03-20-2019
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LEARN ABOUT DEBIAN
plgriddata
PLGRIDDATA(3plplot) PLplot API PLGRIDDATA(3plplot)
NAME
plgriddata - Grid data from irregularly sampled data
SYNOPSIS
plggriddata(x, y, z, npts, xg, nptsx, yg, nptsy, zg, type, data)
DESCRIPTION
Real world data is frequently irregularly sampled, but all PLplot 3D plots require data placed in a uniform grid. This function takes
irregularly sampled data from three input arrays x[npts], y[npts], and z[npts], reads the desired grid location from input arrays xg[nptsx]
and yg[nptsy], and returns the gridded data into output array zg[nptsx][nptsy]. The algorithm used to grid the data is specified with the
argument type which can have one parameter specified in argument data.
Redacted form: General: plgriddata(x, y, z, xg, yg, zg, type, data) Perl/PDL: Not available?
This function is used in example 21.
ARGUMENTS
x (PLFLT *, input)
The input x array.
y (PLFLT *, input)
The input y array.
z (PLFLT *, input)
The input z array. Each triple x[i], y[i], z[i] represents one data sample coordinate.
npts (PLINT, input)
The number of data samples in the x, y and z arrays.
xg (PLFLT *, input)
The input array that specifies the grid spacing in the x direction. Usually xg has nptsx equally spaced values from the minimum to
the maximum values of the x input array.
nptsx (PLINT, input)
The number of points in the xg array.
yg (PLFLT *, input)
The input array that specifies the grid spacing in the y direction. Similar to the xg parameter.
nptsy (PLINT, input)
The number of points in the yg array.
zg (PLFLT **, output)
The output array, where data lies in the regular grid specified by xg and yg. the zg array must exist or be allocated by the user
prior to the call, and must have dimension zg[nptsx][nptsy].
type (PLINT, input)
The type of gridding algorithm to use, which can be: GRID_CSA: Bivariate Cubic Spline approximation GRID_DTLI: Delaunay Triangula-
tion Linear Interpolation GRID_NNI: Natural Neighbors Interpolation GRID_NNIDW: Nearest Neighbors Inverse Distance Weighted
GRID_NNLI: Nearest Neighbors Linear Interpolation GRID_NNAIDW: Nearest Neighbors Around Inverse Distance Weighted For details of
the algorithms read the source file plgridd.c.
data (PLFLT, input)
Some gridding algorithms require extra data, which can be specified through this argument. Currently, for algorithm: GRID_NNIDW,
data specifies the number of neighbors to use, the lower the value, the noisier (more local) the approximation is. GRID_NNLI, data
specifies what a thin triangle is, in the range [1. .. 2.]. High values enable the usage of very thin triangles for interpolation,
possibly resulting in error in the approximation. GRID_NNI, only weights greater than data will be accepted. If 0, all weights will
be accepted.
AUTHORS
Geoffrey Furnish and Maurice LeBrun wrote and maintain PLplot. This man page was automatically generated from the DocBook source of the
PLplot documentation, maintained by Alan W. Irwin and Rafael Laboissiere.
SEE ALSO
PLplot documentation at http://plplot.sourceforge.net/resources.
August, 2012 PLGRIDDATA(3plplot)