Cleaner vocal synth: less static, click-free note transitions

- Jitter reduced (0.3% → 0.1%), shimmer reduced (2% → 0.8%)
- Breath noise halved (0.08 → 0.04), mix 85/15 → 92/8
- 10ms fade in/out on every vocal note prevents clicks
- Smoother syllable transitions

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

CHANGELOG.md

@@ -2,6 +2,30 @@
 
 All notable changes to PyTheory are documented here.
 
+## 0.35.0
+
+- **8.5x faster import** — dropped pytuning/sympy, lazy-load scipy.
+  `import pytheory` now takes ~50ms instead of ~480ms (#44)
+- **Proper shruti JI ratios** — 22 positions with 5-limit just intonation
+  (pure 3/2 fifths, 5/4 thirds), not 22-TET approximation
+- **Arabic maqam JI ratios** — Zalzalian 11-limit ratios.
+  Mi↓ (the Rast third) is exactly 27/22 from Do
+- **B#/Cb octave boundary fix** — B#4 = C5, Cb4 = B3 (#45)
+- **Int tone names** — `Tone(0, system=TET(22))` works alongside strings.
+  Wrapping: `Tone(22)` → tone 0, octave+1. `System.tone()` convenience.
+- **Timpani synth** — inharmonic membrane modes, felt mallet, copper kettle
+  resonance, cathedral reverb
+- **Saxophone synth** — conical bore, reed buzz, brass body warmth.
+  4 presets: saxophone, alto_sax, tenor_sax, bari_sax
+- **Part.roll()** — rapid repeated notes with velocity ramp for crescendo/
+  decrescendo rolls on any instrument
+- **Vibrato tuning** — all instruments reduced to 0.001 depth for cleaner
+  ensemble sound
+- **Granular synthesis** — grain cloud engine with scatter, pitch
+  variation, and Hanning-windowed grains. Two presets: granular_pad,
+  granular_texture.
+- 30 synth waveforms, 838 tests
+
 ## 0.34.0
 
 - **16 dedicated instrument synths** — physical modeling and specialized

docs/guide/sequencing.rst

@@ -620,6 +620,36 @@ Three bend types:
 - ``"late"`` — holds the starting pitch for 60%, bends in the last 40%.
   The classic blues "curl."
 
+Rolls
+-----
+
+Rapid repeated notes with a velocity ramp — perfect for timpani
+rolls, snare rolls, tremolo on any instrument. The velocity ramps
+from ``velocity_start`` to ``velocity_end`` for crescendo or
+decrescendo effects.
+
+.. code-block:: python
+
+   # Timpani crescendo roll
+   timp = score.part("timp", instrument="timpani")
+   timp.roll("C3", Duration.WHOLE, velocity_start=20, velocity_end=110)
+   timp.add("C3", Duration.HALF, velocity=127)  # big accent
+
+   # Snare roll with 32nd notes
+   snare = score.part("snare", synth="noise", envelope="pluck")
+   snare.roll("C4", Duration.HALF, speed=0.125,
+              velocity_start=40, velocity_end=100)
+
+   # Decrescendo (loud to quiet)
+   timp.roll("G2", Duration.WHOLE, velocity_start=100, velocity_end=30)
+
+Parameters:
+
+- ``velocity_start``: Starting velocity (default 40).
+- ``velocity_end``: Ending velocity (default 100).
+- ``speed``: Note subdivision (default ``Duration.SIXTEENTH``).
+  Use ``0.125`` for 32nd notes, ``Duration.EIGHTH`` for 8th notes.
+
 Tuning Systems
 --------------
 

docs/guide/synths.rst

@@ -1,7 +1,7 @@
 Synthesizers
 ============
 
-PyTheory includes 27 built-in waveforms and 10 ADSR envelope presets.
+PyTheory includes 30 built-in waveforms and 10 ADSR envelope presets.
 Every sound is generated from scratch -- no samples or external audio
 files needed.
 
@@ -390,11 +390,11 @@ Dedicated Instrument Synths
 --------------------------
 
 Beyond the classic and physical modeling waveforms, PyTheory includes
-14 dedicated instrument synths. Each one uses tailored synthesis
+17 dedicated instrument synths. Each one uses tailored synthesis
 techniques -- additive harmonics, formant shaping, body resonance
 modeling, and specialized envelopes -- to capture the character of a
 specific acoustic instrument. These are the waveforms that bring the
-total count to 27.
+total count to 30.
 
 Piano Synth
 ~~~~~~~~~~~
@@ -535,6 +535,58 @@ bridge, producing a shimmering, metallic sustain.
 
    sitar = score.part("sitar", synth="sitar_synth")
 
+Timpani Synth
+~~~~~~~~~~~~~
+
+Large kettle drum with definite pitch. Inharmonic membrane modes
+(1.0, 1.5, 1.99, 2.44), felt mallet attack, copper kettle resonance.
+Use ``Part.roll()`` for crescendo timpani rolls.
+
+.. code-block:: python
+
+   timp = score.part("timp", synth="timpani_synth")
+   timp.roll("C3", Duration.WHOLE, velocity_start=20, velocity_end=110)
+
+Saxophone Synth
+~~~~~~~~~~~~~~~
+
+Single reed through a conical brass bore. All harmonics with strong
+mids, reed buzz, and brass body warmth. Four presets: ``saxophone``,
+``alto_sax``, ``tenor_sax``, ``bari_sax``.
+
+.. code-block:: python
+
+   sax = score.part("sax", instrument="tenor_sax")
+
+Granular Synth
+~~~~~~~~~~~~~~
+
+Grain cloud synthesis — chops a source waveform into tiny overlapping
+grains (10-200ms), each windowed and optionally pitch/time scattered.
+Creates textures impossible with other synthesis: frozen tones,
+shimmering clouds, evolving pads, glitchy stutters.
+
+.. code-block:: python
+
+   # Atmospheric granular pad
+   pad = score.part("pad", instrument="granular_pad")
+
+   # Granular with filter envelope sweep + resonance
+   texture = score.part("texture", synth="granular_synth", envelope="pad",
+                        filter_amount=4000, filter_attack=0.5,
+                        filter_decay=1.5, filter_sustain=0.3,
+                        lowpass=600, lowpass_q=3.0,
+                        reverb=0.5, reverb_type="taj_mahal")
+
+Parameters (passed as synth kwargs):
+
+- ``grain_size``: Duration per grain in seconds (default 0.04).
+- ``density``: Grains per second (default 50). Higher = denser cloud.
+- ``scatter``: Random position jitter 0-1 (default 0.5).
+- ``pitch_var``: Per-grain pitch randomization in cents (default 12).
+- ``source``: Base waveform — ``"saw"``, ``"sine"``, ``"triangle"``,
+  ``"square"``, ``"noise"``.
+
 Analog Oscillator Drift
 ~~~~~~~~~~~~~~~~~~~~~~~~
 

docs/index.rst

@@ -77,7 +77,7 @@ What's Inside
   numbers), scale recommendation, modulation, voice leading
 - **Sequencing** — Score, Parts, arpeggiator, legato/glide, velocity,
   swing, humanize, tempo changes, song sections with repeat
-- **Synthesis** — 27 waveforms (including Karplus-Strong pluck, Hammond organ,
+- **Synthesis** — 30 waveforms (including Karplus-Strong pluck, Hammond organ,
   bowed string, and 14 dedicated instrument synths), 10 envelopes, 40+
   instrument presets, configurable FM, sub-oscillator, noise layer, filter
   envelope, velocity-to-brightness, analog oscillator drift, detune, stereo

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "pytheory"
-version = "0.34.1"
+version = "0.35.1"
 description = "Music Theory for Humans"
 readme = "README.md"
 license = "MIT"
@@ -21,7 +21,6 @@ classifiers = [
     "Programming Language :: Python :: 3.13",
 ]
 dependencies = [
-    "pytuning",
     "numeral",
     "sounddevice",
     "scipy",

pytheory/__init__.py

@@ -1,6 +1,6 @@
 """PyTheory: Music Theory for Humans."""
 
-__version__ = "0.34.1"
+__version__ = "0.35.1"
 
 from .tones import Tone, Interval
 from .systems import System, SYSTEMS, TET

pytheory/_statics.py

@@ -1,4 +1,4 @@
-from pytuning import scales
+import math
 
 REFERENCE_A = 440
 
@@ -6,41 +6,59 @@ REFERENCE_A = 440
 # Scientific pitch notation changes octave at C, not A, so this offset
 # is needed for all octave arithmetic.
 C_INDEX = 3
-def _create_just_intonation_scale(n):
-    """5-limit just intonation ratios for 12-tone systems.
 
-    These are the pure frequency ratios derived from the harmonic series —
-    the way intervals "want" to sound before equal temperament imposed
-    compromise. Each ratio is mathematically exact: a perfect fifth is
-    exactly 3/2, a major third is exactly 5/4.
 
-    For non-12 systems, falls back to equal temperament.
+# ── Temperament scale generators (replaces pytuning dependency) ──────────
+
+def _create_edo_scale(n):
+    """N-tone equal division of the octave. Each step = 2^(1/n)."""
+    return [2 ** (i / n) for i in range(n + 1)]
+
+
+def _create_pythagorean_scale(n):
+    """Pythagorean tuning — spiral of pure fifths (3/2 ratio).
+
+    Each tone is generated by stacking perfect fifths and octave-reducing.
     """
-    from fractions import Fraction
+    ratios = [1.0]
+    for i in range(1, n):
+        # Stack fifths: (3/2)^i, then reduce to within one octave
+        r = (3 / 2) ** i
+        while r >= 2.0:
+            r /= 2.0
+        ratios.append(r)
+    ratios.sort()
+    ratios.append(2.0)
+    return ratios
+
+
+def _create_quarter_comma_meantone_scale(n):
+    """Quarter-comma meantone — pure major thirds (5/4), tempered fifths.
+
+    The fifth is narrowed by 1/4 of a syntonic comma so that four
+    fifths make a pure major third (5/4). The meantone fifth =
+    5^(1/4) ≈ 1.49535.
+    """
+    fifth = 5 ** 0.25  # meantone fifth ≈ 1.49535 (vs 1.5 pure)
+    ratios = [1.0]
+    for i in range(1, n):
+        r = fifth ** i
+        while r >= 2.0:
+            r /= 2.0
+        ratios.append(r)
+    ratios.sort()
+    ratios.append(2.0)
+    return ratios
+def _create_just_intonation_scale(n):
+    """5-limit just intonation ratios for 12-tone systems."""
     if n != 12:
-        return scales.create_edo_scale(n)
-    # Standard 5-limit JI ratios (A-based: A=1/1)
-    ratios = [
-        Fraction(1, 1),       # A  — unison
-        Fraction(16, 15),     # A# — minor second
-        Fraction(9, 8),       # B  — major second
-        Fraction(6, 5),       # C  — minor third
-        Fraction(5, 4),       # C# — major third
-        Fraction(4, 3),       # D  — perfect fourth
-        Fraction(45, 32),     # D# — augmented fourth
-        Fraction(3, 2),       # E  — perfect fifth
-        Fraction(8, 5),       # F  — minor sixth
-        Fraction(5, 3),       # F# — major sixth
-        Fraction(9, 5),       # G  — minor seventh
-        Fraction(15, 8),      # G# — major seventh
-        Fraction(2, 1),       # A  — octave
-    ]
-    return [float(r) for r in ratios]
+        return _create_edo_scale(n)
+    return [1, 16/15, 9/8, 6/5, 5/4, 4/3, 45/32, 3/2, 8/5, 5/3, 9/5, 15/8, 2.0]
 
 TEMPERAMENTS = {
-    "equal": scales.create_edo_scale,
-    "pythagorean": scales.create_pythagorean_scale,
-    "meantone": scales.create_quarter_comma_meantone_scale,
+    "equal": _create_edo_scale,
+    "pythagorean": _create_pythagorean_scale,
+    "meantone": _create_quarter_comma_meantone_scale,
     "just": _create_just_intonation_scale,
 }
 

pytheory/play.py

@@ -2,11 +2,24 @@ from enum import Enum
 import time
 
 import numpy
-import scipy.signal
 
 from .tones import Tone
 
 
+class _LazyModule:
+    """Lazy import wrapper — module loaded on first attribute access."""
+    def __init__(self, name):
+        self._name = name
+        self._mod = None
+    def __getattr__(self, attr):
+        if self._mod is None:
+            import importlib
+            self._mod = importlib.import_module(self._name)
+        return getattr(self._mod, attr)
+
+scipy = type('scipy', (), {'signal': _LazyModule('scipy.signal')})()
+
+
 def _get_sd():
     """Lazy import sounddevice — only needed for actual audio playback."""
     import sounddevice as sd
@@ -257,7 +270,7 @@ def strings_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
 
     # Delayed vibrato: ramps in over ~200ms, like a real bow
     vib_rate = 5.2 + rng.uniform(-0.3, 0.3)  # slight randomness per note
-    vib_depth = hz * 0.003  # ~5 cents
+    vib_depth = hz * 0.001  # subtle
     vib_onset = numpy.clip(t / 0.2, 0.0, 1.0)  # ramp over 200ms
     vibrato = vib_depth * vib_onset * numpy.sin(2 * numpy.pi * vib_rate * t)
 
@@ -481,7 +494,7 @@ def trumpet_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
 
     # Vibrato
     vib_onset = numpy.clip(t / 0.15, 0.0, 1.0)
-    vib = hz * 0.002 * vib_onset * numpy.sin(2 * numpy.pi * 5.5 * t)
+    vib = hz * 0.001 * vib_onset * numpy.sin(2 * numpy.pi * 5.5 * t)
 
     # Lip buzz — additive with brass spectral shape
     # Trumpet has strong even AND odd harmonics (unlike clarinet)
@@ -523,7 +536,7 @@ def clarinet_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
     rng = numpy.random.default_rng(int(hz * 100) % 2**31)
 
     vib_onset = numpy.clip(t / 0.3, 0.0, 1.0)
-    vib = hz * 0.002 * vib_onset * numpy.sin(2 * numpy.pi * 4.5 * t)
+    vib = hz * 0.001 * vib_onset * numpy.sin(2 * numpy.pi * 4.5 * t)
 
     # Cylindrical bore: odd harmonics dominate
     wave = numpy.zeros(n_samples, dtype=numpy.float64)
@@ -592,7 +605,7 @@ def oboe_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
     rng = numpy.random.default_rng(int(hz * 100) % 2**31)
 
     vib_onset = numpy.clip(t / 0.2, 0.0, 1.0)
-    vib = hz * 0.002 * vib_onset * numpy.sin(2 * numpy.pi * 5.0 * t)
+    vib = hz * 0.001 * vib_onset * numpy.sin(2 * numpy.pi * 5.0 * t)
 
     wave = numpy.zeros(n_samples, dtype=numpy.float64)
     n_harmonics = min(18, int((SAMPLE_RATE / 2) / hz))
@@ -668,7 +681,7 @@ def cello_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
 
     # Delayed vibrato
     vib_rate = 5.0 + rng.uniform(-0.3, 0.3)
-    vib_depth = hz * 0.002
+    vib_depth = hz * 0.001
     vib_onset = numpy.clip(t / 0.25, 0.0, 1.0)
     vibrato = vib_depth * vib_onset * numpy.sin(2 * numpy.pi * vib_rate * t)
 
@@ -787,6 +800,336 @@ def upright_bass_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
     return (peak * out).astype(numpy.int16)
 
 
+def timpani_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Timpani — large kettle drum with definite pitch.
+
+    The copper kettle creates a tuned resonance with inharmonic
+    overtones. The head modes are at ratios 1.0, 1.5, 1.99, 2.44
+    (not integer multiples like strings). The felt mallet gives a
+    soft attack with a deep, booming body.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+
+    # Timpani head modes — inharmonic but definite pitch
+    # Mode ratios from vibrating circular membrane physics
+    wave = numpy.sin(2 * numpy.pi * hz * t) * 0.8
+    wave += numpy.sin(2 * numpy.pi * hz * 1.5 * t) * 0.35 * numpy.exp(-6 * t)
+    wave += numpy.sin(2 * numpy.pi * hz * 1.99 * t) * 0.2 * numpy.exp(-10 * t)
+    wave += numpy.sin(2 * numpy.pi * hz * 2.44 * t) * 0.1 * numpy.exp(-15 * t)
+
+    # Two-stage decay: initial thump fades fast, fundamental rings
+    decay = numpy.where(t < 0.15,
+                        numpy.exp(-4 * t),
+                        numpy.exp(-4 * 0.15) * numpy.exp(-1.5 * (t - 0.15)))
+    wave *= decay
+
+    # Felt mallet impact — warm, not sharp
+    mallet_len = min(int(SAMPLE_RATE * 0.02), n_samples)
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+    mallet = rng.uniform(-0.3, 0.3, mallet_len)
+    mallet *= numpy.exp(-numpy.linspace(0, 8, mallet_len))
+    wave[:mallet_len] += mallet
+
+    # Copper kettle resonance — boosts low-mids
+    import scipy.signal as _sig
+    lo, hi = max(20, int(hz * 0.7)), min(SAMPLE_RATE // 2 - 1, int(hz * 2))
+    if lo < hi:
+        bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+        kettle = _sig.lfilter(bp, ap, wave) * 0.3
+        wave += kettle
+
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+
+    return (peak * wave).astype(numpy.int16)
+
+
+def saxophone_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Saxophone — single reed through a conical brass bore.
+
+    The conical bore produces all harmonics (like oboe), but the
+    brass body and larger mouthpiece give a warmer, fatter, more
+    vocal quality. The reed adds a slight buzz. Saxophone is
+    between clarinet (odd harmonics) and oboe (nasal even+odd) —
+    it has everything, with a strong fundamental and rich mids.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+
+    # Vibrato — develops after ~250ms, wider than flute
+    vib_onset = numpy.clip(t / 0.25, 0.0, 1.0)
+    vib = hz * 0.0012 * vib_onset * numpy.sin(2 * numpy.pi * 5.2 * t)
+
+    wave = numpy.zeros(n_samples, dtype=numpy.float64)
+    n_harmonics = min(20, int((SAMPLE_RATE / 2) / hz))
+
+    for n in range(1, n_harmonics + 1):
+        f_n = hz * n
+        if f_n >= SAMPLE_RATE / 2:
+            break
+        # Sax spectral shape: strong fundamental, broad mid peak (3-6),
+        # slower rolloff than oboe (brass body carries harmonics further)
+        if n == 1:
+            amp = 1.0
+        elif n <= 3:
+            amp = 0.6
+        elif n <= 6:
+            amp = 0.4 * numpy.exp(-0.1 * (n - 4) ** 2)
+        else:
+            amp = 0.2 / n
+        phase = rng.uniform(0, 2 * numpy.pi)
+        wave += amp * numpy.sin(2 * numpy.pi * (f_n + vib * n) * t + phase)
+
+    # Reed buzz — more present than oboe but still warm
+    reed = rng.normal(0, 0.07, n_samples)
+    # Bandpass the reed noise around 1-3kHz (the "honk" range)
+    import scipy.signal as _sig
+    reed_lo = max(20, int(hz * 2))
+    reed_hi = min(SAMPLE_RATE // 2 - 1, int(hz * 6))
+    if reed_lo < reed_hi:
+        br, ar = _sig.butter(2, [reed_lo, reed_hi], btype='band', fs=SAMPLE_RATE)
+        reed = _sig.lfilter(br, ar, reed).astype(numpy.float64) * 2.0
+    wave += reed
+
+    # Brass body warmth — low-mid boost
+    center = min(1500, hz * 4)
+    bw = 500
+    lo = max(20, int(center - bw))
+    hi = min(SAMPLE_RATE // 2 - 1, int(center + bw))
+    if lo < hi:
+        bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+        body = _sig.lfilter(bp, ap, wave) * 0.2
+        wave += body
+
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+
+    return (peak * wave).astype(numpy.int16)
+
+
+def vocal_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE, lyric="ah"):
+    """Vocal/formant synthesis — sings vowel sounds at a given pitch.
+
+    Models the human voice with:
+    1. LF glottal model — asymmetric pulse with sharp closure (not just sines)
+    2. 5 parallel resonant formant filters (real voice has 5 formant peaks)
+    3. Jitter + shimmer (natural pitch/amplitude irregularity)
+    4. Aspiration noise mixed with the glottal source
+    5. Consonant onsets (plosives, sibilants, nasals, etc.)
+    """
+    import scipy.signal as _sig
+
+    # 5-formant table: (F1, F2, F3, F4, F5) frequencies and bandwidths
+    # Based on Peterson & Barney (1952) measurements, male voice
+    FORMANTS = {
+        'a': [(800, 130), (1200, 100), (2500, 140), (3300, 250), (3750, 300)],
+        'e': [(530, 80),  (1850, 100), (2500, 130), (3300, 250), (3750, 300)],
+        'i': [(280, 60),  (2250, 100), (2900, 120), (3350, 250), (3750, 300)],
+        'o': [(500, 100), (1000, 80),  (2500, 140), (3300, 250), (3750, 300)],
+        'u': ((325, 70),  (700, 60),   (2530, 140), (3300, 250), (3750, 300)),
+    }
+    # Formant gains (relative amplitude per formant)
+    FGAINS = [1.0, 0.8, 0.5, 0.25, 0.15]
+
+    rng = numpy.random.default_rng(int(hz * 100 + len(lyric) * 7) % 2**31)
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+
+    # Parse vowels from lyric
+    vowels_in_lyric = [c.lower() for c in lyric if c.lower() in FORMANTS]
+    if not vowels_in_lyric:
+        vowels_in_lyric = ['a']
+
+    # ── Glottal source: LF model approximation ──
+    # Asymmetric pulse: slow open phase, sharp closure, then closed phase.
+    # Much more "voice-like" than a sine or sawtooth.
+    # Jitter (pitch irregularity) + shimmer (amplitude irregularity)
+    jitter = rng.normal(0, hz * 0.001, n_samples)  # ~0.1% pitch jitter
+    shimmer = 1.0 + rng.normal(0, 0.008, n_samples)  # ~0.8% amp shimmer
+    # Vibrato
+    vib = hz * 0.001 * numpy.sin(2 * numpy.pi * 5.5 * t)
+    inst_freq = hz + vib + jitter
+    phase = numpy.cumsum(2 * numpy.pi * inst_freq / SAMPLE_RATE)
+    # LF glottal shape: sharper falling edge via phase shaping
+    saw = (phase / (2 * numpy.pi)) % 1.0  # 0 to 1 sawtooth
+    # Asymmetric: slow rise (60%), fast fall (40%)
+    glottal = numpy.where(saw < 0.6,
+                          numpy.sin(numpy.pi * saw / 0.6),   # smooth rise
+                          -numpy.sin(numpy.pi * (saw - 0.6) / 0.4) * 0.8)  # sharp fall
+    glottal *= shimmer
+
+    # Aspiration noise (breathiness) — subtle
+    breath = rng.normal(0, 0.04, n_samples)
+    source = glottal * 0.92 + breath * 0.08
+
+    # ── Formant filtering ──
+    n_vowels = len(vowels_in_lyric)
+    out = numpy.zeros(n_samples, dtype=numpy.float64)
+
+    if n_vowels == 1:
+        # Single vowel — filter the whole thing
+        formants = FORMANTS[vowels_in_lyric[0]]
+        for (fc, bw), gain in zip(formants, FGAINS):
+            lo = max(20, fc - bw)
+            hi = min(SAMPLE_RATE // 2 - 1, fc + bw)
+            if lo < hi:
+                bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+                out += _sig.lfilter(bp, ap, source).astype(numpy.float64) * gain
+    else:
+        # Multiple vowels — crossfade formants
+        samples_per_vowel = n_samples // n_vowels
+        for vi, vowel in enumerate(vowels_in_lyric):
+            formants = FORMANTS[vowel]
+            start = vi * samples_per_vowel
+            end = n_samples if vi == n_vowels - 1 else start + samples_per_vowel
+            seg = source[start:end].copy()
+            seg_out = numpy.zeros_like(seg)
+            for (fc, bw), gain in zip(formants, FGAINS):
+                lo = max(20, fc - bw)
+                hi = min(SAMPLE_RATE // 2 - 1, fc + bw)
+                if lo < hi:
+                    bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+                    seg_out += _sig.lfilter(bp, ap, seg).astype(numpy.float64) * gain
+            # Crossfade
+            fade = min(int(SAMPLE_RATE * 0.02), len(seg_out) // 4)
+            if vi > 0 and fade > 0:
+                seg_out[:fade] *= numpy.linspace(0, 1, fade)
+            if vi < n_vowels - 1 and fade > 0:
+                seg_out[-fade:] *= numpy.linspace(1, 0, fade)
+            out[start:end] += seg_out[:end - start]
+
+    # ── Consonant onsets ──
+    lyric_lower = lyric.lower()
+    if lyric_lower and lyric_lower[0] not in 'aeiou':
+        c = lyric_lower[0]
+        cl = min(int(SAMPLE_RATE * 0.035), n_samples)
+        if c in 'tdkpb':
+            burst = rng.uniform(-0.5, 0.5, cl) * numpy.exp(-numpy.linspace(0, 18, cl))
+            out[:cl] = burst + out[:cl] * 0.2
+        elif c in 'sz':
+            sib = rng.uniform(-0.4, 0.4, cl)
+            if cl > 20:
+                bl, al = _sig.butter(2, [3000, min(8000, SAMPLE_RATE//2-1)], btype='band', fs=SAMPLE_RATE)
+                sib = _sig.lfilter(bl, al, numpy.pad(sib, (0, max(0, n_samples-cl))))[:cl]
+            sib *= numpy.exp(-numpy.linspace(0, 10, cl))
+            out[:cl] = sib * 0.6 + out[:cl] * 0.4
+        elif c in 'mn':
+            nl = min(int(SAMPLE_RATE * 0.06), n_samples)
+            nasal = numpy.sin(2*numpy.pi*250*t[:nl]) * 0.4 * numpy.exp(-numpy.linspace(0, 4, nl))
+            out[:nl] = nasal + out[:nl] * 0.4
+        elif c in 'fv':
+            fric = rng.uniform(-0.25, 0.25, cl) * numpy.exp(-numpy.linspace(0, 12, cl))
+            out[:cl] = fric * 0.5 + out[:cl] * 0.5
+        elif c in 'lr':
+            gl = min(int(SAMPLE_RATE * 0.05), n_samples)
+            ghz = hz * 0.7 + hz * 0.3 * numpy.linspace(0, 1, gl)
+            glide = numpy.sin(numpy.cumsum(2*numpy.pi*ghz/SAMPLE_RATE)) * 0.35
+            out[:gl] = glide + out[:gl] * 0.65
+        elif c == 'h':
+            hl = min(int(SAMPLE_RATE * 0.05), n_samples)
+            asp = rng.uniform(-0.4, 0.4, hl) * numpy.exp(-numpy.linspace(0, 5, hl))
+            out[:hl] = asp * 0.6 + out[:hl] * 0.4
+        elif c == 'w':
+            wl = min(int(SAMPLE_RATE * 0.06), n_samples)
+            ws = numpy.sin(numpy.cumsum(2*numpy.pi*hz/SAMPLE_RATE*numpy.ones(wl)))
+            if wl > 20:
+                bp, ap = _sig.butter(2, [max(20,300), min(800, SAMPLE_RATE//2-1)], btype='band', fs=SAMPLE_RATE)
+                ws = _sig.lfilter(bp, ap, ws)
+            ws *= numpy.linspace(0.5, 0, wl)
+            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))
+    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)
+
+    out = numpy.zeros(n_samples, dtype=numpy.float64)
+
+    for i in range(n_grains):
+        # Output position — evenly spaced with jitter
+        base_pos = int(i * n_samples / n_grains)
+        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.
 
@@ -1087,6 +1430,10 @@ class Synth(Enum):
     CELLO = "cello_synth"
     HARP = "harp_synth"
     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"
@@ -1108,6 +1455,8 @@ _SYNTH_FUNCTIONS = {
     "marimba_synth": marimba_wave, "oboe_synth": oboe_wave,
     "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,
 }
@@ -3323,8 +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:

pytheory/rhythm.py

@@ -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,
@@ -275,6 +295,31 @@ INSTRUMENTS = {
         "fm_ratio": 2.0, "fm_index": 3.0,
         "reverb": 0.4, "reverb_type": "cathedral",
     },
+    "timpani": {
+        "synth": "timpani_synth", "envelope": "none",
+        "reverb": 0.4, "reverb_type": "cathedral",
+    },
+
+    # ── Woodwinds (continued) ──
+    "saxophone": {
+        "synth": "saxophone_synth", "envelope": "bowed",
+        "humanize": 0.15, "vel_to_filter": 1500,
+    },
+    "alto_sax": {
+        "synth": "saxophone_synth", "envelope": "bowed",
+        "humanize": 0.15, "vel_to_filter": 1800,
+    },
+    "tenor_sax": {
+        "synth": "saxophone_synth", "envelope": "bowed",
+        "lowpass": 3000,
+        "humanize": 0.15, "vel_to_filter": 1200,
+    },
+    "bari_sax": {
+        "synth": "saxophone_synth", "envelope": "bowed",
+        "lowpass": 2000,
+        "humanize": 0.15, "vel_to_filter": 800,
+        "sub_osc": 0.15,
+    },
 }
 
 
@@ -332,6 +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:
@@ -2060,7 +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).
@@ -2078,7 +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":
@@ -2435,6 +2481,50 @@ class Part:
 
         return self
 
+    def roll(self, tone_or_string, duration=Duration.WHOLE, *,
+             velocity_start: int = 40, velocity_end: int = 100,
+             speed=Duration.SIXTEENTH) -> "Part":
+        """Play a roll — rapid repeated notes with velocity ramp.
+
+        Perfect for timpani rolls, snare rolls, tremolo on any
+        instrument. The velocity ramps from ``velocity_start`` to
+        ``velocity_end`` over the duration for crescendo/decrescendo.
+
+        Args:
+            tone_or_string: The note to repeat.
+            duration: Total duration of the roll.
+            velocity_start: Velocity of the first hit (default 40).
+            velocity_end: Velocity of the last hit (default 100).
+            speed: How fast to repeat (default SIXTEENTH notes).
+
+        Returns:
+            Self for chaining.
+
+        Example::
+
+            >>> timp = score.part("timp", instrument="timpani")
+            >>> timp.roll("C3", Duration.WHOLE, velocity_start=30, velocity_end=110)
+        """
+        if hasattr(duration, 'value'):
+            total = duration.value
+        else:
+            total = float(duration)
+        if hasattr(speed, 'value'):
+            step = speed.value
+        else:
+            step = float(speed)
+
+        n_hits = max(1, int(total / step))
+        for i in range(n_hits):
+            frac = i / max(1, n_hits - 1)
+            vel = int(velocity_start + (velocity_end - velocity_start) * frac)
+            vel = max(1, min(127, vel))
+            remaining = total - i * step
+            note_dur = min(step, remaining)
+            if note_dur > 0:
+                self.add(tone_or_string, note_dur, velocity=vel)
+        return self
+
     @property
     def is_drums(self) -> bool:
         """True if this part contains drum hits."""

pytheory/tones.py

@@ -816,8 +816,7 @@ class Tone:
             pitch_scale = list(custom_ratios) + [period]
         elif period != 2.0 and temperament == "equal":
             # Non-octave period (e.g. Bohlen-Pierce tritave=3.0)
-            import sympy
-            pitch_scale = [period ** sympy.Rational(i, tones) for i in range(tones + 1)]
+            pitch_scale = [period ** (i / tones) for i in range(tones + 1)]
         else:
             pitch_scale = TEMPERAMENTS[temperament](tones)
         octave = self.octave if self.octave is not None else 4
@@ -834,7 +833,7 @@ class Tone:
         if symbolic:
             return reference_pitch * ratio
         else:
-            result = reference_pitch * ratio
+            result = float(reference_pitch * ratio)
             if precision:
-                return float(result.evalf(precision))
-            return float(result)
+                return round(result, precision)
+            return result

test_pytheory.py

@@ -5320,7 +5320,7 @@ def test_supersaw_wave():
 @needs_portaudio
 def test_all_synths_in_enum():
     from pytheory.play import Synth
-    assert len(Synth) == 27
+    assert len(Synth) == 30
     for s in Synth:
         wave = s(440, n_samples=1000)
         assert len(wave) == 1000

uv.lock

@@ -444,15 +444,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979, upload-time = "2022-08-14T12:40:09.779Z" },
 ]
 
-[[package]]
-name = "mpmath"
-version = "1.3.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/e0/47/dd32fa426cc72114383ac549964eecb20ecfd886d1e5ccf5340b55b02f57/mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f", size = 508106, upload-time = "2023-03-07T16:47:11.061Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c", size = 536198, upload-time = "2023-03-07T16:47:09.197Z" },
-]
-
 [[package]]
 name = "myst-parser"
 version = "4.0.1"
@@ -707,11 +698,10 @@ wheels = [
 
 [[package]]
 name = "pytheory"
-version = "0.34.1"
+version = "0.35.1"
 source = { editable = "." }
 dependencies = [
     { name = "numeral" },
-    { name = "pytuning" },
     { name = "scipy", version = "1.15.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
     { name = "scipy", version = "1.17.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
     { name = "sounddevice" },
@@ -732,7 +722,6 @@ docs = [
 [package.metadata]
 requires-dist = [
     { name = "numeral" },
-    { name = "pytuning" },
     { name = "scipy" },
     { name = "sounddevice" },
 ]
@@ -744,19 +733,6 @@ docs = [
     { name = "sphinx" },
 ]
 
-[[package]]
-name = "pytuning"
-version = "0.7.3"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
-    { name = "numpy", version = "2.4.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
-    { name = "sympy" },
-]
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/26/59/e2c2fc91688f788587fb387ef6120c9a1ad3a8b88771fba9fc6a9c9a969d/PyTuning-0.7.3-py3-none-any.whl", hash = "sha256:db0b1231c012c1cf6a3c73aa7d791b4cff79a72f2ec6535f159c873fe302214b", size = 108174, upload-time = "2023-09-02T21:11:00.657Z" },
-]
-
 [[package]]
 name = "pyyaml"
 version = "6.0.3"
@@ -1151,18 +1127,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/52/a7/d2782e4e3f77c8450f727ba74a8f12756d5ba823d81b941f1b04da9d033a/sphinxcontrib_serializinghtml-2.0.0-py3-none-any.whl", hash = "sha256:6e2cb0eef194e10c27ec0023bfeb25badbbb5868244cf5bc5bdc04e4464bf331", size = 92072, upload-time = "2024-07-29T01:10:08.203Z" },
 ]
 
-[[package]]
-name = "sympy"
-version = "1.14.0"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "mpmath" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/83/d3/803453b36afefb7c2bb238361cd4ae6125a569b4db67cd9e79846ba2d68c/sympy-1.14.0.tar.gz", hash = "sha256:d3d3fe8df1e5a0b42f0e7bdf50541697dbe7d23746e894990c030e2b05e72517", size = 7793921, upload-time = "2025-04-27T18:05:01.611Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/a2/09/77d55d46fd61b4a135c444fc97158ef34a095e5681d0a6c10b75bf356191/sympy-1.14.0-py3-none-any.whl", hash = "sha256:e091cc3e99d2141a0ba2847328f5479b05d94a6635cb96148ccb3f34671bd8f5", size = 6299353, upload-time = "2025-04-27T18:04:59.103Z" },
-]
-
 [[package]]
 name = "tomli"
 version = "2.4.0"