pyABC - distributed, likelihood-free inference
- Release:
0.12.12
- Source code:

pyABC is a framework for distributed, likelihood-free inference. That means, if you have a model and some data and want to know the posterior distribution over the model parameters, i.e. you want to know with which probability which parameters explain the observed data, then pyABC might be for you.
All you need is some way to numerically draw samples from the model, given the model parameters. pyABC “inverts” the model for you and tells you which parameters were well matching and which ones not. You do not need to analytically calculate the likelihood function.
pyABC runs efficiently on multi-core machines and distributed cluster setups. It is easy to use and flexibly extensible.
User's guide
- What is pyABC about?
- Install
- Examples
- Getting started
- Algorithms and features
- Early stopping of model simulations
- Resuming stored ABC runs
- Custom priors
- Adaptive distances
- Informative distances and summary statistics
- Aggregating and weighting diverse data
- Wasserstein distances
- Data plots
- Measurement noise and exact inference
- Optimal acceptance thresholds
- Discrete parameters
- Look-ahead sampling
- External interfaces
- Application examples
- Parallel sampling
- Data store
- Visualization and analysis
- API reference
- pyabc.acceptor
- pyabc.copasi
- pyabc.distance
- Distances
AcceptAllDistance
AdaptiveAggregatedDistance
AdaptivePNormDistance
AggregatedDistance
BinomialKernel
Distance
DistanceWithMeasureList
FunctionDistance
FunctionKernel
IndependentLaplaceKernel
IndependentNormalKernel
InfoWeightedPNormDistance
MinMaxDistance
NegativeBinomialKernel
NoDistance
NormalKernel
PCADistance
PNormDistance
PercentileDistance
PoissonKernel
RangeEstimatorDistance
SlicedWassersteinDistance
StochasticKernel
WassersteinDistance
ZScoreDistance
- pyabc.epsilon
- Epsilons
AcceptanceRateScheme
ConstantEpsilon
DalyScheme
Epsilon
EssScheme
ExpDecayFixedIterScheme
ExpDecayFixedRatioScheme
FrielPettittScheme
ListEpsilon
ListTemperature
MedianEpsilon
NoEpsilon
PolynomialDecayFixedIterScheme
QuantileEpsilon
SilkOptimalEpsilon
Temperature
TemperatureBase
TemperatureScheme
- pyabc.external
- pyabc.external.r
- pyabc.external.julia
- pyabc.inference
- pyabc.inference_util
- Inference utilities
AnalysisVars
create_analysis_id()
create_prior_pdf()
create_simulate_from_prior_function()
create_simulate_function()
create_transition_pdf()
create_weight_function()
eps_from_hist()
evaluate_preliminary_particle()
evaluate_proposal()
generate_valid_proposal()
only_simulate_data_for_proposal()
termination_criteria_fulfilled()
- pyabc.model
- pyabc.parameters
- pyabc.population
- pyabc.populationstrategy
- pyabc.predictor
- pyabc.random_choice
- pyabc.random_variables
- pyabc.sampler
- Parallel sampling
ConcurrentFutureSampler
DaskDistributedSampler
MappingSampler
MulticoreEvalParallelSampler
MulticoreParticleParallelSampler
RedisEvalParallelSampler
RedisEvalParallelSamplerServerStarter
RedisStaticSampler
RedisStaticSamplerServerStarter
Sampler
SingleCoreSampler
nr_cores_available()
- pyabc.settings
- pyabc.sge
- pyabc.storage
- pyabc.sumstat
- pyabc.transition
- pyabc.util
- pyabc.visserver
- pyabc.visualization
- Visualization
plot_acceptance_rates_trajectory()
plot_contour_2d()
plot_contour_2d_lowlevel()
plot_contour_matrix()
plot_contour_matrix_lowlevel()
plot_credible_intervals()
plot_credible_intervals_for_time()
plot_data_callback()
plot_data_default()
plot_distance_weights()
plot_effective_sample_sizes()
plot_eps_walltime()
plot_eps_walltime_lowlevel()
plot_epsilons()
plot_histogram_1d()
plot_histogram_1d_lowlevel()
plot_histogram_2d()
plot_histogram_2d_lowlevel()
plot_histogram_matrix()
plot_histogram_matrix_lowlevel()
plot_kde_1d()
plot_kde_1d_highlevel()
plot_kde_2d()
plot_kde_2d_highlevel()
plot_kde_matrix()
plot_kde_matrix_highlevel()
plot_lookahead_acceptance_rates()
plot_lookahead_evaluations()
plot_lookahead_final_acceptance_fractions()
plot_model_probabilities()
plot_sample_numbers()
plot_sample_numbers_trajectory()
plot_sensitivity_sankey()
plot_total_sample_numbers()
plot_total_walltime()
plot_walltime()
plot_walltime_lowlevel()
- pyabc.weighted_statistics
Developer's guide
About
- Release Notes
- 0.12 Series
- 0.11 series
- 0.10 series
- 0.10.16 (2021-05-11)
- 0.10.15 (2021-05-09)
- 0.10.14 (2021-02-21)
- 0.10.13 (2021-02-04)
- 0.10.12 (2021-01-20)
- 0.10.11 (2021-01-02)
- 0.10.10 (2021-01-01)
- 0.10.9 (2020-11-28)
- 0.10.8 (2020-11-27)
- 0.10.7 (2020-08-20)
- 0.10.6 (2020-08-04)
- 0.10.5 (2020-08-01)
- 0.10.4 (2020-06-15)
- 0.10.3 (2020-05-17)
- 0.10.2 (2020-05-09)
- 0.10.1 (2020-03-17)
- 0.10.0 (2020-02-20)
- 0.9 series
- 0.9.26 (2020-01-24)
- 0.9.25 (2020-01-08)
- 0.9.24 (2019-11-19)
- 0.9.23 (2019-11-10)
- 0.9.22 (2019-11-05)
- 0.9.21 (2019-11-05)
- 0.9.20 (2019-10-30)
- 0.9.19 (2019-10-23)
- 0.9.18 (2019-10-20)
- 0.9.17 (2019-10-10)
- 0.9.16 (2019-10-08)
- 0.9.15 (2019-09-15)
- 0.9.14 (2019-08-08)
- 0.9.13 (2019-06-25)
- 0.9.12 (2019-05-02)
- 0.9.11 (2019-04-01)
- 0.9.10 (2019-03-27)
- 0.9.9 (2019-03-25)
- 0.9.8 (2019-02-21)
- 0.9.7 (2019-02-20)
- 0.9.6 (2019-02-01)
- 0.9.5 (2019-01-17)
- 0.9.4 (2018-12-18)
- 0.9.3 (2018-12-01)
- 0.9.2 (2018-09-10)
- 0.9.1 (2018-06-05)
- 0.9.0
- 0.8 series
- 0.7 series
- 0.6 series
- 0.5 series
- 0.4 series
- 0.3 series
- 0.2 series
- 0.1 series
- About
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