#!F-adobe-helvetica-medium-r-normal--18*
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#!CSeaGreen #!N  #!Rplohis Plots and Histograms #!N #!EC #!N #!N 
Data Explorer provides a Plot module that will give you a 
simple 2-D graphics plot of your data. This can be convenient 
for showing one parameter plotted "traditionally" while you show a colored 
3-D height Field illustrating the same or other parameters, in the 
same scene. #!N #!N Histogram regroups your data into a specified 
number of bins (it acts like a form of filter on 
your data). The output of Histogram is a new Field with 
connection-dependent data. The connections are the bars on the histogram (which 
can be plotted). The height of each histogram bar is proportional 
to the number of samples of original data that occur in 
the range covered by that bar. You can feed the output 
of Histogram through AutoColor then Plot to get a colored plot 
of the data distribution. #!N #!N If the aspect ratio of 
the Plot is distorted, you can correct it in the Plot 
module. This will stretch the Plot out in either the X 
or the Y direction until you achieve the look you want. 
Visual designers recommend an aspect ratio of approximately 4 units wide 
to 3 units high; since this is also the aspect ratio 
of television, your image will be ready both for video and 
for print. #!N #!N Be aware that "binning" your data with 
Histogram can sometimes create rather arbitrary distributions. It is important to 
make this clear to the viewer of your visualization. For example, 
by carefully selecting bin size, you may turn a unimodal distribution 
into a bimodal one. Which distribution is correct for the phenomenon 
under study must be determined by the underlying science, not by 
the arbitrary picture you create. #!N #!N On the other hand, 
if you wish to actually redistribute your data rather than just 
show a histogram of its distribution, you can use the Equalize 
module. The output of this module is essentially the same scalar 
Field you fed into it, but the data values have been 
changed to fit the specified distribution. By default, the data values 
are changed to approximate a uniform distribution, but you can create 
your own custom distribution, like a normal Gaussian curve. Equalize is 
useful to reduce extreme values back to a range similar to 
the majority of data values. You may also wish to experiment 
with other data "compression" and "expansion" techniques by connecting your data 
Field to Compute and applying a function like "ln(a)" or "a^2," 
where "a" is the input Field. #!N #!N #!N  #!F-adobe-times-medium-i-normal--18*   Next 
Topic #!EF #!N #!N  #!Lrubsht,dxall605 h Rubbersheet  #!EL  #!N  #!F-adobe-times-medium-i-normal--18*   #!N 
