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#!F-adobe-helvetica-medium-r-normal--18*
#!N 
#!CSeaGreen #!N  #!Rinvdat Invalid Data 
#!N #!EC #!N #!N Sometimes in the process of collecting or 
analyzing data, certain regions or positions have no data value associated 
with them. For example, an instrument may have a "data drop-out" 
or a simulation may (for whatever reason) produce an invalid entry. 
Of course, if you are explicitly listing your positions or connections, 
you can simply leave those positions out when you create your 
data file. However, if you have a regular grid (for which 
you simply list the origin of the grid and the delta 
in each dimension), this is not convenient. Data Explorer has a 
way to easily handle this situation, using "invalid positions" and "invalid 
connections" components. These components are discussed in  #!Ldatmod,dxall197 h Understanding the Data Model  #!EL  , but briefly, 
when present in a Field, they instruct any module processing that 
Field to completely ignore any position or connection identified in that 
component. For example, an "invalid positions" component may list the integers 
0, 15, and 23. This instructs Data Explorer to ignore the 
positions 0, 15, and 23 (and the data associated with those 
positions). #!N #!N You can create these components in a Data 
Explorer format file (see  #!Limd,dxall618 h Importing Data: File Formats  #!EL  ) or, often more easily, using 
the Include module. For example, suppose in your data file drop-outs 
are indicated with a data value of 9999, while all valid 
data lies in the range 0-100. Then set the  #!F-adobe-times-bold-r-normal--18*   max 
#!EF parameter of Include to 9998. Include will then remove or 
invalidate all of the positions with the value 9999. Note that 
it is usually preferable to set the  #!F-adobe-times-bold-r-normal--18*   cull #!EF flag 
of Include to 0 so that the data values are invalidated 
rather than actually removed (see Include in IBM Visualization Data Explorer 
User's Reference). #!N #!N All Data Explorer modules know to ignore 
invalid data. For example, Streamlines will stop when they reach an 
invalid element, and Statistics will ignore data values associated with invalid 
elements. #!N #!N #!N  #!F-adobe-times-medium-i-normal--18*   Next Topic #!EF #!N #!N  #!Lfields,dxall195 h Fields  #!EL  
#!N  #!F-adobe-times-medium-i-normal--18*   #!N