Analysts often have their preferred spatial or temporal data
structure that they prefer to use for spatio-temporal analysis. For
example, the tbl_ts class from the tsibble package (Wang, Cook, and Hyndman 2020) is commonly used
in time series forecasting and the sf class (Pebesma 2018) is frequently used in spatial
data science. In cubble, analysts have the flexibility to combine these
two structures together by allowing the spatial component to be an sf
object and the temporal component to also be a tsibble object.
The key and index arguments in a cubble
object corresponds to the tsibble counterparts and they can be safely
omitted, if the temporal component is a tsibble object,
i.e. meteo_ts in the example below. The tsibble class from
the input will be carried over to the cubble object:
ts_nested <- make_cubble(
spatial = stations, temporal = meteo_ts, coords = c(long, lat))
(ts_long <- face_temporal(ts_nested))
#> # cubble: key: id [3], index: date, long form, [tsibble]
#> # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps
#> # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl]
#> id date prcp tmax tmin
#> <chr> <date> <dbl> <dbl> <dbl>
#> 1 ASN00086038 2020-01-01 0 26.8 11
#> 2 ASN00086038 2020-01-02 0 26.3 12.2
#> 3 ASN00086038 2020-01-03 0 34.5 12.7
#> 4 ASN00086038 2020-01-04 0 29.3 18.8
#> 5 ASN00086038 2020-01-05 18 16.1 12.5
#> 6 ASN00086038 2020-01-06 104 17.5 11.1
#> 7 ASN00086038 2020-01-07 14 20.7 12.1
#> 8 ASN00086038 2020-01-08 0 26.4 16.4
#> 9 ASN00086038 2020-01-09 0 33.1 17.4
#> 10 ASN00086038 2020-01-10 0 34 19.6
#> # ℹ 20 more rows
class(ts_long)
#> [1] "temporal_cubble_df" "cubble_df" "tbl_ts"
#> [4] "tbl_df" "tbl" "data.frame"The long cubble shows [tsibble] in the header to
indicate the object also being in a tbl_ts class. Methods
applies to the tbl_ts class can also be applied to the
temporal cubble objects, for example, checking whether the data contain
temporal gaps:
ts_long |> has_gaps()
#> # A tibble: 3 × 2
#> id .gaps
#> <chr> <lgl>
#> 1 ASN00086038 FALSE
#> 2 ASN00086077 FALSE
#> 3 ASN00086282 FALSEAn existing cubble object can promote its temporal component to a
tsibble object by applying make_temporal_tsibble(). The
promoted cubble object (ts_long2) will be the same as the
one created with a tsibble component initially
(ts_long):
ts_long2 <- make_cubble(
stations, meteo,
key = id, index = date, coords = c(long, lat)) |>
face_temporal() |>
make_temporal_tsibble()
identical(ts_long2, ts_long)
#> [1] TRUESimilarly, an sf object can be supplied as the spatial component to
create a cubble object, with the coords argument being
omitted. This opens up the possibility to represent fixed area with
polygons or multipolygons and the coords argument will be
calculated as the centroids of the (multi)polygons. The
[sf] print in the cubble header suggest an spatial
component being also a sf object:
(sf_nested <- make_cubble(
spatial = stations_sf, temporal = meteo,
key = id, index = date))
#> # cubble: key: id [3], index: date, nested form, [sf]
#> # spatial: [144.8321, -37.98, 145.0964, -37.6655], WGS 84
#> # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl]
#> id elev name wmo_id long lat geometry ts
#> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <POINT [°]> <list>
#> 1 ASN00086038 78.4 essen… 95866 145. -37.7 (144.9066 -37.7276) <tibble>
#> 2 ASN00086077 12.1 moora… 94870 145. -38.0 (145.0964 -37.98) <tibble>
#> 3 ASN00086282 113. melbo… 94866 145. -37.7 (144.8321 -37.6655) <tibble>
class(sf_nested)
#> [1] "spatial_cubble_df" "cubble_df" "sf"
#> [4] "tbl_df" "tbl" "data.frame"The following code shows how to perform coordinate transformation
with st_transform on a cubble object:
sf_nested |> sf::st_transform(crs = "EPSG:3857")
#> Warning: st_crs<- : replacing crs does not reproject data; use st_transform for
#> that
#> # cubble: key: id [3], index: date, nested form, [sf]
#> # spatial: [16122635.6225205, -4576600.8687746, 16152057.3639371,
#> # -4532279.35567565], WGS 84
#> # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl]
#> id elev name wmo_id long lat geometry ts
#> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <POINT [°]> <list>
#> 1 ASN00086038 78.4 essen… 95866 145. -37.7 (16130929 -4541016) <tibble>
#> 2 ASN00086077 12.1 moora… 94870 145. -38.0 (16152057 -4576601) <tibble>
#> 3 ASN00086282 113. melbo… 94866 145. -37.7 (16122636 -4532279) <tibble>The counterpart to promote the spatial component in an existing
cubble to be an sf object is make_spatial_sf():
(sf_nested2 <- make_cubble(
stations, meteo,
key = id, index = date, coords = c(long, lat)) |>
make_spatial_sf())
#> CRS missing: using OGC:CRS84 (WGS84) as default
#> # cubble: key: id [3], index: date, nested form, [sf]
#> # spatial: [144.8321, -37.98, 145.0964, -37.6655], WGS 84
#> # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl]
#> id long lat elev name wmo_id ts geometry
#> <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <POINT [°]>
#> 1 ASN00086038 145. -37.7 78.4 essen… 95866 <tibble> (144.9066 -37.7276)
#> 2 ASN00086077 145. -38.0 12.1 moora… 94870 <tibble> (145.0964 -37.98)
#> 3 ASN00086282 145. -37.7 113. melbo… 94866 <tibble> (144.8321 -37.6655)