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#######################################################################
# rEMM - Extensible Markov Model (EMM) for Data Stream Clustering in R
# Copyright (C) 2011 Michael Hahsler
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# any later version.
#
# This program 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 General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
setMethod("c", signature(x = "EMM"),
function(x,
...,
copy = TRUE,
recursive = FALSE) {
args <- list(...)
if (copy)
x <- copy(x)
if (recursive)
args <- unlist(args)
for (y in args) {
if (!is(y, "EMM"))
stop("can combine EMM only")
## combine tracds
nx <- smc_size(x@tracds_d$mm)
ny <- smc_size(y@tracds_d$mm)
n <- nx + ny
new_labels <- as.character(1:n)
#new_labels <- c(clusters(x), paste("A", clusters(y)))
x@tracds_d$mm <- new(
"SimpleMC",
unused = rep(as.integer(NA), n),
top = 0L,
counts = structure(rbind(
cbind(
smc_countMatrix(x@tracds_d$mm),
matrix(0, ncol = ny, nrow = nx)
),
cbind(
matrix(0, ncol = nx, nrow = ny),
smc_countMatrix(y@tracds_d$mm)
)
),
dimnames = list(new_labels, new_labels)),
initial_counts = structure(c(
smc_initialCounts(x@tracds_d$mm),
smc_initialCounts(y@tracds_d$mm)
),
names = new_labels)
)
x@tracds_d$current_state <- NA
## combine tNN
x@tnn_d$centers <- structure(rbind(x@tnn_d$centers, y@tnn_d$centers),
dimnames = list(new_labels, colnames(x@tnn_d$centers)))
x@tnn_d$counts <- structure(c(x@tnn_d$counts, y@tnn_d$counts),
names = new_labels)
x@tnn_d$var_thresholds <- structure(c(x@tnn_d$var_thresholds,
y@tnn_d$var_thresholds),
names = new_labels)
x@tnn_d$last <- NA
}
invisible(x)
})
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