jaxns
latest
User Guide
Installation
Change Log
API Reference
jaxns
Examples
Bayesian computations with Neural Networks
Inference of Jones scalars observables (noisy angular quantities)
Lennard-Jones Potentials for modelling phase transitions in materials
Constant Likelihood
Dual Moons likelihood
Egg-box Likelihood with Uniform Prior
Evidence Maximisation
Generate data
Define the model with parameters
Poisson likelihood and Gamma prior
Gaussian processes with outliers
Gaussian processes with outliers
Thin Gaussian Shells with Uniform Prior
Multivariate Normal Likelihood with Multivariate Normal Prior
Measuring placebo effect on hunger
Simulate Data
Define likelihood
Make a model that is unaware of the effect
Logic rules
Self-Exciting process (Hawkes process)
jaxns
Index
Edit on GitHub
Index
_
|
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
I
|
J
|
K
|
L
|
M
|
N
|
P
|
R
|
S
|
T
|
U
|
V
|
X
|
Y
_
__add__() (LogSpace method)
__and__() (GlobalOptimisationTerminationCondition method)
,
[1]
(TerminationCondition method)
,
[1]
,
[2]
,
[3]
,
[4]
__call__() (DefaultGlobalOptimisation method)
(DefaultNestedSampler method)
,
[1]
(Model method)
,
[1]
,
[2]
__ge__() (LogSpace method)
__getitem__() (LogSpace method)
__gt__() (LogSpace method)
__hash__() (AbstractModel method)
(Model method)
,
[1]
,
[2]
__le__() (LogSpace method)
__lt__() (LogSpace method)
__mul__() (LogSpace method)
__neg__() (LogSpace method)
__or__() (GlobalOptimisationTerminationCondition method)
,
[1]
(TerminationCondition method)
,
[1]
,
[2]
,
[3]
,
[4]
__post_init__() (EvidenceMaximisation method)
,
[1]
__pow__() (LogSpace method)
__repr__() (BaseAbstractPrior method)
(BaseAbstractSampler method)
(DefaultNestedSampler method)
,
[1]
(Distribution method)
(LogSpace method)
(Model method)
,
[1]
,
[2]
(StandardStaticNestedSampler method)
,
[1]
__sub__() (LogSpace method)
__truediv__() (LogSpace method)
A
abs() (LogSpace method)
absolute_spread (GlobalOptimisationResults attribute)
,
[1]
AbstractDistribution (class in jaxns.framework.abc)
AbstractModel (class in jaxns.framework.abc)
AbstractNestedSampler (class in jaxns.nested_sampler.abc)
AbstractPrior (class in jaxns.framework.abc)
AbstractSampler (class in jaxns.samplers.abc)
add_chunk_dim() (in module jaxns.internals.maps)
analytic_posterior_samples() (in module jaxns)
(in module jaxns.utils)
ApproximateNestedSampler (class in jaxns)
(class in jaxns.public)
argmax() (LogSpace method)
atol (GlobalOptimisationTerminationCondition attribute)
,
[1]
B
base_ndims (BaseAbstractPrior property)
base_shape (BaseAbstractDistribution property)
(BaseAbstractPrior property)
BaseAbstractDistribution (class in jaxns.framework.bases)
BaseAbstractMarkovSampler (class in jaxns.samplers.bases)
BaseAbstractModel (class in jaxns.framework.bases)
BaseAbstractNestedSampler (class in jaxns.nested_sampler.bases)
BaseAbstractPrior (class in jaxns.framework.bases)
BaseAbstractRejectionSampler (class in jaxns.samplers.bases)
BaseAbstractSampler (class in jaxns.samplers.bases)
batch_size (EvidenceMaximisation attribute)
,
[1]
Bernoulli (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.special_priors)
Beta (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.special_priors)
BoolArray (in module jaxns.internals.types)
broadcast_dtypes() (in module jaxns.internals.shapes)
broadcast_shapes() (in module jaxns.internals.shapes)
bruteforce_evidence() (in module jaxns)
(in module jaxns.utils)
bruteforce_posterior_samples() (in module jaxns)
(in module jaxns.utils)
C
Categorical (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.special_priors)
chunked_pmap() (in module jaxns.internals.maps)
chunked_vmap() (in module jaxns.internals.maps)
cluster_id (MultEllipsoidState attribute)
complex_type (in module jaxns.internals.types)
compute_enclosed_prior_volume() (in module jaxns.internals.shrinkage_statistics)
compute_evidence_stats() (in module jaxns.internals.shrinkage_statistics)
compute_num_live_points_from_unit_threads() (in module jaxns.internals.tree_structure)
concatenate() (LogSpace method)
concatenate_sample_trees() (in module jaxns.internals.tree_structure)
convert_to_array() (in module jaxns.internals.shapes)
count_crossed_edges() (in module jaxns.internals.tree_structure)
count_crossed_edges_less_fast() (in module jaxns.internals.tree_structure)
count_intervals_naive() (in module jaxns.internals.tree_structure)
count_old() (in module jaxns.internals.tree_structure)
cumprod() (LogSpace method)
cumsum() (LogSpace method)
cumulative_logsumexp() (in module jaxns.internals.log_semiring)
cumulative_op_dynamic() (in module jaxns.internals.cumulative_ops)
cumulative_op_static() (in module jaxns.internals.cumulative_ops)
D
DefaultGlobalOptimisation (class in jaxns.experimental.public)
DefaultNestedSampler (class in jaxns)
(class in jaxns.public)
density_estimation() (in module jaxns.internals.stats)
deprecated() (in module jaxns.warnings)
diff() (LogSpace method)
dist (Prior property)
,
[1]
,
[2]
Distribution (class in jaxns.framework.distribution)
dlogZ (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
dtype (BaseAbstractDistribution property)
(BaseAbstractPrior property)
(LogSpace property)
E
e_step() (EvidenceMaximisation method)
,
[1]
(in module jaxns.samplers.multi_ellipsoid.em_gmm)
effective_sample_size() (in module jaxns.internals.stats)
efficiency_threshold (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
ellipsoid_clustering() (in module jaxns.samplers.multi_ellipsoid.multi_ellipsoid_utils)
em_gmm() (in module jaxns.samplers.multi_ellipsoid.em_gmm)
ESS (NestedSamplerResults attribute)
ess (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
evaluate_map_estimate() (in module jaxns)
(in module jaxns.utils)
evidence_uncert (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
EvidenceCalculation (class in jaxns.internals.types)
EvidenceMaximisation (class in jaxns.experimental)
(class in jaxns.experimental.evidence_maximisation)
EvidenceUpdateVariables (class in jaxns.internals.shrinkage_statistics)
ExactNestedSampler (class in jaxns)
(class in jaxns.public)
exp() (LogSpace method)
F
F (in module jaxns.internals.maps)
fast_perfect_live_point_computation_jax() (in module jaxns.internals.tree_structure)
float_type (in module jaxns.internals.types)
FloatArray (in module jaxns.internals.types)
ForcedIdentifiability (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.special_priors)
forward() (AbstractModel method)
(BaseAbstractDistribution method)
(BaseAbstractPrior method)
(Model method)
,
[1]
,
[2]
front_idx (StaticStandardNestedSamplerState attribute)
FV (in module jaxns.internals.maps)
G
get_index() (in module jaxns.internals.maps)
get_sample() (AbstractSampler method)
(BaseAbstractMarkovSampler method)
(MultiEllipsoidalSampler method)
,
[1]
(UniformSampler method)
,
[1]
get_sample_from_seed() (BaseAbstractMarkovSampler method)
(MultiDimSliceSampler method)
,
[1]
(UniDimSliceSampler method)
,
[1]
get_seed_point() (BaseAbstractMarkovSampler method)
(MultiDimSliceSampler method)
,
[1]
(UniDimSliceSampler method)
,
[1]
GlobalOptimisationResults (class in jaxns.experimental)
(class in jaxns.experimental.global_optimisation)
GlobalOptimisationState (class in jaxns.experimental)
(class in jaxns.experimental.global_optimisation)
GlobalOptimisationTerminationCondition (class in jaxns.experimental)
(class in jaxns.experimental.global_optimisation)
gtol (EvidenceMaximisation attribute)
,
[1]
H
H_mean (NestedSamplerResults attribute)
I
init_evidence_calc() (in module jaxns.internals.shrinkage_statistics)
init_params() (Model method)
,
[1]
,
[2]
initialize_params() (in module jaxns.samplers.multi_ellipsoid.em_gmm)
int_type (in module jaxns.internals.types)
IntArray (in module jaxns.internals.types)
InvalidDistribution
InvalidPriorName
,
[1]
,
[2]
inverse() (BaseAbstractDistribution method)
(BaseAbstractPrior method)
is_complex() (in module jaxns.internals.log_semiring)
J
jaxns
module
jaxns.experimental
module
jaxns.experimental.evidence_maximisation
module
jaxns.experimental.global_optimisation
module
jaxns.experimental.public
module
jaxns.framework
module
jaxns.framework.abc
module
jaxns.framework.bases
module
jaxns.framework.distribution
module
jaxns.framework.model
module
jaxns.framework.ops
module
jaxns.framework.prior
module
jaxns.framework.special_priors
module
jaxns.internals
module
jaxns.internals.cumulative_ops
module
jaxns.internals.linalg
module
jaxns.internals.log_semiring
module
jaxns.internals.maps
module
jaxns.internals.random
module
jaxns.internals.shapes
module
jaxns.internals.shrinkage_statistics
module
jaxns.internals.stats
module
jaxns.internals.tree_structure
module
jaxns.internals.types
module
jaxns.nested_sampler
module
jaxns.nested_sampler.abc
module
jaxns.nested_sampler.bases
module
jaxns.nested_sampler.standard_static
module
jaxns.plotting
module
jaxns.public
module
jaxns.samplers
module
jaxns.samplers.abc
module
jaxns.samplers.bases
module
jaxns.samplers.multi_ellipsoid
module
jaxns.samplers.multi_ellipsoid.em_gmm
module
jaxns.samplers.multi_ellipsoid.multi_ellipsoid_utils
module
jaxns.samplers.multi_ellipsoidal_samplers
module
jaxns.samplers.multi_slice_sampler
module
jaxns.samplers.uni_slice_sampler
module
jaxns.samplers.uniform_samplers
module
jaxns.utils
module
jaxns.warnings
module
K
key (GlobalOptimisationState attribute)
,
[1]
(StaticStandardNestedSamplerState attribute)
L
LikelihoodInputType (in module jaxns.internals.types)
LikelihoodType (in module jaxns.internals.types)
linear_to_log_stats() (in module jaxns.internals.stats)
live_evidence_frac (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
load_pytree() (in module jaxns)
(in module jaxns.utils)
load_results() (in module jaxns)
(in module jaxns.utils)
log() (LogSpace method)
log_abs_val (LogSpace property)
log_dp_mean (NestedSamplerResults attribute)
log_dZ2_mean (EvidenceCalculation attribute)
log_dZ_mean (EvidenceCalculation attribute)
log_efficiency (NestedSamplerResults attribute)
log_L (EvidenceCalculation attribute)
(SampleTreeGraph attribute)
log_L0 (SeedPoint attribute)
log_L_contour (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
log_L_next (EvidenceUpdateVariables attribute)
log_L_samples (NestedSamplerResults attribute)
log_L_solution (GlobalOptimisationResults attribute)
,
[1]
log_likelihood (BaseAbstractModel property)
log_likelihood_contour (GlobalOptimisationTerminationCondition attribute)
,
[1]
log_posterior_density (NestedSamplerResults attribute)
log_prob() (BaseAbstractDistribution method)
(BaseAbstractPrior method)
log_prob_joint() (AbstractModel method)
log_prob_likelihood() (AbstractModel method)
log_prob_prior() (AbstractModel method)
(Model method)
,
[1]
,
[2]
log_X2_mean (EvidenceCalculation attribute)
log_X_mean (EvidenceCalculation attribute)
(NestedSamplerResults attribute)
log_Z2_mean (EvidenceCalculation attribute)
log_Z_atol (EvidenceMaximisation attribute)
,
[1]
log_Z_ftol (EvidenceMaximisation attribute)
,
[1]
log_Z_mean (EvidenceCalculation attribute)
(NestedSamplerResults attribute)
log_Z_uncert (NestedSamplerResults attribute)
log_ZX_mean (EvidenceCalculation attribute)
logaddexp() (in module jaxns.internals.log_semiring)
logger (in module jaxns)
(in module jaxns.internals.maps)
(in module jaxns.warnings)
LogSpace (class in jaxns.internals.log_semiring)
M
m_step() (EvidenceMaximisation method)
,
[1]
(in module jaxns.samplers.multi_ellipsoid.em_gmm)
marginalise_dynamic() (in module jaxns)
(in module jaxns.utils)
marginalise_dynamic_from_U() (in module jaxns)
(in module jaxns.utils)
marginalise_static() (in module jaxns)
(in module jaxns.utils)
marginalise_static_from_U() (in module jaxns)
(in module jaxns.utils)
max() (LogSpace method)
max_likelihood_evaluations (GlobalOptimisationTerminationCondition attribute)
,
[1]
max_num_ellipsoids (MultiEllipsoidalSampler property)
,
[1]
max_num_epochs (EvidenceMaximisation attribute)
,
[1]
max_num_likelihood_evaluations (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
max_samples (TerminationCondition attribute)
,
[1]
,
[2]
,
[3]
,
[4]
maximum() (LogSpace method)
maximum_a_posteriori_point() (in module jaxns)
(in module jaxns.utils)
mean() (LogSpace method)
MeasureType (in module jaxns.internals.types)
min() (LogSpace method)
min_efficiency (GlobalOptimisationTerminationCondition attribute)
,
[1]
minimum() (LogSpace method)
Model (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.model)
model (EvidenceMaximisation attribute)
,
[1]
module
jaxns
jaxns.experimental
jaxns.experimental.evidence_maximisation
jaxns.experimental.global_optimisation
jaxns.experimental.public
jaxns.framework
jaxns.framework.abc
jaxns.framework.bases
jaxns.framework.distribution
jaxns.framework.model
jaxns.framework.ops
jaxns.framework.prior
jaxns.framework.special_priors
jaxns.internals
jaxns.internals.cumulative_ops
jaxns.internals.linalg
jaxns.internals.log_semiring
jaxns.internals.maps
jaxns.internals.random
jaxns.internals.shapes
jaxns.internals.shrinkage_statistics
jaxns.internals.stats
jaxns.internals.tree_structure
jaxns.internals.types
jaxns.nested_sampler
jaxns.nested_sampler.abc
jaxns.nested_sampler.bases
jaxns.nested_sampler.standard_static
jaxns.plotting
jaxns.public
jaxns.samplers
jaxns.samplers.abc
jaxns.samplers.bases
jaxns.samplers.multi_ellipsoid
jaxns.samplers.multi_ellipsoid.em_gmm
jaxns.samplers.multi_ellipsoid.multi_ellipsoid_utils
jaxns.samplers.multi_ellipsoidal_samplers
jaxns.samplers.multi_slice_sampler
jaxns.samplers.uni_slice_sampler
jaxns.samplers.uniform_samplers
jaxns.utils
jaxns.warnings
momentum (EvidenceMaximisation attribute)
,
[1]
msqrt() (in module jaxns.internals.linalg)
MultEllipsoidState (class in jaxns.samplers.multi_ellipsoid.multi_ellipsoid_utils)
MultiDimSliceSampler (class in jaxns.samplers)
(class in jaxns.samplers.multi_slice_sampler)
MultiEllipsoidalSampler (class in jaxns.samplers)
(class in jaxns.samplers.multi_ellipsoidal_samplers)
N
nansum() (LogSpace method)
nested_sampler (DefaultNestedSampler property)
,
[1]
NestedSamplerResults (class in jaxns.internals.types)
next_sample_idx (StaticStandardNestedSamplerState attribute)
normal_to_lognormal() (in module jaxns.internals.stats)
normalise_log_space() (in module jaxns.internals.log_semiring)
ns_kwargs (EvidenceMaximisation attribute)
,
[1]
num_likelihood_evaluations (GlobalOptimisationResults attribute)
,
[1]
(GlobalOptimisationState attribute)
,
[1]
num_likelihood_evaluations_per_sample (NestedSamplerResults attribute)
num_live_points (DefaultNestedSampler property)
,
[1]
(EvidenceUpdateVariables attribute)
(SampleLivePointCounts attribute)
num_live_points_per_sample (NestedSamplerResults attribute)
num_params (Model property)
,
[1]
,
[2]
num_phantom() (AbstractSampler method)
(MultiDimSliceSampler method)
,
[1]
(MultiEllipsoidalSampler method)
,
[1]
(UniDimSliceSampler method)
,
[1]
(UniformSampler method)
,
[1]
num_samples (GlobalOptimisationResults attribute)
,
[1]
(GlobalOptimisationState attribute)
,
[1]
P
parametrised() (Prior method)
,
[1]
,
[2]
parametrised_samples (NestedSamplerResults attribute)
params (Model property)
,
[1]
,
[2]
(MultEllipsoidState attribute)
plot_cornerplot() (in module jaxns)
(in module jaxns.plotting)
plot_diagnostics() (in module jaxns)
(in module jaxns.plotting)
plot_tree() (in module jaxns.internals.tree_structure)
Poisson (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.special_priors)
post_process() (AbstractSampler method)
(MultiDimSliceSampler method)
,
[1]
(MultiEllipsoidalSampler method)
,
[1]
(UniDimSliceSampler method)
,
[1]
(UniformSampler method)
,
[1]
pre_process() (AbstractSampler method)
(MultiDimSliceSampler method)
,
[1]
(MultiEllipsoidalSampler method)
,
[1]
(UniDimSliceSampler method)
,
[1]
(UniformSampler method)
,
[1]
prepad() (in module jaxns.internals.maps)
prepare_func_args() (in module jaxns.internals.maps)
prepare_input() (AbstractModel method)
(Model method)
,
[1]
,
[2]
Prior (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.prior)
prior_model (BaseAbstractModel property)
PriorModelGen (in module jaxns)
(in module jaxns.framework)
(in module jaxns.framework.bases)
PriorModelType (in module jaxns)
(in module jaxns.framework)
(in module jaxns.framework.bases)
PRNGKey (in module jaxns.internals.types)
R
random_ortho_matrix() (in module jaxns.internals.random)
RandomVariableType (in module jaxns.internals.types)
relative_spread (GlobalOptimisationResults attribute)
,
[1]
remove_chunk_dim() (in module jaxns.internals.maps)
replace_index() (in module jaxns.internals.maps)
resample() (in module jaxns)
(in module jaxns.utils)
resample_indicies() (in module jaxns.internals.random)
rtol (GlobalOptimisationTerminationCondition attribute)
,
[1]
S
sample_collection (StaticStandardNestedSamplerState attribute)
sample_evidence() (in module jaxns)
(in module jaxns.utils)
sample_multi_ellipsoid() (in module jaxns.samplers.multi_ellipsoid.multi_ellipsoid_utils)
sample_U() (AbstractModel method)
(Model method)
,
[1]
,
[2]
SampleLivePointCounts (class in jaxns.internals.tree_structure)
SamplerState (in module jaxns.samplers.abc)
samples (GlobalOptimisationState attribute)
,
[1]
(NestedSamplerResults attribute)
samples_indices (SampleLivePointCounts attribute)
SampleTreeGraph (class in jaxns.internals.tree_structure)
sanity_check() (AbstractModel method)
(Model method)
,
[1]
,
[2]
save_pytree() (in module jaxns)
(in module jaxns.utils)
save_results() (in module jaxns)
(in module jaxns.utils)
SeedPoint (class in jaxns.samplers.bases)
sender_node_idx (SampleTreeGraph attribute)
set_params() (Model method)
,
[1]
,
[2]
shape (BaseAbstractDistribution property)
(BaseAbstractPrior property)
sign (LogSpace property)
signed_log (LogSpace property)
signed_logaddexp() (in module jaxns.internals.log_semiring)
SimpleGlobalOptimisation (class in jaxns.experimental)
(class in jaxns.experimental.global_optimisation)
simulate_prior_model() (in module jaxns.framework.ops)
size (LogSpace property)
solution (GlobalOptimisationResults attribute)
,
[1]
sqrt() (LogSpace method)
square() (LogSpace method)
squared_norm() (in module jaxns.internals.linalg)
StandardStaticNestedSampler (class in jaxns.nested_sampler)
(class in jaxns.nested_sampler.standard_static)
StaticStandardNestedSamplerState (class in jaxns.internals.types)
sum() (LogSpace method)
summary() (DefaultGlobalOptimisation method)
(in module jaxns)
(in module jaxns.utils)
T
T (in module jaxns.internals.maps)
termination_cond (EvidenceMaximisation attribute)
,
[1]
termination_reason (GlobalOptimisationResults attribute)
,
[1]
(NestedSamplerResults attribute)
TerminationCondition (class in jaxns)
(class in jaxns.internals.types)
(class in jaxns.nested_sampler)
(class in jaxns.nested_sampler.standard_static)
(class in jaxns.public)
to_results() (DefaultNestedSampler method)
,
[1]
total_num_likelihood_evaluations (NestedSamplerResults attribute)
total_num_samples (NestedSamplerResults attribute)
total_phantom_samples (NestedSamplerResults attribute)
train() (EvidenceMaximisation method)
,
[1]
transform() (AbstractModel method)
(Model method)
,
[1]
,
[2]
transform_parametrised() (AbstractModel method)
(Model method)
,
[1]
,
[2]
trim_results() (DefaultNestedSampler static method)
,
[1]
tuple_prod() (in module jaxns.internals.shapes)
U
U0 (SeedPoint attribute)
U_ndims (BaseAbstractModel property)
U_placeholder (BaseAbstractModel property)
U_samples (NestedSamplerResults attribute)
U_solution (GlobalOptimisationResults attribute)
,
[1]
unbatch_state() (in module jaxns.internals.tree_structure)
UniDimSliceSampler (class in jaxns.samplers)
(class in jaxns.samplers.uni_slice_sampler)
UniformSampler (class in jaxns.samplers)
(class in jaxns.samplers.uniform_samplers)
UnnormalisedDirichlet (class in jaxns)
(class in jaxns.framework)
(class in jaxns.framework.special_priors)
update_evicence_calculation() (in module jaxns.internals.shrinkage_statistics)
UType (in module jaxns.internals.types)
V
V (in module jaxns.internals.cumulative_ops)
value (LogSpace property)
(Prior property)
,
[1]
,
[2]
var() (LogSpace method)
verbose (EvidenceMaximisation attribute)
,
[1]
X
X_placeholder (BaseAbstractModel property)
X_solution (GlobalOptimisationResults attribute)
,
[1]
XType (in module jaxns.internals.types)
Y
Y (in module jaxns.internals.cumulative_ops)
Read the Docs
v: latest
Versions
latest
main
Downloads
On Read the Docs
Project Home
Builds