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### testRHydro.R ### | |
# Load library | |
library(RHydro) | |
# Load data | |
data(modlist) | |
data(mopex) | |
# Calculate instantaneous runoff | |
Qinst <- fusesma.sim (fuse.DATA,mid=5,modlist,deltim=1, |
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# Step A: install RHydro | |
if(!require(RHydro)) install.packages("RHydro",repos="http://R-Forge.R-project.org") | |
# Step B: prepare your data | |
library(RHydro) | |
temp <- read.csv("dummyData.csv") |
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if(!require(RHydro)) install.packages("RHydro",repos="http://R-Forge.R-project.org") | |
library(RHydro) | |
temp <- read.csv("dummyData.csv") | |
DATA <- zooreg(temp[,2:4], order.by=temp[,1]) | |
myDELTIM <- 1 | |
myMID <- 60 | |
# Sample parameter space using the Latin Hypercube Sampling method |
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if(!require(RHydro)) install.packages("RHydro",repos="http://R-Forge.R-project.org") | |
library(RHydro) | |
temp <- read.csv("dummyData.csv") | |
DATA <- zooreg(temp[,2:4], order.by=temp[,1]) | |
myDELTIM <- 1 | |
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# Load the package and prepare the list of models | |
library(hydromad) | |
library(RHydro) | |
data(modlist) | |
# read data in | |
temp <- read.csv("dummyData.csv") | |
# Convert to date | |
temp[,1] <- as.Date(temp[,1],format="%Y-%m-%d") |
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# install/load dependent libraries | |
if(!require(zoo)) install.packages("zoo") | |
library(zoo) | |
if(!require(tgp)) install.packages("tgp") | |
library(tgp) | |
if(!require(qualV)) install.packages("qualV") | |
library(qualV) | |
if(!require(hydromad)) install.packages("hydromad",repos="http://hydromad.catchment.org") | |
library(hydromad) | |
if(!require(devtools)) install.packages("devtools") |
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if(!require(RHydro)) install.packages("RHydro",repos="http://R-Forge.R-project.org") | |
if(!require(fuse)) install.packages("fuse", repos="http://R-Forge.R-project.org") | |
library(RHydro) | |
library(fuse) | |
data(DATA) | |
data(modlist) | |
# Set parameter space |
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#' Download and convert TRMM data | |
#' | |
#' @author Claudia Vitolo | |
#' | |
#' @description The TRMM dataset provide global historical rainfall estimation in a gridded format. | |
#' | |
#' @param fileLocation file path where to save the GeoTiff | |
#' @param url url where data is stored (e.g. "ftp://disc2.nascom.nasa.gov/data/TRMM/Gridded/3B43_V7/2012/") | |
#' @param product this is the code that identifies a product, default is "3B43" | |
#' @param version this is the version number, default is 7 |
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#' Generate map of gauging stations. | |
#' | |
#' @author Claudia Vitolo <cvitolodev@gmail.com> | |
#' | |
#' @description This function takes as input a table of UK NRFA stations (output of getStationSummary() function) and generates a map using leaflet javascript library. | |
#' | |
#' @param selectedStationSummary This is the data.frame containing at least a column called "gridReference" (in which OS Grid references are stored) with 1 row for each station. Alternatively the table could contain 2 columns called "Latitude" and "Longitude" containing the coordinates of stations in WGS84, with 1 row for each station. | |
#' | |
#' @return displays a map | |
#' |
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# Load library | |
library(xts) | |
# Generate dummy time series | |
from <- as.Date("1950-01-01") | |
to <- as.Date("1990-12-31") | |
myDates <- seq.Date(from=from,to=to,by="day") | |
myTS <- as.xts(runif(length(myDates)),order.by=myDates) | |
# SPLIT THE TIME SERIES INTO CALENDAR YEARS |
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