-
Notifications
You must be signed in to change notification settings - Fork 0
/
ASTM_RTcorrection_withF001A.R
103 lines (83 loc) · 4.5 KB
/
ASTM_RTcorrection_withF001A.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
# Cross check ASTM with F00187, F00187-2, F00187-3
library(dplyr)
library(stringr)
library(readxl)
library(purrr)
library(plotly)
file_list <- list.files(path = "C:/Users/huyng/OneDrive - Toronto Metropolitan University/Huy Nguyen/PhD_EnSciMan_Ryerson_University/Arson project/Rproject/data",
pattern = '*.xlsx')
# Pipe operator for isolating IL types
F001A_file_list <- file_list %>%
.[!str_ends(., "check.xlsx")] %>%
.[!str_detect(., "grouping_compounds")] %>%
.[!str_detect(., "Station")] %>%
.[!str_detect(., "Workflow")] %>%
.[!str_detect(., "ASTM")] %>%
.[!str_detect(., "data_table")] %>%
.[str_detect(., "F00187")]
# Import IL samples to list
F001A_1 <- read_xlsx(path = "C:/Users/huyng/OneDrive - Toronto Metropolitan University/Huy Nguyen/PhD_EnSciMan_Ryerson_University/Arson project/Rproject/data/0220F00187-2.xlsx",
sheet = "Results")
F001A_2 <- read_xlsx(path = "C:/Users/huyng/OneDrive - Toronto Metropolitan University/Huy Nguyen/PhD_EnSciMan_Ryerson_University/Arson project/Rproject/data/0220F00187-2.xlsx",
sheet = "Results")
F001A_3 <- read_xlsx(path = "C:/Users/huyng/OneDrive - Toronto Metropolitan University/Huy Nguyen/PhD_EnSciMan_Ryerson_University/Arson project/Rproject/data/0220F00187-2.xlsx",
sheet = "Results")
F001A <- list(F001A_1, F001A_2, F001A_3)
# purrr::map(F001A_file_list,
# read_xlsx,
# path = "C:/Users/huyng/OneDrive - Toronto Metropolitan University/Huy Nguyen/PhD_EnSciMan_Ryerson_University/Arson project/Rproject/data",
# sheet = "Results")
# df_step1.1 <- dplyr::bind_rows(df_list_step1.1)
# remove spaces in column names in df_list_step1.1
for (i in 1:length(F001A)) {
colnames(F001A[[i]]) <- gsub(" ", "", colnames(F001A[[i]]))
}
step2 <- purrr::map(F001A, filtering, filter_list = c("^Carbon disulfide$",
"Cyclotrisiloxane..hexamethyl",
"Cyclotetrasiloxane..octamethyl",
"^Benzene$",
"^Toluene$",
"^Ethylbenzene$",
"Xylene"))
list_remaining_area <- limit_obser(step2, ILR_file_list, cap = 50000)[[1]]
step3 <- bind_rows(list_remaining_area)
step4 <- grouping_comp_ver1(step3,
rt1thres = 0.2,
rt2thres = 0.125,
ion1thres = 0.05, # Ion 1 and 2 indicates molecular structure (2 most prevalent mass-to-charge)
ion2thres = 0.05)
# ASTM compound list
ASTM_list <- read_xlsx(paste0("C:/Users/huyng/OneDrive - Toronto Metropolitan University/Huy Nguyen/PhD_EnSciMan_Ryerson_University/Arson project/Rproject/data",
"/ASTM Compound List.xlsx"), sheet = "Sheet1") %>%
arrange(RT1, RT2)
# Subset ASTM in light & mid range ----------------------
ASTM_light <- ASTM_list[, 1:5] %>%
filter(., (RT1 < 20 & RT1 > 8 & RT2 < 4.4 & RT2 > 3.4))
ASTM_mid <- ASTM_list[, 1:5] %>%
filter(., (RT1 < 30 & RT1 > 23 & RT2 < 5.4 & RT2 > 3.5))
ASTM_light_mid <- rbind(ASTM_light, ASTM_mid)
# Firstly, Visual estimation of how much adjustment needed prior to the adjustment
plotly::ggplotly(ggplot(data = step4,
aes(x=RT1, y= RT2)) +
geom_point(pch = 1, size = 0.5) +
geom_point(data = ASTM_light_mid, pch = 4,
aes(x=RT1, y= RT2,
colour = "ASTM",
label = Compound)))
# Adjusting ASTM Retention Time indices after initial visual estimation
ASTM_light_mid_F001A_aligned <- ASTM_light_mid %>%
mutate(RT1_aligned = RT1 - 0.045) %>%
mutate(RT2_aligned = RT2 - 0.145)
ASTM_list_aligned <- ASTM_list %>%
filter(., RT1 < 36) %>%
mutate(RT1_aligned = RT1 - 0.045) %>%
mutate(RT2_aligned = RT2 - 0.145)
# Visual inspection of the adjustment
plotly::ggplotly(ggplot(data = step4,
aes(x=RT1, y= RT2)) +
geom_point(pch = 1, size = 0.75) +
geom_point(data = ASTM_list_aligned, pch = 4,
size = 1.75,
aes(x=RT1_aligned, y= RT2_aligned,
colour = "ASTM",
label = Compound)))