Optimus {ROptimus}

Acceptance Ratio Simulated Annealing and Acceptance Ratio Replica Exchange Monte Carlo Optimisation Engine

Description

Acceptance Ratio Simulated Annealing and Acceptance Ratio Replica Exchange Monte Carlo Optimisation Engine

Usage

Optimus(
  NUMITER = 1e+06,
  STATWINDOW = 70,
  T.INI = 1e-05,
  T.ADJSTEP = 5e-09,
  TSCLnum = 2,
  T.SCALING = 3,
  T.MIN = 5e-09,
  T.DELTA = 2,
  DUMP.FREQ = 10000,
  LIVEPLOT = TRUE,
  LIVEPLOT.FREQ = 1e+05,
  PDFheight = 29,
  PDFwidth = 20,
  NCPU = 4,
  LONG = TRUE,
  SEED = 840,
  OPTNAME = "",
  DATA = NULL,
  K.INITIAL = 0,
  rDEF,
  mDEF,
  uDEF,
  EXCHANGE.FREQ = 1000,
  ACCRATIO = c(90, 50, 5, 1),
  CYCLES = 10,
  ACCRATIO.IN = 90,
  ACCRATIO.FIN = 0.5,
  OPT.TYPE = "SA",
  DIR,
  starcore = NULL
)

Arguments

NUMITER

Number of model optimisation steps.

STATWINDOW

Number of last ongoing iterations to calculate acceptance ratio for temperature auto-adjustment.

T.INI

Initial temperature (K) for Metropolis criterion.

T.ADJSTEP

Temperature change step-size for temperature auto-adjustment based on the actual acceptance ratio.

TSCLnum

Cutoff for one of the NumofAccRatSMIdeal and NumofAccRatGRIdeal numbers after which the adjustment step is multiplied by T.SCALING.

T.SCALING

See above.

T.MIN

Value to which the pseudo-temperature is set when the

T.DELTA

Minimum value by which acceptance ratio in a STATWINDOW must differ from the ideal acceptance ratio for the temperature control unit to make a temperature adjustment.

DUMP.FREQ

The frequency (in steps) of writing the found ongoing best model.

LIVEPLOT

Plotting the optimisation process in a pdf file.

LIVEPLOT.FREQ

Frequency (in steps) of plotting the results.

PDFheight

Plot height in inches.

PDFwidth

Plot width in inches.

NCPU

Number of CPU cores to use, by running more replicas of the optimisation. The usage of more than 1 cores will attempt to load the foreach and doParallel libraries in the case of SA Optimus

LONG

If TRUE, it means that a long simulation is expected to be done, hence the memory-friendly mode will be activated.

SEED

Setting the seed for the random number generator.

OPTNAME

The name of the optimisation process.

DATA

A list that holds any supplementary data that functions mDEF or uDEF need to access.

K.INITIAL

The initial parameter configuration from which the optimisation process will begin.

rDEF

Function that defines a rule by which the parameters(K) are randomly altered.

mDEF

Model function that operates on the parameters to be optimized (K) and returns an observable object O.

uDEF

Function that evaluates the performance of a given set of parameters K.

EXCHANGE.FREQ

Frequency of exchanges (NUMITER should be divisible by this number, for RE Optimus).

ACCRATIO

Vector of Acceptance Ratios for each replica (length of ACCRATIO must be equal to NCPU, for RE Optimus).

CYCLES

Number of annealing cycles (NUMITER should be divisible by this number, for SA Optimus).

ACCRATIO.IN

Initial acceptance ratio (%) at the beginning of each constituent annealing cycles (for SA Optimus).

ACCRATIO.FIN

Final acceptance ratio (%) at the end of each constituent annealing cycles (for SA Optimus).

OPT.TYPE

String specifying which optimisation protocol to use. Enter "SA" for Simulated Annealing or "RE" for Replica Exchange (default value is "SA")

DIR

String specifying which optimisation protocol to use.

starcore

Experimental variable of type list, holding some parameters for in-lab starcore use only.

Value

A probabilistic optimal parameter configuration K.

Examples

K <- IJ_ORIG
K$j <- sample(x=K$j, size=nrow(K), replace=FALSE)
out.dir <- tempdir()

Optimus(NCPU=1, OPTNAME="IJ.NEW.OPTI.SA", NUMITER=500, CYCLES=2, DIR=out.dir,
        DUMP.FREQ=10, LONG=FALSE, OPT.TYPE="SA", K.INITIAL=K,
        rDEF=ex.r.fun, mDEF=ex.m.fun, uDEF=ex.u.fun,
        DATA=list(IJ_ORIG=IJ_ORIG, gaplimit=50, numContacts=nrow(IJ_ORIG)))