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
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
|
context("FOCUS Step 1 calculations") # {{{1
test_txt <- readLines(
system.file("testdata/Steps_12_pesticide.txt", package = "pfm")
)
# Define test compounds as in pesticide.txt
dummy_1 <- chent_focus_sw("Dummy 1", cwsat = 6000, DT50_ws = 6, DT50_soil = 6, Koc = 344.8,
DT50_water = 6, DT50_sediment = 6)
dummy_2 <- chent_focus_sw("Dummy 2", cwsat = 30, DT50_ws = 26, DT50_soil = 56, Koc = 110,
DT50_water = 26, DT50_sediment = 26)
dummy_4 <- chent_focus_sw("Dummy 4", cwsat = 2e-3, DT50_ws = 4, Koc = 970,
DT50_soil = 19, DT50_water = 4, DT50_sediment = 4)
dummy_5 <- chent_focus_sw("Dummy 5", cwsat = 1.15, DT50_ws = 118, Koc = 860,
DT50_soil = 250, DT50_water = 6, DT50_sediment = 118)
dummy_7 <- chent_focus_sw("Dummy 7", cwsat = 2.60, DT50_ws = 28, Koc = 500,
DT50_soil = 50, DT50_water = 2.5, DT50_sediment = 28)
new_dummy <- chent_focus_sw("New Dummy", mw = 250, Koc = 100,
DT50_soil = 10)
M1 <- chent_focus_sw("Metabolite M1",
mw = 100, cwsat = 100, DT50_ws = 100,
Koc = 50, max_ws = 0, max_soil = 0.5,
DT50_soil = 20, DT50_water = 10, DT50_sediment = 100)
M2 <- chent_focus_sw("Metabolite M2",
mw = 100, cwsat = 100, DT50_ws = 100,
Koc = 50, max_ws = 0.5, max_soil = 0,
DT50_soil = 20, DT50_water = 10, DT50_sediment = 100)
t_out_1 <- c(0, 1, 2, 4) # Checking the first four days is sufficient for Step 1
PEC_template_1 <- matrix(NA, nrow = length(t_out_1), ncol = 4,
dimnames = list(Time = t_out_1, type = c("PECsw", "TWAECsw", "PECsed", "TWAECsed")))
t_out_2 <- c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100) # We read in text from rtf reports for Step 2
test_that("Results of Steps 1/2 calculator for Dummy 1 are reproduced", { # {{{1
res_step_1_1 <- PEC_sw_focus(dummy_1, 3000,
comment = "Potatoes, Southern Europe, spring, 1 app/season, soil incorporation",
scenario = "no drift (incorp or seed trtmt)",
region = "s", season = "mm",
append = FALSE, overwrite = TRUE)
PEC_step_1_1 <- PEC_template_1
PEC_step_1_1[, "PECsw"] = c(685.06, 610.32, 543.73, 431.56)
PEC_step_1_1[, "TWAECsw"] = c(NA, 647.69, 612.03, 548.76)
PEC_step_1_1[, "PECsed"] = c(2.36, 2.1, 1.87, 1.49) * 1e3
PEC_step_1_1[, "TWAECsed"] = c(NA, 2.23e3, 2.11e3, 1.89e3)
expect_equal(res_step_1_1$PEC[1:4, c(1, 2)], PEC_step_1_1[, c(1, 2)], tolerance = 0.01, scale = 1)
expect_equal(res_step_1_1$PEC[1:4, c(3, 4)], PEC_step_1_1[, c(3, 4)], tolerance = 10, scale = 1)
# This is pasted from the file "Dummy 1 step 2.rtf" generated with Steps12 version 3.2 from 15/05/2017
PEC_step_2_1_raw <- read.table(text = "0 172.6235 NA 595.2057 NA
1 153.7900 163.2067 530.2680 562.7368
2 137.0113 154.3037 472.4151 532.0392
4 108.7460 138.3873 374.9561 477.1595
7 76.8950 118.5090 265.1340 408.6191
14 34.2528 85.6494 118.1038 295.3191
21 15.2579 64.9380 52.6092 223.9062
28 6.7966 51.3222 23.4348 176.9589
42 1.3486 35.3389 4.6500 121.8484
50 0.5352 29.8256 1.8454 102.8388
100 0.0017 14.9591 0.0057 51.5788")
PEC_step_2_1 = PEC_step_2_1_raw[, 2:5]
dimnames(PEC_step_2_1) = list(Time = t_out_2,
type = c("PECsw", "TWAECsw", "PECsed", "TWAECsed"))
# Step 2 is not implemented, so this can not be tested.
})
test_that("Results of Steps 1/2 calculator for Dummy 2 are reproduced", { # {{{1
res_dummy_2 <- PEC_sw_focus(dummy_2, 1000,
comment = "Maize, Southern Europe, spring, 1 app/season",
scenario = "maize",
region = "s", season = "mm",
append = TRUE)
PEC_step_1_2 = PEC_template_1
PEC_step_1_2[, "PECsw"] = c(299.89, 290.86, 283.21, 268.50)
PEC_step_1_2[, "TWAECsw"] = c(NA, 295.38, 291.20, 283.49)
PEC_step_1_2[, "PECsed"] = c(319.77, 319.95, 311.53, 295.35)
PEC_step_1_2[, "TWAECsed"] = c(NA, 319.86, 317.79, 310.58)
expect_equal(res_dummy_2$PEC[1:4, ], PEC_step_1_2[, ], tolerance = 0.01, scale = 1)
})
test_that("Results of Steps 1/2 calculator for Dummy 4 are reproduced", { # {{{1
res_dummy_4 <- PEC_sw_focus(dummy_4, 7.5, n = 3, i = 14,
comment = "Apples, Southern Europe, spring, 3 app./season, 14 d int, orchards",
region = "s", season = "mm",
scenario = "pome / stone fruit, early",
append = TRUE)
PEC_step_1_4 = PEC_template_1
PEC_step_1_4[, "PECsw"] = c(1.82, 1.18, 1.00, 0.70)
PEC_step_1_4[, "TWAECsw"] = c(NA, 1.50, 1.29, 1.07)
PEC_step_1_4[, "PECsed"] = c(10.57, 11.49, 9.66, 6.83)
PEC_step_1_4[, "TWAECsed"] = c(NA, 11.03, 10.79, 9.48)
expect_equal(res_dummy_4$PEC[1:4, ], PEC_step_1_4[, ], tolerance = 0.01, scale = 1)
})
test_that("Results of Steps 1/2 calculator for Dummy 5 are reproduced", { # {{{1
res_dummy_5 <- PEC_sw_focus(dummy_5, 75, n = 5, i = 14,
comment = "Vines, Northern Europe, spring, 5 app/seaon 14 d int.",
region = "n", season = "mm",
scenario = "vines, early",
append = TRUE)
PEC_step_1_5 = PEC_template_1
PEC_step_1_5[, "PECsw"] = c(61.60, 59.45, 59.10, 58.41)
PEC_step_1_5[, "TWAECsw"] = c(NA, 60.53, 59.90, 59.33)
PEC_step_1_5[, "PECsed"] = c(500.78, 511.28, 508.29, 502.35)
PEC_step_1_5[, "TWAECsed"] = c(NA, 506.03, 507.90, 506.61)
expect_equal(res_dummy_5$PEC[1:4, ], PEC_step_1_5[, ], tolerance = 0.01, scale = 1)
})
test_that("Results of Steps 1/2 calculator for Dummy 7 are reproduced", { # {{{1
res_dummy_7 <- PEC_sw_focus(dummy_7, 750, n = 4, i = 14,
comment = "Vines, Southern Europe, spring, 4 app/seaon 14 d int.",
region = "s", season = "mm",
scenario = "vines, early",
append = TRUE)
PEC_step_1_7 = PEC_template_1
PEC_step_1_7[, "PECsw"] = c(626.99, 601.13, 586.43, 558.10)
PEC_step_1_7[, "TWAECsw"] = c(NA, 614.06, 603.90, 588.03)
PEC_step_1_7[, "PECsed"] = c(3.0, 3.01, 2.93, 2.79) * 1e3
PEC_step_1_7[, "TWAECsed"] = c(NA, 3.01e3, 2.99e3, 2.92e3)
expect_equal(res_dummy_7$PEC[1:4, c(1, 2)], PEC_step_1_7[, c(1, 2)], tolerance = 0.01, scale = 1)
expect_equal(res_dummy_7$PEC[1:4, c(3, 4)], PEC_step_1_7[, c(3, 4)], tolerance = 10, scale = 1)
})
test_that("Results of Steps 1/2 calculator for New Dummy (M1-M2) are reproduced", { # {{{1
res_M1 <- PEC_sw_focus(new_dummy, 1000, scenario = "cereals, winter",
comment = "Soil Metabolite",
region = "n", season = "of",
met = M1,
append = TRUE)
PEC_step_1_M1 = PEC_template_1
PEC_step_1_M1[, "PECsw"] = c(62.5, 62.07, 61.64, 60.79)
PEC_step_1_M1[, "TWAECsw"] = c(NA, 62.28, 62.07, 61.64)
PEC_step_1_M1[, "PECsed"] = c(31.25, 31.03, 30.82, 30.40)
PEC_step_1_M1[, "TWAECsed"] = c(NA, 31.14, 31.03, 30.82)
expect_equal(res_M1$PEC[1:4, ], PEC_step_1_M1[, ], tolerance = 0.01, scale = 1)
res_M2 <- PEC_sw_focus(new_dummy, 1000, scenario = "cereals, winter",
comment = "Water Metabolite",
region = "n", season = "of",
met = M2,
append = TRUE)
PEC_step_1_M2 = PEC_template_1
PEC_step_1_M2[, "PECsw"] = c(64.34, 63.78, 63.34, 62.47)
PEC_step_1_M2[, "TWAECsw"] = c(NA, 64.06, 63.81, 63.36)
PEC_step_1_M2[, "PECsed"] = c(31.25, 31.89, 31.67, 31.23)
PEC_step_1_M2[, "TWAECsed"] = c(NA, 31.57, 31.68, 31.56)
expect_equal(res_M2$PEC[1:4, ], PEC_step_1_M2[, ], tolerance = 0.01, scale = 1)
})
context("FOCUS Steps 12 input files") # {{{1
# When we compare the generated input file with the test file,
# we can ignore some fields if we are looking at the parent ai
# Also, the ai and compound names are not checked, as we append
# scenario, region and season in order to get unique names
# for Step 2 result files of the Step12 calculator
field_index <- c(ai = 1, compound = 2, comment = 3,
mw_ai = 4, mw_met = 5,
cwsat = 6, Koc_assessed = 7,
Koc_parent = 8,
DT50_ws = 9,
max_ws = 10, max_soil = 11,
rate = 12, n = 13, i = 14, app_type = 15,
DT50_soil_parent = 16, DT50_soil = 17, DT50_water = 18, DT50_sediment = 19,
reg_sea = 20, int_class = 21)
field_index_mets <- field_index[-c(1, 2)]
field_index_parent <- field_index[-c(1:2, 4:5, 8, 10:11, 16)]
test_that("Runs are correctly defined in the Steps 12 input file", { # {{{1
pest_txt <- readLines("pesticide.txt")
expect_equal(test_txt[1], pest_txt[1]) # Header
# Dummy 1
test_1 <- strsplit(test_txt[2], "\t")[[1]][field_index_parent]
pest_1 <- strsplit(pest_txt[2], "\t")[[1]][field_index_parent]
expect_equal(test_1, pest_1) # Parent fields
# Dummy 2
test_2 <- strsplit(test_txt[3], "\t")[[1]][field_index_parent]
pest_2 <- strsplit(pest_txt[3], "\t")[[1]][field_index_parent]
expect_equal(test_2, pest_2) # Parent fields
# Dummy 4
test_4 <- strsplit(test_txt[5], "\t")[[1]][field_index_parent]
pest_4 <- strsplit(pest_txt[4], "\t")[[1]][field_index_parent]
expect_equal(test_4, pest_4) # Parent fields
# Dummy 5
test_5 <- strsplit(test_txt[6], "\t")[[1]][field_index_parent]
pest_5 <- strsplit(pest_txt[5], "\t")[[1]][field_index_parent]
expect_equal(test_5, pest_5) # Parent fields
# Dummy 7
test_7 <- strsplit(test_txt[9], "\t")[[1]][field_index_parent]
pest_7 <- strsplit(pest_txt[6], "\t")[[1]][field_index_parent]
expect_equal(test_7, pest_7) # Parent fields
# New Dummy / M1
test_m1 <- strsplit(test_txt[10], "\t")[[1]][field_index_mets]
pest_m1 <- strsplit(pest_txt[7], "\t")[[1]][field_index_mets]
expect_equal(test_m1, pest_m1) # All fields except ai and met names
# New Dummy / M2
test_m2 <- strsplit(test_txt[11], "\t")[[1]][field_index_mets]
pest_m2 <- strsplit(pest_txt[8], "\t")[[1]][field_index_mets]
expect_equal(test_m2, pest_m2) # All fields except ai and met names
})
unlink("pesticide.txt")
# vim: set foldmethod=marker: {{{
|