Returns agridded, 3D array containing intensity values, given random 4D coordinates (this function works best with dense data points).
grid_x The x dimension of the grid. The x values are scaled to fit this dimension.
grid_y The y dimension of the grid. The y values are scaled to fit this dimension.
grid_z The z dimension of the grid. The z values are scaled to fit this dimension.
Nghbr The size of the neighborhood to smooth. If not supplied, the neighborhood size is calculated from the distribution of the points. The amount of memory required increases by the square of the neighborhood size.
No_Avg Normally, if multiple data points fall in the same cell in the gridded array, then the value of that cell is the average value of all the data points that fall in that cell.
If the No_Avg keyword is present and nonzero, however, the value of the cell in the gridded array is the total of all the points that fall in that cell.
XMax The x-coordinate of the right edge of the grid. If omitted, maps the maximum x value found in the points(0, *) array to the right edge of the grid.
XMin The x-coordinate of the left edge of the grid. If omitted, maps the minimum x value found in the points(0, *) array to the left edge of the grid.
YMax The y-coordinate of the top edge of the grid. If omitted, maps the maximum y value found in the points(1, *) array to the top edge of the grid.
YMin The y-coordinate of the bottom edge of the grid. If omitted, maps the minimum y value found in the points(1, *) array to the bottom edge of the grid.
ZMax The z-coordinate of the front edge of the grid. If omitted, maps the maximum z value found in the points(2, *) array to the front edge of the grid.
ZMin The z-coordinate of the back edge of the grid. If omitted, maps the minimum z value found in the points(2, *) array to the back edge of the grid.
FAST_GRID4 is similar to GRID_4D. FAST_GRID4, however, works best with dense data points (more than 1000 points to be gridded) and is considerably faster, but slightly less accurate, than GRID_4D. (GRID_4D works best with sparse data points and is stable when extrapolating into large void areas.)
TIP: For best results, use a small neighborhood (such as 3) and a large number of iterations (more than 16).
UNIX and OpenVMS Users: For information on the optional software package for advanced gridding, PV-WAVE:GTGRID, contact your Visual Numerics account representative.