NAME

       plgriddata - Grid data from irregularly sampled data

SYNOPSIS

       plgriddata(x, y, z, npts, xg, nptsx, yg, nptsy, zg, type, data)

DESCRIPTION

       Real  world  data  is  frequently  irregularly  sampled,  but PLplot 3D plots require data
       organized as a grid, i.e., with x sample point values independent of y coordinate and vice
       versa.   This  function  takes  irregularly  sampled  data  from the x[npts], y[npts], and
       z[npts] vectors; reads the desired grid location from  the  input  vectors  xg[nptsx]  and
       yg[nptsy];  and  returns  the  interpolated  result  on  that grid using the output matrix
       zg[nptsx][nptsy].  The algorithm used to interpolate the data to  the  grid  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?  Python: zg=plgriddata(x, y, z, xg, yg, type, data)

       This function is used in example 21.

ARGUMENTS

       x (PLFLT_VECTOR(3plplot), input)
              The input x vector.

       y (PLFLT_VECTOR(3plplot), input)
              The input y vector.

       z (PLFLT_VECTOR(3plplot), input)
              The input z vector. Each  triple  x[i],  y[i],  z[i]  represents  one  data  sample
              coordinate.

       npts (PLINT(3plplot), input)
              The number of data samples in the x, y and z vectors.

       xg (PLFLT_VECTOR(3plplot), input)
              A  vector  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 vector.

       nptsx (PLINT(3plplot), input)
              The number of points in the xg vector.

       yg (PLFLT_VECTOR(3plplot), input)
              A vector that specifies the grid spacing in the y  direction.  Similar  to  the  xg
              parameter.

       nptsy (PLINT(3plplot), input)
              The number of points in the yg vector.

       zg (PLFLT_NC_MATRIX(3plplot), output)
              The  matrix of interpolated results where data lies in the grid specified by xg and
              yg. Therefore the zg matrix must be dimensioned nptsx by nptsy.

       type (PLINT(3plplot), input)
              The type of grid interpolation 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(3plplot), 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

       Many  developers  (who  are  credited  at  http://plplot.sourceforge.net/credits.php) have
       contributed to PLplot over its long history.

SEE ALSO

       PLplot documentation at http://plplot.sourceforge.net/documentation.php.

                                          November, 2017                      PLGRIDDATA(3plplot)