fixed user module (dt)

prompt.py

@@ -542,8 +542,8 @@ def prompt(running = lambda:True, next = lambda:input('> '), state = None):
                 state.stats.need_print = True
                 state.stats.print(clear = False)
                 continue
-            trimed = ws.sub(' ', q.lower()).split(' ') 
+            trimed = ws.sub(' ', og_q).split(' ') 
-            if trimed[0].startswith('f'):
+            if trimed[0].lower().startswith('f'):
                 fn = 'stock.a' if len(trimed) <= 1 or len(trimed[1]) == 0 \
                                 else trimed[1]
                 try:

sdk/Makefile

@@ -1,4 +1,5 @@
 example:
 	$(CXX) -shared -fPIC example.cpp aquery_mem.cpp -fno-semantic-interposition -Ofast -march=native -flto --std=c++1z -o ../test.so
-
+irf:
+	$(CXX) -shared -fPIC RF.cpp irf.cpp incrementalDecisionTree.cpp aquery_mem.cpp Evaluation.cpp -fno-semantic-interposition -Ofast -march=native -flto --std=c++1z -o ../libirf.so
 all: example

sdk/incrementalDecisionTree.cpp

@@ -7,7 +7,10 @@
 #include <fstream>
 #include <float.h>
 #include <ctime>
+#include <random>
 
+std::random_device rd;
+std::mt19937 g(rd());
 struct minEval{
 	double value;
 	int* values;
@@ -54,7 +57,7 @@ long* Rands(long feature, long maxFeature){
 	if(maxFeature==feature){
 		return ret;
 	}
-	std::random_shuffle(ret, &ret[feature]);
+	std::shuffle(ret, &ret[feature], g);
 	long* ret2 = (long*) malloc(maxFeature*sizeof(long)); 
 	for(i=0; i<maxFeature; i++)ret2[i] = ret[i];
 	free(ret);
@@ -473,7 +476,7 @@ void DecisionTree::IncrementalUpdate(double** data, long* result, long size, DT*
 		for(i=0; i<current->size; i++){
 			index[i] = i;
 		}
-		std::random_shuffle(index, index+current->size);
+		std::shuffle(index, index+current->size, g);
 		long x = 0;
 		for(i=0;i<current->size;i++){
 			if(i>=current->size-forgetSize){

sdk/irf.cpp

@@ -33,6 +33,7 @@ __AQEXPORT__(bool) additem(ColRef<double>X, long y, long size){
 		data[pt][j]=X.container[j];
 	}
 	result[pt] = y;
+	pt ++;
 	return 1;
 }
 __AQEXPORT__(bool) fit(){
@@ -46,8 +47,8 @@ __AQEXPORT__(ColRef_storage) predict(){
 	for(long i=0; i<pt; i++){
 		result[i]=dt->Test(data[i], dt->DTree);
 	}
-	ColRef_storage ret(result, pt, pt, "prediction", 0);
+	
-	return ret;
+	return ColRef_storage(new ColRef_storage(result, pt, 0, "prediction", 0), 1, 0, "prediction", 0);
 }
 
 

tests/dt.a

@@ -1,14 +1,11 @@
 LOAD MODULE FROM "./libirf.so"
 FUNCTIONS (
-    mydiv(a:int, b:int) -> double,
+    newtree(height:int, f:int64, sparse:vecint, forget:double, maxf:int64, noclasses:int64, e:int, r:int64, rb:int64) -> bool,
-    mulvec(a:int, b:vecfloat) -> vecfloat,
-    newtree(height:int, f:int64, sparse:vecint, forget:double, maxF:int64, noClasses:int64, e:int, r:int64, rb:int64) -> bool,
     additem(X:vecdouble, y:int64, size:int64) -> bool,
     fit() -> bool,
     predict() -> vecint
 );
 
-select mydiv(2,3);
 create table tb(x int);
 create table tb2(x double, y double, z double);
 insert into tb values (0);
@@ -22,4 +19,4 @@ select additem(tb2.x, 1, 3) from tb2;
 select additem(tb2.y, 0, -1) from tb2;
 select additem(tb2.z, 1, -1) from tb2;
 select fit();
-select predict();
+select predict();

tests/modules.a

@@ -1,22 +1,8 @@
-LOAD MODULE FROM "./libirf.so"
+LOAD MODULE FROM "./test.so" 
 FUNCTIONS (
-    newtree(height:int, f:int64, sparse:vecint, forget:double, maxf:int64, noclasses:int64, e:int, r:int64, rb:int64) -> bool,
+    mydiv(a:int, b:int) -> double, 
-    additem(X:vecdouble, y:int64, size:int64) -> bool,
+    mulvec(a:int, b:vecfloat) -> vecfloat
-    fit() -> bool,
-    predict() -> vecint
 );
 
-create table tb(x int);
+select mydiv(2,3);
-create table tb2(x double, y double, z double);
+
-insert into tb values (0);
-insert into tb values (0);
-insert into tb values (0);
-select newtree(5, 3, tb.x, 0, 3, 2, 0, 100, 1) from tb;
-insert into tb2 values (1, 0, 1);
-insert into tb2 values (0, 1, 1);
-insert into tb2 values (1, 1, 1);
-select additem(tb2.x, 1, 3) from tb2;
-select additem(tb2.y, 0, -1) from tb2;
-select additem(tb2.z, 1, -1) from tb2;
-select fit();
-select predict();