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# libsoc - Library to handle standardised output files
# Copyright (C) 2015 Rikard Nordgren
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 3 of the License, or (at your option) any later version.
#
# his library 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
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with this library; if not, see <http://www.gnu.org/licenses/>.
.self <- NULL # Work around to silent notes for R CMD check
isnull <- function(pointer) {
stopifnot(is(pointer, "externalptr"))
.Call("isnull", pointer)
}
so_SO_read <- function(name) {
ext = .Call("r_so_SO_read", path.expand(name))
so = so_SO$new(cobj=ext)
return(so)
}
so_SO_write <- function(self, filename, pretty) {
.Call("r_so_SO_write", self, filename, pretty)
}
so_SO_all_population_estimates <- function(self) {
.Call("r_so_SO_all_population_estimates", self)
}
so_SO_all_standard_errors <- function(self) {
.Call("r_so_SO_all_standard_errors", self)
}
so_SO_is_structural_parameter <- function(self, name) {
.Call("r_so_SO_is_structural_parameter", self, name)
}
so_SO_is_ruv_parameter <- function(self, name) {
.Call("r_so_SO_is_ruv_parameter", self, name)
}
so_SO_random_variable_from_variability_parameter <- function(self, name) {
.Call("r_so_SO_random_variable_from_variability_parameter", self, name)
}
so_SO_is_correlation_parameter <- function(self, name) {
.Call("r_so_SO_is_correlation_parameter", self, name)
}
so_Table_ref <- function(self) {
.Call("r_so_Table_ref", self)
}
so_Table_free <- function(self) {
.Call("r_so_Table_free", self)
}
so_Matrix_free <- function(self) {
.Call("r_so_Matrix_free", self)
}
id_column <- function(table) {
colTypes <- attributes(table)$columnType
if (is.null(colTypes)) {
stop("Could not find columnTypes attribute. Did this data.frame not come from an SO object?")
}
for (i in 1:length(colTypes)) {
if ("id" %in% colTypes[[i]]) {
return(i)
}
}
stop("Could not find ID column")
}
id_column_name <- function(table) {
names(table)[id_column(table)]
}
idv_column <- function(table) {
colTypes <- attributes(table)$columnType
if (is.null(colTypes)) {
stop("Could not find columnTypes attribute. Did this data.frame not come from an SO object?")
}
for (i in 1:length(colTypes)) {
if ("idv" %in% colTypes[[i]]) {
return(i)
}
}
stop("Could not find idv column")
}
idv_column_name <- function(table) {
names(table)[idv_column(table)]
}
dv_column <- function(table) {
colTypes <- attributes(table)$columnType
if (is.null(colTypes)) {
stop("Could not find columnTypes attribute. Did this data.frame not come from an SO object?")
}
for (i in 1:length(colTypes)) {
if ("dv" %in% colTypes[[i]]) {
return(i)
}
}
stop("Could not find dv column")
}
dv_column_name <- function(table) {
names(table)[dv_column(table)]
}
variability_func <- function(symbol, self) {
struct <- so_SO_is_structural_parameter(self, symbol)
if (struct == 0) {
"structParameter"
} else if (struct == -1) {
"unknown"
} else if (so_SO_is_ruv_parameter(self, symbol) == 0) {
"residualError"
} else {
"parameterVariability"
}
}
random_variable_func <- function(symbol, self) {
so_SO_random_variable_from_variability_parameter(self, symbol)
}
correlation_func <- function(symbol, self) {
corr <- so_SO_is_correlation_parameter(self, symbol)
if (corr == 0) {
TRUE
} else if (corr == 1) {
FALSE
} else {
NA
}
}
so_SO$methods(list(
write = function(filename, pretty=TRUE) {
fail = so_SO_write(.self$.cobj, filename, ifelse(pretty, 1L, 0L))
if (fail != 0) {
stop(paste0("Could not write to file ", filename))
}
},
all_population_estimates = function() {
so_SO_all_population_estimates(.self$.cobj)
},
all_standard_errors = function() {
so_SO_all_standard_errors(.self$.cobj)
},
variability_type = function(symbols) {
sapply(symbols, variability_func, .self$.cobj)
},
correlation_parameters = function(symbols) {
sapply(symbols, correlation_func, .self$.cobj)
},
random_variable_from_variability_parameter = function(symbols) {
sapply(symbols, random_variable_func, .self$.cobj)
}
)
)
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