fryplot(X, ..., width=NULL)
frypoints(X)"ppp") or something
acceptable to as.ppp.fryplot returns NULL.
frypoints returns a point pattern (object of class "ppp").fryplot generates a Fry plot (or Patterson plot);
frypoints returns the points of the Fry plot as a point pattern
dataset.Fry (1979) and Hanna and Fry (1979) introduced a manual graphical method for investigating features of a spatial point pattern of mineral deposits. A transparent sheet, marked with an origin or centre point, is placed over the point pattern. The transparent sheet is shifted so that the origin lies over one of the data points, and the positions of all the other data points are copied onto the transparent sheet. This procedure is repeated for each data point in turn. The resulting plot (the Fry plot) is a pattern of $n(n-1)$ points, where $n$ is the original number of data points. This procedure was previously proposed by Patterson (1934, 1935) for studying inter-atomic distances in crystals, and is also known as a Patterson plot.
The function fryplot generates the Fry/Patterson plot.
Standard graphical parameters
such as main, pch,
lwd, col, bg, cex can be used to control
the appearance of the plot.
To zoom in (to view only a subset of the Fry plot at higher
magnification), use the argument width to specify the width
of a rectangular field of view centred at the origin, or the standard
graphical arguments xlim and ylim to specify another
rectangular field of view. (The actual field of view may be slightly
larger, depending on the graphics device.)
The function frypoints returns the points of the Fry
plot as a point pattern object. There may be a large number of points
in this pattern, so this function should be used only if further
analysis of the Fry plot is required.
Fry plots are particularly useful for recognising anisotropy in regular point patterns. A void around the origin in the Fry plot suggests regularity (inhibition between points) and the shape of the void gives a clue to anisotropy in the pattern. Fry plots are also useful for detecting periodicity or rounding of the spatial coordinates.
In mathematical terms, the Fry plot of a point pattern X
is simply a plot of the vectors X[i] - X[j] connecting all
pairs of distinct points in X.
The Fry plot is related to the $K$ function (see
Kest) and the reduced second moment measure
(see Kmeasure). For example, the number
of points in the Fry plot lying within a circle of given radius
is an unnormalised and uncorrected version of the $K$ function.
The Fry plot has a similar appearance to the plot of the
reduced second moment measure Kmeasure when the
smoothing parameter sigma is very small.
The Fry plot does not adjust for the effect
of the size and shape of the sampling window.
The density of points in the Fry plot tapers off near the edges of the
plot. This is an edge effect, a consequence of the bounded sampling
window. In geological applications this is usually not
important, because interest is focused on the behaviour near the
origin where edge effects can be ignored.
To correct for the edge effect, use Kmeasure or
Kest or its relatives.
Hanna, S.S. and Fry, N. (1979) A comparison of methods of strain determination in rocks from southwest Dyfed (Pembrokeshire) and adjacent areas. Journal of Structural Geology 1, 155--162.
Patterson, A.L. (1934) A Fourier series method for the determination of the component of inter-atomic distances in crystals. Physics Reviews 46, 372--376.
Patterson, A.L. (1935) A direct method for the determination of the components of inter-atomic distances in crystals. Zeitschrift fuer Krystallographie 90, 517--554.
Kmeasure,
Kestdata(cells)
fryplot(cells)
Y <- frypoints(cells)
data(amacrine)
X <- split(amacrine)$off
fryplot(X, width=0.25)Run the code above in your browser using DataLab