ACHR¶
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ACBSampler
(model, warmupPoints, fileName, nFiles, pointsPerFile, nMixPts, nWarmupNeeded, saveMatFlag, biasOpt)[source]¶ Artificial centering boundary sampler
Usage
ACBSampler(model, warmupPoints, fileName, nFiles, pointsPerFile, nMixPts, nWarmupNeeded, saveMatFlag, biasOpt)Inputs
- model – Model structure
- warmupPoints – Warmup points
- fileName – Base fileName for saving results
- nFiles – Number of sample point files created
- pointsPerFile – Number of points per file saved
- nMixPts – Number of steps initially used for mixing (not saved)
Optional inputs
- nWarmupNeeded – Number of warmup points needed (Default = 20000)
- saveMatFlag – Save points in mat format vs txt format (Default = true)
- biasOpt – Options for biasing sampler (Default = no bias)
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ACHRSampler
(model, warmupPoints, fileName, nFiles, pointsPerFile, stepsPerPoint, initPoint, fileBaseNo, maxTime, printLevel, minFlux, maxFlux)[source]¶ Artificial Centering Hit-and-Run sampler
Usage
ACHRSampler(model, warmupPoints, fileName, nFiles, pointsPerFile, stepsPerPoint, initPoint, fileBaseNo, maxTime)Inputs
- model – Model structure
- warmupPoints – Warmup points
- fileName – Base fileName for saving results
- nFiles – Number of files created
- pointsPerFile – Number of points per file saved
- stepsPerPoint – Number of sampler steps per point saved
- printLevel – 0 silent / 1 active
Optional inputs
- initPoint – Initial point (Default = centerPoint)
- fileBaseNo – Base file number for continuing previous sampler run (Default = 0)
- maxTime – Maximum time limit (Default = 36000 s)
- minFlux – Lower bound of the solution space given by FVA
- maxFlux – Upper bound of the solution space given by FVA
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ACHRSamplerParallelGeneral
(sampleStruct, nLoops, stepsPerPoint, maxtime, proc, fdirectory)[source]¶ Artificial Centering Hit-and-Run sampler with in place (memory) point management
Usage
sampleStruct = ACHRSamplerParallelGeneral(sampleStruct, nLoops, stepsPerPoint, maxtime, proc, fdirectory)Inputs
- sampleStruct – Sampling structure
- nLoops – Number of iterations
- stepsPerPoint – Number of sampler steps per point saved
- maxtime – Amount of time to spend on calculation (in seconds)
Optional inputs
- proc – Number of processes if > 0. Otherwise, the proces #.
- fdirectory – Do not use this parameter when calling function directly.
Output
- sampleStruct – Sampling structure with sample points
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convRevSamples
(model, samples)[source]¶ Converts signs for reactions that are only running in reverse direction
Usage
[model, samples] = convRevSamples(model, samples)Input
- model – Constraint-based model
Optional input
- samples – Sample set
Outputs
- model – COBRA model structure with negative-direction fluxes reversed
- samples – Sample set with negative-direction fluxes reversed
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createHRWarmup
(model, nPoints, verbFlag, bias, nPointsCheck)[source]¶ Creates a warmup point set for hit-and-run sampling by combining orthogonal and random points
Usage
warmupPts = createHRWarmup(model, nPoints, verbFlag, bias, nPointsCheck)Input
- model – Model structure
Optional inputs
- nPoints – Number of warmup points (Default = 5000);
- verbFlag – Verbose flag (Default = false)
- bias –
Structure with fields:
- method - Biasing distribution: ‘uniform’, ‘normal’
- index - The reaction indexes which to bias (nBias total)
- param - nBias x 2 matrix of parameters (for uniform it’s min max, for normal it’s mu, sigma).
Output
- warmupPts – Set of warmup points
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gpSampler
(sampleStruct, nPoints, bias, maxTime, maxSteps, threads, nPointsCheck)[source]¶ Samples an arbitrary linearly constrained space using a fixed number of points that are moved in parallel The space is defined by
\[\begin{split}A x \leq, =, \geq b \\ lb \leq x \leq ub\end{split}\]Usage
[sampleStructOut, mixedFraction] = gpSampler(sampleStruct, nPoints, bias, maxTime, maxSteps, threads, nPointsCheck)Input
sampleStruct – Structure describing the space to be sampled and previous point sets:
- A - LHS matrix (optionally, if not A script checks for S)
- b - RHS vector
- lb - Lower bound
- ub - Upper bound
- csense - Constraint type for each row in A (‘G’, ‘L’, ‘E’)
- warmupPoints - Set of warmup points (optional, generated by default)
- points - Currently sampled points (optional)
Optional inputs
- nPoints – Number of points used in sampling (default = 2 * nRxns or 5000 whichever is greater)
- bias –
Structure with fields:
- method - Biasing distribution: ‘uniform’, ‘normal’
- index - The reaction indexes which to bias (nBias total)
- param - nBias x 2 matrix of parameters (for uniform it’s min max, for normal it’s mu, sigma).
- maxTime – Maximum time alloted for the sampling in seconds (default 600 s, pass an empty number [] to set maxSteps instead)
- maxSteps – Maximum number of steps to take (default 1e10). Sampler will run until either maxStep or maxTime is reached. Set maxStep or maxTime to 0 and no sampling will occur (only warmup points generated).
- threads – number of threads the sampler will use. If you have a dual core machine, you can set it to 2 etc. The speed up is almost linear w/ the number of cores. If using this feature and 2009a or newer, a futher speedup can be obtained by starting matlab from the command line by “typing matlab -singleCompThread” New feature: if threads < 0, use distributed toolbox.
- nPointsCheck – Checks that minimum number of points (2 * nRxns) are used. (Default = true).
Outputs
- sampleStructOut – The sampling structure with some extra fields.
- mixedFract – The fraction mixed (relative to the warmupPts). A value of 1 means not mixed at all. A value of .5 means completely mixed.
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mixFraction
(sample1, sample2, fixed)[source]¶ Compares two sets of sampled points and determines how mixed they are.
Usage
mix = mixFraction(sample1, sample2, fixed)Input
- sample1, sample2 – Ordered set of points. The points must be in the same order otherwise it does not make sense.
Optional input
- fixed – The indexes of sampled reactions which are fixed and are not expected to mix. They are ignored.
Output
- mix – The mix fraction. Goes from 0 to 1 with 1 being completely unmixed and .5 being essentially perfectly mixed.
Example
example 1: mix = mixFraction(sample1, sample2) example 2: fixed = findRxnIDs({R1, R2, ..., Rx}) mix = mixFraction(sample1, sample2, fixed)
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removeCorrelRxns
(model, R, correlCutoff)[source]¶ Removes fully or almost fully correlated reactions
Usage
[selRxns, rxnSets, rxnList, Rfilt] = removeCorrelRxns(model, R, correlCutoff)Inputs
- model – COBRA model structure
- R – Correl coefficient matrix
Optional input
- correlCutoff – Cutoff level for fully correlated rxns (Default 0.99999)
Outputs
- selRxns – true/false vector that allow selecting non-redundant data
- rxnSets – Correlated reaction sets
- rxnList – Reaction list with correlated reactions concatenated
- Rfilt – Filtered R
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verifyPoints
(sampleStruct)[source]¶ Verify that a set of points are in the solutoin space of sampleStruct. Typically, this method would be called to check a set of warmup points or points generated via gpSampler. Also verifies if points moved from warmup points.
Usage
[errorsA, errorsLUB, stuckPoints] = verifyPoints(sampleStruct)Input
- sampleStruct – LPProblem containing points and warmup points
Outputs
- errorsA – Row index of the constraint in sampleStruct that is not consistent with the given points
- errorsLUB – Upper and lower bounds of the constraint + tolerance
- stuckPoints – Index of points which did not move.