similar to: Satellite ocean color palette?

Has anyone written a script or function to read data from NODC?s World Ocean Database files? (I know there are simple Fortran and C programs to read these files, but the output is not suitable for easy analysis) Thanks, Franz _____________________________________________________ Dr. Franz J. Mueter School of Fisheries and Ocean Sciences, Juneau Center University of Alaska Fairbanks 11120

Hi: I am working with someone remotely to allow them access to our data. The follow command using "download.file" works perfectly on my Mac: > > download.file(url="http://oceanwatch.pfeg.noaa.gov:8081/thredds/ > wcs/satellite/AG/ssta/14day? > request=GetCoverage&version=1.0.0&service=WCS&format=NetCDF3&coverage= >

Greetings! Is there in any package for R which can help me generate madogram, rodogram, semi-variogram, cross variogram from landsat imagery. I intend to select portions of large imagery (i.e., obtain subsets) and generate the above said texture layers. A simple Google search led to me a result suggesting SpatialExtremes for generating madograms. However I am not sure about its capability to

Hi All: I am using httr to download files form a service, in this case a .csv file. When I use httr::content on the result, I get a message. Since this will be in a package. I want to suppress the message, but haven't figured out how to do so. The following should reproduce the result: myURL <-

Is there a way to increase the "sensitivity" of the color palette in order to more clearly represent certain sections of data? For example I am wanting to clearly differentiate between height data for a rolling landscape but because of the extremes of the dataset (sea and mountain tops), the bulk of the landscape is shaded in closely approximating green - i have attempted to do this by

Hi, I have been working with R for the last year and using the UKFSST package to look at satellite tag track data and SST information. Fpr those not familiar, the package uses the positions estimated by the satellite tags themselves and the associated SST data from servers (in this case, from the University of Hawaii and the NOAA Coastwatch website) for the time preiod to estimate a reasonable

Dear useRs, I got stuck trying to generate a palette of topographic colors that would satisfy these two requirements: - the pallete must be 'anchored' at 0 (just like on a map), with light blue/lawn green corresponding to data values close to 0 (dark blue to light blue for negative values, green-yellow-brown for positive values) - the brown must get darker for higher positive

Dear List, I would like to create several graphs of similar data. I have x and y values for several different individuals (in this case fish). I would like to plot the x and y values for each fish separately. I can do it using a for loop, but I think I should be using "apply". Please let me know what I am doing wrong, or if there is a "better" way to do this. What I have

Dear List, I am having problems converting a file with fractional seconds to class POSIXct. I have set my options to include digits.secs and my format to just time, but my output is the current date with my time lacking the fractions of a second. For example: options(digits.secs=3) t<-c("06:00:00.100","06:00:01.231") myt<-as.POSIXct(t,format="%H:%M:%S")

On Fri, 30 Nov 2018, Kees Cook wrote: >On Fri, Nov 30, 2018 at 11:27 AM Jarkko Sakkinen ><jarkko.sakkinen at linux.intel.com> wrote: >> >> In order to comply with the CoC, replace **** with a hug. I hope this is some kind of joke. How would anyone get offended by reading technical comments? This is all beyond me... Thanks, Davidlohr

Dear List, I need some help in coming up with a function that will take two data sets, determine if a value is missing in one, find a value in the second that was taken at about the same time, and substitute the second value in for where the first should have been. My problem is from a fish tracking study. We put acoustic tags in fish and track them for several days. Location data is supposed

I am trying to combine two data sets, one with daily values and one with weekly values.  SurveyData conatins environmental data collected on a daily basis.  sat.data contains satellite sea surface temperature that is an average of satellite measurements over a six day period.  I would like to combine the two files so that my output file has the daily dates from SurveyData and the weekly average

Hello all- I have a question related to encoding. I'm using a seperate program which takes either 16 bit or 8 bit (flat binary files) as inputs (they are raster satellite imagery and the associated quality files), but can't handle both at the same time. Problem is the quality and the image come in different formats (quality- 8bit, image- 16bit). I need to switch the encoding on the

Dear All, Could anyone?give me a hand?to suggest few packages in R to running Kalman prediction and filtration ? Thanks Fir

Dear R Helpers, Currently I'm working with the ts package of R and created a TimeSerie from pixels extracted from satellite imagery(S10 NDVI data, 10 daily composites). I'm trying to decompose this signal in different signals (seasonal and trend). When testing out the STL method is says => Only univariate timeseries are allowed, but the current Timeserie I'm using is univariate!

Dear List, I have a data frame of data taken every few seconds. I would like to subset the data to retain only the data taken on the quarter hour, and as close to the quarter hour as possible. So far I have figured out how to subset the data to the quarter hour, but not how to keep only the minimum time for each quarter hour. For example:

Dear List, I am wanting to produce a multiple line plot, and know I can do it with matplot but can't get my data in the format I need. I have a dataframe with three columns; individuals ID, x, and y. I have tried split() but it gives me a list of matrices, which is closer but not quite what I need. For example: id<-rep(seq(1,5,1),length.out=100) x<-rnorm(100,5,1)

A couple more thoughts... On Jan 16, 2015, at 10:42 AM, Warren Young <wyml at etr-usa.com> wrote: > On Jan 15, 2015, at 11:40 AM, Glenn Eychaner <geychaner at mac.com> wrote: > >> When the DOS box exits, crashes, or is rebooted, it fails to shut down the >> socket properly. > > Yes, that?s what happens when you use an OS that doesn?t implement sockets in

Hi, I have a dataset of dimensions 50 x 15000, and tried to use princomp or prcomp on this dataset with 15000 columns as variables, but it seems that the 2 functions can;t handle this large number of columns, anyone has nay suggestions to get around this? Thanks --------------------------------- [[alternate HTML version deleted]]

Dear R Users - R is a wonderful software package. CRAN provides a variety of tools to work on your data. But R is not apt to utilize all the public databases in an efficient manner. I observed the most tedious part with R is searching and downloading the data from public databases and putting it into the right format. I could not find a package on CRAN which offers exactly this fundamental