"ppp" representing 
  a point pattern dataset in the two-dimensional plane.
ppp(x,y, ..., window, marks, check=TRUE, drop=TRUE)"owin"owin to create the
    window, if window is missingFALSE unless you are sure that this
    check is unnecessary.
  "ppp" 
  describing a point pattern in the two-dimensional plane
  (see ppp.object).
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."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.
    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.
  
  The argument marks can be either
  
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.
    ith row of the data frame is interpreted
    as containing the mark values for the ith point in the point
    pattern. The columns of the data frame correspond to different
    mark variables (e.g. tree species and tree diameter).
    If drop=TRUE (the default), then 
  a data frame with only one column will be
  converted to a vector, and a data frame with no columns will be
  converted to NULL.
  
  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.
ppp.object,
  as.ppp,
  owin.object,
  owin,
  as.owin
  # 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"))
  ## Not run: 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)
  ## Not run: plot(X)
  # polygonal window
  X <- ppp(x, y, poly=list(x=c(0,10,0), y=c(0,0,10)))
  ## Not run: plot(X)
  # copy the window from another pattern
  data(cells)
  X <- ppp(x, y, window=Window(cells))
Run the code above in your browser using DataLab