[READ-ONLY] Mirror of https://github.com/jmrplens/PyOctaveBand. [Python3] Octave-Band and Fractional Octave-Band filter. For signal in time domain.
jmrplens.github.io/PyOctaveBand/
acoustics
audio
filter
frequency
frequency-analysis
frequency-domain
octave
python3
signal
time-domain
feat: noise-induced hearing loss (ISO 1999:2013 NIPTS and HTLAN) (#103)
Adds a `phonometry.iso1999` module estimating occupational noise-induced hearing loss, extending the ISO 7029 age-related threshold with a noise component.
* `nipts(l_ex, years, fractile)` — noise-induced permanent threshold shift over 500-6000 Hz: median N50 (clause 6.3.1, Formula 2/3, Table 1) and population fractiles from the half-Gaussian spreads du/dl (clause 6.3.2, Formulae 4-7, Tables 2-3), clamped at zero.
* `htlan(age, sex, l_ex, years, fractile)` — hearing threshold level associated with age and noise, combining the age component (HTLA = ISO 7029) with the NIPTS by H' = H + N - H*N/120 (clause 6.1, Formula 1).
Validated against ISO 1999 Annex D (Tables D.1-D.4, 85-100 dB, 10-40 years): reproduces every tabulated dB value. Conformance 82/82; full suite 1686 passed. Figure + two-lane NIHL diagram (EN/ES, light/dark), repo doc and EN/ES site guides.
authored by
José M. Requena Plens
and committed by
GitHub
(Jul 9, 2026, 2:58 PM +0200)
1069f0a6
c7b3a020
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docs/CONFORMANCE.md
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docs/CONFORMANCE.md
···
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## Numerical conformance report
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✅ **79/79 conformance checks pass** across 17 domains and 52 standards - filters class 1 - weightings within IEC 61672-1 class 1.
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✅ **82/82 conformance checks pass** across 18 domains and 53 standards - filters class 1 - weightings within IEC 61672-1 class 1.
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### Numerical validation - filters & weightings
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···
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| ISO/IEC Guide 98-3-1 clause 9.2 | Combined uncertainty, additive model | 2 (+/-0) | 2 | 0 | ✅ |
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| ISO/IEC Guide 98-3 Table G.2 | Coverage factor, p=0.99, v=16 | 2.92 (+/-0.005) | 2.921 | 0.001 | ✅ |
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| ISO/IEC Guide 98-3 Annex G.4 | Welch-Satterthwaite effective dof | 40 (+/-0) | 40 | 0 | ✅ |
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</details>
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<details>
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<summary>✅ <b>Noise-induced hearing loss (ISO 1999)</b> — 100% (3/3)</summary>
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| Standard | Quantity | Expected (norm) | Computed | Δ | Status |
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|:---|:---|:---|:---|:---|:---:|
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| ISO 1999:2013 Table D.2 | Median NIPTS, 4 kHz, 90 dB, 20 yr | 13 dB (+/-0.5 dB) | 12.9 dB | -0.057 dB | ✅ |
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| ISO 1999:2013 Table D.2 | Worst-10 % NIPTS, 4 kHz, 90 dB, 20 yr | 18 dB (+/-0.5 dB) | 17.8 dB | -0.239 dB | ✅ |
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| ISO 1999:2013 Table D.4 | Worst-10 % NIPTS, 3 kHz, 100 dB, 40 yr | 60 dB (+/-0.5 dB) | 59.8 dB | -0.172 dB | ✅ |
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</details>
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docs/README.md
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docs/README.md
···
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- [Speech Intelligibility Index](speech-intelligibility.md) — the ANSI S3.5-1997 one-third-octave-band SII: band-importance weighting (Table 3), self-speech and upward spread of masking, band audibility, and the index in noise and hearing loss
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- [Room-noise criteria](room-noise.md) — the ANSI/ASA S12.2-2019 room-noise ratings: the NC tangency method (Table 1) and the RC Mark II rating with its rumble/hiss/neutral spectral tag (Annex D)
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- [Hearing threshold](hearing-threshold.md) — the age-related hearing threshold distribution (ISO 7029:2017) and the free-field/diffuse-field reference threshold of hearing (ISO 389-7:2006)
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- [Noise-induced hearing loss](noise-induced-hearing-loss.md) — the ISO 1999:2013 noise-induced permanent threshold shift (NIPTS) and its population distribution, and the combination with age into the hearing threshold level associated with age and noise (HTLAN)
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- [Measurement uncertainty](gum-uncertainty.md) — the GUM law of propagation of uncertainty and the Monte Carlo method (ISO/IEC Guide 98-3:2008 and Supplement 1): combined and expanded uncertainty, Welch–Satterthwaite effective degrees of freedom, and probabilistically symmetric coverage intervals
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- [Sound Intensity (p-p)](intensity.md) — two-microphone intensity and field indicators
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- [Room and Building Acoustics](room-acoustics.md) — impulse-response acquisition, reverberation and room parameters, open-plan speech metrics, field airborne/impact/façade sound insulation (ISO 16283-1/2/3), laboratory characterisation (ISO 10140), flanking-transmission prediction (EN 12354-1/2), measurement uncertainty (ISO 12999-1), sound absorption (ISO 354)
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docs/noise-induced-hearing-loss.md
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docs/noise-induced-hearing-loss.md
···
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← [Documentation index](README.md)
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# Noise-induced hearing loss (ISO 1999)
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**ISO 1999:2013** estimates the hearing loss a population suffers from
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occupational noise. It gives the **noise-induced permanent threshold shift**
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(NIPTS) — the extra hearing loss caused by the noise, on top of ageing — as a
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function of the exposure level, the exposure duration and the audiometric
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frequency, together with its spread across a population. It then combines the
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noise component with the age component (the ISO 7029 threshold, "database A")
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into the **hearing threshold level associated with age and noise** (HTLAN).
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Both are defined at the six audiometric frequencies 500 Hz to 6000 Hz, where
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noise damage concentrates (the characteristic 4 kHz notch).
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<picture><source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/diagram_nihl_dark.svg"><img src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/diagram_nihl.svg" alt="Two converging lanes. Left: age, sex and a population fractile with database A (ISO 7029) give the age threshold H (HTLA). Right: the 8-hour-normalised exposure level and the exposure duration in years give the median NIPTS N50 (N50 equals u plus v times log of t over t0, times the squared excess of the level over the cut-off L0), then the fractile NIPTS N by adding the standard-normal quantile times the upper or lower spread. The two components combine into the hearing threshold associated with age and noise, HTLAN, equal to H plus N minus H times N over 120" width="86%"></picture>
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## 1. Noise-induced permanent threshold shift (clause 6.3)
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The median NIPTS for exposure durations of 10 to 40 years grows with the square
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of the excess of the noise exposure level over a frequency-dependent cut-off
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$L_0$ (ISO 1999 clause 6.3.1, Formula 2, Table 1):
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$$
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N_{50} = \left[u + v\,\lg\!\frac{t}{t_0}\right](L_{EX,8h} - L_0)^2,
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$$
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with $t$ the exposure in years and $t_0 = 1$ year; below $L_0$ the effect is
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zero. A population **fractile** follows from two half-Gaussians whose spreads
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$d_u$ (worse than the median) and $d_l$ (better) are given by Formulae 6/7 and
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Table 3: $N_Q = N_{50} + z\,d$ with $z$ the standard-normal quantile, clamped at
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zero (clause 6.3.2).
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```python
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import phonometry as ph
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# Median NIPTS after 20 years at an 8 h-normalised level of 90 dB(A).
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r = ph.nipts(90.0, 20.0, fractile=0.5)
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print(r.frequencies.astype(int)) # [ 500 1000 2000 3000 4000 6000]
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print(r.median.round(1)) # [ 0. 0.1 4.1 10.2 12.9 8.5]
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# The most-susceptible tenth of the population (90th percentile):
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print(ph.nipts(90.0, 20.0, fractile=0.9).value.round(1))
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# [ 0. 0.1 7.7 16.2 17.8 13.6]
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```
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The shift peaks near 4 kHz and deepens with both level and duration. Below the
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cut-off — here 500 Hz ($L_0 = 93$ dB) and 1000 Hz ($L_0 = 89$ dB) at 90 dB —
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the noise causes no permanent shift. For durations under 10 years the median is
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extrapolated from the 10-year value (Formula 3); a subset of the frequencies
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can be requested with `frequencies=`.
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## 2. Age and noise combined — HTLAN (clause 6.1)
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The noise component does not simply add to the age component: ISO 1999
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Formula (1) combines them with a compression term that matters once the total
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exceeds about 40 dB:
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$$
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H' = H + N - \frac{H\,N}{120},
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$$
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where $H$ is the age threshold (HTLA, from ISO 7029 at the same fractile) and
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$N$ the NIPTS. `htlan` evaluates both components and their combination.
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```python
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import phonometry as ph
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# A 60-year-old man, 30 years at 95 dB(A), median.
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h = ph.htlan(60, "male", 95.0, 30.0, fractile=0.5)
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print(h.htla.round(1)) # [ 6. 7.8 12.5 16.6 20.2 25.9] age alone
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print(h.nipts.round(1)) # [ 0.5 3. 11.8 21.6 24.8 17.6] noise alone
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print(h.threshold.round(1)) # [ 6.5 10.7 23. 35.2 40.8 39.8] age + noise
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```
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At 4 kHz the age component (20.2 dB) and the noise component (24.8 dB) combine
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to 40.8 dB rather than their 45.0 dB sum — the compression term removes 4.2 dB.
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<picture><source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/noise_induced_hearing_loss_dark.png"><img src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/noise_induced_hearing_loss.png" alt="Two panels. Left: the median NIPTS at 95 dB for 10, 20, 30 and 40 years on an inverted (audiogram) axis, with the 10 to 90 percent fractile band around the 40-year curve; the loss deepens toward a maximum near 4 kHz and grows with duration. Right: for a 60-year-old man exposed 30 years at 95 dB, the age component (HTLA), the noise component (NIPTS) and their HTLAN combination, which lies below the simple sum because of the compression term" width="96%"></picture>
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<details>
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<summary>Show the code for this figure</summary>
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```python
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import matplotlib.pyplot as plt
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import phonometry as ph
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from phonometry.iso1999 import NIPTS_FREQUENCIES as f
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# One line for the NIPTS spectrum with its fractile band:
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ph.nipts(95.0, 40.0, 0.9).plot()
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plt.show()
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# By hand, both panels:
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12.5, 5.6))
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for yr in (10, 20, 30, 40):
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ax1.plot(f, ph.nipts(95.0, yr, 0.5).median, "o-", label=f"{yr} yr")
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ax1.set_xscale("log"); ax1.invert_yaxis(); ax1.legend()
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h = ph.htlan(60, "male", 95.0, 30.0, 0.5)
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ax2.plot(f, h.htla, "o-", label="Age (HTLA)")
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ax2.plot(f, h.nipts, "^-", label="Noise (NIPTS)")
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ax2.plot(f, h.threshold, "s--", label="Age + noise (HTLAN)")
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ax2.set_xscale("log"); ax2.invert_yaxis(); ax2.legend()
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plt.show()
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```
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</details>
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The `NiptsResult` carries the `median` (`N50`), the `spread_upper`/`spread_lower`
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and the `value` at the requested fractile; the `HtlanResult` carries `htla`,
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`nipts` and the combined `threshold`. Both expose `.plot()`. The age component
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alone is the subject of the [hearing-threshold](hearing-threshold.md) guide.
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---
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**Standards.** ISO 1999:2013, *Acoustics — Estimation of noise-induced hearing
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loss* — the HTLAN combination (clause 6.1, Formula 1), the median NIPTS
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(clause 6.3.1, Formulae 2-3, Table 1) and its statistical distribution
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(clause 6.3.2, Formulae 4-7, Tables 2-3), validated against the worked examples
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of Annex D. The age component (database A) is ISO 7029:2017.
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scripts/conformance_report.py
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scripts/conformance_report.py
···
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return numeric(ref.GUM_WELCH_VEFF, result.effective_dof, 1e-6, places=3)
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_NIHL = "Noise-induced hearing loss (ISO 1999)"
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@register(_NIHL, "ISO 1999:2013 Table D.2", "Median NIPTS, 4 kHz, 90 dB, 20 yr")
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def _chk_iso1999_median() -> Outcome:
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value = float(ph.nipts(90.0, 20.0, 0.5).value[4])
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return numeric(ref.ISO1999_N50_4K_90_20, value, 0.5, unit="dB", places=1)
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@register(_NIHL, "ISO 1999:2013 Table D.2", "Worst-10 % NIPTS, 4 kHz, 90 dB, 20 yr")
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def _chk_iso1999_fractile() -> Outcome:
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value = float(ph.nipts(90.0, 20.0, 0.9).value[4])
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return numeric(ref.ISO1999_N10_4K_90_20, value, 0.5, unit="dB", places=1)
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@register(_NIHL, "ISO 1999:2013 Table D.4", "Worst-10 % NIPTS, 3 kHz, 100 dB, 40 yr")
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def _chk_iso1999_high() -> Outcome:
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value = float(ph.nipts(100.0, 40.0, 0.9).value[3])
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return numeric(ref.ISO1999_N10_3K_100_40, value, 0.5, unit="dB", places=1)
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# ===========================================================================
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# Markdown rendering
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# ===========================================================================
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scripts/generate_diagrams.py
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scripts/generate_diagrams.py
···
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"prob.-symmetric 95 % interval": "intervalo simétrico en prob. al 95 %",
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"coverage interval": "intervalo de cobertura",
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"[y_low, y_high] (clause 7.7)": "[y_low, y_high] (cláusula 7.7)",
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# Noise-induced hearing loss (ISO 1999)
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"Noise-induced hearing loss (ISO 1999): NIPTS and HTLAN":
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"Pérdida auditiva inducida por ruido (ISO 1999): NIPTS y HTLAN",
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"Age Y, sex, fractile Q": "Edad Y, sexo, fractil Q",
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"database A = ISO 7029": "base de datos A = ISO 7029",
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"Exposure L_EX,8h, t years": "Exposición L_EX,8h, t años",
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"normalized to 8 h / 5 days": "normalizada a 8 h / 5 días",
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"Age threshold H (HTLA)": "Umbral por edad H (HTLA)",
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"ISO 7029 fractile, dB": "fractil ISO 7029, dB",
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"Median NIPTS N50 (6.3.1)": "NIPTS mediana N50 (6.3.1)",
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"N50 = [u + v·lg(t/t0)]·(L − L0)²":
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"N50 = [u + v·lg(t/t0)]·(L − L0)²",
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"Fractile NIPTS N (6.3.2)": "NIPTS del fractil N (6.3.2)",
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"N = N50 + z·(du if z ≥ 0 else dl)":
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"N = N50 + z·(du si z ≥ 0, si no dl)",
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"HTLAN H' = H + N − H·N / 120": "HTLAN H' = H + N − H·N / 120",
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"threshold from age and noise (Formula 1, 6.1)":
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"umbral por edad y ruido (Fórmula 1, 6.1)",
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"Speech Ei'": "Habla Ei'",
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"Noise Ni'": "Ruido Ni'",
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"Threshold Ti'": "Umbral Ti'",
···
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s.text(rxc, 482, "[y_low, y_high] (clause 7.7)", 14, th.muted, "middle")
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def _d_nihl(s: SVG, th: Theme) -> None:
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"""Noise-induced hearing loss (ISO 1999:2013): NIPTS and HTLAN.
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Two converging lanes — the age component H (HTLA, database A = ISO 7029)
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and the noise component N (NIPTS, Formulae 2-7) — combine into the hearing
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threshold associated with age and noise (HTLAN, Formula 1).
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"""
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cx = 450.0
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lxc, rxc = 232.0, 668.0
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bw, bh = 372.0, 62.0
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def _step(cxx: float, y: float, l1: str, l2: str, color: str) -> None:
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s.rect(cxx - bw / 2, y, bw, bh, th.panel, color, rx=10, sw=2)
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s.text(cxx, y + 27, l1, 18, th.fg, "middle", bold=True)
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if l2:
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s.text(cxx, y + 48, l2, 13, th.muted, "middle")
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# --- Inputs -------------------------------------------------------------
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_step(lxc, 56, "Age Y, sex, fractile Q", "database A = ISO 7029", th.fg)
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_step(rxc, 56, "Exposure L_EX,8h, t years",
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"normalized to 8 h / 5 days", th.fg)
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# --- Left lane: age component H (HTLA) ----------------------------------
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s.arrow(lxc, 118, lxc, 150, th.fg, 1.8)
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_step(lxc, 150, "Age threshold H (HTLA)",
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"ISO 7029 fractile, dB", th.primary)
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# --- Right lane: noise component N (NIPTS) ------------------------------
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s.arrow(rxc, 118, rxc, 150, th.fg, 1.8)
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_step(rxc, 150, "Median NIPTS N50 (6.3.1)",
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"N50 = [u + v·lg(t/t0)]·(L − L0)²", th.secondary)
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s.arrow(rxc, 212, rxc, 244, th.fg, 1.8)
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_step(rxc, 244, "Fractile NIPTS N (6.3.2)",
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"N = N50 + z·(du if z ≥ 0 else dl)", th.fg)
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# --- Converge into HTLAN ------------------------------------------------
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box_y = 372.0
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s.arrow(lxc, 212, cx - 118.0, box_y, th.fg, 1.8)
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s.arrow(rxc, 306, cx + 118.0, box_y, th.fg, 1.8)
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s.rect(cx - bw / 2, box_y, bw, 66, "none", th.primary, rx=10, sw=2.4)
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s.text(cx, box_y + 29, "HTLAN H' = H + N − H·N / 120", 20, th.fg,
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"middle", bold=True)
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s.text(cx, box_y + 51, "threshold from age and noise (Formula 1, 6.1)",
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13, th.muted, "middle")
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DIAGRAMS = {
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"diagram_calibration_setup": (_d1, "Calibration chain — from calibrator to physical units", 560),
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"diagram_env_measurement": (_d2, "Environmental noise measurement positions (ISO 1996-2)", 560),
···
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"diagram_uncertainty": (
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_d_uncertainty,
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"Uncertainty: GUM propagation vs Monte Carlo (Guide 98-3)", 540),
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"diagram_nihl": (
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_d_nihl,
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"Noise-induced hearing loss (ISO 1999): NIPTS and HTLAN", 470),
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}
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scripts/generate_graphs.py
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scripts/generate_graphs.py
···
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"Reference threshold [dB]": "Umbral de referencia [dB]",
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"Free-field (frontal)": "Campo libre (frontal)",
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"Diffuse-field": "Campo difuso",
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r"ISO 1999 — NIPTS at $L_{EX,8h}$ = 95 dB":
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r"ISO 1999 — NIPTS a $L_{EX,8h}$ = 95 dB",
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"ISO 1999 — HTLAN (male, age 60, 95 dB / 30 yr)":
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"ISO 1999 — HTLAN (hombres, 60 años, 95 dB / 30 años)",
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"Median NIPTS [dB]": "NIPTS mediana [dB]",
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"Hearing threshold level [dB]": "Nivel del umbral de audición [dB]",
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"10-90 % band (40 yr)": "Banda 10-90 % (40 años)",
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"Age (HTLA, ISO 7029)": "Edad (HTLA, ISO 7029)",
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"Noise (NIPTS)": "Ruido (NIPTS)",
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"Age + noise (HTLAN)": "Edad + ruido (HTLAN)",
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"GUM uncertainty budget": "Presupuesto de incertidumbre (GUM)",
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"Contribution to combined uncertainty [dB]":
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"Contribución a la incertidumbre combinada [dB]",
···
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}
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_ES_PATTERNS = [
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(r"^(\d+) yr$", r"\1 años"),
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(r"^Octave Band: (.+) Hz$", r"Banda de octava: \1 Hz"),
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(r"^(\d+) phon$", r"\1 fonios"),
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(r"^TNR = (.+) dB\n\(criterion (.+) dB\)$", "TNR = \\1 dB\\n(criterio \\2 dB)"),
···
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plt.close()
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def generate_nihl(output_dir: str) -> None:
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"""ISO 1999 noise-induced permanent threshold shift and HTLAN combination."""
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print("Generating noise_induced_hearing_loss.png...")
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from phonometry import htlan, nipts
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from phonometry.iso1999 import NIPTS_FREQUENCIES
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freqs = NIPTS_FREQUENCIES
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fig, (ax_n, ax_h) = plt.subplots(1, 2, figsize=(12.5, 5.6))
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3577
+
# --- Left: median NIPTS growth with exposure duration at 95 dB. ---
3578
+
durations = [(10, COLOR_GRID), (20, "#7f7f7f"), (30, COLOR_PRIMARY),
3579
+
(40, COLOR_SECONDARY)]
3580
+
for years, color in durations:
3581
+
r = nipts(95.0, years, 0.5)
3582
+
ax_n.plot(freqs, r.median, "o-", color=color, label=f"{years} yr")
3583
+
r40 = nipts(95.0, 40.0, 0.5)
3584
+
z90 = 1.2816
3585
+
ax_n.fill_between(freqs, np.maximum(r40.median - z90 * r40.spread_lower, 0.0),
3586
+
r40.median + z90 * r40.spread_upper,
3587
+
color=COLOR_SECONDARY, alpha=0.12,
3588
+
label="10-90 % band (40 yr)")
3589
+
ax_n.set_xscale("log")
3590
+
ax_n.set_xticks(list(freqs))
3591
+
ax_n.set_xticklabels([f"{f:g}" for f in freqs], rotation=45, ha="right")
3592
+
ax_n.xaxis.set_minor_formatter(mticker.NullFormatter())
3593
+
ax_n.invert_yaxis()
3594
+
ax_n.set_xlabel("Audiometric frequency [Hz]")
3595
+
ax_n.set_ylabel("Median NIPTS [dB]")
3596
+
ax_n.set_title(r"ISO 1999 — NIPTS at $L_{EX,8h}$ = 95 dB",
3597
+
fontweight="bold", pad=10)
3598
+
ax_n.grid(which="both", color=COLOR_GRID, linestyle="-", alpha=0.4)
3599
+
ax_n.set_axisbelow(True)
3600
+
ax_n.legend(loc="lower left")
3601
+
3602
+
# --- Right: HTLAN = age + noise for a 60-year-old worker, 95 dB / 30 yr. ---
3603
+
h = htlan(60, "male", 95.0, 30.0, 0.5)
3604
+
ax_h.plot(freqs, h.htla, "o-", color=COLOR_PRIMARY,
3605
+
label="Age (HTLA, ISO 7029)")
3606
+
ax_h.plot(freqs, h.nipts, "^-", color="#ff7f0e", label="Noise (NIPTS)")
3607
+
ax_h.plot(freqs, h.threshold, "s--", color=COLOR_SECONDARY,
3608
+
label="Age + noise (HTLAN)")
3609
+
ax_h.set_xscale("log")
3610
+
ax_h.set_xticks(list(freqs))
3611
+
ax_h.set_xticklabels([f"{f:g}" for f in freqs], rotation=45, ha="right")
3612
+
ax_h.xaxis.set_minor_formatter(mticker.NullFormatter())
3613
+
ax_h.invert_yaxis()
3614
+
ax_h.set_xlabel("Audiometric frequency [Hz]")
3615
+
ax_h.set_ylabel("Hearing threshold level [dB]")
3616
+
ax_h.set_title("ISO 1999 — HTLAN (male, age 60, 95 dB / 30 yr)",
3617
+
fontweight="bold", pad=10)
3618
+
ax_h.grid(which="both", color=COLOR_GRID, linestyle="-", alpha=0.4)
3619
+
ax_h.set_axisbelow(True)
3620
+
ax_h.legend(loc="lower left")
3621
+
3622
+
plt.tight_layout()
3623
+
plt.savefig(themed_path(output_dir, "noise_induced_hearing_loss.png"))
3624
+
plt.close()
3625
+
3626
+
3557
3627
def generate_uncertainty(output_dir: str) -> None:
3558
3628
"""GUM uncertainty budget and Monte Carlo distribution (Guide 98-3 + S1)."""
3559
3629
print("Generating uncertainty_budget.png...")
···
3697
3767
3698
3768
# Hearing threshold (ISO 7029 age-related, ISO 389-7 reference).
3699
3769
generate_hearing_threshold(img_dir)
3770
+
3771
+
# Noise-induced hearing loss (ISO 1999 NIPTS and HTLAN).
3772
+
generate_nihl(img_dir)
3700
3773
3701
3774
# Measurement uncertainty (GUM Guide 98-3 + Supplement 1 Monte Carlo).
3702
3775
generate_uncertainty(img_dir)
+1
-1
site/astro.config.mjs
+1
-1
site/astro.config.mjs
···
291
291
{
292
292
label: 'Perception & speech',
293
293
translations: { es: 'Percepción e inteligibilidad' },
294
-
items: ['guides/psychoacoustics', 'guides/speech-intelligibility', 'guides/hearing-threshold'],
294
+
items: ['guides/psychoacoustics', 'guides/speech-intelligibility', 'guides/hearing-threshold', 'guides/noise-induced-hearing-loss'],
295
295
},
296
296
{
297
297
label: 'Sound power & intensity',
+10
tests/reference_data.py
+10
tests/reference_data.py
···
491
491
GUM_ADDITIVE_UC = 2.0 # combined standard uncertainty, additive model
492
492
GUM_COVERAGE_K99_16 = 2.92 # coverage factor t at p=0.99, v=16
493
493
GUM_WELCH_VEFF = 40.0 # Welch-Satterthwaite effective degrees of freedom
494
+
495
+
# ---------------------------------------------------------------------------
496
+
# Noise-induced hearing loss - ISO 1999:2013, Annex D worked examples (dB).
497
+
# Table D.2 (L_EX,8h = 90 dB, 20 years) at 4 kHz: median NIPTS = 13 dB and the
498
+
# most-susceptible tenth (fractile 0.9) = 18 dB. Table D.4 (100 dB, 40 years)
499
+
# at 3 kHz, fractile 0.9 = 60 dB.
500
+
# ---------------------------------------------------------------------------
501
+
ISO1999_N50_4K_90_20 = 13.0 # median NIPTS, 4 kHz, 90 dB, 20 yr
502
+
ISO1999_N10_4K_90_20 = 18.0 # worst-10 % NIPTS, 4 kHz, 90 dB, 20 yr
503
+
ISO1999_N10_3K_100_40 = 60.0 # worst-10 % NIPTS, 3 kHz, 100 dB, 40 yr
+133
tests/test_iso1999.py
+133
tests/test_iso1999.py
···
1
+
# Copyright (c) 2026. Jose M. Requena-Plens
2
+
"""Tests for :mod:`phonometry.iso1999` (noise-induced hearing loss).
3
+
4
+
Validated against the worked examples of ISO 1999:2013 Annex D (Tables D.1 to
5
+
D.4), which tabulate the NIPTS in dB for the six audiometric frequencies, four
6
+
exposure levels (85, 90, 95, 100 dB), four durations (10, 20, 30, 40 years) and
7
+
the 90 % / 50 % / 10 % fractiles. In the standard's notation the percentage is
8
+
the fraction of the population with worse hearing, so its 10 % column is the
9
+
most-susceptible tenth (fractile 0.9 here) and its 90 % column the least
10
+
(fractile 0.1).
11
+
"""
12
+
13
+
from __future__ import annotations
14
+
15
+
import numpy as np
16
+
import pytest
17
+
18
+
from phonometry import iso1999 as m
19
+
20
+
# Annex D, per (level, years): rows are the six frequencies 500..6000 Hz,
21
+
# columns the (90 %, 50 %, 10 %) fractiles -> here (0.10, 0.50, 0.90).
22
+
_ANNEX_D = {
23
+
(85.0, 40.0): [(0, 0, 0), (0, 0, 0), (1, 2, 2), (3, 5, 7), (5, 7, 9), (2, 4, 6)],
24
+
(90.0, 20.0): [(0, 0, 0), (0, 0, 0), (2, 4, 8), (7, 10, 16), (9, 13, 18), (4, 8, 14)],
25
+
(95.0, 10.0): [(0, 0, 1), (1, 2, 4), (0, 5, 13), (8, 16, 25), (13, 20, 27), (5, 14, 23)],
26
+
(100.0, 40.0): [(5, 7, 11), (8, 11, 19), (16, 24, 39), (29, 38, 60),
27
+
(30, 41, 56), (19, 30, 48)],
28
+
}
29
+
30
+
31
+
@pytest.mark.parametrize(("key", "expected"), _ANNEX_D.items())
32
+
def test_nipts_matches_annex_d(key: tuple[float, float], expected: list) -> None:
33
+
l_ex, years = key
34
+
got = np.column_stack([
35
+
np.round(m.nipts(l_ex, years, frac).value).astype(int)
36
+
for frac in (0.10, 0.50, 0.90)
37
+
])
38
+
np.testing.assert_array_equal(got, np.array(expected))
39
+
40
+
41
+
def test_median_formula_2_by_hand() -> None:
42
+
# 4000 Hz, 20 years, 90 dB: N50 = (u + v*lg t)*(L - L0)^2
43
+
# = (0.025 + 0.025*log10(20)) * (90 - 75)^2 = 12.94 dB.
44
+
r = m.nipts(90.0, 20.0, 0.5)
45
+
assert r.median[4] == pytest.approx(12.9435, abs=1e-3)
46
+
assert r.frequencies[4] == 4000.0
47
+
48
+
49
+
def test_level_below_cutoff_gives_zero() -> None:
50
+
# At 85 dB the 500 Hz (L0 = 93) and 1000 Hz (L0 = 89) bands are below the
51
+
# cut-off, so the NIPTS is zero at every fractile.
52
+
for frac in (0.1, 0.5, 0.9):
53
+
r = m.nipts(85.0, 30.0, frac)
54
+
assert r.value[0] == 0.0 # 500 Hz
55
+
assert r.value[1] == 0.0 # 1000 Hz
56
+
57
+
58
+
def test_fractile_ordering_and_median() -> None:
59
+
# The median is the 0.5 fractile; higher fractile => larger (worse) NIPTS.
60
+
low = m.nipts(95.0, 30.0, 0.1).value
61
+
mid = m.nipts(95.0, 30.0, 0.5).value
62
+
high = m.nipts(95.0, 30.0, 0.9).value
63
+
np.testing.assert_allclose(mid, m.nipts(95.0, 30.0, 0.5).median)
64
+
assert np.all(low <= mid) and np.all(mid <= high)
65
+
66
+
67
+
def test_negative_nipts_clamped_to_zero() -> None:
68
+
# For short durations the lower-fractile NIPTS can go negative and must be
69
+
# clamped to zero (clause 6.3.2).
70
+
r = m.nipts(90.0, 1.0, 0.05)
71
+
assert np.all(r.value >= 0.0)
72
+
73
+
74
+
def test_short_duration_extrapolation() -> None:
75
+
# Formula (3): N50(t<10) = lg(t+1)/lg(11) * N50(t=10).
76
+
n50_10 = m.nipts(95.0, 10.0, 0.5).median
77
+
n50_5 = m.nipts(95.0, 5.0, 0.5).median
78
+
factor = np.log10(5.0 + 1.0) / np.log10(11.0)
79
+
np.testing.assert_allclose(n50_5, factor * n50_10, rtol=1e-9)
80
+
81
+
82
+
def test_spreads_non_negative_subyear() -> None:
83
+
# Below 1 year the linear spread term can go negative; du/dl are clamped so
84
+
# the fractile ordering never inverts (spreads are standard deviations).
85
+
r_low = m.nipts(100.0, 0.02, 0.1)
86
+
r_high = m.nipts(100.0, 0.02, 0.9)
87
+
assert np.all(r_high.value >= r_low.value)
88
+
assert np.all(r_low.spread_upper >= 0.0)
89
+
assert np.all(r_low.spread_lower >= 0.0)
90
+
91
+
92
+
def test_htlan_formula_1() -> None:
93
+
# H' = H + N - H*N/120 at each frequency (clause 6.1).
94
+
r = m.htlan(60, "male", 90.0, 30.0, 0.5)
95
+
expected = r.htla + r.nipts - r.htla * r.nipts / 120.0
96
+
np.testing.assert_allclose(r.threshold, expected)
97
+
# The combined threshold is at least the age component alone.
98
+
assert np.all(r.threshold >= r.htla - 1e-9)
99
+
100
+
101
+
def test_htlan_matches_components() -> None:
102
+
r = m.htlan(50, "female", 100.0, 20.0, 0.9)
103
+
np.testing.assert_allclose(
104
+
r.nipts, m.nipts(100.0, 20.0, 0.9).value)
105
+
106
+
107
+
def test_frequency_subset() -> None:
108
+
r = m.nipts(95.0, 20.0, 0.5, frequencies=[4000.0, 6000.0])
109
+
full = m.nipts(95.0, 20.0, 0.5)
110
+
np.testing.assert_allclose(r.frequencies, [4000.0, 6000.0])
111
+
np.testing.assert_allclose(r.value, full.value[[4, 5]])
112
+
113
+
114
+
def test_invalid_inputs_raise() -> None:
115
+
with pytest.raises(ValueError, match="years must be positive"):
116
+
m.nipts(90.0, 0.0)
117
+
with pytest.raises(ValueError, match="fractile"):
118
+
m.nipts(90.0, 20.0, 1.5)
119
+
with pytest.raises(ValueError, match="not an ISO 1999"):
120
+
m.nipts(90.0, 20.0, frequencies=[1234.0])
121
+
with pytest.raises(ValueError, match="at least 18"):
122
+
m.htlan(10, "male", 90.0, 20.0)
123
+
124
+
125
+
def test_plots_return_axes() -> None:
126
+
import matplotlib
127
+
128
+
matplotlib.use("Agg")
129
+
import matplotlib.pyplot as plt
130
+
131
+
assert isinstance(m.nipts(95.0, 20.0, 0.9).plot(), plt.Axes)
132
+
assert isinstance(m.htlan(60, "male", 95.0, 20.0, 0.9).plot(), plt.Axes)
133
+
plt.close("all")
+1
.github/images/diagram_nihl.svg
+1
.github/images/diagram_nihl.svg
···
1
+
<svg xmlns="http://www.w3.org/2000/svg" width="900" height="470" viewBox="0 0 900 470"><rect width="900" height="470" fill="#ffffff"/><text x="450.0" y="30" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="26" font-weight="600" fill="#1a1a1a" text-anchor="middle">Noise-induced hearing loss (ISO 1999): NIPTS and HTLAN</text><rect x="46.0" y="56" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1a1a1a" stroke-width="2"/><text x="232.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Age Y, sex, fractile Q</text><text x="232.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">database A = ISO 7029</text><rect x="482.0" y="56" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1a1a1a" stroke-width="2"/><text x="668.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Exposure L_EX,8h, t years</text><text x="668.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">normalized to 8 h / 5 days</text><line x1="232.0" y1="118" x2="232.0" y2="141.0" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 232.0 150.0 L 228.4 141.0 L 235.6 141.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="46.0" y="150" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1f77b4" stroke-width="2"/><text x="232.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Age threshold H (HTLA)</text><text x="232.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">ISO 7029 fractile, dB</text><line x1="668.0" y1="118" x2="668.0" y2="141.0" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 150.0 L 664.4 141.0 L 671.6 141.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="150" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#d62728" stroke-width="2"/><text x="668.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Median NIPTS N50 (6.3.1)</text><text x="668.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">N50 = [u + v·lg(t/t0)]·(L − L0)²</text><line x1="668.0" y1="212" x2="668.0" y2="235.0" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 244.0 L 664.4 235.0 L 671.6 235.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="244" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1a1a1a" stroke-width="2"/><text x="668.0" y="271" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Fractile NIPTS N (6.3.2)</text><text x="668.0" y="292" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">N = N50 + z·(du if z ≥ 0 else dl)</text><line x1="232.0" y1="212" x2="327.2300095399714" y2="364.3680152639542" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 332.0 372.0 L 324.2 366.3 L 330.3 362.5 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><line x1="668.0" y1="306" x2="575.5114846590556" y2="367.04242012502334" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 568.0 372.0 L 573.5 364.0 L 577.5 370.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="264.0" y="372.0" width="372.0" height="66" rx="10" fill="none" stroke="#1f77b4" stroke-width="2.4"/><text x="450.0" y="401.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="20" fill="#1a1a1a" text-anchor="middle" font-weight="600">HTLAN H' = H + N − H·N / 120</text><text x="450.0" y="423.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">threshold from age and noise (Formula 1, 6.1)</text></svg>
+1
.github/images/diagram_nihl_dark.svg
+1
.github/images/diagram_nihl_dark.svg
···
1
+
<svg xmlns="http://www.w3.org/2000/svg" width="900" height="470" viewBox="0 0 900 470"><rect width="900" height="470" fill="#0d1117"/><text x="450.0" y="30" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="26" font-weight="600" fill="#e6e6e6" text-anchor="middle">Noise-induced hearing loss (ISO 1999): NIPTS and HTLAN</text><rect x="46.0" y="56" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e6e6e6" stroke-width="2"/><text x="232.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Age Y, sex, fractile Q</text><text x="232.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">database A = ISO 7029</text><rect x="482.0" y="56" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e6e6e6" stroke-width="2"/><text x="668.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Exposure L_EX,8h, t years</text><text x="668.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">normalized to 8 h / 5 days</text><line x1="232.0" y1="118" x2="232.0" y2="141.0" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 232.0 150.0 L 228.4 141.0 L 235.6 141.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="46.0" y="150" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#4da3d8" stroke-width="2"/><text x="232.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Age threshold H (HTLA)</text><text x="232.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">ISO 7029 fractile, dB</text><line x1="668.0" y1="118" x2="668.0" y2="141.0" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 150.0 L 664.4 141.0 L 671.6 141.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="150" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e46a6a" stroke-width="2"/><text x="668.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Median NIPTS N50 (6.3.1)</text><text x="668.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">N50 = [u + v·lg(t/t0)]·(L − L0)²</text><line x1="668.0" y1="212" x2="668.0" y2="235.0" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 244.0 L 664.4 235.0 L 671.6 235.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="244" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e6e6e6" stroke-width="2"/><text x="668.0" y="271" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Fractile NIPTS N (6.3.2)</text><text x="668.0" y="292" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">N = N50 + z·(du if z ≥ 0 else dl)</text><line x1="232.0" y1="212" x2="327.2300095399714" y2="364.3680152639542" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 332.0 372.0 L 324.2 366.3 L 330.3 362.5 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><line x1="668.0" y1="306" x2="575.5114846590556" y2="367.04242012502334" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 568.0 372.0 L 573.5 364.0 L 577.5 370.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="264.0" y="372.0" width="372.0" height="66" rx="10" fill="none" stroke="#4da3d8" stroke-width="2.4"/><text x="450.0" y="401.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="20" fill="#e6e6e6" text-anchor="middle" font-weight="600">HTLAN H' = H + N − H·N / 120</text><text x="450.0" y="423.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">threshold from age and noise (Formula 1, 6.1)</text></svg>
+1
.github/images/diagram_nihl_es.svg
+1
.github/images/diagram_nihl_es.svg
···
1
+
<svg xmlns="http://www.w3.org/2000/svg" width="900" height="470" viewBox="0 0 900 470"><rect width="900" height="470" fill="#ffffff"/><text x="450.0" y="30" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="26" font-weight="600" fill="#1a1a1a" text-anchor="middle">Pérdida auditiva inducida por ruido (ISO 1999): NIPTS y HTLAN</text><rect x="46.0" y="56" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1a1a1a" stroke-width="2"/><text x="232.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Edad Y, sexo, fractil Q</text><text x="232.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">base de datos A = ISO 7029</text><rect x="482.0" y="56" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1a1a1a" stroke-width="2"/><text x="668.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Exposición L_EX,8h, t años</text><text x="668.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">normalizada a 8 h / 5 días</text><line x1="232.0" y1="118" x2="232.0" y2="141.0" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 232.0 150.0 L 228.4 141.0 L 235.6 141.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="46.0" y="150" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1f77b4" stroke-width="2"/><text x="232.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">Umbral por edad H (HTLA)</text><text x="232.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">fractil ISO 7029, dB</text><line x1="668.0" y1="118" x2="668.0" y2="141.0" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 150.0 L 664.4 141.0 L 671.6 141.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="150" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#d62728" stroke-width="2"/><text x="668.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">NIPTS mediana N50 (6.3.1)</text><text x="668.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">N50 = [u + v·lg(t/t0)]·(L − L0)²</text><line x1="668.0" y1="212" x2="668.0" y2="235.0" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 244.0 L 664.4 235.0 L 671.6 235.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="244" width="372.0" height="62.0" rx="10" fill="#f0f2f5" stroke="#1a1a1a" stroke-width="2"/><text x="668.0" y="271" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#1a1a1a" text-anchor="middle" font-weight="600">NIPTS del fractil N (6.3.2)</text><text x="668.0" y="292" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">N = N50 + z·(du si z ≥ 0, si no dl)</text><line x1="232.0" y1="212" x2="327.2300095399714" y2="364.3680152639542" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 332.0 372.0 L 324.2 366.3 L 330.3 362.5 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><line x1="668.0" y1="306" x2="575.5114846590556" y2="367.04242012502334" stroke="#1a1a1a" stroke-width="1.8" stroke-linecap="round"/><path d="M 568.0 372.0 L 573.5 364.0 L 577.5 370.0 Z" fill="#1a1a1a" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="264.0" y="372.0" width="372.0" height="66" rx="10" fill="none" stroke="#1f77b4" stroke-width="2.4"/><text x="450.0" y="401.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="20" fill="#1a1a1a" text-anchor="middle" font-weight="600">HTLAN H' = H + N − H·N / 120</text><text x="450.0" y="423.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#666666" text-anchor="middle">umbral por edad y ruido (Fórmula 1, 6.1)</text></svg>
+1
.github/images/diagram_nihl_es_dark.svg
+1
.github/images/diagram_nihl_es_dark.svg
···
1
+
<svg xmlns="http://www.w3.org/2000/svg" width="900" height="470" viewBox="0 0 900 470"><rect width="900" height="470" fill="#0d1117"/><text x="450.0" y="30" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="26" font-weight="600" fill="#e6e6e6" text-anchor="middle">Pérdida auditiva inducida por ruido (ISO 1999): NIPTS y HTLAN</text><rect x="46.0" y="56" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e6e6e6" stroke-width="2"/><text x="232.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Edad Y, sexo, fractil Q</text><text x="232.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">base de datos A = ISO 7029</text><rect x="482.0" y="56" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e6e6e6" stroke-width="2"/><text x="668.0" y="83" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Exposición L_EX,8h, t años</text><text x="668.0" y="104" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">normalizada a 8 h / 5 días</text><line x1="232.0" y1="118" x2="232.0" y2="141.0" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 232.0 150.0 L 228.4 141.0 L 235.6 141.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="46.0" y="150" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#4da3d8" stroke-width="2"/><text x="232.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">Umbral por edad H (HTLA)</text><text x="232.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">fractil ISO 7029, dB</text><line x1="668.0" y1="118" x2="668.0" y2="141.0" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 150.0 L 664.4 141.0 L 671.6 141.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="150" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e46a6a" stroke-width="2"/><text x="668.0" y="177" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">NIPTS mediana N50 (6.3.1)</text><text x="668.0" y="198" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">N50 = [u + v·lg(t/t0)]·(L − L0)²</text><line x1="668.0" y1="212" x2="668.0" y2="235.0" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 668.0 244.0 L 664.4 235.0 L 671.6 235.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="482.0" y="244" width="372.0" height="62.0" rx="10" fill="#1c2128" stroke="#e6e6e6" stroke-width="2"/><text x="668.0" y="271" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="18" fill="#e6e6e6" text-anchor="middle" font-weight="600">NIPTS del fractil N (6.3.2)</text><text x="668.0" y="292" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">N = N50 + z·(du si z ≥ 0, si no dl)</text><line x1="232.0" y1="212" x2="327.2300095399714" y2="364.3680152639542" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 332.0 372.0 L 324.2 366.3 L 330.3 362.5 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><line x1="668.0" y1="306" x2="575.5114846590556" y2="367.04242012502334" stroke="#e6e6e6" stroke-width="1.8" stroke-linecap="round"/><path d="M 568.0 372.0 L 573.5 364.0 L 577.5 370.0 Z" fill="#e6e6e6" stroke="none" stroke-width="1.5" stroke-linejoin="round"/><rect x="264.0" y="372.0" width="372.0" height="66" rx="10" fill="none" stroke="#4da3d8" stroke-width="2.4"/><text x="450.0" y="401.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="20" fill="#e6e6e6" text-anchor="middle" font-weight="600">HTLAN H' = H + N − H·N / 120</text><text x="450.0" y="423.0" font-family="Segoe UI, Helvetica, Arial, sans-serif" font-size="13" fill="#9a9a9a" text-anchor="middle">umbral por edad y ruido (Fórmula 1, 6.1)</text></svg>
.github/images/noise_induced_hearing_loss.png
.github/images/noise_induced_hearing_loss.png
This is a binary file and will not be displayed.
.github/images/noise_induced_hearing_loss_dark.png
.github/images/noise_induced_hearing_loss_dark.png
This is a binary file and will not be displayed.
.github/images/noise_induced_hearing_loss_es.png
.github/images/noise_induced_hearing_loss_es.png
This is a binary file and will not be displayed.
.github/images/noise_induced_hearing_loss_es_dark.png
.github/images/noise_induced_hearing_loss_es_dark.png
This is a binary file and will not be displayed.
+10
src/phonometry/__init__.py
+10
src/phonometry/__init__.py
···
43
43
age_threshold,
44
44
reference_threshold,
45
45
)
46
+
from .iso1999 import (
47
+
HtlanResult,
48
+
NiptsResult,
49
+
htlan,
50
+
nipts,
51
+
)
46
52
from .uncertainty import (
47
53
MonteCarloResult,
48
54
Quantity,
···
420
426
"age_threshold",
421
427
"reference_threshold",
422
428
"AgeThresholdResult",
429
+
"nipts",
430
+
"htlan",
431
+
"NiptsResult",
432
+
"HtlanResult",
423
433
"combine_uncertainty",
424
434
"monte_carlo",
425
435
"rectangular",
+73
src/phonometry/_plotting.py
+73
src/phonometry/_plotting.py
···
38
38
from .room_acoustics import DecayCurve, RoomAcousticsResult
39
39
from .room_ir import ImpulseResponseResult
40
40
from .hearing import AgeThresholdResult
41
+
from .iso1999 import HtlanResult, NiptsResult
41
42
from .room_noise import NCResult, RCResult
42
43
from .tonality_ecma import EcmaTonality
43
44
from .roughness_ecma import EcmaRoughness
···
1474
1475
ax.invert_yaxis() # audiogram convention: worse hearing downward
1475
1476
ax.set_title(f"ISO 7029 hearing threshold — {result.sex}, age {result.age:g}")
1476
1477
ax.legend(loc=_LEGEND_UPPER_RIGHT, fontsize="small")
1478
+
ax.grid(True, which="both", alpha=0.3)
1479
+
return ax
1480
+
1481
+
1482
+
# ---------------------------------------------------------------------------
1483
+
# Noise-induced hearing loss (ISO 1999)
1484
+
# ---------------------------------------------------------------------------
1485
+
1486
+
1487
+
def plot_nipts(
1488
+
result: "NiptsResult", ax: Axes | None = None, **kwargs: Any
1489
+
) -> Axes:
1490
+
"""Median NIPTS spectrum with the 10-90 % fractile band (ISO 1999).
1491
+
1492
+
:param result: A :class:`~phonometry.iso1999.NiptsResult`.
1493
+
:param ax: Existing axes, or ``None`` to create a figure.
1494
+
:param kwargs: Forwarded to the median line ``plot``.
1495
+
:return: The axes.
1496
+
"""
1497
+
ax = ax if ax is not None else _new_axes()
1498
+
freqs = np.asarray(result.frequencies, dtype=np.float64)
1499
+
median = np.asarray(result.median, dtype=np.float64)
1500
+
du = np.asarray(result.spread_upper, dtype=np.float64)
1501
+
dl = np.asarray(result.spread_lower, dtype=np.float64)
1502
+
z90 = 1.2816 # standard-normal quantile of 0.9
1503
+
1504
+
ax.fill_between(freqs, np.maximum(median - z90 * dl, 0.0), median + z90 * du,
1505
+
color="#ffbb78", alpha=0.5, label="10-90 % fractile band")
1506
+
kwargs.setdefault("color", "#ff7f0e")
1507
+
ax.plot(freqs, median, "o-", label="Median $N_{50}$", **kwargs)
1508
+
if abs(result.fractile - 0.5) > 1e-9:
1509
+
ax.plot(freqs, np.asarray(result.value, dtype=np.float64), "s--",
1510
+
color="#d62728", label=f"Fractile {result.fractile:g}")
1511
+
_freq_axis(ax, freqs)
1512
+
ax.set_ylabel("NIPTS [dB]")
1513
+
ax.invert_yaxis() # audiogram convention: worse hearing downward
1514
+
ax.set_title(
1515
+
f"ISO 1999 NIPTS — $L_{{EX,8h}}$ = {result.l_ex:g} dB, "
1516
+
f"{result.years:g} yr"
1517
+
)
1518
+
ax.legend(loc=_LEGEND_UPPER_RIGHT, fontsize="small")
1519
+
ax.grid(True, which="both", alpha=0.3)
1520
+
return ax
1521
+
1522
+
1523
+
def plot_htlan(
1524
+
result: "HtlanResult", ax: Axes | None = None, **kwargs: Any
1525
+
) -> Axes:
1526
+
"""Age, noise and combined hearing threshold components (ISO 1999, 6.1).
1527
+
1528
+
:param result: A :class:`~phonometry.iso1999.HtlanResult`.
1529
+
:param ax: Existing axes, or ``None`` to create a figure.
1530
+
:param kwargs: Forwarded to the combined-threshold line ``plot``.
1531
+
:return: The axes.
1532
+
"""
1533
+
ax = ax if ax is not None else _new_axes()
1534
+
freqs = np.asarray(result.frequencies, dtype=np.float64)
1535
+
ax.plot(freqs, np.asarray(result.htla, dtype=np.float64), "o-",
1536
+
color="#1f77b4", label="Age (HTLA, ISO 7029)")
1537
+
ax.plot(freqs, np.asarray(result.nipts, dtype=np.float64), "^-",
1538
+
color="#ff7f0e", label="Noise (NIPTS)")
1539
+
kwargs.setdefault("color", "#d62728")
1540
+
ax.plot(freqs, np.asarray(result.threshold, dtype=np.float64), "s--",
1541
+
label="Age + noise (HTLAN)", **kwargs)
1542
+
_freq_axis(ax, freqs)
1543
+
ax.set_ylabel("Hearing threshold level [dB]")
1544
+
ax.invert_yaxis() # audiogram convention: worse hearing downward
1545
+
ax.set_title(
1546
+
f"ISO 1999 HTLAN — {result.sex}, age {result.age:g}, "
1547
+
f"{result.l_ex:g} dB / {result.years:g} yr"
1548
+
)
1549
+
ax.legend(loc="lower left", fontsize="small")
1477
1550
ax.grid(True, which="both", alpha=0.3)
1478
1551
return ax
1479
1552
+282
src/phonometry/iso1999.py
+282
src/phonometry/iso1999.py
···
1
+
# Copyright (c) 2026. Jose M. Requena-Plens
2
+
"""
3
+
Estimation of noise-induced hearing loss (ISO 1999:2013).
4
+
5
+
Implements the noise-induced permanent threshold shift (NIPTS) of a
6
+
noise-exposed population and its combination with the age-related threshold
7
+
into the hearing threshold level associated with age and noise (HTLAN), over
8
+
the six audiometric frequencies 500 Hz to 6000 Hz.
9
+
10
+
The median NIPTS for exposure durations of 10 to 40 years is
11
+
``N50 = [u + v*lg(t/t0)] * (L_EX,8h - L0)**2`` (clause 6.3.1, Formula 2, with
12
+
the values ``u, v, L0`` of Table 1), extrapolated below 10 years by Formula 3.
13
+
The statistical distribution about the median is two half-Gaussians whose
14
+
spreads ``du`` (worse than the median) and ``dl`` (better) follow Formulae 6/7
15
+
with the coefficients of Table 3; a population fractile is
16
+
``N50 + z * spread`` with ``z`` the standard-normal quantile (clause 6.3.2,
17
+
Formulae 4/5, Table 2), clamped at zero. The HTLAN combines the age component
18
+
``H`` (HTLA, database A = ISO 7029) with the noise component ``N`` by
19
+
``H' = H + N - H*N/120`` (clause 6.1, Formula 1).
20
+
"""
21
+
22
+
from __future__ import annotations
23
+
24
+
import math
25
+
from dataclasses import dataclass
26
+
from typing import TYPE_CHECKING, Any
27
+
28
+
import numpy as np
29
+
30
+
from .hearing import age_threshold
31
+
32
+
if TYPE_CHECKING:
33
+
from matplotlib.axes import Axes
34
+
35
+
from numpy.typing import ArrayLike
36
+
37
+
# ---------------------------------------------------------------------------
38
+
# Normative constants.
39
+
# ---------------------------------------------------------------------------
40
+
41
+
#: Audiometric frequencies of ISO 1999, in hertz (clause 6.3.1, Table 1).
42
+
NIPTS_FREQUENCIES: np.ndarray = np.array(
43
+
[500.0, 1000.0, 2000.0, 3000.0, 4000.0, 6000.0], dtype=np.float64
44
+
)
45
+
46
+
#: Table 1 columns ``u``, ``v`` and ``L0`` (dB) for the median NIPTS N50.
47
+
_UVL0: np.ndarray = np.array(
48
+
[[-0.033, 0.110, 93.0],
49
+
[-0.020, 0.070, 89.0],
50
+
[-0.045, 0.066, 80.0],
51
+
[0.012, 0.037, 77.0],
52
+
[0.025, 0.025, 75.0],
53
+
[0.019, 0.024, 77.0]],
54
+
dtype=np.float64,
55
+
)
56
+
57
+
#: Table 3 columns ``Xu``, ``Yu``, ``Xl``, ``Yl`` for the spreads du and dl.
58
+
_XY: np.ndarray = np.array(
59
+
[[0.044, 0.016, 0.033, 0.002],
60
+
[0.022, 0.016, 0.020, 0.000],
61
+
[0.031, -0.002, 0.016, 0.000],
62
+
[0.007, 0.016, 0.029, -0.010],
63
+
[0.005, 0.009, 0.016, -0.002],
64
+
[0.013, 0.008, 0.028, -0.007]],
65
+
dtype=np.float64,
66
+
)
67
+
68
+
_HTLAN_DENOM = 120.0 # the compression term denominator of Formula (1).
69
+
70
+
71
+
@dataclass(frozen=True)
72
+
class NiptsResult:
73
+
"""Noise-induced permanent threshold shift (ISO 1999:2013, clause 6.3).
74
+
75
+
All arrays are in dB and aligned with :data:`NIPTS_FREQUENCIES`.
76
+
77
+
:ivar l_ex: Noise exposure level normalized to 8 h, ``L_EX,8h``, in dB.
78
+
:ivar years: Exposure duration, in years.
79
+
:ivar fractile: Population fractile of ``value`` (0-1); the fraction of the
80
+
population with a smaller shift, so ``0.9`` is the most-susceptible 10 %.
81
+
:ivar frequencies: Audiometric frequencies, in hertz.
82
+
:ivar median: Median NIPTS ``N50`` (Formula 2/3).
83
+
:ivar value: NIPTS at ``fractile`` (Formula 4/5), clamped at zero.
84
+
:ivar spread_upper: Upper half-Gaussian spread ``du`` (Formula 6).
85
+
:ivar spread_lower: Lower half-Gaussian spread ``dl`` (Formula 7).
86
+
"""
87
+
88
+
l_ex: float
89
+
years: float
90
+
fractile: float
91
+
frequencies: np.ndarray
92
+
median: np.ndarray
93
+
value: np.ndarray
94
+
spread_upper: np.ndarray
95
+
spread_lower: np.ndarray
96
+
97
+
def plot(self, ax: "Axes | None" = None, **kwargs: Any) -> "Axes":
98
+
"""Plot the NIPTS spectrum with the fractile band over frequency.
99
+
100
+
Requires matplotlib (``pip install phonometry[plot]``); returns the
101
+
:class:`~matplotlib.axes.Axes`.
102
+
"""
103
+
from ._plotting import plot_nipts
104
+
105
+
return plot_nipts(self, ax=ax, **kwargs)
106
+
107
+
108
+
@dataclass(frozen=True)
109
+
class HtlanResult:
110
+
"""Hearing threshold level associated with age and noise (clause 6.1).
111
+
112
+
All arrays are in dB and aligned with :data:`NIPTS_FREQUENCIES`.
113
+
114
+
:ivar age: Listener age, in years.
115
+
:ivar sex: ``"male"`` or ``"female"``.
116
+
:ivar l_ex: Noise exposure level normalized to 8 h, in dB.
117
+
:ivar years: Exposure duration, in years.
118
+
:ivar fractile: Population fractile (0-1) applied to both components.
119
+
:ivar frequencies: Audiometric frequencies, in hertz.
120
+
:ivar htla: Age component ``H`` (HTLA, database A = ISO 7029).
121
+
:ivar nipts: Noise component ``N`` (NIPTS at ``fractile``).
122
+
:ivar threshold: Combined HTLAN ``H' = H + N - H*N/120``.
123
+
"""
124
+
125
+
age: float
126
+
sex: str
127
+
l_ex: float
128
+
years: float
129
+
fractile: float
130
+
frequencies: np.ndarray
131
+
htla: np.ndarray
132
+
nipts: np.ndarray
133
+
threshold: np.ndarray
134
+
135
+
def plot(self, ax: "Axes | None" = None, **kwargs: Any) -> "Axes":
136
+
"""Plot the age, noise and combined threshold components over frequency.
137
+
138
+
Requires matplotlib (``pip install phonometry[plot]``); returns the
139
+
:class:`~matplotlib.axes.Axes`.
140
+
"""
141
+
from ._plotting import plot_htlan
142
+
143
+
return plot_htlan(self, ax=ax, **kwargs)
144
+
145
+
146
+
def _select(values: np.ndarray, frequencies: ArrayLike | None) -> np.ndarray:
147
+
"""Return ``values`` for a requested frequency subset, or all of them."""
148
+
if frequencies is None:
149
+
return values.copy()
150
+
fr = np.atleast_1d(np.asarray(frequencies, dtype=np.float64))
151
+
idx = []
152
+
for f in fr:
153
+
matches = np.isclose(NIPTS_FREQUENCIES, f, rtol=1e-3)
154
+
if not matches.any():
155
+
raise ValueError(
156
+
f"frequency {f} Hz is not an ISO 1999 audiometric frequency "
157
+
f"(500 Hz - 6000 Hz)."
158
+
)
159
+
idx.append(int(np.argmax(matches)))
160
+
return values[idx]
161
+
162
+
163
+
def _nipts_components(l_ex: float, years: float) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
164
+
"""Median N50 and the spreads du, dl at every audiometric frequency."""
165
+
u, v, l0 = _UVL0[:, 0], _UVL0[:, 1], _UVL0[:, 2]
166
+
# L_EX,8h deemed equal to L0 where it is smaller, so the effect is zero.
167
+
excess2 = np.maximum(l_ex - l0, 0.0) ** 2
168
+
lg_t = math.log10(years) # lg(t / t0), t0 = 1 year
169
+
170
+
n50_10 = (u + v * math.log10(10.0)) * excess2
171
+
if years >= 10.0:
172
+
n50 = (u + v * lg_t) * excess2
173
+
else:
174
+
# Formula (3): extrapolate below 10 years from the 10-year value.
175
+
n50 = (math.log10(years + 1.0) / math.log10(11.0)) * n50_10
176
+
n50 = np.maximum(n50, 0.0)
177
+
178
+
xu, yu, xl, yl = _XY[:, 0], _XY[:, 1], _XY[:, 2], _XY[:, 3]
179
+
# The spreads are half-Gaussian standard deviations and must stay >= 0; the
180
+
# linear term can only turn negative for a sub-1-year extrapolation, outside
181
+
# the standard's range, where it would otherwise invert the percentiles.
182
+
du = np.maximum((xu + yu * lg_t) * excess2, 0.0)
183
+
dl = np.maximum((xl + yl * lg_t) * excess2, 0.0)
184
+
return n50, du, dl
185
+
186
+
187
+
def nipts(
188
+
l_ex: float,
189
+
years: float,
190
+
fractile: float = 0.5,
191
+
frequencies: ArrayLike | None = None,
192
+
) -> NiptsResult:
193
+
"""Noise-induced permanent threshold shift (ISO 1999:2013, clause 6.3).
194
+
195
+
Returns, per audiometric frequency, the median NIPTS ``N50`` (Formula 2,
196
+
extrapolated below 10 years by Formula 3), the upper/lower spreads
197
+
``du``/``dl`` (Formulae 6/7) and the NIPTS at the requested population
198
+
``fractile`` (Formulae 4/5): ``N50 + z * spread`` where ``z`` is the
199
+
standard-normal quantile of ``fractile`` and the spread is the upper one for
200
+
``z >= 0`` (worse than the median) or the lower one otherwise, clamped at
201
+
zero.
202
+
203
+
:param l_ex: Noise exposure level normalized to a nominal 8 h working day,
204
+
``L_EX,8h``, in dB.
205
+
:param years: Exposure duration, in years (> 0; the standard establishes
206
+
10-40 years and extrapolates 1-10 years by Formula 3, below 1 year the
207
+
result is a further extrapolation).
208
+
:param fractile: Population fractile in the open interval (0, 1); ``0.5``
209
+
gives the median. The reliable range of the standard is 0.05-0.95.
210
+
:param frequencies: Optional subset of the audiometric frequencies, in
211
+
hertz; ``None`` uses all six (500 Hz - 6000 Hz).
212
+
:return: A :class:`NiptsResult` with the distribution and ``.plot()``.
213
+
:raises ValueError: for a non-positive duration, a fractile outside (0, 1),
214
+
or an unknown frequency.
215
+
"""
216
+
if years <= 0.0:
217
+
raise ValueError(f"years must be positive; got {years}.")
218
+
if not 0.0 < fractile < 1.0:
219
+
raise ValueError(f"fractile must be in (0, 1); got {fractile}.")
220
+
221
+
from scipy.special import ndtri # standard-normal quantile
222
+
223
+
n50, du, dl = _nipts_components(float(l_ex), float(years))
224
+
z = float(ndtri(fractile))
225
+
value = np.maximum(n50 + z * (du if z >= 0.0 else dl), 0.0)
226
+
227
+
return NiptsResult(
228
+
l_ex=float(l_ex),
229
+
years=float(years),
230
+
fractile=float(fractile),
231
+
frequencies=_select(NIPTS_FREQUENCIES, frequencies),
232
+
median=_select(n50, frequencies),
233
+
value=_select(value, frequencies),
234
+
spread_upper=_select(du, frequencies),
235
+
spread_lower=_select(dl, frequencies),
236
+
)
237
+
238
+
239
+
def htlan(
240
+
age: float,
241
+
sex: str,
242
+
l_ex: float,
243
+
years: float,
244
+
fractile: float = 0.5,
245
+
frequencies: ArrayLike | None = None,
246
+
) -> HtlanResult:
247
+
"""Hearing threshold level associated with age and noise (clause 6.1).
248
+
249
+
Combines the age component ``H`` (HTLA from database A, i.e. ISO 7029, at
250
+
the same population fractile) with the noise component ``N`` (the NIPTS at
251
+
that fractile) by Formula (1): ``H' = H + N - H*N/120``. The formula applies
252
+
to corresponding percentage values, so the same ``fractile`` drives both
253
+
components.
254
+
255
+
:param age: Listener age, in years (at least 18, the ISO 7029 lower limit).
256
+
:param sex: ``"male"`` or ``"female"``.
257
+
:param l_ex: Noise exposure level normalized to 8 h, ``L_EX,8h``, in dB.
258
+
:param years: Exposure duration, in years.
259
+
:param fractile: Population fractile in (0, 1) applied to both components.
260
+
:param frequencies: Optional subset of the audiometric frequencies, in
261
+
hertz; ``None`` uses all six (500 Hz - 6000 Hz).
262
+
:return: An :class:`HtlanResult` with ``htla``, ``nipts``, ``threshold`` and
263
+
``.plot()``.
264
+
:raises ValueError: for an age below 18, an unknown sex, a non-positive
265
+
duration, a fractile outside (0, 1), or an unknown frequency.
266
+
"""
267
+
freqs = _select(NIPTS_FREQUENCIES, frequencies)
268
+
htla = age_threshold(age, sex, fractile, frequencies=freqs).threshold
269
+
noise = nipts(l_ex, years, fractile, frequencies=freqs).value
270
+
threshold = htla + noise - htla * noise / _HTLAN_DENOM
271
+
272
+
return HtlanResult(
273
+
age=float(age),
274
+
sex=sex,
275
+
l_ex=float(l_ex),
276
+
years=float(years),
277
+
fractile=float(fractile),
278
+
frequencies=freqs,
279
+
htla=htla,
280
+
nipts=noise,
281
+
threshold=threshold,
282
+
)
+121
site/src/content/docs/guides/noise-induced-hearing-loss.md
+121
site/src/content/docs/guides/noise-induced-hearing-loss.md
···
1
+
---
2
+
title: "Noise-induced hearing loss (ISO 1999)"
3
+
description: "The ISO 1999:2013 noise-induced permanent threshold shift (NIPTS) as a function of exposure level, duration and audiometric frequency with its population distribution, and its combination with the age component (ISO 7029) into the hearing threshold level associated with age and noise (HTLAN), over 500 Hz to 6000 Hz."
4
+
---
5
+
6
+
**ISO 1999:2013** estimates the hearing loss a population suffers from
7
+
occupational noise. It gives the **noise-induced permanent threshold shift**
8
+
(NIPTS) — the extra hearing loss caused by the noise, on top of ageing — as a
9
+
function of the exposure level, the exposure duration and the audiometric
10
+
frequency, together with its spread across a population. It then combines the
11
+
noise component with the age component (the ISO 7029 threshold, "database A")
12
+
into the **hearing threshold level associated with age and noise** (HTLAN).
13
+
Both are defined at the six audiometric frequencies 500 Hz to 6000 Hz, where
14
+
noise damage concentrates (the characteristic 4 kHz notch).
15
+
16
+
<img class="light-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/diagram_nihl.svg" alt="Two converging lanes: age, sex and a fractile give the age threshold H (HTLA, ISO 7029); the 8-hour-normalised level and duration give the median NIPTS N50 and then the fractile NIPTS N; the two combine into HTLAN = H + N - H*N/120" style="width:86%"><img class="dark-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/diagram_nihl_dark.svg" alt="Two converging lanes: age, sex and a fractile give the age threshold H (HTLA, ISO 7029); the 8-hour-normalised level and duration give the median NIPTS N50 and then the fractile NIPTS N; the two combine into HTLAN = H + N - H*N/120" style="width:86%">
17
+
18
+
## 1. Noise-induced permanent threshold shift (clause 6.3)
19
+
20
+
The median NIPTS for exposure durations of 10 to 40 years grows with the square
21
+
of the excess of the noise exposure level over a frequency-dependent cut-off
22
+
$L_0$ (ISO 1999 clause 6.3.1, Formula 2, Table 1):
23
+
24
+
$$
25
+
N_{50} = \left[u + v\,\lg\frac{t}{t_0}\right](L_{EX,8h} - L_0)^2,
26
+
$$
27
+
28
+
with $t$ the exposure in years and $t_0 = 1$ year; below $L_0$ the effect is
29
+
zero. A population **fractile** follows from two half-Gaussians whose spreads
30
+
$d_u$ (worse than the median) and $d_l$ (better) are given by Formulae 6/7 and
31
+
Table 3: $N_Q = N_{50} + z\,d$ with $z$ the standard-normal quantile, clamped at
32
+
zero (clause 6.3.2).
33
+
34
+
```python
35
+
import phonometry as ph
36
+
37
+
# Median NIPTS after 20 years at an 8 h-normalised level of 90 dB(A).
38
+
r = ph.nipts(90.0, 20.0, fractile=0.5)
39
+
print(r.frequencies.astype(int)) # [ 500 1000 2000 3000 4000 6000]
40
+
print(r.median.round(1)) # [ 0. 0.1 4.1 10.2 12.9 8.5]
41
+
42
+
# The most-susceptible tenth of the population (90th percentile):
43
+
print(ph.nipts(90.0, 20.0, fractile=0.9).value.round(1))
44
+
# [ 0. 0.1 7.7 16.2 17.8 13.6]
45
+
```
46
+
47
+
The shift peaks near 4 kHz and deepens with both level and duration. Below the
48
+
cut-off — here 500 Hz ($L_0 = 93$ dB) and 1000 Hz ($L_0 = 89$ dB) at 90 dB —
49
+
the noise causes no permanent shift. For durations under 10 years the median is
50
+
extrapolated from the 10-year value (Formula 3); a subset of the frequencies
51
+
can be requested with `frequencies=`.
52
+
53
+
## 2. Age and noise combined — HTLAN (clause 6.1)
54
+
55
+
The noise component does not simply add to the age component: ISO 1999
56
+
Formula (1) combines them with a compression term that matters once the total
57
+
exceeds about 40 dB:
58
+
59
+
$$
60
+
H' = H + N - \frac{H\,N}{120},
61
+
$$
62
+
63
+
where $H$ is the age threshold (HTLA, from ISO 7029 at the same fractile) and
64
+
$N$ the NIPTS. `htlan` evaluates both components and their combination.
65
+
66
+
```python
67
+
import phonometry as ph
68
+
69
+
# A 60-year-old man, 30 years at 95 dB(A), median.
70
+
h = ph.htlan(60, "male", 95.0, 30.0, fractile=0.5)
71
+
print(h.htla.round(1)) # [ 6. 7.8 12.5 16.6 20.2 25.9] age alone
72
+
print(h.nipts.round(1)) # [ 0.5 3. 11.8 21.6 24.8 17.6] noise alone
73
+
print(h.threshold.round(1)) # [ 6.5 10.7 23. 35.2 40.8 39.8] age + noise
74
+
```
75
+
76
+
At 4 kHz the age component (20.2 dB) and the noise component (24.8 dB) combine
77
+
to 40.8 dB rather than their 45.0 dB sum — the compression term removes 4.2 dB.
78
+
79
+
<img class="light-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/noise_induced_hearing_loss.png" alt="Two panels. Left: the median NIPTS at 95 dB for 10, 20, 30 and 40 years on an inverted audiogram axis with the 10 to 90 percent band around the 40-year curve, deepening toward 4 kHz. Right: for a 60-year-old man exposed 30 years at 95 dB, the age (HTLA), noise (NIPTS) and combined HTLAN curves, the HTLAN lying below the simple sum" style="width:96%"><img class="dark-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/noise_induced_hearing_loss_dark.png" alt="Two panels. Left: the median NIPTS at 95 dB for 10, 20, 30 and 40 years on an inverted audiogram axis with the 10 to 90 percent band around the 40-year curve, deepening toward 4 kHz. Right: for a 60-year-old man exposed 30 years at 95 dB, the age (HTLA), noise (NIPTS) and combined HTLAN curves, the HTLAN lying below the simple sum" style="width:96%">
80
+
81
+
<details>
82
+
<summary>Show the code for this figure</summary>
83
+
84
+
```python
85
+
import matplotlib.pyplot as plt
86
+
import phonometry as ph
87
+
from phonometry.iso1999 import NIPTS_FREQUENCIES as f
88
+
89
+
# One line for the NIPTS spectrum with its fractile band:
90
+
ph.nipts(95.0, 40.0, 0.9).plot()
91
+
plt.show()
92
+
93
+
# By hand, both panels:
94
+
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12.5, 5.6))
95
+
for yr in (10, 20, 30, 40):
96
+
ax1.plot(f, ph.nipts(95.0, yr, 0.5).median, "o-", label=f"{yr} yr")
97
+
ax1.set_xscale("log"); ax1.invert_yaxis(); ax1.legend()
98
+
99
+
h = ph.htlan(60, "male", 95.0, 30.0, 0.5)
100
+
ax2.plot(f, h.htla, "o-", label="Age (HTLA)")
101
+
ax2.plot(f, h.nipts, "^-", label="Noise (NIPTS)")
102
+
ax2.plot(f, h.threshold, "s--", label="Age + noise (HTLAN)")
103
+
ax2.set_xscale("log"); ax2.invert_yaxis(); ax2.legend()
104
+
plt.show()
105
+
```
106
+
107
+
</details>
108
+
109
+
The `NiptsResult` carries the `median` (`N50`), the `spread_upper`/`spread_lower`
110
+
and the `value` at the requested fractile; the `HtlanResult` carries `htla`,
111
+
`nipts` and the combined `threshold`. Both expose `.plot()`. The age component
112
+
alone is the subject of the
113
+
[hearing-threshold](/phonometry/guides/hearing-threshold/) guide.
114
+
115
+
---
116
+
117
+
**Standards.** ISO 1999:2013, *Acoustics — Estimation of noise-induced hearing
118
+
loss* — the HTLAN combination (clause 6.1, Formula 1), the median NIPTS
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(clause 6.3.1, Formulae 2-3, Table 1) and its statistical distribution
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(clause 6.3.2, Formulae 4-7, Tables 2-3), validated against the worked examples
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of Annex D. The age component (database A) is ISO 7029:2017.
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site/src/content/docs/es/guides/noise-induced-hearing-loss.md
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site/src/content/docs/es/guides/noise-induced-hearing-loss.md
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---
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title: "Pérdida auditiva inducida por ruido (ISO 1999)"
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description: "El desplazamiento permanente del umbral inducido por ruido (NIPTS) de ISO 1999:2013 en función del nivel de exposición, la duración y la frecuencia audiométrica con su distribución poblacional, y su combinación con la componente por edad (ISO 7029) en el umbral de audición asociado a la edad y al ruido (HTLAN), de 500 Hz a 6000 Hz."
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---
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**ISO 1999:2013** estima la pérdida auditiva que sufre una población por el
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ruido laboral. Da el **desplazamiento permanente del umbral inducido por ruido**
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(NIPTS) — la pérdida auditiva adicional causada por el ruido, sobre la del
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envejecimiento — en función del nivel de exposición, la duración de la
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exposición y la frecuencia audiométrica, junto con su dispersión en la
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población. Después combina la componente de ruido con la componente de edad (el
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umbral de ISO 7029, «base de datos A») en el **umbral de audición asociado a la
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edad y al ruido** (HTLAN). Ambos se definen en las seis frecuencias
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audiométricas de 500 Hz a 6000 Hz, donde se concentra el daño por ruido (la
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muesca característica a 4 kHz).
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<img class="light-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/diagram_nihl_es.svg" alt="Dos vías que convergen: la edad, el sexo y un fractil dan el umbral por edad H (HTLA, ISO 7029); el nivel normalizado a 8 h y la duración dan el NIPTS mediano N50 y luego el NIPTS del fractil N; ambos se combinan en HTLAN = H + N - H*N/120" style="width:86%"><img class="dark-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/diagram_nihl_es_dark.svg" alt="Dos vías que convergen: la edad, el sexo y un fractil dan el umbral por edad H (HTLA, ISO 7029); el nivel normalizado a 8 h y la duración dan el NIPTS mediano N50 y luego el NIPTS del fractil N; ambos se combinan en HTLAN = H + N - H*N/120" style="width:86%">
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## 1. Desplazamiento permanente del umbral por ruido (cláusula 6.3)
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El NIPTS mediano para duraciones de exposición de 10 a 40 años crece con el
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cuadrado del exceso del nivel de exposición sobre un umbral de corte $L_0$
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dependiente de la frecuencia (ISO 1999, cláusula 6.3.1, Fórmula 2, Tabla 1):
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$$
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N_{50} = \left[u + v\,\lg\frac{t}{t_0}\right](L_{EX,8h} - L_0)^2,
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$$
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con $t$ la exposición en años y $t_0 = 1$ año; por debajo de $L_0$ el efecto es
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nulo. Un **fractil** poblacional se obtiene de dos semi-gaussianas cuyas
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dispersiones $d_u$ (peor que la mediana) y $d_l$ (mejor) se dan en las Fórmulas
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6/7 y la Tabla 3: $N_Q = N_{50} + z\,d$ con $z$ el cuantil normal estándar,
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recortado a cero (cláusula 6.3.2).
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```python
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import phonometry as ph
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# Median NIPTS after 20 years at an 8 h-normalised level of 90 dB(A).
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r = ph.nipts(90.0, 20.0, fractile=0.5)
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print(r.frequencies.astype(int)) # [ 500 1000 2000 3000 4000 6000]
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print(r.median.round(1)) # [ 0. 0.1 4.1 10.2 12.9 8.5]
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# The most-susceptible tenth of the population (90th percentile):
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print(ph.nipts(90.0, 20.0, fractile=0.9).value.round(1))
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# [ 0. 0.1 7.7 16.2 17.8 13.6]
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```
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El desplazamiento alcanza su máximo cerca de 4 kHz y se acentúa con el nivel y
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la duración. Por debajo del corte —aquí 500 Hz ($L_0 = 93$ dB) y 1000 Hz
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($L_0 = 89$ dB) a 90 dB— el ruido no produce desplazamiento permanente. Para
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duraciones menores de 10 años la mediana se extrapola del valor a 10 años
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(Fórmula 3); puede pedirse un subconjunto de frecuencias con `frequencies=`.
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## 2. Edad y ruido combinados — HTLAN (cláusula 6.1)
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La componente de ruido no se suma sin más a la de edad: la Fórmula (1) de
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ISO 1999 las combina con un término de compresión que importa cuando el total
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supera unos 40 dB:
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$$
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H' = H + N - \frac{H\,N}{120},
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$$
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donde $H$ es el umbral por edad (HTLA, de ISO 7029 al mismo fractil) y $N$ el
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NIPTS. `htlan` evalúa ambas componentes y su combinación.
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```python
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import phonometry as ph
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# A 60-year-old man, 30 years at 95 dB(A), median.
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h = ph.htlan(60, "male", 95.0, 30.0, fractile=0.5)
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print(h.htla.round(1)) # [ 6. 7.8 12.5 16.6 20.2 25.9] age alone
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print(h.nipts.round(1)) # [ 0.5 3. 11.8 21.6 24.8 17.6] noise alone
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print(h.threshold.round(1)) # [ 6.5 10.7 23. 35.2 40.8 39.8] age + noise
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```
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A 4 kHz la componente de edad (20,2 dB) y la de ruido (24,8 dB) se combinan en
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40,8 dB en lugar de su suma de 45,0 dB: el término de compresión quita 4,2 dB.
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<img class="light-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/noise_induced_hearing_loss_es.png" alt="Dos paneles. Izquierda: el NIPTS mediano a 95 dB para 10, 20, 30 y 40 años en un eje de audiograma invertido con la banda del 10 al 90 por ciento en torno a la curva de 40 años, que se acentúa hacia 4 kHz. Derecha: para un hombre de 60 años expuesto 30 años a 95 dB, las curvas de edad (HTLA), ruido (NIPTS) y HTLAN combinada, que queda por debajo de la suma simple" style="width:96%"><img class="dark-only" src="https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/images/noise_induced_hearing_loss_es_dark.png" alt="Dos paneles. Izquierda: el NIPTS mediano a 95 dB para 10, 20, 30 y 40 años en un eje de audiograma invertido con la banda del 10 al 90 por ciento en torno a la curva de 40 años, que se acentúa hacia 4 kHz. Derecha: para un hombre de 60 años expuesto 30 años a 95 dB, las curvas de edad (HTLA), ruido (NIPTS) y HTLAN combinada, que queda por debajo de la suma simple" style="width:96%">
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<details>
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<summary>Mostrar el código de esta figura</summary>
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```python
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import matplotlib.pyplot as plt
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import phonometry as ph
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from phonometry.iso1999 import NIPTS_FREQUENCIES as f
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# One line for the NIPTS spectrum with its fractile band:
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ph.nipts(95.0, 40.0, 0.9).plot()
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plt.show()
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# By hand, both panels:
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12.5, 5.6))
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for yr in (10, 20, 30, 40):
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ax1.plot(f, ph.nipts(95.0, yr, 0.5).median, "o-", label=f"{yr} yr")
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ax1.set_xscale("log"); ax1.invert_yaxis(); ax1.legend()
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h = ph.htlan(60, "male", 95.0, 30.0, 0.5)
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ax2.plot(f, h.htla, "o-", label="Age (HTLA)")
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ax2.plot(f, h.nipts, "^-", label="Noise (NIPTS)")
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ax2.plot(f, h.threshold, "s--", label="Age + noise (HTLAN)")
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ax2.set_xscale("log"); ax2.invert_yaxis(); ax2.legend()
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plt.show()
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```
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</details>
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El `NiptsResult` lleva la `median` (`N50`), las `spread_upper`/`spread_lower` y
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el `value` en el fractil pedido; el `HtlanResult` lleva `htla`, `nipts` y el
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`threshold` combinado. Ambos exponen `.plot()`. La componente de edad por sí
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sola es el tema de la guía de
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[umbral de audición](/phonometry/es/guides/hearing-threshold/).
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---
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**Normas.** ISO 1999:2013, *Acoustics — Estimation of noise-induced hearing
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loss* — la combinación HTLAN (cláusula 6.1, Fórmula 1), el NIPTS mediano
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(cláusula 6.3.1, Fórmulas 2-3, Tabla 1) y su distribución estadística
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(cláusula 6.3.2, Fórmulas 4-7, Tablas 2-3), validado frente a los ejemplos
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resueltos del Anexo D. La componente de edad (base de datos A) es ISO 7029:2017.