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API reference

The API reference is generated from the docstrings of the package.

sbmlsim

The top level modules: data, units and the shared output.

module description
data Data objects referencing simulation results and datasets, the input of plots and calculations
units unit registry of a model and unit conversions with pint
serialization JSON serialization of experiments
utils timing and other helpers
console shared rich console
log logging of the package

sbmlsim.model

Models and model changes, see Models.

module description
model.model AbstractModel, the model of a simulation experiment with its changes and selections
model.model_roadrunner RoadrunnerSBMLModel, the roadrunner instance of an SBML model with its units and parameter changes
model.model_change ModelChange, clamping species and other structural changes
model.model_resources resolving model sources, i.e., files, URNs and URLs

sbmlsim.simulation

Definition of simulations, see Timecourse simulations and Parameter scans.

module description
simulation.timecourse Timecourse and TimecourseSim, concatenated timecourses with changes
simulation.scan ScanSim, a simulation over the dimensions of parameter changes
simulation.sensitivity ModelSensitivity, sensitivity scans of parameters and initial conditions
simulation.range ranges of values for scans
simulation.change changes applied to a model before a simulation
simulation.algorithm Algorithm and AlgorithmParameter, the KISAO description of an integrator
simulation.kisaos the KISAO terms of the supported algorithms and parameters
simulation.calculation calculations on simulation results
simulation.base base classes shared by the simulation objects and SED-ML
simulation.simulation AbstractSim, the base of all simulations

sbmlsim.simulator, sbmlsim.task

Execution of simulations.

module description
simulator.simulation_serial SimulatorSerial, running timecourses and scans on a roadrunner model
task.task Task, a simulation applied to a model

sbmlsim.experiment, sbmlsim.result

Simulation experiments and their results, see Simulation experiments.

module description
experiment.experiment SimulationExperiment, models, datasets, simulations, tasks, data and figures of an experiment
experiment.runner ExperimentRunner, executing experiments and writing their results
result.xresult XResult, simulation results as an xarray dataset with units
result.datagenerator data generators processing results
result.report reports of results

sbmlsim.plot, sbmlsim.report

Figures and reports, see Plots and reports.

module description
plot.plotting Figure, Plot, Axis, Curve and their styles, the plot description independent of the backend
plot.serialization_matplotlib rendering of the figures with matplotlib
report.experiment_report HTML and markdown reports of simulation experiments

sbmlsim.fit

Parameter fitting, see Parameter fitting.

module description
fit.objects FitParameter, FitMapping, FitData and FitExperiment, the objects of a fit problem
fit.optimization OptimizationProblem, the residuals and cost of a fit problem
fit.options FitSettings and the options of the optimization, i.e., algorithms, residuals, weighting and loss functions
fit.parameters ParameterSet and ParameterSets, the fitted parameters a report is created from
fit.result OptimizationResult, the result of an optimization
fit.runner running optimizations serially or in parallel
fit.report FitReport, the figures and reports of one or more parameter sets
fit.cli FitDefinition and the general command line tools which run and report a fit
fit.sampling sampling of initial parameter values
fit.metrics FitMetrics and the metrics of a fit: PRED, IPRED, residuals, MSE, RMSE, R² and AIC
fit.helpers helpers for fitting
fit.petab_omex COMBINE archives of PEtab problems

sbmlsim.sensitivity

Local and global sensitivity analysis, see Sensitivity analysis.

module description
sensitivity.analysis the common analysis of a model, i.e., outputs, observables and the simulation of parameter samples
sensitivity.parameters selection, bounds and distributions of the analysed parameters
sensitivity.sensitivity_local local sensitivities by finite differences
sensitivity.sensitivity_sampling sampling based sensitivity and uncertainty analysis
sensitivity.sensitivity_morris Morris elementary effects screening
sensitivity.sensitivity_sobol variance based Sobol indices
sensitivity.sensitivity_fast Fourier amplitude sensitivity test (FAST)
sensitivity.classification classification of sensitivities and uncertainties
sensitivity.plots plots of the sensitivity results

sbmlsim.combine

SED-ML, NuML and COMBINE archives, see SED-ML and COMBINE archives.

module description
combine.sedml.parser SEDMLParser, a SED-ML document into a simulation experiment
combine.sedml.runner executing SED-ML files and COMBINE archives
combine.sedml.task tasks and repeated tasks of SED-ML
combine.sedml.data data descriptions, i.e., NuML, CSV and TSV data
combine.sedml.numl parser for NuML data
combine.sedml.report SED-ML reports
combine.sedml.io reading and writing SED-ML documents
combine.datagenerator data generators of SED-ML
combine.mathml evaluation of MathML expressions

sbmlsim.interpolation, sbmlsim.comparison

module description
interpolation.interpolation interpolation of datasets as SBML models
comparison.diff numerical comparison of simulation results from different simulators