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...ck(grib_file_path) # Check the names of the layers to identify which ones to extract > layer_names <- names(raster_data) > print(layer_names) # Prints > # Extract layers based on layer names - adjust as necessary > t2m <- raster_data[[grep("t2m", layer_names)]] > d2m <- raster_data[[grep("d2m", layer_names)]] > tcc <- raster_data[[grep("tcc", layer_names)]] > valid_time <- raster_data[[grep("valid_time", layer_names)]] > t2m class : RasterStack nlayers : 0 > # Check if the raster layers are loaded corr...

...ames of the layers to identify which ones to extract > > layer_names <- names(raster_data) > > print(layer_names) # Prints > > > > # Extract layers based on layer names - adjust as necessary > > t2m <- raster_data[[grep("t2m", layer_names)]] > > d2m <- raster_data[[grep("d2m", layer_names)]] > > tcc <- raster_data[[grep("tcc", layer_names)]] > > valid_time <- raster_data[[grep("valid_time", layer_names)]] > > t2m > class : RasterStack > nlayers : 0 > > > # Check if...

...h ones to extract > > > layer_names <- names(raster_data) > > > print(layer_names) # Prints > > > > > > > # Extract layers based on layer names - adjust as necessary > > > t2m <- raster_data[[grep("t2m", layer_names)]] > > > d2m <- raster_data[[grep("d2m", layer_names)]] > > > tcc <- raster_data[[grep("tcc", layer_names)]] > > > valid_time <- raster_data[[grep("valid_time", layer_names)]] > > > t2m > > class : RasterStack > > nlayers : 0...

...>>>> layer_names <- names(raster_data) >>>> print(layer_names) # Prints >>> >>> >>>> # Extract layers based on layer names - adjust as necessary >>>> t2m <- raster_data[[grep("t2m", layer_names)]] >>>> d2m <- raster_data[[grep("d2m", layer_names)]] >>>> tcc <- raster_data[[grep("tcc", layer_names)]] >>>> valid_time <- raster_data[[grep("valid_time", layer_names)]] >>>> t2m >>> class : RasterStack >>> nla...

...s <- names(raster_data) > >>>> print(layer_names) # Prints > >>> > >>> > >>>> # Extract layers based on layer names - adjust as necessary > >>>> t2m <- raster_data[[grep("t2m", layer_names)]] > >>>> d2m <- raster_data[[grep("d2m", layer_names)]] > >>>> tcc <- raster_data[[grep("tcc", layer_names)]] > >>>> valid_time <- raster_data[[grep("valid_time", layer_names)]] > >>>> t2m > >>> class : RasterSt...

...>> >>>> print(layer_names) # Prints >> >>> >> >>> >> >>>> # Extract layers based on layer names - adjust as necessary >> >>>> t2m <- raster_data[[grep("t2m", layer_names)]] >> >>>> d2m <- raster_data[[grep("d2m", layer_names)]] >> >>>> tcc <- raster_data[[grep("tcc", layer_names)]] >> >>>> valid_time <- raster_data[[grep("valid_time", layer_names)]] >> >>>> t2m >> >>> class...

...a) >> >>>> print(layer_names) # Prints >> >>> >> >>> >> >>>> # Extract layers based on layer names - adjust as necessary >> >>>> t2m <- raster_data[[grep("t2m", layer_names)]] >> >>>> d2m <- raster_data[[grep("d2m", layer_names)]] >> >>>> tcc <- raster_data[[grep("tcc", layer_names)]] >> >>>> valid_time <- raster_data[[grep("valid_time", layer_names)]] >> >>>> t2m >> >>> class...

...gt; print(layer_names) # Prints > >> >>> > >> >>> > >> >>>> # Extract layers based on layer names - adjust as necessary > >> >>>> t2m <- raster_data[[grep("t2m", layer_names)]] > >> >>>> d2m <- raster_data[[grep("d2m", layer_names)]] > >> >>>> tcc <- raster_data[[grep("tcc", layer_names)]] > >> >>>> valid_time <- raster_data[[grep("valid_time", layer_names)]] > >> >>>> t2m > >&gt...

...e # Compress JavaScripts and CSS config.assets.compress = true config.assets.precompile = [''*.js'', ''*.css''] at application.js // = require jquery_ujs // = require jquery // = require jquery.jcarousel.min // = requier_tree . how I do for that Regards, D2M -- You received this message because you are subscribed to the Google Groups "Ruby on Rails: Talk" group. To post to this group, send email to rubyonrails-talk-/JYPxA39Uh5TLH3MbocFF+G/Ez6ZCGd0@public.gmane.org To unsubscribe from this group, send email to rubyonrails-talk+unsubscribe@g...

Dear R list, I'm trying to calculate Mahalanobis distances for 'Species' of 'iris' data as obtained below: Squared Distance to Species From Species: Setosa Versicolor Virginica Setosa 0 89.86419 179.38471 Versicolor 89.86419 0 17.20107 Virginica 179.38471 17.20107 0 These distances were obtained with proc 'CANDISC'

Dear R list, I'm trying to calculate Mahalanobis distances for 'Species' of 'iris' data as obtained below: Squared Distance to Species From Species: Setosa Versicolor Virginica Setosa 0 89.86419 179.38471 Versicolor 89.86419 0 17.20107 Virginica 179.38471 17.20107 0 This distances above were obtained with proc