Errr... You could reshape to a long format data.frame but an arguably
easier way:
dimnames(array.3d) - list(lat= 1:7 , long = 1:11 , lev = 1:5) # not needed
just for clarity
levelplot(array.3d)
On Sat, Nov 17, 2012 at 9:36 PM, Tom Roche tom_ro...@pobox.com wrote:
summary: how to convert a 3D array (as obtained from ncdf4::ncvar_get)
to a dataframe suitable for use by lattice::levelplot(), e.g.,
levelplot(conc ~ lon * lat | lev, data = data.frame)
details:
I have atmospheric data in netCDF files specifying gas concentrations
over a 3D space with dimensions longitude, latitude, and (vertical)
level. I need to plot the data by level. Since there are several levels,
I'm guessing I should use package=lattice, which I have not previously
used. (I have used package=fields, and I would like to plot the levels
over a map, but lattice seems to provide the best way to organize
multiple plots--please correct me if wrong.)
From reading Sarkar's excellent lattice book
http://dx.doi.org/10.1007/978-0-387-75969-2
it seems that one best provides data to lattice::levelplot() via
dataframe, since the dataframe provides a sort of namespace for the
trellis formula. I know that ncdf4::ncvar_get will return my
concentrations as the values in a 3D array with dimensions={lon, lat,
lev} so I'm trying to find a way to convert a 3D array to a dataframe.
Here's my small, self-contained example:
lon=11
lat=7
lev=5
len=lon*lat*lev
array.3d - array(data=c(1:len), dim=c(lat, lon, lev))
# Rewrite the array values more spatially, i.e., row-wise from
# bottom left. If there's a more-R-ish way to fill this array
# as specified, please let me know: I know 'for' loops are deprecated
# in R.
i=1
for (z in 1:lev) {
for (x in lat:1) {
for (y in 1:lon) {
array.3d[x,y,z]=i ; i=i+1
}
}
}
produces (with rows=latitudes and cols=longitudes)
array.3d[,,1]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
[1,] 67 68 69 70 71 72 73 74 757677
[2,] 56 57 58 59 60 61 62 63 646566
[3,] 45 46 47 48 49 50 51 52 535455
[4,] 34 35 36 37 38 39 40 41 424344
[5,] 23 24 25 26 27 28 29 30 313233
[6,] 12 13 14 15 16 17 18 19 202122
[7,]1234567891011
array.3d[,,lev]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
[1,] 375 376 377 378 379 380 381 382 383 384 385
[2,] 364 365 366 367 368 369 370 371 372 373 374
[3,] 353 354 355 356 357 358 359 360 361 362 363
[4,] 342 343 344 345 346 347 348 349 350 351 352
[5,] 331 332 333 334 335 336 337 338 339 340 341
[6,] 320 321 322 323 324 325 326 327 328 329 330
[7,] 309 310 311 312 313 314 315 316 317 318 319
I want to convert array.3d to a dataframe with structure like the
following (note order of data values is arbitrary):
lon lat lev conc
--- --- ---
171 1
271 2
371 3
...
91175
101176
111177
...
915 383
1015 384
1115 385
How to do that? I'm guessing this involves function=reshape, but I can't
see how to make `reshape` work for this usecase.
TIA, Tom Roche tom_ro...@pobox.com
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
