Index

A | B | C | D | E | F | G | I | J | L | M | N | O | P | Q | R | S | T | U | V

A

add() (probability.gaussian.GaussianAccumulator method)
addFromSampler() (probability.gaussian.GaussianAccumulator method)
AlwaysProposer (class in noise.sample_observation_density)
AlwaysSampler (class in probability.sampler)
appendChannelPhase() (in module noise.factor_integrand)
appendSubstitute() (in module noise.factor_integrand)
appendToTuple() (in module probability.sequential_importance_resample)
appendToVector() (in module probability.sequential_importance_resample)

B

BoundFunctionPromise (class in promise.promise)

C

Categorical (class in probability.categorical)
computeHash() (promise.promise.Promise method)
ConditionalDistribution (built-in class)
consistentHash() (in module tools.consistent_hash)
CorruptedSpeechSampler (class in noise.corrupted_speech_sampler)

D

dct() (in module speech.dct)
deltas() (probability.categorical.Categorical method)
density() (noise.sample_observation_density.SampleObservationDensity method)
(ProbabilityDistribution method)
(probability.gaussian.Gaussian method)
(probability.mixture.Mixture method)
(probability.uniform.Uniform method)
densityWeighter() (in module probability.sequential_importance_resample)
determinant() (in module tools.linear_algebra)
diagonaliseCepstral() (in module speech.diagonalise_cepstral)
distribution() (probability.gaussian.GaussianAccumulator method)
dpmcCompensate() (in module noise.dpmc)
drop() (in module tools.iterator_tools)
DummyFactor (class in noise.sample_observation_density)

E

evaluate() (promise.fulfill.MemoFulfill method)
(promise.promise.Promise method)

F

factorise() (probability.mixture.Mixture method)
factoriseGaussian() (in module probability.gaussian)
factoriseGaussianCompletely() (in module probability.gaussian)
FulfillDisk (class in promise.fulfill_disk)
FunctionPromise (class in promise.promise)

G

Gaussian (class in probability.gaussian)
GaussianAccumulator (class in probability.gaussian)
getAll() (promise.promise.Promise method)
getCovariance() (probability.gaussian.Gaussian method)
getExponent() (probability.log_float.LogFloat method)
getParentClasses() (promise.promise.Promise method)
getPrecision() (probability.gaussian.Gaussian method)
getShallow() (promise.promise.Promise method)
getUnrememberedPromises() (promise.fulfill.MemoFulfill method)
given() (ConditionalDistribution method)
(noise.factor_integrand.PostponedFactorGenerator method)
(noise.factor_integrand.QuasiConditionalFactorGenerator method)
(noise.sample_observation_density.DummyFactor method)

I

IncrementalSystematicSampler (class in probability.sampler)
inverse() (in module tools.linear_algebra)

J

joinGaussians() (in module probability.gaussian)

L

log() (in module probability.log_float)
LogFloat (class in probability.log_float)

M

makePath() (promise.fulfill_disk.FulfillDisk method)
makeStandardNumeric() (in module probability.log_float)
mass() (probability.mixture.Mixture method)
(ProbabilityDistribution method)
massWeighter() (in module probability.sequential_importance_resample)
melFilter() (in module speech.mel_filter)
melFilterVariance() (in module noise.phase_factor_gaussian)
MemoFulfill (class in promise.fulfill)
Mixture (class in probability.mixture)
multinomialResampling() (in module probability.categorical)

N

noiseFrom() (in module noise.noise_environment)

O

observationFrom() (in module noise.noise_environment)
oneWeighter() (in module noise.sample_observation_density)

P

parents() (promise.promise.Promise method)
PartialSample (class in noise.factor_integrand)
path() (promise.fulfill_disk.FulfillDisk method)
PhaseFactorGaussianSampler (class in noise.phase_factor_gaussian)
PhaseProposer (class in noise.sample_observation_density)
pickleableClone() (promise.fulfill_disk.FulfillDisk method)
PostponedFactorGenerator (class in noise.factor_integrand)
printState() (probability.sampler.UniformUnitSampler method)
ProbabilityDistribution (built-in class)
Promise (class in promise.promise)
PromiseProxy (class in promise.promise)
proposalForFactor() (in module noise.factor_integrand)

Q

QuasiConditionalFactorGenerator (class in noise.factor_integrand)

R

readGaussian() (in module speech.model)
remember() (promise.fulfill.MemoFulfill method)
remembered() (promise.fulfill.MemoFulfill method)
resample() (in module probability.categorical)
residualResampling() (in module probability.categorical)
retrieve() (promise.fulfill.MemoFulfill method)

S

SampleObservationDensity (class in noise.sample_observation_density)
sampler() (Categorical method)
(Gaussian method)
(Mixture method)
(ProbabilityDistribution method)
(probability.uniform.Uniform method)
scanl() (in module tools.iterator_tools)
seed() (probability.sampler.UniformUnitSampler method)
sequentialImportanceResample() (in module probability.sequential_importance_resample)
showProgress() (in module tools.progress)
speechFrom() (in module noise.noise_environment)
splitGaussian() (in module probability.gaussian)
SubstituteFactor (class in noise.factor_integrand)
SubstituteFactorOneSource (class in noise.factor_integrand)
substituteFrom() (in module noise.noise_environment)
systematicResampling() (in module probability.categorical)

T

take() (in module tools.iterator_tools)
trainGaussianMixtureFromScratch() (in module probability.mix_up)
trainMixture() (in module probability.mix_up)

U

Uniform (class in probability.uniform)
UniformUnitSampler (class in probability.sampler)
UnitGaussianSampler (class in probability.sampler)
unitWeightSamples() (probability.categorical.Categorical method)
unnormalisedComponents() (probability.mixture.Mixture method)
unnormalisedDensity() (noise.factor_integrand.SubstituteFactor method)
(noise.factor_integrand.SubstituteFactorOneSource method)
(probability.gaussian.Gaussian method)
unnormalisedDensityWeighter() (in module probability.sequential_importance_resample)

V

ValuePromise (class in promise.promise)
vtsCompensate() (in module noise.vts)