Source: https://jmrplens.github.io/phonometry/io/ # Audio files Every other area of this library starts from an array that is already in memory; this one is about the files the array comes from and returns to. Its premise is that an audio file made by a measurement chain is a *measurement record*: the samples are only meaningful next to the sample rate, the calibration that maps digital full scale to pascals, and the provenance that says where, when and through what the recording was made. The module `phonometry.io` reads and writes with exactly that in mind — and never resamples, never mixes channels down, never normalizes, and never touches a level, because each of those is a documented default somewhere in the ecosystem and each one quietly destroys the quantity a measurement exists to preserve. The practical shape follows from an equipment survey rather than from format completism. Sound level meters and field recorders emit linear WAV — 24-bit PCM, `WAVE_FORMAT_EXTENSIBLE` for multichannel, BWF `bext` metadata, RF64 once an overnight recording passes 4 GiB — so the **base install** (NumPy and SciPy alone) reads all of it, and the compressed formats live behind the optional `[audio]` extra (python-soundfile, whose wheel bundles libsndfile under the LGPL-2.1). Lossy sources are read but flagged, loudly: a level computed from an ADPCM or MP3 approximation of the waveform is not defensible, and the warning plus the `lossy` stamp keep that fact attached to the data. What comes back from a file is a `Signal` (`io.Signal`, or `phonometry.Signal`; the module it is defined in is private): the samples with their rate, calibration, channel labels and `bext` provenance in one immutable object that behaves as the bare array everywhere (`np.asarray` hands any existing function the samples), draws itself with `.plot()`, and walks straight into the level functions — `leq`, `laeq`, `ln_levels`, `sel`, `lc_peak`, `sound_exposure`, `lex_8h` — without repeating the rate or the calibration by hand. In the other direction, `write()` produces WAV/BWF (24-bit packed in-house) and FLAC, refuses to clip silently, extends the `CodingHistory` rather than replacing it, can measure the five EBU R 128 loudness values of `bext` version 2 with the library's own BS.1770 implementation, and puts the calibration in a small versioned JSON sidecar beside the audio — the one number no audio container has a field for, made to travel. ## Pages in this section - [Reading and writing measurement audio](https://jmrplens.github.io/phonometry/audio-files/): the whole workflow on one runnable page — reading a meter's WAV into a calibrated `Signal`, deriving the calibration from the calibrator take, the lossy warning and the listening-copy story behind it, streaming an overnight recording through stateful filters, writing BWF with its provenance, the sidecar round trip, and conversion that keeps the measurement a measurement. ## What this section does not cover **No playback, no editing, no effects.** This is a file layer for measurements, not an audio workstation: nothing here plays a sound, trims a region by ear, or applies gain. There is deliberately no lossy *writing* either — no measurement ends in an MP3, and a library whose job is preserving levels should not make one easy to produce. **AAC/M4A stays external.** Dictaphone and phone recordings in MP4 containers are not decoded; the honest route is a one-line `ffmpeg -i note.m4a note.wav` and then `read()`, with the same lossy caveat either way. Likewise the DAQ formats that are not audio at all — TDMS (LabVIEW) and UFF (modal analysis) have their own Python readers, `npTDMS` and `pyuff`, and pretending they are audio files would serve neither. **Ambisonic files are tolerated, not interpreted.** A B-format `.amb` file or an ambisonic GUID reads fine and its channels come back labelled, but no FuMa-to-AmbiX conversion matrix is applied: channel 0 of a FuMa file carries W at −3 dB, and turning that into a pressure without saying so would be a silent level change — the exact class of default this module exists to refuse. ## Before and after these pages Before: [Calibration and dBFS](https://jmrplens.github.io/phonometry/signals/metrology/calibration/) explains where the calibration factor a `Signal` carries actually comes from, and [Getting started](https://jmrplens.github.io/phonometry/start/getting-started/) runs a first file through the chain. After: everything — the point of the file layer is that [levels](https://jmrplens.github.io/phonometry/signals/levels/levels/), [octave filtering](https://jmrplens.github.io/phonometry/signals/filters/filter-banks/), [block processing](https://jmrplens.github.io/phonometry/signals/filters/block-processing/) and the rest of the library receive a calibrated signal and never learn it came from a file. If you arrived here from a search and want the shape of the whole library, [What do you need to measure?](https://jmrplens.github.io/phonometry/start/tasks/) indexes it by the job and [All guides](https://jmrplens.github.io/phonometry/) lists every page with a line on each.