-
Notifications
You must be signed in to change notification settings - Fork 5
/
test_numpy_kendall.R
136 lines (105 loc) · 2.25 KB
/
test_numpy_kendall.R
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
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
library(reticulate)
use_python("/usr/local/bin/python3")
#py_config()
run_np_kt = function(x, y, py_stats, type = "global"){
if (type == "local") {
x_na = is.na(x)
y_na = is.na(y)
match_na = x_na & y_na
x = x[!match_na]
y = y[!match_na]
}
min_xy = min(c(x, y), na.rm = TRUE)
na_replace = min_xy - 0.1
x2 = x
y2 = y
x2[is.na(x)] = na_replace
y2[is.na(y)] = na_replace
np_out = py_stats$kendalltau(x2, y2)
np_out
}
run_cor_test = function(x, y, type = "global"){
if (type == "local") {
x_na = is.na(x)
y_na = is.na(y)
match_na = x_na & y_na
x = x[!match_na]
y = y[!match_na]
}
min_xy = min(c(x, y), na.rm = TRUE)
na_replace = min_xy - 0.1
x2 = x
y2 = y
x2[is.na(x)] = na_replace
y2[is.na(y)] = na_replace
r_out = cor.test(x2, y2, method = "kendall", continuity = TRUE)
r_out
}
py_scipy = import("scipy")
py_stats = import("scipy.stats")
x = rnorm(100)
y = x + 1
#x = round(x, 2)
#y = round(y, 2)
np1 = run_np_kt(x, y, py_stats)
np1$correlation
np1$pvalue
r1 = run_cor_test(x, y)
r1
library(visualizationQualityControl)
ici1 = ici_kendallt(x, y, perspective = "global")
ici1
x2 = x
x2[1:5] = x[100]
y2 = y
y2[10:15] = y[100]
np2 = run_np_kt(x2, y, py_stats)
np2$correlation
np2$pvalue
r2 = run_cor_test(x2, y)
r2
ici2 = ici_kendallt(x2, y, perspective = "global")
ici2
np3 = run_np_kt(x2, y2, py_stats)
np3$correlation
np3$pvalue
r3 = run_cor_test(x2, y2)
r3
ici3 = ici_kendallt(x2, y2, perspective = "global")
ici3
x3 = x
x3[1:20] = NA
y3 = y
y3[40:60] = NA
np4 = run_np_kt(x3, y, py_stats)
np4$correlation
np4$pvalue
r4 = run_cor_test(x3, y)
r4
ici4 = ici_kendallt(x3, y, perspective = "global")
ici4
np5 = run_np_kt(x3, y3, py_stats)
np5$correlation
np5$pvalue
r5 = run_cor_test(x3, y3)
r5
ici5 = ici_kendallt(x3, y3, perspective = "global")
ici5
# very good thus far, everything tracks nicely
# Now lets try putting some in common to verify local vs global
y4 = y
y4[c(1:5, 35:40)] = NA
np4 = run_np_kt(x3, y4, py_stats)
np4$correlation
np4$pvalue
r4 = run_cor_test(x3, y4)
r4
ici4 = ici_kendallt(x3, y4, perspective = "global")
ici4
np5 = run_np_kt(x3, y4, py_stats, "local")
np5$correlation
np5$pvalue
r4 = run_cor_test(x3, y4, "local")
r4
ici5 = ici_kendallt(x3, y4, "local")
ici5