;+ ;spd_ui_draw_object method: makeLineReference ; ; ;this routine constructs a reference for legend lookup that has ;no more than the number of points on the screen times some number ;to account for pixel-level aliasing. Operation vectorized with ;value-locate ;x = clipped abcissa values, normalized to fractions of the total ;y = clipped data values, with the same number of elements as x ;n = the number of points requested in the output ;ref = data returned in named variable ;tolerance = the distance that a cursor can be from a real data point, before NaNs ; get filled in. This is a number proportional to the x range.(ex: .01 = 1% tolerance) ; ;$LastChangedBy: jimm $ ;$LastChangedDate: 2014-02-11 10:54:32 -0800 (Tue, 11 Feb 2014) $ ;$LastChangedRevision: 14326 $ ;$URL: svn+ssh://thmsvn@ambrosia.ssl.berkeley.edu/repos/spdsoft/trunk/spedas/gui/display/draw_object/spd_ui_draw_object__makelinereference.pro $ ;- pro spd_ui_draw_object::makeLineReference,x,y,n,ref=ref,tolerance=tolerance compile_opt idl2,hidden ;m = n_elements(x) ;set to 100% tolerance. Meaning NANs will never be filled in unless they are in the data. if ~keyword_set(tolerance) then begin tolerance = 1. endif minx = min(x,/nan) maxx = max(x,/nan) ref = dblarr(n) ref[*] = !VALUES.D_NAN ;These are fractional positions of points ;at which data values will be requested vals = (dindgen(n)/(n-1) > 0) < 1 ;This pads the abcissas to deal with some ;of the weirdness in value_locate's output indexes datx = [minx-.001,x,maxx+.001] ;**********Save this code*********** ;This code resamples the data rather than interpolates, it is being commented ;because it can leave large NaN sized gaps in the results. ; ;value_locate requires sorted data, but ;the abcissa values may not be. ;So we sort, then later we unsort sort_idx = bsort(datx) ;sort transform isort_idx = bsort(sort_idx) ;inverse sort transform datx = datx[sort_idx] ;Locate the values close_idx = value_locate(datx,vals) ;The list of abcissa values one higher than the requested locations lows = abs((datx)[close_idx]-vals) ;The list of abcissa values one lower than the requested locations highs = abs((datx)[close_idx+1]-vals) ;The list of lows that are closer to the values than highs and within ;the tolerance idx_lows = where(lows lt highs and lows lt tolerance,count_lows) ;Store these values. To get to the final results, we need to use the inverse sort ;on the locations if count_lows gt 0 then begin ref[idx_lows] = ([!VALUES.D_NAN,y,!VALUES.D_NAN])[isort_idx[close_idx[idx_lows]]] endif ;The list of highs that are closer to the values than lows and within ;the tolerance idx_highs = where(highs lt lows and highs lt tolerance,count_highs) ;Store these values. To get to the final results, we need to use the inverse sort ;on the locations if count_highs gt 0 then begin ref[idx_highs] = ([!VALUES.D_NAN,y,!VALUES.D_NAN])[isort_idx[close_idx[idx_highs]+1]] endif end