stats.svGPFA package

Submodules

stats.svGPFA.expectedLogLikelihood module

class stats.svGPFA.expectedLogLikelihood.ExpectedLogLikelihood(svEmbeddingAllTimes)[source]

Bases: abc.ABC

abstract buildKernelsMatrices()[source]
abstract computeSVPosteriorOnLatentsStats()[source]
abstract evalSumAcrossTrialsAndNeurons(svPosteriorOnLatentsStats=None)[source]
getIndPointsLocs()[source]
getKernelsParams()[source]
getSVEmbeddingParams()[source]
getSVPosteriorOnIndPointsParams()[source]
predictLatents(newTimes)[source]
abstract setIndPointsLocs(locs)[source]
abstract setInitialParams(initialParams)[source]
abstract setKernels(kernels)[source]
abstract setMeasurements(measurements)[source]
abstract setQuadParams(quadParams)[source]
class stats.svGPFA.expectedLogLikelihood.PointProcessELL(svEmbeddingAllTimes, svEmbeddingAssocTimes)[source]

Bases: stats.svGPFA.expectedLogLikelihood.ExpectedLogLikelihood

buildKernelsMatrices()[source]
computeSVPosteriorOnLatentsStats()[source]
evalSumAcrossTrialsAndNeurons(svPosteriorOnLatentsStats=None)[source]
setIndPointsLocs(locs)[source]
setInitialParams(initialParams)[source]
setKernels(kernels)[source]
setMeasurements(measurements)[source]
setQuadParams(quadParams)[source]

Bases: stats.svGPFA.expectedLogLikelihood.PointProcessELL

class stats.svGPFA.expectedLogLikelihood.PointProcessELLQuad(svEmbeddingAllTimes, svEmbeddingAssocTimes, linkFunction)[source]

Bases: stats.svGPFA.expectedLogLikelihood.PointProcessELL

setQuadParams(quadParams)[source]
class stats.svGPFA.expectedLogLikelihood.PoissonELL(svEmbeddingAllTimes)[source]

Bases: stats.svGPFA.expectedLogLikelihood.ExpectedLogLikelihood

buildKernelsMatrices()[source]
computeSVPostOnLatentsStats()[source]
evalSumAcrossTrialsAndNeurons(svPosteriorOnLatentsStats=None)[source]
setIndPointsLocs(locs)[source]
setInitialParams(initialParams)[source]
setKernels(kernels)[source]
setMeasurements(measurements)[source]
setMiscParams(miscParams)[source]

Bases: stats.svGPFA.expectedLogLikelihood.PoissonELL

class stats.svGPFA.expectedLogLikelihood.PoissonELLQuad(svEmbeddingAllTime, linkFunction)[source]

Bases: stats.svGPFA.expectedLogLikelihood.PoissonELL

stats.svGPFA.kernelMatricesStore module

class stats.svGPFA.kernelMatricesStore.IndPointsLocsAndAllTimesKMS[source]

Bases: stats.svGPFA.kernelMatricesStore.IndPointsLocsAndTimesKMS

buildKernelsMatrices()[source]
class stats.svGPFA.kernelMatricesStore.IndPointsLocsAndAssocTimesKMS[source]

Bases: stats.svGPFA.kernelMatricesStore.IndPointsLocsAndTimesKMS

buildKernelsMatrices()[source]
class stats.svGPFA.kernelMatricesStore.IndPointsLocsAndTimesKMS[source]

Bases: stats.svGPFA.kernelMatricesStore.KernelMatricesStore

getKtt()[source]
getKtz()[source]
setTimes(times)[source]
class stats.svGPFA.kernelMatricesStore.IndPointsLocsKMS[source]

Bases: stats.svGPFA.kernelMatricesStore.KernelMatricesStore

buildKernelsMatrices(epsilon=1e-05)[source]
getKzz()[source]
getKzzChol()[source]
class stats.svGPFA.kernelMatricesStore.KernelMatricesStore[source]

Bases: abc.ABC

abstract buildKernelsMatrices()[source]
getIndPointsLocs()[source]
getKernels()[source]
getKernelsParams()[source]
setIndPointsLocs(indPointsLocs)[source]
setInitialParams(initialParams)[source]
setKernels(kernels)[source]

stats.svGPFA.klDivergence module

class stats.svGPFA.klDivergence.KLDivergence(indPointsLocsKMS, svPosteriorOnIndPoints)[source]

Bases: object

evalSumAcrossLatentsAndTrials()[source]

stats.svGPFA.simulations module

class stats.svGPFA.simulations.EmbeddingSimulator(latents, C, d, latentsEpsilon)[source]

Bases: object

getEmbeddingFunctionForNeuronAndTrial(n, r)[source]
class stats.svGPFA.simulations.GPFASimulator[source]

Bases: object

simulate(nNeurons, trialsLengths, latents, C, d, linkFunction, dt, latentsEpsilon=1e-05)[source]

Simulates spikes for N=nNeurons neurons and R=len(trialLengths) trials using K=len(latents) per trial.

nNeurons: int

number of neurons to simulate.

trialsLengths: numpy array in R^R

trialsLengths[r] is the duration, T_r, of the rth trial

latents: list of length K

len(latents[k])=R and contains kth latent processes (i.e., Gaussian processes) for all R trials.

C: numpy ndarray in R^{N imes K} d: numpy array in R^N linkFunction: function

function to map embedding values to point-process intensity values.

list[n][r]

containing a list of spike times for neuron n in trial r

stats.svGPFA.svEM module

class stats.svGPFA.svEM.SVEM[source]

Bases: object

maximize(model, measurements, initialParams, quadParams, optimParams)[source]

stats.svGPFA.svEmbedding module

class stats.svGPFA.svEmbedding.LinearSVEmbedding(svPosteriorOnLatents)[source]

Bases: stats.svGPFA.svEmbedding.SVEmbedding

getParams()[source]
setInitialParams(initialParams)[source]
class stats.svGPFA.svEmbedding.LinearSVEmbeddingAllTimes(svPosteriorOnLatents)[source]

Bases: stats.svGPFA.svEmbedding.LinearSVEmbedding

predictLatents(newTimes)[source]
class stats.svGPFA.svEmbedding.LinearSVEmbeddingAssocTimes(svPosteriorOnLatents)[source]

Bases: stats.svGPFA.svEmbedding.LinearSVEmbedding

setNeuronForSpikeIndex(neuronForSpikeIndex)[source]
class stats.svGPFA.svEmbedding.SVEmbedding(svPosteriorOnLatents)[source]

Bases: abc.ABC

buildKernelsMatrices()[source]
computeMeansAndVars(svPosteriorOnLatentsStats=None)[source]
computeSVPosteriorOnLatentsStats()[source]
getIndPointsLocs()[source]
getKernelsParams()[source]
abstract getParams()[source]
getSVPosteriorOnIndPointsParams()[source]
setIndPointsLocs(indPointsLocs)[source]
abstract setInitialParams(initialParams)[source]
setKernels(kernels)[source]
setTimes(times)[source]

stats.svGPFA.svGPFAModelFactory module

stats.svGPFA.svGPFAModelFactory.LinearEmbedding = 100
stats.svGPFA.svGPFAModelFactory.PointProcess = 0
stats.svGPFA.svGPFAModelFactory.Poisson = 1
class stats.svGPFA.svGPFAModelFactory.SVGPFAModelFactory[source]

Bases: object

static buildModel(conditionalDist, linkFunction, embeddingType, kernels)[source]

stats.svGPFA.svLowerBound module

class stats.svGPFA.svLowerBound.SVLowerBound(eLL, klDiv)[source]

Bases: object

buildKernelsMatrices()[source]
computeSVPosteriorOnLatentsStats()[source]
eval()[source]
evalELLSumAcrossTrialsAndNeurons(svPosteriorOnLatentsStats)[source]
getIndPointsLocs()[source]
getKernelsParams()[source]
getSVEmbeddingParams()[source]
getSVPosteriorOnIndPointsParams()[source]
predictLatents(newTimes)[source]
setIndPointsLocs(locs)[source]
setInitialParams(initialParams)[source]
setKernels(kernels)[source]
setMeasurements(measurements)[source]
setQuadParams(quadParams)[source]

stats.svGPFA.svPosteriorOnIndPoints module

class stats.svGPFA.svPosteriorOnIndPoints.SVPosteriorOnIndPoints[source]

Bases: object

buildQSigma()[source]
getParams()[source]
getQMu()[source]
setInitialParams(initialParams)[source]

stats.svGPFA.svPosteriorOnLatents module

class stats.svGPFA.svPosteriorOnLatents.SVPosteriorOnLatents(svPosteriorOnIndPoints, indPointsLocsKMS, indPointsLocsAndTimesKMS)[source]

Bases: abc.ABC

abstract buildKernelsMatrices()[source]
abstract computeMeansAndVars()[source]
getIndPointsLocs()[source]
getKernelsParams()[source]
getSVPosteriorOnIndPointsParams()[source]
abstract setIndPointsLocs(indPointsLocs)[source]
abstract setInitialParams(initialParams)[source]
abstract setKernels()[source]
setTimes(times)[source]
class stats.svGPFA.svPosteriorOnLatents.SVPosteriorOnLatentsAllTimes(svPosteriorOnIndPoints, indPointsLocsKMS, indPointsLocsAndTimesKMS)[source]

Bases: stats.svGPFA.svPosteriorOnLatents.SVPosteriorOnLatents

buildKernelsMatrices()[source]
computeMeansAndVars()[source]
predict(newTimes)[source]
setIndPointsLocs(indPointsLocs)[source]
setInitialParams(initialParams)[source]
setKernels(kernels)[source]
class stats.svGPFA.svPosteriorOnLatents.SVPosteriorOnLatentsAssocTimes(svPosteriorOnIndPoints, indPointsLocsKMS, indPointsLocsAndTimesKMS)[source]

Bases: stats.svGPFA.svPosteriorOnLatents.SVPosteriorOnLatents

buildKernelsMatrices()[source]
computeMeansAndVars()[source]
setIndPointsLocs(indPointsLocs)[source]
setInitialParams(initialParams)[source]
setKernels(kernels)[source]

stats.svGPFA.utils module

stats.svGPFA.utils.build3DdiagFromDiagVector(v, N, M)[source]
stats.svGPFA.utils.chol3D(K)[source]
stats.svGPFA.utils.clock(func)[source]
stats.svGPFA.utils.flattenListsOfArrays(*lists)[source]
stats.svGPFA.utils.getDiagIndicesIn3DArray(N, M)[source]

Module contents