momentum_spatial function

Spatial Representation of momentum() Data Frames

Given an sf data frame with geometry types POLYGON, MULTIPOLYGON, or POINT representing time series locations, this function transforms the output of momentum(), momentum_ls(), momentum_dtw() to an sf data frame.

If network = TRUE, the sf data frame is of type LINESTRING, with edges connecting time series locations. This output is helpful to build many-to-many dissimilarity maps (see examples).

If network = FALSE, the sf data frame contains the geometry in the input sf argument. This output helps build one-to-many dissimilarity maps.

momentum_spatial(df = NULL, sf = NULL, network = TRUE)

Arguments

• df: (required, data frame) Output of momentum(), momentum_ls(), or momentum_dtw(). Default: NULL
• sf: (required, sf data frame) Points or polygons representing the location of the time series in argument 'df'. It must have a column with all time series names in df$x and df$y. Default: NULL
• network: (optional, logical) If TRUE, the resulting sf data frame is of time LINESTRING and represent network edges. Default: TRUE

Returns

sf data frame (LINESTRING geometry)

Examples

tsl <- distantia::tsl_initialize(
  x = distantia::eemian_pollen,
  name_column = "name",
  time_column = "time"
) |>
#reduce size to speed-up example runtime
distantia::tsl_subset(
  names = 1:3
  )

df_momentum <- distantia::momentum(
  tsl = tsl
)

#network many to many
sf_momentum <- distantia::momentum_spatial(
  df = df_momentum,
  sf = distantia::eemian_coordinates,
  network = TRUE
)

#network map
# mapview::mapview(
#   sf_momentum,
#   layer.name = "Importance - Abies",
#   label = "edge_name",
#   zcol = "importance__Abies",
#   lwd = 3
# ) |>
#   suppressWarnings()

See Also

Other momentum_support: momentum_aggregate(), momentum_boxplot(), momentum_model_frame(), momentum_stats(), momentum_to_wide()