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)