Converts various kinds of data to a pixel image on a linear network.

`as.linim(X, …)` # S3 method for linim
as.linim(X, …)

# S3 method for default
as.linim(X, L, …,
eps = NULL, dimyx = NULL, xy = NULL,
delta=NULL)

# S3 method for linfun
as.linim(X, L=domain(X), …,
eps = NULL, dimyx = NULL, xy = NULL,
delta=NULL)

X

Data to be converted to a pixel image on a linear network.

L

Linear network (object of class `"linnet"`

).

…

Additional arguments passed to `X`

when `X`

is a function.

eps,dimyx,xy

Optional arguments passed to `as.mask`

to control
the pixel resolution.

delta

Optional. Numeric value giving the approximate distance (in coordinate units) between successive sample points along each segment of the network.

An image object on a linear network; an object of class `"linim"`

.

This function converts the data `X`

into a pixel image
on a linear network, an object of class `"linim"`

(see `linim`

).

The argument `X`

may be any of the following:

a function on a linear network, an object of class

`"linfun"`

.a pixel image on a linear network, an object of class

`"linim"`

.a pixel image, an object of class

`"im"`

.any type of data acceptable to

`as.im`

, such as a function, numeric value, or window.

First `X`

is converted to a pixel image object `Y`

(object of class `"im"`

).
The conversion is performed by `as.im`

.
The arguments `eps`

, `dimyx`

and `xy`

determine the pixel resolution.

Next `Y`

is converted to a pixel image on a linear network
using `linim`

. The argument `L`

determines the
linear network. If `L`

is missing or `NULL`

,
then `X`

should be an object of class `"linim"`

,
and `L`

defaults to the linear network on which `X`

is defined.

In addition to converting the
function to a pixel image, the algorithm also generates a fine grid of
sample points evenly spaced along each segment of the network
(with spacing at most `delta`

coordinate units). The function values
at these sample points are stored in the resulting object as a data frame
(the argument `df`

of `linim`

). This mechanism allows
greater accuracy for some calculations (such as
`integral.linim`

).

# NOT RUN { f <- function(x,y){ x + y } plot(as.linim(f, simplenet)) # }