← Back to the catalog
Private

ECOSTRESS rock all axis be345a03

ecostress · other

ECOSTRESS rock all axis be345a03. v2.0 standardized NIRS package: 1 spectral source(s), 5 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2ecostress
🔒
Private dataset. Full metadata and metrics are shown, but the bytes are not redistributed here — exporting the data requires a Dataverse token. The identity card carries no spectra, only descriptive statistics.
39
samples
2,868
wavelengths
1
sources
5
targets
27
metadata
other
family

Dataset property explorer

Mean profile risk0.62
Highest axisArtefacts locaux · 1.00
Diagnostics8
Sources profiled1
ECOSTRESS rock all axis be345a03 property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureECOSTRESS rock all axis be345a03 profileintegrity: 0.00noise: 0.00artefacts: 1.00baseline: 1.00PCA outliers: 0.41reference: 1.00repeatability: 1.00structure: 0.51ECOSTRESS rock …0 center · 1 outer ring · outward = stronger anomaly / heterogeneity signal

Profile axes

Intégrité0.00
Artefacts locaux1.00
Bruit0.00
Outliers PCA0.41
Distance à la référence1.00
Répétabilité1.00
Baseline / forme1.00
Structure multi-régimes0.51
Diagnostic hypotheses00.250.50.751hypothesis scoreMauvaise répétabilité d'acqui…Mauvaise répétabilité d'acquisition: 0.830.83Splice / raccord détecteursSplice / raccord détecteurs: 0.820.82Erreur calibration / référenc…Erreur calibration / référence blanche: 0.710.71Différence de sonde / géométr…Différence de sonde / géométrie: 0.690.69Signature VERA25-likeSignature VERA25-like: 0.670.67Fond différentFond différent: 0.630.63Mélange feuille + fondMélange feuille + fond: 0.580.58Erreur interpolation / réécha…Erreur interpolation / rééchantillonnage: 0.560.56
DiagnosticScoreForceSignauxInterprétation probable
Mauvaise répétabilité d'acquisitionX0.83forteRMS/SAM intra-ID 1.00, Bruit/artefacts variables 1.00Positionnement, opérateur ou protocole instable; investiguer les répétitions intra-ID.
Splice / raccord détecteursX0.82forteSpike rate 1.00, Jump rate 1.00, RMS/SAM référence 1.00Rupture aux jonctions de détecteurs, calibration locale ou sonde différente.
Erreur calibration / référence blancheX0.71moyenneBaseline/mean/area 1.00, RMS/SAM référence 1.00, artefacts locaux 1.00Décalage systématique entre campagnes, instruments ou référence blanche.
Différence de sonde / géométrieX0.69moyenneBaseline/mean/area 1.00, RMS/SAM référence 1.00, Répétabilité 1.00Modification de l'illumination, collecte, angle ou distance sonde-échantillon.
Signature VERA25-likeX0.67moyenneSpike rate 1.00, Jump rate 1.00, RMS/SAM référence 1.00Combinaison possible changement de sonde + splice, amplifiée par géométrie, fond ou calibration.
Fond différentX0.63moyenneBaseline/mean/area 1.00, RMS/SAM référence 1.00, PCA Q 0.41Effet systématique du support, blanc/noir, transflectance ou environnement de mesure.
Mélange feuille + fondX0.58moyenneBaseline/mean/area 1.00, RMS/SAM référence 1.00, Répétabilité 1.00Couverture partielle du spot; contribution du fond ou du support.
Erreur interpolation / rééchantillonnageX0.56moyenneSpike rate 1.00, Jump rate 1.00, SNR normal/élevé 1.00Artefacts numériques ou traitement spectral incorrect.

Spectral sources

rock all

X · other · source instruments vary by sample
rock all spectra0255075100051015q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / none14.983none — median 2.812 (q25–q75 1.863–8.53)14.126none — median 3.388 (q25–q75 2.387–5.71)13.396none — median 3.651 (q25–q75 2.698–9.305)12.706none — median 2.911 (q25–q75 2.343–9.533)12.084none — median 6.253 (q25–q75 4.04–12.39)11.546none — median 7.288 (q25–q75 4.792–9.86)11.03none — median 5.445 (q25–q75 4.225–11.14)10.58none — median 4.859 (q25–q75 3.743–9.669)10.145none — median 4.758 (q25–q75 3.44–8.322)9.7447none — median 4.864 (q25–q75 3.651–7.039)9.3916none — median 5.758 (q25–q75 3.918–9.525)9.0474none — median 7.088 (q25–q75 3.855–13.77)8.7275none — median 6.248 (q25–q75 3.834–14.17)8.4432none — median 6.056 (q25–q75 3.793–12.36)8.164none — median 8.916 (q25–q75 4.221–15.02)7.9147none — median 4.642 (q25–q75 3.432–13.32)7.6689none — median 6.796 (q25–q75 2.701–11.97)7.4378none — median 7.358 (q25–q75 3.422–9.314)7.2303none — median 5.2 (q25–q75 4.245–6.413)7.0246none — median 5.349 (q25–q75 3.543–8.03)6.8302none — median 5.757 (q25–q75 3.709–9.414)6.6549none — median 7.485 (q25–q75 4.5–10.31)6.4802none — median 11.56 (q25–q75 7.661–13.9)6.3221none — median 9.316 (q25–q75 5.367–13.08)6.1643none — median 6.526 (q25–q75 3.911–10.55)6.0141none — median 9.382 (q25–q75 5.891–13.46)5.8777none — median 11.7 (q25–q75 8.961–14.68)5.741none — median 14.3 (q25–q75 10.77–18.23)5.6106none — median 13.31 (q25–q75 10.61–14.91)5.4917none — median 17.45 (q25–q75 14.03–21.99)5.3722none — median 16.77 (q25–q75 12.33–27.77)5.2631none — median 19.37 (q25–q75 15.21–37.23)5.1532none — median 24.5 (q25–q75 21.16–40.18)5.0479none — median 26.46 (q25–q75 20.5–36.78)4.9514none — median 29.18 (q25–q75 24.63–39.33)4.8541none — median 38.59 (q25–q75 33.3–47.09)4.7605none — median 42.05 (q25–q75 36.29–49.27)4.6746none — median 41.51 (q25–q75 34.58–43.93)4.5877none — median 46.74 (q25–q75 39.58–51.04)4.508none — median 47.69 (q25–q75 41.14–53.08)4.4271none — median 49.12 (q25–q75 42.68–54.94)4.3491none — median 53 (q25–q75 43.99–58.38)4.2774none — median 53.27 (q25–q75 38.88–59.21)4.2045none — median 53.92 (q25–q75 44.87–60.1)4.1341none — median 53.75 (q25–q75 44.83–60.29)4.0692none — median 46.48 (q25–q75 40.72–57.98)4.0032none — median 34.41 (q25–q75 17.32–57.33)3.9423none — median 32.12 (q25–q75 14.38–57.18)3.8804none — median 38.87 (q25–q75 18.71–57.64)3.8203none — median 40.59 (q25–q75 24.63–57.66)3.7648none — median 49.23 (q25–q75 38.62–61.1)3.7083none — median 52.7 (q25–q75 43.69–61.08)3.6534none — median 52.88 (q25–q75 43.42–61.31)3.6026none — median 50.63 (q25–q75 42.38–60.42)3.5508none — median 46.69 (q25–q75 35.88–54.23)3.5028none — median 31.23 (q25–q75 18.05–52.3)3.4538none — median 30.07 (q25–q75 18.59–50.99)3.4061none — median 30.45 (q25–q75 20–49.29)3.362none — median 28.31 (q25–q75 17.73–48.06)3.3168none — median 37.85 (q25–q75 22.43–47.32)3.2728none — median 42.16 (q25–q75 29.15–48.05)3.232none — median 40.87 (q25–q75 29.23–51.12)3.1902none — median 38.75 (q25–q75 27.04–48.97)3.1515none — median 34.99 (q25–q75 25.5–47.18)3.1117none — median 32.04 (q25–q75 23.5–45.11)3.073none — median 30.92 (q25–q75 21.23–42.52)3.037none — median 29.71 (q25–q75 17.93–40.53)3.0001none — median 28.67 (q25–q75 15.58–39.21)2.9641none — median 27.43 (q25–q75 15.74–38.2)2.9306none — median 26.51 (q25–q75 14.99–37.8)2.8962none — median 26.48 (q25–q75 15.52–38.57)2.8642none — median 25.8 (q25–q75 16.12–38.56)2.8313none — median 25.08 (q25–q75 15.04–37.93)2.7992none — median 23.15 (q25–q75 13.69–38.94)2.7693none — median 22.01 (q25–q75 10.48–31.45)2.7386none — median 21.34 (q25–q75 9.636–37.09)2.7085none — median 38.02 (q25–q75 20.9–45.84)2.6805none — median 51.87 (q25–q75 40.72–62.42)2.6517none — median 58.75 (q25–q75 44.63–68.76)2.6249none — median 59.67 (q25–q75 44.62–69.67)2.5973none — median 60.05 (q25–q75 44.63–70.01)2.5702none — median 58.83 (q25–q75 44.56–70.63)2.545none — median 57.96 (q25–q75 43.43–68.58)2.519none — median 57.74 (q25–q75 43.46–69.39)2.4936none — median 57.8 (q25–q75 43.36–69.4)2.4698none — median 59.01 (q25–q75 43.37–68.82)2.4454none — median 59.62 (q25–q75 43.75–69.84)2.4225none — median 60.62 (q25–q75 43.77–71.15)2.399none — median 61.01 (q25–q75 44.04–71.65)2.3759none — median 61.63 (q25–q75 44.02–71.52)2.3543none — median 60.97 (q25–q75 43.7–71.15)2.3321none — median 57.92 (q25–q75 43.53–72.12)2.3102none — median 58.97 (q25–q75 44.06–71.43)2.2898none — median 61.06 (q25–q75 44.25–73.8)2.2688none — median 62.39 (q25–q75 44.24–74.43)2.2491none — median 63.35 (q25–q75 43.86–74.79)2.2288none — median 64.18 (q25–q75 43.26–76.85)2.2088none — median 64.11 (q25–q75 42.66–77.45)2.1902none — median 64.18 (q25–q75 42.88–77.66)2.1709none — median 65.69 (q25–q75 43.82–78.68)2.152none — median 66.81 (q25–q75 44.01–78.61)2.1343none — median 66.88 (q25–q75 43.95–78.95)2.116none — median 67 (q25–q75 43.87–78.72)2.0988none — median 67.08 (q25–q75 44.68–79.83)2.0812none — median 66.89 (q25–q75 45.14–80.56)2.004none — median 65.43 (q25–q75 43.58–79.21)1.924none — median 62.29 (q25–q75 43.61–75.22)1.84none — median 63.22 (q25–q75 43.24–79.43)1.756none — median 61.26 (q25–q75 42.45–78.1)1.676none — median 59.9 (q25–q75 41.96–77.91)1.592none — median 56.92 (q25–q75 41.15–76.16)1.512none — median 54.42 (q25–q75 40.14–74.17)1.428none — median 51.47 (q25–q75 39.37–73.53)1.344none — median 49.64 (q25–q75 39.34–73.4)1.264none — median 44.62 (q25–q75 37.91–72.84)1.18none — median 43.03 (q25–q75 35.28–72.33)1.096none — median 42.08 (q25–q75 32.33–72.8)1.016none — median 42.74 (q25–q75 30.31–71.93)0.932none — median 41.18 (q25–q75 27.26–64.5)0.852none — median 40.23 (q25–q75 25.35–62.57)0.792none — median 39.83 (q25–q75 26.87–62.26)0.771none — median 39.66 (q25–q75 26.8–62.24)0.751none — median 38.85 (q25–q75 26.34–62.53)0.73none — median 38.28 (q25–q75 25.71–61.89)0.709none — median 36.26 (q25–q75 25.16–62.55)0.689none — median 35.99 (q25–q75 24.59–63.58)0.668none — median 35.52 (q25–q75 23.63–62.99)0.648none — median 35.52 (q25–q75 23.22–62.74)0.627none — median 35.68 (q25–q75 23.61–62.98)0.606none — median 35.77 (q25–q75 23.88–62.97)0.586none — median 36.26 (q25–q75 21.92–61.45)0.565none — median 34.03 (q25–q75 21.47–58.65)0.544none — median 30.91 (q25–q75 20.27–56.07)0.524none — median 30.08 (q25–q75 19.94–55.1)0.503none — median 28.57 (q25–q75 19.43–54.42)0.483none — median 27.89 (q25–q75 18.63–52.78)0.462none — median 26.92 (q25–q75 17.53–49.47)0.441none — median 26.43 (q25–q75 16.86–49.51)0.421none — median 24.82 (q25–q75 15.29–48.33)0.4none — median 24.06 (q25–q75 13.97–47.43)

Sampling

Wavelengths2,868
Axis range0.4–14.98 none
Mean spacing0.00509 none
Gridirregular
Observations41

Signal & quality

Value range0.5 – 95.2
Mean range3.51 – 61.7
Mean level37.3
Area305.8
PTP58.18
Noise RMS0.010288
SNR3.6e+03
SNR dB7e+01 dB
Dynamic range58.2
Smoothness0.1968
Saturated0.0%
X-outliers13

Integrity & artefacts

NaN ratio0.00%
Inf count0
Zero ratio0.00%
Spike count15,743
Spike rate13.40%
Jump count2,074
Jump rate1.76%
Clip fraction0.00%

Shape & reference

Baseline slope-64.196
Curvature RMS0.16732
D1 RMS0.22423
RMS to mean13.716
RMS p9530.444
SAM to mean0.2158
SAM p950.29602
Affine offset p9511.681
Affine gain p95 Δ0.65328
Affine residual p9516.368
Xcorr lag p9514

Outliers & repeatability

PCA Q p95/median3.3
Hotelling T2 p95/median2.5
Mahalanobis H p95/median1.6
Repeat groups2
RMS intra-ID14.883
SAM intra-ID0.15086
CV intra-ID0.67619

Dimensionality (PCA)

Effective rank2.6
PCs → 95% var4
PCs → 99% var9
Top-10 cum. var99.3%
Computed metric scores 29worst 1.00
FamilleMétrique calculéeValeurScoreNiveauInterprétation datasetCauses typiquesCalcul / scoring
Intégrité des donnéesNaN ratiointegrity.nan_ratio0%0.00faibleSpectre completErreur acquisition/exportcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Intégrité des donnéesInf countintegrity.inf_count00.00faibleNormalCalculs invalidescount(isinf(X))alert = min(1, inf_count / 1)
Intégrité des donnéesZero ratiointegrity.zero_ratio0%0.00faibleNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceamplitude.mean_reflectance37.3041.00fortValeur atypique: Trop clair / fond visible ou Trop sombreFond, géométriemean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Amplitude globaleArea under curveamplitude.area_under_curve305.761.00fortValeur atypique: Différence d'éclairement ou NormalDistance sondetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Amplitude globalePeak-to-peak (PTP)amplitude.peak_to_peak58.1810.00faibleVariabilité forteSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceamplitude.variance634.960.00faibleNormal ou hétérogèneMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSnoise.noise_rms0.0102880.00faibleStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRnoise.snr3625.90.00faibleBon signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRnoise.bandwise_snr_min66.1090.00faibleZone fiableDétecteurmin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Artefacts locauxSpike countartefacts.spike_count15,7431.00fortArtefactsCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateartefacts.spike_rate13.4%1.00fortSpectre suspectInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countartefacts.jump_count2,0741.00fortRaccord détecteurSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateartefacts.jump_rate1.76%1.00fortProblème spectralCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionartefacts.clip_fraction0.0017%0.00faibleNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopeshape.baseline_slope-64.1961.00fortDériveÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSshape.curvature_rms0.167320.29faibleLisseFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSshape.d1_rms0.224230.08faiblePlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)outliers.pca_q_ratio3.29490.41faibleConformeArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²outliers.hotelling_t2_ratio2.53050.32faibleCentralVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis Houtliers.mahalanobis_h_ratio1.59080.40faiblePopulation normaleDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumreference.rms_to_mean_spectrum_p9530.4441.00fortSpectre différentDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparaison à référenceSpectral Angle Mapper (SAM)reference.sam_to_mean_spectrum_p950.296020.85fortForme différenteFond, géométriep95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RépétabilitéRMS intra-IDrepeatability.rms_intra_id14.8831.00fortMauvaise répétabilitéPositionnementmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RépétabilitéSAM intra-IDrepeatability.sam_intra_id0.150861.00fortInstableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RépétabilitéCV intra-IDrepeatability.cv_intra_id0.676191.00fortMauvais contrôleOpérateurmedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure du datasetPCA score densitystructure.pca_score_density0.00209550.51moyenSous-populationsLots différents1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure du datasetLocal Outlier Factor (LOF)structure.local_outlier_factor_p951.53660.27faiblePopulation normaleCas raresp95 approximate LOF from PCA-score kNN distancesalert = min(1, max(0, LOF_p95 - 1) / 2)
Structure du datasetIsolation Forest scorestructure.isolation_forest_score_p950.568280.51moyenSpectre atypiqueDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
X PCA score plot-2,000-1,00001,0002,000-1,000-50005001,000PC1 -1520 · PC2 -127.5PC1 -1176 · PC2 -176.2PC1 605.6 · PC2 423.4PC1 -114.9 · PC2 15.62PC1 876.8 · PC2 298.1PC1 -38.81 · PC2 526.9PC1 113.6 · PC2 415.8PC1 -92.08 · PC2 282.9PC1 542.6 · PC2 -580.7PC1 259.5 · PC2 -202.1PC1 1481 · PC2 -647.6PC1 1175 · PC2 -630.8PC1 809.9 · PC2 -334.5PC1 1466 · PC2 -624.8PC1 1302 · PC2 -516.1PC1 -1651 · PC2 -375.3PC1 729.8 · PC2 243.2PC1 830.1 · PC2 164.9PC1 476.1 · PC2 164.6PC1 1228 · PC2 242PC1 -1037 · PC2 -268.3PC1 -610.3 · PC2 -219.2PC1 261.8 · PC2 539.3PC1 1088 · PC2 126PC1 -647.9 · PC2 171.1PC1 -203.3 · PC2 346.3PC1 -128.5 · PC2 127.9PC1 100.2 · PC2 563.8PC1 -1738 · PC2 -413.1PC1 -321.1 · PC2 -333.9PC1 -30.98 · PC2 -335.5PC1 65.56 · PC2 356.9PC1 -592.8 · PC2 10.04PC1 -423.8 · PC2 -116PC1 188.9 · PC2 329.1PC1 131.6 · PC2 183.9PC1 -1200 · PC2 -105.7PC1 -122.2 · PC2 288.3PC1 -1171 · PC2 -153.5PC1 -715.8 · PC2 82.11PC1 -196.7 · PC2 258.4PC1 (75.3%)PC2 (12.6%)41 scores
PCA explained variance0%25%50%75%100%PC1: 75.3% (cumulative 75.3%)1PC2: 12.6% (cumulative 87.9%)2PC3: 4.9% (cumulative 92.8%)3PC4: 3.0% (cumulative 95.8%)4PC5: 1.1% (cumulative 96.8%)5PC6: 0.9% (cumulative 97.8%)6PC7: 0.6% (cumulative 98.4%)7PC8: 0.4% (cumulative 98.8%)8PC9: 0.3% (cumulative 99.1%)9PC10: 0.3% (cumulative 99.3%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)

Metric interpretation reference

Metric catalog 29
FamilleMétriqueCe qu’elle détecteForte valeur =Faible valeur =Causes typiquesCalcul / score
Intégrité des donnéesNaN ratioDonnées manquantesSpectre corrompuSpectre completErreur acquisition/exportcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Intégrité des donnéesInf countValeurs infiniesCorruptionNormalCalculs invalidescount(isinf(X))alert = min(1, inf_count / 1)
Intégrité des donnéesZero ratioColonnes ou cellules nullesSpectre tronquéNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceNiveau moyenTrop clair / fond visibleTrop sombreFond, géométriemean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Amplitude globaleArea under curveIntensité globaleDifférence d'éclairementNormalDistance sondetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Amplitude globalePeak-to-peak (PTP)DynamiqueVariabilité forteSpectre platSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceVariabilité spectraleNormal ou hétérogèneSpectre platMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSBruit haute fréquenceBruitéStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRQualité signalBon signalMauvais signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRBruit localiséZone fiableZone problématiqueDétecteurmin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Artefacts locauxSpike countPics étroitsArtefactsSpectre propreCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateDensité de picsSpectre suspectNormalInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countDiscontinuitésRaccord détecteurContinuSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateFréquence de sautsProblème spectralNormalCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionSaturationClippingNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopePente globaleDériveStableÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSCourbureForme inhabituelleLisseFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSVariabilité localeSpectre structuréPlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)Non expliqué par PCASpectre atypiqueConformeArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²Extrême dans PCAExtrême mais cohérentCentralVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis HDistance au nuageOutlier globalPopulation normaleDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumDistance moyenneSpectre différentTypiqueDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparaison à référenceSpectral Angle Mapper (SAM)Différence de formeForme différenteSimilaireFond, géométriep95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RépétabilitéRMS intra-IDReproductibilitéMauvaise répétabilitéStablePositionnementmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RépétabilitéSAM intra-IDVariation de formeInstableStableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RépétabilitéCV intra-IDVariabilité interneMauvais contrôleStableOpérateurmedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure du datasetPCA score densityClustersSous-populationsHomogèneLots différents1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure du datasetLocal Outlier Factor (LOF)Anomalie localeSpectre isoléPopulation normaleCas raresp95 approximate LOF from PCA-score kNN distancesalert = min(1, max(0, LOF_p95 - 1) / 2)
Structure du datasetIsolation Forest scoreAnomalie globaleSpectre atypiqueNormalDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
Technology-specific extensions
TechnologieAdaptations / métriquesAnomalies cibléesCommentaire pratique
UV-Vis 300-1000 nmBaseline, pente globale, dérive aux bords 300-350 et 900-1000; métriques par zonesLumière parasite, mauvais blanc, saturation, faible signal aux extrémitésLes bords sont souvent instables; calculer aussi des scores edge/middle.
UV-Vis 300-1000 nmSaturation / clipping proche absorbance max ou réflectance maxSignal écrêtéTrès important si absorption forte.
UV-Vis 300-1000 nmRed-edge, position de maximum, ratios de bandes si végétalDécalage biologique ou artefact optiqueAide à distinguer changement réel et problème d'acquisition.
UV-Vis 300-1000 nmSmoothness / roughness indexBruit haute fréquenceSouvent plus informatif que le SNR seul.
MIR / ATR-FTIRATR contact quality index: intensité globale, aire totale, profondeur des bandes clésMauvais contact cristal-échantillonCrucial: beaucoup d'anomalies viennent du contact ATR.
MIR / ATR-FTIRCO2 / H2O atmospheric bandsMauvaise correction atmosphériquePics parasites fréquents.
MIR / ATR-FTIRBaseline curvature / rubber-band residualDiffusion, contact, dérive baselineTrès utile avant PCA.
MIR / ATR-FTIRPeak position shiftMauvais alignement spectral / calibrationImportant en FTIR car de petits shifts comptent.
MIR / ATR-FTIRBand area ratios sur bandes connuesSpectre chimiquement incohérentÀ adapter par matrice: polysaccharides, protéines, lipides, etc.
HS-MSTotal Ion Current (TIC), Base Peak Intensity (BPI)Injection faible, ionisation instableÉquivalent MS du niveau global spectral.
HS-MSNombre de pics détectésSpectre pauvre ou trop bruitéTrop peu = mauvais signal; trop = bruit/contamination.
HS-MSMass accuracy / m/z driftProblème calibration masseFondamental en HRMS.
HS-MSRetention time drift si LC/GC-MSDérive chromatographiqueÀ suivre sur standards/QC pools.
HS-MSBlank contamination scoreContaminants / carry-overComparer échantillons vs blancs.
HS-MSInternal standard CVVariabilité instrumentaleTrès robuste si standards disponibles.
HS-MSMissingness par featureInstabilité de détectionCrucial pour filtrer les variables.
Avec répétitionsRMS intra-échantillonRépétabilité globaleApplicable à toutes les technologies.
Avec répétitionsSAM / corrélation intra-échantillonRépétabilité de formeTrès utile pour spectres.
Avec répétitionsCV intra-échantillon par bande / featureRépétabilité localeDétecte les zones instables.
Avec répétitionsICC ou variance componentsPart variance échantillon vs techniqueTrès utile si plusieurs répétitions par sample.
Avec répétitionsDistance au centroïde intra-IDRépétition aberrantePermet de flagger la mauvaise répétition plutôt que le sample entier.
Bug-hunting / supervised audits
Famille de bug potentielMéthodes à ajouterCe que ça détecteÉtat dans l’explorateur
Shift spectral globalCorrélation spectre moyen inter-dataset, DTW, cross-correlation, comparaison positions de picsDécalage en longueur d'onde, mauvais alignement, interpolation différentePartiellement calculé: cross-correlation lag et dispersion des positions de pics vs spectre moyen.
Baseline / offset / gainRégression chaque spectre vs spectre moyen: x = a + b ref + residual; suivi de a, b, RMS résiduelOffset additif, effet multiplicatif, dérive de baselineCalculé dans reference.affine_*.
Mélange de lignes / mauvais appariement X-M-YVérification index, hash des lignes, duplication ID, distance spectrale intra-ID, labels incohérentsLignes mélangées, metadata mal alignées, Y attribué au mauvais spectrePartiellement couvert par répétabilité intra-ID; checks index/hash à ajouter au pipeline canonical.
Fuite d'information / répétitions mal splitéesGroupKFold par sample_id vs StratifiedKFold random; audit des partitions par sample_idPerformance artificiellement bonne due aux répétitionsNécessite splits et benchmark modèle; non calculé par la carte descriptive.
Label bugsÉchantillons proches en X mais Y différents, confident learning, erreurs systématiques FP/FNY inversés, erreurs de saisie, classes ambiguësNécessite Y et/ou modèle; recommandé pour l'explorateur supervisé.
Sous-domaines cachésPCA/UMAP/t-SNE + clustering non supervisé + association avec dataset/Y/date/operatorLots, campagnes, sondes, backgrounds non renseignésPartiellement calculé par structure PCA/LOF; UMAP/t-SNE hors carte statique.
Artefacts localisés inconnusCarte wavelength x dataset: différence moyenne, différence variance, KS par longueur d'ondeRégions spectrales anormales non anticipéesÀ calculer au niveau banque quand plusieurs datasets partagent un axe spectral.
Ruptures instrumentalesDiscontinuités dans dérivées, changepoint detectionSplice, raccord détecteur, saut local non prévuCalculé par jump/spike rates; changepoint plus avancé à ajouter.
Mélange / contamination spectraleNMF / unmixing / reconstruction par convex hullComposante externe: fond, plastique, solNon calculé automatiquement; nécessite hypothèses de composants ou grande bibliothèque.
Features instables mais prédictivesImportance modèle vs instabilité QC par variableModèle qui apprend un artefact plutôt qu'un signal biologiqueNécessite modèle supervisé; recommandé pour rapports de benchmark.

Variables

Targets 5

material_name

target · categorical
material_name classesDolomitic MarbleDolomitic Marble: 22Serpentine MarbleSerpentine Marble: 22Hornblende SchistHornblende Schist: 22Hornblende GneissHornblende Gneiss: 11Augen GneissAugen Gneiss: 11Felsitic GneissFelsitic Gneiss: 11Syenite GneissSyenite Gneiss: 11Albite GneissAlbite Gneiss: 11Spotted HornfelsSpotted Hornfels: 11MarbleMarble: 11+10 more+10 more: 1010
n / missing39 / 0
Classes36
Balance (entropy)0.99
Imbalance ratio2
Top classDolomitic Marble (2)

class_label

target · categorical
class_label classesMetamorphicMetamorphic: 2727SedimentarySedimentary: 1212
n / missing39 / 0
Classes2
Balance (entropy)0.89
Imbalance ratio2
Top classMetamorphic (27)

subclass

target · categorical
subclass classesMarbleMarble: 77SchistSchist: 66GneisGneis: 55ShaleShale: 55QuartziteQuartzite: 44SandstoneSandstone: 44SlateSlate: 33LimestoneLimestone: 22HornfelHornfel: 11PhyllitePhyllite: 11+1 more+1 more: 11
n / missing39 / 0
Classes11
Balance (entropy)0.93
Imbalance ratio7
Top classMarble (7)

particle_size

target · categorical
particle_size classesFineFine: 3636CoarseCoarse: 33
n / missing39 / 0
Classes2
Balance (entropy)0.39
Imbalance ratio12
Top classFine (36)

measurement

target · categorical
measurement classesDirectional (10 Degree) Hemis…Directional (10 Degree) Hemispherical Reflectance: 3838Directional (10 degree) Hemis…Directional (10 degree) Hemispherical Reflectance: 11
n / missing39 / 0
Classes2
Balance (entropy)0.17
Imbalance ratio38
Top classDirectional (10 Degree) Hemispherical Reflectance (38)

Metadata 5

ecostress_resource_id

metadata · categorical
n / missing39 / 0
Classes39
Balance (entropy)1
Imbalance ratio1
Top classrock.metamorphic.gneis.coarse.all.gneiss6.jhu.becknic.spectrum (1)

location

metadata · categorical
n / missing39 / 0
Classes39
Balance (entropy)1
Imbalance ratio1
Top classSample No. 465, The Hunt and Salisbury Collection at the U.S.Geological Survey, Denver, Co. (1)

sample_description

metadata · categorical
n / missing39 / 0
Classes39
Balance (entropy)1
Imbalance ratio1
Top classCoarse grains of slightly lineated hornblende euhedra with anhedra of alkali feldspar make up the bulk of this rock. There are scattered grains of pyrite and possibly a trace of quartz as well. The modes were 69% hornblende, 30.4% feldspar and 0.6% opaques. Particle size was 500-1500 Micrometer. Original ASTER Spectral Library name was jhu.becknic.rock.metamorphic.gneiss.coarse.gneiss6.spectrum.txt (1)

acquisition_mode

metadata · categorical
acquisition_mode classesDirectional (10 Degree) Hemis…Directional (10 Degree) Hemispherical Reflectance: 3838Directional (10 degree) Hemis…Directional (10 degree) Hemispherical Reflectance: 11
n / missing39 / 0
Classes2
Balance (entropy)0.17
Imbalance ratio38
Top classDirectional (10 Degree) Hemispherical Reflectance (38)

notes

metadata · categorical
notes classesnonenone: 3535rock.metamorphic.gneis.coarse…rock.metamorphic.gneis.coarse.all.gneiss8.jhu.becknic.ancillary.txt: 11rock.metamorphic.gneis.fine.a…rock.metamorphic.gneis.fine.all.gneiss3.jhu.becknic.ancillary.txt: 11rock.metamorphic.quartzite.fi…rock.metamorphic.quartzite.fine.all.qrtzit5.jhu.becknic.ancillary.txt: 11rock.metamorphic.schist.fine.…rock.metamorphic.schist.fine.all.schist9.jhu.becknic.ancillary.txt: 11
n / missing39 / 0
Classes5
Balance (entropy)0.29
Imbalance ratio35
Top classnone (35)
Constant metadata 13
  • categoryrock
  • material_typerock
  • instrumentjhu.becknic
  • signal_typeReflectance (percent)
  • axis_unitWavelength (micrometers)
  • axis_min0.4
  • axis_max14.98
  • n_points_original2,868
  • publication_doi10.1016/j.rse.2019.05.015
  • citationMeerdink et al. 2019, Baldridge et al. 2009
  • licenseCopyright California Institute of Technology / JPL, all rights reserved
  • rights_statusmanual_review_needed
  • usage_scopeprivate_use_only

9 variable(s) omitted (no recorded values).

Alignment

Alignment levelobservation
Sample id availableyes
Samples39
Observations (total)41
Reps per samplemin 1 · mean 1.051 · max 2

Provenance & citation

ContributorECOSTRESS Spectral Library
Origin · url [open]https://speclib.jpl.nasa.gov/download
Origin · url [open]https://speclib.jpl.nasa.gov/
Origin · script [manual]source_to_standard.py — standardization script (maintainer-only)
Publication10.1016/j.rse.2019.05.015 — The ECOSTRESS spectral library version 1.0
Publication10.1016/j.rse.2008.11.007 — The ASTER Spectral Library Version 2.0

Governance & integrity

Tierprivate
LicenseLicenseRef-not-cleared
Permitted useResearch and benchmarking; private use only.
Access policyManual download / private-use-only per source.
RedistributionOfficial ECOSTRESS page requests citation and states copyright/all rights reserved; converted matrices are private/internal until redistribution rights are clarified.
Content version1.0.0
Schema / protocol2.0
Content hash83fea9238b90eb9e…
Processing hash2547b45d486e8fde…
Metadata hash39a32b6edb555fe8…

Load this dataset

# pip install nirs4all-datasets
from nirs4all_datasets import get

# private dataset — export requires a Dataverse token
ds = get("ecostress_rock_all_2868points_41rows", token="…")
X, y = ds.x(), ds.y()
print(X.shape, y.shape)

Metadata downloads are available for public datasets only. The dataset bytes are never served here — fetch them from the origin / DOI above.