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knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(filteRjsats)
# Choose a Directory path <- system.file("extdata", package = "filteRjsats") # List Files in Directory file <- list.files(path = path, recursive = TRUE)
# Get a list of Time Zones # Not Run # OlsonNames() # Set Time Zone timezone <- "America/Los_Angeles"
# Empty list to store dataframes det_list <- list() # Process each file in the list of files for(i in 1:length(file)){ jsats_file <- read_jsats(path, file[i]) det_list[[i]] <- jsats_file }
# Get a list of reference tags reference_tags <- get_reference_tags()
# Empty list to store dataframes pref_list <- list() # Apply prefilter for(i in 1:length(det_list)){ prefilter_file <- prefilter(det_list[[i]], reference_tags) pref_list[[i]] <- prefilter_file }
# View all the fish fields get_fish_fields() # NOT RUN # Choose important fields if don't want all fields, shown are the minimum # important_fields <- c("fish_type","tag_id_hex", # "fish_release_date", "release_location", # "release_latitude", "release_longitude", # "tag_pulse_rate_interval_nominal", # "tag_warranty_life", "fish_length_type", # "fish_length","fish_weight") # Query ERDAPP for all tagged fish fish <- get_tagged_fish()
# Empty list to store dataframes fish_list <- list() # Join fish data to detection and filter based on release date and battery for(i in 1:length(pref_list)){ fish_file <- add_fish(pref_list[[i]], fish) fish_list[[i]] <- fish_file }
# Empty list to store dataframes final_list <- list() # Apply the final 2 hit or 4 hit filter for(i in 1:length(fish_list)){ final_filter <- second_filter_2h4h(fish_list[[i]]) final_list[[i]] <- final_filter } # NOT RUN # Alternately apply a 4 hit filter # for(i in 1:length(fish_list)){ # final_filter <- second_filter_4h(fish_list[[i]]) # final_list[[i]] <- final_filter # }
# View all the receiver metadata fields get_rcvr_fields() # NOT RUN # # Choose important fields if don't want all fields, shown are the minimum # rcvr_fields <- c("dep_id","receiver_serial_number","latitude","longitude", # "receiver_location","receiver_river_km", # "receiver_general_location","receiver_general_river_km", # "receiver_beacon_id_hex", "receiver_start", # "receiver_end") #Get the receiver metadata rcvr_data <- get_rcvr_data() #Join the receiver metadata to the filtered detections for(i in 1:length(final_list)){ out <- join_rcvr_data(final_list[[i]], rcvr_data) final_list[[i]] } print(final_list[[1]]) print(final_list[[2]])
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