plgriddata: Grid data from irregularly sampled data

The PLplot Plotting Library: Programmer's Reference Manual
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### `plgriddata`: Grid data from irregularly sampled data

`plggriddata` (x, y, z, npts, xg, nptsx, yg, nptsy, zg, type, data);

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`.

`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.

Redacted form:

- General: `plgriddata(x, y, z, xg, yg, zg, type, data)`

- Perl/PDL: Not available?

This function is used in examples 1,14.

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