A class `"ppp"`

to represent a two-dimensional point
pattern. Includes information about the window in which the
pattern was observed. Optionally includes marks.

The internal representation of marks is likely to change in the next release of this package.

This class represents a two-dimensional point pattern dataset. It specifies

the locations of the points

the window in which the pattern was observed

optionally, ``marks'' attached to each point (extra information such as a type label).

If `X`

is an object of type `ppp`

,
it contains the following elements:

`x` |
vector of \(x\) coordinates of data points |

`y` |
vector of \(y\) coordinates of data points |

`n` |
number of points |

`window` |
window of observation |

(an object of class `owin` ) |

Users are strongly advised not to manipulate these entries directly.

Objects of class `"ppp"`

may be created by the function
`ppp`

and converted from other types of data by the function
`as.ppp`

.
Note that you must always specify the window of observation;
there is intentionally no default action of ``guessing'' the window
dimensions from the data points alone.

Standard point pattern datasets provided with the package
include
`amacrine`

,
`betacells`

,
`bramblecanes`

,
`cells`

,
`demopat`

,
`ganglia`

,
`lansing`

,
`longleaf`

,
`nztrees`

,
`redwood`

,
`simdat`

and
`swedishpines`

.

Point patterns may be scanned from your own data files by
`scanpp`

or by using `read.table`

and
`as.ppp`

.

They may be manipulated by the functions
`[.ppp`

and
`superimpose`

.

Point pattern objects can be plotted just by typing `plot(X)`

which invokes the `plot`

method for point pattern objects,
`plot.ppp`

. See `plot.ppp`

for further information.

There are also methods for `summary`

and `print`

for point patterns. Use `summary(X)`

to see a useful description
of the data.

Patterns may be generated at random by
`runifpoint`

,
`rpoispp`

,
`rMaternI`

,
`rMaternII`

,
`rSSI`

,
`rNeymanScott`

,
`rMatClust`

,
and
`rThomas`

.

Most functions which are intended to operate on a window
(of class `owin`

)
will, if presented with a `ppp`

object instead,
automatically extract the window information from the point pattern.

# NOT RUN { x <- runif(100) y <- runif(100) X <- ppp(x, y, c(0,1),c(0,1)) X if(human <- interactive()) plot(X) mar <- sample(1:3, 100, replace=TRUE) mm <- ppp(x, y, c(0,1), c(0,1), marks=mar) if(human) plot(mm) # points with mark equal to 2 ss <- mm[ mm$marks == 2 , ] if(human) plot(ss) # left half of pattern 'mm' lu <- owin(c(0,0.5),c(0,1)) mmleft <- mm[ , lu] if(human) plot(mmleft) if(FALSE) { # input data from file qq <- scanpp("my.table", unit.square()) # interactively build a point pattern plot(unit.square()) X <- as.ppp(locator(10), unit.square()) plot(X) } # }