-
Notifications
You must be signed in to change notification settings - Fork 23
/
test-smk-ds.tapply.R
143 lines (124 loc) · 4.76 KB
/
test-smk-ds.tapply.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
137
138
139
140
141
142
143
#-------------------------------------------------------------------------------
# Copyright (c) 2014 OBiBa,
# 2019-2020 University of Newcastle upon Tyne. All rights reserved.
#
# This program and the accompanying materials
# are made available under the terms of the GNU Public License v3.0.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#-------------------------------------------------------------------------------
#
# Set up
#
context("ds.tapply::smk::setup")
connect.studies.dataset.cnsim(list("LAB_TSC", "GENDER"))
test_that("setup", {
ds_expect_variables(c("D"))
})
#
# Tests
#
ds.assign('D$LAB_TSC', 'LAB_TSC')
ds.assign('D$GENDER', 'GENDER')
context("ds.tapply::smk::fun=mean")
test_that("simplest 'ds.tapply', fun=mean", {
list <- ds.tapply('LAB_TSC', INDEX.names=c('GENDER'), FUN.name='mean')
expect_length(list, 3)
expect_length(list$sim1, 2)
expect_length(list$sim1$Mean, 2)
expect_equal(list$sim1$Mean[[1]], 5.915789, tolerance=0.0001)
expect_equal(list$sim1$Mean[[2]], 5.827805, tolerance=0.0001)
expect_length(list$sim1$N, 2)
expect_equal(list$sim1$N[[1]], 910)
expect_equal(list$sim1$N[[2]], 897)
expect_length(list$sim2, 2)
expect_length(list$sim2$Mean, 2)
expect_equal(list$sim2$Mean[[1]], 5.935422, tolerance=0.0001)
expect_equal(list$sim2$Mean[[2]], 5.748556, tolerance=0.0001)
expect_length(list$sim2$N, 2)
expect_equal(list$sim2$N[[1]], 1314)
expect_equal(list$sim2$N[[2]], 1225)
expect_length(list$sim3, 2)
expect_length(list$sim3$Mean, 2)
expect_equal(list$sim3$Mean[[1]], 5.910215, tolerance=0.0001)
expect_equal(list$sim3$Mean[[2]], 5.779415, tolerance=0.0001)
expect_length(list$sim3$N, 2)
expect_equal(list$sim3$N[[1]], 1779)
expect_equal(list$sim3$N[[2]], 1700)
})
context("ds.tapply::smk::fun=sd")
test_that("simplest 'ds.tapply', fun=sd", {
list <- ds.tapply('LAB_TSC', INDEX.names=c('GENDER'), FUN.name='sd')
expect_length(list, 3)
expect_length(list$sim1, 2)
expect_length(list$sim1$SD, 2)
expect_equal(list$sim1$SD[[1]], 1.161280, tolerance=0.0001)
expect_equal(list$sim1$SD[[2]], 1.051423, tolerance=0.0001)
expect_length(list$sim1$N, 2)
expect_equal(list$sim1$N[[1]], 910)
expect_equal(list$sim1$N[[2]], 897)
expect_length(list$sim2, 2)
expect_length(list$sim2$SD, 2)
expect_equal(list$sim2$SD[[1]], 1.092681, tolerance=0.0001)
expect_equal(list$sim2$SD[[2]], 1.032583, tolerance=0.0001)
expect_length(list$sim2$N, 2)
expect_equal(list$sim2$N[[1]], 1314)
expect_equal(list$sim2$N[[2]], 1225)
expect_length(list$sim3, 2)
expect_length(list$sim3$SD, 2)
expect_equal(list$sim3$SD[[1]], 1.107388, tolerance=0.0001)
expect_equal(list$sim3$SD[[2]], 1.015554, tolerance=0.0001)
expect_length(list$sim3$N, 2)
expect_equal(list$sim3$N[[1]], 1779)
expect_equal(list$sim3$N[[2]], 1700)
})
context("ds.tapply::smk::fun=sum")
test_that("simplest 'ds.tapply', fun=sum", {
list <- ds.tapply('LAB_TSC', INDEX.names=c('GENDER'), FUN.name='sum')
expect_length(list, 3)
expect_length(list$sim1, 2)
expect_length(list$sim1$Sum, 2)
expect_equal(list$sim1$Sum[[1]], 5383.368, tolerance=0.0001)
expect_equal(list$sim1$Sum[[2]], 5227.541, tolerance=0.0001)
expect_length(list$sim1$N, 2)
expect_equal(list$sim1$N[[1]], 910)
expect_equal(list$sim1$N[[2]], 897)
expect_length(list$sim2, 2)
expect_length(list$sim2$Sum, 2)
expect_equal(list$sim2$Sum[[1]], 7799.144, tolerance=0.0001)
expect_equal(list$sim2$Sum[[2]], 7041.981, tolerance=0.0001)
expect_length(list$sim2$N, 2)
expect_equal(list$sim2$N[[1]], 1314)
expect_equal(list$sim2$N[[2]], 1225)
expect_length(list$sim3, 2)
expect_length(list$sim3$Sum, 2)
expect_equal(list$sim3$Sum[[1]], 10514.273, tolerance=0.0001)
expect_equal(list$sim3$Sum[[2]], 9825.005, tolerance=0.0001)
expect_length(list$sim3$N, 2)
expect_equal(list$sim3$N[[1]], 1779)
expect_equal(list$sim3$N[[2]], 1700)
})
context("ds.tapply::smk::fun=quantile")
test_that("simplest 'ds.tapply', fun=quantile", {
list <- ds.tapply('LAB_TSC', INDEX.names=c('GENDER'), FUN.name='quantile')
expect_length(list, 3)
expect_length(list$sim1, 2)
expect_length(list$sim1$`0`, 15)
expect_length(list$sim1$`1`, 15)
expect_length(list$sim2, 2)
expect_length(list$sim2$`0`, 15)
expect_length(list$sim2$`1`, 15)
expect_length(list$sim3, 2)
expect_length(list$sim3$`0`, 15)
expect_length(list$sim3$`1`, 15)
})
#
# Tear down
#
context("ds.tapply::smk::shutdown")
test_that("shutdown", {
ds_expect_variables(c("D", "GENDER", "LAB_TSC"))
})
disconnect.studies.dataset.cnsim()
context("ds.tapply::smk::done")