noise

class BrownNoise(*, calculation_rate: CalculationRate | SupportsInt | str | None, **kwargs)

Bases: UGen

A brown noise unit generator.

>>> supriya.ugens.BrownNoise.ar()
<BrownNoise.ar()[0]>
classmethod ar() → UGenOperable
classmethod kr() → UGenOperable
class ClipNoise(*, calculation_rate: CalculationRate | SupportsInt | str | None, **kwargs)

Bases: UGen

A clipped noise unit generator.

>>> supriya.ugens.ClipNoise.ar()
<ClipNoise.ar()[0]>
classmethod ar() → UGenOperable
classmethod kr() → UGenOperable
class CoinGate(*, calculation_rate: CalculationRate | SupportsInt | str | None, probability: SupportsFloat | UGenScalar = 0.5, trigger: SupportsFloat | UGenScalar, **kwargs)

Bases: UGen

A probabilistic trigger gate.

>>> trigger = supriya.ugens.Impulse.ar()
>>> coin_gate = supriya.ugens.CoinGate.ar(
...     probability=0.5,
...     trigger=trigger,
... )
>>> coin_gate
<CoinGate.ar()[0]>
classmethod ar(*, probability: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.5, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]]) → UGenOperable
classmethod kr(*, probability: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.5, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]]) → UGenOperable
property probability : UGenScalar
property trigger : UGenScalar
class Crackle(*, calculation_rate: CalculationRate | SupportsInt | str | None, chaos_parameter: SupportsFloat | UGenScalar = 1.5, **kwargs)

Bases: UGen

A chaotic noise generator.

>>> crackle = supriya.ugens.Crackle.ar(
...     chaos_parameter=1.25,
... )
>>> crackle
<Crackle.ar()[0]>
classmethod ar(*, chaos_parameter: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.5) → UGenOperable
classmethod kr(*, chaos_parameter: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.5) → UGenOperable
property chaos_parameter : UGenScalar
class Dust(*, calculation_rate: CalculationRate | SupportsInt | str | None, density: SupportsFloat | UGenScalar = 0.0, **kwargs)

Bases: UGen

A unipolar random impulse generator.

>>> dust = supriya.ugens.Dust.ar(
...     density=23,
... )
>>> dust
<Dust.ar()[0]>
classmethod ar(*, density: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0) → UGenOperable
classmethod kr(*, density: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0) → UGenOperable
property density : UGenScalar
class Dust2(*, calculation_rate: CalculationRate | SupportsInt | str | None, density: SupportsFloat | UGenScalar = 0.0, **kwargs)

Bases: UGen

A bipolar random impulse generator.

>>> dust_2 = supriya.ugens.Dust2.ar(
...     density=23,
... )
>>> dust_2
<Dust2.ar()[0]>
classmethod ar(*, density: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0) → UGenOperable
classmethod kr(*, density: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0) → UGenOperable
property density : UGenScalar
class ExpRand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0.0, maximum: SupportsFloat | UGenScalar = 1.0, **kwargs)

Bases: UGen

An exponential random distribution.

>>> exp_rand = supriya.ugens.ExpRand.ir()
>>> exp_rand
<ExpRand.ir()[0]>
classmethod ir(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
class GrayNoise(*, calculation_rate: CalculationRate | SupportsInt | str | None, **kwargs)

Bases: UGen

A gray noise unit generator.

>>> supriya.ugens.GrayNoise.ar()
<GrayNoise.ar()[0]>
classmethod ar() → UGenOperable
classmethod kr() → UGenOperable
class Hasher(*, calculation_rate: CalculationRate | SupportsInt | str | None, source: SupportsFloat | UGenScalar, **kwargs)

Bases: UGen

A signal hasher.

>>> source = supriya.ugens.SinOsc.ar()
>>> hasher = supriya.ugens.Hasher.ar(
...     source=source,
... )
>>> hasher
<Hasher.ar()[0]>
classmethod ar(*, source: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]]) → UGenOperable
classmethod kr(*, source: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]]) → UGenOperable
property source : UGenScalar
class IRand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0, maximum: SupportsFloat | UGenScalar = 127, **kwargs)

Bases: UGen

An integer uniform random distribution.

>>> supriya.ugens.IRand.ir()
<IRand.ir()[0]>
classmethod ir(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 127) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
class LFClipNoise(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A dynamic clipped noise generator.

>>> supriya.ugens.LFClipNoise.ar()
<LFClipNoise.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LFDClipNoise(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A clipped noise generator.

>>> supriya.ugens.LFDClipNoise.ar()
<LFDClipNoise.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LFDNoise0(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A dynamic step noise generator.

>>> supriya.ugens.LFDNoise0.ar()
<LFDNoise0.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LFDNoise1(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A dynamic ramp noise generator.

>>> supriya.ugens.LFDNoise1.ar()
<LFDNoise1.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LFDNoise3(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A dynamic polynomial noise generator.

>>> supriya.ugens.LFDNoise3.ar()
<LFDNoise3.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LFNoise0(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A step noise generator.

>>> supriya.ugens.LFNoise0.ar()
<LFNoise0.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LFNoise1(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A ramp noise generator.

>>> supriya.ugens.LFNoise1.ar()
<LFNoise1.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LFNoise2(*, calculation_rate: CalculationRate | SupportsInt | str | None, frequency: SupportsFloat | UGenScalar = 500.0, **kwargs)

Bases: UGen

A quadratic noise generator.

>>> supriya.ugens.LFNoise2.ar()
<LFNoise2.ar()[0]>
classmethod ar(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
classmethod kr(*, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 500.0) → UGenOperable
property frequency : UGenScalar
class LinRand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0.0, maximum: SupportsFloat | UGenScalar = 1.0, skew: SupportsFloat | UGenScalar = 0, **kwargs)

Bases: UGen

A skewed linear random distribution.

>>> lin_rand = supriya.ugens.LinRand.ir(
...     minimum=-1.0,
...     maximum=1.0,
...     skew=0.5,
... )
>>> lin_rand
<LinRand.ir()[0]>
classmethod ir(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0, skew: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
property skew : UGenScalar
class Logistic(*, calculation_rate: CalculationRate | SupportsInt | str | None, chaos_parameter: SupportsFloat | UGenScalar = 3, frequency: SupportsFloat | UGenScalar = 1000, initial_y: SupportsFloat | UGenScalar = 0.5, **kwargs)

Bases: UGen

A chaotic noise function.

>>> logistic = supriya.ugens.Logistic.ar(
...     chaos_parameter=3.0,
...     frequency=1000,
...     initial_y=0.5,
... )
>>> logistic
<Logistic.ar()[0]>
classmethod ar(*, chaos_parameter: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 3, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1000, initial_y: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.5) → UGenOperable
classmethod kr(*, chaos_parameter: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 3, frequency: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1000, initial_y: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.5) → UGenOperable
property chaos_parameter : UGenScalar
property frequency : UGenScalar
property initial_y : UGenScalar
class MantissaMask(*, calculation_rate: CalculationRate | SupportsInt | str | None, source: SupportsFloat | UGenScalar = 0, bits: SupportsFloat | UGenScalar = 3, **kwargs)

Bases: UGen

A floating-point mantissa mask.

>>> source = supriya.ugens.SinOsc.ar()
>>> mantissa_mask = supriya.ugens.MantissaMask.ar(
...     source=source,
...     bits=3,
... )
>>> mantissa_mask
<MantissaMask.ar()[0]>
classmethod ar(*, source: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, bits: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 3) → UGenOperable
classmethod kr(*, source: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, bits: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 3) → UGenOperable
property bits : UGenScalar
property source : UGenScalar
class NRand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0.0, maximum: SupportsFloat | UGenScalar = 1.0, n: SupportsFloat | UGenScalar = 1, **kwargs)

Bases: UGen

A sum of n uniform distributions.

>>> n_rand = supriya.ugens.NRand.ir(
...     minimum=-1,
...     maximum=1,
...     n=1,
... )
>>> n_rand
<NRand.ir()[0]>
classmethod ir(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0, n: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
property n : UGenScalar
class PinkNoise(*, calculation_rate: CalculationRate | SupportsInt | str | None, **kwargs)

Bases: UGen

A pink noise unit generator.

>>> supriya.ugens.PinkNoise.ar()
<PinkNoise.ar()[0]>
classmethod ar() → UGenOperable
classmethod kr() → UGenOperable
class Rand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0.0, maximum: SupportsFloat | UGenScalar = 1.0, **kwargs)

Bases: UGen

A uniform random distribution.

>>> supriya.ugens.Rand.ir()
<Rand.ir()[0]>
classmethod ir(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
class RandID(*, calculation_rate: CalculationRate | SupportsInt | str | None, rand_id: SupportsFloat | UGenScalar = 1, **kwargs)

Bases: UGen

Sets the synth’s random generator ID.

>>> rand_id = supriya.ugens.RandID.ir(
...     rand_id=1,
... )
>>> rand_id
<RandID.ir()[0]>
classmethod ir(*, rand_id: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1) → UGenOperable
classmethod kr(*, rand_id: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1) → UGenOperable
property rand_id : UGenScalar
class RandSeed(*, calculation_rate: CalculationRate | SupportsInt | str | None, trigger: SupportsFloat | UGenScalar = 0, seed: SupportsFloat | UGenScalar = 56789, **kwargs)

Bases: UGen

Sets the synth’s random generator seed.

>>> trigger = supriya.ugens.Impulse.ar()
>>> rand_seed = supriya.ugens.RandSeed.ar(
...     seed=1,
...     trigger=trigger,
... )
>>> rand_seed
<RandSeed.ar()[0]>
classmethod ar(*, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, seed: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 56789) → UGenOperable
classmethod ir(*, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, seed: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 56789) → UGenOperable
classmethod kr(*, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, seed: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 56789) → UGenOperable
property seed : UGenScalar
property trigger : UGenScalar
class TExpRand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0.01, maximum: SupportsFloat | UGenScalar = 1.0, trigger: SupportsFloat | UGenScalar = 0, **kwargs)

Bases: UGen

A triggered exponential random number generator.

>>> trigger = supriya.ugens.Impulse.ar()
>>> t_exp_rand = supriya.ugens.TExpRand.ar(
...     minimum=-1.0,
...     maximum=1.0,
...     trigger=trigger,
... )
>>> t_exp_rand
<TExpRand.ar()[0]>
classmethod ar(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.01, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0) → UGenOperable
classmethod kr(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.01, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
property trigger : UGenScalar
class TIRand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0, maximum: SupportsFloat | UGenScalar = 127, trigger: SupportsFloat | UGenScalar = 0, **kwargs)

Bases: UGen

A triggered integer random number generator.

>>> trigger = supriya.ugens.Impulse.ar()
>>> t_i_rand = supriya.ugens.TIRand.ar(
...     minimum=0,
...     maximum=127,
...     trigger=trigger,
... )
>>> t_i_rand
<TIRand.ar()[0]>
classmethod ar(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 127, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0) → UGenOperable
classmethod kr(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 127, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
property trigger : UGenScalar
class TRand(*, calculation_rate: CalculationRate | SupportsInt | str | None, minimum: SupportsFloat | UGenScalar = 0.0, maximum: SupportsFloat | UGenScalar = 1.0, trigger: SupportsFloat | UGenScalar = 0, **kwargs)

Bases: UGen

A triggered random number generator.

>>> trigger = supriya.ugens.Impulse.ar()
>>> t_rand = supriya.ugens.TRand.ar(
...     minimum=-1.0,
...     maximum=1.0,
...     trigger=trigger,
... )
>>> t_rand
<TRand.ar()[0]>
classmethod ar(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0) → UGenOperable
classmethod kr(*, minimum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0.0, maximum: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 1.0, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0) → UGenOperable
property maximum : UGenScalar
property minimum : UGenScalar
property trigger : UGenScalar
class TWindex(*, calculation_rate: CalculationRate | SupportsInt | str | None, trigger: SupportsFloat | UGenScalar, normalize: SupportsFloat | UGenScalar = 0, array: UGenSerializable | Sequence[SupportsFloat | UGenScalar], **kwargs)

Bases: UGen

A triggered windex.

>>> trigger = supriya.ugens.Impulse.ar()
>>> t_windex = supriya.ugens.TWindex.ar(
...     trigger=trigger,
...     normalize=0,
...     array=[1, 2, 3],
... )
>>> t_windex
<TWindex.ar()[0]>
classmethod ar(*, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]], normalize: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, array: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]]) → UGenOperable
classmethod kr(*, trigger: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]], normalize: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]] = 0, array: SupportsFloat | UGenOperable | UGenSerializable | Sequence[SupportsFloat | UGenOperable | UGenSerializable | Sequence[UGenRecursiveInput]]) → UGenOperable
property array : UGenVector
property normalize : UGenScalar
property trigger : UGenScalar
class WhiteNoise(*, calculation_rate: CalculationRate | SupportsInt | str | None, **kwargs)

Bases: UGen

A white noise unit generator.

>>> supriya.ugens.WhiteNoise.ar()
<WhiteNoise.ar()[0]>
classmethod ar() → UGenOperable
classmethod kr() → UGenOperable