Coerce to an Array
Arguments
- x
A
TimeSeries.- ...
Currently not used.
Value
An array.
Note
June 2026: aperm.default() now copy attributes, this change how apply() works on classed objects. The simplest "fix" is to add an aperm() S3 method for the class which drops attributes as aperm.default() previously did. Alternatively, one could also consider providing as.matrix()/as.array() methods which change to standard matrix/array.
Examples
## Create time-series of 20 observations
## Univariate
## Sampled every years starting from 1029 BCE
(X <- series(rnorm(30), time = 1029:1000, calendar = BCE()))
#> 30 x 1 x 1 time series observed between -1029 CE and -1000 CE
## Terminal and sampling times (returns rata die)
start(X)
#> [1] -376199
end(X)
#> [1] -365607
time(X)
#> Rata die: number of days since 01-01-01 (Gregorian)
#> [1] -376199 -375834 -375468 -375103 -374738 -374373 -374007 -373642 -373277
#> [10] -372912 -372546 -372181 -371816 -371451 -371085 -370720 -370355 -369990
#> [19] -369624 -369259 -368894 -368529 -368163 -367798 -367433 -367068 -366702
#> [28] -366337 -365972 -365607
span(X)
#> [1] 10592
## Multivariate
## Sampled every century starting from 1000 CE
(Y <- series(matrix(rnorm(90), 30, 3), time = 1000:1029, calendar = CE()))
#> 30 x 3 x 1 time series observed between 1000 CE and 1029 CE
## Terminal and sampling times (returns Gregorian Common Era years)
start(Y, calendar = CE())
#> [1] 1000
end(Y, calendar = CE())
#> [1] 1029
time(Y, calendar = CE())
#> [1] 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014
#> [16] 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029
span(Y, calendar = CE())
#> [1] 29
## Coerce to data frame
df <- as.data.frame(Y, calendar = BP())
head(df)
#> time series variable value
#> 1 950 S1 V1 0.9353632
#> 2 949 S1 V1 0.1764886
#> 3 948 S1 V1 0.2436855
#> 4 947 S1 V1 1.6235489
#> 5 946 S1 V1 0.1120381
#> 6 945 S1 V1 -0.1339970