#!F-adobe-helvetica-medium-r-normal--18* #!N #!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
Generated by dwww version 1.15 on Sat Jun 22 12:52:50 CEST 2024.