In Urban-Meteorology-Reading/analysisToolsLUMA: Tools that can help speed up data analysis for LUMA instruments

analysisToolsLUMA

Functions that can be used to analyse and check LUMA observation data.

Installation

devtools::install_github('kitbenjamin/analysisToolsLUMA') 

library(analysisToolsLUMA)

dependencies

Plotting time series of instrument variables

Checking time series of data can be useful in diagnosing when, and at what stage of processing, something has gone wrong. plotData() will plot raw and processed data.

Example 1: plotting raw data

Take the simple example of plotting one day of SWT metdata data from /storage/basic/micromet/Tier_raw/RAW/2020/London/SWT/MetData/02

readLines('man/data/20200227_SWT_MetData.dat', n = 5)

To plot this we need to define several variables

instrument <- list(id = 'SWTWXSTATION', site = 'SWT') #define the id and site as it's listed on the metadata site
level <- 'RAW' 
startDate <- as.Date('2020-02-27') #start and end date must be class 'Date'
endDate <- as.Date('2020-02-27')
variables <- c('Tair', 'RH', 'dir', 'WS') # these must also be consistent with the metadata system
tickBreaks <- '2 hours' # where ticks will be on the plot
dateLabelFormat <- '%H:%M' #how the time axis will be formatted
sep <- ',' #the separator in the file
variableColNos = c(2, 10, 8, 5) # what column is each variable represented by
timeColFormat = '%Y-%m-%d %H:%M:%S' # format of the time column

Now plot the data

rawWXTPlot <- analysisToolsLUMA::plotLUMAdata(instrument, level, startDate, endDate, variables, tickBreaks, dateLabelFormat, sep = sep, variableColNos = variableColNos, timeColFormat = timeColFormat) 

Example 2: plotting raw data

This time take the slightly more difficult example of this Microlite data from /storage/basic/micromet/Tier_raw/RAW/2020/London/microlite/02

readLines('man/data/9178815_2020-02-27.txt', n = 20)

Also, save the output to a plots directory

instrument <- list(serial = '9178815') # use the serial number as there's multiple microlites at its site. Equally valid is instrument <- list(id = 'MICROLITE', site = 'BMH', serial = '9178815')
level <- 'RAW' 
startDate <- as.Date('2020-02-20') # plot a few days 
endDate <- as.Date('2020-02-27')
variables <- c('Tair_indoor', 'RH_indoor') 
tickBreaks <- '12 hours' 
dateLabelFormat <- '%j %H:%M' 
sep <- ',' 
variableColNos = c(3, 5) 
timeColFormat = c('%d/%m/%Y', '%H:%M:%S') #time is now over 2 columns so timeColFormat must be a vector
skipRows <- 9 # the first 9 rows are headers
title <- 'My microlite plot' # manually define title this time
SAVEplot <- TRUE
SAVEname <- 'MicroliteTS.png' # dont forget toadd the device (.png)
SAVEpath <- 'man/plots'
SAVEsize <- c(h = 8, w = 5, unit = 'in') # vector for height, width and unit. 

rawMicroPlot <- analysisToolsLUMA::plotLUMAdata(instrument, level, startDate, endDate, variables, tickBreaks, dateLabelFormat, sep = sep, variableColNos = variableColNos, timeColFormat = timeColFormat, skipRows = skipRows, title = title, SAVEplot = SAVEplot, SAVEname = SAVEname, SAVEpath = SAVEpath, SAVEsize = SAVEsize) 

Example 3: plotting processed EC data

Plotting processed data is even easier. Here we plot IMU eddy covariance data:

instrument <- list(id = 'LI7500A', site = 'IMU', ECpack = TRUE) #omit EC pack to plot non-ECpack data 
level <- 1 # as an integer
startDate <- as.Date('2020-01-01') 
endDate <- as.Date('2020-02-27')
variables <- c('C_CO2', 'Q_E') 
tickBreaks <- '7 days' # where ticks will be on the plot
dateLabelFormat <- '%d-%m %H' #how the time axis will be formatted
fileTimeRes = '30min' # for processed data the file time resolution must be manually defined as there's often several options.
lOneLicorPlot <- analysisToolsLUMA::plotLUMAdata(instrument, level, startDate, endDate, variables, tickBreaks, dateLabelFormat, fileTimeRes) 

plotLUMAdata() constists of 2 main functions that 1. get the data 2. plots the data

These can each be done seperately using these two functions:

allData <- getLUMAdata

finalPlot <- plotTimeSeries

Use ?getLUMAdata() and ?plotTimeSeries for more details.

Notes doesn't deal with changes in site and time res instrument can just be a serial number, or can be site, id and serial. I is faster to define site and ID. * for level RAW fileTimeRes can either be defined manually or it will be obtained from the metadata system

Urban-Meteorology-Reading/analysisToolsLUMA documentation built on June 8, 2021, 6:29 p.m.