moved example data into data folder; added initial version of quad_reg.awk;

1 files changed, 91 insertions, 0 deletions

diff --git a/quad_reg.awk b/quad_reg.awk
new file mode 100644
index 0000000..8939947
--- /dev/null
+++ b/quad_reg.awk
@@ -0,0 +1,91 @@
+#!/usr/bin/awk -f
+
+### lin_reg2.awk
+# simple linear regression between columns
+
+BEGIN {
+    sign = "[+-]?"
+    decimal = "[0-9]+[.]?[0-9]*"
+    fraction = "[.][0-9]*"
+    exponent = "([Ee]" sign "[0-9]+)?"
+    number = "^" sign "(" decimal "|" fraction ")" exponent "$"
+}
+
+NR == 1 {
+    for (n=1; n<=NF; n++)
+        ($n ~ number) ? header[n] = "col" n : header[n] = $n
+}
+
+NF > 0 {
+    if (NF > nf_max)
+        nf_max = NF
+
+    ### iterate over columns
+    for (y=1; y<=nf_max; y++) {
+        if ($y ~ number) {
+
+            ### mean
+            count[y] += 1
+            sum[y] += $y
+            sum2[y] += $y*$y
+            mean[y] = sum[y]/count[y]
+
+            ### difference from the mean
+            delta[y] = $y - mean[y]
+            sum_delta[y] += delta[y]
+            sum_delta2[y] += delta[y]*delta[y]
+
+            ### sample variance
+            (count[y] > 1) ? var[y] = sum_delta2[y]/(count[y] - 1) : var[y] = ""
+
+            # x = row, y = col
+            for (x=1; x<=nf_max; x++) {
+                count[x,y] += 1
+                sum_xy[x,y] += $x*$y
+                sum_delta_xy[x,y] += delta[x]*delta[y]
+
+                # correlation
+                r_den[x,y] = sqrt(sum_delta2[x]*sum_delta2[y])
+                (r_den[x,y]) ? r[x,y] = sum_delta_xy[x,y]/r_den[x,y] : r[x,y] = 1
+
+                ab_den[x,y] = (count[x,y]*sum2[x] - sum[x]*sum[x])
+                if (ab_den[x,y]) {
+                    a[x,y] = (sum[y]*sum2[x] - sum[x]*sum_xy[x,y])/ab_den[x,y]
+                    b[x,y] = (count[x,y]*sum_xy[x,y] - sum[x]*sum[y])/ab_den[x,y]
+                }
+                else {
+                    a[x,y] = 0
+                    b[x,y] = 1
+                }
+
+                ### error estimate
+                err_den[x,y] = count[x,y]*(count[x,y] - 2)
+                if (count[x,y] > 2) {
+                    err[x,y] = $y - (a[x,y] + b[x,y]*$x)
+                    sum_err2[x,y] += err[x,y]*err[x,y]
+                }
+                b_err_den[x,y] = (count[x,y] - 2)*sum_delta2[x]
+                if (b_err_den[x,y])
+                    b_err[x,y] = sqrt(sum_err2[x,y]/b_err_den[x,y])
+                a_err_den[x,y] = count[x,y]*b_err_den[x,y]
+                if (a_err_den[x,y])
+                    a_err[x,y] = sqrt(sum2[x]/count[x,y])*b_err[x,y]
+            }
+        }
+        else
+            continue
+    }
+}
+
+END {
+    for (y=1; y<=nf_max; y++) {
+        for (x=1; x<=nf_max; x++) {
+            if (x != y && r[x,y]) {
+                printf(OFMT OFS "(%s)" OFS " = (" OFMT " +/- " OFMT ")(%s)" OFS " + (" OFMT " +/- " OFMT ")" ORS,
+                    10.0*log(r[x,y]*r[x,y])/log(10), header[y], b[x,y], b_err[x,y], header[x],
+                    a[x,y], a_err[x,y])
+            }
+        }
+    }
+}
+