CLEANDATA Usage: cleanx = CleanData(x, rnge, choice, epsilon); This function will take in a data set x, a specific portion of that data, rnge, and look for any points below (choice = 'below') or above ( (choice = 'above') the threshold epsilon. It will then get rid of those points and create linearly extrapolated points in their place. It returns the cleaned data set cleanx. Note: This function is to be used ONLY when the user knows for a fact that spurious points exist in the data set. It is not very automatic, but assures that only KNOWN false points will be removed from the set. In order to use this, one must look at a plot of the data to determine the portion to look at and the threshold to set.

- FTrack FTRACK

0001 function cleanx = CleanData(x, rnge, choice, epsilon); 0002 0003 %CLEANDATA 0004 % Usage: 0005 % cleanx = CleanData(x, rnge, choice, epsilon); 0006 % 0007 % This function will take in a data set x, a specific portion of that data, 0008 % rnge, and look for any points below (choice = 'below') or above ( 0009 % (choice = 'above') the threshold epsilon. It will then get rid of those 0010 % points and create linearly extrapolated points in their place. It 0011 % returns the cleaned data set cleanx. 0012 % 0013 % Note: This function is to be used ONLY when the user knows for a fact that 0014 % spurious points exist in the data set. It is not very automatic, but 0015 % assures that only KNOWN false points will be removed from the set. In 0016 % order to use this, one must look at a plot of the data to determine the 0017 % portion to look at and the threshold to set. 0018 0019 % Written by Dan Valente 0020 % 10 November 2006 0021 0022 cleanx = x; 0023 dirtyx = x(rnge); 0024 0025 if (strcmp(choice, 'below')) 0026 goodpoints = find(dirtyx > epsilon); 0027 elseif (strcmp(choice, 'above')) 0028 goodpoints = find(dirtyx < epsilon); 0029 end 0030 0031 goodpoints = goodpoints + rnge(1) - 1; 0032 for i = 1:(length(goodpoints)-1) 0033 if ((goodpoints(i+1)-goodpoints(i)) ~= 1) 0034 xf = x(goodpoints(i+1)); 0035 xs = x(goodpoints(i)); 0036 m = (xf-xs)/(goodpoints(i+1)-goodpoints(i)); 0037 count = goodpoints(i); 0038 while count < goodpoints(i+1) 0039 cleanx(count) = m*(count-goodpoints(i))+xs; 0040 count = count+1; 0041 end 0042 end 0043 end 0044 0045 return;

Generated on Fri 28-Sep-2012 12:34:30 by