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6 Commits
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| 751d5a49b8 | |||
| 6a836dd891 | |||
| 1f888e2b21 | |||
| fb923f6c76 | |||
| 59e3338892 | |||
| 8cf4145c15 |
+4
-1
@@ -21,7 +21,10 @@ All notable changes to PyTheory are documented here.
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decrescendo rolls on any instrument
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- **Vibrato tuning** — all instruments reduced to 0.001 depth for cleaner
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ensemble sound
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- 29 synth waveforms, 838 tests
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- **Granular synthesis** — grain cloud engine with scatter, pitch
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variation, and Hanning-windowed grains. Two presets: granular_pad,
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granular_texture.
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- 30 synth waveforms, 838 tests
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## 0.34.0
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@@ -620,6 +620,36 @@ Three bend types:
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- ``"late"`` — holds the starting pitch for 60%, bends in the last 40%.
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The classic blues "curl."
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Rolls
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-----
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Rapid repeated notes with a velocity ramp — perfect for timpani
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rolls, snare rolls, tremolo on any instrument. The velocity ramps
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from ``velocity_start`` to ``velocity_end`` for crescendo or
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decrescendo effects.
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.. code-block:: python
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# Timpani crescendo roll
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timp = score.part("timp", instrument="timpani")
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timp.roll("C3", Duration.WHOLE, velocity_start=20, velocity_end=110)
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timp.add("C3", Duration.HALF, velocity=127) # big accent
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# Snare roll with 32nd notes
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snare = score.part("snare", synth="noise", envelope="pluck")
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snare.roll("C4", Duration.HALF, speed=0.125,
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velocity_start=40, velocity_end=100)
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# Decrescendo (loud to quiet)
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timp.roll("G2", Duration.WHOLE, velocity_start=100, velocity_end=30)
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Parameters:
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- ``velocity_start``: Starting velocity (default 40).
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- ``velocity_end``: Ending velocity (default 100).
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- ``speed``: Note subdivision (default ``Duration.SIXTEENTH``).
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Use ``0.125`` for 32nd notes, ``Duration.EIGHTH`` for 8th notes.
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Tuning Systems
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--------------
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+55
-3
@@ -1,7 +1,7 @@
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Synthesizers
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============
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PyTheory includes 27 built-in waveforms and 10 ADSR envelope presets.
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PyTheory includes 30 built-in waveforms and 10 ADSR envelope presets.
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Every sound is generated from scratch -- no samples or external audio
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files needed.
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@@ -390,11 +390,11 @@ Dedicated Instrument Synths
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--------------------------
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Beyond the classic and physical modeling waveforms, PyTheory includes
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14 dedicated instrument synths. Each one uses tailored synthesis
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17 dedicated instrument synths. Each one uses tailored synthesis
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techniques -- additive harmonics, formant shaping, body resonance
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modeling, and specialized envelopes -- to capture the character of a
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specific acoustic instrument. These are the waveforms that bring the
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total count to 27.
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total count to 30.
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Piano Synth
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~~~~~~~~~~~
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@@ -535,6 +535,58 @@ bridge, producing a shimmering, metallic sustain.
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sitar = score.part("sitar", synth="sitar_synth")
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Timpani Synth
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~~~~~~~~~~~~~
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Large kettle drum with definite pitch. Inharmonic membrane modes
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(1.0, 1.5, 1.99, 2.44), felt mallet attack, copper kettle resonance.
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Use ``Part.roll()`` for crescendo timpani rolls.
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.. code-block:: python
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timp = score.part("timp", synth="timpani_synth")
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timp.roll("C3", Duration.WHOLE, velocity_start=20, velocity_end=110)
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Saxophone Synth
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~~~~~~~~~~~~~~~
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Single reed through a conical brass bore. All harmonics with strong
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mids, reed buzz, and brass body warmth. Four presets: ``saxophone``,
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``alto_sax``, ``tenor_sax``, ``bari_sax``.
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.. code-block:: python
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sax = score.part("sax", instrument="tenor_sax")
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Granular Synth
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~~~~~~~~~~~~~~
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Grain cloud synthesis — chops a source waveform into tiny overlapping
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grains (10-200ms), each windowed and optionally pitch/time scattered.
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Creates textures impossible with other synthesis: frozen tones,
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shimmering clouds, evolving pads, glitchy stutters.
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.. code-block:: python
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# Atmospheric granular pad
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pad = score.part("pad", instrument="granular_pad")
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# Granular with filter envelope sweep + resonance
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texture = score.part("texture", synth="granular_synth", envelope="pad",
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filter_amount=4000, filter_attack=0.5,
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filter_decay=1.5, filter_sustain=0.3,
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lowpass=600, lowpass_q=3.0,
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reverb=0.5, reverb_type="taj_mahal")
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Parameters (passed as synth kwargs):
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- ``grain_size``: Duration per grain in seconds (default 0.04).
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- ``density``: Grains per second (default 50). Higher = denser cloud.
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- ``scatter``: Random position jitter 0-1 (default 0.5).
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- ``pitch_var``: Per-grain pitch randomization in cents (default 12).
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- ``source``: Base waveform — ``"saw"``, ``"sine"``, ``"triangle"``,
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``"square"``, ``"noise"``.
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Analog Oscillator Drift
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~~~~~~~~~~~~~~~~~~~~~~~~
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+1
-1
@@ -77,7 +77,7 @@ What's Inside
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numbers), scale recommendation, modulation, voice leading
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- **Sequencing** — Score, Parts, arpeggiator, legato/glide, velocity,
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swing, humanize, tempo changes, song sections with repeat
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- **Synthesis** — 29 waveforms (including Karplus-Strong pluck, Hammond organ,
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- **Synthesis** — 30 waveforms (including Karplus-Strong pluck, Hammond organ,
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bowed string, and 14 dedicated instrument synths), 10 envelopes, 40+
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instrument presets, configurable FM, sub-oscillator, noise layer, filter
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envelope, velocity-to-brightness, analog oscillator drift, detune, stereo
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+1
-1
@@ -1,6 +1,6 @@
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[project]
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name = "pytheory"
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version = "0.35.0"
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version = "0.35.1"
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description = "Music Theory for Humans"
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readme = "README.md"
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license = "MIT"
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@@ -1,6 +1,6 @@
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"""PyTheory: Music Theory for Humans."""
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__version__ = "0.35.0"
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__version__ = "0.35.1"
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from .tones import Tone, Interval
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from .systems import System, SYSTEMS, TET
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+231
-2
@@ -909,6 +909,227 @@ def saxophone_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
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return (peak * wave).astype(numpy.int16)
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def vocal_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE, lyric="ah"):
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"""Vocal/formant synthesis — sings vowel sounds at a given pitch.
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Models the human voice with:
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1. LF glottal model — asymmetric pulse with sharp closure (not just sines)
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2. 5 parallel resonant formant filters (real voice has 5 formant peaks)
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3. Jitter + shimmer (natural pitch/amplitude irregularity)
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4. Aspiration noise mixed with the glottal source
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5. Consonant onsets (plosives, sibilants, nasals, etc.)
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"""
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import scipy.signal as _sig
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# 5-formant table: (F1, F2, F3, F4, F5) frequencies and bandwidths
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# Based on Peterson & Barney (1952) measurements, male voice
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FORMANTS = {
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'a': [(800, 130), (1200, 100), (2500, 140), (3300, 250), (3750, 300)],
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'e': [(530, 80), (1850, 100), (2500, 130), (3300, 250), (3750, 300)],
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'i': [(280, 60), (2250, 100), (2900, 120), (3350, 250), (3750, 300)],
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'o': [(500, 100), (1000, 80), (2500, 140), (3300, 250), (3750, 300)],
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'u': ((325, 70), (700, 60), (2530, 140), (3300, 250), (3750, 300)),
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}
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# Formant gains (relative amplitude per formant)
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FGAINS = [1.0, 0.8, 0.5, 0.25, 0.15]
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rng = numpy.random.default_rng(int(hz * 100 + len(lyric) * 7) % 2**31)
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t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
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# Parse vowels from lyric
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vowels_in_lyric = [c.lower() for c in lyric if c.lower() in FORMANTS]
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if not vowels_in_lyric:
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vowels_in_lyric = ['a']
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# ── Glottal source: LF model approximation ──
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# Asymmetric pulse: slow open phase, sharp closure, then closed phase.
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# Much more "voice-like" than a sine or sawtooth.
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# Jitter (pitch irregularity) + shimmer (amplitude irregularity)
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jitter = rng.normal(0, hz * 0.001, n_samples) # ~0.1% pitch jitter
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shimmer = 1.0 + rng.normal(0, 0.008, n_samples) # ~0.8% amp shimmer
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# Vibrato
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vib = hz * 0.001 * numpy.sin(2 * numpy.pi * 5.5 * t)
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inst_freq = hz + vib + jitter
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phase = numpy.cumsum(2 * numpy.pi * inst_freq / SAMPLE_RATE)
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# LF glottal shape: sharper falling edge via phase shaping
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saw = (phase / (2 * numpy.pi)) % 1.0 # 0 to 1 sawtooth
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# Asymmetric: slow rise (60%), fast fall (40%)
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glottal = numpy.where(saw < 0.6,
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numpy.sin(numpy.pi * saw / 0.6), # smooth rise
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-numpy.sin(numpy.pi * (saw - 0.6) / 0.4) * 0.8) # sharp fall
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glottal *= shimmer
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# Aspiration noise (breathiness) — subtle
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breath = rng.normal(0, 0.04, n_samples)
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source = glottal * 0.92 + breath * 0.08
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# ── Formant filtering ──
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n_vowels = len(vowels_in_lyric)
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out = numpy.zeros(n_samples, dtype=numpy.float64)
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if n_vowels == 1:
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# Single vowel — filter the whole thing
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formants = FORMANTS[vowels_in_lyric[0]]
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for (fc, bw), gain in zip(formants, FGAINS):
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lo = max(20, fc - bw)
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hi = min(SAMPLE_RATE // 2 - 1, fc + bw)
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if lo < hi:
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bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
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out += _sig.lfilter(bp, ap, source).astype(numpy.float64) * gain
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else:
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# Multiple vowels — crossfade formants
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samples_per_vowel = n_samples // n_vowels
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for vi, vowel in enumerate(vowels_in_lyric):
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formants = FORMANTS[vowel]
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start = vi * samples_per_vowel
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end = n_samples if vi == n_vowels - 1 else start + samples_per_vowel
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seg = source[start:end].copy()
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seg_out = numpy.zeros_like(seg)
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for (fc, bw), gain in zip(formants, FGAINS):
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lo = max(20, fc - bw)
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hi = min(SAMPLE_RATE // 2 - 1, fc + bw)
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if lo < hi:
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bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
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seg_out += _sig.lfilter(bp, ap, seg).astype(numpy.float64) * gain
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# Crossfade
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fade = min(int(SAMPLE_RATE * 0.02), len(seg_out) // 4)
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if vi > 0 and fade > 0:
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seg_out[:fade] *= numpy.linspace(0, 1, fade)
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if vi < n_vowels - 1 and fade > 0:
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seg_out[-fade:] *= numpy.linspace(1, 0, fade)
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out[start:end] += seg_out[:end - start]
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# ── Consonant onsets ──
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lyric_lower = lyric.lower()
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if lyric_lower and lyric_lower[0] not in 'aeiou':
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c = lyric_lower[0]
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cl = min(int(SAMPLE_RATE * 0.035), n_samples)
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if c in 'tdkpb':
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burst = rng.uniform(-0.5, 0.5, cl) * numpy.exp(-numpy.linspace(0, 18, cl))
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out[:cl] = burst + out[:cl] * 0.2
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elif c in 'sz':
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sib = rng.uniform(-0.4, 0.4, cl)
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if cl > 20:
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bl, al = _sig.butter(2, [3000, min(8000, SAMPLE_RATE//2-1)], btype='band', fs=SAMPLE_RATE)
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sib = _sig.lfilter(bl, al, numpy.pad(sib, (0, max(0, n_samples-cl))))[:cl]
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sib *= numpy.exp(-numpy.linspace(0, 10, cl))
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out[:cl] = sib * 0.6 + out[:cl] * 0.4
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elif c in 'mn':
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nl = min(int(SAMPLE_RATE * 0.06), n_samples)
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nasal = numpy.sin(2*numpy.pi*250*t[:nl]) * 0.4 * numpy.exp(-numpy.linspace(0, 4, nl))
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out[:nl] = nasal + out[:nl] * 0.4
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elif c in 'fv':
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fric = rng.uniform(-0.25, 0.25, cl) * numpy.exp(-numpy.linspace(0, 12, cl))
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out[:cl] = fric * 0.5 + out[:cl] * 0.5
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elif c in 'lr':
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gl = min(int(SAMPLE_RATE * 0.05), n_samples)
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ghz = hz * 0.7 + hz * 0.3 * numpy.linspace(0, 1, gl)
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glide = numpy.sin(numpy.cumsum(2*numpy.pi*ghz/SAMPLE_RATE)) * 0.35
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out[:gl] = glide + out[:gl] * 0.65
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elif c == 'h':
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hl = min(int(SAMPLE_RATE * 0.05), n_samples)
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asp = rng.uniform(-0.4, 0.4, hl) * numpy.exp(-numpy.linspace(0, 5, hl))
|
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out[:hl] = asp * 0.6 + out[:hl] * 0.4
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elif c == 'w':
|
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wl = min(int(SAMPLE_RATE * 0.06), n_samples)
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ws = numpy.sin(numpy.cumsum(2*numpy.pi*hz/SAMPLE_RATE*numpy.ones(wl)))
|
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if wl > 20:
|
||||
bp, ap = _sig.butter(2, [max(20,300), min(800, SAMPLE_RATE//2-1)], btype='band', fs=SAMPLE_RATE)
|
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ws = _sig.lfilter(bp, ap, ws)
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ws *= numpy.linspace(0.5, 0, wl)
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out[:wl] = ws * 0.4 + out[:wl] * 0.6
|
||||
|
||||
# Soft edges — prevent clicks at note boundaries
|
||||
fade_samples = min(int(SAMPLE_RATE * 0.01), n_samples // 4)
|
||||
if fade_samples > 0:
|
||||
out[:fade_samples] *= numpy.linspace(0, 1, fade_samples)
|
||||
out[-fade_samples:] *= numpy.linspace(1, 0, fade_samples)
|
||||
|
||||
mx = numpy.abs(out).max()
|
||||
if mx > 0:
|
||||
out /= mx
|
||||
|
||||
return (peak * out).astype(numpy.int16)
|
||||
|
||||
|
||||
def granular_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE,
|
||||
grain_size=0.04, density=50, scatter=0.5,
|
||||
pitch_var=12, source="saw"):
|
||||
"""Granular synthesis — clouds of tiny sound grains.
|
||||
|
||||
Chops a source waveform into overlapping micro-grains (10-200ms),
|
||||
each independently windowed and optionally pitch/time scattered.
|
||||
Creates textures impossible with other synthesis: frozen tones,
|
||||
shimmering clouds, evolving pads, glitchy stutters.
|
||||
|
||||
Args:
|
||||
hz: Base frequency.
|
||||
grain_size: Duration of each grain in seconds (default 0.05 = 50ms).
|
||||
density: Grains per second (default 20). Higher = denser cloud.
|
||||
scatter: Random position jitter 0-1 (default 0.3). How much each
|
||||
grain's read position varies from sequential order.
|
||||
pitch_var: Random pitch variation per grain in cents (default 5).
|
||||
source: Base waveform — ``"saw"``, ``"sine"``, ``"triangle"``,
|
||||
``"square"``, ``"noise"`` (default ``"saw"``).
|
||||
"""
|
||||
rng = numpy.random.default_rng(int(hz * 100) % 2**31)
|
||||
|
||||
# Generate source material — longer than needed for scatter headroom
|
||||
src_len = n_samples + int(SAMPLE_RATE * scatter * 2)
|
||||
src_fns = {
|
||||
"saw": sawtooth_wave, "sine": sine_wave, "triangle": triangle_wave,
|
||||
"square": square_wave, "noise": noise_wave,
|
||||
}
|
||||
src_fn = src_fns.get(source, sawtooth_wave)
|
||||
src = src_fn(hz, n_samples=src_len).astype(numpy.float64) / SAMPLE_PEAK
|
||||
|
||||
# Grain parameters
|
||||
grain_samples = max(64, int(grain_size * SAMPLE_RATE))
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||||
n_grains = max(1, int(n_samples / SAMPLE_RATE * density))
|
||||
|
||||
# Hanning window for each grain (smooth fade in/out, no clicks)
|
||||
window = numpy.hanning(grain_samples).astype(numpy.float64)
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||||
|
||||
out = numpy.zeros(n_samples, dtype=numpy.float64)
|
||||
|
||||
for i in range(n_grains):
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||||
# Output position — evenly spaced with jitter
|
||||
base_pos = int(i * n_samples / n_grains)
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||||
jitter = int(rng.uniform(-0.5, 0.5) * n_samples / n_grains * 0.3)
|
||||
out_pos = max(0, min(n_samples - grain_samples, base_pos + jitter))
|
||||
|
||||
# Source read position — sequential with scatter
|
||||
src_pos = int(base_pos * src_len / n_samples)
|
||||
src_jitter = int(rng.uniform(-scatter, scatter) * grain_samples * 4)
|
||||
src_pos = max(0, min(src_len - grain_samples, src_pos + src_jitter))
|
||||
|
||||
# Per-grain pitch variation via resampling
|
||||
if pitch_var > 0:
|
||||
cents = rng.uniform(-pitch_var, pitch_var)
|
||||
rate = 2 ** (cents / 1200)
|
||||
read_len = max(2, min(int(grain_samples * rate), src_len - src_pos))
|
||||
grain_src = src[src_pos:src_pos + read_len]
|
||||
x_old = numpy.linspace(0, 1, len(grain_src))
|
||||
x_new = numpy.linspace(0, 1, grain_samples)
|
||||
grain = numpy.interp(x_new, x_old, grain_src)
|
||||
else:
|
||||
end = min(src_pos + grain_samples, src_len)
|
||||
grain = src[src_pos:end]
|
||||
if len(grain) < grain_samples:
|
||||
grain = numpy.pad(grain, (0, grain_samples - len(grain)))
|
||||
|
||||
# Apply window and mix
|
||||
grain *= window[:len(grain)]
|
||||
end = min(out_pos + len(grain), n_samples)
|
||||
out[out_pos:end] += grain[:end - out_pos]
|
||||
|
||||
mx = numpy.abs(out).max()
|
||||
if mx > 0:
|
||||
out /= mx
|
||||
|
||||
return (peak * out).astype(numpy.int16)
|
||||
|
||||
|
||||
def acoustic_guitar_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
|
||||
"""Acoustic guitar — Karplus-Strong with wooden body resonance.
|
||||
|
||||
@@ -1211,6 +1432,8 @@ class Synth(Enum):
|
||||
UPRIGHT_BASS = "upright_bass_synth"
|
||||
TIMPANI = "timpani_synth"
|
||||
SAXOPHONE = "saxophone_synth"
|
||||
GRANULAR = "granular_synth"
|
||||
VOCAL = "vocal_synth"
|
||||
ACOUSTIC_GUITAR = "acoustic_guitar_synth"
|
||||
SITAR = "sitar_synth"
|
||||
ELECTRIC_GUITAR = "electric_guitar_synth"
|
||||
@@ -1233,6 +1456,7 @@ _SYNTH_FUNCTIONS = {
|
||||
"harpsichord_synth": harpsichord_wave, "cello_synth": cello_wave,
|
||||
"harp_synth": harp_wave, "upright_bass_synth": upright_bass_wave,
|
||||
"timpani_synth": timpani_wave, "saxophone_synth": saxophone_wave,
|
||||
"granular_synth": granular_wave, "vocal_synth": vocal_wave,
|
||||
"acoustic_guitar_synth": acoustic_guitar_wave,
|
||||
"sitar_synth": sitar_wave, "electric_guitar_synth": electric_guitar_wave,
|
||||
}
|
||||
@@ -3448,8 +3672,13 @@ def _render_notes_to_buf(notes, buf, samples_per_beat, total_samples,
|
||||
bent = src_f[idx] * (1 - frac) + src_f[numpy.minimum(idx + 1, src_len - 1)] * frac
|
||||
waves.append((bent * SAMPLE_PEAK).astype(numpy.int16))
|
||||
else:
|
||||
# Render oscillators (pass synth_kwargs for FM etc.)
|
||||
waves = [synth_fn(hz, n_samples=n_samples, **_skw)
|
||||
# Per-note kwargs (e.g. lyric for vocal synth)
|
||||
note_skw = dict(_skw)
|
||||
note_lyric = getattr(note, 'lyric', '')
|
||||
if note_lyric:
|
||||
note_skw['lyric'] = note_lyric
|
||||
# Render oscillators
|
||||
waves = [synth_fn(hz, n_samples=n_samples, **note_skw)
|
||||
for hz in pitches]
|
||||
# Sub-oscillator: octave-below sine
|
||||
if sub_osc > 0:
|
||||
|
||||
+23
-2
@@ -241,6 +241,26 @@ INSTRUMENTS = {
|
||||
"vel_to_filter": 3000,
|
||||
"analog": 0.3,
|
||||
},
|
||||
"granular_pad": {
|
||||
"synth": "granular_synth", "envelope": "pad",
|
||||
"reverb": 0.4, "reverb_type": "cathedral",
|
||||
"analog": 0.3,
|
||||
},
|
||||
"vocal": {
|
||||
"synth": "vocal_synth", "envelope": "strings",
|
||||
"reverb": 0.3, "reverb_type": "hall",
|
||||
"humanize": 0.15,
|
||||
},
|
||||
"choir": {
|
||||
"synth": "vocal_synth", "envelope": "pad",
|
||||
"detune": 8, "spread": 0.4,
|
||||
"reverb": 0.45, "reverb_type": "cathedral",
|
||||
},
|
||||
"granular_texture": {
|
||||
"synth": "granular_synth", "envelope": "none",
|
||||
"reverb": 0.5, "reverb_type": "taj_mahal",
|
||||
"delay": 0.3, "delay_time": 0.4, "delay_feedback": 0.4,
|
||||
},
|
||||
"808_bass": {
|
||||
"synth": "sine", "envelope": "pluck",
|
||||
"distortion": 0.4, "distortion_drive": 2.5,
|
||||
@@ -357,6 +377,7 @@ class Note:
|
||||
velocity: int = 100
|
||||
bend: float = 0.0
|
||||
bend_type: str = "smooth" # "smooth" (log), "linear", "late"
|
||||
lyric: str = "" # syllable for vocal synth
|
||||
|
||||
@property
|
||||
def beats(self) -> float:
|
||||
@@ -2085,7 +2106,7 @@ class Part:
|
||||
self._automation: list[tuple[float, dict]] = [] # (beat, {param: value})
|
||||
|
||||
def add(self, tone_or_string, duration=Duration.QUARTER, *, velocity: int = 100,
|
||||
bend: float = 0.0, bend_type: str = "smooth") -> "Part":
|
||||
bend: float = 0.0, bend_type: str = "smooth", lyric: str = "") -> "Part":
|
||||
"""Add a note. Accepts Tone/Chord objects or note strings like ``"E5"``.
|
||||
|
||||
Duration can be a ``Duration`` enum or a raw float (beats).
|
||||
@@ -2103,7 +2124,7 @@ class Part:
|
||||
duration = _RawDuration(duration)
|
||||
self.notes.append(Note(tone=tone_or_string, duration=duration,
|
||||
velocity=velocity, bend=bend,
|
||||
bend_type=bend_type))
|
||||
bend_type=bend_type, lyric=lyric))
|
||||
return self
|
||||
|
||||
def set(self, **params) -> "Part":
|
||||
|
||||
+1
-1
@@ -5320,7 +5320,7 @@ def test_supersaw_wave():
|
||||
@needs_portaudio
|
||||
def test_all_synths_in_enum():
|
||||
from pytheory.play import Synth
|
||||
assert len(Synth) == 29
|
||||
assert len(Synth) == 30
|
||||
for s in Synth:
|
||||
wave = s(440, n_samples=1000)
|
||||
assert len(wave) == 1000
|
||||
|
||||
Reference in New Issue
Block a user