random - simple way to randomly subset a raster in R -

-

i work in r. have raster (raster_entrop). want automatically generate random subset of raster. issue extent not rectangular , want subsets completly enclosed in extent. solution check if there not "nan" (corresponding pixel outside extent of raster_entrop) in coordinate of "subextent" randomly chosen inside extent of original raster. 

ext<-extent(raster_entrop) repeat{   rnd.x<-runif(1,ext@xmin, ext@xmax)   rnd.y<-runif(1,ext@ymin, ext@ymax)    #test if sub extent within "big extent"    test<-is.na(extract(raster_entrop, cbind(rnd.x,rnd.y)))+   is.na(extract(raster_entrop, cbind(rnd.x,rnd.y+0.02)))+   is.na(extract(raster_entrop, cbind(rnd.x+(0.02),rnd.y)))+   is.na(extract(raster_entrop, cbind(rnd.x+(0.02),rnd.y+0.02)))    if (test==0){     break   } } ext_sub<-extent(c(rnd.x, rnd.x+0.02,rnd.y,rnd.y+0.02)) raster_entrop_sub <- crop(raster_entrop, ext_sub)

my question: there simpler solution not use loop ?


Popular posts from this blog

How to calculate SNR of signals in MATLAB? -

-
i've encountered simple, yet fundamental problem on calculating snr: there several signals : s1 = original , pure clean signal without noise. n1 = white gaussian noise going added s1. s2 = s1 + n1 (the noisy signal before performing noise-reduction algorithm) s3 = noise-reduced signal (after performing noise reduction algorithm) n2 = s3 - s1 (the amount of noise after performing noise-reduction algorithm) now want compare snr before , after performing noise-reduction algorithm. which signals should consider snr_before!? s1/n1 or s2/n1 ? which signals should consider snr_after!? s3/n1 or s3/n2 ? which commands or functions should use in matlab in order compute snr_before , snr_after? thanks billion putting time on helping me. what know calculating snr before : snrbeforenoise = mean( signal .^ 2 ) / mean( noise .^ 2 ); and snr after : residual_noise = signal - noise_reduced_signal; snr_after = mean( signal .^ 2 ) / mean( residual_noise .^ 2...
Read more

c# - Attempting to upload to FTP: System.Net.WebException: System error -

-
i have api takes in xml , uploads files based on information in xml. uploads on schedule (also xml), , have tested surrounding , know works. i getting error 40% of time on first file attempt upload in each time cycle (time cycle = 45 minutes files, 30 minutes others). here code upload: try { loggerftp.log("uploading file: " + filename, false); // create request. ftpwebrequest request = (ftpwebrequest)webrequest.create(appsettingsftp.ftpurl + @"/" + filename); request.method = webrequestmethods.ftp.uploadfile; request.timeout = 6000000; //set 100 minutes //request.timeout = -1; //set infinite // add login credentials. request.credentials = new networkcredential(appsettingsftp.ftplogin, appsettingsftp.ftppassword); // grab file contents. streamreader sourcestream = new streamreader(appsettingsftp.uploadfiledirectory + filename); byte[] filecontents = encoding.utf8.getbytes(sourcestream.readtoend()); sourcest...
Read more

ios - UISlider customization: how to properly add shadow to custom knob image -

-
Image
i need place custom knob image shadow uislider. far have image of 38x38, of there region defines shadow of knob. now while using image, when slide knob extreme ends actual knob not able cover end points, hence end points visible under transparent region of knob image this code using customize uislider uiimage *slidebtimg = [uiimage imagenamed:sliderknobimg]; [self.ratingslider setthumbimage:slidebtimg forstate:uicontrolstatenormal]; [self.ratingslider setthumbimage:slidebtimg forstate:uicontrolstatehighlighted]; how can implement custom knob shadow beneath it, covering end points?? look inside uislider.h , there methods let customize slider knob , track needed. (ios 2.0 , above) // lets subclass lay out track , thumb needed - (cgrect)minimumvalueimagerectforbounds:(cgrect)bounds; - (cgrect)maximumvalueimagerectforbounds:(cgrect)bounds; - (cgrect)trackrectforbounds:(cgrect)bounds; - (cgrect)thumbrectforbounds:(cgrect)bounds trackrect:(cgrect)rect value:...
Read more