R/801-getCPI.R
In wind22zhu/BioMedR: Generating Various Molecular Representations for Chemicals, Proteins, DNAs, RNAs and Their Interactions
.inner = function (a, b, f, ...) {
# For computing column-by-column (pseudo)-tensor product type interactions
f = match.fun(f)
apply(b, 2, function (x) apply(a, 1, function (y) f(x, y, ...)))
}
.getCPICombine = function (drugmat, protmat) {
return(cbind(drugmat, protmat))
}
.getCPITensor = function (drugmat, protmat, row, dcol, pcol) {
return(array(.inner(t(drugmat), protmat, '*'), c(row, dcol * pcol)))
}
.getPPICombine = function (protmat1, protmat2) {
return(cbind(protmat1, protmat2))
}
.getPPITensor = function (protmat1, protmat2, row, col) {
return(array(.inner(t(protmat1), protmat2, '*'), c(row, col^2)))
}
.getPPIEntry = function (protmat1, protmat2) {
return(cbind((protmat1 * protmat2), (protmat1 + protmat2)))
}
.getDDICombine = function (DNAmat1, DNAmat2) {
return(cbind(DNAmat1, DNAmat2))
}
.getDDITensor = function (DNAmat1, DNAmat2, row, col) {
return(array(.inner(t(DNAmat1), DNAmat2, '*'), c(row, col^2)))
}
.getDDIEntry = function (DNAmat1, DNAmat2) {
return(cbind((DNAmat1 * DNAmat2), (DNAmat1 + DNAmat2)))
}
.getDPIinner = function (a, b, f, ...) {
# For computing column-by-column (pseudo)-tensor product type interactions
f = match.fun(f)
apply(b, 2, function (x) apply(a, 1, function (y) f(x, y, ...)))
}
.getDPICombine = function (DNAmat, protmat) {
return(cbind(DNAmat, protmat))
}
.getDPITensor = function (DNAmat, protmat, row, dcol, pcol) {
return(array(.getDPIinner(t(DNAmat), protmat, '*'), c(row, dcol * pcol)))
}
.getCCICombine = function (drugmat1, drugmat2) {
return(cbind(drugmat1, drugmat2))
}
.getCCITensor = function (drugmat1, drugmat2, row, col) {
return(array(.inner(t(drugmat1), drugmat2, '*'), c(row, col^2)))
}
.getCCIEntry = function (drugmat1, drugmat2) {
return(cbind((drugmat1 * drugmat2), (drugmat1 + drugmat2)))
}
.getCDIinner = function (a, b, f, ...) {
# For computing column-by-column (pseudo)-tensor product type interactions
f = match.fun(f)
apply(b, 2, function (x) apply(a, 1, function (y) f(x, y, ...)))
}
.getCDICombine = function (drugmat, DNAmat) {
return(cbind(drugmat, DNAmat))
}
.getCDITensor = function (drugmat, DNAmat, row, dcol, pcol) {
return(array(.getCDIinner(t(drugmat), DNAmat, '*'), c(row, dcol * pcol)))
}
#' @title Generating Interaction Descriptors
#'
#' @description Generating Interaction Descriptors
#'
#' @details This function calculates the interaction descriptors
#' by three types of interaction:
#' \itemize{
#' \item \code{combine} - combine the two descriptor matrix,
#' result has \code{(p1 + p2)} columns
#' \item \code{tensorprod} - calculate column-by-column
#' (pseudo)-tensor product type interactions, result has
#' \code{(p1 * p2)} columns
#' \item \code{entrywise} - calculate entrywise product and
#' entrywise sum of the two matrices, then combine them,
#' result has \code{(p + p)} columns
#' }
#'
#' @param drugmat The compound descriptor matrix.
#' @param protmat The protein descriptor matrix.
#' @param type The interaction type, one or more of
#' \code{"combine"}, \code{"tensorprod"}, and \code{"entrywise"}.
#'
#' @return A matrix containing the interaction descriptors
#'
#' @keywords getCPI getCDI getDPI getPPI getDDI getCCI interaction
#'
#' @aliases getCPI
#'
#' @author Min-feng Zhu <\email{wind2zhu@@163.com}>,
#' Nan Xiao <\url{http://r2s.name}>
#'
#' @export getCPI
#'
#' @examples
#' x = matrix(1:10, ncol = 2)
#' y = matrix(1:15, ncol = 3)
#' # getCPI
#' getCPI(x, y, 'combine')
#' # getCDI
#' getCDI(x, y, 'tensorprod')
#' # getDPI
#' getDPI(x, y, type = c('combine', 'tensorprod'))
#' getDPI(x, y, type = c('tensorprod', 'combine'))
#'
getCPI = function (drugmat, protmat, type = c('combine', 'tensorprod')) {
if (!is.matrix(drugmat)) drugmat = as.matrix(drugmat)
if (!is.matrix(protmat)) protmat = as.matrix(protmat)
drugrow = nrow(drugmat)
protrow = nrow(protmat)
if (drugrow != protrow) stop('Matrix row count must match')
drugcol = ncol(drugmat)
protcol = ncol(protmat)
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getCPICombine(drugmat, protmat)
} else if (all(type == 'tensorprod')) {
result = .getCPITensor(drugmat, protmat, row = drugrow,
dcol = drugcol, pcol = protcol)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getCPICombine(drugmat, protmat),
.getCPITensor(drugmat, protmat, row = drugrow,
dcol = drugcol, pcol = protcol))
} else {
stop('Interaction type must be in "tensorprod" and "combine" or both')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getPPI
#'
#' @param protmat1 The first protein descriptor matrix,
#' must have the same ncol with \code{protmat2}.
#' @param protmat2 The second protein descriptor matrix,
#' must have the same ncol with \code{protmat1}.
#'
#' @export getPPI
#'
#' @examples
#' x = matrix(1:10, ncol = 2)
#' y = matrix(5:14, ncol = 2)
#'
#' # getPPI
#' getPPI(x, y, type = 'combine')
#' getPPI(x, y, type = 'tensorprod')
#' # getDDI
#' getDDI(x, y, type = 'entrywise')
#' getDDI(x, y, type = c('combine', 'tensorprod'))
#' # getCCI
#' getCCI(x, y, type = c('combine', 'entrywise'))
#' getCCI(x, y, type = c('entrywise', 'tensorprod'))
#' getCCI(x, y, type = c('combine', 'entrywise', 'tensorprod'))
getPPI = function (protmat1, protmat2, type = c('combine', 'tensorprod',
'entrywise')) {
if (!is.matrix(protmat1)) protmat1 = as.matrix(protmat1)
if (!is.matrix(protmat2)) protmat2 = as.matrix(protmat2)
protrow1 = nrow(protmat1)
protrow2 = nrow(protmat2)
if (protrow1 != protrow2) stop('Matrix row count must match')
protcol1 = ncol(protmat1)
protcol2 = ncol(protmat2)
if (protcol1 != protcol2) stop('Matrix column count must match')
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getPPICombine(protmat1, protmat2)
} else if (all(type == 'tensorprod')) {
result = .getPPITensor(protmat1, protmat2,
row = protrow1, col = protcol1)
} else if (all(type == 'entrywise')) {
result = .getPPIEntry(protmat1, protmat2)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getPPICombine(protmat1, protmat2),
.getPPITensor(protmat1, protmat2,
row = protrow1, col = protcol1))
} else if (length(setdiff(type, c('tensorprod', 'entrywise'))) == 0L) {
result = cbind(.getPPITensor(protmat1, protmat2,
row = protrow1,
col = protcol1),
.getPPIEntry(protmat1, protmat2))
} else if (length(setdiff(type, c('combine', 'entrywise'))) == 0L) {
result = cbind(.getPPICombine(protmat1, protmat2),
.getPPIEntry(protmat1, protmat2))
} else if (length(setdiff(type, c('tensorprod',
'combine',
'entrywise'))) == 0L) {
result = cbind(.getPPICombine(protmat1, protmat2),
.getPPITensor(protmat1, protmat2,
row = protrow1,
col = protcol1),
.getPPIEntry(protmat1, protmat2))
} else {
stop('Interaction type must be in "tensorprod", "combine" and "entrywise"')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getDDI
#'
#' @param DNAmat1 The first DNA descriptor matrix,
#' must have the same ncol with \code{DNAmat2}.
#' @param DNAmat2 The second DNA descriptor matrix,
#' must have the same ncol with \code{DNAmat1}.
#'
#' @export getDDI
#'
getDDI = function (DNAmat1, DNAmat2, type = c('combine', 'tensorprod',
'entrywise')) {
if (!is.matrix(DNAmat1)) DNAmat1 = as.matrix(DNAmat1)
if (!is.matrix(DNAmat2)) DNAmat2 = as.matrix(DNAmat2)
DNArow1 = nrow(DNAmat1)
DNArow2 = nrow(DNAmat2)
if (DNArow1 != DNArow2) stop('Matrix row count must match')
DNAcol1 = ncol(DNAmat1)
DNAcol2 = ncol(DNAmat2)
if (DNAcol1 != DNAcol2) stop('Matrix column count must match')
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getDDICombine(DNAmat1, DNAmat2)
} else if (all(type == 'tensorprod')) {
result = .getDDITensor(DNAmat1, DNAmat2,
row = DNArow1, col = DNAcol1)
} else if (all(type == 'entrywise')) {
result = .getDDIEntry(DNAmat1, DNAmat2)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getDDICombine(DNAmat1, DNAmat2),
.getDDITensor(DNAmat1, DNAmat2,
row = DNArow1, col = DNAcol1))
} else if (length(setdiff(type, c('tensorprod', 'entrywise'))) == 0L) {
result = cbind(.getDDITensor(DNAmat1, DNAmat2,
row = DNArow1,
col = DNAcol1),
.getDDIEntry(DNAmat1, DNAmat2))
} else if (length(setdiff(type, c('combine', 'entrywise'))) == 0L) {
result = cbind(.getDDICombine(DNAmat1, DNAmat2),
.getDDIEntry(DNAmat1, DNAmat2))
} else if (length(setdiff(type, c('tensorprod',
'combine',
'entrywise'))) == 0L) {
result = cbind(.getDDICombine(DNAmat1, DNAmat2),
.getDDITensor(DNAmat1, DNAmat2,
row = DNArow1,
col = DNAcol1),
.getDDIEntry(DNAmat1, DNAmat2))
} else {
stop('Interaction type must be in "tensorprod", "combine" and "entrywise"')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getDPI
#'
#' @param DNAmat The DNA descriptor matrix.
#'
#' @export getDPI
#'
getDPI = function (DNAmat, protmat, type = c('combine', 'tensorprod')) {
if (!is.matrix(DNAmat)) DNAmat = as.matrix(DNAmat)
if (!is.matrix(protmat)) protmat = as.matrix(protmat)
DNArow = nrow(DNAmat)
protrow = nrow(protmat)
if (DNArow != protrow) stop('Matrix row count must match')
DNAcol = ncol(DNAmat)
protcol = ncol(protmat)
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getDPICombine(DNAmat, protmat)
} else if (all(type == 'tensorprod')) {
result = .getDPITensor(DNAmat, protmat, row = DNArow,
dcol = DNAcol, pcol = protcol)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getDPICombine(DNAmat, protmat),
.getDPITensor(DNAmat, protmat, row = DNArow,
dcol = DNAcol, pcol = protcol))
} else {
stop('Interaction type must be in "tensorprod" and "combine" or both')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getCCI
#'
#' @param drugmat1 The first compound descriptor matrix,
#' must have the same ncol with \code{drugmat2}.
#' @param drugmat2 The second compound descriptor matrix,
#' must have the same ncol with \code{drugmat1}.
#'
#' @export getCCI
#'
getCCI = function (drugmat1, drugmat2, type = c('combine', 'tensorprod',
'entrywise')) {
if (!is.matrix(drugmat1)) drugmat1 = as.matrix(drugmat1)
if (!is.matrix(drugmat2)) drugmat2 = as.matrix(drugmat2)
drugrow1 = nrow(drugmat1)
drugrow2 = nrow(drugmat2)
if (drugrow1 != drugrow2) stop('Matrix row count must match')
drugcol1 = ncol(drugmat1)
drugcol2 = ncol(drugmat2)
if (drugcol1 != drugcol2) stop('Matrix column count must match')
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getCCICombine(drugmat1, drugmat2)
} else if (all(type == 'tensorprod')) {
result = .getCCITensor(drugmat1, drugmat2,
row = drugrow1, col = drugcol1)
} else if (all(type == 'entrywise')) {
result = .getCCIEntry(drugmat1, drugmat2)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getCCICombine(drugmat1, drugmat2),
.getCCITensor(drugmat1, drugmat2,
row = drugrow1, col = drugcol1))
} else if (length(setdiff(type, c('tensorprod', 'entrywise'))) == 0L) {
result = cbind(.getCCITensor(drugmat1, drugmat2,
row = drugrow1,
col = drugcol1),
.getCCIEntry(drugmat1, drugmat2))
} else if (length(setdiff(type, c('combine', 'entrywise'))) == 0L) {
result = cbind(.getCCICombine(drugmat1, drugmat2),
.getCCIEntry(drugmat1, drugmat2))
} else if (length(setdiff(type, c('tensorprod',
'combine',
'entrywise'))) == 0L) {
result = cbind(.getCCICombine(drugmat1, drugmat2),
.getCCITensor(drugmat1, drugmat2,
row = drugrow1,
col = drugcol1),
.getCCIEntry(drugmat1, drugmat2))
} else {
stop('Interaction type must be in "tensorprod", "combine" and "entrywise"')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getCDI
#'
#' @export getCDI
#'
getCDI = function (drugmat, DNAmat, type = c('combine', 'tensorprod')) {
if (!is.matrix(drugmat)) drugmat = as.matrix(drugmat)
if (!is.matrix(DNAmat)) DNAmat = as.matrix(DNAmat)
drugrow = nrow(drugmat)
DNArow = nrow(DNAmat)
if (drugrow != DNArow) stop('Matrix row count must match')
drugcol = ncol(drugmat)
DNAcol = ncol(DNAmat)
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getCDICombine(drugmat, DNAmat)
} else if (all(type == 'tensorprod')) {
result = .getCDITensor(drugmat, DNAmat, row = drugrow,
dcol = drugcol, pcol = DNAcol)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getCDICombine(drugmat, DNAmat),
.getCDITensor(drugmat, DNAmat, row = drugrow,
dcol = drugcol, pcol = DNAcol))
} else {
stop('Interaction type must be in "tensorprod" and "combine" or both')
}
return(result)
}
wind22zhu/BioMedR documentation built on Oct. 21, 2019, 12:51 p.m.
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.inner = function (a, b, f, ...) {
# For computing column-by-column (pseudo)-tensor product type interactions
f = match.fun(f)
apply(b, 2, function (x) apply(a, 1, function (y) f(x, y, ...)))
}
.getCPICombine = function (drugmat, protmat) {
return(cbind(drugmat, protmat))
}
.getCPITensor = function (drugmat, protmat, row, dcol, pcol) {
return(array(.inner(t(drugmat), protmat, '*'), c(row, dcol * pcol)))
}
.getPPICombine = function (protmat1, protmat2) {
return(cbind(protmat1, protmat2))
}
.getPPITensor = function (protmat1, protmat2, row, col) {
return(array(.inner(t(protmat1), protmat2, '*'), c(row, col^2)))
}
.getPPIEntry = function (protmat1, protmat2) {
return(cbind((protmat1 * protmat2), (protmat1 + protmat2)))
}
.getDDICombine = function (DNAmat1, DNAmat2) {
return(cbind(DNAmat1, DNAmat2))
}
.getDDITensor = function (DNAmat1, DNAmat2, row, col) {
return(array(.inner(t(DNAmat1), DNAmat2, '*'), c(row, col^2)))
}
.getDDIEntry = function (DNAmat1, DNAmat2) {
return(cbind((DNAmat1 * DNAmat2), (DNAmat1 + DNAmat2)))
}
.getDPIinner = function (a, b, f, ...) {
# For computing column-by-column (pseudo)-tensor product type interactions
f = match.fun(f)
apply(b, 2, function (x) apply(a, 1, function (y) f(x, y, ...)))
}
.getDPICombine = function (DNAmat, protmat) {
return(cbind(DNAmat, protmat))
}
.getDPITensor = function (DNAmat, protmat, row, dcol, pcol) {
return(array(.getDPIinner(t(DNAmat), protmat, '*'), c(row, dcol * pcol)))
}
.getCCICombine = function (drugmat1, drugmat2) {
return(cbind(drugmat1, drugmat2))
}
.getCCITensor = function (drugmat1, drugmat2, row, col) {
return(array(.inner(t(drugmat1), drugmat2, '*'), c(row, col^2)))
}
.getCCIEntry = function (drugmat1, drugmat2) {
return(cbind((drugmat1 * drugmat2), (drugmat1 + drugmat2)))
}
.getCDIinner = function (a, b, f, ...) {
# For computing column-by-column (pseudo)-tensor product type interactions
f = match.fun(f)
apply(b, 2, function (x) apply(a, 1, function (y) f(x, y, ...)))
}
.getCDICombine = function (drugmat, DNAmat) {
return(cbind(drugmat, DNAmat))
}
.getCDITensor = function (drugmat, DNAmat, row, dcol, pcol) {
return(array(.getCDIinner(t(drugmat), DNAmat, '*'), c(row, dcol * pcol)))
}
#' @title Generating Interaction Descriptors
#'
#' @description Generating Interaction Descriptors
#'
#' @details This function calculates the interaction descriptors
#' by three types of interaction:
#' \itemize{
#' \item \code{combine} - combine the two descriptor matrix,
#' result has \code{(p1 + p2)} columns
#' \item \code{tensorprod} - calculate column-by-column
#' (pseudo)-tensor product type interactions, result has
#' \code{(p1 * p2)} columns
#' \item \code{entrywise} - calculate entrywise product and
#' entrywise sum of the two matrices, then combine them,
#' result has \code{(p + p)} columns
#' }
#'
#' @param drugmat The compound descriptor matrix.
#' @param protmat The protein descriptor matrix.
#' @param type The interaction type, one or more of
#' \code{"combine"}, \code{"tensorprod"}, and \code{"entrywise"}.
#'
#' @return A matrix containing the interaction descriptors
#'
#' @keywords getCPI getCDI getDPI getPPI getDDI getCCI interaction
#'
#' @aliases getCPI
#'
#' @author Min-feng Zhu <\email{wind2zhu@@163.com}>,
#' Nan Xiao <\url{http://r2s.name}>
#'
#' @export getCPI
#'
#' @examples
#' x = matrix(1:10, ncol = 2)
#' y = matrix(1:15, ncol = 3)
#' # getCPI
#' getCPI(x, y, 'combine')
#' # getCDI
#' getCDI(x, y, 'tensorprod')
#' # getDPI
#' getDPI(x, y, type = c('combine', 'tensorprod'))
#' getDPI(x, y, type = c('tensorprod', 'combine'))
#'
getCPI = function (drugmat, protmat, type = c('combine', 'tensorprod')) {
if (!is.matrix(drugmat)) drugmat = as.matrix(drugmat)
if (!is.matrix(protmat)) protmat = as.matrix(protmat)
drugrow = nrow(drugmat)
protrow = nrow(protmat)
if (drugrow != protrow) stop('Matrix row count must match')
drugcol = ncol(drugmat)
protcol = ncol(protmat)
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getCPICombine(drugmat, protmat)
} else if (all(type == 'tensorprod')) {
result = .getCPITensor(drugmat, protmat, row = drugrow,
dcol = drugcol, pcol = protcol)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getCPICombine(drugmat, protmat),
.getCPITensor(drugmat, protmat, row = drugrow,
dcol = drugcol, pcol = protcol))
} else {
stop('Interaction type must be in "tensorprod" and "combine" or both')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getPPI
#'
#' @param protmat1 The first protein descriptor matrix,
#' must have the same ncol with \code{protmat2}.
#' @param protmat2 The second protein descriptor matrix,
#' must have the same ncol with \code{protmat1}.
#'
#' @export getPPI
#'
#' @examples
#' x = matrix(1:10, ncol = 2)
#' y = matrix(5:14, ncol = 2)
#'
#' # getPPI
#' getPPI(x, y, type = 'combine')
#' getPPI(x, y, type = 'tensorprod')
#' # getDDI
#' getDDI(x, y, type = 'entrywise')
#' getDDI(x, y, type = c('combine', 'tensorprod'))
#' # getCCI
#' getCCI(x, y, type = c('combine', 'entrywise'))
#' getCCI(x, y, type = c('entrywise', 'tensorprod'))
#' getCCI(x, y, type = c('combine', 'entrywise', 'tensorprod'))
getPPI = function (protmat1, protmat2, type = c('combine', 'tensorprod',
'entrywise')) {
if (!is.matrix(protmat1)) protmat1 = as.matrix(protmat1)
if (!is.matrix(protmat2)) protmat2 = as.matrix(protmat2)
protrow1 = nrow(protmat1)
protrow2 = nrow(protmat2)
if (protrow1 != protrow2) stop('Matrix row count must match')
protcol1 = ncol(protmat1)
protcol2 = ncol(protmat2)
if (protcol1 != protcol2) stop('Matrix column count must match')
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getPPICombine(protmat1, protmat2)
} else if (all(type == 'tensorprod')) {
result = .getPPITensor(protmat1, protmat2,
row = protrow1, col = protcol1)
} else if (all(type == 'entrywise')) {
result = .getPPIEntry(protmat1, protmat2)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getPPICombine(protmat1, protmat2),
.getPPITensor(protmat1, protmat2,
row = protrow1, col = protcol1))
} else if (length(setdiff(type, c('tensorprod', 'entrywise'))) == 0L) {
result = cbind(.getPPITensor(protmat1, protmat2,
row = protrow1,
col = protcol1),
.getPPIEntry(protmat1, protmat2))
} else if (length(setdiff(type, c('combine', 'entrywise'))) == 0L) {
result = cbind(.getPPICombine(protmat1, protmat2),
.getPPIEntry(protmat1, protmat2))
} else if (length(setdiff(type, c('tensorprod',
'combine',
'entrywise'))) == 0L) {
result = cbind(.getPPICombine(protmat1, protmat2),
.getPPITensor(protmat1, protmat2,
row = protrow1,
col = protcol1),
.getPPIEntry(protmat1, protmat2))
} else {
stop('Interaction type must be in "tensorprod", "combine" and "entrywise"')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getDDI
#'
#' @param DNAmat1 The first DNA descriptor matrix,
#' must have the same ncol with \code{DNAmat2}.
#' @param DNAmat2 The second DNA descriptor matrix,
#' must have the same ncol with \code{DNAmat1}.
#'
#' @export getDDI
#'
getDDI = function (DNAmat1, DNAmat2, type = c('combine', 'tensorprod',
'entrywise')) {
if (!is.matrix(DNAmat1)) DNAmat1 = as.matrix(DNAmat1)
if (!is.matrix(DNAmat2)) DNAmat2 = as.matrix(DNAmat2)
DNArow1 = nrow(DNAmat1)
DNArow2 = nrow(DNAmat2)
if (DNArow1 != DNArow2) stop('Matrix row count must match')
DNAcol1 = ncol(DNAmat1)
DNAcol2 = ncol(DNAmat2)
if (DNAcol1 != DNAcol2) stop('Matrix column count must match')
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getDDICombine(DNAmat1, DNAmat2)
} else if (all(type == 'tensorprod')) {
result = .getDDITensor(DNAmat1, DNAmat2,
row = DNArow1, col = DNAcol1)
} else if (all(type == 'entrywise')) {
result = .getDDIEntry(DNAmat1, DNAmat2)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getDDICombine(DNAmat1, DNAmat2),
.getDDITensor(DNAmat1, DNAmat2,
row = DNArow1, col = DNAcol1))
} else if (length(setdiff(type, c('tensorprod', 'entrywise'))) == 0L) {
result = cbind(.getDDITensor(DNAmat1, DNAmat2,
row = DNArow1,
col = DNAcol1),
.getDDIEntry(DNAmat1, DNAmat2))
} else if (length(setdiff(type, c('combine', 'entrywise'))) == 0L) {
result = cbind(.getDDICombine(DNAmat1, DNAmat2),
.getDDIEntry(DNAmat1, DNAmat2))
} else if (length(setdiff(type, c('tensorprod',
'combine',
'entrywise'))) == 0L) {
result = cbind(.getDDICombine(DNAmat1, DNAmat2),
.getDDITensor(DNAmat1, DNAmat2,
row = DNArow1,
col = DNAcol1),
.getDDIEntry(DNAmat1, DNAmat2))
} else {
stop('Interaction type must be in "tensorprod", "combine" and "entrywise"')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getDPI
#'
#' @param DNAmat The DNA descriptor matrix.
#'
#' @export getDPI
#'
getDPI = function (DNAmat, protmat, type = c('combine', 'tensorprod')) {
if (!is.matrix(DNAmat)) DNAmat = as.matrix(DNAmat)
if (!is.matrix(protmat)) protmat = as.matrix(protmat)
DNArow = nrow(DNAmat)
protrow = nrow(protmat)
if (DNArow != protrow) stop('Matrix row count must match')
DNAcol = ncol(DNAmat)
protcol = ncol(protmat)
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getDPICombine(DNAmat, protmat)
} else if (all(type == 'tensorprod')) {
result = .getDPITensor(DNAmat, protmat, row = DNArow,
dcol = DNAcol, pcol = protcol)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getDPICombine(DNAmat, protmat),
.getDPITensor(DNAmat, protmat, row = DNArow,
dcol = DNAcol, pcol = protcol))
} else {
stop('Interaction type must be in "tensorprod" and "combine" or both')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getCCI
#'
#' @param drugmat1 The first compound descriptor matrix,
#' must have the same ncol with \code{drugmat2}.
#' @param drugmat2 The second compound descriptor matrix,
#' must have the same ncol with \code{drugmat1}.
#'
#' @export getCCI
#'
getCCI = function (drugmat1, drugmat2, type = c('combine', 'tensorprod',
'entrywise')) {
if (!is.matrix(drugmat1)) drugmat1 = as.matrix(drugmat1)
if (!is.matrix(drugmat2)) drugmat2 = as.matrix(drugmat2)
drugrow1 = nrow(drugmat1)
drugrow2 = nrow(drugmat2)
if (drugrow1 != drugrow2) stop('Matrix row count must match')
drugcol1 = ncol(drugmat1)
drugcol2 = ncol(drugmat2)
if (drugcol1 != drugcol2) stop('Matrix column count must match')
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getCCICombine(drugmat1, drugmat2)
} else if (all(type == 'tensorprod')) {
result = .getCCITensor(drugmat1, drugmat2,
row = drugrow1, col = drugcol1)
} else if (all(type == 'entrywise')) {
result = .getCCIEntry(drugmat1, drugmat2)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getCCICombine(drugmat1, drugmat2),
.getCCITensor(drugmat1, drugmat2,
row = drugrow1, col = drugcol1))
} else if (length(setdiff(type, c('tensorprod', 'entrywise'))) == 0L) {
result = cbind(.getCCITensor(drugmat1, drugmat2,
row = drugrow1,
col = drugcol1),
.getCCIEntry(drugmat1, drugmat2))
} else if (length(setdiff(type, c('combine', 'entrywise'))) == 0L) {
result = cbind(.getCCICombine(drugmat1, drugmat2),
.getCCIEntry(drugmat1, drugmat2))
} else if (length(setdiff(type, c('tensorprod',
'combine',
'entrywise'))) == 0L) {
result = cbind(.getCCICombine(drugmat1, drugmat2),
.getCCITensor(drugmat1, drugmat2,
row = drugrow1,
col = drugcol1),
.getCCIEntry(drugmat1, drugmat2))
} else {
stop('Interaction type must be in "tensorprod", "combine" and "entrywise"')
}
return(result)
}
#' @rdname getCPI
#'
#' @aliases getCDI
#'
#' @export getCDI
#'
getCDI = function (drugmat, DNAmat, type = c('combine', 'tensorprod')) {
if (!is.matrix(drugmat)) drugmat = as.matrix(drugmat)
if (!is.matrix(DNAmat)) DNAmat = as.matrix(DNAmat)
drugrow = nrow(drugmat)
DNArow = nrow(DNAmat)
if (drugrow != DNArow) stop('Matrix row count must match')
drugcol = ncol(drugmat)
DNAcol = ncol(DNAmat)
if (missing(type)) stop('Must provide at least one interaction type')
if (all(type == 'combine')) {
result = .getCDICombine(drugmat, DNAmat)
} else if (all(type == 'tensorprod')) {
result = .getCDITensor(drugmat, DNAmat, row = drugrow,
dcol = drugcol, pcol = DNAcol)
} else if (length(setdiff(type, c('tensorprod', 'combine'))) == 0L) {
result = cbind(.getCDICombine(drugmat, DNAmat),
.getCDITensor(drugmat, DNAmat, row = drugrow,
dcol = drugcol, pcol = DNAcol))
} else {
stop('Interaction type must be in "tensorprod" and "combine" or both')
}
return(result)
}
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