NAME:spl_keep_mean PURPOSE: Given the arrays X and Y, which tabulate a function (with the X[i] AND Y[i] in ascending order), and given an input value X2, the SPL_INCR function returns an interpolated value for the given values of X2. The interpolation method is based on cubic spline, corrected in a way that integral of the interpolated values is the same as the integral of the input values. (-> for exemple to build daily data from monthly mean and keep the monthly mean of the computed daily data equa to the original values) CATEGORY: CALLING SEQUENCE: y2 = spl_keep_mean(x, y, x2) INPUTS: x: An n-element (at least 2) input vector that specifies the tabulate points in a strict ascending order. y: an array with one element less than x. y[i] represents the mean value between x[i] and x[i+1]. if /GE0 is activated, y must have positive values. x2: The input values for which the interpolated values are desired. Its values must be strictly monotonically increasing. KEYWORD PARAMETERS: /GE0: to force that y2 is always GE than 0. In that case, y must also be GE than 0. YP0: The first derivative of the interpolating function at the point X0. If YP0 is omitted, the second derivative at the boundary is set to zero, resulting in a "natural spline." YPN_1: The first derivative of the interpolating function at the point Xn-1. If YPN_1 is omitted, the second derivative at the boundary is set to zero, resulting in a "natural spline." OUTPUTS: y2: the meean value between two consecutive values of x2. This array has one element less than y2. y2 has double precision. COMMON BLOCKS: none SIDE EFFECTS: ? RESTRICTIONS: It might be possible that y2 has very small negative values (amplitude smaller than 1.e-6)... EXAMPLE: 12 monthly values of precipitations into daily values: yr1 = 1990 yr2 = 1992 nyr = yr2-yr1+1 n1 = 12*nyr+1 x = julday(1+findgen(n1), replicate(1, n1) $ , replicate(yr1, n1), fltarr(n1)) n2 = 365*nyr + total(leapyr(yr1+indgen(nyr))) + 1 x2 = julday(replicate(1, n2), 1+findgen(n2) $ , replicate(yr1, n2), fltarr(n2)) y = abs(randomn(0, n1-1)) y2 = spl_keep_mean(x, y, x2, /ge0) print, min(x, max = ma), ma print, min(x2, max = ma), ma print, vairdate([min(x, max = ma), ma]) print, total(y*(x[1:n1-1]-x[0:n1-2])) print, total(y2*(x2[1:n2-1]-x2[0:n2-2])) MODIFICATION HISTORY: