initial support for pack expr

tests/q.sql

@@ -1,112 +0,0 @@
-FUNCTION
-execStrategy ( alloc , mavgday , mavgmonth , px ) {
-buySignal := mavgday > mavgmonth ;
-f := a + b ;
-alloc * prd (
-CASE maxs ( buySignal )
-WHEN TRUE THEN
-CASE buySignal
-WHEN TRUE THEN 1 / px
-ELSE px
-END
-ELSE 1
-END )
-}
-FUNCTION covariance (x , y ) {
-xmean := avg (x) ;
-ymean := avg (y) ;
-avg (( x - xmean ) * (y - ymean ))
-}
-FUNCTION sd ( x) {
-sqrt ( covariance (x , x) )
-}
-FUNCTION pairCorr (x , y ) {
-covariance (x , y ) / ( sd (x) * sd (y ))
-}
-<k>
-`
-p:5
-q:2
-phi:(p+1)?1.
-theta:q?1.
-"p q phi theta"
-p
-q
-phi
-theta
-l:()
-e:()
-
-`
-L1:10?20
-Le1:10?2.
-L2:3?20
-Le2:3?2.
-"L1 Le1 L2 Le2"
-L1
-Le1
-L2
-Le2
-
-`
-"Add L1, then predict"
-l:l,L1
-e:e,Le1
-predict:(phi(0)) + (sum ({[x](phi(x+1)) * (l(((#l)-1)-x))}[!p])) - (sum ({[x](theta(x)) * (e(((#e)-1)-x))}[!q]))
-predict
-
-`
-"Add L2, then predict"
-l:l,L2
-e:e,Le2
-predict:(phi(0)) + (sum ({[x](phi(x+1)) * (l(((#l)-1)-x))}[!p])) - (sum ({[x](theta(x)) * (e(((#e)-1)-x))}[!q]))
-predict
-
- </k>
-
-WITH
-Target (Id , TradeDate , ClosePrice ) AS
-( SELECT
-Id , TradeDate , ClosePrice
-FROM price
-WHERE Id IN stock10 AND
-TradeDate >= startYear10 AND
-TradeDate <= startYear10 + 365 * 10),
-weekly (Id , bucket , name , low , high , mean ) AS
-( SELECT
-Id ,
-timeBucket ,
-" weekly " ,
-min ( ClosePrice ) ,
-max ( ClosePrice ) ,
-avg ( ClosePrice )
-FROM Target
-GROUP BY Id , getWeek ( TradeDate ) as
-timeBucket ),
-monthly ( Id , bucket , name , low , high , mean ) AS
-( SELECT
-Id ,
-timeBucket ,
-" monthly " ,
-min ( ClosePrice ) ,
-max ( ClosePrice ) ,
-avg ( ClosePrice )
-FROM Target
-GROUP BY Id , getMonth ( TradeDate ) as
-timeBucket ),
-yearly (Id , bucket , name , low , high , mean ) AS
-( SELECT
-Id ,
-timeBucket ,
-" yearly " ,
-min ( ClosePrice ) ,
-max ( ClosePrice ) ,
-avg ( ClosePrice )
-FROM Target
-GROUP BY Id , getYear ( TradeDate ) as
-timeBucket )
-SELECT
-Id , bucket , name , low , high , mean
-FROM
-CONCATENATE ( weekly , monthly , yearly )
-ASSUMING ASC Id , ASC name , ASC bucket

tests/udf2.a

@@ -1,14 +0,0 @@
-AGGREGATION FUNCTION covariances(x, y, w){
-    static xmeans := 0., ymeans := 0., cnt := 0; 
-    if (cnt < w) 
-    { 
-        xmeans += x; 
-        ymeans += y; 
-        cnt+=1;
-    }
-    else {       
-        xmeans += (x - x.vec[cnt - w]) / w;
-        ymeans += (y - y.vec[cnt - w]) / w;   
-    }
-    avg (( x.vec(x.len-w, x.len) - xmeans ) * (y.vec(y.len - w, y.len) - ymeans ))
-}

tests/udf4.a

@@ -1,32 +0,0 @@
-AGGREGATION FUNCTION covariances2(x, y, w){
-    xmeans := 0.;
-    ymeans := 0.;
-    l := _builtin_len;
-    if (w > l)
-        w := l;
-    elif (w > l + 2)
-    {
-        l := 3;
-        w := 4;
-    }
-    elif(w < 99){
-        l := 8;
-    }
-    elif(w<999)
-        w := 6;
-    else
-        l := l / 2;
-
-    for (i := 0, j:= 0; i < w; i := i+1) {
-        xmeans += x[i]; 
-        ymeans += y[i]; 
-        _builtin_ret[i] := avg (( x(l-w, l) - xmeans ) * (y(l - w, l) - ymeans ));
-    }
-    for (i := 0; i < l; i += 1) 
-    {
-        xmeans += (x[i] - x[i - w]) / w;
-        ymeans += (y[i] - y[i - w]) / w;   
-        _builtin_ret[i] := avg (( x(l-w, l) - xmeans ) * (y(l - w, l) - ymeans ));
-    }
-    Null
-}