similar to: Color scale graphic

note: whole function is below- I am sure I am doing something silly. when I use it like USGS(input="precipitation") it is choking on the precip.1 <- subset(DF, precipitation!="NA") b <- ddply(precip.1$precipitation, .(precip.1$gauge_name), cumsum) DF.precip <- precip.1 DF.precip$precipitation <- b$.data part, but runs fine outside of the function: days=7

Hi all, I have gone through some basics of R in eclipse environment. What I need to work is more than basic level so I could not find out the solution by myself. could anyone help me ? My case, I have climate data (precipitation) in nc format with single layer for each time interval in a day. That means for January 1, 2013, I have 8 separate files each containing 3 hrs cumulative precipitation

Dear all, I have a list of precipitation record and a list of time I would like to sum them up per hour, or per day. Does such a function exist ? example: time<-c("2000-10-03 14:00:00","2000-10-03 14:10:00","2000-10-03 14:20:00","2000-10-03 15:30:00","2000-10-03 16:40:00","2000-10-03 16:50:00","2000-10-03

I am performing a precipitation analysis. data is in the form of daily precipitation amounts, e.g. x<- c(4,5,3,0,0,0,2,4,6,4,0,0,0,2,2,0,3,4,1,0,...) I would like to find the length of the "storm", length of storm would be defined as the number of days with continues precipitation. in this case the returned vector would be: (3,4,2,3,...) I would also like the amount of

Dear All, I have to get the value of say 90th percentile of precipitation time series.. The series is of daily precipitation value of 96 years, I have to to get 90the percentile value of daily precipitation each year. If you know the R code or command for this please let me know. I would appreciate your early response. Thanking you, Sincerely, Ajay.

Dear R gurus, I have some climatic data for a region of the world. They are monthly averages 1950 -2000 of precipitation (12 months), minimum temperature (12 months), maximum temperature (12 months). I have scaled them to 2 km x 2km cells, and I have around 75,000 cells. I need to feed them into a statistical model as co-variates, to use them to predict a response variable. The climatic

Hello, I am creating plots of hourly precipitation and accumulated precipitation (on different axis, see attached image). I was wondering how can I have the plot frame (black border) start at zero, it looks like it is plotted less than zero? The code I use to create the png files is below: CairoPNG(PNG_file,width=1000, height=600, pointsize=14, bg="white") opar <-

Hello friends of R, My name is Toni, i'm 25 and I'm working on the Meteorological Investigation team from Balearic Islands. I had contact to you because I have a problem: I done a file for every day since 1912 about precipitation. That file has the following structure: > str(Ast) Loading required package: sp Formal class 'SpatialPixelsDataFrame' [package "sp"]

Dear all, I have some additionale question concerning the spgrass6 package. * When you set a region in GRASS, does the readGRASS6 function in R only load data contained in the zoomed region or the whole map ? * When you have a MASK map in grass, does the readGRASS6 function in R only load data contained inside the MASK area ? Could this be the problem ? Thanks, Jessica

Hello to everyone. I´m writing you because I´m feeling a bit frustrated with my work. My work consists in finding the relation between the amount of fires and the weather, so, my response variable is the amount of fires in a fire season and the explanatory variables are the temperature, the amount of precipitation and the some others…. my problem is this; I keep getting the wrong sign in the

Look at the bottom of the message for my question #here is a little function that I wrote USGS <- function(input="discharge", days=7){ library(chron) library(gsubfn) #021973269 is the Waynesboro Gauge on the Savannah River Proper (SRS) #02102908 is the Flat Creek Gauge (ftbrfcms) #02133500 is the Drowning Creek (ftbrbmcm) #02341800 is the Upatoi Creek Near Columbus (ftbn) #02342500 is

OK, so maybe last night was a little too much at one throw, so I have reduced the data to two stations- one that has precipitation and one that does not. This is going to be in the context of a larger data set. I would like to be able to issue a ggplot command and have cum sum just act on the facets (factors) to apply this. library(chron) library(ggplot2) DF <- structure(list(date_time =

Dear all, I have a data set which has latitude, longitude (not in increasing order) and observed precipitation corresponding to those locations. I am using image.plot command for that. But I want to overlay a map of US on that plot. I know we can use map('usa') to draw it, but I dont know how can I overlay it on the plot of the precipitation data. Can anyone please help me with it?

Hi all, I want to arrange two ggplot2 plots on the same page with their x-axes lined up - even though one is a boxplot and the other is a line plot. Is there a simple way to do this? I know I could do this using facetting if they were both the same type of plot (for example, if they were both boxplots), but I haven't been able to figure it out for two different types of plots. Below is my

Hello, This maybe a newbie question. I have a dataframe that looks like the sample at the bottom of the email. I have monthly precipitation data from several sites over several years. For each site, I need to extract years that have a complete series of 12 monthly precipitation values, while excluding that year for sites with incomplete data. I can't figure out how to do this gracefully

Hello, I am new to R exploratory data analysis and plotting. Is anyone aware of a way to overlay a set of conditional histograms with conditional PDFs? Below, I generate a lattice plot of precipitation histograms based on different months and stations, given a subset of the dataset: histogram(~ data | month * station, data = sta.stack[sta.stack[,"type"]=="precip" &

Hi everyone, I am desperately looking for a method to interpolate strings within an SQL statement as follows: I get a lot of rows out of a database (in my example POSITION_to_ZIPCODE Database with holds records for German ZIP Code <--> Gauss-Krueger Coordinate System ) and want this to be selected and computed individually row by row as follows: library(RODBC) channel <-

Hi there I have precipitation data from 2004 to 2006 in varying resolutions (10 to 20min intervals) with time in seconds from beginnig of the year (summation) and a second variable as year. I applied follwing code to convert the time into a date: times<-strptime("2004-01-01", "%Y-%m-%d", tz="GMT") + precipitation$time1 everytihng went well, except that every

Hi, I'm interpolating a list of syncronous accumulated precipitation observations collected over a number of raingauge stations sited over land, over a regular lat/lon grid using akima's interp(). Then, I plot and locate geographycally the resulting field with a filled.contour() and a call to map(). Everything is fine but I need to "blank" (in Golden Surfer nomenclature)

Using the small reproducible example below, I'm wondering how best to complete the following task: In the small reproducible example below, the 3D array prec has indexes that correspond to time, x, y (i.e., prec[time, x, y]). In this case, the time index is hours since some predefined start time. I'd like to add up all the time indexes in 'prec' based on whether or not the