A tessellation on a linear network L is a partition of the
network into non-overlapping pieces (tiles). Each tile consists of one
or more line segments which are subsets of the line segments making up
the network. A tile can consist of several disjoint pieces.
The data frame df should have columns named
seg, t0, t1 and tile.
Any additional columns will be ignored.
Each row of the data frame specifies one sub-segment of the network
and allocates it to a particular tile.
The seg column specifies which line segment of the network
contains the sub-segment. Values of seg are integer indices
for the segments in as.psp(L).
The t0 and t1 columns specify the start and end points
of the sub-segment. They should be numeric values between 0 and 1
inclusive, where the values 0 and 1 representing the network vertices
that are joined by this network segment.
The tile column specifies which tile of the tessellation
includes this sub-segment. It will be coerced to a factor and its
levels will be the names of the tiles.
If df is missing or NULL, the result is a tessellation
with only one tile, consisting of the entire network L.
Additional data called marks may be associated with
each tile of the tessellation. The argument marks should be
a vector with one entry for each tile (that is, one entry for each
level of df$tile) or a data frame with one row for each tile.
In general df and marks will have different numbers of rows.