CRAN Package Check Results for Package netcoh

Last updated on 2020-02-19 10:49:00 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2 39.19 61.05 100.24 ERROR
r-devel-linux-x86_64-debian-gcc 0.2 27.64 48.26 75.90 ERROR
r-devel-linux-x86_64-fedora-clang 0.2 128.13 ERROR
r-devel-linux-x86_64-fedora-gcc 0.2 124.44 ERROR
r-devel-windows-ix86+x86_64 0.2 57.00 98.00 155.00 OK
r-devel-windows-ix86+x86_64-gcc8 0.2 93.00 131.00 224.00 OK
r-patched-linux-x86_64 0.2 28.97 53.60 82.57 OK
r-patched-solaris-x86 0.2 152.00 OK
r-release-linux-x86_64 0.2 29.28 53.64 82.92 OK
r-release-windows-ix86+x86_64 0.2 66.00 96.00 162.00 OK
r-release-osx-x86_64 0.2 OK
r-oldrel-windows-ix86+x86_64 0.2 49.00 83.00 132.00 OK
r-oldrel-osx-x86_64 0.2 OK

Check Details

Version: 0.2
Check: examples
Result: ERROR
    Running examples in 'netcoh-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: predict.rncReg
    > ### Title: make predictions from a "rncReg" object.
    > ### Aliases: predict.rncReg
    > ### Keywords: models networks regression
    >
    > ### ** Examples
    >
    > set.seed(100)
    >
    > A <- matrix(0,200,200)
    > A[1:100,1:100] <- 1
    > A[101:200,101:200] <- 1
    > diag(A) <- 0
    >
    > alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
    > A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
    > alpha <- alpha[c(1:50,101:150,51:100,151:200)]
    >
    > beta <- rnorm(2)
    >
    > X <- matrix(rnorm(400),ncol=2)
    >
    > Y <- X
    >
    > A1 <- A[1:100,1:100]
    > X1 <- X[1:100,]
    > Y1 <- matrix(Y[1:100],ncol=1)
    >
    >
    > ## If one wants to regularize the Laplacian by
    > ## using gamma > 0 in rncreg, we suggest use
    > ## centered data.
    > #mean.x <- colMeans(X1)
    > #mean.y <- mean(Y1)
    > #Y1 <- Y1-mean.y
    > #X1 <- t(t(X1)-mean.x)
    > #Y <- Y-mean.y
    > #X <- t(t(X)-mean.x)
    >
    >
    >
    > m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    netcoh
     --- call from context ---
    rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
     --- call from argument ---
    if (class(X) != "matrix") stop("X should be a matrix!")
     --- R stacktrace ---
    where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
    
     --- value of length: 2 type: logical ---
    [1] FALSE TRUE
     --- function from context ---
    function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
     model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
     init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
    {
     if (length(model) > 1)
     model <- model[1]
     if (!any(c("linear", "logistic", "cox") == model))
     stop("model must be one of linear, logistic and cox.")
     n <- nrow(A)
     if (norm(t(A) - A, "F") > 0)
     warning("A is not symmetric....")
     if (!is.null(X)) {
     if (class(X) != "matrix")
     stop("X should be a matrix!")
     if (nrow(X) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(Y)) {
     if (class(Y) != "matrix")
     stop("Y should be a matrix!")
     if (nrow(Y) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(dt)) {
     if (nrow(dt) != n)
     stop("Dimensions do not match!")
     if (class(dt) != "data.frame")
     stop("dt must be a data.frame!")
     }
     if (model == "linear") {
     result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "logistic") {
     result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "cox") {
     result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
    }
    <bytecode: 0xc0800d0>
    <environment: namespace:netcoh>
     --- function search by body ---
    Function rncreg in namespace netcoh has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(X) != "matrix") stop("X should be a matrix!") :
     the condition has length > 1
    Calls: rncreg
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.2
Check: examples
Result: ERROR
    Running examples in ‘netcoh-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: predict.rncReg
    > ### Title: make predictions from a "rncReg" object.
    > ### Aliases: predict.rncReg
    > ### Keywords: models networks regression
    >
    > ### ** Examples
    >
    > set.seed(100)
    >
    > A <- matrix(0,200,200)
    > A[1:100,1:100] <- 1
    > A[101:200,101:200] <- 1
    > diag(A) <- 0
    >
    > alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
    > A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
    > alpha <- alpha[c(1:50,101:150,51:100,151:200)]
    >
    > beta <- rnorm(2)
    >
    > X <- matrix(rnorm(400),ncol=2)
    >
    > Y <- X
    >
    > A1 <- A[1:100,1:100]
    > X1 <- X[1:100,]
    > Y1 <- matrix(Y[1:100],ncol=1)
    >
    >
    > ## If one wants to regularize the Laplacian by
    > ## using gamma > 0 in rncreg, we suggest use
    > ## centered data.
    > #mean.x <- colMeans(X1)
    > #mean.y <- mean(Y1)
    > #Y1 <- Y1-mean.y
    > #X1 <- t(t(X1)-mean.x)
    > #Y <- Y-mean.y
    > #X <- t(t(X)-mean.x)
    >
    >
    >
    > m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    netcoh
     --- call from context ---
    rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
     --- call from argument ---
    if (class(X) != "matrix") stop("X should be a matrix!")
     --- R stacktrace ---
    where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
    
     --- value of length: 2 type: logical ---
    [1] FALSE TRUE
     --- function from context ---
    function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
     model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
     init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
    {
     if (length(model) > 1)
     model <- model[1]
     if (!any(c("linear", "logistic", "cox") == model))
     stop("model must be one of linear, logistic and cox.")
     n <- nrow(A)
     if (norm(t(A) - A, "F") > 0)
     warning("A is not symmetric....")
     if (!is.null(X)) {
     if (class(X) != "matrix")
     stop("X should be a matrix!")
     if (nrow(X) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(Y)) {
     if (class(Y) != "matrix")
     stop("Y should be a matrix!")
     if (nrow(Y) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(dt)) {
     if (nrow(dt) != n)
     stop("Dimensions do not match!")
     if (class(dt) != "data.frame")
     stop("dt must be a data.frame!")
     }
     if (model == "linear") {
     result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "logistic") {
     result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "cox") {
     result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
    }
    <bytecode: 0x55897df4d4a8>
    <environment: namespace:netcoh>
     --- function search by body ---
    Function rncreg in namespace netcoh has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(X) != "matrix") stop("X should be a matrix!") :
     the condition has length > 1
    Calls: rncreg
    Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.2
Check: compiled code
Result: NOTE
    File ‘netcoh/libs/netcoh.so’:
     Found no calls to: ‘R_registerRoutines’, ‘R_useDynamicSymbols’
    
    It is good practice to register native routines and to disable symbol
    search.
    
    See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.2
Check: examples
Result: ERROR
    Running examples in ‘netcoh-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: predict.rncReg
    > ### Title: make predictions from a "rncReg" object.
    > ### Aliases: predict.rncReg
    > ### Keywords: models networks regression
    >
    > ### ** Examples
    >
    > set.seed(100)
    >
    > A <- matrix(0,200,200)
    > A[1:100,1:100] <- 1
    > A[101:200,101:200] <- 1
    > diag(A) <- 0
    >
    > alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
    > A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
    > alpha <- alpha[c(1:50,101:150,51:100,151:200)]
    >
    > beta <- rnorm(2)
    >
    > X <- matrix(rnorm(400),ncol=2)
    >
    > Y <- X
    >
    > A1 <- A[1:100,1:100]
    > X1 <- X[1:100,]
    > Y1 <- matrix(Y[1:100],ncol=1)
    >
    >
    > ## If one wants to regularize the Laplacian by
    > ## using gamma > 0 in rncreg, we suggest use
    > ## centered data.
    > #mean.x <- colMeans(X1)
    > #mean.y <- mean(Y1)
    > #Y1 <- Y1-mean.y
    > #X1 <- t(t(X1)-mean.x)
    > #Y <- Y-mean.y
    > #X <- t(t(X)-mean.x)
    >
    >
    >
    > m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    netcoh
     --- call from context ---
    rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
     --- call from argument ---
    if (class(X) != "matrix") stop("X should be a matrix!")
     --- R stacktrace ---
    where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
    
     --- value of length: 2 type: logical ---
    [1] FALSE TRUE
     --- function from context ---
    function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
     model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
     init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
    {
     if (length(model) > 1)
     model <- model[1]
     if (!any(c("linear", "logistic", "cox") == model))
     stop("model must be one of linear, logistic and cox.")
     n <- nrow(A)
     if (norm(t(A) - A, "F") > 0)
     warning("A is not symmetric....")
     if (!is.null(X)) {
     if (class(X) != "matrix")
     stop("X should be a matrix!")
     if (nrow(X) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(Y)) {
     if (class(Y) != "matrix")
     stop("Y should be a matrix!")
     if (nrow(Y) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(dt)) {
     if (nrow(dt) != n)
     stop("Dimensions do not match!")
     if (class(dt) != "data.frame")
     stop("dt must be a data.frame!")
     }
     if (model == "linear") {
     result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "logistic") {
     result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "cox") {
     result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
    }
    <bytecode: 0xc604948>
    <environment: namespace:netcoh>
     --- function search by body ---
    Function rncreg in namespace netcoh has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(X) != "matrix") stop("X should be a matrix!") :
     the condition has length > 1
    Calls: rncreg
    Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.2
Check: examples
Result: ERROR
    Running examples in ‘netcoh-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: predict.rncReg
    > ### Title: make predictions from a "rncReg" object.
    > ### Aliases: predict.rncReg
    > ### Keywords: models networks regression
    >
    > ### ** Examples
    >
    > set.seed(100)
    >
    > A <- matrix(0,200,200)
    > A[1:100,1:100] <- 1
    > A[101:200,101:200] <- 1
    > diag(A) <- 0
    >
    > alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
    > A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
    > alpha <- alpha[c(1:50,101:150,51:100,151:200)]
    >
    > beta <- rnorm(2)
    >
    > X <- matrix(rnorm(400),ncol=2)
    >
    > Y <- X
    >
    > A1 <- A[1:100,1:100]
    > X1 <- X[1:100,]
    > Y1 <- matrix(Y[1:100],ncol=1)
    >
    >
    > ## If one wants to regularize the Laplacian by
    > ## using gamma > 0 in rncreg, we suggest use
    > ## centered data.
    > #mean.x <- colMeans(X1)
    > #mean.y <- mean(Y1)
    > #Y1 <- Y1-mean.y
    > #X1 <- t(t(X1)-mean.x)
    > #Y <- Y-mean.y
    > #X <- t(t(X)-mean.x)
    >
    >
    >
    > m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    netcoh
     --- call from context ---
    rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
     --- call from argument ---
    if (class(X) != "matrix") stop("X should be a matrix!")
     --- R stacktrace ---
    where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
     gamma = 0, cv = 5)
    
     --- value of length: 2 type: logical ---
    [1] FALSE TRUE
     --- function from context ---
    function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
     model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
     init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
    {
     if (length(model) > 1)
     model <- model[1]
     if (!any(c("linear", "logistic", "cox") == model))
     stop("model must be one of linear, logistic and cox.")
     n <- nrow(A)
     if (norm(t(A) - A, "F") > 0)
     warning("A is not symmetric....")
     if (!is.null(X)) {
     if (class(X) != "matrix")
     stop("X should be a matrix!")
     if (nrow(X) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(Y)) {
     if (class(Y) != "matrix")
     stop("Y should be a matrix!")
     if (nrow(Y) != n)
     stop("Dimensions do not match!")
     }
     if (!is.null(dt)) {
     if (nrow(dt) != n)
     stop("Dimensions do not match!")
     if (class(dt) != "data.frame")
     stop("dt must be a data.frame!")
     }
     if (model == "linear") {
     result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "logistic") {
     result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
     if (model == "cox") {
     result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
     gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
     tol = tol, init = init, verbose = verbose)
     result.obj <- list(alpha = result$alpha, beta = result$beta,
     A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
     cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
     model = model)
     class(result.obj) <- "rncReg"
     return(result.obj)
     }
    }
    <bytecode: 0xd7a8900>
    <environment: namespace:netcoh>
     --- function search by body ---
    Function rncreg in namespace netcoh has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(X) != "matrix") stop("X should be a matrix!") :
     the condition has length > 1
    Calls: rncreg
    Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc