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"""A list of the simulation methods."""
# [['category',
# [['method', hasGeneric, hasCustom, hasPython,
# [['options', 'executable', 'parameterName', 'parameterValue',
# 'parameterToolTip'],
# ...]], ...]]]
# The first method is the default. The first option for each method is the
# default.
_homogeneousTimeSeriesUniform_direct =\
['Direct', True, True, False,
[['2-D search', 'HomogeneousDirect2DSearch', '', '', ''],
['2-D search, sorted', 'HomogeneousDirect2DSearchSorted', '', '', ''],
['2-D search, bubble sort', 'HomogeneousDirect2DSearchBubbleSort', '', '', ''],
['Composition rejection', 'HomogeneousDirectCompositionRejection', '', '',
''],
['Binary search, full CDF', 'HomogeneousDirectBinarySearch', '', '', ''],
['Binary search, sorted CDF', 'HomogeneousDirectBinarySearchSorted', '',
'', ''],
['Binary search, recursive CDF',
'HomogeneousDirectBinarySearchRecursiveCdf', '', '', ''],
['Linear search', 'HomogeneousDirectLinearSearch', '', '', ''],
['Linear search, delayed update',
'HomogeneousDirectLinearSearchDelayedUpdate', '', '', ''],
['Linear search, sorted', 'HomogeneousDirectLinearSearchSorted', '', '',
''],
['Linear search, bubble sort', 'HomogeneousDirectLinearSearchBubbleSort',
'', '', '']]
]
_homogeneousTimeSeriesUniform_next =\
['Next Reaction', True, True, False,
[['Hashing', 'HomogeneousNextReactionHashing', '', '', ''],
['Binary heap, pointer', 'HomogeneousNextReactionBinaryHeapPointer', '',
'', ''],
['Binary heap, pair', 'HomogeneousNextReactionBinaryHeapPair', '', '',
''],
['Partition', 'HomogeneousNextReactionPartitionCostAdaptive', '', '', ''],
['Linear search', 'HomogeneousNextReactionLinearSearchUnrolled', '', '',
'']]
]
_homogeneousTimeSeriesUniform_first =\
['First Reaction', True, True, False,
[['Simple', 'HomogeneousFirstReaction', '', '', ''],
['Reaction influence', 'HomogeneousFirstReactionInfluence', '', '', ''],
['Absolute time', 'HomogeneousFirstReactionAbsoluteTime', '', '', '']]
]
_homogeneousTimeSeriesUniform_tau =\
['Tau-Leaping', True, True, False,
[['Runge-Kutta, 4th order', 'HomogeneousTauLeapingRungeKutta4',
'Error:', '0.01', 'The allowed error in a step.'],
['Midpoint', 'HomogeneousTauLeapingMidpoint', 'Error:', '0.01',
'The allowed error in a step.'],
['Forward', 'HomogeneousTauLeapingForward', 'Error:', '0.01',
'The allowed error in a step.'],
['Runge-Kutta, 4th order, no correction',
'HomogeneousTauLeapingRungeKutta4NoCorrection', 'Error:', '0.01',
'The allowed error in a step.'],
['Midpoint, no correction', 'HomogeneousTauLeapingMidpointNoCorrection',
'Error:', '0.01', 'The allowed error in a step.'],
['Forward, no correction', 'HomogeneousTauLeapingForwardNoCorrection',
'Error:', '0.01', 'The allowed error in a step.'],
['Runge-Kutta, 4th order, fixed step size',
'HomogeneousTauLeapingFixedRungeKutta4', 'Step size:', '0.01',
'The time step.'],
['Midpoint, fixed step size', 'HomogeneousTauLeapingFixedMidpoint',
'Step size:', '0.01', 'The time step.'],
['Forward, fixed step size', 'HomogeneousTauLeapingFixedForward',
'Step size:', '0.01', 'The time step.']]
]
_homogeneousTimeSeriesUniform_sal =\
['SAL Tau-Leaping', True, False, False,
[['Linear', 'HomogeneousTauLeapingSalLinear',
'Error:', '0.01', 'The allowed error in a step.'],
['Linear, fixed step size', 'HomogeneousTauLeapingSalFixedLinear',
'Step size:', '0.01', 'The time step.']]
]
_homogeneousTimeSeriesUniform_tauImplicit =\
['Implicit Tau-Leaping', True, False, False,
[['Euler, fixed step size', 'HomogeneousTauLeapingImplicitFixedEuler',
'Step size:', '0.01', 'The time step.']]
]
_homogeneousTimeSeriesUniform_hybrid =\
['Hybrid Direct/Tau-Leaping', True, True, False,
[['Runge-Kutta, 4th order', 'HomogeneousHybridDirectTauLeapingRungeKutta4',
'Error:', '0.01', 'The allowed error in a step.'],
['Midpoint', 'HomogeneousHybridDirectTauLeapingMidpoint', 'Error:',
'0.01', 'The allowed error in a step.'],
['Forward', 'HomogeneousHybridDirectTauLeapingForward', 'Error:', '0.01',
'The allowed error in a step.']]
]
_homogeneousTimeSeriesUniform =\
['Time Series, Uniform',
[_homogeneousTimeSeriesUniform_direct, _homogeneousTimeSeriesUniform_next,
_homogeneousTimeSeriesUniform_first, _homogeneousTimeSeriesUniform_tau,
_homogeneousTimeSeriesUniform_sal,
_homogeneousTimeSeriesUniform_tauImplicit,
_homogeneousTimeSeriesUniform_hybrid]
]
_homogeneousTimeSeriesAllReactions =\
['Time Series, All Reactions',
[['Direct', True, True, False,
[['2-D search', 'HomogeneousDirectAllReactions2DSearch', '', '', '']]
]]
]
_homogeneousTimeSeriesDeterministic =\
['Time Series, Deterministic',
[['ODE, Integrate Reactions', True, True, False,
[['Runge-Kutta, Cash-Karp', 'HomogeneousOdeReactionRungeKuttaCashKarp',
'Error:', '1e-8', 'The allowed error in a step.'],
['Runge-Kutta, Cash-Karp, fixed step size',
'HomogeneousOdeReactionFixedRungeKuttaCashKarp', 'Step size:', '0.01',
'The time step.'],
['Runge-Kutta, 4th order, fixed step size',
'HomogeneousOdeReactionFixedRungeKutta4', 'Step size:', '0.01',
'The time step.'],
['Midpoint, fixed step size', 'HomogeneousOdeReactionFixedMidpoint',
'Step size:', '0.01', 'The time step.'],
['Forward, fixed step size', 'HomogeneousOdeReactionFixedForward',
'Step size:', '0.01', 'The time step.']
]],
['Mathematica', False, False, False,
[['NDSolve', 'MathematicaNDSolve', '', '', '']]
]
]
]
_homogeneousHistogramsTransient =\
['Histograms, Transient Behavior',
[['Direct', True, True, False,
[['Standard', 'HomogeneousHistogramsDirect2DSearch', '', '', ''],
['Tree Exp. Last',
'HomogeneousHistogramsTransientDirectTreeExponentialLast',
'', '', ''],
['Tree Exp. Limit',
'HomogeneousHistogramsTransientDirectTreeExponentialLimit',
'', '', ''],
['Tree Hypoexp. Limit',
'HomogeneousHistogramsTransientDirectTreeHypoexponentialLimit',
'# of parameters:', '10', 'The number of parameters in the hypoexponential distribution.'],
['Tree Normal Approx.',
'HomogeneousHistogramsTransientDirectTreeNormalApproximation',
'Allowed error:', '0.1', 'The allowed error in the normal approximation of the hypoexponental distribution.']
# ,
# ['Multi-time', 'HomogeneousHistogramsMultiTimeDirect2DSearch', 'Multiplicity:', '16'],
# ['Tree', 'HomogeneousHistogramsDirectTree', 'Multiplicity:', '8']
]]
]
]
_homogeneousHistogramsSteadyState =\
['Histograms, Steady State',
[['Direct', True, True, False,
[['Elapsed time', 'HomogeneousHistogramsAverageElapsedTime', '', '', ''],
['Time steps', 'HomogeneousHistogramsAverage', '', '', ''],
['All possible steps', 'HomogeneousHistogramsAverageAps', '', '', '']]]
]
]
_statisticsTransient =\
['Statistics, Transient Behavior',
[['Import Solution', False, False, False,
[['', '', '', '', '']
]]
]
]
_statisticsSteadyState =\
['Statistics, Steady State',
[['Import Solution', False, False, False,
[['', '', '', '', '']
]]
]
]
_inhomogeneousTimeSeriesUniform =\
['Time Series, Uniform',
[['Direct', False, True, False,
[['Constant propensities', 'InhomogeneousTimeSeriesUniformDirect',
'', '', '']]]
]
]
_inhomogeneousTimeSeriesAllReactions =\
['Time Series, All Reactions',
[['Direct', False, True, False,
[['Constant propensities', 'InhomogeneousTimeSeriesAllReactionsDirect',
'', '', '']]]
]
]
_inhomogeneousTimeSeriesDeterministic =\
['Time Series, Deterministic',
[['ODE, Integrate Reactions', False, True, False,
[['Runge-Kutta, Cash-Karp', 'InhomogeneousOdeReactionRungeKuttaCashKarp',
'Error:', '1e-8', 'The allowed error in a step.']
]]
]
]
_inhomogeneousHistogramsTransient =\
['Histograms, Transient Behavior',
[['Direct', False, True, False,
[['Constant propensities', 'InhomogeneousHistogramsTransientDirect',
'', '', '']
]]
]
]
_inhomogeneousHistogramsSteadyState =\
['Histograms, Steady State',
[['Direct', False, True, False,
[['Time steps', 'InhomogeneousHistogramsSteadyStateDirectTimeSteps',
'', '', '']]]
]
]
_eventsTimeSeriesUniform =\
['Time Series, Uniform',
[['Direct', False, False, True,
[['Constant propensities', '',
'', '', '']]],
['First Reaction', False, False, True,
[['Constant propensities', '',
'', '', '']]]
]
]
_homogeneous =\
[_homogeneousTimeSeriesUniform, _homogeneousTimeSeriesAllReactions,
_homogeneousTimeSeriesDeterministic, _homogeneousHistogramsTransient,
_homogeneousHistogramsSteadyState, _statisticsTransient,
_statisticsSteadyState]
_inhomogeneous =\
[_inhomogeneousTimeSeriesUniform, _inhomogeneousTimeSeriesAllReactions,
_inhomogeneousTimeSeriesDeterministic, _inhomogeneousHistogramsTransient,
_inhomogeneousHistogramsSteadyState, _statisticsTransient,
_statisticsSteadyState]
_events =\
[_eventsTimeSeriesUniform, _statisticsTransient, _statisticsSteadyState]
_solvers = [_homogeneous, _inhomogeneous, _events]
timeDependence = ['Time Homogeneous', 'Time Inhomogeneous', 'Use Events']
categories = [[x[0] for x in t] for t in _solvers]
methods = [[[x[0] for x in y[1]] for y in t] for t in _solvers]
hasGeneric = [[[x[1] for x in y[1]] for y in t] for t in _solvers]
hasCustom = [[[x[2] for x in y[1]] for y in t] for t in _solvers]
hasPython = [[[x[3] for x in y[1]] for y in t] for t in _solvers]
options = [[[[x[0] for x in y[4]] for y in z[1]] for z in t] for t in _solvers]
names = [[[[x[1] for x in y[4]] for y in z[1]] for z in t] for t in _solvers]
parameterNames1 = [[[[x[2] for x in y[4]] for y in z[1]] for z in t] for t in _solvers]
parameterValues1 = [[[[x[3] for x in y[4]] for y in z[1]] for z in t] for t in _solvers]
parameterToolTips1 = [[[[x[4] for x in y[4]] for y in z[1]] for z in t] for t in _solvers]
numberOfTimeDependence = len(timeDependence)
numberOfCategories = [len(category) for category in categories]
numberOfMethods = [[len(x) for x in method] for method in methods]
numberOfOptions = [[[len(x) for x in y] for y in option] for option in options]
def usesFrames(timeDependenceIndex, categoryIndex):
return categories[timeDependenceIndex][categoryIndex] in \
('Time Series, Uniform', 'Time Series, Deterministic',
'Histograms, Transient Behavior')
def usesStatistics(timeDependenceIndex, categoryIndex):
return categories[timeDependenceIndex][categoryIndex] in \
('Statistics, Transient Behavior', 'Statistics, Steady State')
def isStochastic(timeDependenceIndex, categoryIndex):
return categories[timeDependenceIndex][categoryIndex] !=\
'Time Series, Deterministic'
def isDiscrete(timeDependenceIndex, categoryIndex):
return categories[timeDependenceIndex][categoryIndex] !=\
'Time Series, Deterministic'
def supportsEvents(timeDependenceIndex):
return timeDependenceIndex == 2
if __name__ == '__main__':
print('\ntimeDependence')
print(timeDependence)
print('\ncategories')
print(categories)
print('\nmethods')
print(methods)
print('\nhasGeneric')
print(hasGeneric)
print('\nhasCustom')
print(hasCustom)
print('\nhasPython')
print(hasPython)
print('\noptions')
print(options)
print('\nnames')
print(names)
print('\nparameterNames1')
print(parameterNames1)
print('\nparameterValues1')
print(parameterValues1)
print('\nparameterToolTips1')
print(parameterToolTips1)
print('\nnumberOfTimeDependence')
print(numberOfTimeDependence)
print('\nnumberOfCategories')
print(numberOfCategories)
print('\nnumberOfMethods')
print(numberOfMethods)
print('\nnumberOfOptions')
print(numberOfOptions)
|
