inst/doc/WaterML-Tutorial.R

In WaterML: Fetch and Analyze Data from 'WaterML' and 'WaterOneFlow' Web Services

## ---- echo = FALSE, message = FALSE-------------------------------------------
knitr::opts_chunk$set(collapse = T, comment = "#>")
library(WaterML)

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#import required libraries
library(WaterML)

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#get the list of supported CUAHSI HIS services
services <- GetServices()

## ---- eval = FALSE------------------------------------------------------------
#  View(services)

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#point to an CUAHSI HIS service and get a list of the variables and sites
server <- "http://hydroportal.cuahsi.org/ipswich/cuahsi_1_1.asmx?WSDL"
variables <- GetVariables(server)
sites <- GetSites(server)

## ---- results='hide'----------------------------------------------------------
#get full site info for all sites using the GetSiteInfo method
siteinfo <- GetSiteInfo(server, "IRWA:FB-BV")

## ---- eval = FALSE------------------------------------------------------------
#  View(siteinfo)

## ---- results='hide'----------------------------------------------------------
#get full site info for all sites using the GetSiteInfo method
Temp <- GetValues(server,siteCode="IRWA:FB-BV",variableCode="IRWA:Temp")
DO <- GetValues(server, siteCode="IRWA:FB-BV",variableCode="IRWA:DO")

## -----------------------------------------------------------------------------
plot(DataValue~time, data=Temp, col="red")
points(DataValue~time, data=DO, col="blue")

## -----------------------------------------------------------------------------
years <- strftime(DO$time, "%Y")
months <- strftime(DO$time, "%m")
days <- strftime(DO$time, "%d")
hours <- strftime(DO$time, "%h")
minutes <- strftime(DO$time, "%M")
seconds <- strftime(DO$time, "%s")

## -----------------------------------------------------------------------------
#merge our two tables based on the time column
data <- merge(DO, Temp, by="time")
#rename the column DataValue.x in the merged table to "DO"
names(data)[names(data)=="DataValue.x"] <- "DO"
#rename the column DataValue.y in the merged table to "Temp"
names(data)[names(data)=="DataValue.y"] <- "Temp"

## ---- eval=FALSE--------------------------------------------------------------
#  plot(DO~Temp, data=data)

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# Perform a linear regression on the dissolved oxygen vs. temperature values
model <- lm(DO~Temp, data=data)

## ---- eval=FALSE--------------------------------------------------------------
#  summary(model)
#  abline(model)

## ---- echo = FALSE, message = FALSE-------------------------------------------
plot(DO~Temp, data=data)
model <- lm(DO~Temp, data=data)
abline(model)

## ---- echo = FALSE------------------------------------------------------------
summary(model)