# with.fv

##### Evaluate an Expression in a Function Table

Evaluate an R expression in a
function value table (object of class `"fv"`

).

- Keywords
- manip, spatial, programming

##### Usage

```
# S3 method for fv
with(data, expr, ..., fun = NULL, enclos=NULL)
```

##### Arguments

- data
A function value table (object of class

`"fv"`

) in which the expression will be evaluated.- expr
The expression to be evaluated. An R language expression, which may involve the names of columns in

`data`

, the special abbreviations`.`

,`.x`

and`.y`

, and global constants or functions.- …
Ignored.

- fun
Logical value, specifying whether the result should be interpreted as another function (

`fun=TRUE`

) or simply returned as a numeric vector or array (`fun=FALSE`

). See Details.- enclos
An environment in which to search for variables that are not found in

`data`

. Defaults to`parent.frame()`

.

##### Details

This is a method for the generic command `with`

for an object of class `"fv"`

(function value table).

An object of class `"fv"`

is a convenient way of storing and
plotting several different estimates of the same function. It is
effectively a data frame with extra attributes.
See `fv.object`

for further explanation.

This command makes it possible to perform computations that involve different estimates of the same function. For example we use it to compute the arithmetic difference between two different edge-corrected estimates of the \(K\) function of a point pattern.

The argument `expr`

should be an R language expression. The expression
may involve

the name of any column in

`data`

, referring to one of the estimates of the function;the symbol

`.`

which stands for all the available estimates of the function;the symbol

`.y`

which stands for the recommended estimate of the function (in an`"fv"`

object, one of the estimates is always identified as the recommended estimate);the symbol

`.x`

which stands for the argument of the function;global constants or functions.

See the Examples. The expression should be capable of handling vectors and matrices.

The interpretation of the argument `fun`

is as follows:

If

`fun=FALSE`

, the result of evaluating the expression`expr`

will be returned as a numeric vector, matrix or data frame.If

`fun=TRUE`

, then the result of evaluating`expr`

will be interpreted as containing the values of a new function. The return value will be an object of class`"fv"`

. (This can only happen if the result has the right dimensions.)The default is

`fun=TRUE`

if the result of evaluating`expr`

has more than one column, and`fun=FALSE`

otherwise.

To perform calculations involving *several* objects of
class `"fv"`

, use `eval.fv`

.

##### Value

A function value table (object of class `"fv"`

)
or a numeric vector or data frame.

##### See Also

##### Examples

```
# NOT RUN {
# compute 4 estimates of the K function
X <- rpoispp(42)
K <- Kest(X)
plot(K)
# derive 4 estimates of the L function L(r) = sqrt(K(r)/pi)
L <- with(K, sqrt(./pi))
plot(L)
# compute 4 estimates of V(r) = L(r)/r
V <- with(L, ./.x)
plot(V)
# compute the maximum absolute difference between
# the isotropic and translation correction estimates of K(r)
D <- with(K, max(abs(iso - trans)))
# }
```

*Documentation reproduced from package spatstat, version 1.56-1, License: GPL (>= 2)*