1PLGRIDDATA(3plplot) PLplot API PLGRIDDATA(3plplot)
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6 plgriddata - Grid data from irregularly sampled data
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9 plggriddata(x, y, z, npts, xg, nptsx, yg, nptsy, zg, type, data)
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12 Real world data is frequently irregularly sampled, but all PLplot 3D
13 plots require data placed in a uniform grid. This function takes irreg‐
14 ularly sampled data from three input arrays x[npts], y[npts], and
15 z[npts], reads the desired grid location from input arrays xg[nptsx]
16 and yg[nptsy], and returns the gridded data into output array
17 zg[nptsx][nptsy]. The algorithm used to grid the data is specified
18 with the argument type which can have one parameter specified in argu‐
19 ment data.
20 Redacted form: General: plgriddata(x, y, z, xg, yg, zg, type, data)
22 Perl/PDL: Not available?
23 This function is used in example 21.
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28 x (PLFLT *, input)
29 The input x array.
30 y (PLFLT *, input)
32 The input y array.
33 z (PLFLT *, input)
35 The input z array. Each triple x[i], y[i], z[i] represents one
36 data sample coordinate.
37 npts (PLINT, input)
39 The number of data samples in the x, y and z arrays.
40 xg (PLFLT *, input)
42 The input array that specifies the grid spacing in the x direc‐
43 tion. Usually xg has nptsx equally spaced values from the mini‐
44 mum to the maximum values of the x input array.
45 nptsx (PLINT, input)
47 The number of points in the xg array.
48 yg (PLFLT *, input)
50 The input array that specifies the grid spacing in the y direc‐
51 tion. Similar to the xg parameter.
52 nptsy (PLINT, input)
54 The number of points in the yg array.
55 zg (PLFLT **, output)
57 The output array, where data lies in the regular grid specified
58 by xg and yg. the zg array must exist or be allocated by the
59 user prior to the call, and must have dimension
60 zg[nptsx][nptsy].
61 type (PLINT, input)
63 The type of gridding algorithm to use, which can be: GRID_CSA:
64 Bivariate Cubic Spline approximation GRID_DTLI: Delaunay Trian‐
65 gulation Linear Interpolation GRID_NNI: Natural Neighbors Inter‐
66 polation GRID_NNIDW: Nearest Neighbors Inverse Distance Weighted
67 GRID_NNLI: Nearest Neighbors Linear Interpolation GRID_NNAIDW:
68 Nearest Neighbors Around Inverse Distance Weighted For details
69 of the algorithms read the source file plgridd.c.
70 data (PLFLT, input)
72 Some gridding algorithms require extra data, which can be speci‐
73 fied through this argument. Currently, for algorithm:
74 GRID_NNIDW, data specifies the number of neighbors to use, the
75 lower the value, the noisier (more local) the approximation is.
76 GRID_NNLI, data specifies what a thin triangle is, in the range
77 [1. .. 2.]. High values enable the usage of very thin triangles
78 for interpolation, possibly resulting in error in the approxima‐
79 tion. GRID_NNI, only weights greater than data will be
80 accepted. If 0, all weights will be accepted.
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85 Geoffrey Furnish and Maurice LeBrun wrote and maintain PLplot. This
86 man page was automatically generated from the DocBook source of the
87 PLplot documentation, maintained by Alan W. Irwin and Rafael
88 Laboissiere.
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91 PLplot documentation at http://plplot.sourceforge.net/resources.
92 July, 2010 PLGRIDDATA(3plplot)