R_NN_Model_Hake_Scripts/Read OPUS Hake 2019 Spectra into R.R
In John-R-Wallace-NOAA/FishNIRS: NIRS on fish structures.
# Install some utility functions and the plotly.Spec() plotting function from GitHub
sourceFunctionURL <- function (URL) {
" # For more functionality, see gitAFile() in the rgit package ( https://github.com/John-R-Wallace-NOAA/rgit ) which includes gitPush() and git() "
require(httr)
File.ASCII <- tempfile()
on.exit(file.remove(File.ASCII))
getTMP <- httr::GET(URL)
write(paste(readLines(textConnection(httr::content(getTMP))), collapse = "\n"), File.ASCII)
source(File.ASCII)}
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/JRWToolBox/master/R/lib.R")
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/JRWToolBox/master/R/get.subs.R")
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/JRWToolBox/master/R/strSplit.R")
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/FishNIRS/master/R/plotly.Spec.R")
# Create a list of all spectral files
PATH <- "W:/ALL_USR/JRW/SIDT/Hake Data 2019/Original"
setwd(PATH) # set working directory to folder containing spectral files
getwd()
(listspc <- dir(pattern = '*HAKE*'))[1:20] # creates the list of all the .001 file names in the directory
length(listspc) # 2340
## ================ Old way to read in spectra =================================
# # lib("philipp-baumann/simplerspec") # https://github.com/philipp-baumann/simplerspec
# lib(simplerspec)
# ldf <- list() # creates an empty list
# for (k in 1:length(listspc[1:5])) { # loops through and uploads each file using read_opus_bin_univ() from the simplerspec package
# test_spec <- simplerspec::read_opus_bin_univ(listspc[k], extract = "spc", print_progress = TRUE, atm_comp_minus4offset = FALSE)
# if(any(grepl('Error', test_spec[[1]])))
# next
# ldf[[as.character(k)]] <- test_spec
# }
#
# (N <- length(ldf)) # 2848
#
# names(ldf[[1]]) # Names of first element
# ## [1] "metadata" "spc" "spc_nocomp" "sc_sm" "sc_rf" "ig_sm" "ig_rf" "wavenumbers"
# ## [9] "wavenumbers_sc_sm" "wavenumbers_sc_rf"
#
#
# str(ldf[[1]]) # check first element
#
# ldf[[1]]$wavenumbers[1:20] # 8th Element
#
# ldf[[2848]]$wavenumbers[1:20] # 8th Element
#
# len(ldf[[1]]$wavenumbers)
# len(ldf[[2848]]$wavenumbers)
#
# save(ldf, file = 'ldf.RData')
#
# # Interpolate
# # prospectr::resample() uses spline interpolation method
# testdf <- (prospectr::resample(X = ldf[[1]][[2]], wav = ldf[[1]][[8]], new.wav = ldf[[N]][[8]]))
#
# # plot to test
# plot(as.vector(ldf[[1]]$wavenumbers), as.vector(ldf[[2]]$spc))
# points(as.vector(ldf[[N]]$wavenumbers), as.vector(testdf), col = 'green')
# (filenames <- unlist(sapply(ldf, function(x) x[[1]][2]), use.names = FALSE))[1:10]
# (dat <- cbind(filenames, dat_spc))[1:5, c(1:5, 1110:1113)]
# ================== New way to read in spectra with opusreader::opus_read() ========================================
lib("pierreroudier/opusreader") # https://github.com/pierreroudier/opusreader
# < simplerspec::read_opus_bin_univ > does not have the "spec_no_atm_comp" option
# Character vector of spectra types to extract from OPUS binary file. Default is "spec", which will extract the final spectra, e.g. expressed in absorbance
# (named AB in Bruker OPUS programs). Possible additional values for the character vector supplied to type are "spec_no_atm_comp"
# (spectrum of the sample without compensation for atmospheric gases, water vapor and/or carbon dioxide), "sc_sample" (single channel spectrum of the sample measurement),
# "sc_ref" (single channel spectrum of the reference measurement), "ig_sample" (interferogram of the sample measurement) and "ig_ref" (interferogram of the reference measurement).
test_spec <- opusreader::opus_read(listspc[1222])
test_spec_no_comp <- opusreader::opus_read(listspc[1222], type = "spec_no_atm_comp")
# temp_sc_sample <- opusreader::opus_read(listspc[1222], type = "sc_sample") # No 'sc_sample' spectra found
# temp_sc_ref <- opusreader::opus_read(listspc[1222], type = "sc_ref") # No 'sc_ref' spectra found
test_spec_ig_ref <- opusreader::opus_read(listspc[1222], type = "ig_ref")
test_spec_ig_sample <- opusreader::opus_read(listspc[1222], type = "ig_sample")
data.frame(t(test_spec$metadata))
t.test_spec.metadata.
unique_id C STD XPP _2021-03-11 14:33:13
sample_id C STD XPP
date_time_sm 2021-03-11 14:33:13
date_time_rf 2021-03-11 13:44:01
sample_name C STD XPP
instr_name_range MPA-High Intensity NIR
resolution_wn 4
result_spc AB
beamspl 1906206D_1253_OT1
laser_wn 15799.35
spc_in_file ig_sample;ig_ref;spec_no_atm_comp;spec
zero_filling 2
temp_scanner_sm 37.1
temp_scanner_rf 37
hum_rel_sm 40
hum_rel_rf <NA>
hum_abs_sm <NA>
hum_abs_rf <NA>
gof()
par(mfrow = c(2,2))
plot(test_spec$wavenumbers, test_spec$spec, type = 'l', col = 'green', xlab = 'Wave Numbers', ylab = 'Absorbance', main = 'Final Spectra')
plot(test_spec_no_comp$wavenumbers, test_spec_no_comp$spec_no_atm_comp, type = 'l', col = 'red', xlab = 'Wave Numbers', ylab = 'Absorbance', main = 'No compensation for atmos. gas, water vapor, and/or CO2')
y_range <- range(c(test_spec_ig_ref$ig_ref, test_spec_ig_sample$ig_sample)) + c(-0.05, 0.05)
plot(1:len(test_spec_ig_ref$ig_ref), test_spec_ig_ref$ig_ref, type = 'l', col = 'blue', ylim = y_range, xlab = 'Time', ylab = 'Intensity (V)', main = 'Interferogram of the Reference Measurement')
plot(1:len(test_spec_ig_sample$ig_sample), test_spec_ig_sample$ig_sample, type = 'l', col = 'magenta', ylim = y_range, xlab = 'Time', ylab = 'Intensity (V)', main = 'Interferogram of the Sample Measurement')
# plot(test_spec$ig_ref, test_spec$ig_sample, type = 'l', col = 'blue')
# Wave length differences are not all equal in the first scans, but are by the end. opusreader::opus_read() with simlify = TRUE uses the very first file passed as a reference for linear interpolation.
# So need to put the last scan first temporarily and remove 2 other scans with bad numbers.
test_spec_1 <- opusreader::opus_read(listspc[1])
Table(diff(test_spec_1$wavenumbers))
-7.71452447070442 -7.71452447070351 -7.71452447070305 -7.7145244707026
190 259 55 649
test_spec_2340 <- opusreader::opus_read(listspc[2340])
Table(diff(test_spec_2340$wavenumbers))
-8
1111
ldf <- opusreader::opus_read(listspc[c(2340, 1:914, 916:1207, 1209:2339)], simplify = TRUE) # Last first temporarily and 915 and 1208 have bad numbers
# save(ldf, file = 'ldf using opusread, 30 Aug 2023.RData')
dat <- data.frame(c(listspc[c(2340, 1:914, 916:1207, 1209:2339)]), ldf[[2]])
names(dat) <- c('filenames', round(ldf[[1]]))
dat <- dat[c(2:2338, 1), ] # Switch back to order the oties where scanned in.
dat[1:5, c(1:5, 1150:1155)]
Table(diff(as.numeric(names(dat)[-1])))
-8
1111
# Compare to Morgan's data (which has metadata at the end (see below for adding meta data to 'dat')
base::load('hake_all_2019.8.10 ORG, from Morgans csv File.RData') # hake_all_2019.8.10
hake_all_2019.8.10[1:5, c(1:5, 1110:1113)]
Table(diff(as.numeric(names(hake_all_2019.8.10)[2:1113])))
-8
1111
sum(as.numeric(names(dat)[-1]) - as.numeric(names(hake_all_2019.8.10)[2:1113]))
[1] 0
save(dat, file = 'dat 30 Aug 2023.RData')
base::load(file = 'dat 30 Aug 2023.RData') # If needed
# =============================================================
# ADD VESSEL, CRUISE, REGION, LOCATION, AND BIO METADATA
scan_data <- read.csv(paste0(PATH, "hake_scandata_2019.csv"), strip.white = TRUE) #load in ancillary data
(int_data <- left_join(dat, scan_data, by = "filenames"))[1:5, c(1:3, 1112:1120, 1135:(ncol(dat) + ncol(scan_data) - 1))]
# ADD AGE DATA
age_data <- read.csv(paste0(PATH, "hake_agedata_2019.csv"), strip.white = TRUE) #load in age data
(int2_data <- left_join(int_data, age_data, by = "sequence"))[1:5, c(1:3, 1112:1120, 1135:(ncol(int_data) + ncol(age_data) - 1))]
# ADD HAUL METADATA
haul_data <- read.csv(paste0(PATH, "hake_haulmetadata_2019.csv"))
(all_data <- left_join(int2_data, haul_data, by = "Barcode"))[1:5, c(1:3, 1112:1120, 1135:(ncol(int2_data) + ncol(haul_data) - 1))]
hake_all_2019.6.20 <- all_data
hake_all_2019.6.20$Group <- substr(hake_all_2019.6.20$filenames, 26, 26)
hake_all_2019.6.20$GroupNum <- as.numeric(factor(hake_all_2019.6.20$Group))
hake_all_2019.6.20$shortName <- apply(hake_all_2019.6.20[, 'filenames', drop = FALSE], 1, function(x) paste(get.subs(x, sep = "_")[c(2,4)], collapse = "_"))
hake_all_2019.6.20$ID <- as.numeric(strSplit(hake_all_2019.6.20$shortName, "_", elements = 2))
hake_all_2019.6.20 <- sort.f(hake_all_2019.6.20, "ID")
save(hake_all_2019.6.20, file = "hake_all_2019.6.20 6 Oct 2022.RData")
# ========================== Look at the data and plot it =========================================================
base::load(file = "hake_all_2019.6.20 6 Oct 2022.RData") # If needed
# hake_all_2019.6.20[1:5, c(1:3, 1112:1120, 1135:(ncol(int2_data) + ncol(haul_data) - 1))]
hake_all_2019.6.20[1:5, c(1:3, 1112:1120, 1159:ncol(hake_all_2019.6.20))]
dim(hake_all_2019.6.20)
[1] 2849 1158
len(!duplicated(hake_all_2019.6.20$Barcode))
[1] 2849
names(hake_all_2019.6.20[, 2:1114]) # Check end of wavelengths
(WaveLengths <- as.numeric(names(hake_all_2019.6.20[, 2:1113])))
len(WaveLengths)
# Plot by group
Cols <- rainbow(7)
dev.new()
pie(rep(1, length(Cols)), col = Cols)
N <- 400 # Number in random sample
dev.new(height = 8, width = 14)
plot(WaveLengths, hake_all_2019.6.20[1, 2:1113], type = 'l', ylab = 'Reflectance', col = 'black',
ylim = c(floor(min(hake_all_2019.6.20[, 2:1113])*100)/100, ceiling(max(hake_all_2019.6.20[, 2:1113])*100)/100))
for (i in sample(2:nrow(hake_all_2019.6.20), N)) {
lines(WaveLengths, hake_all_2019.6.20[i, 2:1113], col = Cols[hake_all_2019.6.20$GroupNum[i]])
# cat(paste0('Row = ', i, "\n"))
# ask()
}
names(hake_all_2019.6.20)[-(2:1113)]
[1] "filenames" "vessel_code" "cruise_number" "date_collected" "collection_year" "region" "latitude"
[8] "longitude" "sequence" "length" "weight" "sex" "read_age" "test_age"
[15] "final_age" "readability" "unscannable" "broken" "crystallized" "other_problem" "percent_affected"
[22] "instrument_name" "comments" "misc_data" "gear_depth" "bottom_depth" "Cruise" "Barcode"
[29] "Age" "Species" "SampleYear" "Oto_Weight" "OtolithSide" "Processed.by" "Shipped.Date"
[36] "CatchDate" "sex_determination" "fork_length" "Notes" "Survey" "Haul" "TD_Time"
[43] "TD_Lat" "TD_Lon" "Avg_Bot_Depth_m" "Avg_Gear_Depth_m" "Group" "GroupNum" "Age_BB"
[50] "Age_OPUS"
Table(hake_all_2019.6.20$Age, hake_all_2019.6.20$Group)
# Some of the 'A' group have shifted signature in the reflectance
plotly.Spec(hake_all_2019.6.20, 200, 'Group')
# Remove all of group A for now...
# hake_all_2019.6.20 <- hake_all_2019.6.20[!hake_all_2019.6.20$Group == 'A', ]
# Table(hake_all_2019.6.20$Group) # Check all the 'A' group was removed
plotly.Spec(hake_all_2019.6.20, 50)
plotly.Spec(hake_all_2019.6.20, 150)
plotly.Spec(hake_all_2019.6.20, 500)
plotly.Spec(hake_all_2019.6.20, 40, 'Sex')
plotly.Spec(hake_all_2019.6.20, 200, 'fork_length')
John-R-Wallace-NOAA/FishNIRS documentation built on April 12, 2025, 12:59 a.m.
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# Install some utility functions and the plotly.Spec() plotting function from GitHub
sourceFunctionURL <- function (URL) {
" # For more functionality, see gitAFile() in the rgit package ( https://github.com/John-R-Wallace-NOAA/rgit ) which includes gitPush() and git() "
require(httr)
File.ASCII <- tempfile()
on.exit(file.remove(File.ASCII))
getTMP <- httr::GET(URL)
write(paste(readLines(textConnection(httr::content(getTMP))), collapse = "\n"), File.ASCII)
source(File.ASCII)}
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/JRWToolBox/master/R/lib.R")
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/JRWToolBox/master/R/get.subs.R")
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/JRWToolBox/master/R/strSplit.R")
sourceFunctionURL("https://raw.githubusercontent.com/John-R-Wallace-NOAA/FishNIRS/master/R/plotly.Spec.R")
# Create a list of all spectral files
PATH <- "W:/ALL_USR/JRW/SIDT/Hake Data 2019/Original"
setwd(PATH) # set working directory to folder containing spectral files
getwd()
(listspc <- dir(pattern = '*HAKE*'))[1:20] # creates the list of all the .001 file names in the directory
length(listspc) # 2340
## ================ Old way to read in spectra =================================
# # lib("philipp-baumann/simplerspec") # https://github.com/philipp-baumann/simplerspec
# lib(simplerspec)
# ldf <- list() # creates an empty list
# for (k in 1:length(listspc[1:5])) { # loops through and uploads each file using read_opus_bin_univ() from the simplerspec package
# test_spec <- simplerspec::read_opus_bin_univ(listspc[k], extract = "spc", print_progress = TRUE, atm_comp_minus4offset = FALSE)
# if(any(grepl('Error', test_spec[[1]])))
# next
# ldf[[as.character(k)]] <- test_spec
# }
#
# (N <- length(ldf)) # 2848
#
# names(ldf[[1]]) # Names of first element
# ## [1] "metadata" "spc" "spc_nocomp" "sc_sm" "sc_rf" "ig_sm" "ig_rf" "wavenumbers"
# ## [9] "wavenumbers_sc_sm" "wavenumbers_sc_rf"
#
#
# str(ldf[[1]]) # check first element
#
# ldf[[1]]$wavenumbers[1:20] # 8th Element
#
# ldf[[2848]]$wavenumbers[1:20] # 8th Element
#
# len(ldf[[1]]$wavenumbers)
# len(ldf[[2848]]$wavenumbers)
#
# save(ldf, file = 'ldf.RData')
#
# # Interpolate
# # prospectr::resample() uses spline interpolation method
# testdf <- (prospectr::resample(X = ldf[[1]][[2]], wav = ldf[[1]][[8]], new.wav = ldf[[N]][[8]]))
#
# # plot to test
# plot(as.vector(ldf[[1]]$wavenumbers), as.vector(ldf[[2]]$spc))
# points(as.vector(ldf[[N]]$wavenumbers), as.vector(testdf), col = 'green')
# (filenames <- unlist(sapply(ldf, function(x) x[[1]][2]), use.names = FALSE))[1:10]
# (dat <- cbind(filenames, dat_spc))[1:5, c(1:5, 1110:1113)]
# ================== New way to read in spectra with opusreader::opus_read() ========================================
lib("pierreroudier/opusreader") # https://github.com/pierreroudier/opusreader
# < simplerspec::read_opus_bin_univ > does not have the "spec_no_atm_comp" option
# Character vector of spectra types to extract from OPUS binary file. Default is "spec", which will extract the final spectra, e.g. expressed in absorbance
# (named AB in Bruker OPUS programs). Possible additional values for the character vector supplied to type are "spec_no_atm_comp"
# (spectrum of the sample without compensation for atmospheric gases, water vapor and/or carbon dioxide), "sc_sample" (single channel spectrum of the sample measurement),
# "sc_ref" (single channel spectrum of the reference measurement), "ig_sample" (interferogram of the sample measurement) and "ig_ref" (interferogram of the reference measurement).
test_spec <- opusreader::opus_read(listspc[1222])
test_spec_no_comp <- opusreader::opus_read(listspc[1222], type = "spec_no_atm_comp")
# temp_sc_sample <- opusreader::opus_read(listspc[1222], type = "sc_sample") # No 'sc_sample' spectra found
# temp_sc_ref <- opusreader::opus_read(listspc[1222], type = "sc_ref") # No 'sc_ref' spectra found
test_spec_ig_ref <- opusreader::opus_read(listspc[1222], type = "ig_ref")
test_spec_ig_sample <- opusreader::opus_read(listspc[1222], type = "ig_sample")
data.frame(t(test_spec$metadata))
t.test_spec.metadata.
unique_id C STD XPP _2021-03-11 14:33:13
sample_id C STD XPP
date_time_sm 2021-03-11 14:33:13
date_time_rf 2021-03-11 13:44:01
sample_name C STD XPP
instr_name_range MPA-High Intensity NIR
resolution_wn 4
result_spc AB
beamspl 1906206D_1253_OT1
laser_wn 15799.35
spc_in_file ig_sample;ig_ref;spec_no_atm_comp;spec
zero_filling 2
temp_scanner_sm 37.1
temp_scanner_rf 37
hum_rel_sm 40
hum_rel_rf <NA>
hum_abs_sm <NA>
hum_abs_rf <NA>
gof()
par(mfrow = c(2,2))
plot(test_spec$wavenumbers, test_spec$spec, type = 'l', col = 'green', xlab = 'Wave Numbers', ylab = 'Absorbance', main = 'Final Spectra')
plot(test_spec_no_comp$wavenumbers, test_spec_no_comp$spec_no_atm_comp, type = 'l', col = 'red', xlab = 'Wave Numbers', ylab = 'Absorbance', main = 'No compensation for atmos. gas, water vapor, and/or CO2')
y_range <- range(c(test_spec_ig_ref$ig_ref, test_spec_ig_sample$ig_sample)) + c(-0.05, 0.05)
plot(1:len(test_spec_ig_ref$ig_ref), test_spec_ig_ref$ig_ref, type = 'l', col = 'blue', ylim = y_range, xlab = 'Time', ylab = 'Intensity (V)', main = 'Interferogram of the Reference Measurement')
plot(1:len(test_spec_ig_sample$ig_sample), test_spec_ig_sample$ig_sample, type = 'l', col = 'magenta', ylim = y_range, xlab = 'Time', ylab = 'Intensity (V)', main = 'Interferogram of the Sample Measurement')
# plot(test_spec$ig_ref, test_spec$ig_sample, type = 'l', col = 'blue')
# Wave length differences are not all equal in the first scans, but are by the end. opusreader::opus_read() with simlify = TRUE uses the very first file passed as a reference for linear interpolation.
# So need to put the last scan first temporarily and remove 2 other scans with bad numbers.
test_spec_1 <- opusreader::opus_read(listspc[1])
Table(diff(test_spec_1$wavenumbers))
-7.71452447070442 -7.71452447070351 -7.71452447070305 -7.7145244707026
190 259 55 649
test_spec_2340 <- opusreader::opus_read(listspc[2340])
Table(diff(test_spec_2340$wavenumbers))
-8
1111
ldf <- opusreader::opus_read(listspc[c(2340, 1:914, 916:1207, 1209:2339)], simplify = TRUE) # Last first temporarily and 915 and 1208 have bad numbers
# save(ldf, file = 'ldf using opusread, 30 Aug 2023.RData')
dat <- data.frame(c(listspc[c(2340, 1:914, 916:1207, 1209:2339)]), ldf[[2]])
names(dat) <- c('filenames', round(ldf[[1]]))
dat <- dat[c(2:2338, 1), ] # Switch back to order the oties where scanned in.
dat[1:5, c(1:5, 1150:1155)]
Table(diff(as.numeric(names(dat)[-1])))
-8
1111
# Compare to Morgan's data (which has metadata at the end (see below for adding meta data to 'dat')
base::load('hake_all_2019.8.10 ORG, from Morgans csv File.RData') # hake_all_2019.8.10
hake_all_2019.8.10[1:5, c(1:5, 1110:1113)]
Table(diff(as.numeric(names(hake_all_2019.8.10)[2:1113])))
-8
1111
sum(as.numeric(names(dat)[-1]) - as.numeric(names(hake_all_2019.8.10)[2:1113]))
[1] 0
save(dat, file = 'dat 30 Aug 2023.RData')
base::load(file = 'dat 30 Aug 2023.RData') # If needed
# =============================================================
# ADD VESSEL, CRUISE, REGION, LOCATION, AND BIO METADATA
scan_data <- read.csv(paste0(PATH, "hake_scandata_2019.csv"), strip.white = TRUE) #load in ancillary data
(int_data <- left_join(dat, scan_data, by = "filenames"))[1:5, c(1:3, 1112:1120, 1135:(ncol(dat) + ncol(scan_data) - 1))]
# ADD AGE DATA
age_data <- read.csv(paste0(PATH, "hake_agedata_2019.csv"), strip.white = TRUE) #load in age data
(int2_data <- left_join(int_data, age_data, by = "sequence"))[1:5, c(1:3, 1112:1120, 1135:(ncol(int_data) + ncol(age_data) - 1))]
# ADD HAUL METADATA
haul_data <- read.csv(paste0(PATH, "hake_haulmetadata_2019.csv"))
(all_data <- left_join(int2_data, haul_data, by = "Barcode"))[1:5, c(1:3, 1112:1120, 1135:(ncol(int2_data) + ncol(haul_data) - 1))]
hake_all_2019.6.20 <- all_data
hake_all_2019.6.20$Group <- substr(hake_all_2019.6.20$filenames, 26, 26)
hake_all_2019.6.20$GroupNum <- as.numeric(factor(hake_all_2019.6.20$Group))
hake_all_2019.6.20$shortName <- apply(hake_all_2019.6.20[, 'filenames', drop = FALSE], 1, function(x) paste(get.subs(x, sep = "_")[c(2,4)], collapse = "_"))
hake_all_2019.6.20$ID <- as.numeric(strSplit(hake_all_2019.6.20$shortName, "_", elements = 2))
hake_all_2019.6.20 <- sort.f(hake_all_2019.6.20, "ID")
save(hake_all_2019.6.20, file = "hake_all_2019.6.20 6 Oct 2022.RData")
# ========================== Look at the data and plot it =========================================================
base::load(file = "hake_all_2019.6.20 6 Oct 2022.RData") # If needed
# hake_all_2019.6.20[1:5, c(1:3, 1112:1120, 1135:(ncol(int2_data) + ncol(haul_data) - 1))]
hake_all_2019.6.20[1:5, c(1:3, 1112:1120, 1159:ncol(hake_all_2019.6.20))]
dim(hake_all_2019.6.20)
[1] 2849 1158
len(!duplicated(hake_all_2019.6.20$Barcode))
[1] 2849
names(hake_all_2019.6.20[, 2:1114]) # Check end of wavelengths
(WaveLengths <- as.numeric(names(hake_all_2019.6.20[, 2:1113])))
len(WaveLengths)
# Plot by group
Cols <- rainbow(7)
dev.new()
pie(rep(1, length(Cols)), col = Cols)
N <- 400 # Number in random sample
dev.new(height = 8, width = 14)
plot(WaveLengths, hake_all_2019.6.20[1, 2:1113], type = 'l', ylab = 'Reflectance', col = 'black',
ylim = c(floor(min(hake_all_2019.6.20[, 2:1113])*100)/100, ceiling(max(hake_all_2019.6.20[, 2:1113])*100)/100))
for (i in sample(2:nrow(hake_all_2019.6.20), N)) {
lines(WaveLengths, hake_all_2019.6.20[i, 2:1113], col = Cols[hake_all_2019.6.20$GroupNum[i]])
# cat(paste0('Row = ', i, "\n"))
# ask()
}
names(hake_all_2019.6.20)[-(2:1113)]
[1] "filenames" "vessel_code" "cruise_number" "date_collected" "collection_year" "region" "latitude"
[8] "longitude" "sequence" "length" "weight" "sex" "read_age" "test_age"
[15] "final_age" "readability" "unscannable" "broken" "crystallized" "other_problem" "percent_affected"
[22] "instrument_name" "comments" "misc_data" "gear_depth" "bottom_depth" "Cruise" "Barcode"
[29] "Age" "Species" "SampleYear" "Oto_Weight" "OtolithSide" "Processed.by" "Shipped.Date"
[36] "CatchDate" "sex_determination" "fork_length" "Notes" "Survey" "Haul" "TD_Time"
[43] "TD_Lat" "TD_Lon" "Avg_Bot_Depth_m" "Avg_Gear_Depth_m" "Group" "GroupNum" "Age_BB"
[50] "Age_OPUS"
Table(hake_all_2019.6.20$Age, hake_all_2019.6.20$Group)
# Some of the 'A' group have shifted signature in the reflectance
plotly.Spec(hake_all_2019.6.20, 200, 'Group')
# Remove all of group A for now...
# hake_all_2019.6.20 <- hake_all_2019.6.20[!hake_all_2019.6.20$Group == 'A', ]
# Table(hake_all_2019.6.20$Group) # Check all the 'A' group was removed
plotly.Spec(hake_all_2019.6.20, 50)
plotly.Spec(hake_all_2019.6.20, 150)
plotly.Spec(hake_all_2019.6.20, 500)
plotly.Spec(hake_all_2019.6.20, 40, 'Sex')
plotly.Spec(hake_all_2019.6.20, 200, 'fork_length')
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