# ppp

##### Create a Point Pattern

Creates an object of class `"ppp"`

representing
a point pattern dataset in the two-dimensional plane.

- Keywords
- spatial

##### Usage

```
ppp(x,y, xrange, yrange, marks)
ppp(x,y, window, marks)
ppp(x,y, poly, marks)
ppp(x,y, mask, marks)
ppp(x,y, ..., marks)
```

##### Arguments

- x
- Vector of $x$ coordinates of data points
- y
- Vector of $y$ coordinates of data points
- xrange
- $x$ coordinate limits of enclosing box
- yrange
- $y$ coordinate limits of enclosing box
- marks
- (optional) vector of mark values
- poly
- vertices of polygonal boundary of window
- mask
- logical matrix giving binary image of window
- window
- window of observation,
an object of class
`"owin"`

- ...
- arguments passed to
`owin`

to create the window

##### Details

In the `spatstat`

library, a point pattern dataset is
described by an object of class `"ppp"`

. This function
creates such objects.

The vectors `x`

and `y`

must be numeric vectors of
equal length. They are interpreted as the cartesian coordinates
of the points in the pattern.

A point pattern dataset is assumed to have been observed within a specific
region of the plane called the observation window.
An object of class `"ppp"`

representing a point pattern
contains information specifying the observation window.
This window must always be specified when creating a point pattern dataset;
there is intentionally no default action of ``guessing'' the window
dimensions from the data points alone.

You can specify the observation window in several (mutually exclusive) ways:

`xrange, yrange`

specify a rectangle with these dimensions;`poly`

specifies a polygonal boundary. If the boundary is a single polygon then`poly`

must be a list with components`x,y`

giving the coordinates of the vertices. If the boundary consists of several disjoint polygons then`poly`

must be a list of such lists so that`poly[[i]]$x`

gives the$x$coordinates of the vertices of the$i$th boundary polygon.`mask`

specifies a binary pixel image with entries that are`TRUE`

if the corresponding pixel is inside the window.`window`

is an object of class`"owin"`

(see`owin.object`

) specifying the window.

`xrange, yrange`

or `poly`

or `mask`

are passed to the window creator function
`owin`

for interpretation. See
`owin`

for further details. The argument `window`

, if given, must be an object of class
`"owin"`

. It is a full description of the window geometry,
and could have been obtained from `owin`

or
`as.owin`

, or by just extracting the observation window
of another point pattern, or by manipulating such windows.
See `owin`

or the Examples below.

The optional argument `marks`

is given if the point pattern
is marked, i.e. if each data point carries additional information.
For example, points which are classified into two or more different
types, or colours, may be regarded as having a mark which identifies
which colour they are. Data recording the locations and heights of
trees in a forest can be regarded as a marked point pattern where the
mark is the tree height.

In the current implementation, `marks`

must be a vector, of
the same length as `x`

and `y`

, which is interpreted so
that `marks[i]`

is the mark attached to the point
`(x[i],y[i])`

. If the mark is a real number then `marks`

should be a numeric vector, while if the mark takes only a finite
number of possible values (e.g. colours or types) then
`marks`

should be a `factor`

.
See `ppp.object`

for a description of the
class `"ppp"`

.

Users would normally invoke `ppp`

to create a point pattern,
but the functions `as.ppp`

and
`scanpp`

may sometimes be convenient.

##### Value

- An object of class
`"ppp"`

describing a point pattern in the two-dimensional plane (see`ppp.object`

).

##### synopsis

ppp(x,y, ..., window, marks)

##### See Also

##### Examples

```
# some arbitrary coordinates in [0,1]
x <- runif(20)
y <- runif(20)
# the following are equivalent
X <- ppp(x, y, c(0,1), c(0,1))
X <- ppp(x, y)
X <- ppp(x, y, window=owin(c(0,1),c(0,1)))
plot(X)
# marks
m <- sample(1:2, 20, replace=TRUE)
m <- factor(m, levels=1:2)
X <- ppp(x, y, c(0,1), c(0,1), marks=m)
plot(X)
# polygonal window
X <- ppp(x, y, poly=list(x=c(0,10,0), y=c(0,0,10)))
plot(X)
# copy the window from another pattern
data(cells)
X <- ppp(x, y, window=cells$window)
```

*Documentation reproduced from package spatstat, version 1.5-9, License: GPL version 2 or newer*