1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
|
#!/usr/bin/awk -f
### lin_reg.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 == header[n])
continue
if ($y ~ number) {
### mean
count[y] += 1
sum[y] += $y
sum2[y] += $y*$y
delta0[y] = $y - mean[y]
mean[y] += delta0[y]/count[y]
delta1[y] = $y - mean[y]
sum_delta[y] += delta1[y]
sum_delta2[y] += delta0[y]*delta1[y]
### sample variance
#(count[y] > 1) ? var[y] = sum_delta2[y]/(count[y] - 1) : var[y] = ""
# x = row, y = col, trendline: y = A + Bx
for (x=1; x<=nf_max; x++) {
count[x,y] += 1
sum_xy[x,y] += $x*$y
sum_delta_xy[x,y] += delta0[x]*delta1[y]
# covariance
#(count[x,y] > 1) ? cov[x,y] = sum_delta_xy[x,y]/(count[x,y] - 1) : cov[x,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(10.0),
header[y], b[x,y], b_err[x,y],
header[x], a[x,y], a_err[x,y])
}
}
}
}
|
