# Rmetrics is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# Rmetrics is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library General Public License for more details.
#
# You should have received a copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA  02111-1307  USA

# Copyrights (C)
# for this R-port: 
#   1999 - 2007, Diethelm Wuertz, GPL
#   Diethelm Wuertz <wuertz@itp.phys.ethz.ch>
#   info@rmetrics.org
#   www.rmetrics.org
# for the code accessed (or partly included) from other R-ports:
#   see R's copyright and license files
# for the code accessed (or partly included) from contributed R-ports
# and other sources
#   see Rmetrics's copyright file


################################################################################
# OLD FUNCTIONS:            DESCRIPTION:
#  removeNA                  Remove NAs from a matrix object
#  substituteNA              Substitute NAs by zero, the column mean or median
#  interpNA                  Interpolate NAs using R's "approx" function
################################################################################


test.removeNA =
function()
{  
    # Create matrix object:
    set.seed(1985)
    M = 5
    N = 20
    x = matrix(round(rnorm(M*N), 3), ncol = M)
    colnames(x) = 1:M
    rownames(x) = 1:N
    nNA = 10
    nCol = trunc(runif(nNA, 1, M+1))
    nRow = trunc(runif(nNA, 1, N+1))
    for (i in 1:nNA) x[nRow[i], nCol[i]] = NA
    print(x)
    ans = removeNA(x)
    print(ans)
       
    # Create data.frame object:
    x.df = as.data.frame(x)
    class(x.df)
    ans = removeNA(x.df)
    print(ans)
    class(ans)
       
    # Create timeSeries object:
    tD = timeCalendar(m = 1, d = 1:N)
    x.tS = timeSeries(x, tD)
    print(x.tS)
    ans = removeNA(x.tS)
    print(ans)
    class(ans)
    
    # Return Value:
    return()    
}


# ------------------------------------------------------------------------------


test.substituteNA =
function()
{
    # Create matrix object:
    set.seed(1985)
    M = 5
    N = 20
    x = matrix(round(rnorm(M*N), 3), ncol = M)
    colnames(x) = 1:M
    rownames(x) = 1:N
    nNA = 10
    nCol = trunc(runif(nNA, 1, M+1))
    nRow = trunc(runif(nNA, 1, N+1))
    for (i in 1:nNA) x[nRow[i], nCol[i]] = NA
    print(x)
    
    # Substitute:
    ans = substituteNA(x)
    print(ans)
    ans = substituteNA(x, "mean")
    print(ans)
    ans = substituteNA(x, "median")
    print(ans)
       
    # Create data.frame object:
    x.df = as.data.frame(x)
    print(x.df)
    class(x.df)
    
    # Substitute:
    ans = substituteNA(x.df)
    print(ans)
    ans = substituteNA(x.df, "mean")
    print(ans)
    ans = substituteNA(x.df, "median")
    print(ans)
      
    # Create timeSeries object:
    tD = timeCalendar(m = 1, d = 1:N)
    x.tS = timeSeries(x, tD)
    print(x.tS)
    class(x.tS)
    
    # Substitute:
    ans = substituteNA(x.tS)
    print(ans)
    ans = substituteNA(x.tS, "mean")
    print(ans)
    ans = substituteNA(x.tS, "median")
    print(ans)
    
    # Return Value:
    return()      
}


# ------------------------------------------------------------------------------


test.interpNA =
function()
{
    # Interpolate Column-by-Column
    
    # Create matrix object:
    set.seed(1985)
    M = 5
    N = 20
    x = matrix(round(rnorm(M*N), 3), ncol = M)
    colnames(x) = 1:M
    rownames(x) = 1:N
    nNA = 10
    nCol = trunc(runif(nNA, 1, M+1))
    nRow = trunc(runif(nNA, 1, N+1))
    for (i in 1:nNA) x[nRow[i], nCol[i]] = NA
    print(x)
    
    # Interpolate:
    ans = interpNA(x, "linear")
    print(ans)
    ans = interpNA(x, "before")
    print(ans)
    ans = interpNA(x, "after")
    print(ans)
    
    # Return Value:
    return()    
}
 

################################################################################