loopTillConvergence | R Documentation |
Iteratively call testAllSigMatrices numLoops times with the option to fast stop if correlation, correlation spear, mae and rmse all converge
loopTillConvergence( numLoops, fastStop, exprData, changePer, handMetaCluster, testOnHalf, condTol = 1.01 )
numLoops |
The number of iterations. Set to null to loop until results converge. |
fastStop |
Set to TRUE to break the loop when correlation, correlation spear, mae and rmse all converge |
exprData |
The single cell matrix |
changePer |
The maximum percentage of change allowed for convergence |
handMetaCluster |
A List of pre-defined meta clusters. Set to NULL to automatically group indistinguishable cells into same cluster use clustWspillOver (DEFAULT: NULL) |
testOnHalf |
Set to TRUE to leave half the data as a test set to validate all the matrices |
condTol |
The tolerance in the reconstruction algorithm. 1.0 = no tolerance, 1.05 = 5% tolerance (DEFAULT: 1.01) |
A list of results generated from all the iterative calls of testAllSigMatrices
ct1 <- runif(1000, 0, 100) ct2 <- runif(1000, 0, 100) ct3 <- runif(1000, 0, 100) ct4 <- runif(1000, 0, 100) dataMat <- cbind(ct1, ct1, ct1, ct1, ct1, ct1, ct2, ct2, ct2, ct2, ct3, ct3, ct3,ct3,ct4,ct4) rownames(dataMat) <- make.names(rep('gene', nrow(dataMat)), unique=TRUE) noise <- matrix(runif(nrow(dataMat)*ncol(dataMat), -2, 2), nrow = nrow(dataMat), byrow = TRUE) dataMat <- dataMat + noise #options(mc.cores=2) # This is a meta-function that calls other functions, # The execution speed is too slow for the CRAN automated check #loopTillConvergence(numLoops=10, fastStop=TRUE, exprData=dataMat, # changePer=10,handMetaCluster=NULL, testOnHalf=TRUE)
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