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kennethreitz
69ddb1eb64
intervals: now returns semitone counts (integers) instead of Hz differences — octave-invariant and musically meaningful harmony: frequency ratio simplicity model — reduces each pairwise frequency ratio to simplest form and scores by 1/(num+denom). Simple ratios (octave 2:1, fifth 3:2) score highest. dissonance: Plomp-Levelt roughness with Bark-scale critical bandwidth (Zwicker & Terhardt 1980). Models sensory roughness from interfering fundamentals — peaks when freq difference ≈ critical bandwidth. beat_frequencies: new property returning all pairwise beat frequencies as sorted (tone, tone, hz) tuples beat_pulse: returns smallest non-zero beat frequency (most perceptible) All properties have detailed docstrings with psychoacoustic references, perceptual ranges, and usage examples. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
PyTheory: Music Theory for Humans
This (work in progress) library attempts to make exploring music theory approachable to humans.
True Scale -> Pitch Evaluation
>>> from pytheory import TonedScale
>>> c_minor = TonedScale(tonic='C4')['minor']
>>> c_minor
<Scale I=C4 II=D4 III=Eb4 IV=F4 V=G4 VI=Ab4 VII=Bb5 VIII=C5>
>>> c_minor[0].pitch()
523.251130601197
>>> c_minor["I"].pitch(symbolic=True)
440*2**(1/4)
>>> c_minor["tonic"].pitch(temperament='pythagorean', symbolic=True)
14080/27
Audibly play a note (or chord)
>>> from pytheory import play
play(c_minor[0], t=1_000)
Chord Fingerings for Custom Tunings
>>> from pytheory import Tone, Fretboard, CHARTS
>>> tones = (
... Tone.from_string("F2"),
... Tone.from_string("C3"),
... Tone.from_string("G3"),
... Tone.from_string("D4"),
... Tone.from_string("A5"),
... Tone.from_string("E5")
... )
>>> fretboard = Fretboard(tones=tones)
>>>
>>> c_chord = CHARTS['western']["C"]
>>> print(c_chord.fingering(fretboard=fretboard))
(0, 0, 0, 3, 3, 3)
It can also generate charts for all known chords for any instrument (accuracy to be determined!).
✨🍰✨