Find the index in the time series for each timestamp given in argument x.
Values of x that are before the earliest value or after the latest value in
y will be returned as NA. Alternatively, when x is a numeric vector of
index values, return the valid indices of the same vector, with the side
effect being the attribute "CFTime" associated with the result.
Arguments
- x
Vector of
character,POSIXtorDatevalues to find indices for, or a numeric vector.- y
A CFTime instance.
- method
Single value of "constant" or "linear". If
"constant"or when bounds are set on argumenty, return the index value for each match. If"linear", return the index value with any fractional value.- rightmost.closed
Whether or not to include the upper limit of argument
x. Default isFALSE. This argument is ignored when argumentxcontains index values.
Value
A numeric vector giving indices into y for the values of
x. If there is at least 1 valid index, then attribute "CFTime"
contains an instance of CFTime that describes the dimension of
filtering the dataset associated with y with the result of this
method, excluding any NA values.
Details
Timestamps can be provided as vectors of character strings, POSIXct or
Date.
Matching also returns index values for timestamps that fall between two
elements of the time series - this can lead to surprising results when time
series elements are positioned in the middle of an interval (as the CF
Metadata Conventions instruct us to "reasonably assume"): a time series of
days in January would be encoded in a netCDF file as
c("2024-01-01 12:00:00", "2024-01-02 12:00:00", "2024-01-03 12:00:00", ...)
so x <- c("2024-01-01", "2024-01-02", "2024-01-03") would result in
(NA, 1, 2) (or (NA, 1.5, 2.5) with method = "linear") because the date
values in x are at midnight. This situation is easily avoided by ensuring
that y has bounds set (use bounds(y) <- TRUE as a proximate solution if
bounds are not stored in the netCDF file). See the Examples.
If bounds are set, the indices are informed by those bounds. If the
bounds are not contiguous, returned values may be NA even if the
value of x falls between two valid timestamps.
Values of x that are not valid timestamps according to the calendar of y
will be returned as NA.
x can also be a numeric vector of index values, in which case the valid
values in x are returned. If negative values are passed, the positive
counterparts will be excluded and then the remainder returned. Positive and
negative values may not be mixed. Using a numeric vector has the side effect
that the result has the attribute "CFTime" describing the temporal dimension
of the slice. If index values outside of the range of y (1:length(y)) are
provided, an error will be thrown.
Examples
cf <- CFtime("days since 2020-01-01", "360_day", 1440:1799 + 0.5)
as_timestamp(cf)[1:3]
#> [1] "2024-01-01T12:00:00" "2024-01-02T12:00:00" "2024-01-03T12:00:00"
x <- c("2024-01-01", "2024-01-02", "2024-01-03")
indexOf(x, cf)
#> [1] NA 1 2
#> attr(,"CFTime")
#> CF calendar:
#> Origin : 2020-01-01T00:00:00
#> Units : days
#> Type : 360_day
#> Time series:
#> Elements: [2024-01-02 .. 2024-01-03] (average of 1.000000 days between 2 elements)
#> Bounds : not set
indexOf(x, cf, method = "linear")
#> [1] NA 1.5 2.5
#> attr(,"CFTime")
#> CF calendar:
#> Origin : 2020-01-01T00:00:00
#> Units : days
#> Type : 360_day
#> Time series:
#> Elements: [2024-01-02 .. 2024-01-03] (average of 1.000000 days between 2 elements)
#> Bounds : not set
bounds(cf) <- TRUE
indexOf(x, cf)
#> [1] 1 2 3
#> attr(,"CFTime")
#> CF calendar:
#> Origin : 2020-01-01T00:00:00
#> Units : days
#> Type : 360_day
#> Time series:
#> Elements: [2024-01-01 .. 2024-01-03] (average of 1.000000 days between 3 elements)
#> Bounds : set
# Non-existent calendar day in a `360_day` calendar
x <- c("2024-03-30", "2024-03-31", "2024-04-01")
indexOf(x, cf)
#> [1] 90 NA 91
#> attr(,"CFTime")
#> CF calendar:
#> Origin : 2020-01-01T00:00:00
#> Units : days
#> Type : 360_day
#> Time series:
#> Elements: [2024-03-30 .. 2024-04-01] (average of 1.000000 days between 2 elements)
#> Bounds : set
# Numeric x
indexOf(c(29, 30, 31), cf)
#> [1] 29 30 31
#> attr(,"CFTime")
#> CF calendar:
#> Origin : 2020-01-01T00:00:00
#> Units : days
#> Type : 360_day
#> Time series:
#> Elements: [2024-01-29T12:00:00 .. 2024-02-01T12:00:00] (average of 1.000000 days between 3 elements)
#> Bounds : set