Reorganize source tree to use single autotools instance

Change-Id: I7b51f88292e057c6443b12224486f2d0c9f8ae23
Signed-off-by: Damjan Marion <damarion@cisco.com>

1 files changed, 78 insertions, 0 deletions

diff --git a/src/tools/perftool/linreg.c b/src/tools/perftool/linreg.c
new file mode 100644
index 00000000000..084091bb907
--- /dev/null
+++ b/src/tools/perftool/linreg.c
@@ -0,0 +1,78 @@
+/* 
+ *------------------------------------------------------------------
+ * Copyright (c) 2006-2016 Cisco and/or its affiliates.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at:
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/* see "Numerical Recipies in C, 2nd ed." p 665 */
+
+#include <stdio.h>
+#include <math.h>
+
+/*
+ * linreg
+ * Linear regression of (xi, yi), returns parameters for least-squares
+ * fit y = a + bx.  Also, compute Pearson's R.
+ */
+void linreg (double *x, double *y, int nitems, double *a, double *b,
+             double *minp, double *maxp, double *meanp, double *r)
+{
+    double sx = 0.0;
+    double sy = 0.0;
+    double st2 = 0.0;
+    double min = y[0];
+    double max = 0.0;
+    double ss, meanx, meany, t;
+    double errx, erry, prodsum, sqerrx, sqerry;
+    int i;
+
+    *b = 0.0;
+    
+    for (i = 0; i < nitems; i++) {
+        sx += x[i];
+        sy += y[i];
+        if (y[i] < min)
+            min = y[i];
+        if (y[i] > max)
+            max = y[i];
+    }
+    ss = nitems;
+    meanx = sx / ss;
+    meany = *meanp = sy / ss;
+    *minp = min;
+    *maxp = max;
+
+    for (i = 0; i < nitems; i++) {
+        t = x[i] - meanx;
+        st2 += t*t;
+        *b += t*y[i];
+    }
+
+    *b /= st2;
+    *a = (sy-sx*(*b))/ss;
+
+    prodsum = 0.0;
+    sqerrx = 0.0;
+    sqerry = 0.0;
+
+    /* Compute numerator of Pearson's R */
+    for (i = 0; i < nitems; i++) {
+        errx = x[i] - meanx;
+        erry = y[i] - meany;
+        prodsum += errx * erry;
+        sqerrx += errx*errx;
+        sqerry += erry*erry;
+    }
+
+    *r = prodsum / (sqrt(sqerrx)*sqrt(sqerry));
+}