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Home
Examples
Learn
API
Community
Contributing
GitHub
Twitter
YouTube
Discourse
Section Navigation
Distributions
Continuous
pymc.Uniform
pymc.Flat
pymc.HalfFlat
pymc.Normal
pymc.TruncatedNormal
pymc.Beta
pymc.Kumaraswamy
pymc.Exponential
pymc.Laplace
pymc.StudentT
pymc.Cauchy
pymc.HalfCauchy
pymc.Gamma
pymc.Weibull
pymc.HalfStudentT
pymc.LogNormal
pymc.ChiSquared
pymc.HalfNormal
pymc.Wald
pymc.Pareto
pymc.InverseGamma
pymc.ExGaussian
pymc.VonMises
pymc.SkewNormal
pymc.Triangular
pymc.Gumbel
pymc.Logistic
pymc.LogitNormal
pymc.Interpolated
pymc.Rice
pymc.Moyal
pymc.AsymmetricLaplace
pymc.PolyaGamma
Discrete
pymc.Binomial
pymc.BetaBinomial
pymc.Bernoulli
pymc.DiscreteWeibull
pymc.Poisson
pymc.NegativeBinomial
pymc.DiracDelta
pymc.ZeroInflatedPoisson
pymc.ZeroInflatedBinomial
pymc.ZeroInflatedNegativeBinomial
pymc.DiscreteUniform
pymc.Geometric
pymc.HyperGeometric
pymc.Categorical
pymc.OrderedLogistic
pymc.OrderedProbit
Multivariate
pymc.MvNormal
pymc.MvStudentT
pymc.ZeroSumNormal
pymc.Dirichlet
pymc.Multinomial
pymc.DirichletMultinomial
pymc.OrderedMultinomial
pymc.Wishart
pymc.WishartBartlett
pymc.LKJCorr
pymc.LKJCholeskyCov
pymc.MatrixNormal
pymc.KroneckerNormal
pymc.CAR
pymc.StickBreakingWeights
Mixture
pymc.Mixture
pymc.NormalMixture
Timeseries
pymc.AR
pymc.GaussianRandomWalk
pymc.GARCH11
pymc.EulerMaruyama
pymc.MvGaussianRandomWalk
pymc.MvStudentTRandomWalk
Truncated
pymc.Truncated
Censored
pymc.Censored
Simulator
pymc.Simulator
Transformations
pymc.distributions.transforms.simplex
pymc.distributions.transforms.logodds
pymc.distributions.transforms.log_exp_m1
pymc.distributions.transforms.ordered
pymc.distributions.transforms.log
pymc.distributions.transforms.sum_to_1
pymc.distributions.transforms.circular
pymc.distributions.transforms.CholeskyCovPacked
pymc.distributions.transforms.Interval
pymc.distributions.transforms.LogExpM1
pymc.distributions.transforms.Ordered
pymc.distributions.transforms.SumTo1
pymc.distributions.transforms.ZeroSumTransform
pymc.distributions.transforms.Chain
Distribution utilities
pymc.Distribution
pymc.Discrete
pymc.Continuous
pymc.DensityDist
pymc.SymbolicRandomVariable
Gaussian Processes
Implementations
pymc.gp.Latent
pymc.gp.LatentKron
pymc.gp.Marginal
pymc.gp.MarginalKron
pymc.gp.MarginalApprox
pymc.gp.TP
Mean Functions
pymc.gp.mean.Zero
pymc.gp.mean.Constant
pymc.gp.mean.Linear
Covariance Functions
pymc.gp.cov.Constant
pymc.gp.cov.WhiteNoise
pymc.gp.cov.ExpQuad
pymc.gp.cov.RatQuad
pymc.gp.cov.Exponential
pymc.gp.cov.Matern52
pymc.gp.cov.Matern32
pymc.gp.cov.Linear
pymc.gp.cov.Polynomial
pymc.gp.cov.Cosine
pymc.gp.cov.Periodic
pymc.gp.cov.WarpedInput
pymc.gp.cov.Gibbs
pymc.gp.cov.Coregion
pymc.gp.cov.ScaledCov
pymc.gp.cov.Kron
Model
Samplers
pymc.sample
pymc.sample_prior_predictive
pymc.sample_posterior_predictive
pymc.sample_posterior_predictive_w
pymc.sampling.jax.sample_blackjax_nuts
pymc.sampling.jax.sample_numpyro_nuts
pymc.iter_sample
pymc.init_nuts
pymc.draw
pymc.NUTS
pymc.HamiltonianMC
pymc.BinaryGibbsMetropolis
pymc.BinaryMetropolis
pymc.CategoricalGibbsMetropolis
pymc.CauchyProposal
pymc.DEMetropolis
pymc.DEMetropolisZ
pymc.LaplaceProposal
pymc.Metropolis
pymc.MultivariateNormalProposal
pymc.NormalProposal
pymc.PoissonProposal
pymc.UniformProposal
pymc.CompoundStep
pymc.Slice
Variational Inference
pymc.ADVI
pymc.ASVGD
pymc.SVGD
pymc.FullRankADVI
pymc.ImplicitGradient
pymc.Inference
pymc.KLqp
pymc.fit
pymc.Empirical
pymc.FullRank
pymc.MeanField
pymc.sample_approx
pymc.Approximation
pymc.Group
pymc.variational.operators.KL
pymc.variational.operators.KSD
pymc.Stein
pymc.adadelta
pymc.adagrad
pymc.adagrad_window
pymc.adam
pymc.adamax
pymc.apply_momentum
pymc.apply_nesterov_momentum
pymc.momentum
pymc.nesterov_momentum
pymc.norm_constraint
pymc.rmsprop
pymc.sgd
pymc.total_norm_constraint
Sequential Monte Carlo
pymc.smc.sample_smc
pymc.smc.kernels.SMC_KERNEL
pymc.smc.kernels.IMH
pymc.smc.kernels.MH
Storage backends
pymc.to_inference_data
pymc.predictions_to_inference_data
pymc.backends.NDArray
pymc.backends.point_list_to_multitrace
pymc.backends.base.BaseTrace
pymc.backends.base.MultiTrace
Data
pymc.ConstantData
pymc.MutableData
pymc.get_data
pymc.Data
pymc.GeneratorAdapter
pymc.Minibatch
pymc.align_minibatches
Ordinary differential equations (ODEs)
pymc.ode.DifferentialEquation
Tuning
pymc.find_hessian
pymc.guess_scaling
pymc.trace_cov
pymc.find_MAP
Math
pymc.expand_packed_triangular
pymc.logit
pymc.invlogit
pymc.probit
pymc.invprobit
pymc.logsumexp
pymc.math.dot
pymc.math.constant
pymc.math.flatten
pymc.math.zeros_like
pymc.math.ones_like
pymc.math.stack
pymc.math.concatenate
pymc.math.sum
pymc.math.prod
pymc.math.lt
pymc.math.gt
pymc.math.le
pymc.math.ge
pymc.math.eq
pymc.math.neq
pymc.math.switch
pymc.math.clip
pymc.math.where
pymc.math.and_
pymc.math.or_
pymc.math.exp
pymc.math.log
pymc.math.cos
pymc.math.sin
pymc.math.tan
pymc.math.cosh
pymc.math.sinh
pymc.math.tanh
pymc.math.sqr
pymc.math.sqrt
pymc.math.erf
pymc.math.erfinv
pymc.math.dot
pymc.math.maximum
pymc.math.minimum
pymc.math.sgn
pymc.math.ceil
pymc.math.floor
pymc.math.det
pymc.math.matrix_inverse
pymc.math.extract_diag
pymc.math.matrix_dot
pymc.math.trace
pymc.math.sigmoid
pymc.math.logsumexp
pymc.math.invlogit
pymc.math.logit
Aesara utils
pymc.compile_pymc
pymc.gradient
pymc.hessian
pymc.hessian_diag
pymc.jacobian
pymc.inputvars
pymc.cont_inputs
pymc.floatX
pymc.intX
pymc.smartfloatX
pymc.constant_fold
pymc.CallableTensor
pymc.join_nonshared_inputs
pymc.make_shared_replacements
pymc.generator
pymc.set_at_rng
pymc.at_rng
shape_utils
pymc.distributions.shape_utils.to_tuple
pymc.distributions.shape_utils.shapes_broadcasting
pymc.distributions.shape_utils.broadcast_dist_samples_shape
pymc.distributions.shape_utils.get_broadcastable_dist_samples
pymc.distributions.shape_utils.broadcast_distribution_samples
pymc.distributions.shape_utils.broadcast_dist_samples_to
pymc.distributions.shape_utils.rv_size_is_none
pymc.distributions.shape_utils.change_dist_size
Other utils
pymc.find_constrained_prior
pymc.DictToArrayBijection
pymc.str_for_dist
pymc.str_for_model
pymc.str_for_potential_or_deterministic
pymc.Minibatch.clip
#
Minibatch.
clip
(
a_min
,
a_max
)
#
See
aesara.tensor.math.clip
.
On this page
Minibatch.clip()
Show Source
Support PyMC