All the .fld files in this directory are representations of seismic P-wave velocity in the lower mantle of the earth. The data is derived from a spherical harmonic expansion and so can be converted to several different kinds of AVS data structure. The value is defined only in the region of the lower mantle -- between two spherical shells at 3441km and 5700km from the centre. The range of the data is between -21 and 21. lm1-uniform.fld Sampled on a 51x51x51 grid. Points outside the lower mantle are given a value of -800. lm1-scatter.n.fld Sampled on a grid in spherical polar co-ordinates. The cartesian co-ordinates of the grid points are added to complete a 1D "scatter" AVS field. The data has been downsized from the 61x31x10 grid by n. lm1-irreg.fld Sampled on a 61x31x10 grid in spherical polar co-ordinates. The cartesian co-ordinates of the grid points are added to complete a 3D irregular AVS field. There are several illustrative networks to demonstrate the merits and demerits of each type of field. 1) Isosurface -- iso.net. Can be used with uniform or irregular data. The disadvantage of the uniform sampling is that an isosurface is always drawn between the data and the non-data. 2) Arbitrary slicer -- still one of the best ways to look at fine detail in 3D data. Compare uniform and irregular datasets. 3) 3D voxel rendering -- tracer.net and shade.net. In general volume rendering only works on uniform data. The colormap "hole.cmap" makes the bulk of the data around 0 fairly transparent so the structure can be seen. 4) Example of the scatter_to_ucd module -- scatter.net This is one way to use scatter fields. Note that the time varies as a high power of the data size -- try it with the most downsized field first! 5) UCD. ucd-*.net The irregular field is converted to a UCD structure by the "field_to_ucd" module. ucd-rslice and ucd-crop give excellent 3D renditions showing the 3D structure as well as the data. 6) ucd-iso.net. Compare with iso.net. 7) UCD Voxel rendering -- ucd-tracer.net. This is the only way to do voxel rendering of irregular 3D data in AVS. Keep the downsize low though! Some vague conclusions. a) The bounded nature of the data makes the uniform field representation nearly useless. The only technique that works is 3D voxel rendering. The trick is to assign an out-of-band value to the underined region and assign that range a zero opacity in thr colourmap. b) Scatter fields are not much use as there is no explicit information on the spatial locality of the points. That is you can't find the neighbouring points easily. Scatter_to_ucd adds this information, but at a heavy and unbounded cost in CPU time. c) Provide the locality information by defining a field of true curvilinear co-ordinates, with a mapping from computational to physical space. You (nearly) lose the ability to do voxel rendering but gain much more. You get a clear view of the domain of your data using volume bounds -- or even more clearly by converting it to UCD.