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check_show_dev.R
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la <- devtools::load_all
la()
# Check and show
# MPs ----
## Empty ----
MPs <- MPs()
MPs
Check(MPs)
## Minimum Complete ----
nMP <- 4
Code(MPs) <- paste('MP', 1:nMP)
Label(MPs) <- paste('MP', 1:nMP)
MPs
Check(MPs)
## Fully Complete ----
Description(MPs) <- paste('Description', 1:nMP)
Color(MPs) <- c('red', 'blue')
Preset(MPs) <- list(All=c(1:4),
`First Two`=1:2)
MPs
Check(MPs)
## Multi-language ----
Label(MPs) <- list(en=paste('EN Label', 1:nMP),
es=paste('ES Label', 1:nMP),
fr=paste('FR Label', 1:nMP))
Description(MPs) <- list(en=paste('EN Description', 1:nMP),
es=paste('ES Description', 1:nMP),
fr=paste('FR Description', 1:nMP))
MPs
Check(MPs)
## Incomplete ----
### Code missing
MPs <- MPs()
Label(MPs) <- c('one', 'two')
MPs
Check(MPs)
### Label missing
MPs <- MPs()
Code(MPs) <- c('one', 'two')
MPs
Check(MPs)
### Code and Label missing
MPs <- MPs()
Description(MPs) <- c('one', 'two')
MPs
Check(MPs)
## Errors ----
## Code and Label different lengths
MPs <- MPs()
Code(MPs) <- paste('MP', 1:4)
Label(MPs) <- paste('MP', 1:2)
## Multi-language different lengths
MPs <- MPs()
Code(MPs) <- paste('MP', 1:4)
Label(MPs) <- list(en=paste('MP', 1:2))
## Multi-language invalid lang codes
MPs <- MPs()
Label(MPs) <- list(en=paste('EN MP', 1:2),
tt=paste('TT MP', 1:2))
# OMs ----
## Empty ----
object <- OMs()
object
Check(object)
## Minimum Complete ----
object <- OMs()
Factors(object) <- data.frame(Factor=c(rep('M',3),
rep('h', 3),
rep('Set',6)),
Level=c(0.1, 0.2, 0.3,
0.69, 0.8, 0.88,
'Reference',
'R1',
'R2',
'R3a',
'R3b',
'R4'),
Description=c('Natural Mortality = 0.1',
'Natural Mortality = 0.2',
'Natural Mortality = 0.3',
'Steepness = 0.69',
'Steepness = 0.80',
'Steepness = 0.88',
'Reference OMs',
'Robustness 1: Assumed 1 percent annual increase catchability (q), that is not accounted for in the standardization of the indices of abundance (historical and projection)',
'Robustness 2: Same as R1, except only in the historical period',
'Robustness 3a: Cyclical pattern in recruitment deviations in projection period; a proxy for impact of climate change on stock productivity',
'Lower than expected recruitment deviations for first 15 years of projection period; a proxy for impact of climate change on stock productivity',
'Illegal, unreported, or unregulated catches')
)
Design(object) <- data.frame(M=c(rep(c(0.1,0.2,0.3), each=3), rep(0.2, 5)),
h=c(rep(c(0.69,0.8,0.88),3), rep(0.8,5)),
Set=c(rep('Reference', 9),
'R1', 'R2', 'R3a', 'R3b', 'R4'))
object
Check(object)
## Fully Complete ----
Preset(object) <- list('Reference'=list(1:3, 1:3, 1),
'R0'=list(2, 2, 1),
'R1'=list(2, 2, 2),
'R2'=list(2, 2, 3),
'R3a'=list(2, 2, 4),
'R3b'=list(2, 2, 5),
'R4'=list(2, 2, 6))
object
Check(object)
## Multi-language ----
object <- OMs()
Factors(object) <- list(en=data.frame(Factor=c(rep('M',3),
rep('h', 3),
rep('Set',6)),
Level=c(0.1, 0.2, 0.3,
0.69, 0.8, 0.88,
'Reference',
'R1',
'R2',
'R3a',
'R3b',
'R4'),
Description=c('Natural Mortality = 0.1',
'Natural Mortality = 0.2',
'Natural Mortality = 0.3',
'Steepness = 0.69',
'Steepness = 0.80',
'Steepness = 0.88',
'Reference OMs',
'Robustness 1: Assumed 1 percent annual increase catchability (q), that is not accounted for in the standardization of the indices of abundance (historical and projection)',
'Robustness 2: Same as R1, except only in the historical period',
'Robustness 3a: Cyclical pattern in recruitment deviations in projection period; a proxy for impact of climate change on stock productivity',
'Lower than expected recruitment deviations for first 15 years of projection period; a proxy for impact of climate change on stock productivity',
'Illegal, unreported, or unregulated catches')),
es=data.frame(Factor=c(rep('M',3),
rep('h', 3),
rep('Set',6)),
Level=c(0.1, 0.2, 0.3,
0.69, 0.8, 0.88,
'Reference',
'R1',
'R2',
'R3a',
'R3b',
'R4'),
Description=c('ES Natural Mortality = 0.1',
'ES Natural Mortality = 0.2',
'ES Natural Mortality = 0.3',
'ES Steepness = 0.69',
'ES Steepness = 0.80',
'ES Steepness = 0.88',
'ES Reference OMs',
'ES Robustness 1: Assumed 1 percent annual increase catchability (q), that is not accounted for in the standardization of the indices of abundance (historical and projection)',
'ES Robustness 2: Same as R1, except only in the historical period',
'ES Robustness 3a: Cyclical pattern in recruitment deviations in projection period; a proxy for impact of climate change on stock productivity',
'ES Lower than expected recruitment deviations for first 15 years of projection period; a proxy for impact of climate change on stock productivity',
'ES Illegal, unreported, or unregulated catches'))
)
object
Check(object)
## Incomplete ----
### No Factors
object <- OMs()
Design(object) <- data.frame(one=1, two=2)
object
Check(object)
### No Design
object <- OMs()
Factors(object) <- data.frame(one=1, two=2)
object
Check(object)
## Errors ----
# non matching Factors and Design
object <- OMs()
Factors(object) <- data.frame(Factor=c(rep('M',3),
rep('h', 3),
rep('Set',6)),
Level=c(0.1, 0.2, 0.3,
0.69, 0.8, 0.88,
'Reference',
'R1',
'R2',
'R3a',
'R3b',
'R4'),
Description=c('Natural Mortality = 0.1',
'Natural Mortality = 0.2',
'Natural Mortality = 0.3',
'Steepness = 0.69',
'Steepness = 0.80',
'Steepness = 0.88',
'Reference OMs',
'Robustness 1: Assumed 1 percent annual increase catchability (q), that is not accounted for in the standardization of the indices of abundance (historical and projection)',
'Robustness 2: Same as R1, except only in the historical period',
'Robustness 3a: Cyclical pattern in recruitment deviations in projection period; a proxy for impact of climate change on stock productivity',
'Lower than expected recruitment deviations for first 15 years of projection period; a proxy for impact of climate change on stock productivity',
'Illegal, unreported, or unregulated catches')
)
# error
Design(object) <- data.frame(M=1, h=2, Sett=3)
# error
Design(object) <- data.frame(M=1, h=2, Set=3)
# ok
Design(object) <- data.frame(M=1:3, h=1:3, Set=1:6)
# ok
Design(object) <- data.frame(M=c(0.1, 0.2, 0.3),
h=c(0.69, 0.8, 0.88),
Set=1:6)
# ok
Design(object) <- data.frame(M=c('0.1', '0.2', '0.3'),
h=c(0.69, 0.8, 0.88),
Set=1:6)
object
Check(object)
# Boxplot ----
## Empty ----
object <- Boxplot()
object
Check(object)
## Complete ----
nPI <- 4
Code(object) <- c('AAVY', 'LTY', 'STY', 'Something Else')
Label(object) <- paste('PI', 1:nPI)
Value(object) <- array(runif(100), dim=c(3,2,6,4))
object
Check(object)
## Errors
# error
object <- Boxplot()
Value(object) <- array(runif(100), dim=c(1,2))
# ok
object <- Boxplot()
Value(object) <- array(runif(100), dim=c(1,1,1,3))
# Kobe ----
## Empty ----
object <- Kobe()
object
Check(object)
## Minimum ----
nPI <- 4
Code(object) <- c('AAVY', 'LTY', 'STY', 'Something Else')
Label(object) <- paste('PI', 1:nPI)
Value(object) <- array(runif(100), dim=c(3,2,6,4, 51))
object
Check(object)
## Complete ----
Time(object) <- 1950:2000
Target(object) <- c(1,2,3, 4)
Limit(object) <- 3
object
Check(object)
# Quilt ----
## Empty ----
object <- Quilt()
object
Check(object)
## Minimum Complete ----
object <- Quilt()
nPI <- 4
Code(object) <- c('AAVY', 'LTY', 'STY', 'Something Else')
Label(object) <- paste('PI', 1:nPI)
Value(object) <- array(runif(100), dim=c(3,2,4))
object
Check(object)
# Spider ----
## Empty ----
object <- Spider()
object
Check(object)
nPI <- 4
Code(object) <- c('AAVY', 'LTY', 'STY', 'Something Else')
Label(object) <- paste('PI', 1:nPI)
Value(object) <- array(runif(100), dim=c(3,2,4))
object
Check(object)
# Timeseries ----
## Empty ----
object <- Timeseries()
object
Check(object)
## Minimum Complete ----
nPI <- 4
Code(object) <- c('AAVY', 'LTY', 'STY', 'Something Else')
Label(object) <- paste('PI', 1:nPI)
Value(object) <- array(runif(100), dim=c(3,2,6,4, 51))
Time(object) <- 1950:2000
TimeNow(object) <- 1995
object
Check(object)
# Tradeoff ----
## Empty ----
object <- Tradeoff()
object
Check(object)
## Minimum Complete ----
object <- Tradeoff()
nPI <- 4
Code(object) <- c('AAVY', 'LTY', 'STY', 'Something Else')
Label(object) <- paste('PI', 1:nPI)
Value(object) <- array(runif(100), dim=c(3,2,4))
object
Check(object)
# Slick ----
## Empty
object <- Slick()
object
Check(object)
## Meta text
Title(object) <- 'This is the Title'
Subtitle(object) <- 'This is the sub title'
Author(object) <- c('Author 1', 'Author 2')
Email(object) <- c('email 1 ')
Institution(object) <- c('one', 'two', 'three')
Introduction(object) <- '
This is the introduction.
This is a new paragraph.
This is some **bold** text.
'
# MPs
nMP <- 4
mps <- MPs()
Code(mps) <- paste('MP', 1:nMP)
Label(mps) <- paste('MP', 1:nMP)
Description(mps) <- paste('Description', 1:nMP)
Color(mps) <- c('red', 'blue', 'green', 'red')
Preset(mps) <- list(All=c(1:4),
`First Two`=1:2)
MPs(object) <- mps
object
# multi language tests
object <- Slick()
Check(object)
Introduction(object) <- list(en='
This is the introduction.
This is a new paragraph.
This i
',
es=' This is the spanish intro',
fr='this is the french intro'
)
object
Boxplot(object) <- Boxplot()