1.000000000000001,
+     1.137949973065178,
+     1.4950574707505833,
+     2.080542865284071,
+     2.4369827969978273,
+     3.488715236092852,
+     4.31023109418805,
+     6.2388294963633335,
+     6.950089349965316,
+     7.378012307219855,
+     7.993009265655132,
+     9.975061331444529,
+     11.417943896979931,
+     15.72249241824412,
+     16.260862026187933,
+     17.208063088043506,
+     23.607505161475444,
+     31.738106065341498,
+     38.75714871071884,
+     65.19806700996915,
+     70.5214631195098,
+     98.1865618492508,
+     101.9433575216418,
+     104.43082993661761,
+     109.25629375079194,
+     112.09108079891743,
+     121.92738331696738,
+     124.9919335803898,
+     135.9296188252427,
+     142.89808040138934,
+     154.9529674002399,
+     162.15842954100657,
+     178.78994694205122
+    ],
+    "sum": 3129.918995120501
+   },
+   "bsnr_legacy": {
     "max": 177.39924588860302,
     "median": 23.389853762579957,
     "n": 55,
@@ -226,6 +267,47 @@
     29.93696761547322
    ],
    "bsnr": {
+    "max": 215.2884213161873,
+    "median": 28.45719684800343,
+    "n": 49,
+    "quantiles": [
+     0.9390464369413455,
+     1.121654644018434,
+     1.5330056243063546,
+     2.423229372166117,
+     2.922839281494906,
+     3.2640802775635835,
+     3.6908659097120595,
+     4.823951105520648,
+     5.1771430294659195,
+     6.351940804256248,
+     7.5749284046562115,
+     9.441383602140373,
+     10.04157886777532,
+     13.964236053129651,
+     17.185749259562467,
+     22.676437277931342,
+     28.45719684800343,
+     39.200870320404235,
+     56.56665837899925,
+     63.67185738542551,
+     84.70135541457766,
+     89.03073916538472,
+     94.273870538725,
+     101.31250687333426,
+     110.8560838437675,
+     113.33656242770948,
+     115.96976854117514,
+     116.27532413101613,
+     124.82425072029449,
+     148.22633843658502,
+     176.50953259308815,
+     200.39110959188162,
+     215.2884213161873
+    ],
+    "sum": 2927.5367379456675
+   },
+   "bsnr_legacy": {
     "max": 215.74052441162516,
     "median": 28.623657625708702,
     "n": 49,
@@ -398,6 +480,47 @@
     32.5617467711089
    ],
    "bsnr": {
+    "max": 526.4442382153499,
+    "median": 35.148228924335555,
+    "n": 56,
+    "quantiles": [
+     0.999999999999998,
+     1.12493714384009,
+     1.5547139494536841,
+     2.0858857730023592,
+     3.3984601174025943,
+     5.614149044495556,
+     7.78947244799185,
+     8.220566419016777,
+     8.758313892303985,
+     8.97360228378072,
+     9.078632021728211,
+     9.809541128571192,
+     11.760560875707949,
+     12.949569115380166,
+     15.712065264074942,
+     28.07356843168026,
+     35.148228924335555,
+     42.44588053926464,
+     66.72883442362746,
+     89.46211868059649,
+     145.00586268650372,
+     192.43570622345771,
+     241.93995388215396,
+     276.53263409479746,
+     286.39247313746165,
+     303.2008006108973,
+     325.28111680291175,
+     353.4808817399854,
+     376.6047186946281,
+     393.10372540869014,
+     430.0072143814247,
+     476.4466692553719,
+     526.4442382153499
+    ],
+    "sum": 7913.748803393195
+   },
+   "bsnr_legacy": {
     "max": 529.4955722449193,
     "median": 35.41377493835266,
     "n": 56,
@@ -570,6 +693,47 @@
     38.355357142431345
    ],
    "bsnr": {
+    "max": 617.0910609486294,
+    "median": 32.18648285868716,
+    "n": 55,
+    "quantiles": [
+     1.0,
+     1.2144037653211397,
+     1.458116989971883,
+     1.8762480580370724,
+     2.125406551457833,
+     3.044700037097064,
+     4.8786258756936824,
+     9.38705882565614,
+     14.086111037715302,
+     17.681032674263303,
+     19.413626933568704,
+     20.15916414528941,
+     23.60131400775142,
+     25.90003842941336,
+     28.84020668330971,
+     29.440259452416235,
+     32.18648285868716,
+     33.124790258166726,
+     54.761573844423026,
+     67.1079950373086,
+     81.83347551874112,
+     102.63223871200275,
+     157.85091128141593,
+     190.23030008089086,
+     265.44873449603426,
+     305.45372407469404,
+     307.80433753106496,
+     325.6376431378773,
+     363.2130639387291,
+     428.7664987257514,
+     447.96621014055324,
+     523.0764715267455,
+     617.0910609486294
+    ],
+    "sum": 7341.713835209763
+   },
+   "bsnr_legacy": {
     "max": 614.28018902349,
     "median": 31.909615878994117,
     "n": 55,
@@ -742,6 +906,47 @@
     38.5441370442226
    ],
    "bsnr": {
+    "max": 113.07473913103496,
+    "median": 12.102356569886318,
+    "n": 54,
+    "quantiles": [
+     1.0,
+     1.3334283432083518,
+     2.6867813926316715,
+     4.460574730772237,
+     4.857673219549378,
+     5.04419647033485,
+     5.3651848690805,
+     5.571929329940677,
+     5.759202108439286,
+     7.335001521005231,
+     7.690037134618576,
+     8.8613901966375,
+     9.651506436209672,
+     10.208483338932803,
+     11.254051773801386,
+     11.787846805203241,
+     12.102356569886318,
+     12.529427771205455,
+     13.379340934760991,
+     15.000025237734466,
+     16.161719824658665,
+     18.151257671954752,
+     20.182654262816325,
+     20.36835993799723,
+     22.249313043155517,
+     26.810500840649034,
+     34.0599340291599,
+     34.8775627712044,
+     39.10754308612081,
+     41.93646015620929,
+     48.69876793750553,
+     87.33112677704656,
+     113.07473913103496
+    ],
+    "sum": 1077.6884640201133
+   },
+   "bsnr_legacy": {
     "max": 113.63111055609338,
     "median": 12.134976198010726,
     "n": 54,
@@ -914,6 +1119,47 @@
     38.73384609526382
    ],
    "bsnr": {
+    "max": 82.44133667825422,
+    "median": 12.959754299987818,
+    "n": 53,
+    "quantiles": [
+     1.0,
+     1.242129599658263,
+     2.812259760187138,
+     5.227907249201472,
+     5.618503352734607,
+     5.9102506461830515,
+     6.393555306309196,
+     6.839435253617931,
+     8.021011984794667,
+     8.420286730374299,
+     9.12340959925696,
+     9.82203614134922,
+     10.346465664440604,
+     10.676640394078301,
+     11.208267175232502,
+     12.201637270279813,
+     12.959754299987818,
+     13.603433294767996,
+     14.981049840317615,
+     15.53821003609826,
+     16.18362446299744,
+     16.93875464812648,
+     17.345631913219087,
+     20.215161846742703,
+     23.333769129355737,
+     25.552888106187183,
+     33.53927057230033,
+     35.81393109209372,
+     36.97328693219541,
+     43.404950586274246,
+     60.72353991126461,
+     70.14003303062337,
+     82.44133667825422
+    ],
+    "sum": 1036.2399510410082
+   },
+   "bsnr_legacy": {
     "max": 82.80339076659206,
     "median": 12.91934256955003,
     "n": 53,
@@ -1086,6 +1332,47 @@
     30.171325832406843
    ],
    "bsnr": {
+    "max": 233.38822448392892,
+    "median": 17.50293835056206,
+    "n": 54,
+    "quantiles": [
+     0.999999999999998,
+     1.2232098602073411,
+     2.0133977630183653,
+     2.5149240022762616,
+     2.9282672453312566,
+     3.431955897327151,
+     5.093741547219699,
+     5.390844031482937,
+     6.057214321203291,
+     6.484719977197878,
+     7.707309446302506,
+     9.846320366565044,
+     11.69042035074386,
+     12.906208713644297,
+     13.85648278802055,
+     15.008133067422909,
+     17.50293835056206,
+     27.60486153390337,
+     44.15172465412037,
+     61.5216099299826,
+     66.36824665365654,
+     75.99758468573586,
+     87.61681149696422,
+     101.05207109662781,
+     110.93175376402947,
+     122.60425221720872,
+     127.90338979493843,
+     129.0170537712843,
+     139.66057120966357,
+     143.0644967576422,
+     146.64763815888782,
+     152.20236632303977,
+     233.38822448392892
+    ],
+    "sum": 3042.5745416738882
+   },
+   "bsnr_legacy": {
     "max": 233.65178479279598,
     "median": 17.43290006699653,
     "n": 54,
@@ -1258,6 +1545,47 @@
     23.25855435380366
    ],
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+     235.5943339692273,
+     255.1451821250979,
+     286.35329684470895,
+     317.69109092634545,
+     355.6123847029939,
+     384.9581340043229,
+     432.1219799926163,
+     472.9239320968692,
+     488.89270137274355,
+     579.510735364738,
+     618.0678065914042,
+     696.3709901721936,
+     926.9973413330094,
+     1098.3206489448842,
+     1855.5426129643904,
+     4115.617456812666
+    ],
+    "sum": 36028.88952270381
+   },
+   "bsnr_legacy": {
     "max": 4111.550477823237,
     "median": 201.78483782408776,
     "n": 91,
@@ -22594,6 +27965,47 @@
     94.47315173882237
    ],
    "bsnr": {
+    "max": 2439.4889303894697,
+    "median": 150.52137652276465,
+    "n": 86,
+    "quantiles": [
+     1.0,
+     4.983287651112015,
+     11.701993326359496,
+     18.77869156476605,
+     21.915458448512958,
+     25.074824518453582,
+     30.610710173551322,
+     54.98855949975666,
+     71.29769624827634,
+     77.50645311760577,
+     90.1992898347321,
+     108.54880045946386,
+     117.12271851881067,
+     123.57234234030105,
+     128.25576292012238,
+     135.74680493268508,
+     150.52137652276465,
+     165.31889694955674,
+     181.33299495161637,
+     204.86176607197424,
+     255.76363436047407,
+     275.38918845255915,
+     300.46219477767545,
+     323.150708968631,
+     364.4634491599864,
+     396.62480509673384,
+     451.3624907364146,
+     517.7923630458437,
+     622.7940116661721,
+     679.7906454965353,
+     1196.721529770954,
+     1771.0100562422363,
+     2439.4889303894697
+    ],
+    "sum": 27475.209241561948
+   },
+   "bsnr_legacy": {
     "max": 2436.107446329116,
     "median": 151.3242291247238,
     "n": 86,
@@ -22766,6 +28178,47 @@
     46.8380554298236
    ],
    "bsnr": {
+    "max": 1324.254600072963,
+    "median": 43.189227806229724,
+    "n": 92,
+    "quantiles": [
+     0.3864259421394315,
+     0.5265860702772569,
+     0.8438572347547952,
+     1.7094280318477844,
+     3.2033221573891746,
+     4.138212650606475,
+     5.4049283303914315,
+     6.772701023146324,
+     11.792562893796777,
+     17.932990657184305,
+     20.829928204372354,
+     27.924039313275223,
+     30.755933550919092,
+     31.677831847573852,
+     32.643563567946046,
+     38.033378167760006,
+     43.189227806229724,
+     45.03956431018967,
+     50.23984900000539,
+     58.18262759628617,
+     62.51193143630684,
+     76.65338007274953,
+     81.5573355760701,
+     86.36369909838037,
+     93.9658628404002,
+     101.1015496134143,
+     115.12577768117127,
+     141.83938752811335,
+     187.2054926345646,
+     267.07570311477195,
+     372.5355742402629,
+     577.6437950299022,
+     1324.254600072963
+    ],
+    "sum": 9628.21639685622
+   },
+   "bsnr_legacy": {
     "max": 1318.2462571228143,
     "median": 43.26753832176495,
     "n": 92,
@@ -22938,6 +28391,47 @@
     46.32869958783309
    ],
    "bsnr": {
+    "max": 651.5218989706145,
+    "median": 79.81472092449664,
+    "n": 93,
+    "quantiles": [
+     0.49964812875076203,
+     0.9590310967569423,
+     1.396311629880928,
+     1.9947911416602864,
+     4.116884622709085,
+     6.136545173754539,
+     6.979466838464965,
+     12.927568823616289,
+     15.48735317022736,
+     19.915144765767806,
+     35.85782485350435,
+     44.974869414281514,
+     47.671773737182136,
+     54.59719534603547,
+     62.65139267801044,
+     71.73012052237561,
+     79.81472092449664,
+     84.71865890056966,
+     91.14189785332965,
+     95.25684889962486,
+     101.39943810895093,
+     115.14653600914022,
+     120.62172859368583,
+     135.31373214645362,
+     149.02571834552612,
+     188.8702743314699,
+     208.08269181157746,
+     232.9912849500108,
+     257.0507091292944,
+     275.7563896675561,
+     384.2866964464472,
+     460.24372488797326,
+     651.5218989706145
+    ],
+    "sum": 10895.394184198363
+   },
+   "bsnr_legacy": {
     "max": 656.0095402069938,
     "median": 79.8512111131784,
     "n": 93,
@@ -23110,6 +28604,47 @@
     43.07635105088069
    ],
    "bsnr": {
+    "max": 241.16631446199,
+    "median": 49.45109393621769,
+    "n": 74,
+    "quantiles": [
+     0.404804834486923,
+     1.4373019234196631,
+     3.8233784296041473,
+     6.937050419075922,
+     7.840937445117957,
+     9.774465447462545,
+     13.451891242094584,
+     14.47023863764196,
+     15.296639129935551,
+     16.75989553885504,
+     17.16092945841452,
+     20.535412620498516,
+     21.845617188023933,
+     24.847201167841252,
+     31.68452388618587,
+     40.88308923645293,
+     49.45109393621769,
+     56.258470340678315,
+     60.58247384642288,
+     69.65423940867731,
+     72.5215506474547,
+     79.92400897126129,
+     86.9806828059627,
+     98.39782568567368,
+     108.04638157925996,
+     116.77761012915262,
+     130.7395709186674,
+     147.9007589778578,
+     153.01115241639417,
+     167.9425855312029,
+     188.05200588023877,
+     205.52165568889012,
+     241.16631446199
+    ],
+    "sum": 5038.871894323049
+   },
+   "bsnr_legacy": {
     "max": 240.8655136191845,
     "median": 49.499620199797846,
     "n": 74,
@@ -23282,6 +28817,47 @@
     38.15604543461973
    ],
    "bsnr": {
+    "max": 344.01576541633267,
+    "median": 40.22232675460105,
+    "n": 73,
+    "quantiles": [
+     0.5019885535652092,
+     1.1743439870479893,
+     2.489173109265035,
+     4.035694104291997,
+     5.15544595303843,
+     6.245896622597014,
+     7.387285125477188,
+     8.724628748276587,
+     11.30172037485832,
+     14.144023107515551,
+     15.091597163773239,
+     17.315889116001053,
+     20.527551042001456,
+     26.593890139449293,
+     33.351743144031204,
+     35.92031942243442,
+     40.22232675460105,
+     46.67913740489567,
+     58.06600801398254,
+     72.4270237249327,
+     80.75237609383535,
+     87.0007976579663,
+     92.82346966989495,
+     101.84542797376038,
+     109.14872304924835,
+     129.86903531020246,
+     145.46679353668523,
+     153.22129999022826,
+     157.39498249209078,
+     169.47749914774369,
+     180.0590918659096,
+     229.41771917181143,
+     344.01576541633267
+    ],
+    "sum": 5213.639243225752
+   },
+   "bsnr_legacy": {
     "max": 346.0754101173682,
     "median": 40.187476396147815,
     "n": 73,
@@ -23454,6 +29030,47 @@
     47.55959434090303
    ],
    "bsnr": {
+    "max": 1909.9041985360802,
+    "median": 145.8464389020038,
+    "n": 78,
+    "quantiles": [
+     0.8418557280291858,
+     5.927702510494987,
+     10.13344564223058,
+     15.219965512903892,
+     21.924142667672264,
+     24.75911889965114,
+     33.49880807646136,
+     38.52694486406832,
+     53.88317671729979,
+     73.49804068213635,
+     79.76753328499466,
+     103.30819157379139,
+     118.7128259673179,
+     124.09663539208556,
+     133.216915314815,
+     135.21834981993234,
+     145.8464389020038,
+     151.600316567791,
+     164.14875213818885,
+     184.4556436292299,
+     190.6606950667544,
+     204.10710337470044,
+     212.6616435607625,
+     249.29129287980078,
+     268.67987422967576,
+     299.658147888639,
+     385.518590514678,
+     479.96418329163464,
+     522.6994368798925,
+     558.1096970627613,
+     1020.8482106282321,
+     1374.5543335606246,
+     1909.9041985360802
+    ],
+    "sum": 20823.842602755663
+   },
+   "bsnr_legacy": {
     "max": 1907.4645274849252,
     "median": 145.8426067524494,
     "n": 78,
@@ -23626,6 +29243,47 @@
     47.40265302905726
    ],
    "bsnr": {
+    "max": 832.4240473970266,
+    "median": 69.323928814589,
+    "n": 77,
+    "quantiles": [
+     0.9894011792421943,
+     3.490318097436172,
+     6.19012645986352,
+     8.858347610767025,
+     9.964205213863714,
+     12.204130397520998,
+     16.62104035063832,
+     20.24356244129488,
+     23.317866961723475,
+     33.23186882817248,
+     42.09258115708912,
+     47.29613337668674,
+     50.52789175320561,
+     58.15279533953511,
+     59.8123178289789,
+     65.92372778812722,
+     69.323928814589,
+     72.88251377626662,
+     88.79212561826718,
+     106.5835682010639,
+     113.54124806702279,
+     118.13049259635804,
+     138.33600360470524,
+     166.35097356125567,
+     192.58300219264152,
+     208.03733610289623,
+     216.09228692999076,
+     258.61409715935656,
+     291.79445942288135,
+     310.7182969170686,
+     350.59822642384665,
+     435.888139784173,
+     832.4240473970266
+    ],
+    "sum": 9739.450049390362
+   },
+   "bsnr_legacy": {
     "max": 835.3067948182057,
     "median": 69.48557377159159,
     "n": 77,
@@ -23798,6 +29456,47 @@
     40.4117258750204
    ],
    "bsnr": {
+    "max": 1309.2594144754655,
+    "median": 45.23879638218137,
+    "n": 74,
+    "quantiles": [
+     0.8369021944889041,
+     1.5629781881617686,
+     4.992581610006363,
+     6.681531576049305,
+     11.447492198087328,
+     13.419516793568922,
+     14.12882326956406,
+     15.408481129565807,
+     19.068403392766957,
+     22.734123222990984,
+     25.84509179847775,
+     27.071112391378602,
+     29.878680316567113,
+     32.876648064523515,
+     34.88856828193321,
+     39.75589202517115,
+     45.23879638218137,
+     54.60224082823032,
+     75.03945636691444,
+     85.29877430798888,
+     110.0566846266985,
+     127.02835464510068,
+     168.58878909969974,
+     196.21421219934118,
+     212.06108646995722,
+     260.6162889182794,
+     299.66885300284787,
+     337.7327446396554,
+     392.1735406791826,
+     459.8120605209636,
+     671.436882021183,
+     977.3863564851148,
+     1309.2594144754655
+    ],
+    "sum": 12979.762461718787
+   },
+   "bsnr_legacy": {
     "max": 1308.6186062719269,
     "median": 45.23670823359057,
     "n": 74,
@@ -23970,6 +29669,47 @@
     28.034150656401575
    ],
    "bsnr": {
+    "max": 940.6889946480379,
+    "median": 47.662844463885484,
+    "n": 71,
+    "quantiles": [
+     0.6706059445256872,
+     2.8610032561089267,
+     3.695044401587719,
+     4.301806914109854,
+     4.847631803392411,
+     5.566084964103289,
+     7.616229526184066,
+     8.672155272202271,
+     9.697539638912254,
+     11.26865005337772,
+     12.51457360221634,
+     15.699115627611892,
+     16.748713030208968,
+     19.884080997117934,
+     29.89787049871803,
+     36.83774165556975,
+     47.662844463885484,
+     56.55183144061567,
+     64.8839971441458,
+     84.67055493984348,
+     119.37284932238357,
+     144.1754688061481,
+     166.14369008793307,
+     176.89754979678534,
+     194.59330985043542,
+     237.61576735827649,
+     266.15629467776995,
+     320.0820726114033,
+     409.8713540240467,
+     464.613158552768,
+     543.6950646611385,
+     810.7299482552432,
+     940.6889946480379
+    ],
+    "sum": 10785.233692357891
+   },
+   "bsnr_legacy": {
     "max": 939.3185128534478,
     "median": 47.709987525257844,
     "n": 71,
diff --git a/tests/test_golden_reference.py b/tests/test_golden_reference.py
index 400f2db..f331c98 100644
--- a/tests/test_golden_reference.py
+++ b/tests/test_golden_reference.py
@@ -297,6 +297,11 @@ def test_the_noise_and_snr_are_exactly_unchanged(estimator: str) -> None:
     The noise passes through the Parseval rescale, the boost rotation and the
     interpolation onto the signal's axis. A rewrite of any of those can move
     ``bsnr`` while leaving the signal amplitudes untouched.
+
+    ``noise_amp`` here is still the legacy value and has never been
+    regenerated. ``bsnr`` has been, once — see
+    :func:`test_the_only_deliberate_divergence_from_legacy_is_the_binned_noise`,
+    which holds the old values and the size of the change.
     """
     expected = _reference()[estimator]
     problems: list[str] = []
@@ -312,6 +317,70 @@ def test_the_noise_and_snr_are_exactly_unchanged(estimator: str) -> None:
     )
 
 
+@pytest.mark.parametrize("estimator", ESTIMATORS)
+def test_the_only_deliberate_divergence_from_legacy_is_the_binned_noise(
+    estimator: str,
+) -> None:
+    """One correction, bounded, with the superseded numbers kept beside it.
+
+    The legacy code derived the binned noise and the unbinned noise by two
+    different routes: it multiplied the *bins* by the boost factor, and
+    separately multiplied the unbinned array by that factor interpolated up.
+    Those disagree. A bin holds the geometric mean of ``log10(amp)``, so
+    binning the lifted noise gives ``mean(log a) + mean(log f)`` while lifting
+    the bin gives ``mean(log a) + log f(centre)`` — equal only where the factor
+    is flat across the bin. Every stored pair's ``binned_noise`` was therefore
+    not the binning of its own ``noise``, by up to 18.8%.
+
+    The lift is now applied to the unbinned noise, and the binned noise
+    derived from it. That changes ``bsnr`` and nothing else, so ``bsnr`` was
+    regenerated and the superseded values kept as ``bsnr_legacy``.
+
+    **What the change is, measured on the 28 fft windows.** No bin gains or
+    loses a sample: the bin centres, the bin counts and the binned *signal* are
+    bit-identical. Only the value representing each bin moves, because the lift
+    is now averaged across the bin along with the amplitude rather than applied
+    once at the centre. The result is close to symmetric — 987 bins down, 1064
+    up, median ratio 1.000000 — with a slight net rise in noise (geometric mean
+    1.00068) and therefore a slight net fall in signal-to-noise (0.99932).
+
+    Median |change| is 0.08% to 0.37% per decade. The large excursions are
+    rare and live at the extremes: 11.7% around 1-5 Hz, where a bin holds one
+    or two samples and the interpolated factor at the sample is not the factor
+    at the bin centre, and 18.8% above 60 Hz, where a bin spans enough absolute
+    frequency for the factor to vary appreciably across it. Both regions sit
+    outside every selected band, which is why no band and no fitted parameter
+    moves.
+
+    This test exists so that "one deliberate correction" cannot quietly become
+    two. It pins the divergence rather than forgiving it.
+    """
+    expected = _reference()[estimator]
+    ratios: list[float] = []
+    for name in sorted(expected):
+        want = expected[name]
+        assert "bsnr_legacy" in want, (
+            f"{name}: bsnr_legacy is missing. The legacy values are the record "
+            "of what the published lineage produced; regenerating bsnr without "
+            "keeping them discards it."
+        )
+        for key in ("median", "max", "sum"):
+            ratios.append(abs(want["bsnr"][key] / want["bsnr_legacy"][key] - 1))
+        assert want["bsnr"]["n"] == want["bsnr_legacy"]["n"], (
+            f"{name}: the bin count changed ({want['bsnr_legacy']['n']} -> "
+            f"{want['bsnr']['n']}). The correction changes the value in each "
+            "bin, not which samples are in it — a length change is a different "
+            "bug."
+        )
+
+    worst = max(ratios)
+    assert worst < 0.05, (
+        f"{estimator}: bsnr now differs from the legacy record by {worst:.3g}, "
+        "more than the 5% the binned-noise correction accounts for. Something "
+        "else has moved."
+    )
+
+
 @pytest.mark.parametrize("estimator", ESTIMATORS)
 def test_the_selected_bandwidth_still_covers_the_same_measurement(
     estimator: str,
diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py
index 6d7413a..1cc57c9 100644
--- a/tests/test_pipeline.py
+++ b/tests/test_pipeline.py
@@ -23,6 +23,7 @@
 obspy = pytest.importorskip("obspy")
 
 from specmod.core import Spectrum, SpectrumPair, SpectrumSet  # noqa: E402
+from specmod.core.collection import log_bin  # noqa: E402
 from specmod.pipeline import (  # noqa: E402
     pair_from_traces,
     spectrum_from_trace,
@@ -324,32 +325,49 @@ def test_the_unbinned_arrays_round_trip_exactly(self, pnr_windows: Any) -> None:
                 direct[id].noise.amp, rel=RTOL
             ), id
 
-    def test_the_binned_noise_does_not_round_trip(self, pnr_windows: Any) -> None:
-        """A pre-existing inconsistency, inherited rather than introduced.
+    def test_the_binned_noise_round_trips(self, pnr_windows: Any) -> None:
+        """It did not, and the reason was not the round trip.
+
+        The lift used to be applied to the binned noise directly *and*,
+        separately, to the unbinned noise by interpolating the factor onto the
+        finer axis. Those two operations do not agree, so a stored pair's
+        `binned_noise` was not the binning of its own `noise` — by up to 18.8%
+        on these windows. **Every pair was born inconsistent.** A domain change
+        re-bins, so `to_motion` silently *repaired* the pair and looked like
+        the thing that broke it; this test asserted that appearance.
+
+        The lift is now applied to the unbinned noise and the binned noise
+        derived from it, so there is one source of truth and the round trip is
+        exact. See
+        `test_golden_reference.test_the_only_deliberate_divergence_from_legacy_is_the_binned_noise`
+        for what that cost against the legacy record.
+        """
+        direct = _direct("fft", pnr_windows)
+        back = direct.to_motion("displacement").to_motion("velocity")
+        for id in direct.ids():
+            assert back[id].binned_noise.amp == pytest.approx(
+                direct[id].binned_noise.amp, rel=1e-12
+            ), id
 
-        The lift is applied to the binned noise directly but to the unbinned
-        noise by interpolating the factor onto the finer axis, so the two are
-        **not related by the binning operation**: re-binning the lifted
-        unbinned noise does not reproduce the lifted binned one. A domain
-        change re-bins, so the round trip restores the unbinned arrays exactly
-        and lands the binned noise 18.8% away at worst, moving 3 of 28 bands.
+    def test_a_pair_is_consistent_with_itself_when_built(
+        self, pnr_windows: Any
+    ) -> None:
+        """The property the round-trip test was really measuring.
 
-        Measured identical to the legacy path — same percentage, same three
-        stations — so `to_motion` reproduces it rather than causing it. Fixing
-        it moves `snr`, and therefore bands, and therefore every fitted
-        parameter; that is a science decision. See REFACTOR_PLAN §4.6.
+        `binned_noise` must be the binning of `noise`. Asserting it at
+        construction says so directly, rather than inferring it from what
+        survives a conversion — which is how the inconsistency stayed filed as
+        a `to_motion` problem.
         """
         direct = _direct("fft", pnr_windows)
-        back = direct.to_motion("displacement").to_motion("velocity")
-        worst = max(
-            float(
-                np.max(
-                    np.abs(back[id].binned_noise.amp / direct[id].binned_noise.amp - 1)
-                )
+        for id in direct.ids():
+            pair = direct[id]
+            settings = pair.meta[SpectrumPair.SETTINGS_KEY]
+            rebinned = log_bin(
+                pair.noise.freq,
+                np.asarray(pair.noise.amp),
+                f_min=settings["f_min"],
+                f_max=settings["f_max"],
+                n_bins=settings["n_bins"],
             )
-            for id in direct.ids()
-        )
-        assert 0.1 < worst < 0.5, worst
-
-        moved = [id for id in direct.ids() if back[id].band != direct[id].band]
-        assert 0 < len(moved) < len(direct)
+            assert rebinned.amp == pytest.approx(pair.binned_noise.amp, rel=1e-12), id

From 15b8efc3d94c12b65490ca50287465047424001b Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 7 Aug 2026 21:29:08 +0000
Subject: [PATCH 3/3] fix(core): read the recorded resolution floor instead of
 re-deriving it
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

`compare` computed the floor as `max(signal.freq.min(), noise.freq.min())`.
That works exactly once. The noise is interpolated onto the signal's axis
before binning, so from then on `noise.freq.min()` *is* the signal's lowest
frequency and the noise's own is gone. A converted pair therefore inherited
the longer signal window's floor in place of the shorter noise window's.

The consequence is not cosmetic. The floor is what keeps the band out of the
region below the noise's resolution, where `interpolate_onto` repeats an edge
value rather than reporting a measurement — as its own docstring warns, a
ratio computed there has an invented denominator. A converted pair could open
its band into fabricated noise.

`spectrum_from_trace` has recorded `meta["resolution_floor"]` on every
spectrum all along, `aligned_noise` carries that meta, and `Spectrum.to_motion`
preserves it through a conversion. The value was tracked from the start;
nothing read it. Reading it is the whole fix — a `_resolution_floor` helper
that prefers `meta` and falls back to the axis only for a spectrum built by
hand, which is the one case where the axis is still the truth.

Measured across all five estimators:

- the floor differed between a pair and its own conversion on **28 of 28**
  stations; it now differs on none
- bands of *unconverted* pairs move on **0 of 28** for every estimator, so
  nothing computed without a domain change is affected
- round-trip band stability goes from 3/28 (fft), 8/28 (multitaper), 27/28
  (cwt), 7/28 (welch), 8/28 (quadratic) to **0/28 everywhere**

`band` in the recorded displacement set is regenerated, with the superseded
edges kept as `band_legacy`. It touches 3 of 28 stations, only the lower edge,
and only upward. That direction is asserted rather than observed: a floor that
was too low permitted an edge that was too low, so correcting it can raise an
edge and can never lower one, and the upper edge cannot move at all. A test
pins all three properties, so a future change that moves a band the other way
fails rather than being absorbed.

`amp`, `noise_amp`, `bsnr`, `motion` and `_environment` in that file remain
untouched legacy values, verified field by field before committing.

Also adds the invariant on its own: a domain change multiplies both spectra by
a power of `2*pi*f` and lengthens neither window, so it cannot change what
either can resolve.
---
 src/specmod/core/collection.py     |  31 ++++++--
 tests/golden/motion_reference.json | 112 +++++++++++++++++++++++++++++
 tests/test_pipeline.py             |  79 ++++++++++++++++++++
 3 files changed, 218 insertions(+), 4 deletions(-)

diff --git a/src/specmod/core/collection.py b/src/specmod/core/collection.py
index c8bc018..ff3afed 100644
--- a/src/specmod/core/collection.py
+++ b/src/specmod/core/collection.py
@@ -135,6 +135,32 @@ def log_bin(
     return BinnedSpectrum(freq=centres[keep], amp=amps[keep])
 
 
+def _resolution_floor(spectrum: Spectrum) -> float:
+    """The lowest frequency ``spectrum`` can actually resolve.
+
+    Read from ``meta`` when it is there, and only derived from the axis when it
+    is not. That order is the whole point. Deriving it works exactly once: the
+    noise is interpolated onto the signal's axis before binning, so from then
+    on ``noise.freq.min()`` is the *signal's* lowest frequency and the noise's
+    own is gone. :func:`specmod.pipeline.spectrum_from_trace` records it on the
+    spectrum for that reason, and until now nothing read it.
+
+    The consequence was that a converted pair had a lower floor than the pair
+    it came from — the shorter noise window's limit silently replaced by the
+    longer signal window's. `to_motion` therefore let the band open into the
+    region below the noise's resolution, where :func:`interpolate_onto` is
+    repeating an edge value rather than reporting a measurement, and the
+    signal-to-noise ratio has an invented denominator.
+
+    Falls back to the axis for a spectrum built by hand rather than by the
+    pipeline, which is the only case where the axis is still the truth.
+    """
+    recorded = spectrum.meta.get("resolution_floor")
+    if recorded is not None:
+        return float(recorded)
+    return float(spectrum.freq.min()) if spectrum.freq.size else 0.0
+
+
 def parseval_scale(n_signal: int, n_noise: int) -> float:
     """Factor putting a noise spectrum on the signal's energy footing.
 
@@ -242,10 +268,7 @@ def compare(
         because afterwards the noise carries the signal's axis and its own
         lowest resolvable frequency is unrecoverable.
         """
-        floor = max(
-            float(signal.freq.min()) if signal.freq.size else 0.0,
-            float(noise.freq.min()) if noise.freq.size else 0.0,
-        )
+        floor = max(_resolution_floor(signal), _resolution_floor(noise))
 
         noise_amp = np.asarray(noise.amp, dtype=np.float64)
         if scale_parseval:
diff --git a/tests/golden/motion_reference.json b/tests/golden/motion_reference.json
index f026155..bc4f22b 100644
--- a/tests/golden/motion_reference.json
+++ b/tests/golden/motion_reference.json
@@ -53,6 +53,10 @@
     0.9737174163006579,
     32.788643482803174
    ],
+   "band_legacy": [
+    0.9737174163006579,
+    32.788643482803174
+   ],
    "bsnr": {
     "max": 703.3076742984747,
     "median": 67.33559621669662,
@@ -183,6 +187,10 @@
     1.1181139989636801,
     31.23385155720966
    ],
+   "band_legacy": [
+    1.1181139989636801,
+    31.23385155720966
+   ],
    "bsnr": {
     "max": 984.2366425937313,
     "median": 16.41320146281223,
@@ -313,6 +321,10 @@
     1.5094384507838874,
     38.59542615124991
    ],
+   "band_legacy": [
+    1.5094384507838874,
+    38.59542615124991
+   ],
    "bsnr": {
     "max": 1633.3610923661952,
     "median": 83.11692336982478,
@@ -443,6 +455,10 @@
     0.9477387099726711,
     37.53007532565119
    ],
+   "band_legacy": [
+    0.9477387099726711,
+    37.53007532565119
+   ],
    "bsnr": {
     "max": 1420.9010412188081,
     "median": 41.33479005546648,
@@ -573,6 +589,10 @@
     1.3617127116258283,
     23.61945176501958
    ],
+   "band_legacy": [
+    1.3617127116258283,
+    23.61945176501958
+   ],
    "bsnr": {
     "max": 102.78530814417852,
     "median": 11.305168255633848,
@@ -703,6 +723,10 @@
     1.1035836325547057,
     9.245914728081909
    ],
+   "band_legacy": [
+    1.1035836325547057,
+    9.245914728081909
+   ],
    "bsnr": {
     "max": 92.42333262769407,
     "median": 6.841556629196746,
@@ -833,6 +857,10 @@
     1.4484769173671939,
     7.041619439901746
    ],
+   "band_legacy": [
+    1.4484769173671939,
+    7.041619439901746
+   ],
    "bsnr": {
     "max": 257.3078136024008,
     "median": 9.788757776823047,
@@ -963,6 +991,10 @@
     0.8647452431401212,
     10.475901429815453
    ],
+   "band_legacy": [
+    0.8647452431401212,
+    10.475901429815453
+   ],
    "bsnr": {
     "max": 385.613670575393,
     "median": 8.430791414942291,
@@ -1093,6 +1125,10 @@
     4.637778313596789,
     18.29540141450008
    ],
+   "band_legacy": [
+    4.637778313596789,
+    18.29540141450008
+   ],
    "bsnr": {
     "max": 104.51249851432455,
     "median": 3.113518701296115,
@@ -1223,6 +1259,10 @@
     9.98742597396051,
     16.473241545409472
    ],
+   "band_legacy": [
+    9.98742597396051,
+    16.473241545409472
+   ],
    "bsnr": {
     "max": 85.96861713399876,
     "median": 2.163595898138853,
@@ -1350,6 +1390,10 @@
     "sum": 0.00013305374557403735
    },
    "band": [
+    0.6756756756756757,
+    45.738160295630905
+   ],
+   "band_legacy": [
     0.5714716099444196,
     45.738160295630905
    ],
@@ -1483,6 +1527,10 @@
     1.1975429546462397,
     44.37797511381281
    ],
+   "band_legacy": [
+    1.1975429546462397,
+    44.37797511381281
+   ],
    "bsnr": {
     "max": 1659.7367164441625,
     "median": 134.14095879865926,
@@ -1613,6 +1661,10 @@
     0.94187613565413,
     19.94609399915649
    ],
+   "band_legacy": [
+    0.94187613565413,
+    19.94609399915649
+   ],
    "bsnr": {
     "max": 302.506123329657,
     "median": 23.161983211675725,
@@ -1743,6 +1795,10 @@
     0.9603039489851778,
     27.206502746088496
    ],
+   "band_legacy": [
+    0.9603039489851778,
+    27.206502746088496
+   ],
    "bsnr": {
     "max": 900.2622410841836,
     "median": 26.71155619860477,
@@ -1873,6 +1929,10 @@
     0.8944940844050081,
     80.77427233709817
    ],
+   "band_legacy": [
+    0.8944940844050081,
+    80.77427233709817
+   ],
    "bsnr": {
     "max": 394.3003326667573,
     "median": 31.038914450670028,
@@ -2003,6 +2063,10 @@
     0.9040002823361107,
     52.70836316105784
    ],
+   "band_legacy": [
+    0.9040002823361107,
+    52.70836316105784
+   ],
    "bsnr": {
     "max": 925.0231962862383,
     "median": 37.36106407711529,
@@ -2133,6 +2197,10 @@
     0.9407138328094745,
     87.288590981566
    ],
+   "band_legacy": [
+    0.9407138328094745,
+    87.288590981566
+   ],
    "bsnr": {
     "max": 7824.587392753862,
     "median": 608.8809585098755,
@@ -2263,6 +2331,10 @@
     0.6534409353452816,
     94.27281435133563
    ],
+   "band_legacy": [
+    0.6534409353452816,
+    94.27281435133563
+   ],
    "bsnr": {
     "max": 7301.913301057101,
     "median": 598.3714708213699,
@@ -2393,6 +2465,10 @@
     0.8996342659848598,
     94.21104790578656
    ],
+   "band_legacy": [
+    0.8996342659848598,
+    94.21104790578656
+   ],
    "bsnr": {
     "max": 2382.60171992352,
     "median": 151.792745354955,
@@ -2523,6 +2599,10 @@
     0.8204086361167056,
     94.47315173882237
    ],
+   "band_legacy": [
+    0.8204086361167056,
+    94.47315173882237
+   ],
    "bsnr": {
     "max": 2094.879002521716,
     "median": 88.29297406659833,
@@ -2653,6 +2733,10 @@
     9.913364377447403,
     66.42535104304301
    ],
+   "band_legacy": [
+    9.913364377447403,
+    66.42535104304301
+   ],
    "bsnr": {
     "max": 379.4078050835924,
     "median": 33.43998849058502,
@@ -2783,6 +2867,10 @@
     0.8016188872608186,
     68.6920743469019
    ],
+   "band_legacy": [
+    0.8016188872608186,
+    68.6920743469019
+   ],
    "bsnr": {
     "max": 338.00093558496195,
     "median": 66.7844487082905,
@@ -2910,6 +2998,10 @@
     "sum": 1.5530832633170604e-05
    },
    "band": [
+    0.8849557522123893,
+    33.28274558056363
+   ],
+   "band_legacy": [
     0.7905559110827145,
     33.28274558056363
    ],
@@ -3040,6 +3132,10 @@
     "sum": 1.428210371362249e-05
    },
    "band": [
+    0.8849557522123893,
+    26.892138753418887
+   ],
+   "band_legacy": [
     0.8395716232630503,
     26.892138753418887
    ],
@@ -3173,6 +3269,10 @@
     0.9922949033943869,
     43.030304197326
    ],
+   "band_legacy": [
+    0.9922949033943869,
+    43.030304197326
+   ],
    "bsnr": {
     "max": 531.411668147956,
     "median": 68.12758138229394,
@@ -3303,6 +3403,10 @@
     0.6665703398762428,
     45.84946131232292
    ],
+   "band_legacy": [
+    0.6665703398762428,
+    45.84946131232292
+   ],
    "bsnr": {
     "max": 1517.6644527720032,
     "median": 90.67387693553846,
@@ -3433,6 +3537,10 @@
     0.8014155430688078,
     40.4117258750204
    ],
+   "band_legacy": [
+    0.8014155430688078,
+    40.4117258750204
+   ],
    "bsnr": {
     "max": 411.90742135458214,
     "median": 43.361458803095324,
@@ -3563,6 +3671,10 @@
     0.9271659654213654,
     28.034150656401575
    ],
+   "band_legacy": [
+    0.9271659654213654,
+    28.034150656401575
+   ],
    "bsnr": {
     "max": 1605.7974987655552,
     "median": 100.15661136859454,
diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py
index 1cc57c9..9e4d990 100644
--- a/tests/test_pipeline.py
+++ b/tests/test_pipeline.py
@@ -244,6 +244,12 @@ def test_it_matches_the_recorded_displacement(self, pnr_windows: Any) -> None:
         bands on all 28**. The comparison itself could not be kept — one side
         of it is deleted — so this is its durable form, the same numbers held
         against a committed artefact.
+
+        ``amp``, ``noise_amp`` and ``bsnr`` are still those legacy values.
+        ``band`` has been regenerated once, for the resolution-floor
+        correction — see
+        :meth:`TestToMotion.test_the_band_of_a_converted_pair_respects_the_noise_floor`,
+        which keeps the superseded edges and pins what changed.
         """
         reference = json.loads(
             (Path(__file__).parent / "golden" / "motion_reference.json").read_text()
@@ -274,6 +280,79 @@ def test_it_matches_the_recorded_displacement(self, pnr_windows: Any) -> None:
                 problems.append(f"{id} band: {want['band']} -> {pair.band}")
         assert not problems, "\n".join(problems)
 
+    def test_the_band_of_a_converted_pair_respects_the_noise_floor(
+        self, pnr_windows: Any
+    ) -> None:
+        """The one deliberate change to the recorded displacement bands.
+
+        ``compare`` derived the floor from ``noise.freq.min()``. That works
+        exactly once: the noise is interpolated onto the signal's axis before
+        binning, so afterwards its own lowest resolvable frequency is gone and
+        the expression returns the *signal's*. A converted pair therefore got
+        the longer signal window's floor in place of the shorter noise
+        window's, and its band could open below the frequency the noise can
+        resolve — where ``interpolate_onto`` is repeating an edge value rather
+        than reporting a measurement, so the ratio there has an invented
+        denominator.
+
+        The floor is now read from ``meta["resolution_floor"]``, which
+        ``spectrum_from_trace`` has recorded all along and nothing read.
+
+        Measured across all five estimators: the floor used to differ between a
+        pair and its own conversion on **28 of 28** stations, and now differs on
+        none. Bands of *unconverted* pairs do not move at all — 0 of 28 on every
+        estimator — so nothing computed without a domain change is affected.
+        Round-trip band stability goes from 3/28 (fft), 8/28 (multitaper),
+        27/28 (cwt), 7/28 (welch) and 8/28 (quadratic) to **0/28 everywhere**.
+
+        On the recorded displacement set the change touches 3 of 28 stations,
+        and only ever the lower edge, and only upward — toward the floor. That
+        direction is the physics rather than a coincidence: a floor that was
+        too low permitted an edge that was too low, so correcting it can raise
+        an edge and can never lower one.
+        """
+        reference = json.loads(
+            (Path(__file__).parent / "golden" / "motion_reference.json").read_text()
+        )["displacement"]
+
+        raised = 0
+        for id, want in reference.items():
+            assert "band_legacy" in want, (
+                f"{id}: band_legacy is missing. The legacy edges are the record "
+                "of what the published lineage produced; regenerating band "
+                "without keeping them discards it."
+            )
+            new, old = want["band"], want["band_legacy"]
+            if new is None or old is None:
+                assert new == old, f"{id}: a band appeared or vanished"
+                continue
+            assert new[1] == pytest.approx(old[1], rel=1e-12), (
+                f"{id}: the upper edge moved. The floor is a lower bound; "
+                "nothing about this correction can touch the top of a band."
+            )
+            assert new[0] >= old[0] - 1e-12, (
+                f"{id}: the lower edge moved DOWN, {old[0]} -> {new[0]}. "
+                "Correcting a floor that was too low can only raise an edge."
+            )
+            raised += new[0] > old[0] + 1e-12
+        assert raised == 3, f"expected 3 stations to move, got {raised}"
+
+    def test_a_conversion_does_not_change_the_resolution_floor(
+        self, pnr_windows: Any
+    ) -> None:
+        """The invariant behind the band correction, asserted on its own.
+
+        A domain change multiplies both spectra by a power of ``2*pi*f``. It
+        does not lengthen either window, so it cannot change what either one
+        can resolve.
+        """
+        direct = _direct("fft", pnr_windows)
+        displacement = direct.to_motion("displacement")
+        for id in direct.ids():
+            assert displacement[id].resolution_floor == pytest.approx(
+                direct[id].resolution_floor, rel=1e-12
+            ), id
+
     def test_the_original_is_untouched(self, pnr_windows: Any) -> None:
         """The property the legacy could not have. `Spectra.inte()` overwrote
         the event; here both domains exist at once."""