spatstat (version 1.16-1)

ppp: Create a Point Pattern


Creates an object of class "ppp" representing a point pattern dataset in the two-dimensional plane.


ppp(x,y, ..., window, marks, check=TRUE)


Vector of $x$ coordinates of data points
Vector of $y$ coordinates of data points
window of observation, an object of class "owin"
arguments passed to owin to create the window, if window is missing
(optional) vector of mark values
Logical flag indicating whether to check that all the $(x,y)$ points lie inside the specified window. Do not set this to FALSE unless you are sure that this check is unnecessary.


  • An object of class "ppp" describing a point pattern in the two-dimensional plane (see ppp.object).

Rejected points

The points with coordinates x and y must lie inside the specified window, in order to define a valid object of class "ppp". Any points which do not lie inside the window will be removed from the point pattern, and a warning will be issued.

The rejected points are still accessible: they are stored as an attribute of the point pattern called "rejects" (which is an object of class "ppp" containing the rejected points in a large window). However, rejected points in a point pattern will be ignored by all other functions except plot.ppp.

To remove the rejected points altogether, use as.ppp. To include the rejected points, you will need to find a larger window that contains them, and use this larger window in a call to ppp.


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, yrangespecify a rectangle with these dimensions;
  • polyspecifies a polygonal boundary. If the boundary is a single polygon thenpolymust be a list with componentsx,ygiving the coordinates of the vertices. If the boundary consists of several disjoint polygons thenpolymust be a list of such lists so thatpoly[[i]]$xgives the$x$coordinates of the vertices of the$i$th boundary polygon.
  • maskspecifies a binary pixel image with entries that areTRUEif the corresponding pixel is inside the window.
  • windowis an object of class"owin"(seeowin.object) specifying the window.
The arguments 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 points with coordinates x and y must lie inside the specified window, in order to define a valid object of this class. Any points which do not lie inside the window will be removed from the point pattern, and a warning will be issued. See the section on Rejected Points.

The name of the unit of length for the x and y coordinates can be specified in the dataset, using the argument unitname, which is passed to owin. See the examples below, or the help file for owin. 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.

See Also

ppp.object, as.ppp, owin.object, owin, as.owin


Run this code
# 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)))

  # specify that the coordinates are given in metres
  X <- ppp(x, y, c(0,1), c(0,1), unitname=c("metre","metres"))


  # 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)

  # polygonal window
  X <- ppp(x, y, poly=list(x=c(0,10,0), y=c(0,0,10)))

  # copy the window from another pattern
  X <- ppp(x, y, window=cells$window)

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