Changes between Version 33 and Version 34 of EcomsUdg/RPackage/Functions


Ignore:
Timestamp:
May 28, 2013 7:27:16 PM (8 years ago)
Author:
gutierjm
Comment:

--

Legend:

Unmodified
Added
Removed
Modified
  • EcomsUdg/RPackage/Functions

    v33 v34  
    1 = makeNcmlDataset =
    2 
    3 
    4 
    5 === ''__Description''
    6 
    7 Generates a NcML file from a collection of netCDF files.
    8 
    9 
    10 === ''__Usage''
    11 
    12 {{{
    13 makeNcmlDataset(source.dir, ncml.file)
    14 }}}
    15 
    16 
    17 === ''__Arguments''
    18 
    19 * `source.dir`: character string indicating a valid path of the directory containing the files
    20 * `ncml.file`: character string indicating the NcML file name (and path, default to working directory), including the extension ''.ncml''.
    21 
    22 The output is a NcML file named as `file.name` which will be stored in the `output.dir`.
    23 
    24 
    25 === ''__Details''
    26 
    27 * All files of the same dataset should be put together in the same directory, indicated by the `source.dir` argument.
    28 * Currently the function works only with netCDF (''.nc'') file collections.
    29 * A number of useful recommendations regarding dataset naming are provided [http://www.unidata.ucar.edu/software/netcdf-java/reference/DatasetUrls.html#NcmlScan here]
    30 
    31 
    32 === ''__Value''
    33 
    34 Creates a NcML file at the specified location
    35 
    36 === ''__Notes''
    37 
    38 A NcML file is a [http://en.wikipedia.org/wiki/XML XML] representation of netCDF metadata. This is approximately the same information one gets when dumping the header of a netCDF file (e.g. by typing on the terminal the command `ncdump -h`). By means of NcML it is possible to create virtual datasets by modifying and  aggregating other datasets, thus providing maximum flexibility and ease of access to data stored in collections of files containing data from different variables/time slices. The function `makeNcmlDataset` is intended to deal with reanalysis, forecasts and other climate data products, often consisting of collections of netCDF files corresponding to different variables and partitioned by years/decades or other time slices. It operates by applying to types of [http://www.unidata.ucar.edu/software/netcdf/ncml/v2.2/Aggregation.html aggregation operations]:
    39 
    40 1. `Union`: Performs the union of all the dimensions, attributes, and variables in multiple NetCDF files
    41 2. `JoinExisting`: Variables of the same name (in different files) are connected along their existing, outer dimension, called the aggregation dimension. In this case the aggregation dimension is ''time''.
    42 
    43 
    44 === ''__Examples'' ===
    45 
    46 An example of this function is provided in the [wiki:SpecsEuporias/RPackage/Examples#loadSeasonalForecast Examples section]
    47 
    48 
    49 
    50 
    51 
    521= dataInventory =
    532
     
    9140=== ''__Examples__''
    9241
    93 An example of this function is provided in the [wiki:SpecsEuporias/RPackage/Examples Examples section]
     42An example of this function is provided in the [wiki:SpecsEuporias/RPackage/Examples#dataInventory Examples section]
    9443
    9544
     
    282231An example of this function is provided in the [wiki:SpecsEuporias/RPackage/Examples Examples section]
    283232
    284 
    285 
    286 
     233= makeNcmlDataset =
     234
     235
     236
     237=== ''__Description''
     238
     239Generates a NcML file from a collection of netCDF files.
     240
     241
     242=== ''__Usage''
     243
     244{{{
     245makeNcmlDataset(source.dir, ncml.file)
     246}}}
     247
     248
     249=== ''__Arguments''
     250
     251* `source.dir`: character string indicating a valid path of the directory containing the files
     252* `ncml.file`: character string indicating the NcML file name (and path, default to working directory), including the extension ''.ncml''.
     253
     254The output is a NcML file named as `file.name` which will be stored in the `output.dir`.
     255
     256
     257=== ''__Details''
     258
     259* All files of the same dataset should be put together in the same directory, indicated by the `source.dir` argument.
     260* Currently the function works only with netCDF (''.nc'') file collections.
     261* A number of useful recommendations regarding dataset naming are provided [http://www.unidata.ucar.edu/software/netcdf-java/reference/DatasetUrls.html#NcmlScan here]
     262
     263
     264=== ''__Value''
     265
     266Creates a NcML file at the specified location
     267
     268=== ''__Notes''
     269
     270A NcML file is a [http://en.wikipedia.org/wiki/XML XML] representation of netCDF metadata. This is approximately the same information one gets when dumping the header of a netCDF file (e.g. by typing on the terminal the command `ncdump -h`). By means of NcML it is possible to create virtual datasets by modifying and  aggregating other datasets, thus providing maximum flexibility and ease of access to data stored in collections of files containing data from different variables/time slices. The function `makeNcmlDataset` is intended to deal with reanalysis, forecasts and other climate data products, often consisting of collections of netCDF files corresponding to different variables and partitioned by years/decades or other time slices. It operates by applying to types of [http://www.unidata.ucar.edu/software/netcdf/ncml/v2.2/Aggregation.html aggregation operations]:
     271
     2721. `Union`: Performs the union of all the dimensions, attributes, and variables in multiple NetCDF files
     2732. `JoinExisting`: Variables of the same name (in different files) are connected along their existing, outer dimension, called the aggregation dimension. In this case the aggregation dimension is ''time''.
     274
     275
     276=== ''__Examples'' ===
     277
     278An example of this function is provided in the [wiki:SpecsEuporias/RPackage/Examples#loadSeasonalForecast Examples section]
     279
     280
     281
     282
     283
     284
     285
     286