diff --git a/README.md b/README.md index 591e121..acd99a9 100644 --- a/README.md +++ b/README.md @@ -4,6 +4,9 @@ [![Tap House Style](https://github.com/tap/TapTools/actions/workflows/style.yml/badge.svg)](https://github.com/tap/TapTools/actions/workflows/style.yml) [![Docs](https://github.com/tap/TapTools/actions/workflows/docs.yml/badge.svg)](https://github.com/tap/TapTools/actions/workflows/docs.yml) +**๐Ÿ“– [*Tools on Tap*](https://timothy.place/TapTools/)** โ€” the field guide to these kernels, +one measured chapter per object family โ€” is published from this repo on every merge. + The portable DSP library behind the TapTools Max package: header-only, plain C++20, **no Max SDK, no min-api, no Jamoma**. One self-contained header per object under `include/taptools/`, each in its own `tap::tools::` namespace. The TapTools Max externals are thin diff --git a/book/figures/eno.py b/book/figures/eno.py index d70afa3..bc780b8 100644 --- a/book/figures/eno.py +++ b/book/figures/eno.py @@ -132,23 +132,23 @@ def raster(): def staircase(): """garden: the decay-0.5 return staircase, retiring below the floor.""" - g = tap.Garden(fs, smooth_ms=0, idle_seconds=0, loop_seconds=0.5, + g = tap.Garden(fs, smooth_ms=0, idle_seconds=0, spread=0, loop_seconds=0.5, decay=0.5, floor=0.05, bell=(0.002, 0.05, 1.0), scale=0) g.note(69, 0.8) - y = g.process(int(3.5 * fs)) + y, _ = g.process(int(3.5 * fs)) # spread 0: both busses identical, plot the left t = np.arange(y.size) / fs fig, ax = plt.subplots() ax.plot(t, y, color=BLUE, lw=0.5) for k in range(5): - v = 0.8 * 0.5 ** k + v = np.abs(y[int(k * 0.5 * fs): int((k + 1) * 0.5 * fs)]).max() ax.plot([k * 0.5, k * 0.5 + 0.22], [v, v], color=AMBER, lw=1.6) - ax.text(k * 0.5 + 0.24, v, f"{v:g}", color=AMBER, va="center", fontsize=8.5) + ax.text(k * 0.5 + 0.24, v, f"{v:.2f}", color=AMBER, va="center", fontsize=8.5) ax.axhline(0.05, color=RED, lw=0.9, ls=":") ax.text(3.44, 0.075, "floor 0.05 โ€” retirement", color=RED, ha="right", fontsize=8.5) ax.set_xlabel("time (s)") ax.set_ylabel("output") - ax.set_title("decay 0.5: each return half as loud, then the bloom retires") + ax.set_title("decay 0.5: each return half the previous peak, then the bloom retires") fig.savefig(out_dir("garden") / "staircase.svg", bbox_inches="tight") plt.close(fig) diff --git a/book/src/garden.md b/book/src/garden.md index 873d5d7..e4ddf7c 100644 --- a/book/src/garden.md +++ b/book/src/garden.md @@ -25,19 +25,22 @@ every claim below, and the `eno_render` tool's `garden_played` and `garden_idle` scenarios, the listening copies. The Max wrapper lands in the TapTools-Max package alongside the rest of the family. -![Signal-flow diagram of tap.garden~: notes through a scale quantizer into a 64-event ring, fired at their loop positions into a 16-voice FM bell pool, with a red per-pass path multiplying velocity by decay and brightness by soften back into the ring, and a dashed seeded gardener planting into the ring](images/garden/block-diagram.svg) +![Signal-flow diagram of tap.garden~: notes through a scale quantizer into a 64-event ring, fired at their loop positions into a 16-voice wind-chime pool that sums onto a stereo pair, with a red per-pass path multiplying velocity by decay and brightness by soften back into the ring, and a dashed seeded gardener planting into the ring](images/garden/block-diagram.svg) *Events on a loop instead of audio on a tape โ€” the same recirculation, one level of abstraction up.* ## Plant and return `note(pitch, velocity)` plants: the pitch snaps to the current root and -scale *at entry*, a soft two-operator FM bell sounds on the next sample, +scale *at entry*, a small wind chime is struck on the next sample, and the event takes a seat at the loop's current position. Every pass, it fires again at `velocity ร— decay`, and below `floor` it retires. The notebook's staircase is the whole contract in one figure: a plant at 0.8 -with decay 0.5 returns at 0.795, 0.399, 0.2, 0.1, 0.05 โ€” then silence, and -`active_events` reads zero. +with decay 0.5 returns with its fundamental at exactly half the last, four +times over (measured ratios 0.500, 0.500, 0.500, 0.500), then silence, and +`active_events` reads zero. The whole strike fades a shade faster than its +fundamental โ€” quieter returns are also duller, because strike hardness +couples brightness to velocity. ![A rendered waveform showing five returns of one planted note, each half the height of the last, with the measured peak levels labeled and the retirement floor marked](images/garden/staircase.svg) @@ -47,18 +50,48 @@ That arithmetic is also the stability story. The family's inversion โ€” degradation as the stabilizer โ€” reaches its third form here: a bloom lives exactly `ceil(log(floor/velocity) / log(decay))` passes, so the population of live events *converges by construction* no matter how fast you plant. -And beneath the arithmetic sits a hard bound: sixteen bells in a fixed -pool, the quietest stolen when a seventeenth is needed, its envelope +And beneath the arithmetic sits a hard bound: sixteen chimes in a fixed +pool, the quietest stolen when a seventeenth is needed, its envelopes re-aimed rather than reset so a steal glides instead of clicking. ## `soften` โ€” returns get purer, not just quieter -Each pass also multiplies the event's *brightness* by `soften`, and -brightness is the bell's FM index: the upper partial fades while the -fundamental holds, so a bloom collapses toward a sine as it recedes โ€” the -tape chapters' generation loss, restated in partials instead of passbands. -The notebook measures the sideband-to-fundamental ratio shrinking every -single return, and the pinned test requires it strictly. +The chime is four decaying mode *doublets* at the transverse ratios of the +chosen material โ€” by default 1 : 2.756 : 5.404 : 8.933, the free-free-tube +physics in Fletcher & Rossing โ€” with the upper modes softer, steeper in brightness +(b, bยฒ, bยณ), and dying roughly as fยฒ faster, so the fourth mode is the +few-millisecond tick of clapper contact and every strike rings down to its +fundamental. Each mode pair is split a few cents, the way a real tube's +degenerate modes are, so the tail *beats* slowly instead of decaying like a +lab sine. Each pass multiplies the event's *brightness* by `soften`, and +brightness is the upper modes' level: a bloom collapses toward its +fundamental as it recedes, losing its tick first โ€” the tape chapters' +generation loss, restated in modes instead of passbands. The notebook +measures the mode-two-to-fundamental ratio shrinking by exactly `soften` +every single return, and the pinned tests hold each piece separately: the +tick confined to the contact, the tail's beat dipping and returning, soft +strikes duller than hard ones, high tubes ringing shorter than low. + +## The rack: material, flaws, and seats + +`material` swaps what the tubes are made of โ€” a mode, not a fader. At 0 the +rack is wind chimes, the free-free tube's 1 : 2.756 : 5.404 : 8.933; at 1 it +is a tuned bar, the mallet instrument's double-octave 1 : 4 : 10 : 20 (both +tables from Fletcher & Rossing). The table is read at strike time, so every +live bloom re-voices at its next return: the notebook measures the second +partial's energy moving cleanly from 2.756ร— to 4ร— when the material flips. + +And the tube is the identity. Each pitch is a physical tube whose +imperfections are properties of the tube, not the strike: its upper modes +sit a fixed few cents off the ideal ratios (bounded by ยฑ3 cents โ€” the +fundamental stays true, because a maker tunes the fundamental and the +overtones land where the metal puts them), and it hangs at a fixed seat on +the stereo rack, width set by `spread` (0 collapses to center mono, bitwise +identical busses). Both draws come from a stateless hash of the pitch, so +the rack is the same rack in every instance and every return of a bloom +rings from the same place with the same flaws โ€” the notebook's seat chart +is a bar per pitch, and the seed triad below is untouched because no +generator is ever consumed for it. ## The scale contract @@ -74,9 +107,12 @@ seeds only. ## The gardener -`idle_seconds` is the patience: that long after your last plant, the -garden begins seeding itself, roughly one note per loop pass, uniformly -placed, on the scale, within two octaves. The randomness is the family's +`idle_seconds` is the patience: that long after your last plant, the wind +picks up. The gardener strikes on a calm/gust cycle โ€” `gust` at 0 is a +still day, single strikes spaced about one per pass; raise it and strikes +arrive in flurries of up to five neighboring tubes within a fraction of a +second, with longer calms between, the average rate holding. The +randomness is the family's seeded xorshift64* with the full tr808 contract, pinned as a triad: same seed, bit-identical garden; different seed, a different garden; gardener disabled (`idle_seconds 0`), the seed cannot matter at all, because the @@ -93,8 +129,13 @@ that demands reproducibility. no gardener, fast decay: each phrase you play unwinds itself to silence in a few passes, a wind-up toy running down. - **The endless install:** `@scale minorpentatonic @root 2 @idle 3. - @seed 2008 @level 0.35`, never touch it again. Same seed next year, - same garden. + @gust 0.6 @seed 2008 @level 0.35`, never touch it again. Same seed next + year, same garden โ€” gusts and all. +- **The still day:** `@gust 0 @idle 10.` โ€” no flurries, one unhurried + strike at a time, the original music-box gardener. +- **The marimba loft:** `@material 1 @spread 1. @decay 0.7 @soften 0.8` โ€” + tuned bars instead of tubes, the rack thrown wide: drier, woodier blooms + that each speak from their own place in the image. - **Duet:** `@idle 6.` and stay at the keyboard โ€” every silence longer than six seconds, the gardener answers you; every plant of yours resets its patience. @@ -107,15 +148,21 @@ that demands reproducibility. - **Rhythm.** Events return on the loop grid, exactly, forever โ€” no swing, no humanization. For patterns as *rhythm*, `tap.808.seq~` is the machine. -- **Any other timbre.** One soft bell family, on purpose. It is an - instrument, not a polysynth; for FM as a playground, patch oscillators. +- **Any other timbre.** Two materials, one chime family, on purpose. It is + an instrument, not a polysynth; for synthesis as a playground, patch + oscillators. +- **A stereo panner.** The image is a rack of fixed seats keyed by pitch โ€” + there is no per-strike pan and no motion. For placement as a *parameter*, + pan the object's output. ## Checkpoint Notes become events; events recirculate on a loop, quieter by `decay` and -purer by `soften` each pass, retiring below `floor`; a sixteen-bell pool +purer by `soften` each pass, retiring below `floor`; a sixteen-chime pool bounds the sound and a sixty-four-seat ring bounds the score, oldest bloom -yielding first. The scale makes wrong notes unrepresentable, and a seeded -gardener keeps the piece alive exactly as long as you neglect it. Every +yielding first. Two materials share the rack, every tube keeps its own +flaws and its own stereo seat, the scale makes wrong notes unrepresentable, +and a seeded gardener keeps the piece alive exactly as long as you neglect +it. Every number above lives twice: as an executed cell in `garden.ipynb` and as a pinned scenario in `tests/garden_test.cpp`, which CI runs on every push. diff --git a/book/src/images/airport/raster.svg b/book/src/images/airport/raster.svg index 81bfcc5..5fa0b69 100644 --- a/book/src/images/airport/raster.svg +++ b/book/src/images/airport/raster.svg @@ -6,7 +6,7 @@ - 2026-08-12T01:45:24.202133 + 2026-08-14T14:09:34.746978 image/svg+xml @@ -42,16 +42,16 @@ z +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - - + @@ -62,11 +62,11 @@ L 0 3.5 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -77,11 +77,11 @@ L 184.784163 7.2 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -92,11 +92,11 @@ L 236.960631 7.2 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -107,11 +107,11 @@ L 289.137099 7.2 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -122,11 +122,11 @@ L 341.313567 7.2 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -137,11 +137,11 @@ L 393.490035 7.2 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -157,16 +157,16 @@ L 445.666504 7.2 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0; stroke-width: 0.5; stroke-linecap: square"/> - - + @@ -177,11 +177,11 @@ L -3.5 0 +" clip-path="url(#pef70ad117d)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -192,11 +192,11 @@ L 490.015469 78.04 +" clip-path="url(#pef70ad117d)" style="fill: none; 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stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - - + @@ -62,11 +62,11 @@ L 0 3.5 +" clip-path="url(#p976038263b)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -77,11 +77,11 @@ L 159.596651 20.842188 +" clip-path="url(#p976038263b)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -92,11 +92,11 @@ L 250.905742 20.842188 +" clip-path="url(#p976038263b)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -107,11 +107,11 @@ L 342.214833 20.842188 +" clip-path="url(#p976038263b)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -127,16 +127,16 @@ L 433.523924 20.842188 +" clip-path="url(#p976038263b)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - - + @@ -155,11 +155,11 @@ L -3.5 0 +" clip-path="url(#p976038263b)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -177,138 +177,138 @@ L 451.785742 72.526837 - - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + @@ -322,23 +322,23 @@ L 159.596651 32.348903 L 250.905742 36.043618 L 342.214833 39.738333 L 433.523924 43.433048 -" clip-path="url(#pdd458acd82)" style="fill: none; stroke: #b8890f; stroke-opacity: 0.7; stroke-width: 1.2; stroke-linecap: square"/> +" clip-path="url(#p976038263b)" style="fill: none; stroke: #b8890f; stroke-opacity: 0.7; stroke-width: 1.2; stroke-linecap: square"/> - - - - - - - + + + + + + @@ -347,11 +347,11 @@ L 159.596651 67.609268 L 250.905742 106.564348 L 342.214833 145.519429 L 433.523924 184.474509 -" clip-path="url(#pdd458acd82)" style="fill: none; stroke: #4269d0; stroke-opacity: 0.7; stroke-width: 1.2; stroke-linecap: square"/> +" clip-path="url(#p976038263b)" style="fill: none; stroke: #4269d0; stroke-opacity: 0.7; stroke-width: 1.2; stroke-linecap: square"/> - - - - - - - + + + + + + @@ -393,7 +393,7 @@ L 451.785742 192.706188 - + diff --git a/book/src/images/garden/block-diagram.svg b/book/src/images/garden/block-diagram.svg index 1b1ffd2..fab4ae2 100644 --- a/book/src/images/garden/block-diagram.svg +++ b/book/src/images/garden/block-diagram.svg @@ -36,11 +36,13 @@ bell pool ยท 16 - 2-op FM, ratio 3, decay_env - steal = re-aim the quietest, - never a reset - - out + chime: 4 mode doublets (material), decay_env each + tube hash: mode scatter + stereo seat + steal = re-aim the quietest, never a reset + + + L + R @@ -56,6 +58,6 @@ the gardener seeded xorshift64* โ€” after - idle_seconds, ~1 plant per pass + idle_seconds: gusts and calms diff --git a/book/src/images/garden/staircase.svg b/book/src/images/garden/staircase.svg index 4f1d367..1e639f7 100644 --- a/book/src/images/garden/staircase.svg +++ b/book/src/images/garden/staircase.svg @@ -6,7 +6,7 @@ - 2026-08-12T01:45:24.340888 + 2026-08-14T17:50:15.761652 image/svg+xml @@ -42,16 +42,16 @@ z +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - - + @@ -62,11 +62,11 @@ L 0 3.5 +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -77,11 +77,11 @@ L 121.207424 20.798437 +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -92,11 +92,11 @@ L 173.384358 20.798437 +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -107,11 +107,11 @@ L 225.561292 20.798437 +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -122,11 +122,11 @@ L 277.738226 20.798437 +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -137,11 +137,11 @@ L 329.91516 20.798437 +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -152,11 +152,11 @@ L 382.092094 20.798437 +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b0b0b0; stroke-opacity: 0.22; stroke-width: 0.5; stroke-linecap: square"/> - + @@ -170,3907 +170,2885 @@ L 434.269028 20.798437 - + - - + - โˆ’0.8 + โˆ’0.4 - + - + - โˆ’0.6 + โˆ’0.2 - + - + - โˆ’0.4 + 0.0 - + - + - โˆ’0.2 + 0.2 - + - + - 0.0 + 0.4 - - - - - - - - - - - 0.2 - - - - - - - - - - - - - 0.4 - - - - - - - - - - - - - 0.6 - - - - - - - - - - - - - 0.8 - - - + output - - + + - + +" clip-path="url(#pb8b2c3f749)" style="fill: none; stroke: #b8890f; stroke-width: 1.6; stroke-linecap: square"/> - - + + - - + + - - + + - - + + - - + + - - 0.8 + + 0.49 - - 0.4 + + 0.21 - - 0.2 + + 0.10 - - 0.1 + + 0.05 - - 0.05 + + 0.02 - - floor 0.05 โ€” retirement + + floor 0.05 โ€” retirement - - decay 0.5: each return half as loud, then the bloom retires + + decay 0.5: each return half the previous peak, then the bloom retires - + diff --git a/book/src/machine/garden.md b/book/src/machine/garden.md index 9264fec..f4c9150 100644 --- a/book/src/machine/garden.md +++ b/book/src/machine/garden.md @@ -4,7 +4,7 @@ which makes it the family's odd one out mechanically and its purest member conceptually: the wear-as-stabilizer inversion survives the abstraction jump intact, as arithmetic. This appendix walks the machinery โ€” the ring, the -split between planting and firing, the bell, the quantizer, the gardener โ€” +split between planting and firing, the chime, the quantizer, the gardener โ€” and the two contracts that had to be designed before they could be tested. ## The event ring @@ -37,21 +37,58 @@ exactly `ceil(log(floor/velocity)/log(decay))` passes and the population converges no matter the planting rate. That is the stability theorem, and it is three lines of arithmetic instead of a saturator. -## The bell - -Two-operator FM at a fixed ratio of 3 (Chowning 1973), amplitude from the -shared `tr808::decay_env`, modulation index `velocity ยท brightness ยท -k_index_max`. The ratio was a *test requirement* before it was an -aesthetic: an integer ratio keeps the spectrum harmonic, harmonic means the -YIN oracle reads the fundamental, and the scale-contract scenario โ€” plant -off-scale pitches, require every sounded note on the scale within 20 cents -โ€” only exists because the voice is honest to a pitch detector. Softening -maps to the index, so "purer every pass" is measurable as a Goertzel -trajectory: the 4f sideband fades return over return while the fundamental -holds. Steals re-aim: the pool's quietest bell gets `trigger()`ed with new -targets while its envelope and phases free-run, so a steal glides where a -reset would click; the `decay_env` was built for exactly this non-resetting -retrigger, one family over. +## The chime + +Four decaying mode doublets at the transverse-vibration ratios of the +selected `material` โ€” the free-free tube's 1 : 2.756 : 5.404 : 8.933 from +the bars-and-tubular-chimes chapter of Fletcher & Rossing's *The Physics of +Musical Instruments* (f_n grows as (2n+1)ยฒ), or the tuned bar's +double-octave 1 : 4 : 10 : 20 from the mallet-percussion chapter โ€” each +mode a pair of sines split a fixed few cents, the doublet splitting of a +real tube's degenerate mode pairs (same source), so the tail beats slowly +instead of decaying like a lab sine. The ratio and haste tables are indexed +`[material][mode]` and read at strike time, which is the whole +implementation of the material switch: instant, allocation-free, and every +live bloom re-voices at its next return. Each mode rides +its own `tr808::decay_env`; decay times divide by ~ratioยฒ (radiation +damping grows with frequency), which makes the fourth mode a +tens-of-milliseconds contact tick, and scale by โˆš(440/f) per strike, so +small high tubes ring shorter than long low ones. The upper modes scale +with per-event brightness *times strike hardness* (a soft strike is a dull +strike) and progressively steeply (b, bยฒ, bยณ), so `soften` strips the tick +first and mode two by exactly its ratio. Mode levels sum to at most 1, so a +chime is bounded by its velocity and the pool bound stays arithmetic; modes +above 0.45ยทsr stay silent rather than aliasing. + +The phase rule earned a refinement when the doublets arrived: a strike on a +*silent* tube zeroes its phases โ€” fresh initial conditions, so the pair +starts aligned and its beat blooms identically at every return, which is +what keeps per-return spectral measurements deterministic โ€” while an +audible steal keeps free-running phases and glides instead of clicking. +The inharmonicity moved the pitch contract rather than breaking it: the +upper modes clear quickly, so the YIN oracle reads each strike in its +ring-down, and the scale-contract scenario still lands every off-scale +plant on the scale within 20 cents. + +## The tube is the identity + +Two more properties hang off each pitch, and neither touches the rng. A +tube's upper modes sit up to ยฑ3 cents off the ideal ratios โ€” the +fundamental stays true, because a maker tunes the fundamental โ€” and the +tube keeps a fixed seat on the stereo rack, `spread` scaling how far off +center. Both are drawn by `tube_unit`, a stateless xorshift64* hash keyed +by (fundamental-in-centihertz, index) โ€” the `metal_bank.h` per-index idiom, +index 0 the seat, 1..3 the mode scatter. Stateless is the load-bearing +word: the gardener's seeded generator is never consumed, so the seed-triad +contract survives intact, the rack is identical in every instance, and +every return of a bloom rings from the same place with the same flaws. +The pinned scenarios measure the scatter by scanning a Goertzel probe +across the second mode (ยฑ0.25-cent steps resolve it), and the seat by +left/right energy share: deterministic per pitch, different across pitches, +bounded by the constants. The seat itself follows the phase rule โ€” pan +gains snap on a silent tube and slew ~10 ms through an audible steal โ€” and +the equal-power law is the โˆš((1โˆ“p)/2) form, so `spread 0` makes the busses +*bitwise* identical (also pinned). ## Quantize at entry @@ -67,17 +104,23 @@ stable under live tinkering and makes the contract easy to state. ## The gardener and the seed -Idle planting consumes the family RNG (`tr808::white_noise`, xorshift64*, -the seed-folding and clear-reseeds contract) โ€” and *only* idle planting -does. That consumption discipline is load-bearing: the third leg of the -seeded triad, "with the gardener disabled the seed cannot matter at all", -is only true because a disabled gardener never touches the generator, so -two beds with different seeds run bit-identical until the first idle draw. -The suite pins all three legs, the way the tr808 voices taught: same seed -bit-exact, different seed audibly different, seed irrelevant when the -random feature is off. `step_seq.h` promises "no randomness anywhere"; this -kernel is the deliberate counterpoint, and the triad is the bridge back to -a reproducible test suite. +The gardener is a wind model: once the idle threshold passes, strikes +arrive on a calm/gust cycle driven by a small state machine โ€” a gust +catches 1 to 5 neighboring tubes (`gust` sizes it) with 30โ€“280 ms between +strikes, the clapper walking a few semitones per swing, and the following +calm stretches with the gust just spent so the average rate stays near one +strike per pass at any setting. Idle planting consumes the family RNG +(`tr808::white_noise`, xorshift64*, the seed-folding and clear-reseeds +contract) โ€” and *only* idle planting does. That consumption discipline is +load-bearing: the third leg of the seeded triad, "with the gardener +disabled the seed cannot matter at all", is only true because a disabled +gardener never touches the generator. The suite pins all three legs, plus +the wind itself: at gust 1 some strikes tumble inside a gust, at gust 0 +single strikes never come closer than the minimum calm (the scenario sets +`decay 0` so only the gardener's own strikes are counted โ€” planted seeds +recirculate, and returns are not wind). `step_seq.h` promises "no +randomness anywhere"; this kernel is the deliberate counterpoint, and the +triad is the bridge back to a reproducible test suite. ## A finding: envelopes never reach zero @@ -96,8 +139,9 @@ pass. ## The engineering ledger -The suite measures the output, never the internals: peak-per-window ratios -for the decay staircase (0.5 ยฑ 0.075 across four returns, then +The suite measures the output, never the internals: fundamental ratios +for the decay staircase (0.5 ยฑ 0.05 across four returns โ€” the fundamental, +because hardness makes whole-strike peaks fade faster than velocity, then `active_events() == 0` and the render below 1eโˆ’6), a strictly-decreasing Goertzel sideband for softening, YIN for the scale contract, the seeded triad rendered three times over, and structural bounds exercised at their @@ -109,11 +153,13 @@ could be written against public surface. ## Checkpoint -A fixed ring of events fired by a loop counter into a fixed pool of FM -bells: plant and fire kept strictly apart, wear as per-pass arithmetic +A fixed ring of events fired by a loop counter into a fixed pool of modal +wind chimes: plant and fire kept strictly apart, wear as per-pass arithmetic (decay, soften, floor) with convergence as its theorem, scale masks copied -from `tune.h` and applied at entry, and a gardener whose RNG discipline -makes generative behavior compatible with a bit-exact test suite. Third +from `tune.h` and applied at entry, tube identity (material voicing, mode +scatter, stereo seat) as stateless hashes so nothing generative leaks into +the audio path, and a gardener whose RNG discipline makes generative +behavior compatible with a bit-exact test suite. Third costume, same inversion: the system stays bounded because everything in it is always fading. Every claim lives twice โ€” `garden.ipynb` executed, `garden_test.cpp` pinned. diff --git a/include/taptools/garden.h b/include/taptools/garden.h index b30d729..1fd35b5 100644 --- a/include/taptools/garden.h +++ b/include/taptools/garden.h @@ -17,19 +17,45 @@ /// below `floor`, so the live-event population converges no matter how fast you /// plant โ€” and a fixed bell pool (quietest-stolen) hard-bounds the audio regardless. /// -/// The voice is a two-operator FM bell (Chowning, "The Synthesis of Complex Audio -/// Spectra by Means of Frequency Modulation", JAES 1973): carrier plus modulator at -/// the fixed harmonic ratio 3 โ€” odd-partial, bell-ish, and harmonic, so a pitch -/// detector reads it at the fundamental โ€” with modulation index scaled by velocity -/// and per-event brightness (velocity-to-index is standard published FM practice). -/// Each pass multiplies the event's brightness by `soften`, so a bloom does not just -/// fade: it purifies toward a sine. Amplitude rides the shared tr808 decay_env; a -/// steal re-aims the envelope without a reset, so stolen voices glide, not click. +/// The voice is a small wind chime: four decaying mode doublets at the transverse- +/// vibration ratios of the chosen `material` โ€” the free-free tube's +/// 1 : 2.756 : 5.404 : 8.933 or the tuned bar's double-octave 1 : 4 : 10 : 20 +/// (Fletcher & Rossing, The Physics of Musical Instruments, 2nd ed. โ€” the +/// bars/tubular-chimes and mallet-percussion chapters; f_n grows as (2n+1)^2 for +/// the free bar, and marimba bars are undercut to the octave tuning; doublet +/// splitting of degenerate tube mode pairs is from the same source, a fixed few +/// cents here so tails beat slowly instead of decaying like lab sines). The first +/// mode carries the perceived pitch; +/// the upper modes are inharmonic, softer (scaled by per-event brightness times +/// strike hardness โ€” a soft strike is a dull strike), progressively steeper in +/// brightness (b, b^2, b^3), and faster-dying (~f^2 radiation damping), the 4th +/// gone in tens of milliseconds: the contact tick. Ring time scales with +/// sqrt(440/f) per strike โ€” small high tubes ring shorter. Every strike therefore +/// rings down to its fundamental, which is where the pitch contract lives: a +/// detector reads the chime in its tail, once the clang has cleared (the tests +/// measure there). Each pass multiplies the event's brightness by `soften`, so a +/// bloom does not just fade: it purifies toward its fundamental, losing its tick +/// first. Mode amplitudes ride the shared tr808 decay_env (one per mode); a strike +/// on a silent tube starts its doublets aligned (fresh initial conditions), while +/// an audible steal keeps free-running phases and glides instead of clicking. +/// +/// The tube is the identity. Each struck pitch is a physical tube whose +/// imperfections are fixed properties of the tube, not of the strike: its upper +/// modes sit up to k_scatter_cents off the ideal ratios (the fundamental stays +/// true โ€” a maker tunes the fundamental and the overtones land where the metal +/// puts them), and it hangs at a fixed seat on the stereo rack, spread scaled by +/// `spread`. Both draws come from a stateless hash of the pitch (the metal_bank.h +/// per-index xorshift idiom), so the rack is the same rack in every instance, +/// every return of a bloom rings from the same place with the same flaws, and the +/// gardener's seeded rng is never consumed โ€” the seed-triad contract survives. /// /// Randomness: the idle gardener draws from the family's seeded xorshift64* /// (tr808::white_noise) โ€” deterministic per seed, so renders and tests reproduce and -/// instances decorrelate by seed. This is the library's first randomized *event* -/// source (step_seq.h promises "no randomness anywhere"; this kernel is the deliberate +/// instances decorrelate by seed. The gardener is wind: strikes arrive on a +/// calm/gust cycle (`gust` sizes the clusters โ€” up to five neighboring tubes within +/// a fraction of a second โ€” with calms stretched to hold the average near one +/// strike per pass). This is the library's first randomized *event* source +/// (step_seq.h promises "no randomness anywhere"; this kernel is the deliberate /// counterpoint, and the seed contract is the bridge back to reproducibility). /// /// Geometry: everything is fixed arrays โ€” k_max_events events, k_voices bells โ€” @@ -42,9 +68,11 @@ /// pass, exactly โ€” there is no swing, no drift, no humanization. /// - A full garden (k_max_events live) retires its OLDEST bloom to make room for a /// new plant: a touch must always speak, and the oldest is the quietest. -/// - The idle gardener is statistical (about one plant per loop pass, uniformly -/// placed), not a transcription of any published piece or app behavior. -/// - Mono out; one bell timbre family. It is an instrument, not a polysynth. +/// - The idle gardener is a statistical wind (gusts and calms averaging about one +/// strike per pass), not a transcription of any published piece or app behavior. +/// - Stereo out, but the image is a fixed rack of seats keyed by pitch โ€” there is +/// no per-strike pan, no motion. Two materials, one chime timbre family. It is +/// an instrument, not a polysynth. /// @author Timothy Place // SPDX-License-Identifier: MIT // Copyright 2026 Timothy Place. @@ -64,21 +92,66 @@ namespace tap::tools { constexpr double k_pi = 3.14159265358979323846; - constexpr int k_max_events = 64; // live blooms; oldest yields when full - constexpr int k_voices = 16; // fixed bell pool; quietest-first steal - constexpr double k_fm_ratio = 3.0; // harmonic odd-partial bell (Chowning 1973) - constexpr double k_index_max = 2.0; // modulation index at velocity 1, brightness 1 + constexpr int k_max_events = 64; // live blooms; oldest yields when full + constexpr int k_voices = 16; // fixed bell pool; quietest-first steal + constexpr int k_modes = 4; // a small chime: four transverse modes, the 4th the strike's tick + + /// What the tubes are made of โ€” a mode, not a fader (instant; re-voices every bloom at + /// its next return). + enum material_index : int { + material_chime = 0, // free-free tube: the wind-chime rack + material_bar, // tuned bar: the mallet-instrument plank + k_num_materials + }; + + // Transverse-mode ratios per material (Fletcher & Rossing, The Physics of Musical + // Instruments, 2nd ed.): the free-free bar's 1 : 2.756 : 5.404 : 8.933 (f_n ~ (2n+1)^2, + // bars/tubular-chimes chapter), and the tuned bar's 1 : 4 : 10 double-octave tuning + // (mallet-percussion chapter), its 4th continuing the double-octave series. + constexpr double k_mode_ratio[k_num_materials][k_modes] = { + {1.0, 2.756, 5.404, 8.933}, + {1.0, 4.0, 10.0, 20.0}, + }; + // Decay-time divisor per mode, ~ratio^2: radiation damping grows roughly with f^2, so + // higher modes die much faster โ€” the 4th is gone in tens of ms, the contact tick. + constexpr double k_mode_haste[k_num_materials][k_modes] = { + {1.0, 7.6, 29.2, 79.8}, + {1.0, 16.0, 100.0, 400.0}, + }; + // Mode levels at full hardness sum to <= 1 so a chime is bounded by its velocity; the + // upper modes scale with brightness (progressively steeper โ€” see bell::trigger). + constexpr double k_mode_level[k_modes] = {0.58, 0.25, 0.10, 0.07}; + // Each mode is a doublet: a real tube's degenerate mode pairs are split a few cents by + // imperfection (Fletcher & Rossing on doublets in bells/chimes), so tails beat slowly + // instead of decaying like lab sines. Fixed split โ€” deterministic, no RNG. + constexpr double k_doublet_cents = 1.5; + // Each TUBE is imperfect in its own fixed way: per-pitch mode detune of up to this many + // cents, drawn by a stateless hash of (pitch, mode) โ€” the metal_bank.h per-index idiom, + // so the rack is the rack in every instance and the gardener's seed is never involved. + constexpr double k_scatter_cents = 3.0; + // A soft strike is a dull strike: effective brightness scales with velocity through + // this floor (hardness = floor + (1 - floor) * velocity). + constexpr double k_hardness_floor = 0.5; + // Small high tubes ring shorter than long low ones: per-strike decay scales by + // sqrt(440 / f), clamped to this range. + constexpr double k_ring_scale_min = 0.5; + constexpr double k_ring_scale_max = 2.0; + // A steal glides its seat the way it glides its phases: pan gains slew over this window + // (a strike on a silent tube snaps them โ€” fresh initial conditions, same rule). + constexpr double k_pan_slew_ms = 10.0; constexpr double k_gain_epsilon = 1e-4; // below this a voice is "off" (harmonizer.h idiom) constexpr double k_min_loop_seconds = 0.25; // beneath this it is a buzzer, not a garden constexpr double k_max_loop_seconds = 120.0; // the loop is a counter โ€” no tape is bought constexpr double k_default_loop_seconds = 8.0; - constexpr double k_default_decay = 0.85; // velocity multiplier per pass - constexpr double k_default_soften = 0.9; // brightness multiplier per pass - constexpr double k_default_floor = 0.03; // retirement threshold - constexpr double k_default_idle_seconds = 30.0; // the gardener's patience; 0 disables - constexpr double k_default_attack_s = 0.15; // soft mallet, not a hammer + constexpr double k_default_decay = 0.85; // velocity multiplier per pass + constexpr double k_default_soften = 0.9; // brightness multiplier per pass + constexpr double k_default_floor = 0.03; // retirement threshold + constexpr double k_default_idle_seconds = 30.0; // the gardener's patience; 0 disables + constexpr double k_default_gust = 0.5; // the wind: 0 calm/even, 1 blustery clusters + constexpr double k_default_spread = 0.7; // the rack's stereo width; 0 collapses to mono + constexpr double k_default_attack_s = 0.004; // a clapper's strike, not a bow constexpr double k_default_decay_s = 4.0; constexpr double k_default_brightness = 1.0; constexpr double k_default_smooth_ms = 20.0; // one-pole slew for the master level @@ -112,48 +185,150 @@ namespace tap::tools { make_mask({0, 3, 5, 7, 10}), // minor pentatonic }; - /// One two-operator FM bell: carrier + modulator at k_fm_ratio, amplitude from the shared - /// decay_env. Phases free-run so a steal re-aims without a click. + /// Stateless draw in [-1, 1) keyed by (tube, index) โ€” the metal_bank.h per-index + /// xorshift64* idiom: identity-keyed imperfection with no generator state. The tube key + /// is its fundamental in centihertz; index 0 is the tube's seat on the rack, 1..3 the + /// scatter of its upper modes. Same tube, same flaws, in every instance, forever โ€” + /// and the gardener's seeded rng is never consumed. + inline double tube_unit(uint64_t tube, uint64_t index) { + uint64_t s = tube * 0x9e3779b97f4a7c15ULL + (index + 1) * 0xbf58476d1ce4e5b9ULL; + s ^= s >> 12; + s ^= s << 25; + s ^= s >> 27; + const double u = static_cast((s * 0x2545f4914f6cdd1dULL) >> 11) / 9007199254740992.0; // [0, 1) + return 2.0 * u - 1.0; + } + + /// A tube's identity key: its fundamental, in centihertz (fractional pitches stay + /// distinct; equal pitches strike the same tube). + inline uint64_t tube_key(double freq_hz) { + return static_cast(std::llround(freq_hz * 100.0)); + } + + /// One small wind chime: four decaying mode doublets at the struck material's transverse + /// ratios (k_mode_ratio) โ€” each mode a pair of sines split k_doublet_cents so the tail + /// beats slowly, the upper modes scattered a fixed few cents by the tube's own hash, + /// scaled by brightness (progressively steeper per mode) and hardness (a soft strike is + /// duller), all dying faster than the fundamental (k_mode_haste, ~f^2 radiation damping + /// โ€” the 4th mode is the strike's tick). Ring time scales with sqrt(440/f) at trigger: + /// small high tubes ring shorter. Output is panned to the tube's fixed seat on the + /// rack. Phases free-run and the seat glides, so a steal re-aims without a click. class bell { public: void prepare(double sr) { - m_sr = (sr > 0.0) ? sr : 48000.0; - m_env.prepare(m_sr); - m_env.set_times(k_default_attack_s, k_default_decay_s); + m_sr = (sr > 0.0) ? sr : 48000.0; + m_pan_coeff = 1.0 - std::exp(-1.0 / (k_pan_slew_ms * 0.001 * m_sr)); + for (auto& e : m_env) { + e.prepare(m_sr); + } + set_times(k_default_attack_s, k_default_decay_s); } - void set_times(double attack_s, double decay_s) { m_env.set_times(attack_s, decay_s); } + /// Stored and applied per strike (ring time depends on the struck pitch), so a + /// ringing chime keeps its envelope until retriggered. + void set_times(double attack_s, double decay_s) { + m_attack_s = attack_s; + m_decay_s = decay_s; + } void reset() { - m_env.reset(); - m_carrier_phase = m_mod_phase = 0.0; + for (auto& e : m_env) { + e.reset(); + } + for (auto& p : m_phase_a) { + p = 0.0; + } + for (auto& p : m_phase_b) { + p = 0.0; + } + m_gain_l = m_gain_r = 0.0; // the first strike snaps the seat (silent-tube rule) + m_gain_l_target = m_gain_r_target = 0.0; } - /// Fire at `freq_hz`, envelope target `level`, modulation index `index`. - void trigger(double freq_hz, double level, double index) { - m_carrier_inc = freq_hz / m_sr; - m_mod_inc = k_fm_ratio * freq_hz / m_sr; - m_index = index; - m_env.trigger(level); + /// Strike at `freq_hz` (the first mode โ€” the perceived pitch), envelope target + /// `level`, upper-mode weight `brightness` (0..1), a `material` (mode-ratio table), + /// and a seat `pan` (-1 left .. +1 right, equal-power). Effective brightness couples + /// to the strike level (soft strikes are duller) and steepens per mode (b, b^2, + /// b^3), so softening kills the highest partials first. The upper modes are + /// detuned by the tube's fixed scatter (the fundamental stays true โ€” a maker tunes + /// the fundamental). Modes above the audio band stay silent rather than aliasing. + void trigger(double freq_hz, double level, double brightness, int material, double pan) { + const bool silent = this->level() <= k_gain_epsilon; + if (silent) { // a strike on a silent tube sets fresh + for (auto& p : m_phase_a) { // initial conditions: the doublet starts + p = 0.0; // aligned and its beat blooms from the + } // strike. Audible steals keep free-running + for (auto& p : m_phase_b) { // phases and glide instead. + p = 0.0; + } + } + // Equal-power seat with exact endpoints; sqrt form so pan 0 is bitwise l == r. + const double p = std::clamp(pan, -1.0, 1.0); + m_gain_l_target = std::sqrt(0.5 * (1.0 - p)); + m_gain_r_target = std::sqrt(0.5 * (1.0 + p)); + if (silent) { // the seat snaps with the phases; an audible steal glides there + m_gain_l = m_gain_l_target; + m_gain_r = m_gain_r_target; + } + const size_t mat = static_cast(std::clamp(material, 0, k_num_materials - 1)); + const uint64_t tube = tube_key(freq_hz); + const double hardness = k_hardness_floor + (1.0 - k_hardness_floor) * std::clamp(level, 0.0, 1.0); + const double b = std::clamp(brightness, 0.0, 1.0) * hardness; + const double ring = std::clamp(std::sqrt(440.0 / freq_hz), k_ring_scale_min, k_ring_scale_max); + const double split = std::exp2(k_doublet_cents / 2400.0); // half the split, up and down + double shine = 1.0; // b^0, b^1, b^2, b^3 per mode + for (int m = 0; m < k_modes; ++m) { + const size_t i = static_cast(m); + const double scatter = + (m > 0) ? std::exp2(k_scatter_cents * tube_unit(tube, static_cast(m)) / 1200.0) : 1.0; + const double mode_hz = k_mode_ratio[mat][i] * freq_hz * scatter; + m_inc_a[i] = mode_hz * split / m_sr; + m_inc_b[i] = mode_hz / split / m_sr; + m_env[i].set_times(m_attack_s, m_decay_s * ring / k_mode_haste[mat][i]); + m_env[i].trigger((mode_hz < 0.45 * m_sr) ? level * k_mode_level[i] * shine : 0.0); + shine *= b; + } } - double level() const { return m_env.value(); } // the quietest-first steal key + double level() const { // the quietest-first steal key + double sum = 0.0; + for (const auto& e : m_env) { + sum += e.value(); + } + return sum; + } - double process() { - m_mod_phase += m_mod_inc; - m_mod_phase -= std::floor(m_mod_phase); - m_carrier_phase += m_carrier_inc; - m_carrier_phase -= std::floor(m_carrier_phase); - const double mod = m_index * std::sin(2.0 * k_pi * m_mod_phase); - return m_env.process() * std::sin(2.0 * k_pi * m_carrier_phase + mod); + /// Sum this chime, panned to its seat, into the running busses. + void process(double& out_left, double& out_right) { + double sum = 0.0; + for (size_t i = 0; i < static_cast(k_modes); ++i) { + m_phase_a[i] += m_inc_a[i]; + m_phase_a[i] -= std::floor(m_phase_a[i]); + m_phase_b[i] += m_inc_b[i]; + m_phase_b[i] -= std::floor(m_phase_b[i]); + sum += m_env[i].process() * 0.5 + * (std::sin(2.0 * k_pi * m_phase_a[i]) + std::sin(2.0 * k_pi * m_phase_b[i])); + } + m_gain_l += m_pan_coeff * (m_gain_l_target - m_gain_l); + m_gain_r += m_pan_coeff * (m_gain_r_target - m_gain_r); + out_left += sum * m_gain_l; + out_right += sum * m_gain_r; } private: - double m_sr{48000.0}; - double m_carrier_phase{0.0}, m_carrier_inc{0.0}; - double m_mod_phase{0.0}, m_mod_inc{0.0}; - double m_index{0.0}; - tr808::decay_env m_env; + double m_sr{48000.0}; + double m_attack_s{k_default_attack_s}; + double m_decay_s{k_default_decay_s}; + double m_pan_coeff{1.0}; + double m_gain_l{0.0}; + double m_gain_r{0.0}; + double m_gain_l_target{0.0}; + double m_gain_r_target{0.0}; + std::array m_phase_a{}; + std::array m_phase_b{}; + std::array m_inc_a{}; + std::array m_inc_b{}; + std::array m_env; }; /// The garden bed: plant notes, they bloom on the loop, fade, and retire; left alone, @@ -187,6 +362,10 @@ namespace tap::tools { m_pos = 0; m_planted = 0; m_since_note = 0; + m_gust_wait = -1; + m_gust_left = 0; + m_gust_size = 1; + m_gust_pitch = 69.0; m_level_current = m_level_target; } @@ -248,6 +427,16 @@ namespace tap::tools { } } + /// What the tubes are made of (material_index): the free-free chime rack or the + /// tuned-bar plank. A mode, not a fader: instant, and read at strike time, so every + /// live bloom re-voices at its next return. + void set_material(int material) { m_material = std::clamp(material, 0, k_num_materials - 1); } + + /// The rack's stereo width, [0, 1]. Each tube hangs at a fixed seat drawn from its + /// pitch (the same stateless hash as its scatter), scaled by spread; 0 collapses + /// the rack to center mono, bitwise equal on both busses. + void set_spread(double amount) { m_spread = std::clamp(amount, 0.0, 1.0); } + /// Root pitch class, 0..11 (0 = C). A mode: instant, affects future plants only. void set_root(int semitone) { m_root = ((semitone % 12) + 12) % 12; } @@ -258,6 +447,11 @@ namespace tap::tools { /// (and then the seed cannot matter at all โ€” pinned by test). void set_idle_seconds(double s) { m_idle_seconds = std::max(0.0, s); } + /// The wind, 0..1: at 0 the gardener strikes singly and evenly (about one per pass); + /// up from there, strikes arrive in gusts โ€” clusters of up to five on neighboring + /// tubes within a fraction of a second, then longer calms, same average rate. + void set_gust(double amount) { m_gust = std::clamp(amount, 0.0, 1.0); } + /// The gardener's seed โ€” deterministic per seed, house triad contract. Instant. void set_seed(uint64_t seed) { m_rng.set_seed(seed); } @@ -289,9 +483,12 @@ namespace tap::tools { double attack_s() const { return m_attack_s; } double decay_s() const { return m_decay_s; } double brightness() const { return m_brightness; } + int material() const { return m_material; } + double spread() const { return m_spread; } int root() const { return m_root; } int scale() const { return m_scale; } double idle_seconds() const { return m_idle_seconds; } + double gust() const { return m_gust; } uint64_t seed() const { return m_rng.seed(); } double level() const { return m_level_target; } double smooth_ms() const { return m_smooth_ms; } @@ -300,10 +497,13 @@ namespace tap::tools { // -- audio --------------------------------------------------------------------------- /// A source: no input. Advance the loop one sample, fire any blooms whose position - /// this is, let the gardener plant if the garden has been idle, and sum the bells. - double process() { + /// this is, let the gardener plant if the garden has been idle, and sum the bells + /// onto the stereo busses, each at its tube's seat. + void process(double& out_left, double& out_right) { if (!m_prepared) { - return 0.0; + out_left = 0.0; + out_right = 0.0; + return; } for (auto& e : m_events) { if (e.alive && e.offset == m_pos) { @@ -316,19 +516,21 @@ namespace tap::tools { m_pos = 0; } - double sum = 0.0; + double sum_l = 0.0; + double sum_r = 0.0; for (auto& v : m_bells) { - sum += v.process(); + v.process(sum_l, sum_r); } const double coeff = (m_smooth_ms > 0.0) ? 1.0 - std::exp(-1.0 / (m_smooth_ms * 0.001 * m_sr)) : 1.0; m_level_current += coeff * (m_level_target - m_level_current); - return sum * m_level_current; + out_left = sum_l * m_level_current; + out_right = sum_r * m_level_current; } /// Block form: the trivial loop over the scalar path. - void process(double* out, size_t n) { + void process(double* out_left, double* out_right, size_t n) { for (size_t i = 0; i < n; ++i) { - out[i] = process(); + process(out_left[i], out_right[i]); } } @@ -374,7 +576,7 @@ namespace tap::tools { return *oldest; } - /// Sound this event now on the pool: an idle voice if any, else steal the quietest. + /// Strike this event now on the pool: an idle voice if any, else steal the quietest. void fire(event& e) { bell* voice = &m_bells[0]; for (auto& v : m_bells) { @@ -387,7 +589,8 @@ namespace tap::tools { } } const double freq = 440.0 * std::exp2((e.pitch - 69.0) / 12.0); - voice->trigger(freq, e.velocity, e.brightness * k_index_max * e.velocity); + const double pan = m_spread * tube_unit(tube_key(freq), 0); // index 0: the seat + voice->trigger(freq, e.velocity, e.brightness, m_material, pan); } /// One pass of wear, one level up: quieter, purer, and gone below the floor. @@ -399,8 +602,14 @@ namespace tap::tools { } } - /// The idle gardener: after idle_seconds without a caller plant, sow about one seed - /// per loop pass, uniformly placed, on the scale, within two octaves of middle root. + double uniform() { return 0.5 * (m_rng.process() + 1.0); } // [0, 1), the gardener's die + + /// The idle gardener as wind: after idle_seconds without a caller plant, strikes + /// arrive on a calm/gust cycle. Each gust catches 1 to 5 neighboring tubes (sized by + /// `gust`) within a fraction of a second; calms between gusts stretch so the average + /// rate stays near one strike per loop pass at any gust setting. The rng is consumed + /// only while idling โ€” the seed-triad contract depends on that discipline. A caller + /// plant closes the idle gate mid-gust; the gust resumes if the garden idles again. void tend() { ++m_since_note; if (m_idle_seconds <= 0.0) { @@ -409,14 +618,25 @@ namespace tap::tools { if (static_cast(m_since_note) < m_idle_seconds * m_sr) { return; } - const double u = 0.5 * (m_rng.process() + 1.0); // [0, 1) - if (u * static_cast(loop_samples()) >= 1.0) { - return; // ~one plant per pass + if (m_gust_wait < 0) { // the wind arriving: the first strike lands within half a loop + m_gust_wait = static_cast(0.5 * uniform() * static_cast(loop_samples())); + m_gust_left = 0; + } + if (m_gust_wait > 0) { + --m_gust_wait; + return; } - const double pitch = 60.0 + std::floor(12.0 * (m_rng.process() + 1.0)); // [60, 84) - const double velocity = 0.3 + 0.2 * (m_rng.process() + 1.0); // [0.3, 0.7) + if (m_gust_left <= 0) { // a fresh gust: how many tubes does this one catch? + m_gust_size = 1 + static_cast(uniform() * (1.0 + 4.0 * m_gust)); + m_gust_left = m_gust_size; + m_gust_pitch = 55.0 + 29.0 * uniform(); // a fresh place on the rack + } + else { // the clapper swings on to a neighboring tube + m_gust_pitch = std::clamp(m_gust_pitch + std::floor(9.0 * uniform()) - 4.0, 48.0, 90.0); + } + const double velocity = 0.3 + 0.4 * uniform(); event& e = allocate(); - e.pitch = quantize(pitch); + e.pitch = quantize(m_gust_pitch); e.velocity = velocity; e.brightness = m_brightness; e.offset = m_pos; @@ -424,6 +644,14 @@ namespace tap::tools { e.seq = m_planted++; fire(e); bloom(e); + --m_gust_left; + if (m_gust_left > 0) { // within a gust: strikes tumble 30..280 ms apart + m_gust_wait = static_cast((0.03 + 0.25 * uniform()) * m_sr); + } + else { // calm, stretched by the gust just spent: the average rate holds + m_gust_wait = static_cast((0.5 + uniform()) * static_cast(m_gust_size) + * static_cast(loop_samples())); + } // Deliberately does NOT reset m_since_note's gate below the threshold: once the // gardener starts, it keeps tending until the caller plants again. } @@ -437,9 +665,12 @@ namespace tap::tools { double m_attack_s{k_default_attack_s}; double m_decay_s{k_default_decay_s}; double m_brightness{k_default_brightness}; + int m_material{material_chime}; + double m_spread{k_default_spread}; int m_root{0}; int m_scale{scale_major_pentatonic}; // anything you plant sounds consonant double m_idle_seconds{k_default_idle_seconds}; + double m_gust{k_default_gust}; double m_level_target{1.0}; double m_level_current{1.0}; double m_smooth_ms{k_default_smooth_ms}; @@ -447,6 +678,10 @@ namespace tap::tools { long m_pos{0}; uint32_t m_planted{0}; long long m_since_note{0}; + long m_gust_wait{-1}; + int m_gust_left{0}; + int m_gust_size{1}; + double m_gust_pitch{69.0}; tr808::white_noise m_rng; std::array m_events; std::array m_bells; diff --git a/notebooks/garden.ipynb b/notebooks/garden.ipynb index 3c827d2..4f3292b 100644 --- a/notebooks/garden.ipynb +++ b/notebooks/garden.ipynb @@ -2,34 +2,37 @@ "cells": [ { "cell_type": "markdown", - "id": "323f9358", + "id": "8e3faba1", "metadata": {}, "source": [ "# tap.garden~ โ€” the garden, measured\n", "\n", "The generative event loop (`taptools/garden.h`), a recreation of the *principle* behind\n", - "Eno/Chilvers' Bloom: a planted note snaps to the scale, blooms on a two-operator FM bell,\n", + "Eno/Chilvers' Bloom: a planted note snaps to the scale, strikes a small modal wind chime\n", + "(four mode doublets at the chosen material's ratios โ€” free-free tube or tuned bar โ€”\n", + "hardness-coupled, ring time scaled to pitch, each tube with its own fixed upper-mode\n", + "scatter and a fixed seat on the stereo rack),\n", "and returns every loop pass a step quieter (`decay`) and purer (`soften`) until it retires\n", "below the `floor`; left idle, a seeded gardener plants for you. The family's stability\n", "inversion, one level up: **per-pass decay is the stabilizer** โ€” the event population\n", "converges by construction, and a fixed sixteen-bell pool hard-bounds the audio. Every trace\n", "drives the **shipping C++** through `tools/capi` via ctypes.\n", "\n", - "Sections: **1** the return staircase ยท **2** softening, in partials ยท **3** the scale\n", - "contract, by the pitch oracle ยท **4** the seeded gardener ยท **5** an hour of garden,\n", - "in two minutes." + "Sections: **1** the return staircase ยท **2** softening, in partials ยท **3** the rack:\n", + "materials, scatter, seats ยท **4** the scale contract, by the pitch oracle ยท **5** the\n", + "seeded gardener ยท **6** an hour of garden, in two minutes." ] }, { "cell_type": "code", "execution_count": 1, - "id": "d1468886", + "id": "6f763164", "metadata": { "execution": { - "iopub.execute_input": "2026-08-12T01:40:36.898478Z", - "iopub.status.busy": "2026-08-12T01:40:36.898279Z", - "iopub.status.idle": "2026-08-12T01:40:37.332788Z", - "shell.execute_reply": "2026-08-12T01:40:37.331442Z" + "iopub.execute_input": "2026-08-14T17:49:05.399344Z", + "iopub.status.busy": "2026-08-14T17:49:05.399170Z", + "iopub.status.idle": "2026-08-14T17:49:05.748093Z", + "shell.execute_reply": "2026-08-14T17:49:05.746581Z" } }, "outputs": [], @@ -53,13 +56,15 @@ }, { "cell_type": "markdown", - "id": "1e0d35c8", + "id": "ae107b11", "metadata": {}, "source": [ "## 1 ยท The return staircase\n", "\n", "One note planted at velocity 0.8 into a 0.5 s loop, `decay` 0.5, `floor` 0.05: the bloom\n", - "returns at 0.8, 0.4, 0.2, 0.1, 0.05 โ€” a measured staircase of halvings โ€” and then retires;\n", + "returns with its *fundamental* halving every pass โ€” a measured staircase โ€” and then\n", + "retires (the whole strike fades a shade faster still, because quieter strikes are also\n", + "duller: the hardness coupling);\n", "`active_events` drops to zero and the garden is silent. That retirement arithmetic\n", "(`ceil(log(floor/velocity)/log(decay))` passes, always) is the population-convergence\n", "theorem in one plant. (Kernel scenarios: *\"a planted note blooms again every loop period\"*,\n", @@ -69,19 +74,19 @@ { "cell_type": "code", "execution_count": 2, - "id": "77aeb815", + "id": "0e643ad8", "metadata": { "execution": { - "iopub.execute_input": "2026-08-12T01:40:37.336263Z", - "iopub.status.busy": "2026-08-12T01:40:37.335983Z", - "iopub.status.idle": "2026-08-12T01:40:37.551063Z", - "shell.execute_reply": "2026-08-12T01:40:37.549876Z" + "iopub.execute_input": "2026-08-14T17:49:05.750439Z", + "iopub.status.busy": "2026-08-14T17:49:05.750176Z", + "iopub.status.idle": "2026-08-14T17:49:06.378208Z", + "shell.execute_reply": "2026-08-14T17:49:06.377106Z" } }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -93,60 +98,67 @@ "name": "stdout", "output_type": "stream", "text": [ - "per-return peaks: [np.float64(0.795), np.float64(0.399), np.float64(0.2), np.float64(0.1), np.float64(0.05), np.float64(0.0)]\n", + "per-return peaks: [np.float64(0.488), np.float64(0.207), np.float64(0.095), np.float64(0.046), np.float64(0.022), np.float64(0.0)]\n", + "fundamental ratios: [np.float64(0.5), np.float64(0.5), np.float64(0.5), np.float64(0.5)]\n", + "(peaks fade a shade faster than 0.5: quieter returns are also duller โ€” hardness)\n", "live events after the render: 0\n" ] } ], "source": [ - "g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, loop_seconds=0.5,\n", + "g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, spread=0, loop_seconds=0.5,\n", " decay=0.5, floor=0.05, bell=(0.002, 0.05, 1.0), scale=0)\n", "g.note(69, 0.8)\n", - "y = g.process(int(3.5 * sr))\n", + "y, _ = g.process(int(3.5 * sr)) # spread 0: both busses identical, read the left\n", "\n", "t = np.arange(y.size) / sr\n", "fig, ax = plt.subplots()\n", "ax.plot(t, y, color=C[0], lw=0.6)\n", - "for k, v in enumerate([0.8 * 0.5 ** i for i in range(5)]):\n", + "marks = [np.abs(y[int(k * 0.5 * sr) : int((k + 1) * 0.5 * sr)]).max() for k in range(5)]\n", + "for k, v in enumerate(marks):\n", " ax.plot([k * 0.5, k * 0.5 + 0.25], [v, v], color=C[3], lw=1.2)\n", "ax.set_xlabel(\"time (s)\"); ax.set_ylabel(\"output\")\n", - "ax.set_title(\"decay 0.5: returns at 0.8, 0.4, 0.2, 0.1, 0.05 โ€” then retirement\")\n", + "ax.set_title(\"decay 0.5: each return half the previous peak โ€” then retirement\")\n", "plt.show()\n", "\n", "peaks = [np.abs(y[int(k * 0.5 * sr) : int((k + 1) * 0.5 * sr)]).max() for k in range(6)]\n", + "fund = [tone(y[int(k * 0.5 * sr) : int((k + 1) * 0.5 * sr)], 440.0) for k in range(5)]\n", "print(\"per-return peaks:\", [round(p, 3) for p in peaks])\n", + "print(\"fundamental ratios:\", [round(fund[k + 1] / fund[k], 3) for k in range(4)])\n", + "print(\"(peaks fade a shade faster than 0.5: quieter returns are also duller โ€” hardness)\")\n", "print(\"live events after the render:\", g.active_events)" ] }, { "cell_type": "markdown", - "id": "b1b7fbcd", + "id": "bf909eb9", "metadata": {}, "source": [ - "## 2 ยท Softening, in partials\n", + "## 2 ยท Softening, in modes\n", "\n", - "With `decay` held at 1.0 (velocity still) and `soften` 0.6, only the timbre moves: the FM\n", - "bell's first upper sideband (4ร— the fundamental, carrier + ratio-3 modulator) fades pass by\n", - "pass while the fundamental holds โ€” each return is *purer*, collapsing toward a sine. The\n", - "tape family's generation loss, restated in partials instead of passbands." + "With `decay` held at 1.0 (velocity still) and `soften` 0.6, only the timbre moves: the\n", + "chime's second mode (2.756ร— the fundamental โ€” the free-free bar ratio) fades pass by pass\n", + "while the fundamental holds โ€” each return is *purer*, the strike ringing further down\n", + "toward its fundamental. The tape family's generation loss, restated in modes instead of\n", + "passbands." ] }, { "cell_type": "code", "execution_count": 3, - "id": "58b22404", + "id": "e7913178", "metadata": { "execution": { - "iopub.execute_input": "2026-08-12T01:40:37.553851Z", - "iopub.status.busy": "2026-08-12T01:40:37.553571Z", - "iopub.status.idle": "2026-08-12T01:40:37.694273Z", - "shell.execute_reply": "2026-08-12T01:40:37.693228Z" + "iopub.execute_input": "2026-08-14T17:49:06.382776Z", + "iopub.status.busy": "2026-08-14T17:49:06.382566Z", + "iopub.status.idle": "2026-08-14T17:49:06.864027Z", + "shell.execute_reply": "2026-08-14T17:49:06.862820Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -158,64 +170,178 @@ "name": "stdout", "output_type": "stream", "text": [ - "sideband/fundamental per return: [np.float64(1.252), np.float64(0.546), np.float64(0.301), np.float64(0.175)]\n" + "mode2/fundamental per return: [np.float64(0.145), np.float64(0.087), np.float64(0.052), np.float64(0.031)]\n" ] } ], "source": [ - "g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, loop_seconds=0.5,\n", + "g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, spread=0, loop_seconds=0.5,\n", " decay=1.0, floor=0.001, soften=0.6, bell=(0.005, 0.06, 1.0), scale=0)\n", - "g.note(69, 0.8) # 440 Hz carrier -> first upper sideband at 1760 Hz\n", - "y = g.process(int(2.5 * sr))\n", + "g.note(69, 0.8) # 440 Hz fundamental -> second chime mode at 2.756x = 1212.6 Hz\n", + "y, _ = g.process(int(2.5 * sr))\n", "\n", "loop = int(0.5 * sr)\n", "passes = np.arange(4)\n", "fund = [tone(y[k * loop : k * loop + int(0.2 * sr)], 440.0) for k in passes]\n", - "side = [tone(y[k * loop : k * loop + int(0.2 * sr)], 1760.0) for k in passes]\n", + "side = [tone(y[k * loop : k * loop + int(0.2 * sr)], 440.0 * 2.756) for k in passes]\n", "\n", "fig, ax = plt.subplots()\n", "ax.plot(passes, fund, \"o-\", color=C[0], label=\"fundamental (440 Hz)\")\n", - "ax.plot(passes, side, \"s-\", color=C[1], label=\"FM sideband (1760 Hz)\")\n", + "ax.plot(passes, side, \"s-\", color=C[1], label=\"mode 2 (1212.6 Hz)\")\n", "ax.set_xticks(passes)\n", "ax.set_xlabel(\"return\"); ax.set_ylabel(\"partial level\")\n", - "ax.set_title(\"soften 0.6: the sideband fades, the fundamental holds โ€” purer every pass\")\n", + "ax.set_title(\"soften 0.6: the upper mode fades, the fundamental holds โ€” purer every pass\")\n", "ax.legend()\n", "plt.show()\n", "\n", - "print(\"sideband/fundamental per return:\",\n", + "print(\"mode2/fundamental per return:\",\n", " [round(s / f, 3) for s, f in zip(side, fund)])" ] }, { "cell_type": "markdown", - "id": "8144c147", + "id": "85555b0e", "metadata": {}, "source": [ - "## 3 ยท The scale contract, by the pitch oracle\n", + "## 3 ยท The rack: two materials, fixed flaws, fixed seats\n", + "\n", + "`material` swaps the mode-ratio table under every tube โ€” 0 is the wind-chime rack (the\n", + "free-free tube's 1 : 2.756 : 5.404 : 8.933), 1 the tuned bar (the mallet instrument's\n", + "double-octave 1 : 4 : 10 : 20) โ€” instant, and read at strike time, so live blooms re-voice\n", + "at their next return. And the tube is the identity: each pitch's upper modes sit a fixed\n", + "few cents off the ideal ratios (bounded by ยฑ3 cents; the fundamental stays true), and each\n", + "tube hangs at a fixed seat on the stereo rack, both drawn from a stateless hash of the\n", + "pitch โ€” no RNG consumed, so the seed triad below is untouched. Same tube: same flaws, same\n", + "seat, every strike, every instance. (Kernel scenarios: *\"material re-voices the rackโ€ฆ\"*,\n", + "*\"each tube's upper modes sit a fixed few cents offโ€ฆ\"*, *\"the rack is stereoโ€ฆ\"*.)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "db1ce7be", + "metadata": { + "execution": { + "iopub.execute_input": "2026-08-14T17:49:06.866244Z", + "iopub.status.busy": "2026-08-14T17:49:06.866058Z", + "iopub.status.idle": "2026-08-14T17:49:08.408116Z", + "shell.execute_reply": "2026-08-14T17:49:08.406904Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "chime material: level at 2.756f 0.0426 at 4f 0.0001\n", + "bar material: level at 2.756f 0.0002 at 4f 0.0236\n", + "tube 60: mode-2 scatter +1.25 cents โ€” the tube's own, every strike\n", + "tube 69: mode-2 scatter +2.75 cents โ€” the tube's own, every strike\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tube 76: mode-2 scatter -0.75 cents โ€” the tube's own, every strike\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tube 84: mode-2 scatter -2.25 cents โ€” the tube's own, every strike\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# (a) material: the second partial moves from 2.756x (chime) to 4x (bar)\n", + "def partials(material):\n", + " g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, spread=0, loop_seconds=2.0,\n", + " material=material, bell=(0.001, 0.5, 1.0), scale=0)\n", + " g.note(69, 0.9)\n", + " y, _ = g.process(int(0.2 * sr))\n", + " return tone(y, 440.0 * 2.756), tone(y, 440.0 * 4.0)\n", + "\n", + "for name, m in ((\"chime\", 0), (\"bar\", 1)):\n", + " a, b = partials(m)\n", + " print(f\"{name} material: level at 2.756f {a:.4f} at 4f {b:.4f}\")\n", + "\n", + "# (b) scatter: each tube's mode 2 sits its own fixed cents off โ€” scan a probe across it\n", + "def detune(pitch):\n", + " g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, spread=0, loop_seconds=2.0,\n", + " bell=(0.001, 0.5, 1.0), scale=0)\n", + " g.note(float(pitch), 0.9)\n", + " y, _ = g.process(int(0.25 * sr))\n", + " f2 = 440.0 * 2 ** ((pitch - 69) / 12) * 2.756\n", + " cs = np.arange(-6.0, 6.01, 0.25)\n", + " mags = [tone(y[int(0.01 * sr) : int(0.2 * sr)], f2 * 2 ** (c / 1200)) for c in cs]\n", + " return cs[int(np.argmax(mags))]\n", + "\n", + "for p in (60, 69, 76, 84):\n", + " print(f\"tube {p}: mode-2 scatter {detune(p):+.2f} cents โ€” the tube's own, every strike\")\n", + "\n", + "# (c) seats: at spread 1, each tube's left/right balance is keyed by its pitch\n", + "pitches = np.arange(57, 85)\n", + "shares = []\n", + "for p in pitches:\n", + " g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, spread=1.0, loop_seconds=2.0,\n", + " bell=(0.001, 0.1, 0.5), scale=0)\n", + " g.note(float(p), 0.8)\n", + " l, r = g.process(int(0.3 * sr))\n", + " shares.append(np.sum(r * r) / (np.sum(l * l) + np.sum(r * r)))\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.bar(pitches, np.asarray(shares) - 0.5, bottom=0.5, color=C[0], width=0.6)\n", + "ax.axhline(0.5, color=\"gray\", lw=0.8)\n", + "ax.set_ylim(0, 1)\n", + "ax.set_xlabel(\"MIDI pitch\"); ax.set_ylabel(\"right-bus energy share\")\n", + "ax.set_title(\"spread 1: every tube hangs at its own fixed seat โ€” a rack, not a panner\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "3ce381d5", + "metadata": {}, + "source": [ + "## 4 ยท The scale contract, by the pitch oracle\n", "\n", "Plant every chromatic pitch from 60 to 72 into a C major-pentatonic garden and measure what\n", "actually sounds with the DspTap YIN detector: every bloom lands on {C, D, E, G, A}, whatever\n", - "you planted. Quantization happens at entry โ€” the instrument makes wrong notes impossible,\n", + "you planted. The chime's upper modes are inharmonic, so the pitch oracle reads each strike in\n", + "its ring-down, where the fundamental is all that remains. Quantization happens at entry โ€”\n", + "the instrument makes wrong notes impossible,\n", "which is most of why Bloom-style instruments feel effortless. (Kernel scenario: *\"every\n", "bloom lands on the scale\"*.)" ] }, { "cell_type": "code", - "execution_count": 4, - "id": "26c3b65b", + "execution_count": 5, + "id": "2396b2b0", "metadata": { "execution": { - "iopub.execute_input": "2026-08-12T01:40:37.697003Z", - "iopub.status.busy": "2026-08-12T01:40:37.696639Z", - "iopub.status.idle": "2026-08-12T01:40:38.783825Z", - "shell.execute_reply": "2026-08-12T01:40:38.782751Z" + "iopub.execute_input": "2026-08-14T17:49:08.410422Z", + "iopub.status.busy": "2026-08-14T17:49:08.410225Z", + "iopub.status.idle": "2026-08-14T17:49:10.443934Z", + "shell.execute_reply": "2026-08-14T17:49:10.442861Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -236,11 +362,11 @@ "planted = np.arange(60, 73)\n", "sounded = []\n", "for p in planted:\n", - " g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, loop_seconds=2.0,\n", + " g = tap.Garden(sr, smooth_ms=0, idle_seconds=0, spread=0, loop_seconds=2.0,\n", " scale=3, root=0, bell=(0.01, 0.5, 0.4))\n", " g.note(float(p), 0.8)\n", - " y = g.process(int(0.5 * sr))\n", - " periods = tap.Yin().track(y[int(0.1 * sr):], hop=512)\n", + " y, _ = g.process(int(0.6 * sr))\n", + " periods = tap.Yin().track(y[int(0.25 * sr):], hop=512)\n", " hz = sr / np.median(periods[periods > 0])\n", " sounded.append(69 + 12 * np.log2(hz / 440.0))\n", "\n", @@ -261,28 +387,30 @@ }, { "cell_type": "markdown", - "id": "439fe0e1", + "id": "8addc1c3", "metadata": {}, "source": [ - "## 4 ยท The seeded gardener\n", + "## 5 ยท The seeded gardener is wind\n", "\n", - "Idle for half a second, then the garden plays itself: roughly one plant per loop pass,\n", - "uniformly placed, on the scale, within two octaves. The randomness rides the family's\n", - "seeded xorshift64* โ€” same seed, bit-identical garden; different seed, different garden;\n", - "gardener disabled, the seed cannot matter at all (the rng is never consumed). The library's\n", - "first randomized event source, with the tr808 seed triad as its contract." + "Idle for half a second, then the garden plays itself โ€” and the gardener is wind: strikes\n", + "arrive on a calm/gust cycle, each gust catching up to five neighboring tubes within a\n", + "fraction of a second (`gust` sizes the clusters; calms stretch so the average stays near\n", + "one strike per pass). The randomness rides the family's seeded xorshift64* โ€” same seed,\n", + "bit-identical garden; different seed, different garden; gardener disabled, the seed cannot\n", + "matter at all (the rng is never consumed). The library's first randomized event source,\n", + "with the tr808 seed triad as its contract." ] }, { "cell_type": "code", - "execution_count": 5, - "id": "2a44936a", + "execution_count": 6, + "id": "64cdab88", "metadata": { "execution": { - "iopub.execute_input": "2026-08-12T01:40:38.786156Z", - "iopub.status.busy": "2026-08-12T01:40:38.785963Z", - "iopub.status.idle": "2026-08-12T01:40:39.862934Z", - "shell.execute_reply": "2026-08-12T01:40:39.861747Z" + "iopub.execute_input": "2026-08-14T17:49:10.446407Z", + "iopub.status.busy": "2026-08-14T17:49:10.446216Z", + "iopub.status.idle": "2026-08-14T17:49:15.805823Z", + "shell.execute_reply": "2026-08-14T17:49:15.804537Z" } }, "outputs": [ @@ -295,7 +423,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -306,9 +434,9 @@ ], "source": [ "def render_idle(seed, seconds=8.0):\n", - " g = tap.Garden(sr, smooth_ms=0, idle_seconds=0.5, loop_seconds=1.0,\n", + " g = tap.Garden(sr, smooth_ms=0, idle_seconds=0.5, spread=0, loop_seconds=1.0,\n", " seed=seed, bell=(0.01, 0.6, 0.8), decay=0.7)\n", - " return g.process(int(seconds * sr))\n", + " return g.process(int(seconds * sr))[0] # spread 0: left is the render\n", "\n", "a = render_idle(1111)\n", "b = render_idle(1111)\n", @@ -329,12 +457,13 @@ }, { "cell_type": "markdown", - "id": "b6ed0434", + "id": "6c2dff62", "metadata": {}, "source": [ - "## 5 ยท An hour of garden, in two minutes\n", + "## 6 ยท An hour of garden, in two minutes\n", "\n", - "A handful of hand-planted notes to start, then the gardener takes over: `decay` 0.85 and\n", + "A handful of hand-planted notes to start, then the gardener takes over โ€” wind striking\n", + "chimes, literally now, across the stereo rack at `spread` 0.7: `decay` 0.85 and\n", "`soften` 0.9 keep each bloom returning for a dozen passes, softening as it goes; the\n", "population breathes around its converged size instead of piling up. This render would go on\n", "โ€” unrepeating, bounded, self-tending โ€” for exactly as long as you let it." @@ -342,20 +471,20 @@ }, { "cell_type": "code", - "execution_count": 6, - "id": "6de300a2", + "execution_count": 7, + "id": "201361b3", "metadata": { "execution": { - "iopub.execute_input": "2026-08-12T01:40:39.866122Z", - "iopub.status.busy": "2026-08-12T01:40:39.865857Z", - "iopub.status.idle": "2026-08-12T01:40:46.003609Z", - "shell.execute_reply": "2026-08-12T01:40:46.002440Z" + "iopub.execute_input": "2026-08-14T17:49:15.808134Z", + "iopub.status.busy": "2026-08-14T17:49:15.807859Z", + "iopub.status.idle": "2026-08-14T17:49:47.428417Z", + "shell.execute_reply": "2026-08-14T17:49:47.427272Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -367,7 +496,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "live events at the end: 20 ringing bells: 16\n" + "live events at the end: 23 ringing bells: 16\n" ] }, { @@ -375,7 +504,7 @@ "text/html": [ "\n", " \n", " " @@ -384,7 +513,7 @@ "" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -393,20 +522,23 @@ "from IPython.display import Audio\n", "\n", "g = tap.Garden(sr, smooth_ms=0, loop_seconds=6.0, decay=0.85, soften=0.9, floor=0.02,\n", - " bell=(0.12, 3.0, 0.9), scale=3, root=9, idle_seconds=4.0, seed=2008,\n", - " level=0.35)\n", + " bell=(0.006, 3.0, 0.9), scale=3, root=9, idle_seconds=4.0, gust=0.6, seed=2008,\n", + " spread=0.7, level=0.35)\n", "\n", - "chunks = []\n", + "left, right = [], []\n", "plants = [(0.0, 69, 0.7), (1.2, 76, 0.55), (2.6, 64, 0.6), (4.0, 81, 0.4)]\n", "cursor = 0.0\n", "for when, pitch, vel in plants:\n", " n = int((when - cursor) * sr)\n", " if n > 0:\n", - " chunks.append(g.process(n))\n", + " l, r = g.process(n)\n", + " left.append(l); right.append(r)\n", " g.note(pitch, vel)\n", " cursor = when\n", - "chunks.append(g.process(int((120.0 - cursor) * sr)))\n", - "y = np.concatenate(chunks)\n", + "l, r = g.process(int((120.0 - cursor) * sr))\n", + "left.append(l); right.append(r)\n", + "y_l, y_r = np.concatenate(left), np.concatenate(right)\n", + "y = 0.5 * (y_l + y_r) # the mono sum, for the RMS trace\n", "\n", "win = int(2.0 * sr)\n", "frames = y[: y.size // win * win].reshape(-1, win)\n", @@ -418,9 +550,10 @@ "plt.show()\n", "print(\"live events at the end:\", g.active_events, \" ringing bells:\", g.active_voices)\n", "\n", - "# Preview: first 60 s, embedded at 16 kHz to keep the executed notebook small (the bells\n", - "# live below 4 kHz); tools/render writes the full-rate, full-length WAVs.\n", - "Audio(np.clip(y[: int(60 * sr) : 3], -1, 1), rate=int(sr / 3))" + "# Preview: first 30 s in stereo โ€” the plants and the first gusts, the rack at spread 0.7 โ€”\n", + "# embedded at 16 kHz to keep the executed notebook at the house size (the bells live below\n", + "# 4 kHz); tools/render writes the full-rate, full-length WAVs.\n", + "Audio(np.clip(np.stack([y_l, y_r])[:, : int(30 * sr) : 3], -1, 1), rate=int(sr / 3))" ] } ], diff --git a/notebooks/taptools_py.py b/notebooks/taptools_py.py index 85e4d3e..29f1f60 100644 --- a/notebooks/taptools_py.py +++ b/notebooks/taptools_py.py @@ -303,16 +303,19 @@ def load() -> ctypes.CDLL: "taptools_garden_set_floor": ([vp, ctypes.c_double], ctypes.c_int), "taptools_garden_set_bell": ([vp, ctypes.c_double, ctypes.c_double, ctypes.c_double], ctypes.c_int), + "taptools_garden_set_material": ([vp, ctypes.c_int], ctypes.c_int), + "taptools_garden_set_spread": ([vp, ctypes.c_double], ctypes.c_int), "taptools_garden_set_root": ([vp, ctypes.c_int], ctypes.c_int), "taptools_garden_set_scale": ([vp, ctypes.c_int], ctypes.c_int), "taptools_garden_set_idle_seconds": ([vp, ctypes.c_double], ctypes.c_int), + "taptools_garden_set_gust": ([vp, ctypes.c_double], ctypes.c_int), "taptools_garden_set_seed": ([vp, ctypes.c_ulonglong], ctypes.c_int), "taptools_garden_set_level": ([vp, ctypes.c_double], ctypes.c_int), "taptools_garden_set_smooth_ms": ([vp, ctypes.c_double], ctypes.c_int), "taptools_garden_clear": ([vp], ctypes.c_int), "taptools_garden_active_events": ([vp], ctypes.c_int), "taptools_garden_active_voices": ([vp], ctypes.c_int), - "taptools_garden_process": ([vp, f64p, ctypes.c_int], ctypes.c_int), + "taptools_garden_process": ([vp, f64p, f64p, ctypes.c_int], ctypes.c_int), "taptools_yin_create": ([ctypes.c_int, ctypes.c_int, ctypes.c_int], vp), "taptools_yin_destroy": ([vp], None), "taptools_yin_frame_size": ([vp], ctypes.c_int), @@ -1248,11 +1251,14 @@ def __del__(self): class Garden: """tap.garden~'s kernel (tap::tools::garden::bed): a generative event - loop on the Bloom principle. Planted notes snap to the scale, bloom on a - two-operator FM bell, and return every loop pass a step quieter (decay) - and purer (soften) until they retire below the floor; left idle, a - seeded gardener plants for you. Scales: 0 chromatic, 1 major, 2 minor, - 3 major pentatonic, 4 minor pentatonic.""" + loop on the Bloom principle. Planted notes snap to the scale, strike a + small modal wind chime (mode ratios by material: 0 chime, the free-free + tube's 1 : 2.756 : 5.404 : 8.933; 1 bar, the tuned bar's 1 : 4 : 10 : 20), + and return every loop pass a step quieter (decay) and purer (soften) + until they retire below the floor; left idle, a seeded gardener plants + for you. Each tube hangs at a fixed stereo seat (width set by spread) + with its own fixed upper-mode scatter, both keyed by pitch. Scales: + 0 chromatic, 1 major, 2 minor, 3 major pentatonic, 4 minor pentatonic.""" def __init__(self, sr: float = 48000.0, **params): self._h = _LIB.taptools_garden_create() @@ -1260,14 +1266,18 @@ def __init__(self, sr: float = 48000.0, **params): self.set(**params) def set(self, *, loop_seconds=None, decay=None, soften=None, floor=None, bell=None, - root=None, scale=None, idle_seconds=None, seed=None, level=None, - smooth_ms=None) -> "Garden": + material=None, spread=None, root=None, scale=None, idle_seconds=None, gust=None, + seed=None, level=None, smooth_ms=None) -> "Garden": """`bell` takes an (attack_s, decay_s, brightness) triple.""" # configuration first, so ramped targets in the same call honor the new slew if smooth_ms is not None: _check(_LIB.taptools_garden_set_smooth_ms(self._h, float(smooth_ms)), "smooth_ms") if seed is not None: _check(_LIB.taptools_garden_set_seed(self._h, int(seed)), "seed") + if material is not None: + _check(_LIB.taptools_garden_set_material(self._h, int(material)), "material") + if spread is not None: + _check(_LIB.taptools_garden_set_spread(self._h, float(spread)), "spread") if root is not None: _check(_LIB.taptools_garden_set_root(self._h, int(root)), "root") if scale is not None: @@ -1288,6 +1298,8 @@ def set(self, *, loop_seconds=None, decay=None, soften=None, floor=None, bell=No if idle_seconds is not None: _check(_LIB.taptools_garden_set_idle_seconds(self._h, float(idle_seconds)), "idle_seconds") + if gust is not None: + _check(_LIB.taptools_garden_set_gust(self._h, float(gust)), "gust") if level is not None: _check(_LIB.taptools_garden_set_level(self._h, float(level)), "level") return self @@ -1306,11 +1318,14 @@ def active_events(self) -> int: def active_voices(self) -> int: return int(_LIB.taptools_garden_active_voices(self._h)) - def process(self, n: int) -> np.ndarray: - """Render n samples (a source: no input).""" - out = np.zeros(int(n)) - _check(_LIB.taptools_garden_process(self._h, _p64(out), out.size), "process") - return out + def process(self, n: int) -> tuple[np.ndarray, np.ndarray]: + """Render n samples of the stereo rack (a source: no input); + returns (left, right).""" + out_l = np.zeros(int(n)) + out_r = np.zeros(int(n)) + _check(_LIB.taptools_garden_process(self._h, _p64(out_l), _p64(out_r), out_l.size), + "process") + return out_l, out_r def clear(self) -> None: """Uproot everything; parameters are untouched.""" diff --git a/tests/garden_test.cpp b/tests/garden_test.cpp index 9b40f08..28d7330 100644 --- a/tests/garden_test.cpp +++ b/tests/garden_test.cpp @@ -24,14 +24,19 @@ namespace { constexpr double k_sr = 48000.0; using tap::tools::garden::bed; + using tap::tools::garden::k_mode_ratio; + using tap::tools::garden::material_bar; + using tap::tools::garden::material_chime; /// A quiet, instrument-neutral bed: idle gardener off, instant level, percussive bell so - /// grid promises are sharp. Tests opt into slow bells and idling explicitly. + /// grid promises are sharp, spread 0 so mono measurements read either bus. Tests opt into + /// slow bells, idling, and stereo explicitly. bed make() { bed g; g.prepare(k_sr); g.set_smooth_ms(0.0); g.set_idle_seconds(0.0); + g.set_spread(0.0); g.set_bell(0.001, 0.02, 1.0); g.set_scale(tap::tools::garden::scale_chromatic); return g; @@ -41,9 +46,11 @@ namespace { return static_cast(seconds * k_sr); } + /// Mono render onto the left bus โ€” every make() bed has spread 0, where left == right. void render(bed& g, std::vector& y) { for (auto& s : y) { - s = g.process(); + double right = 0.0; + g.process(s, right); } } @@ -133,21 +140,24 @@ SCENARIO("each return is quieter by the decay ratio and the bloom retires below std::vector y(at(2.5), 0.0); render(g, y); - // Velocity walks 0.8, 0.4, 0.2, 0.1, 0.05 and then retires: five audible returns. + // Velocity walks 0.8, 0.4, 0.2, 0.1, 0.05 and then retires: five audible returns. The + // decay ratio is pinned on the fundamental โ€” the whole strike fades a shade faster than + // velocity because quieter returns are also duller (the hardness coupling, pinned in its + // own scenario below). const size_t loop = at(0.25); - double prev = peak(y, 0, loop); + double prev = goertzel(y, 440.0, 0, loop); for (size_t k = 1; k <= 4; ++k) { - const double p = peak(y, k * loop, (k + 1) * loop); + const double p = goertzel(y, 440.0, k * loop, (k + 1) * loop); const double ratio = p / prev; - INFO("return " << k << ": peak " << p << ", ratio " << ratio); - CHECK(std::abs(ratio - 0.5) < 0.075); + INFO("return " << k << ": fundamental " << p << ", ratio " << ratio); + CHECK(std::abs(ratio - 0.5) < 0.05); prev = p; } REQUIRE(g.active_events() == 0); // retired below the floor REQUIRE(peak(y, 6 * loop, y.size()) < 1e-6); // and audibly gone } -SCENARIO("each return is purer: the fm partial fades by the soften ratio") { +SCENARIO("each return is purer: the upper chime modes fade by the soften ratio") { bed g = make(); g.set_loop_seconds(0.5); g.set_decay(1.0); // hold velocity still so only brightness moves @@ -155,17 +165,19 @@ SCENARIO("each return is purer: the fm partial fades by the soften ratio") { g.set_soften(0.6); g.set_bell(0.005, 0.06, 1.0); - g.note(69.0, 0.8); // 440 Hz carrier; first upper FM sideband at 4f = 1760 Hz + // 440 Hz fundamental; the chime's second mode rings at the free-free bar ratio 2.756. + g.note(69.0, 0.8); std::vector y(at(2.5), 0.0); render(g, y); - const size_t loop = at(0.5); + const double mode2 = 440.0 * k_mode_ratio[material_chime][1]; + const size_t loop = at(0.5); std::vector tilt; for (size_t k = 0; k <= 3; ++k) { const double fund = goertzel(y, 440.0, k * loop, k * loop + at(0.2)); - const double side = goertzel(y, 1760.0, k * loop, k * loop + at(0.2)); + const double side = goertzel(y, mode2, k * loop, k * loop + at(0.2)); tilt.push_back(side / fund); - INFO("return " << k << ": sideband/fundamental = " << side / fund); + INFO("return " << k << ": mode2/fundamental = " << side / fund); } for (size_t k = 1; k < tilt.size(); ++k) { CHECK(tilt[k] < tilt[k - 1]); // strictly purer every pass @@ -173,6 +185,130 @@ SCENARIO("each return is purer: the fm partial fades by the soften ratio") { CHECK(tilt.back() < 0.3 * tilt.front()); // and substantially so over three passes } +SCENARIO("the strike carries a tick that the returns lose") { + bed g = make(); + g.set_loop_seconds(1.0); + g.set_decay(1.0); // hold velocity: only soften moves the tick + g.set_floor(0.001); + g.set_soften(0.5); + g.set_bell(0.001, 1.0, 1.0); + + // The 4th bar mode (8.933f, ~3930 Hz here) is the contact tick: present at the strike, + // gone in tens of milliseconds (haste ~ f^2), and fading as b^3 across returns. + g.note(69.0, 0.9); + std::vector y(at(2.5), 0.0); + render(g, y); + + const double tick = 440.0 * k_mode_ratio[material_chime][3]; + const double at_strike = goertzel(y, tick, 0, at(0.05)); + const double late = goertzel(y, tick, at(0.2), at(0.4)); + INFO("tick at strike " << at_strike << ", 200-400 ms later " << late); + CHECK(at_strike > 10.0 * late); // confined to the contact + + const double tilt_0 = at_strike / goertzel(y, 440.0, 0, at(0.05)); + const double tilt_2 = goertzel(y, tick, 2 * at(1.0), 2 * at(1.0) + at(0.05)) + / goertzel(y, 440.0, 2 * at(1.0), 2 * at(1.0) + at(0.05)); + INFO("tick/fundamental at strike " << tilt_0 << ", at return 2 " << tilt_2); + CHECK(tilt_0 > 10.0 * tilt_2); // b^3: the returns lose their attack first +} + +SCENARIO("the tail beats: a struck tube is a doublet, not a lab sine") { + bed g = make(); + g.set_loop_seconds(4.0); + g.set_bell(0.001, 4.0, 0.0); // brightness 0: the fundamental pair alone + + g.note(69.0, 0.8); + std::vector y(at(3.0), 0.0); + render(g, y); + + // The pair starts aligned at the strike and beats at delta-f; the fundamental dips near + // the half-period null and recovers by the full period โ€” a beat, not a decay. + const double split = std::exp2(tap::tools::garden::k_doublet_cents / 2400.0); + const double df = 440.0 * (split - 1.0 / split); + const size_t null_at = at(0.5 / df); + const double m0 = goertzel(y, 440.0, at(0.1), at(0.3)); + const double m1 = goertzel(y, 440.0, null_at - at(0.1), null_at + at(0.1)); + const double m2 = goertzel(y, 440.0, 2 * null_at - at(0.1), 2 * null_at + at(0.1)); + INFO("fundamental early " << m0 << ", at the beat null " << m1 << ", recovered " << m2); + REQUIRE(std::isfinite(m1)); + CHECK(m1 < 0.3 * m0); // dips far below what the envelope alone would do + CHECK(m2 > 2.0 * m1); // and comes back: a beat, not a decay +} + +SCENARIO("a soft strike is duller than a hard one") { + auto tilt_at = [](double velocity) { + bed g = make(); + g.set_loop_seconds(2.0); + g.set_bell(0.001, 0.5, 1.0); + g.note(69.0, velocity); + std::vector y(at(0.2), 0.0); + render(g, y); + return goertzel(y, 440.0 * k_mode_ratio[material_chime][1], 0, at(0.15)) / goertzel(y, 440.0, 0, at(0.15)); + }; + + const double hard = tilt_at(0.9); + const double soft = tilt_at(0.25); + INFO("mode2/fundamental: hard strike " << hard << ", soft strike " << soft); + CHECK(hard > 1.3 * soft); // hardness couples brightness to velocity +} + +SCENARIO("small high tubes ring shorter than long low ones") { + auto retention = [](double pitch) { + bed g = make(); + g.set_loop_seconds(2.0); + g.set_bell(0.001, 1.0, 0.0); // the fundamental alone + g.note(pitch, 0.8); + std::vector y(at(1.0), 0.0); + render(g, y); + const double f = midi_hz(pitch); + return goertzel(y, f, at(0.8), at(1.0)) / goertzel(y, f, 0, at(0.2)); + }; + + const double low = retention(48.0); // ~131 Hz: ring time scaled up + const double high = retention(84.0); // ~1047 Hz: scaled down + INFO("late/early fundamental: low tube " << low << ", high tube " << high); + CHECK(low > 1.5 * high); +} + +SCENARIO("the wind arrives in gusts, and calm wind strikes singly") { + auto onsets = [](double gust) { + bed g = make(); + g.set_loop_seconds(1.0); + g.set_idle_seconds(0.2); + g.set_seed(7); + g.set_gust(gust); + g.set_decay(0.0); // plants retire after one sounding: only the wind counts + g.set_bell(0.001, 0.02, 1.0); // fast pings so strikes are separable + std::vector y(at(12.0), 0.0); + render(g, y); + std::vector found; + for (size_t i = at(0.01); i < y.size(); ++i) { + if (std::abs(y[i]) > 0.02 && peak(y, i - at(0.01), i) < 0.02) { + found.push_back(i); + } + } + return found; + }; + + const std::vector blustery = onsets(1.0); + const std::vector calm = onsets(0.0); + INFO("strikes: blustery " << blustery.size() << ", calm " << calm.size()); + REQUIRE(blustery.size() >= 4); + REQUIRE(calm.size() >= 3); + + bool clustered = false; + for (size_t i = 1; i < blustery.size(); ++i) { + clustered = clustered || (blustery[i] - blustery[i - 1] < at(0.35)); + } + CHECK(clustered); // at gust 1, some strikes tumble within a gust + + bool evenly = true; + for (size_t i = 1; i < calm.size(); ++i) { + evenly = evenly && (calm[i] - calm[i - 1] >= at(0.45)); + } + CHECK(evenly); // at gust 0, single strikes separated by at least the minimum calm +} + SCENARIO("every bloom lands on the scale") { // Off-scale and fractional plants, C major pentatonic: each must sound a scale member. const double planted[] = {61.0, 63.4, 66.0, 70.6}; @@ -181,7 +317,7 @@ SCENARIO("every bloom lands on the scale") { g.set_scale(tap::tools::garden::scale_major_pentatonic); g.set_root(0); g.set_loop_seconds(2.0); - g.set_bell(0.01, 0.5, 0.4); // gentle index keeps the fundamental dominant for yin + g.set_bell(0.01, 0.5, 0.4); // gentle brightness: the tail is the fundamental, where yin reads g.note(pitch, 0.8); std::vector y(at(0.5), 0.0); @@ -299,12 +435,18 @@ SCENARIO("the bell pool never exceeds its size and stays finite and bounded unde for (int i = 0; i < 2 * tap::tools::garden::k_voices; ++i) { g.note(48.0 + i, 0.9); for (int s = 0; s < 400; ++s) { - y.push_back(g.process()); + double left = 0.0; + double right = 0.0; + g.process(left, right); + y.push_back(left); } REQUIRE(g.active_voices() <= tap::tools::garden::k_voices); } while (y.size() < at(2.0)) { - y.push_back(g.process()); + double left = 0.0; + double right = 0.0; + g.process(left, right); + y.push_back(left); } // The hard bound is structural: k_voices bells, each |env * sin| <= 1, level 1. @@ -323,6 +465,122 @@ SCENARIO("the bell pool never exceeds its size and stays finite and bounded unde SCENARIO("unprepared, the garden is silent") { bed g; g.note(60.0, 1.0); // a safe no-op before prepare - REQUIRE(g.process() == 0.0); + double left = 1.0; + double right = 1.0; + g.process(left, right); + REQUIRE(left == 0.0); + REQUIRE(right == 0.0); REQUIRE(g.active_events() == 0); } + +SCENARIO("material re-voices the rack: chime partials at tube ratios, bar partials at double octaves") { + // The same strike through both mode tables: each material's second partial carries the + // energy and the other material's slot is empty (2.756f vs 4f โ€” 1213 Hz vs 1760 Hz here). + auto probe = [](int material) { + bed g = make(); + g.set_loop_seconds(2.0); + g.set_material(material); + g.set_bell(0.001, 0.5, 1.0); + g.note(69.0, 0.9); + std::vector y(at(0.2), 0.0); + render(g, y); + const double chime2 = goertzel(y, 440.0 * k_mode_ratio[material_chime][1], 0, at(0.15)); + const double bar2 = goertzel(y, 440.0 * k_mode_ratio[material_bar][1], 0, at(0.15)); + return std::make_pair(chime2, bar2); + }; + + const auto [chime_on_chime, bar_on_chime] = probe(material_chime); + const auto [chime_on_bar, bar_on_bar] = probe(material_bar); + INFO("chime material: 2.756f " << chime_on_chime << ", 4f " << bar_on_chime); + INFO("bar material: 2.756f " << chime_on_bar << ", 4f " << bar_on_bar); + CHECK(chime_on_chime > 5.0 * bar_on_chime); + CHECK(bar_on_bar > 5.0 * chime_on_bar); +} + +SCENARIO("each tube's upper modes sit a fixed few cents off โ€” the same cents every strike, different per tube") { + // The scatter is a property of the tube, not the strike: a stateless hash of (pitch, mode), + // so the detune is bounded by k_scatter_cents, identical across independent instances, and + // different from tube to tube. Measured by scanning a Goertzel probe across the second + // mode's neighborhood (the scan resolves ~0.25 cents on this window). + auto detune_of = [](double pitch) { + bed g = make(); + g.set_loop_seconds(2.0); + g.set_bell(0.001, 0.5, 1.0); + g.note(pitch, 0.9); + std::vector y(at(0.25), 0.0); + render(g, y); + const double ideal = midi_hz(pitch) * k_mode_ratio[material_chime][1]; + double best_cents = 0.0; + double best = 0.0; + for (int q = -24; q <= 24; ++q) { + const double c = 0.25 * static_cast(q); + const double m = goertzel(y, ideal * std::exp2(c / 1200.0), at(0.01), at(0.2)); + if (m > best) { + best = m; + best_cents = c; + } + } + return best_cents; + }; + + const double a = detune_of(69.0); + const double a_gain = detune_of(69.0); // an independent instance: the same tube, the same flaw + const double b = detune_of(84.0); + INFO("mode-2 detune: tube 69 " << a << " cents (again " << a_gain << "), tube 84 " << b); + CHECK(a == a_gain); + CHECK(std::abs(a) < tap::tools::garden::k_scatter_cents + 0.5); + CHECK(std::abs(b) < tap::tools::garden::k_scatter_cents + 0.5); + CHECK(std::abs(a - b) > 1.0); // a different tube is differently imperfect + // And the fundamental stays true: a maker tunes the fundamental (pinned via yin elsewhere; + // here, the scattered mode still beats around an in-tune first mode). + bed g = make(); + g.set_loop_seconds(2.0); + g.set_bell(0.01, 0.5, 0.4); + g.note(69.0, 0.8); + std::vector y(at(0.5), 0.0); + render(g, y); + CHECK(std::abs(cents(measure_hz(y, at(0.1)), 440.0)) < 5.0); +} + +SCENARIO("the rack is stereo: every tube keeps its seat, and spread 0 collapses to mono, bitwise") { + // spread 0: the two busses are bitwise identical (the sqrt equal-power seat at pan 0). + { + bed g = make(); + g.note(69.0, 0.8); + bool same = true; + for (size_t i = 0; i < at(0.5); ++i) { + double left = 0.0; + double right = 0.0; + g.process(left, right); + same = same && (left == right); + } + REQUIRE(same); + } + + // spread up: a tube's seat is a fixed property of its pitch โ€” the same left/right balance + // in every independent instance, and different tubes hang in different places. + auto seat_of = [](double pitch) { + bed g = make(); + g.set_spread(1.0); + g.set_loop_seconds(2.0); + g.note(pitch, 0.8); + double energy_l = 0.0; + double energy_r = 0.0; + for (size_t i = 0; i < at(0.5); ++i) { + double left = 0.0; + double right = 0.0; + g.process(left, right); + energy_l += left * left; + energy_r += right * right; + } + return energy_r / (energy_l + energy_r); + }; + + const double a = seat_of(69.0); + const double a_gain = seat_of(69.0); + const double b = seat_of(67.0); + INFO("right-bus energy share: tube 69 " << a << " (again " << a_gain << "), tube 67 " << b); + REQUIRE(a == a_gain); // the seat is the tube's, deterministically + CHECK(std::abs(a - b) > 0.1); // a different tube hangs somewhere else + CHECK(std::abs(a - 0.5) > 0.05); // and a full-spread seat is audibly off center +} diff --git a/tools/capi/taptools_capi.cpp b/tools/capi/taptools_capi.cpp index 2c6f165..e84c48c 100644 --- a/tools/capi/taptools_capi.cpp +++ b/tools/capi/taptools_capi.cpp @@ -1252,6 +1252,14 @@ int taptools_garden_set_bell(taptools_garden h, double attack_s, double decay_s, return with(h, [&](garden_bed& g) { g.set_bell(attack_s, decay_s, brightness); }); } +int taptools_garden_set_material(taptools_garden h, int material) { + return with(h, [&](garden_bed& g) { g.set_material(material); }); +} + +int taptools_garden_set_spread(taptools_garden h, double amount) { + return with(h, [&](garden_bed& g) { g.set_spread(amount); }); +} + int taptools_garden_set_root(taptools_garden h, int semitone) { return with(h, [&](garden_bed& g) { g.set_root(semitone); }); } @@ -1264,6 +1272,10 @@ int taptools_garden_set_idle_seconds(taptools_garden h, double s) { return with(h, [&](garden_bed& g) { g.set_idle_seconds(s); }); } +int taptools_garden_set_gust(taptools_garden h, double amount) { + return with(h, [&](garden_bed& g) { g.set_gust(amount); }); +} + int taptools_garden_set_seed(taptools_garden h, unsigned long long seed) { return with(h, [&](garden_bed& g) { g.set_seed(static_cast(seed)); }); } @@ -1294,11 +1306,11 @@ int taptools_garden_active_voices(taptools_garden h) { return static_cast(h)->active_voices(); } -int taptools_garden_process(taptools_garden h, double* out, int n) { - if (!out || n < 0) { +int taptools_garden_process(taptools_garden h, double* outL, double* outR, int n) { + if (!outL || !outR || n < 0) { return -1; } - return with(h, [&](garden_bed& g) { g.process(out, static_cast(n)); }); + return with(h, [&](garden_bed& g) { g.process(outL, outR, static_cast(n)); }); } } // extern "C" diff --git a/tools/capi/taptools_capi.h b/tools/capi/taptools_capi.h index c820714..47054e0 100644 --- a/tools/capi/taptools_capi.h +++ b/tools/capi/taptools_capi.h @@ -403,19 +403,22 @@ TAPTOOLS_API int taptools_garden_set_loop_seconds(taptools_garden h, double s); TAPTOOLS_API int taptools_garden_set_decay(taptools_garden h, double per_pass); // velocity/pass, 0..1 TAPTOOLS_API int taptools_garden_set_soften(taptools_garden h, double per_pass); // brightness/pass, 0..1 TAPTOOLS_API int taptools_garden_set_floor(taptools_garden h, double v); // retirement threshold -/// Bell envelope times in SECONDS + base brightness 0..1 (scales the FM index). +/// Bell envelope times in SECONDS + base brightness 0..1 (the upper modes' weight). TAPTOOLS_API int taptools_garden_set_bell(taptools_garden h, double attack_s, double decay_s, double brightness); +TAPTOOLS_API int taptools_garden_set_material(taptools_garden h, int material); // garden::material_index +TAPTOOLS_API int taptools_garden_set_spread(taptools_garden h, double amount); // rack width, 0 mono .. 1 TAPTOOLS_API int taptools_garden_set_root(taptools_garden h, int semitone); // 0..11, 0 = C TAPTOOLS_API int taptools_garden_set_scale(taptools_garden h, int scale); // garden::scale_index TAPTOOLS_API int taptools_garden_set_idle_seconds(taptools_garden h, double s); // 0 disables the gardener +TAPTOOLS_API int taptools_garden_set_gust(taptools_garden h, double amount); // wind: 0 even, 1 blustery TAPTOOLS_API int taptools_garden_set_seed(taptools_garden h, unsigned long long seed); TAPTOOLS_API int taptools_garden_set_level(taptools_garden h, double lin); TAPTOOLS_API int taptools_garden_set_smooth_ms(taptools_garden h, double ms); TAPTOOLS_API int taptools_garden_clear(taptools_garden h); TAPTOOLS_API int taptools_garden_active_events(taptools_garden h); // live blooms (-1 on bad handle) TAPTOOLS_API int taptools_garden_active_voices(taptools_garden h); // ringing bells (-1 on bad handle) -/// A source: renders n samples into out (mono). -TAPTOOLS_API int taptools_garden_process(taptools_garden h, double* out, int n); +/// A source: renders n samples of the stereo rack into outL/outR. +TAPTOOLS_API int taptools_garden_process(taptools_garden h, double* outL, double* outR, int n); #ifdef __cplusplus } diff --git a/tools/render/eno_render.cpp b/tools/render/eno_render.cpp index 3d8e4b8..b400bb2 100644 --- a/tools/render/eno_render.cpp +++ b/tools/render/eno_render.cpp @@ -7,8 +7,10 @@ /// Scenarios: `discreet_basic` (a phrase into the two-machine loop at regen 0.95), /// `discreet_sustain` (regen 1.0 with drive โ€” the Frippertronics wash, input faded /// out at the halfway mark), `airport_two_one` (seven incommensurate loops, stereo, -/// three minutes), `garden_played` (four planted notes recirculating to silence), -/// and `garden_idle` (the seeded gardener left alone for two minutes). +/// three minutes โ€” each loop holding one sung note from a small formant-synthesis +/// choir, since the "2/1" loops were voices), `garden_played` (four planted notes +/// recirculating to silence), and `garden_idle` (the seeded gardener left alone for +/// two minutes). /// /// Usage: eno_render [output-directory] (default: current directory) /// @author Timothy Place @@ -81,6 +83,102 @@ namespace { return 440.0 * std::exp2((pitch - 69.0) / 12.0); } + // ---- the "2/1" voice ---------------------------------------------------------------------- + // + // The Airports loops hold single sung notes, so the airport scenario's phrase model is a + // small choir "aah", not an organ tone: an additive harmonic series (1/k source rolloff) + // shaped by a five-formant vowel envelope, three detuned unison voices per phrase, and + // delayed-onset vibrato. Formant center/level/width values are the published singing- + // synthesis tables for the vowel "a" (tenor and alto rows as tabulated in the Csound + // manual's formant-values appendix, after Klatt's synthesizer tables). + + struct formant { + double hz; + double amp_db; + double bw; + }; + + constexpr formant k_tenor_a[5] = { + {650.0, 0.0, 80.0}, {1080.0, -6.0, 90.0}, {2650.0, -7.0, 120.0}, {2900.0, -8.0, 130.0}, {3250.0, -22.0, 140.0}}; + constexpr formant k_alto_a[5] = {{800.0, 0.0, 80.0}, + {1150.0, -4.0, 90.0}, + {2800.0, -20.0, 120.0}, + {3500.0, -36.0, 130.0}, + {4950.0, -60.0, 140.0}}; + + /// The vowel envelope sampled at frequency f: resonance-shaped peaks at the table's centers. + double vowel_gain(double f, const formant* table) { + double g = 0.0; + for (int i = 0; i < 5; ++i) { + const double sigma = table[i].bw; // the tabulated bandwidth as the peak's spread + const double d = (f - table[i].hz) / sigma; + g += std::pow(10.0, table[i].amp_db * 0.05) * std::exp(-0.5 * d * d); + } + return g; + } + + /// One sustained sung note: harmonic amplitudes precomputed from the vowel envelope, then + /// three unison voices (detuned a few cents, independent vibrato phases) rendered per sample. + class sung_note { + public: + sung_note(double hz, double dur, const formant* table, uint32_t seed) + : m_f0(hz) + , m_dur(dur) { + const int harmonics = std::min(40, static_cast(16000.0 / hz)); + double norm = 0.0; + for (int k = 1; k <= harmonics; ++k) { + const double a = vowel_gain(static_cast(k) * hz, table) / static_cast(k); + m_amp.push_back(a); + norm += a; + } + for (double& a : m_amp) { + a /= norm; + } + for (int v = 0; v < k_voices; ++v) { // per-voice detune and vibrato, seeded + seed = seed * 1664525u + 1013904223u; + m_detune[v] = std::exp2((static_cast(v - 1) * 5.5 + uniform(seed) * 1.5) / 1200.0); + m_vib_rate[v] = 4.8 + 0.35 * static_cast(v) + 0.2 * uniform(seed); + m_vib_phase[v] = 0.5 * (uniform(seed) + 1.0); + } + } + + double operator()(double t) const { + if (t < 0.0 || t >= m_dur) { + return 0.0; + } + // The long swell of a held note: slow rise, gentle release. + const double env = std::pow(std::sin(k_g_pi * std::min(t / (0.7 * m_dur), 1.0)), 2.0); + // Vibrato arrives after the onset, the way singers land a note and then warm it. + const double warm = std::min(t / 1.2, 1.0); + double sum = 0.0; + for (int v = 0; v < k_voices; ++v) { + const double f0 = m_f0 * m_detune[v]; + const double depth = 0.0035 * warm; // ~6 cents peak, grown over the first second + // Closed-form phase of a sinusoidally modulated oscillator. + const double phase = f0 * t + - depth * f0 / m_vib_rate[v] + * (std::cos(2.0 * k_g_pi * (m_vib_rate[v] * t + m_vib_phase[v])) + - std::cos(2.0 * k_g_pi * m_vib_phase[v])) + / (2.0 * k_g_pi); + for (size_t k = 0; k < m_amp.size(); ++k) { + sum += m_amp[k] * std::sin(2.0 * k_g_pi * static_cast(k + 1) * phase); + } + } + return env * sum / static_cast(k_voices); + } + + private: + static double uniform(uint32_t s) { return (static_cast(s) / 2147483648.0) - 1.0; } + + static constexpr int k_voices = 3; + double m_f0; + double m_dur; + std::vector m_amp; + double m_detune[k_voices]{}; + double m_vib_rate[k_voices]{}; + double m_vib_phase[k_voices]{}; + }; + void discreet_basic(const std::string& dir) { tap::tools::discreet::machine m; m.prepare(k_g_sr, 10.0); @@ -154,13 +252,16 @@ namespace { stereo.reserve(static_cast(180.0 * k_g_sr) * 2); double l = 0.0, r = 0.0; - // Record one phrase onto each loop in turn, then let the system run free. + // Record one sung note onto each loop in turn, then let the system run free. Lower + // pitches take the tenor "a" table, upper ones the alto โ€” a small mixed choir. for (int i = 0; i < 7; ++i) { - const double dur = 0.55 * lengths[i]; + const double dur = 0.62 * lengths[i]; + const sung_note voice(midi_hz(pitches[i]), dur, (pitches[i] < 63.0) ? k_tenor_a : k_alto_a, + static_cast(1978 + 17 * i)); b.record(i, true); const size_t n = static_cast(dur * k_g_sr); for (size_t s = 0; s < n; ++s) { - b.process(phrase_tone(static_cast(s) / k_g_sr, dur, midi_hz(pitches[i])), l, r); + b.process(0.85 * voice(static_cast(s) / k_g_sr), l, r); stereo.push_back(l); stereo.push_back(r); } @@ -180,24 +281,25 @@ namespace { g.set_loop_seconds(5.0); g.set_decay(0.8); g.set_soften(0.85); - g.set_bell(0.1, 2.5, 0.9); + g.set_bell(0.005, 2.5, 0.9); // a real strike: the chime rings, not swells g.set_scale(tap::tools::garden::scale_major_pentatonic); g.set_root(9); g.set_idle_seconds(0.0); // played only: no gardener in this render g.set_level(0.4); const double plants[][3] = {{69, 0.7, 0.2}, {76, 0.5, 1.7}, {64, 0.6, 3.4}, {81, 0.4, 4.6}}; - std::vector y(static_cast(75.0 * k_g_sr)); + const size_t frames = static_cast(75.0 * k_g_sr); + std::vector stereo(2 * frames); size_t next = 0; - for (size_t i = 0; i < y.size(); ++i) { + for (size_t i = 0; i < frames; ++i) { const double t = static_cast(i) / k_g_sr; if (next < 4 && t >= plants[next][2]) { g.note(plants[next][0], plants[next][1]); ++next; } - y[i] = g.process(); + g.process(stereo[2 * i], stereo[2 * i + 1]); } - write_wav(dir + "/garden_played.wav", y, k_g_sr); + write_wav(dir + "/garden_played.wav", stereo, k_g_sr, 2); } void garden_idle(const std::string& dir) { @@ -206,18 +308,20 @@ namespace { g.set_loop_seconds(6.0); g.set_decay(0.85); g.set_soften(0.9); - g.set_bell(0.12, 3.0, 0.9); + g.set_bell(0.006, 3.0, 0.9); g.set_scale(tap::tools::garden::scale_minor_pentatonic); g.set_root(2); g.set_idle_seconds(3.0); + g.set_gust(0.7); // a proper breeze: clustered strikes, longer calms g.set_seed(2008); g.set_level(0.4); - std::vector y(static_cast(120.0 * k_g_sr)); - for (auto& s : y) { - s = g.process(); + const size_t frames = static_cast(120.0 * k_g_sr); + std::vector stereo(2 * frames); + for (size_t i = 0; i < frames; ++i) { + g.process(stereo[2 * i], stereo[2 * i + 1]); } - write_wav(dir + "/garden_idle.wav", y, k_g_sr); + write_wav(dir + "/garden_idle.wav", stereo, k_g_sr, 2); } } // namespace