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#!F-adobe-helvetica-medium-r-normal--18*
#!N 
#!CSeaGreen #!N  #!Rall191 Connections and Interpolation 
#!N #!EC #!N #!N In the cases just discussed, we made 
the implicit assumption that there is a logical connectivity between adjacent 
members of our 2-dimensional or 3-dimensional grid positions. The path connecting 
grid positions is called a  #!F-adobe-times-medium-i-normal--18*   connection #!EF in Data Explorer. 
For a surface (2- or 3-dimensional positions connected by 2-dimensional connections), 
we could choose to make triangular or quadrilateral connections (i.e.,  #!F-adobe-times-medium-i-normal--18*   
triangles #!EF or  #!F-adobe-times-medium-i-normal--18*   quads #!EF ). Quads require four positions 
for each connection and triangles three. Data Explorer supports these  #!F-adobe-times-medium-i-normal--18*   
element types #!EF as well as cubes, tetrahedra, and lines. #!N 
#!N Suppose we first choose to link adjacent positions in the 
botanist's sample area with  #!F-adobe-times-medium-i-normal--18*   line #!EF connections. The grid markers 
were 1 meter on a side. Given a sampling area of 
5 meters by 3 meters, the entire sample would be 15 
meters square; there would be 24 positions (6 in X, and 
4 in Y). On such a plot, we see that a 
position located at [x=0,y=0] is connected to its neighbor at [x=1,y=0]. 
We can imagine that it is meaningful to draw associations between 
data values at adjacent grid positions considering that so many natural 
phenomena are continuous rather than discrete. We assume that the grasses 
are free to spread across the area and the wind is 
free to blow in any direction over the area. #!N #!N 
Previously, we assumed that samples were measured at the center of 
each grid square; that is, the botanist used  #!F-adobe-times-medium-i-normal--18*   quad #!EF 
connections to associate sets of four positions into 4-sided elements, then 
measured data values at the center of each connection element, yielding 
connection-dependent data. Now, assume that the botanist measures temperature values at 
each grid  #!F-adobe-times-medium-i-normal--18*   position #!EF . Temperature would then be position-dependent 
data. It's perfectly acceptable to have both kinds of data in 
the same data set. We will see how this works when 
we discuss  #!F-adobe-times-medium-i-normal--18*   Fields #!EF . #!N #!N Assume that the 
first grid position (sampling point) lies precisely at the position coordinate 
[x=0,y=0]. We take a measurement and record the value. Then we 
measure the temperature at [x=1,y=0]. Later, we ask, what was the 
temperature at [x=0.5,y=0]? Quite honestly, we do not know, because our 
sampling resolution was not fine enough for us to give a 
definitive answer. However, if we make the assumption (very often, a 
perfectly reasonable assumption, but not always!) that our grid overlaid a 
continuous set of values, we can derive the expected data value 
by interpolation between known values. If we use  #!F-adobe-times-medium-i-normal--18*   line #!EF 
connections to connect adjacent points, we realize by looking at our 
mesh that a straight line connects the grid point [x=0,y=0] and 
[x=1,y=0] and that halfway along this line lies the grid point 
[x=0.5,y=0]. We can further assume that the data value at this 
midpoint is the average of the data values at known sample 
points bordering this location. By linear interpolation, we calculate a reasonable 
value for the temperature at [x=0.5,y=0]. #!N #!N We need to 
define polygonal connections over the 2-D grid if we wish to 
find the value at the point [x=0.2,y=0.7]. With  #!F-adobe-times-medium-i-normal--18*   line #!EF 
connections between adjacent pairs of grid points, we can only reasonably 
perform interpolations along those linear boundaries but not into the middle 
of our grid elements. By defining areas bounded by three or 
more points, we can perform interpolation across the area (the polygon 
surface) using weighting functions that take into account the data values 
at all points surrounding the area. In fact, this is the 
same process used by an image-rendering program: it interpolates from known 
values (at the vertices) across the faces of polygons and computes 
the appropriate color at all visible points on the surface, at 
the resolution allowed by the output device (digital file, computer monitor, 
etc.). #!N #!N #!N  #!F-adobe-times-medium-i-normal--18*   Next Topic #!EF #!N #!N  #!Lall192,dxall193 h Identifying Connections  #!EL  
#!N  #!F-adobe-times-medium-i-normal--18*   #!N