Create parameters that consist of multiple numbers. If an attempt is made to create a parameter with conflicting settings then an error will be thrown.
proportion_parameter_array(name, value, label)
binary_parameter_array(name, value, label)
integer_parameter_array(
name,
value,
label,
lower_limit = rep(as.integer(-.Machine$integer.max), length(value)),
upper_limit = rep(as.integer(.Machine$integer.max), length(value))
)
numeric_parameter_array(
name,
value,
label,
lower_limit = rep(.Machine$double.xmin, length(value)),
upper_limit = rep(.Machine$double.xmax, length(value))
)
character
name of parameter.
vector
of values.
character
vector
of labels for each value.
vector
of values denoting the minimum acceptable
value for each element in value
. Defaults to the
smallest possible number on the system.
vector
of values denoting the maximum acceptable
value for each element in value
. Defaults to the
largest possible number on the system.
ArrayParameter object.
Below is a list of parameter generating functions and a brief description of each.
a parameter that consists of multiple
numeric
values that are between zero and one.
a parameter that consists of multiple
integer
values that are either zero or one.
a parameter that consists of multiple
integer
values.
a parameter that consists of multiple
numeric
values.
# proportion parameter array
p1 <- proportion_parameter_array('prop_array', c(0.1, 0.2, 0.3),
letters[1:3])
print(p1) # print it
#> prop_array (min: 0.1, max: 0.3)
p1$get() # get value
#> value
#> a 0.1
#> b 0.2
#> c 0.3
p1$id # get id
#> id: e48fad35-beb0-4218-893c-ce4876d7dba4
invalid <- data.frame(value = 1:3, row.names=letters[1:3]) # invalid values
p1$validate(invalid) # check invalid input is invalid
valid <- data.frame(value = c(0.4, 0.5, 0.6), row.names=letters[1:3]) # valid
p1$validate(valid) # check valid input is valid
p1$set(valid) # change value to valid input
print(p1)
#> prop_array (min: 0.4, max: 0.6)
# binary parameter array
p2 <- binary_parameter_array('bin_array', c(0L, 1L, 0L), letters[1:3])
print(p2) # print it
#> bin_array (min: 0, max: 1)
p2$get() # get value
#> value
#> a 0
#> b 1
#> c 0
p2$id # get id
#> id: 3bd34428-603f-4bf8-b0b0-a69e5455ec6a
invalid <- data.frame(value = 1:3, row.names=letters[1:3]) # invalid values
p2$validate(invalid) # check invalid input is invalid
valid <- data.frame(value = c(0L, 0L, 0L), row.names=letters[1:3]) # valid
p2$validate(valid) # check valid input is valid
p2$set(valid) # change value to valid input
print(p2)
#> bin_array (min: 0, max: 0)
# integer parameter array
p3 <- integer_parameter_array('int_array', c(1:3), letters[1:3])
print(p3) # print it
#> int_array (min: 1, max: 3)
p3$get() # get value
#> value
#> a 1
#> b 2
#> c 3
p3$id # get id
#> id: a0ea679a-c433-4030-83a4-7bb98fc1aa3c
invalid <- data.frame(value = rnorm(3), row.names=letters[1:3]) # invalid
p3$validate(invalid) # check invalid input is invalid
valid <- data.frame(value = 5:7, row.names=letters[1:3]) # valid
p3$validate(valid) # check valid input is valid
p3$set(valid) # change value to valid input
print(p3)
#> int_array (min: 5, max: 7)
# numeric parameter array
p4 <- numeric_parameter_array('dbl_array', c(0.1, 4, -5), letters[1:3])
print(p4) # print it
#> dbl_array (min: -5, max: 4)
p4$get() # get value
#> value
#> a 0.1
#> b 4.0
#> c -5.0
p4$id # get id
#> id: 418d0e76-eda5-4fab-ae42-a24e8f6abb87
invalid <- data.frame(value = c(NA, 1, 2), row.names=letters[1:3]) # invalid
p4$validate(invalid) # check invalid input is invalid
valid <- data.frame(value = c(1, 2, 3), row.names=letters[1:3]) # valid
p4$validate(valid) # check valid input is valid
p4$set(valid) # change value to valid input
print(p4)
#> dbl_array (min: 1, max: 3)
# numeric parameter array with lower bounds
p5 <- numeric_parameter_array('b_dbl_array', c(0.1, 4, -5), letters[1:3],
lower_limit=c(0, 1, 2))
print(p5) # print it
#> b_dbl_array (min: -5, max: 4)
p5$get() # get value
#> value
#> a 0.1
#> b 4.0
#> c -5.0
p5$id# get id
#> id: 37d2ca83-6605-4645-b81e-a41f3a6a3704
invalid <- data.frame(value = c(-1, 5, 5), row.names=letters[1:3]) # invalid
p5$validate(invalid) # check invalid input is invalid
valid <- data.frame(value = c(0, 1, 2), row.names=letters[1:3]) # valid
p5$validate(valid) # check valid input is valid
p5$set(valid) # change value to valid input
print(p5)
#> b_dbl_array (min: 0, max: 2)