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cuqi
array
CUQIarray
config
data
astronaut
camera
cat
cookie
grains
imresize
p_power
rgb2gray
satellite
shepp_logan
threephases
density
Density
EvaluatedDensity
diagnostics
Geweke
spectrum
spectrum0
distribution
Beta
CMRF
Cauchy
Distribution
DistributionGallery
GMRF
Gamma
Gaussian
InverseGamma
JointDistribution
JointGaussianSqrtPrec
LMRF
Laplace
Lognormal
ModifiedHalfNormal
MultipleLikelihoodPosterior
Normal
Posterior
SmoothedLaplace
TruncatedNormal
UnboundedUniform
Uniform
UserDefinedDistribution
experimental
SamplerRecommender
algebra
geometry
geometry
Continuous
Continuous1D
Continuous2D
CustomKL
Discrete
Geometry
Image2D
KLExpansion
KLExpansion_Full
MappedGeometry
StepExpansion
implicitprior
ConstrainedGMRF
ConstrainedGaussian
MoreauYoshidaPrior
NonnegativeGMRF
NonnegativeGaussian
RegularizedGMRF
RegularizedGaussian
RegularizedUnboundedUniform
RestorationPrior
TweediePrior
legacy
sampler
likelihood
Likelihood
UserDefinedLikelihood
model
AffineModel
LinearModel
Model
PDEModel
operator
FirstOrderFiniteDifference
Operator
PrecisionFiniteDifference
SecondOrderFiniteDifference
pde
LinearPDE
PDE
SteadyStateLinearPDE
TimeDependentLinearPDE
problem
BayesianProblem
sampler
CWMH
Conjugate
ConjugateApprox
Direct
HybridGibbs
LinearRTO
MALA
MH
MYULA
NUTS
PCN
PnPULA
ProposalBasedSampler
RegularizedLinearRTO
Sampler
UGLA
ULA
samples
JointSamples
Samples
solver
ProjectBox
ProjectNonnegative
ProximalL1
ADMM
CGLS
FISTA
LM
PDHG
ScipyLBFGSB
ScipyLSQ
ScipyLinearLSQ
ScipyMaximizer
ScipyMinimizer
testproblem
Abel1D
Deconvolution1D
Deconvolution2D
Heat1D
Poisson1D
WangCubic
utilities
approx_derivative
approx_gradient
check_if_conditional_from_attr
count_constant_components_1D
count_constant_components_2D
count_nonzero
count_within_bounds
force_ndarray
get_direct_attributes
get_indirect_variables
get_non_default_args
get_writeable_attributes
get_writeable_properties
infer_len
piecewise_linear_1D_DoF
plot_1D_density
plot_2D_density
sparse_cholesky
ProblemInfo
API reference
cuqi
samples
Samples
cuqi.samples.Samples.mean
cuqi.samples.Samples.mean
#
Samples.
mean
(
)
[source]
#
Compute mean of the samples.
On this page
Samples.mean()
This Page
Show Source
