Create a tessellation on a linear network.
Linear network (object of class
Data frame of local coordinates for the pieces that make up the tiles of the tessellation. See Details.
Vector or data frame of marks associated with the tiles of the tessellation.
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
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.
seg column specifies which line segment of the network
contains the sub-segment. Values of
seg are integer indices
for the segments in
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.
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.
df is missing or
NULL, the result is a tessellation
with only one tile, consisting of the entire network
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
df$tile) or a data frame with one row for each tile.
marks will have different numbers of rows.
An object of class
There are methods for
summary for this object.
and Greg McSwiggan.
linnet for linear networks.
plot.lintess for plotting.
divide.linnet to make a tessellation demarcated by
lineardirichlet to create the Dirichlet-Voronoi
tessellation from a point pattern on a linear network.
tile.lengths to compute the length of each tile
in the tessellation.
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