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
Triangulation 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.