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eBirdColumnStrip.R
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eBirdColumnStrip.R
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#############################################################################
##### FUNCTION TO READ SPECIFIC COLUMNS IN THE LARGE EBD DATA SET ##########
##### NEED AWK INSTALLED IN YOUR COMPUTER TO RUN ##########
#############################################################################
#############################################################################
# FUNCTION: readEbdColumns ###
# PARAMETER : ebd_file_name: Name of the ebd file without .zip ###
# PARAMETER : ebd_file_location: Absolute/Relative directory of the file ###
# USAGE: readEbdColumns ('ebd_IN_relMay-2018', '..\\..\\data\\') ###
#############################################################################
library(bigmemory)
# Make Test = 1 for testing
Test <- 0
readEbdColumns <- function (ebd_file_name, ebd_file_location)
{
filter_str <- '{print '
#####################COLUMN CONFIGURATIONS######################
# Uncomment the fields that should be retained in the final ebd dataset
# filter_str <- paste(filter_str, '$01\\"\\t\\"', sep='') #GLOBAL_UNIQUE_IDENTIFIER
# filter_str <- paste(filter_str, '$02\\"\\t\\"', sep='') #LAST EDITED DATE
filter_str <- paste(filter_str, '$03\\"\\t\\"', sep='') #TAXONOMIC ORDER
filter_str <- paste(filter_str, '$04\\"\\t\\"', sep='') #CATEGORY
filter_str <- paste(filter_str, '$05\\"\\t\\"', sep='') #COMMON NAME
# filter_str <- paste(filter_str, '$06\\"\\t\\"', sep='') #SCIENTIFIC NAME
filter_str <- paste(filter_str, '$07\\"\\t\\"', sep='') #SUBSPECIES COMMON NAME
# filter_str <- paste(filter_str, '$08\\"\\t\\"', sep='') #SUBSPECIES SCIENTIFIC NAME
filter_str <- paste(filter_str, '$09\\"\\t\\"', sep='') #OBSERVATION COUNT
# filter_str <- paste(filter_str, '$10\\"\\t\\"', sep='') #BREEDING CODE
# filter_str <- paste(filter_str, '$11\\"\\t\\"', sep='') #BREEDING CATEGORY
# filter_str <- paste(filter_str, '$12\\"\\t\\"', sep='') #BEHAVIOUR CODE
# filter_str <- paste(filter_str, '$13\\"\\t\\"', sep='') #AGE/SEX
# filter_str <- paste(filter_str, '$14\\"\\t\\"', sep='') #COUNTRY
# filter_str <- paste(filter_str, '$15\\"\\t\\"', sep='') #COUNTRY CODE
filter_str <- paste(filter_str, '$16\\"\\t\\"', sep='') #STATE
filter_str <- paste(filter_str, '$17\\"\\t\\"', sep='') #STATE CODE
filter_str <- paste(filter_str, '$18\\"\\t\\"', sep='') #COUNTY
filter_str <- paste(filter_str, '$19\\"\\t\\"', sep='') #COUNTY CODE
# filter_str <- paste(filter_str, '$20\\"\\t\\"', sep='') #IBA CODE
# filter_str <- paste(filter_str, '$21\\"\\t\\"', sep='') #BCR CODE
# filter_str <- paste(filter_str, '$22\\"\\t\\"', sep='') #USFWS CODE
# filter_str <- paste(filter_str, '$23\\"\\t\\"', sep='') #ATLAS BLOCK
# filter_str <- paste(filter_str, '$24\\"\\t\\"', sep='') #LOCALITY
# filter_str <- paste(filter_str, '$25\\"\\t\\"', sep='') #LOCALITY ID
# filter_str <- paste(filter_str, '$26\\"\\t\\"', sep='') #LOCALITY TYPE
filter_str <- paste(filter_str, '$27\\"\\t\\"', sep='') #LATITUDE
filter_str <- paste(filter_str, '$28\\"\\t\\"', sep='') #LONGITUDE
filter_str <- paste(filter_str, '$29\\"\\t\\"', sep='') #OBSERVATION DATE
# filter_str <- paste(filter_str, '$30\\"\\t\\"', sep='') #TIME OBSERVATIONS STARTED
# filter_str <- paste(filter_str, '$31\\"\\t\\"', sep='') #OBSERVER ID
filter_str <- paste(filter_str, '$32\\"\\t\\"', sep='') #SAMPLING EVENT IDENTIFIER
# filter_str <- paste(filter_str, '$33\\"\\t\\"', sep='') #PROTOCOL TYPE
# filter_str <- paste(filter_str, '$34\\"\\t\\"', sep='') #PROTOCOL CODE
# filter_str <- paste(filter_str, '$35\\"\\t\\"', sep='') #PROJECT CODE
filter_str <- paste(filter_str, '$36\\"\\t\\"', sep='') #DURATION MINUTES
# filter_str <- paste(filter_str, '$37\\"\\t\\"', sep='') #EFFORT DISTANCE KM
# filter_str <- paste(filter_str, '$38\\"\\t\\"', sep='') #EFFORT AREA HA
# filter_str <- paste(filter_str, '$39\\"\\t\\"', sep='') #NUMBER OBSERVERS
filter_str <- paste(filter_str, '$40\\"\\t\\"', sep='') #ALL SPECIES REPORTED
filter_str <- paste(filter_str, '$41\\"\\t\\"', sep='') #GROUP IDENTIFIER
#filter_str <- paste(filter_str, '$42\\"\\t\\"', sep='') #HAS MEDIA
# filter_str <- paste(filter_str, '$43\\"\\t\\"', sep='') #APPROVED
# filter_str <- paste(filter_str, '$44\\"\\t\\"', sep='') #REVIEWED
# filter_str <- paste(filter_str, '$45\\"\\t\\"', sep='') #REASON
# filter_str <- paste(filter_str, '$46\\"\\t\\"', sep='') #TRIP COMMENTS
# filter_str <- paste(filter_str, '$47\\"\\t\\"', sep='') #SPECIES COMMENTS
################################################################
# Remove terminal tab and add the closing braces
filter_str <- substr(filter_str,0, nchar(filter_str)-6)
filter_str <- paste(filter_str, ';}', sep='')
#Unzip and read eBird records. This assumes the file is stored in a top level folder called 'data'
print(paste("Unzipping file...",filter_str))
unzip(paste(ebd_file_location, ebd_file_name,'.zip',sep=''))
# unzip(paste(ebd_file_location, ebd_file_name,'.txt.gz',sep=''))
# Strip eBird file using an awk script as the file cant load fully in R due to excessive memory requirements
# The field that interest us are indicated by the column numbers in filter_str
awkscript <- paste('\"BEGIN {FS=\\"\\t\\"};',filter_str,'\"',sep='')
# Run the awk command and wait till the operation is completed
print(paste0("Stripping columns...",ebd_file_name))
ret <- system2 ("awk",
args = awkscript,
wait = TRUE, # Wait till awk completes,
stdin = paste0(ebd_file_name,".txt"),
stdout = 'ebd.tmp',
stderr = 'ebderr.tmp')
if(ret == 0)
{
# Read the stripped tmp file
print("Reading columns...")
# ebd <- read.big.matrix('ebd.tmp', sep = ',', type = character, header = TRUE)
ebd <- read.delim('ebd.tmp', na.strings = c("NA", "", "null"), as.is=TRUE, quote="")
# Remove the tmp file
# unlink('ebd.tmp')
}
else
{
# Read the stripped tmp file
print(paste("System awk failed...", ret))
}
return (ebd)
}
# Test Code
if(Test)
{
ebd <- readEbdColumns ('ebd_IN-KL_prv_relMay-2020', '..\\data\\')
print(names(ebd))
print(nrow(ebd))
print(head(ebd, 5))
}