lintess | R Documentation |
Create a tessellation on a linear network.
lintess(L, df, marks=NULL)
L |
Linear network (object of class |
df |
Data frame of local coordinates for the pieces that make up the tiles of the tessellation. See Details. |
marks |
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
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.
An object of class "lintess"
.
There are methods for print
, plot
and
summary
for this object.
and Greg McSwiggan.
linnet
for linear networks.
plot.lintess
for plotting.
divide.linnet
to make a tessellation demarcated by
given points.
chop.linnet
to make a tessellation demarcated by
infinite lines.
lineardirichlet
to create the Dirichlet-Voronoi
tessellation from a point pattern on a linear network.
as.linfun.lintess
, as.linnet.lintess
and
as.linim
to convert to other classes.
tile.lengths
to compute the length of each tile
in the tessellation.
The undocumented methods Window.lintess
and
as.owin.lintess
extract the spatial window.
# tessellation consisting of one tile for each existing segment
ns <- nsegments(simplenet)
df <- data.frame(seg=1:ns, t0=0, t1=1, tile=letters[1:ns])
u <- lintess(simplenet, df)
u
plot(u)
S <- as.psp(simplenet)
marks(u) <- data.frame(len=lengths_psp(S), ang=angles.psp(S))
u
plot(u)
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