Changeset 242 for trunk/SRC/ToBeReviewed/STATISTICS/c_timecorrelate.pro

Timestamp:

04/06/07 10:35:17 (17 years ago)

Author:

pinsard

Message:

improvements/corrections of some *.pro headers + replace some message by some report

File:

• trunk/SRC/ToBeReviewed/STATISTICS/c_timecorrelate.pro (modified) (9 diffs)

trunk/SRC/ToBeReviewed/STATISTICS/c_timecorrelate.pro

@@ -8 +8 @@
 ; @param XD
 ;
-;
 ; @param YD
 ;
-;
 ; @param M
 ;
-;
 ; @param NT
 ;
-;
 ; @param NDIM
 ;
-;
 ; @keyword ZERO2NAN
-;
 ;
 ; @keyword DOUBLE
@@ -30 +24 @@
 ; @examples
 ;
-;
 ; @history
-;
 ;
 ; @version
@@ -38 +30 @@
 ;
 ;-
+;
 FUNCTION timecross_cov, Xd, Yd, M, nT, Ndim, Double = Double, ZERO2NAN = zero2nan
-  ;Sample cross covariance function.
-
+;
   compile_opt hidden
 ;
+;Sample cross covariance function.
    case Ndim OF
       1:res = TOTAL(Xd[0:nT - M - 1L] * Yd[M:nT - 1L] $
@@ -61 +54 @@
 
 END
+;
 ;+
+;
 ; @file_comments
 ; This function computes the "time cross correlation" Pxy(L) or
@@ -71 +66 @@
 ; Statistics
 ;
-; @param X {in}{required}{type=array}
-; An Array which last dimension is the time dimension of
+; @param X {in}{required} {type=array}
+; An array which last dimension is the time dimension of
 ; size n, float or double.
 ;
-; @param Y {in}{required}{type=array}
-; An Array which last dimension is the time dimension of
+; @param Y {in}{required} {type=array}
+; An array which last dimension is the time dimension of
 ; size n, float or double.
 ;
 ; @param LAG {in}{required}{type=scalar or vector}
-; A scalar or n-element vector, in the interval [-(n-2), (n-2)],
+; A scalar or n-elements vector, in the interval [-(n-2),(n-2)],
 ; of type integer that specifies the absolute distance(s) between
 ; indexed elements of X.
@@ -94 +89 @@
 ; @examples
 ;
-;       Define two n-element sample populations.
-;         x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57]
-;         y = [2.31, 2.76, 3.02, 3.13, 3.72, 3.88, 3.97, 4.39, 4.34, 3.95]
-;
-;       Compute the cross correlation of X and Y for LAG = -5, 0, 1, 5, 6, 7
-;         lag = [-5, 0, 1, 5, 6, 7]
-;         result = c_timecorrelate(x, y, lag)
-;
-;       The result should be:
-;         [-0.428246, 0.914755, 0.674547, -0.405140, -0.403100, -0.339685]
+; Define two n-elements sample populations.
+; IDL> x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57]
+; IDL> y = [2.31, 2.76, 3.02, 3.13, 3.72, 3.88, 3.97, 4.39, 4.34, 3.95]
+;
+; Compute the cross correlation of X and Y for LAG = -5, 0, 1, 5, 6, 7
+; IDL> lag = [-5, 0, 1, 5, 6, 7]
+; IDL> result = c_timecorrelate(x, y, lag)
+;
+; The result should be:
+; [-0.428246, 0.914755, 0.674547, -0.405140, -0.403100, -0.339685]
 ;
 ; @history
@@ -120 +115 @@
 ;
 ;-
+;
 FUNCTION c_timecorrelate, X, Y, Lag, Covariance = Covariance, Double = Double
+;
 
 ;Compute the sample cross correlation or cross covariance of
@@ -133 +130 @@
 
    if total(xsize[0:xsize[0]] NE ysize[0:ysize[0]]) NE 0 then $
-    MESSAGE, "X and Y arrays must have the same size and the same dimensions"
+    ras = report("X and Y arrays must have the same size and the same dimensions")
 
 ;Check length.
    if nt lt 2 then $
-    MESSAGE, "Time dimension of X and Y arrays must contain 2 or more elements."
+    ras = report("Time dimension of X and Y arrays must contain 2 or more elements.")
 
 ;If the DOUBLE keyword is not set then the internal precision and
@@ -210 +207 @@
 
 END
-