R/inactivation.R
In albgarre/biorisk: What the Package Does (One Line, Title Case)
#' R6 class describing log-linear inactivation parameterized as k
#'
#'
#' @export
#'
LogLinInactivation_k <- R6::R6Class(
classname = "LogLinInactivation_k",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "k", "logN0"),
input_types = list(t = "continuous",
k = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
k <- self$depends_on$k$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - k*t/log(10)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - k*t
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - k*t
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing log-linear inactivation
#'
#' @details
#' A risk element describing log-linear inactivation. It has 3 inputs: logN0, t
#' and D.
#'
#' @export
#'
LogLinInactivation <- R6::R6Class(
classname = "LogLinInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "D", "logN0"),
input_types = list(t = "continuous",
D = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - t/D
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - t/D
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - t/D
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing a Weibull primary inactivation
#'
#' @details
#' A risk element describing Weibullian inactivation. It has 4 inputs: logN0, t
#' delta, beta.
#'
#' @export
#'
WeibullInactivation <- R6::R6Class(
classname = "WeibullInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "delta", "beta", "logN0"),
input_types = list(t = "continuous",
delta = "continuous",
beta = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
delta <- self$depends_on$delta$point_estimate()
beta <- self$depends_on$beta$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - (t/delta)^beta
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - (t/delta)^beta
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - (t/delta)^beta
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing a Weibull inactivation model
#'
#' @details
#' A risk element describing Weibullian inactivation using the parameterization by
#' Peleg. It has 4 inputs: logN0, t, b and n.
#'
#' @export
#'
PelegInactivation <- R6::R6Class(
classname = "PelegInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "b", "n", "logN0"),
input_types = list(t = "continuous",
b = "continuous",
n = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
b <- self$depends_on$b$point_estimate()
n <- self$depends_on$n$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - b*t^n
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - b*t^n
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - b*t^n
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Tri-linear inactivation
#'
#' @details
#' A risk element describing Tri-linear inactivation. It has 5 inputs: logN0, t, D, SL and Nres.
#'
#' @export
#'
TrilinearInactivation <- R6::R6Class(
classname = "TrilinearInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "SL", "logNres"),
input_types = list(t = "continuous",
D = "continuous",
SL = "continuous",
logNres = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- self$depends_on$SL$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logNres <- self$depends_on$logNres$point_estimate()
logN0 - b*t^n
logN <- logN0 - (t-SL)/D
logN <- ifelse(t < SL, logN0, logN)
logN <- ifelse(logN < logNres, logNres, logN)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - (t-SL)/D
) %>%
dplyr::mutate(
logN = ifelse(t < SL, logN0, logN),
logN = ifelse(logN < logNres, logNres, logN)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - (t-SL)/D
) %>%
dplyr::mutate(
logN = ifelse(t < SL, logN0, logN),
logN = ifelse(logN < logNres, logNres, logN)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Geeraerd inactivation model
#'
#' @details
#' A risk element describing the Geeraerd inactivation model. It has 5 inputs: logN0, t, D, SL and Nres.
#'
#' @export
#'
GeeraerdInactivation <- R6::R6Class(
classname = "GeeraerdInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "SL", "logNres"),
input_types = list(t = "continuous",
D = "continuous",
SL = "continuous",
logNres = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- self$depends_on$SL$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logNres <- self$depends_on$logNres$point_estimate()
k <- log(10)/D
logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Geeraerd inactivation model without shoulder
#'
#' @details
#' A risk element describing Geeraerd inactivation model without shouler.
#' It has 4 inputs: logN0, t, D and Nres.
#'
#' @export
#'
GeeraerdInactivation_noSL <- R6::R6Class(
classname = "GeeraerdInactivation_noSL",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "logNres"),
input_types = list(t = "continuous",
D = "continuous",
logNres = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- 0
logN0 <- self$depends_on$logN0$point_estimate()
logNres <- self$depends_on$logNres$point_estimate()
k <- log(10)/D
logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1) )/(exp(k*t)) + 1)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1) )/(exp(k*t)) + 1)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Geeraerd inactivation model without shoulder
#'
#' @details
#' A risk element describing Geeraerd inactivation model without shouler.
#' It has 4 inputs: logN0, t, D and Nres.
#'
#' @export
#'
GeeraerdInactivation_noTail <- R6::R6Class(
classname = "GeeraerdInactivation_noTail",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "SL"),
input_types = list(t = "continuous",
D = "continuous",
SL = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- self$depends_on$SL$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
k <- log(10)/D
N <- 10^logN0 * exp(-k*t) * exp(k*SL) / ( 1 + ( exp(k*SL) - 1 )*exp(-k*t) )
log10(N)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
k = log(10)/D,
N = 10^logN0 * exp(-k*t) * exp(k*SL) / ( 1 + ( exp(k*SL) - 1 )*exp(-k*t) ),
logN = log10(N)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
k = log(10)/D,
N = 10^logN0 * exp(-k*t) * exp(k*SL) / ( 1 + ( exp(k*SL) - 1 )*exp(-k*t) ),
logN = log10(N)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
albgarre/biorisk documentation built on Feb. 23, 2025, 5:19 a.m.
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#' R6 class describing log-linear inactivation parameterized as k
#'
#'
#' @export
#'
LogLinInactivation_k <- R6::R6Class(
classname = "LogLinInactivation_k",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "k", "logN0"),
input_types = list(t = "continuous",
k = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
k <- self$depends_on$k$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - k*t/log(10)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - k*t
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - k*t
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing log-linear inactivation
#'
#' @details
#' A risk element describing log-linear inactivation. It has 3 inputs: logN0, t
#' and D.
#'
#' @export
#'
LogLinInactivation <- R6::R6Class(
classname = "LogLinInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "D", "logN0"),
input_types = list(t = "continuous",
D = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - t/D
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - t/D
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - t/D
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing a Weibull primary inactivation
#'
#' @details
#' A risk element describing Weibullian inactivation. It has 4 inputs: logN0, t
#' delta, beta.
#'
#' @export
#'
WeibullInactivation <- R6::R6Class(
classname = "WeibullInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "delta", "beta", "logN0"),
input_types = list(t = "continuous",
delta = "continuous",
beta = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
delta <- self$depends_on$delta$point_estimate()
beta <- self$depends_on$beta$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - (t/delta)^beta
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - (t/delta)^beta
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - (t/delta)^beta
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing a Weibull inactivation model
#'
#' @details
#' A risk element describing Weibullian inactivation using the parameterization by
#' Peleg. It has 4 inputs: logN0, t, b and n.
#'
#' @export
#'
PelegInactivation <- R6::R6Class(
classname = "PelegInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "b", "n", "logN0"),
input_types = list(t = "continuous",
b = "continuous",
n = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
b <- self$depends_on$b$point_estimate()
n <- self$depends_on$n$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logN0 - b*t^n
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - b*t^n
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - b*t^n
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Tri-linear inactivation
#'
#' @details
#' A risk element describing Tri-linear inactivation. It has 5 inputs: logN0, t, D, SL and Nres.
#'
#' @export
#'
TrilinearInactivation <- R6::R6Class(
classname = "TrilinearInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "SL", "logNres"),
input_types = list(t = "continuous",
D = "continuous",
SL = "continuous",
logNres = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- self$depends_on$SL$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logNres <- self$depends_on$logNres$point_estimate()
logN0 - b*t^n
logN <- logN0 - (t-SL)/D
logN <- ifelse(t < SL, logN0, logN)
logN <- ifelse(logN < logNres, logNres, logN)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
logN = logN0 - (t-SL)/D
) %>%
dplyr::mutate(
logN = ifelse(t < SL, logN0, logN),
logN = ifelse(logN < logNres, logNres, logN)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
logN = logN0 - (t-SL)/D
) %>%
dplyr::mutate(
logN = ifelse(t < SL, logN0, logN),
logN = ifelse(logN < logNres, logNres, logN)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Geeraerd inactivation model
#'
#' @details
#' A risk element describing the Geeraerd inactivation model. It has 5 inputs: logN0, t, D, SL and Nres.
#'
#' @export
#'
GeeraerdInactivation <- R6::R6Class(
classname = "GeeraerdInactivation",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "SL", "logNres"),
input_types = list(t = "continuous",
D = "continuous",
SL = "continuous",
logNres = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- self$depends_on$SL$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
logNres <- self$depends_on$logNres$point_estimate()
k <- log(10)/D
logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Geeraerd inactivation model without shoulder
#'
#' @details
#' A risk element describing Geeraerd inactivation model without shouler.
#' It has 4 inputs: logN0, t, D and Nres.
#'
#' @export
#'
GeeraerdInactivation_noSL <- R6::R6Class(
classname = "GeeraerdInactivation_noSL",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "logNres"),
input_types = list(t = "continuous",
D = "continuous",
logNres = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- 0
logN0 <- self$depends_on$logN0$point_estimate()
logNres <- self$depends_on$logNres$point_estimate()
k <- log(10)/D
logNres + log10(( (10^(logN0-logNres)-1)*exp(k*SL) )/(exp(k*t) + exp(k*SL) - 1) + 1)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1) )/(exp(k*t)) + 1)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
k = log(10)/D,
logN = logNres + log10(( (10^(logN0-logNres)-1) )/(exp(k*t)) + 1)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
#' R6 class describing Geeraerd inactivation model without shoulder
#'
#' @details
#' A risk element describing Geeraerd inactivation model without shouler.
#' It has 4 inputs: logN0, t, D and Nres.
#'
#' @export
#'
GeeraerdInactivation_noTail <- R6::R6Class(
classname = "GeeraerdInactivation_noTail",
inherit = ContinuousElement,
public = list(
initialize = function(name,
units = NA,
output_unit = NA) {
super$initialize(name,
input_names = c("t", "logN0", "D", "SL"),
input_types = list(t = "continuous",
D = "continuous",
SL = "continuous",
logN0 = "continuous"),
units = units,
element_type = "inactivation",
output_var = "logN",
output_unit = output_unit,
level = 0)
},
#' @description
#' Returns the expected value
#'
point_estimate = function() {
t <- self$depends_on$t$point_estimate()
D <- self$depends_on$D$point_estimate()
SL <- self$depends_on$SL$point_estimate()
logN0 <- self$depends_on$logN0$point_estimate()
k <- log(10)/D
N <- 10^logN0 * exp(-k*t) * exp(k*SL) / ( 1 + ( exp(k*SL) - 1 )*exp(-k*t) )
log10(N)
}
),
private = list(
update_output = function(niter) {
sims <- self$simulations %>%
dplyr::mutate(
k = log(10)/D,
N = 10^logN0 * exp(-k*t) * exp(k*SL) / ( 1 + ( exp(k*SL) - 1 )*exp(-k*t) ),
logN = log10(N)
)
self$simulations <- sims
},
update_output_level = function(niter0, iter1 = 1, level = 0) {
if (self$level > level) {
niter0 <- 1
}
sims <- self$simulations_multi[[iter1]] %>%
dplyr::mutate(
k = log(10)/D,
N = 10^logN0 * exp(-k*t) * exp(k*SL) / ( 1 + ( exp(k*SL) - 1 )*exp(-k*t) ),
logN = log10(N)
)
## Save it
self$simulations_multi[[iter1]] <- sims
## Return the output
invisible(sims[[self$output]])
}
)
)
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