Difference between revisions of "Sample population (analysis)"

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(Automatic synchronization with BioUML)
(Automatic synchronization with BioUML)
 
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* '''Variables to estimate''' – Variables to estimate
 
* '''Variables to estimate''' – Variables to estimate
 
* '''Simulation options''' – Simulation options
 
* '''Simulation options''' – Simulation options
** '''Engine type''' – Engine type.
+
** '''Selected engine''' – Selected simulation engine.
** '''Engine options''' – Engine options.
+
** '''Java simulation engine''' – Deterministic simulation engine to solve system of odinary differential equations.
 
*** '''Initial time''' – Initial time.
 
*** '''Initial time''' – Initial time.
 
*** '''Completion time''' – Completion time.
 
*** '''Completion time''' – Completion time.
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**** '''Mu''' – Upper bandwidth of Banded Jacobian
 
**** '''Mu''' – Upper bandwidth of Banded Jacobian
 
**** '''Ml''' – Lower bandwidth of Banded Jacobian
 
**** '''Ml''' – Lower bandwidth of Banded Jacobian
**** '''Detect incorrect numbers (NaNs and Infs''' – If true then simulation will end when NaN or Infinity encountered
+
**** '''Detect incorrect numbers (NaNs and Infs)''' – If true then simulation will end when NaN or Infinity encountered
 
*** '''Code generation type''' – Type of code generation: if auto then BioUML will try to choose by itself.
 
*** '''Code generation type''' – Type of code generation: if auto then BioUML will try to choose by itself.
 
*** '''Constraints violation''' – How to handle constraints violation in the model.
 
*** '''Constraints violation''' – How to handle constraints violation in the model.

Latest revision as of 18:15, 9 December 2020

Analysis title
Default-analysis-icon.png Sample population
Provider
Institute of Systems Biology
Class
PopulationSampling
Plugin
biouml.plugins.pharm (Support for Pharmocological models)

[edit] Description

Sample population.

[edit] Parameters:

  • Diagram – Diagram.
  • Experimental data – Experimental data
  • Initial values – Mean and variance values for estimated variables.
  • Result path – Result Path.
  • Population size per chain – Population size per chain.
  • Preliminary steps – Preliminary steps
  • Acceptance rate – Acceptance rate
  • Random seed – Seed for random algorithms. 0 means seed defined by time (recommended)
  • Observed variables – Observed variables
  • Variables to estimate – Variables to estimate
  • Simulation options – Simulation options
    • Selected engine – Selected simulation engine.
    • Java simulation engine – Deterministic simulation engine to solve system of odinary differential equations.
      • Initial time – Initial time.
      • Completion time – Completion time.
      • Time increment – Time increment.
      • Simulator name – Simulator name.
      • Simulator options – Simulator options.
        • Absolute tolerance – Absolute tolerance.
        • Relative tolerance – Relative tolerance.
        • Statistics mode – Statistics mode.
        • Integration method – Integration method (ADAMS or BDF)
        • Inner linear solver type – Inner linear solver type
        • Jacobian approximation type – Jacobian approximation type
        • Steps limit – Limitation for solver steps count
        • Minimum time step – Minimum time step.
        • Maximum time step inverted – 1 / maximum time step.
        • Mu – Upper bandwidth of Banded Jacobian
        • Ml – Lower bandwidth of Banded Jacobian
        • Detect incorrect numbers (NaNs and Infs) – If true then simulation will end when NaN or Infinity encountered
      • Code generation type – Type of code generation: if auto then BioUML will try to choose by itself.
      • Constraints violation – How to handle constraints violation in the model.
      • Fast reactions handling – Method to handle fast reactions: either as separate ODE system with very fast rate or as algebraic system.
      • Algebraic solver name – Name of algebraic solver which will be used
      • Algebraic Solver parameters – Parameters of algebraic solver which will be used
        • Maximum iterations – Maximum iterations
        • Function tolerance – Function tolerance
        • Minimal gradient tolerance – Minimal gradient tolerance
        • Points tolerance – Points tolerance
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