rnoaa (version 0.3.3)

erddap_grid: Get ERDDAP griddap data.

Description

Get ERDDAP griddap data.

Usage

erddap_grid(x, ..., fields = "all", stride = 1, store = disk(),
  callopts = list())

Arguments

x

Anything coercable to an object of class erddap_info. So the output of a call to erddap_info, or a datasetid, which will internally be passed through erddap_info.

...

Dimension arguments.

fields

Fields to return, a character vector.

stride

(integer) How many values to get. 1 = get every value, 2 = get every other value, etc. Default: 1 (i.e., get every value)

store

One of disk (default) or memory. You can pass options to disk

callopts

Pass on curl options to GET

Dimensions and Variables

ERDDAP grid dap data has this concept of dimenions vs. variables. So, dimensions are things like time, latitude, longitude, and altitude. Whereas variables are the measured variables, e.g., temperature, salinity, and air. You can't separately adjust values for dimensions for different variables. So, here's how it's gonna work: Pass in lower and upper limits you want for each dimension as a vector (e.g., c(1,2)), or leave to defaults (i.e., don't pass anything to a dimension). Then pick which variables you want returned via the fields parameter. If you don't pass in options to the fields parameter, you get all variables back. To get the dimensions and variables, along with other metadata for a dataset, run erddap_info, and each will be shown, with their min and max values, and some other metadata.

Where does the data go?

You can choose where data is stored. Be careful though. With griddap data, you can easily get a single file of hundreds of MB's or GB's in size with a single request. Using disk() caches files based on the URL of the request you perform, which is the combination of all parameters passed in, so if you refine a query by certain fields, etc., you will cach a different file. If you choose overwrite=TRUE within the disk() function then you'll force writing a new file to disk. When you use memory(), no files are cached, data is stored in R's memory.

Details

Details:

References

http://upwell.pfeg.noaa.gov/erddap/index.html

See Also

erddap_table erddap_clear_cache

Examples

## Not run: ------------------------------------
# # single variable dataset
# ## You can pass in the outpu of a call to erddap_info
# (out <- erddap_info('noaa_esrl_027d_0fb5_5d38'))
# (res <- erddap_grid(out,
#  time = c('2012-01-01','2012-06-12'),
#  latitude = c(21, 18),
#  longitude = c(-80, -75)
# ))
# ## Or, pass in a dataset id
# (res <- erddap_grid(x='noaa_esrl_027d_0fb5_5d38',
#  time = c('2012-01-01','2012-06-12'),
#  latitude = c(21, 18),
#  longitude = c(-80, -75)
# ))
# 
# # multi-variable dataset
# (out <- erddap_info('noaa_gfdl_5081_7d4a_7570'))
# (res <- erddap_grid(out,
#  time = c('2005-11-01','2006-01-01'),
#  latitude = c(20, 21),
#  longitude = c(10, 11)
# ))
# (res <- erddap_grid(out, time = c('2005-11-01','2006-01-01'), latitude = c(20, 21),
#    longitude = c(10, 11), fields = 'uo'))
# (res <- erddap_grid(out, time = c('2005-11-01','2006-01-01'), latitude = c(20, 21),
#    longitude = c(10, 11), fields = 'uo', stride=c(1,2,1,2)))
# (res <- erddap_grid(out, time = c('2005-11-01','2006-01-01'), latitude = c(20, 21),
#    longitude = c(10, 11), fields = c('uo','so')))
# (res <- erddap_grid(out, time = c('2005-09-01','2006-01-01'), latitude = c(20, 21),
#    longitude = c(10, 11), fields = 'none'))
# 
# # multi-variable dataset
# ## this one also has a 0-360 longitude system, BLARGH!!!
# (out <- erddap_info('noaa_gfdl_3c96_7879_a9d3'))
# (res <- erddap_grid(out,
#  time = c('2005-11-01','2006-01-01'),
#  latitude = c(20, 22),
#  longitude = c(-80, -75)
# ))
# (res <- erddap_grid(out,
#  time = c('2005-11-01','2006-01-01'),
#  latitude = c(20, 22),
#  longitude = c(-80, -75),
#  depth = c(5, 50)
# ))
# 
# # Write to memory (within R), or to disk
# (out <- erddap_info('noaa_pfeg_e9ae_3356_22f8'))
# ## disk, by default (to prevent bogging down system w/ large datasets)
# ## you can also pass in path and overwrite options to disk()
# (res <- erddap_grid(out,
#  time = c('2012-06-01','2012-06-12'),
#  latitude = c(20, 21),
#  longitude = c(-80, -75),
#  store = disk()
# ))
# ## the 2nd call is much faster as it's mostly just the time of reading in the table from disk
# system.time( erddap_grid(out,
#  time = c('2012-06-01','2012-06-12'),
#  latitude = c(20, 21),
#  longitude = c(-80, -75),
#  store = disk()
# ) )
# system.time( erddap_grid(out,
#  time = c('2012-06-01','2012-06-12'),
#  latitude = c(20, 21),
#  longitude = c(-80, -75),
#  store = disk()
# ) )
# 
# ## memory
# (res <- erddap_grid(out,
#  time = c('2012-06-01','2012-06-12'),
#  latitude = c(20, 21),
#  longitude = c(-80, -75),
#  store = memory()
# ))
## ---------------------------------------------