exinaceaLab-paxage: exinaceaLab

In stuartWagenius/echinaceaLab: useful functions for the Echinacea Project

exinaceaLab

Description

Functions to help manage and visualize Echinacea Project datasets.

Details

This package contains useful functions for the lab and in the field see examples for how to use the functions

Author(s)

Stuart Wagenius

Examples

#####################################################################
################# check scans and create upload csv #################
#####################################################################
## Not run: 
library(echinaceaLab)
library(plyr)

# this is the simple way of doing it ####
exps15 <- c("96_a", "99m", "99s", "inb1_a", "inb2_a", "2001", "inb2_b")
priority15 <- c(20, 30, 40, 50, 55, 60, 93)
expr <- data.frame(exps15, priority15)

writeUploadCSV("I:/Departments/Research/EchinaceaCG2015/cg2015scans",
               paste0("C:/Users/dhanson/Dropbox/CGData/165_count/count2015/",
                      "summer2016_prep/cg15ForSummer16.csv"), 2015, expr, "online")


# this is the longer, manual way of doing it ####
# check for missing scans ####
# create data frame with all scans found in "F:/cg2013scans" (on cgStorageA1)
loadScans("F:/cg2013scans")
# remove "extra" files, if present
scans <- scans[!(scans$filename %in% c("Thumbs.db", "itfiles.ini")),]
# folders that should be there but aren't
stillNeed <- setdiff(levels(hh.2013$batch), levels(scans$batch))
# folders that are there but shouldn't be
ignore <- setdiff(levels(scans$batch), levels(hh.2013$batch))
# check batch for all batches separately
batchecks <- aaply(levels(scans$batch), .margin = 1, .fun = check.batch, harvestFile=hh.2013)
batchecks <- cbind(batchecks, levels(scans$batch))
colnames(batchecks)[6] <- "batchName"
batchecks <- batchecks[,c(6,1,2,3,4,5)]

# rename writeTo to have date
writeTo <- "C:/Users/dhanson/Dropbox/CGData/155_scan/2013scanSummary.csv"
write.csv(batchecks, file = writeTo, row.names = F)
write.table(c("need experiments:", stillNeed, "\n"), file = writeTo, append = T,
            row.names = F, col.names = F);
write.table(c("ignore:", ignore, "\n"), file = writeTo, append = T,
            row.names = F, col.names = F);
write.table(c("file name:", writeTo, "\n"), file = writeTo, append = T,
            row.names = F, col.names = F)
# now look at your file and file and find everything that's missing 


# creating an assignment file for scans ####
# choose which experiments you'll be uploading and what their priorities will be
exps13 <- c("96_x", "inb1_b", "inb2_x", "M03", "qGen_b", "qGen_c", "qGen_x",
            "qGen2", "99s")
priority13 <- c(80, 79, 80, 90, 80, 85, 90, 60)

# do a quick double check to make sure everything is there 
loadScans(path = "F:/cg2013scans") 
scans <- scans[!(scans$filename %in% c("Thumbs.db", "itfiles.ini")),]
check.batch(batch = exps13, scansdf = scans, harvestFile = hh.2013)

# if there are no missing scans, create assignment csv and write to file
createCSV(scansdf = scans, harvYear = 2013, priority = 50)
# only take ones in the experiments we want to upload
out <- out[out$experiment %in% exps13,]
# change priorities to what you want
for (i in 1:length(exps13)) {
  out[out$experiment %in% exps13[i], "priority"] <- priority13[i]
}
out13 <- out # in case you're doing multiple years at once

# use this if you only want one person to count certain experiments
oneCt13 <- c("99s", "qGen2")
# get only one record per head for these experiments
out13[out13$experiment %in% oneCt13, "round"] <- 1
out13 <- out13[!duplicated(out13),]
# change this to decide who counts
out13[out13$user %in% "99s", "round"] <- "acouglin"
out13[out13$user %in% "qGen2", "round"] <- "lobenauf"

# write the file to a csv
write.csv(out13, 
          "C:/Users/dhanson/Dropbox/CGData/165_count/count2015/scanAssignments2013.csv",
          row.names = FALSE)

## End(Not run)


####################################################################
######################### check count data #########################
####################################################################
## Not run: 
library(echinaceaLab)
# check count data
polaph3 <- read.csv("C:/Users/dhanson/Dropbox/CGData/165_count/count2015/checkCounts/polLon_aphids_2014.csv")
source("C:/Users/dhanson/Dropbox/CGData/165_count/count2014/manageCountData.R")

# checking for large numbers
big <- polaph3[polaph3$letno %in% polaph3[polaph3$count > 300, "letno"],]
big <- big[order(big$letno),c("letno", "count", "notes")]

qman <- manageCountData(polaph3)
library(plyr)
sortqman <- function(probs) {
  probs[order(probs$letno),]
}
qman2 <- llply(qman, .fun = sortqman)

probnos <- qman$checkNotes$letno
probnos <- probnos[!duplicated(probnos)]
probnos <- sort(probnos)
checkem <- polaph3[polaph3$letno %in% probnos,]
checkem <- checkem[order(checkem$letno, checkem$notes), ]

## End(Not run)


####################################################################
########################### add gps data ###########################
####################################################################

## Not run: 
library(echinaceaLab)
# use the gps protocol to copy files from the gps to
# the geospatialDataBackup folder for the summer and then convert those files
# from .tsj to .xml files on HAL using topcon link
# if done on a computer besides Hal, you'll likely have to change "Echinacea" to something else
folderXML <- "C:/Users/Echinacea/Dropbox/geospatialDataBackup2015/convertedXML2015/"
folderRD <- "C:/Users/Echinacea/Dropbox/geospatialDataBackup2015/convertedRDataFiles2015/"
(fileNames <- dir(folderXML)) # make sure your files are there

# copy and paste this for every new job
# use the name format of the original job (from the GPS unit) for convertXMLtoRdata
convertXMLtoRdata("JOB_YYYYMMDD_MACHINE.xml")
(fileNames <- dir(folderRD))
(rdataNames <- makeGPSFileName(newFiles))
# use the name format from make GPS file name for the next two functions
errorCheckRData(folderRD, "aYYYYMMDD_job_MACHINE")
addToSurv.csv("aYYYYMMDD_job_MACHINE")

## End(Not run)

stuartWagenius/echinaceaLab documentation built on April 13, 2025, 5:22 a.m.