I have a very large and dense 3D dataset that I'd like to render as a surface, but I keep getting the error message quoted below, which I don't really understand. Plotting the data points alone works fine though, and gives me http://img196.imageshack.us/img196/1726/74286445.th.png

I'm using the following code to attempt to generate the surface, where x_ymin, z_ymin, and T_ymin are the three variables contained in the yminplane.mat file. I've also tried using "gridfit" (available from matlabcentral) instead of griddata, but to no avail.

Any help would be much appreciated!

Code:`load yminplane.mat`

gx = x_ymin(1):min(x_ymin)/10:min(x_ymin);

gz = z_ymin(1):min(z_ymin)/10:min(z_ymin);

[XI,ZI] = meshgrid(gx,gz);

TI = griddata(x_ymin,z_ymin,T_ymin,XI,ZI);

surf(XI,ZI,TI), hold

plot3(x_ymin,z_ymin,T_ymin,'.')

Quote:

Warning: Duplicate x-y data points detected: using average of the z values.

> In griddata at 83

In yminfig at 12

??? qhull precision warning:

The initial hull is narrow (cosine of min. angle is 1.0000000000000002).

A coplanar point may lead to a wide facet. Options 'QbB' (scale to unit box)

or 'Qbb' (scale last coordinate) may remove this warning. Use 'Pp' to skip

this warning. See 'Limitations' in qh-impre.htm.

qhull precision error: initial simplex is not convex. Distance=-6.1e-014

While executing: | qhull d Qt Qbb Qc

Options selected for Qhull 2003.1 2003/12/30:

delaunay Qtriangulate Qbbound-last Qcoplanar-keep _pre-merge

_zero-centrum Pgood Qinterior-keep _max-width 2.9e+002

Error-roundoff 4.1e-013 _one-merge 2.9e-012 Visible-distance 8.2e-013

U-coplanar-distance 8.2e-013 Width-outside 1.6e-012 _wide-facet 4.9e-012

_narrow-hull -2.2e-016

The input to qhull appears to be less than 3 dimensional, or a

computation has overflowed.

Qhull could not construct a clearly convex simplex from points:

The center point is coplanar with a facet, or a vertex is coplanar

with a neighboring facet. The maximum round off error for

computing distances is 4.1e-013. The center point, facets and distances

to the center point are as follows:

facet

p42

p4257

p0

distance= -2.6e-014

facet

p4299

p4257

p0

distance= -2.8e-014

facet

p4299

p42

p0

distance= -2.8e-014

facet

p4299

p42

p4257

distance= -2.8e-014

These points either have a maximum or minimum x-coordinate, or

they maximize the determinant for k coordinates. Trial points

are first selected from points that maximize a coordinate.

The min and max coordinates for each dimension are:

0: 3.84 295 difference= 291.2

1: 0 17 difference= 17

2: 6.939e-018 291.2 difference= 291.2

If the input should be full dimensional, you have several options that

may determine an initial simplex:

- use 'QJ' to joggle the input and make it full dimensional

- use 'QbB' to scale the points to the unit cube

- use 'QR0' to randomly rotate the input for different maximum points

- use 'Qs' to search all points for the initial simplex

- use 'En' to specify a maximum roundoff error less than 4.1e-013.

- trace execution with 'T3' to see the determinant for each point.

If the input is lower dimensional:

- use 'QJ' to joggle the input and make it full dimensional

- use 'Qbk:0Bk:0' to delete coordinate k from the input. You should

pick the coordinate with the least range. The hull will have the

correct topology.

- determine the flat containing the points, rotate the points

into a coordinate plane, and delete the other coordinates.

- add one or more points to make the input full dimensional.

This is a Delaunay triangulation and the input is co-circular or co-spherical:

- use 'Qz' to add a point "at infinity" (i.e., above the paraboloid)

- or use 'QJ' to joggle the input and avoid co-circular data

Error in ==> delaunayn at 81

t = qhullmx(x', 'd ', opt);

Error in ==> griddata>linear at 125

tri = delaunayn([x y]);

Error in ==> griddata at 98

zi = linear(x,y,z,xi,yi,opt);

Error in ==> yminfig at 12

TI = griddata(x_ymin,z_ymin,T_ymin,XI,ZI);