This document describes the Fortran 90 interface to the netCDF library. It applies to netCDF version 4.0. This document was last updated on 29 January 2008.
For a complete description of the netCDF format and utilities see The NetCDF Users Guide (The NetCDF Users Guide).
--- The Detailed Node Listing ---
Use of the NetCDF Library
Datasets
Dimensions
Variables
Attributes
You can use the netCDF library without knowing about all of the netCDF interface. If you are creating a netCDF dataset, only a handful of routines are required to define the necessary dimensions, variables, and attributes, and to write the data to the netCDF dataset. (Even less are needed if you use the ncgen utility to create the dataset before running a program using netCDF library calls to write data. See ncgen (The NetCDF Users Guide).) Similarly, if you are writing software to access data stored in a particular netCDF object, only a small subset of the netCDF library is required to open the netCDF dataset and access the data. Authors of generic applications that access arbitrary netCDF datasets need to be familiar with more of the netCDF library.
In this chapter we provide templates of common sequences of netCDF calls needed for common uses. For clarity we present only the names of routines; omit declarations and error checking; omit the type-specific suffixes of routine names for variables and attributes; indent statements that are typically invoked multiple times; and use ... to represent arbitrary sequences of other statements. Full parameter lists are described in later chapters.
Here is a typical sequence of netCDF calls used to create a new netCDF dataset:
NF90_CREATE ! create netCDF dataset: enter define mode ... NF90_DEF_DIM ! define dimensions: from name and length ... NF90_DEF_VAR ! define variables: from name, type, dims ... NF90_PUT_ATT ! assign attribute values ... NF90_ENDDEF ! end definitions: leave define mode ... NF90_PUT_VAR ! provide values for variable ... NF90_CLOSE ! close: save new netCDF dataset
Only one call is needed to create a netCDF dataset, at which point you will be in the first of two netCDF modes. When accessing an open netCDF dataset, it is either in define mode or data mode. In define mode, you can create dimensions, variables, and new attributes, but you cannot read or write variable data. In data mode, you can access data and change existing attributes, but you are not permitted to create new dimensions, variables, or attributes.
One call to NF90_DEF_DIM is needed for each dimension created. Similarly, one call to NF90_DEF_VAR is needed for each variable creation, and one call to a member of the NF90_PUT_ATT family is needed for each attribute defined and assigned a value. To leave define mode and enter data mode, call NF90_ENDDEF.
Once in data mode, you can add new data to variables, change old values, and change values of existing attributes (so long as the attribute changes do not require more storage space). Data of all types is written to a netCDF variable using the NF90_PUT_VAR subroutine. Single values, arrays, or array sections may be supplied to NF90_PUT_VAR; optional arguments allow the writing of subsampled or mapped portions of the variable. (Subsampled and mapped access are general forms of data access that are explained later.)
Finally, you should explicitly close all netCDF datasets that have been opened for writing by calling NF90_CLOSE. By default, access to the file system is buffered by the netCDF library. If a program terminates abnormally with netCDF datasets open for writing, your most recent modifications may be lost. This default buffering of data is disabled by setting the NF90_SHARE flag when opening the dataset. But even if this flag is set, changes to attribute values or changes made in define mode are not written out until NF90_SYNC or NF90_CLOSE is called.
Here we consider the case where you know the names of not only the netCDF datasets, but also the names of their dimensions, variables, and attributes. (Otherwise you would have to do "inquire" calls.) The order of typical C calls to read data from those variables in a netCDF dataset is:
NF90_OPEN ! open existing netCDF dataset ... NF90_INQ_DIMID ! get dimension IDs ... NF90_INQ_VARID ! get variable IDs ... NF90_GET_ATT ! get attribute values ... NF90_GET_VAR ! get values of variables ... NF90_CLOSE ! close netCDF dataset
First, a single call opens the netCDF dataset, given the dataset name, and returns a netCDF ID that is used to refer to the open netCDF dataset in all subsequent calls.
Next, a call to NF90_INQ_DIMID for each dimension of interest gets the dimension ID from the dimension name. Similarly, each required variable ID is determined from its name by a call to NF90_INQ_VARID. Once variable IDs are known, variable attribute values can be retrieved using the netCDF ID, the variable ID, and the desired attribute name as input to NF90_GET_ATT for each desired attribute. Variable data values can be directly accessed from the netCDF dataset with calls to NF90_GET_VAR.
Finally, the netCDF dataset is closed with NF90_CLOSE. There is no need to close a dataset open only for reading.
It is possible to write programs (e.g., generic software) which do such things as processing every variable, without needing to know in advance the names of these variables. Similarly, the names of dimensions and attributes may be unknown.
Names and other information about netCDF objects may be obtained from netCDF datasets by calling inquire functions. These return information about a whole netCDF dataset, a dimension, a variable, or an attribute. The following template illustrates how they are used:
NF90_OPEN ! open existing netCDF dataset ... NF90_INQUIRE ! find out what is in it ... NF90_INQUIRE_DIMENSION ! get dimension names, lengths ... NF90_INQUIRE_VARIABLE ! get variable names, types, shapes ... NF90_INQ_ATTNAME ! get attribute names ... NF90_INQUIRE_ATTRIBUTE ! get other attribute information ... NF90_GET_ATT ! get attribute values ... NF90_GET_VAR ! get values of variables ... NF90_CLOSE ! close netCDF dataset
As in the previous example, a single call opens the existing netCDF dataset, returning a netCDF ID. This netCDF ID is given to the NF90_INQUIRE routine, which returns the number of dimensions, the number of variables, the number of global attributes, and the ID of the unlimited dimension, if there is one.
All the inquire functions are inexpensive to use and require no I/O, since the information they provide is stored in memory when a netCDF dataset is first opened.
Dimension IDs use consecutive integers, beginning at 1. Also dimensions, once created, cannot be deleted. Therefore, knowing the number of dimension IDs in a netCDF dataset means knowing all the dimension IDs: they are the integers 1, 2, 3, ...up to the number of dimensions. For each dimension ID, a call to the inquire function NF90_INQUIRE_DIMENSION returns the dimension name and length.
Variable IDs are also assigned from consecutive integers 1, 2, 3, ... up to the number of variables. These can be used in NF90_INQUIRE_VARIABLE calls to find out the names, types, shapes, and the number of attributes assigned to each variable.
Once the number of attributes for a variable is known, successive calls to NF90_INQ_ATTNAME return the name for each attribute given the netCDF ID, variable ID, and attribute number. Armed with the attribute name, a call to NF90_INQUIRE_ATTRIBUTE returns its type and length. Given the type and length, you can allocate enough space to hold the attribute values. Then a call to NF90_GET_ATT returns the attribute values.
Once the IDs and shapes of netCDF variables are known, data values can be accessed by calling NF90_GET_VAR.
With write access to an existing netCDF dataset, you can overwrite data values in existing variables or append more data to record variables along the unlimited (record) dimension. To append more data to non-record variables requires changing the shape of such variables, which means creating a new netCDF dataset, defining new variables with the desired shape, and copying data. The netCDF data model was not designed to make such "schema changes" efficient or easy, so it is best to specify the shapes of variables correctly when you create a netCDF dataset, and to anticipate which variables will later grow by using the unlimited dimension in their definition.
The following code template lists a typical sequence of calls to overwrite some existing values and add some new records to record variables in an existing netCDF dataset with known variable names:
NF90_OPEN ! open existing netCDF dataset ... NF90_INQ_VARID ! get variable IDs ... NF90_PUT_VAR ! provide new values for variables, if any ... NF90_PUT_ATT ! provide new values for attributes, if any ... NF90_CLOSE ! close netCDF dataset
A netCDF dataset is first opened by the NF90_OPEN call. This call puts the open dataset in data mode, which means existing data values can be accessed and changed, existing attributes can be changed, but no new dimensions, variables, or attributes can be added.
Next, calls to NF90_INQ_VARID get the variable ID from the name, for each variable you want to write. Then each call to NF90_PUT_VAR writes data into a specified variable, either a single value at a time, or a whole set of values at a time, depending on which variant of the interface is used. The calls used to overwrite values of non-record variables are the same as are used to overwrite values of record variables or append new data to record variables. The difference is that, with record variables, the record dimension is extended by writing values that don't yet exist in the dataset. This extends all record variables at once, writing "fill values" for record variables for which the data has not yet been written (but see Fill Values to specify different behavior).
Calls to NF90_PUT_ATT may be used to change the values of existing attributes, although data that changes after a file is created is typically stored in variables rather than attributes.
Finally, you should explicitly close any netCDF datasets into which data has been written by calling NF90_CLOSE before program termination. Otherwise, modifications to the dataset may be lost.
An existing netCDF dataset can be extensively altered. New dimensions, variables, and attributes can be added or existing ones renamed, and existing attributes can be deleted. Existing dimensions, variables, and attributes can be renamed. The following code template lists a typical sequence of calls to add new netCDF components to an existing dataset:
NF90_OPEN ! open existing netCDF dataset ... NF90_REDEF ! put it into define mode ... NF90_DEF_DIM ! define additional dimensions (if any) ... NF90_DEF_VAR ! define additional variables (if any) ... NF90_PUT_ATT ! define other attributes (if any) ... NF90_ENDDEF ! check definitions, leave define mode ... NF90_PUT_VAR ! provide new variable values ... NF90_CLOSE ! close netCDF dataset
A netCDF dataset is first opened by the NF90_OPEN call. This call puts the open dataset in data mode, which means existing data values can be accessed and changed, existing attributes can be changed (so long as they do not grow), but nothing can be added. To add new netCDF dimensions, variables, or attributes you must enter define mode, by calling NF90_REDEF. In define mode, call NF90_DEF_DIM to define new dimensions, NF90_DEF_VAR to define new variables, and NF90_PUT_ATT to assign new attributes to variables or enlarge old attributes.
You can leave define mode and reenter data mode, checking all the new definitions for consistency and committing the changes to disk, by calling NF90_ENDDEF. If you do not wish to reenter data mode, just call NF90_CLOSE, which will have the effect of first calling NF90_ENDDEF.
Until the NF90_ENDDEF call, you may back out of all the redefinitions made in define mode and restore the previous state of the netCDF dataset by calling NF90_ABORT. You may also use the NF90_ABORT call to restore the netCDF dataset to a consistent state if the call to NF90_ENDDEF fails. If you have called NF90_CLOSE from definition mode and the implied call to NF90_ENDDEF fails, NF90_ABORT will automatically be called to close the netCDF dataset and leave it in its previous consistent state (before you entered define mode).
At most one process should have a netCDF dataset open for writing at one time. The library is designed to provide limited support for multiple concurrent readers with one writer, via disciplined use of the NF90_SYNC function and the NF90_SHARE flag. If a writer makes changes in define mode, such as the addition of new variables, dimensions, or attributes, some means external to the library is necessary to prevent readers from making concurrent accesses and to inform readers to call NF90_SYNC before the next access.
The netCDF library provides the facilities needed to handle errors in a flexible way. Each netCDF function returns an integer status value. If the returned status value indicates an error, you may handle it in any way desired, from printing an associated error message and exiting to ignoring the error indication and proceeding (not recommended!). For simplicity, the examples in this guide check the error status and call a separate function to handle any errors.
The NF90_STRERROR function is available to convert a returned integer error status into an error message string.
Occasionally, low-level I/O errors may occur in a layer below the netCDF library. For example, if a write operation causes you to exceed disk quotas or to attempt to write to a device that is no longer available, you may get an error from a layer below the netCDF library, but the resulting write error will still be reflected in the returned status value.
Details of how to compile and link a program that uses the netCDF C or Fortran interfaces differ, depending on the operating system, the available compilers, and where the netCDF library and include files are installed.
Every Fortran 90 procedure or module which references netCDF constants or procedures must have access to the module information created when the netCDF module was compiled. The suffix for this file is “MOD” (or sometimes “mod”).
Most F90 compilers allow the user to specify the location of .MOD files, usually with the -I flag. (Some compilers, like Absoft, use -p instead).
f90 -c -I/usr/local/include mymodule.f90
In all netCDF versions before 3.6.2, the Fortran 77, Fortran 90, and the C libraries were all built into the same library file. That is, the libnetcdf.a file contains the C functions, the F77 functions, and the F90 functions. (The C++ library is separate.)
Starting with version 3.6.2, another method of building the netCDF Fortran libraries becomes available. With the –enable-separate-fortran option to configure, the user can specify that the C library should not contain the fortran functions. In these cases an additional library, libnetcdff.a (not the extra “f”) will be built. This library contains the fortran functions.
For more information about configure options, See Specifying the Environment for Building (The NetCDF Installation and Porting Guide).
Building separate fortran libraries is required for shared library builds, but is not done, by default, for static library builds.
When linking fortran programs without a separate fortran library, programs must link to the netCDF library like this:
f90 -o myprogram myprogram.o -L/usr/local/netcdf/lib -lnetcdf
When linking fortran programs with separate fortran, the user must link to both the fortran and the C libraries.
f90 -o myprogram myprogram.o -L/usr/local/netcdf/lib -lnetcdff -lnetcdf
Unless the netCDF library is installed in a standard directory where the linker always looks, you must use the -L and -l options to link an object file that uses the netCDF library.
This chapter presents the interfaces of the netCDF functions that deal with a netCDF dataset or the whole netCDF library.
A netCDF dataset that has not yet been opened can only be referred to by its dataset name. Once a netCDF dataset is opened, it is referred to by a netCDF ID, which is a small non-negative integer returned when you create or open the dataset. A netCDF ID is much like a file descriptor in C or a logical unit number in FORTRAN. In any single program, the netCDF IDs of distinct open netCDF datasets are distinct. A single netCDF dataset may be opened multiple times and will then have multiple distinct netCDF IDs; however at most one of the open instances of a single netCDF dataset should permit writing. When an open netCDF dataset is closed, the ID is no longer associated with a netCDF dataset.
Functions that deal with the netCDF library include:
The operations supported on a netCDF dataset as a single object are:
Each interface description for a particular netCDF function in this and later chapters contains:
The examples follow a simple convention for error handling, always checking the error status returned from each netCDF function call and calling a handle_error function in case an error was detected. For an example of such a function, see Section 5.2 "Get error message corresponding to error status: nc_strerror".
The function NF90_STRERROR returns a static reference to an error message string corresponding to an integer netCDF error status or to a system error number, presumably returned by a previous call to some other netCDF function. The list of netCDF error status codes is available in the appropriate include file for each language binding.
function nf90_strerror(ncerr) integer, intent( in) :: ncerr character(len = 80) :: nf90_strerror
NCERR
If you provide an invalid integer error status that does not correspond to any netCDF error message or or to any system error message (as understood by the system strerror function), NF90_STRERROR returns a string indicating that there is no such error status.
Here is an example of a simple error handling function that uses NF90_STRERROR to print the error message corresponding to the netCDF error status returned from any netCDF function call and then exit:
subroutine handle_err(status) integer, intent ( in) :: status if(status /= nf90_noerr) then print *, trim(nf90_strerror(status)) stop "Stopped" end if end subroutine handle_err
The function NF90_INQ_LIBVERS returns a string identifying the version of the netCDF library, and when it was built.
function nf90_inq_libvers() character(len = 80) :: nf90_inq_libvers
This function takes no arguments, and returns no error status.
Here is an example using nc_inq_libvers to print the version of the netCDF library with which the program is linked:
print *, trim(nf90_inq_libvers())
This function creates a new netCDF dataset, returning a netCDF ID that can subsequently be used to refer to the netCDF dataset in other netCDF function calls. The new netCDF dataset opened for write access and placed in define mode, ready for you to add dimensions, variables, and attributes.
A creation mode flag specifies whether to overwrite any existing dataset with the same name and whether access to the dataset is shared.
function nf90_create(path, cmode, ncid) character (len = *), intent(in ) :: path integer, intent(in ) :: cmode integer, optional, intent(in ) :: initialsize integer, optional, intent(inout) :: chunksize integer, intent( out) :: ncid integer :: nf90_create
path
cmode
Setting NF90_NOCLOBBER means you do not want to clobber (overwrite) an existing dataset; an error (NF90_EEXIST) is returned if the specified dataset already exists.
The NF90_SHARE flag is appropriate when one process may be writing the dataset and one or more other processes reading the dataset concurrently; it means that dataset accesses are not buffered and caching is limited. Since the buffering scheme is optimized for sequential access, programs that do not access data sequentially may see some performance improvement by setting the NF90_SHARE flag.
Setting NF90_64BIT_OFFSET causes netCDF to create a 64-bit offset format file, instead of a netCDF classic format file. The 64-bit offset format imposes far fewer restrictions on very large (i.e. over 2 GB) data files. See Large File Support (The NetCDF Users Guide).
A zero value (defined for convenience as NF90_CLOBBER) specifies the
default behavior: overwrite any existing dataset with the same file
name and buffer and cache accesses for efficiency. The dataset will be
in netCDF classic format. See NetCDF Classic Format Limitations (The NetCDF Users Guide).
ncid
The following optional arguments allow additional performance tuning.
initialsize
chunksize
The library chooses a system-dependent default value if NF90_SIZEHINT_DEFAULT is supplied as input. If the "preferred I/O block size" is available from the stat() system call as member st_blksize this value is used. Lacking that, twice the system pagesize is used. Lacking a call to discover the system pagesize, the default chunksize is set to 8192 bytes.
The chunksize is a property of a given open netcdf descriptor ncid, it is not a persistent property of the netcdf dataset.
NF90_CREATE returns the value NF90_NOERR if no errors occurred. Possible causes of errors include:
In this example we create a netCDF dataset named foo.nc; we want the dataset to be created in the current directory only if a dataset with that name does not already exist:
use netcdf implicit none integer :: ncid, status ... status = nf90_create(path = "foo.nc", cmode = nf90_noclobber, ncid = ncid) if (status /= nf90_noerr) call handle_err(status)
The function NF90_OPEN opens an existing netCDF dataset for access.
function nf90_open(path, mode, ncid, chunksize) character (len = *), intent(in ) :: path integer, intent(in ) :: mode integer, intent( out) :: ncid integer, optional, intent(inout) :: chunksize integer :: nf90_open
path
mode
Otherwise, the creation mode is NF90_WRITE, NF90_SHARE, or
NF90_WRITE|NF90_SHARE. Setting the NF90_WRITE flag opens the dataset with
read-write access. ("Writing" means any kind of change to the dataset,
including appending or changing data, adding or renaming dimensions,
variables, and attributes, or deleting attributes.) The NF90_SHARE flag
is appropriate when one process may be writing the dataset and one or
more other processes reading the dataset concurrently; it means that
dataset accesses are not buffered and caching is limited. Since the
buffering scheme is optimized for sequential access, programs that do
not access data sequentially may see some performance improvement by
setting the NF90_SHARE flag.
ncid
The following optional argument allows additional performance tuning.
chunksize
The library chooses a system-dependent default value if NF90_SIZEHINT_DEFAULT is supplied as input. If the "preferred I/O block size" is available from the stat() system call as member st_blksize this value is used. Lacking that, twice the system pagesize is used. Lacking a call to discover the system pagesize, the default chunksize is set to 8192 bytes.
The chunksize is a property of a given open netcdf descriptor ncid, it is not a persistent property of the netcdf dataset.
NF90_OPEN returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_OPEN to open an existing netCDF dataset named foo.nc for read-only, non-shared access:
use netcdf implicit none integer :: ncid, status ... status = nf90_open(path = "foo.nc", cmode = nf90_nowrite, ncid = ncid) if (status /= nf90_noerr) call handle_err(status)
The function NF90_REDEF puts an open netCDF dataset into define mode, so dimensions, variables, and attributes can be added or renamed and attributes can be deleted.
function nf90_redef(ncid) integer, intent( in) :: ncid integer :: nf90_redef
ncid
NF90_REDEF returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_REDEF to open an existing netCDF dataset named foo.nc and put it into define mode:
use netcdf implicit none integer :: ncid, status ... status = nf90_open("foo.nc", nf90_write, ncid) ! Open dataset if (status /= nf90_noerr) call handle_err(status) ... status = nf90_redef(ncid) ! Put the file in define mode if (status /= nf90_noerr) call handle_err(status)
The function NF90_ENDDEF takes an open netCDF dataset out of define mode. The changes made to the netCDF dataset while it was in define mode are checked and committed to disk if no problems occurred. Non-record variables may be initialized to a "fill value" as well (see NF90_SET_FILL). The netCDF dataset is then placed in data mode, so variable data can be read or written.
This call may involve copying data under some circumstances. For a more extensive discussion See File Structure and Performance (The NetCDF Users Guide).
function nf90_enddef(ncid, h_minfree, v_align, v_minfree, r_align) integer, intent( in) :: ncid integer, optional, intent( in) :: h_minfree, v_align, v_minfree, r_align integer :: nf90_enddef
ncid
The following arguments allow additional performance tuning. Note: these arguments expose internals of the netcdf version 1 file format, and may not be available in future netcdf implementations.
The current netcdf file format has three sections: the "header" section, the data section for fixed size variables, and the data section for variables which have an unlimited dimension (record variables). The header begins at the beginning of the file. The index (offset) of the beginning of the other two sections is contained in the header. Typically, there is no space between the sections. This causes copying overhead to accrue if one wishes to change the size of the sections, as may happen when changing the names of things, text attribute values, adding attributes or adding variables. Also, for buffered i/o, there may be advantages to aligning sections in certain ways.
h_minfree
v_minfree
v_align
r_align
NF90_ENDDEF returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_ENDDEF to finish the definitions of a new netCDF dataset named foo.nc and put it into data mode:
use netcdf implicit none integer :: ncid, status ... status = nf90_create("foo.nc", nf90_noclobber, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! create dimensions, variables, attributes status = nf90_enddef(ncid) if (status /= nf90_noerr) call handle_err(status)
The function NF90_CLOSE closes an open netCDF dataset. If the dataset is in define mode, NF90_ENDDEF will be called before closing. (In this case, if NF90_ENDDEF returns an error, NF90_ABORT will automatically be called to restore the dataset to the consistent state before define mode was last entered.) After an open netCDF dataset is closed, its netCDF ID may be reassigned to the next netCDF dataset that is opened or created.
function nf90_close(ncid) integer, intent( in) :: ncid integer :: nf90_close
ncid
NF90_CLOSE returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_CLOSE to finish the definitions of a new netCDF dataset named foo.nc and release its netCDF ID:
use netcdf implicit none integer :: ncid, status ... status = nf90_create("foo.nc", nf90_noclobber, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! create dimensions, variables, attributes status = nf90_close(ncid) if (status /= nf90_noerr) call handle_err(status)
The NF90_INQUIRE subroutine returns information about an open netCDF dataset, given its netCDF ID. The subroutine can be called from either define mode or data mode, and returns values for any or all of the following: the number of dimensions, the number of variables, the number of global attributes, and the dimension ID of the dimension defined with unlimited length, if any. An additional function, NF90_INQ_FORMAT, returns the (rarely needed) format version.
No I/O is performed when NF90_INQUIRE is called, since the required information is available in memory for each open netCDF dataset.
function nf90_inquire(ncid, nDimensions, nVariables, nAttributes, & unlimitedDimId, formatNum) integer, intent( in) :: ncid integer, optional, intent(out) :: nDimensions, nVariables, & nAttributes, unlimitedDimId, & formatNum integer :: nf90_inquire
ncid
nDimensions
nVariables
nAttributes
unlimitedDimID
format
Function NF90_INQUIRE returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_INQUIRE to find out about a netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, nDims, nVars, nGlobalAtts, unlimDimID ... status = nf90_open("foo.nc", nf90_nowrite, ncid) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_inquire(ncid, nDims, nVars, nGlobalAtts, unlimdimid) if (status /= nf90_noerr) call handle_err(status) status = nf90_inquire(ncid, nDimensions = nDims, & unlimitedDimID = unlimdimid) if (status /= nf90_noerr) call handle_err(status)
The function NF90_SYNC offers a way to synchronize the disk copy of a netCDF dataset with in-memory buffers. There are two reasons you might want to synchronize after writes:
This function is backward-compatible with previous versions of the netCDF library. The intent was to allow sharing of a netCDF dataset among multiple readers and one writer, by having the writer call NF90_SYNC after writing and the readers call NF90_SYNC before each read. For a writer, this flushes buffers to disk. For a reader, it makes sure that the next read will be from disk rather than from previously cached buffers, so that the reader will see changes made by the writing process (e.g., the number of records written) without having to close and reopen the dataset. If you are only accessing a small amount of data, it can be expensive in computer resources to always synchronize to disk after every write, since you are giving up the benefits of buffering.
An easier way to accomplish sharing (and what is now recommended) is to have the writer and readers open the dataset with the NF90_SHARE flag, and then it will not be necessary to call NF90_SYNC at all. However, the NF90_SYNC function still provides finer granularity than the NF90_SHARE flag, if only a few netCDF accesses need to be synchronized among processes.
It is important to note that changes to the ancillary data, such as attribute values, are not propagated automatically by use of the NF90_SHARE flag. Use of the NF90_SYNC function is still required for this purpose.
Sharing datasets when the writer enters define mode to change the data schema requires extra care. In previous releases, after the writer left define mode, the readers were left looking at an old copy of the dataset, since the changes were made to a new copy. The only way readers could see the changes was by closing and reopening the dataset. Now the changes are made in place, but readers have no knowledge that their internal tables are now inconsistent with the new dataset schema. If netCDF datasets are shared across redefinition, some mechanism external to the netCDF library must be provided that prevents access by readers during redefinition and causes the readers to call NF90_SYNC before any subsequent access.
When calling NF90_SYNC, the netCDF dataset must be in data mode. A netCDF dataset in define mode is synchronized to disk only when NF90_ENDDEF is called. A process that is reading a netCDF dataset that another process is writing may call NF90_SYNC to get updated with the changes made to the data by the writing process (e.g., the number of records written), without having to close and reopen the dataset.
Data is automatically synchronized to disk when a netCDF dataset is closed, or whenever you leave define mode.
function nf90_sync(ncid) integer, intent( in) :: ncid integer :: nf90_sync
ncid
NF90_SYNC returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_SYNC to synchronize the disk writes of a netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status ... status = nf90_open("foo.nc", nf90_write, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! write data or change attributes ... status = NF90_SYNC(ncid) if (status /= nf90_noerr) call handle_err(status)
You no longer need to call this function, since it is called automatically by NF90_CLOSE in case the dataset is in define mode and something goes wrong with committing the changes. The function NF90_ABORT just closes the netCDF dataset, if not in define mode. If the dataset is being created and is still in define mode, the dataset is deleted. If define mode was entered by a call to NF90_REDEF, the netCDF dataset is restored to its state before definition mode was entered and the dataset is closed.
function nf90_abort(ncid) integer, intent( in) :: ncid integer :: nf90_abort
ncid
NF90_ABORT returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_ABORT to back out of redefinitions of a dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, LatDimID ... status = nf90_open("foo.nc", nf90_write, ncid) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_redef(ncid) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_def_dim(ncid, "Lat", 18, LatDimID) if (status /= nf90_noerr) then ! Dimension definition failed call handle_err(status) status = nf90_abort(ncid) ! Abort redefinitions if (status /= nf90_noerr) call handle_err(status) end if ...
This function is intended for advanced usage, to optimize writes under some circumstances described below. The function NF90_SET_FILL sets the fill mode for a netCDF dataset open for writing and returns the current fill mode in a return parameter. The fill mode can be specified as either NF90_FILL or NF90_NOFILL. The default behavior corresponding to NF90_FILL is that data is pre-filled with fill values, that is fill values are written when you create non-record variables or when you write a value beyond data that has not yet been written. This makes it possible to detect attempts to read data before it was written. See Fill Values, for more information on the use of fill values. See Attribute Conventions, for information about how to define your own fill values.
The behavior corresponding to NF90_NOFILL overrides the default behavior of prefilling data with fill values. This can be used to enhance performance, because it avoids the duplicate writes that occur when the netCDF library writes fill values that are later overwritten with data.
A value indicating which mode the netCDF dataset was already in is returned. You can use this value to temporarily change the fill mode of an open netCDF dataset and then restore it to the previous mode.
After you turn on NF90_NOFILL mode for an open netCDF dataset, you must be certain to write valid data in all the positions that will later be read. Note that nofill mode is only a transient property of a netCDF dataset open for writing: if you close and reopen the dataset, it will revert to the default behavior. You can also revert to the default behavior by calling NF90_SET_FILL again to explicitly set the fill mode to NF90_FILL.
There are three situations where it is advantageous to set nofill mode:
If the netCDF dataset has an unlimited dimension and the last record was written while in nofill mode, then the dataset may be shorter than if nofill mode was not set, but this will be completely transparent if you access the data only through the netCDF interfaces.
The use of this feature may not be available (or even needed) in future releases. Programmers are cautioned against heavy reliance upon this feature.
function nf90_set_fill(ncid, fillmode, old_mode) integer, intent( in) :: ncid, fillmode integer, intent(out) :: old_mode integer :: nf90_set_fill
ncid
fillmode
old_mode
NF90_SET_FILL returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_SET_FILL to set nofill mode for subsequent writes of a netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, oldMode ... status = nf90_open("foo.nc", nf90_write, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! Write data with prefilling behavior ... status = nf90_set_fill(ncid, nf90_nofill, oldMode) if (status /= nf90_noerr) call handle_err(status) ... ! Write data with no prefilling ...
Dimensions for a netCDF dataset are defined when it is created, while the netCDF dataset is in define mode. Additional dimensions may be added later by reentering define mode. A netCDF dimension has a name and a length. At most one dimension in a netCDF dataset can have the unlimited length, which means variables using this dimension can grow along this dimension.
There is a suggested limit (512) to the number of dimensions that can be defined in a single netCDF dataset. The limit is the value of the constant NF90_MAX_DIMS. The purpose of the limit is to make writing generic applications simpler. They need only provide an array of NF90_MAX_DIMS dimensions to handle any netCDF dataset. The implementation of the netCDF library does not enforce this advisory maximum, so it is possible to use more dimensions, if necessary, but netCDF utilities that assume the advisory maximums may not be able to handle the resulting netCDF datasets.
Ordinarily, the name and length of a dimension are fixed when the dimension is first defined. The name may be changed later, but the length of a dimension (other than the unlimited dimension) cannot be changed without copying all the data to a new netCDF dataset with a redefined dimension length.
A netCDF dimension in an open netCDF dataset is referred to by a small integer called a dimension ID. In the Fortran 90 interface, dimension IDs are 1, 2, 3, ..., in the order in which the dimensions were defined.
Operations supported on dimensions are:
The function NF90_DEF_DIM adds a new dimension to an open netCDF dataset in define mode. It returns (as an argument) a dimension ID, given the netCDF ID, the dimension name, and the dimension length. At most one unlimited length dimension, called the record dimension, may be defined for each netCDF dataset.
function nf90_def_dim(ncid, name, len, dimid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent( in) :: len integer, intent(out) :: dimid integer :: nf90_def_dim
ncid
name
len
dimid
NF90_DEF_DIM returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_DEF_DIM to create a dimension named lat of length 18 and a unlimited dimension named rec in a new netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, LatDimID, RecordDimID ... status = nf90_create("foo.nc", nf90_noclobber, ncid) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_def_dim(ncid, "Lat", 18, LatDimID) if (status /= nf90_noerr) call handle_err(status) status = nf90_def_dim(ncid, "Record", nf90_unlimited, RecordDimID) if (status /= nf90_noerr) call handle_err(status)
The function NF90_INQ_DIMID returns (as an argument) the ID of a netCDF dimension, given the name of the dimension. If ndims is the number of dimensions defined for a netCDF dataset, each dimension has an ID between 1 and ndims.
function nf90_inq_dimid(ncid, name, dimid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent(out) :: dimid integer :: nf90_inq_dimid
ncid
name
dimid
NF90_INQ_DIMID returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_INQ_DIMID to determine the dimension ID of a dimension named lat, assumed to have been defined previously in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, LatDimID ... status = nf90_open("foo.nc", nf90_nowrite, ncid) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_inq_dimid(ncid, "Lat", LatDimID) if (status /= nf90_noerr) call handle_err(status)
This function information about a netCDF dimension. Information about a dimension includes its name and its length. The length for the unlimited dimension, if any, is the number of records written so far.
function nf90_inquire_dimension(ncid, dimid, name, len) integer, intent( in) :: ncid, dimid character (len = *), optional, intent(out) :: name integer, optional, intent(out) :: len integer :: nf90_inquire_dimension
ncid
dimid
name
len
These functions return the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_INQ_DIM to determine the length of a dimension named lat, and the name and current maximum length of the unlimited dimension for an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, LatDimID, RecordDimID integer :: nLats, nRecords character(len = nf90_max_name) :: RecordDimName ... status = nf90_open("foo.nc", nf90_nowrite, ncid) if (status /= nf90_noerr) call handle_err(status) ! Get ID of unlimited dimension status = nf90_inquire(ncid, unlimitedDimId = RecordDimID) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_inq_dimid(ncid, "Lat", LatDimID) if (status /= nf90_noerr) call handle_err(status) ! How many values of "lat" are there? status = nf90_inquire_dimension(ncid, LatDimID, len = nLats) if (status /= nf90_noerr) call handle_err(status) ! What is the name of the unlimited dimension, how many records are there? status = nf90_inquire_dimension(ncid, RecordDimID, & name = RecordDimName, len = Records) if (status /= nf90_noerr) call handle_err(status)
The function NF90_RENAME_DIM renames an existing dimension in a netCDF dataset open for writing. If the new name is longer than the old name, the netCDF dataset must be in define mode. You cannot rename a dimension to have the same name as another dimension.
function nf90_rename_dim(ncid, dimid, name) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent( in) :: dimid integer :: nf90_rename_dim
ncid
dimid
name
NF90_RENAME_DIM returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_RENAME_DIM to rename the dimension lat to latitude in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, LatDimID ... status = nf90_open("foo.nc", nf90_write, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! Put in define mode so we can rename the dimension status = nf90_redef(ncid) if (status /= nf90_noerr) call handle_err(status) ! Get the dimension ID for "Lat"... status = nf90_inq_dimid(ncid, "Lat", LatDimID) if (status /= nf90_noerr) call handle_err(status) ! ... and change the name to "Latitude". status = nf90_rename_dim(ncid, LatDimID, "Latitude") if (status /= nf90_noerr) call handle_err(status) ! Leave define mode status = nf90_enddef(ncid) if (status /= nf90_noerr) call handle_err(status)
Variables for a netCDF dataset are defined when the dataset is created, while the netCDF dataset is in define mode. Other variables may be added later by reentering define mode. A netCDF variable has a name, a type, and a shape, which are specified when it is defined. A variable may also have values, which are established later in data mode.
Ordinarily, the name, type, and shape are fixed when the variable is first defined. The name may be changed, but the type and shape of a variable cannot be changed. However, a variable defined in terms of the unlimited dimension can grow without bound in that dimension.
A netCDF variable in an open netCDF dataset is referred to by a small integer called a variable ID.
Variable IDs reflect the order in which variables were defined within a netCDF dataset. Variable IDs are 1, 2, 3,..., in the order in which the variables were defined. A function is available for getting the variable ID from the variable name and vice-versa.
Attributes (see Attributes) may be associated with a variable to specify such properties as units.
Operations supported on variables are:
The following table gives the netCDF external data types and the corresponding type constants for defining variables in the FORTRAN interface:
| Type | FORTRAN API Mnemonic | Bits
|
| byte | NF90_BYTE | 8
|
| char | NF90_CHAR | 8
|
| short | NF90_SHORT | 16
|
| int | NF90_INT | 32
|
| float | NF90_FLOAT | 32
|
| double | NF90_DOUBLE | 64
|
The first column gives the netCDF external data type, which is the same as the CDL data type. The next column gives the corresponding Fortran 90 parameter for use in netCDF functions (the parameters are defined in the netCDF Fortran 90 module netcdf.f90). The last column gives the number of bits used in the external representation of values of the corresponding type.
Note that there are no netCDF types corresponding to 64-bit integers or to characters wider than 8 bits in the current version of the netCDF library.
NF90_DEF_VAR
The function NF90_DEF_VAR adds a new variable to an open netCDF dataset in define mode. It returns (as an argument) a variable ID, given the netCDF ID, the variable name, the variable type, the number of dimensions, and a list of the dimension IDs.
function nf90_def_var(ncid, name, xtype, dimids, varid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent( in) :: xtype integer, dimension(:), intent( in) :: dimids integer, intent(out) :: varid integer :: nf90_def_var
ncid
name
xtype
dimids
varid
NF90_DEF_VAR returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_DEF_VAR to create a variable named rh of type double with three dimensions, time, lat, and lon in a new netCDF dataset named foo.nc:
use netcdf implicit none integer :: status, ncid integer :: LonDimId, LatDimId, TimeDimId integer :: RhVarId ... status = nf90_create("foo.nc", nf90_NoClobber, ncid) if(status /= nf90_NoErr) call handle_error(status) ... !  Define the variable status = nf90_def_var(ncid, "rh", nf90_double, & (/ LonDimId, LatDimID, TimeDimID /), RhVarId) if(status /= nf90_NoErr) call handle_error(status)
The function NF90_INQ_VARID returns the ID of a netCDF variable, given its name.
function nf90_inq_varid(ncid, name, varid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent(out) :: varid integer :: nf90_inq_varid
ncid
name
varid
NF90_INQ_VARID returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_INQ_VARID to find out the ID of a variable named rh in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: status, ncid, RhVarId ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", RhVarId) if(status /= nf90_NoErr) call handle_err(status)
NF90_INQUIRE_VARIABLE returns information about a netCDF variable given its ID. Information about a variable includes its name, type, number of dimensions, a list of dimension IDs describing the shape of the variable, and the number of variable attributes that have been assigned to the variable.
function nf90_inquire_variable(ncid, varid, name, xtype, ndims, dimids, nAtts) integer, intent( in) :: ncid, varid character (len = *), optional, intent(out) :: name integer, optional, intent(out) :: xtype, ndims integer, dimension(*), optional, intent(out) :: dimids integer, optional, intent(out) :: nAtts integer :: nf90_inquire_variable
ncid
varid
name
xtype
ndims
dimids
nAtts
These functions return the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_INQ_VAR to find out about a variable named rh in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: status, ncid, & RhVarId & numDims, numAtts integer, dimension(nf90_max_var_dims) :: rhDimIds ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_error(status) ... status = nf90_inq_varid(ncid, "rh", RhVarId) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_variable(ncid, RhVarId, ndims = numDims, natts = numAtts) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_variable(ncid, RhVarId, dimids = rhDimIds(:numDims)) if(status /= nf90_NoErr) call handle_err(status)
The function NF90_PUT_VAR puts one or more data values into the variable of an open netCDF dataset that is in data mode. Required inputs are the netCDF ID, the variable ID, and one or more data values. Optional inputs may indicate the starting position of the data values in the netCDF variable (argument start), the sampling frequency with which data values are written into the netCDF variable (argument stride), and a mapping between the dimensions of the data array and the netCDF variable (argument map). The values to be written are associated with the netCDF variable by assuming that the first dimension of the netCDF variable varies fastest in the Fortran 90 interface. Data values converted to the external type of the variable, if necessary.
Take care when using the simplest forms of this interface with record variables when you don't specify how many records are to be written. If you try to write all the values of a record variable into a netCDF file that has no record data yet (hence has 0 records), nothing will be written. Similarly, if you try to write all of a record variable but there are more records in the file than you assume, more data may be written to the file than you supply, which may result in a segmentation violation.
function nf90_put_var(ncid, varid, values, start, count, stride, map) integer, intent( in) :: ncid, varid any valid type, scalar or array of any rank, & intent( in) :: values integer, dimension(:), optional, intent( in) :: start, count, stride, map integer :: nf90_put_var
ncid
varid
values
start
By default, start(:) = 1.
count
By default, count(:numDims) = shape(values) and
count(numDims + 1:) = 1, where numDims = size(shape(values)).
stride
By default, stride(:) = 1.
imap
By default, edgeLengths = shape(values), and map = (/ 1, (product(edgeLengths(:i)), i = 1, size(edgeLengths) - 1) /), that is, there is no mapping.
Use of Fortran 90 intrinsic functions (including reshape, transpose, and spread) may let you avoid using this argument.
NF90_PUT_VAR1_ type returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_PUT_VAR to set the (4,3,2) element of the variable named rh to 0.5 in an existing netCDF dataset named foo.nc. For simplicity in this example, we assume that we know that rh is dimensioned with lon, lat, and time, so we want to set the value of rh that corresponds to the fourth lon value, the third lat value, and the second time value:
use netcdf implicit none integer :: ncId, rhVarId, status ... status = nf90_open("foo.nc", nf90_Write, ncid) if(status /= nf90_NoErr) call handle_err(status) ...ß status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) status = nf90_put_var(ncid, rhVarId, 0.5, start = (/ 4, 3, 2 /) ) if(status /= nf90_NoErr) call handle_err(status)
In this example we use NF90_PUT_VAR to add or change all the values of the variable named rh to 0.5 in an existing netCDF dataset named foo.nc. We assume that we know that rh is dimensioned with lon, lat, and time. In this example we query the netCDF file to discover the lengths of the dimensions, then use the Fortran 90 intrinsic function reshape to create a temporary array of data values which is the same shape as the netCDF variable.
use netcdf implicit none integer :: ncId, rhVarId,status, & lonDimID, latDimId, timeDimId, & numLons, numLats, numTimes, & i integer, dimension(nf90_max_var_dims) :: dimIDs ... status = nf90_open("foo.nc", nf90_Write, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ! How big is the netCDF variable, that is, what are the lengths of ! its constituent dimensions? status = nf90_inquire_variable(ncid, rhVarId, dimids = dimIDs) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_dimension(ncid, dimIDs(1), len = numLons) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_dimension(ncid, dimIDs(2), len = numLats) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_dimension(ncid, dimIDs(3), len = numTimes) if(status /= nf90_NoErr) call handle_err(status) ... ! Make a temporary array the same shape as the netCDF variable. status = nf90_put_var(ncid, rhVarId, & reshape( & (/ (0.5, i = 1, numLons * numLats * numTimes) /) , & shape = (/ numLons, numLats, numTimes /) ) if(status /= nf90_NoErr) call handle_err(status)
Here is an example using NF90_PUT_VAR to add or change a section of the variable named rh to 0.5 in an existing netCDF dataset named foo.nc. For simplicity in this example, we assume that we know that rh is dimensioned with lon, lat, and time, that there are ten lon values, five lat values, and three time values, and that we want to replace all the values at the last time.
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 10, numLats = 5, numTimes = 3 real, dimension(numLons, numLats) & :: rhValues ... status = nf90_open("foo.nc", nf90_Write, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ! Fill in all values at the last time rhValues(:, :) = 0.5 status = nf90_put_var(ncid, rhVarId,rhvalues, & start = (/ 1, 1, numTimes /), & count = (/ numLats, numLons, 1 /)) if(status /= nf90_NoErr) call handle_err(status)
Here is an example of using NF_PUT_VAR to write every other point of a netCDF variable named rh having dimensions (6, 4).
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 6, numLats = 4 real, dimension(numLons, numLats) & :: rhValues = 0.5 ... status = nf90_open("foo.nc", nf90_Write, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ... ! Fill in every other value using an array section status = nf90_put_var(ncid, rhVarId, rhValues(::2, ::2), & stride = (/ 2, 2 /)) if(status /= nf90_NoErr) call handle_err(status)
The following map vector shows the default mapping between a 2x3x4 netCDF variable and an internal array of the same shape:
real, dimension(2, 3, 4):: a ! same shape as netCDF variable integer, dimension(3) :: map = (/ 1, 2, 6 /) ! netCDF dimension inter-element distance ! ---------------- ---------------------- ! most rapidly varying 1 ! intermediate 2 (= map(1)*2) ! most slowly varying 6 (= map(2)*3)
Using the map vector above obtains the same result as simply not passing a map vector at all.
Here is an example of using nf90_put_var to write a netCDF variable named rh whose dimensions are the transpose of the Fortran 90 array:
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 6, numLats = 4 real, dimension(numLons, numLats) :: rhValues ! netCDF variable has dimensions (numLats, numLons) ... status = nf90_open("foo.nc", nf90_Write, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ... !Write transposed values: map vector would be (/ 1, numLats /) for ! no transposition status = nf90_put_var(ncid, rhVarId,rhValues, map = (/ numLons, 1 /)) if(status /= nf90_NoErr) call handle_err(status)
The same effect can be obtained more simply using Fortran 90 intrinsic functions:
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 6, numLats = 4 real, dimension(numLons, numLats) :: rhValues ! netCDF variable has dimensions (numLats, numLons) ... status = nf90_open("foo.nc", nf90_Write, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_put_var(ncid, rhVarId, transpose(rhValues)) if(status /= nf90_NoErr) call handle_err(status)
The function NF90_GET_VAR gets one or more data values from a netCDF variable of an open netCDF dataset that is in data mode. Required inputs are the netCDF ID, the variable ID, and a specification for the data values into which the data will be read. Optional inputs may indicate the starting position of the data values in the netCDF variable (argument start), the sampling frequency with which data values are read from the netCDF variable (argument stride), and a mapping between the dimensions of the data array and the netCDF variable (argument map). The values to be read are associated with the netCDF variable by assuming that the first dimension of the netCDF variable varies fastest in the Fortran 90 interface. Data values are converted from the external type of the variable, if necessary.
Take care when using the simplest forms of this interface with record variables when you don't specify how many records are to be read. If you try to read all the values of a record variable into an array but there are more records in the file than you assume, more data will be read than you expect, which may cause a segmentation violation.
function nf90_get_var(ncid, varid, values, start, count, stride, map) integer, intent( in) :: ncid, varid any valid type, scalar or array of any rank, & intent(out) :: values integer, dimension(:), optional, intent( in) :: start, count, stride, map integer :: nf90_get_var
ncid
varid
values
start
By default, start(:) = 1.
count
By default, count(:numDims) = shape(values) and
count(numDims + 1:) = 1, where numDims = size(shape(values)).
stride
By default, stride(:) = 1.
map
By default, edgeLengths = shape(values), and map = (/ 1, (product(edgeLengths(:i)), i = 1, size(edgeLengths) - 1) /), that is, there is no mapping.
Use of Fortran 90 intrinsic functions (including reshape, transpose, and spread) may let you avoid using this argument.
NF90_GET_VAR returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
(As noted above, another possible source of error is using this interface to read all the values of a record variable without specifying the number of records. If there are more records in the file than you assume, more data will be read than you expect!)
Here is an example using NF90_GET_VAR to read the (4,3,2) element of the variable named rh from an existing netCDF dataset named foo.nc. For simplicity in this example, we assume that we know that rh is dimensioned with lon, lat, and time, so we want to read the value of rh that corresponds to the fourth lon value, the third lat value, and the second time value:
use netcdf implicit none integer :: ncId, rhVarId, status real :: rhValue ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_err(status) - status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) status = nf90_get_var(ncid, rhVarId, rhValue, start = (/ 4, 3, 2 /) ) if(status /= nf90_NoErr) call handle_err(status)
In this example we use NF90_GET_VAR to read all the values of the variable named rh from an existing netCDF dataset named foo.nc. We assume that we know that rh is dimensioned with lon, lat, and time. In this example we query the netCDF file to discover the lengths of the dimensions, then allocate a Fortran 90 array the same shape as the netCDF variable.
use netcdf implicit none integer :: ncId, rhVarId, & lonDimID, latDimId, timeDimId, & numLons, numLats, numTimes, & status integer, dimension(nf90_max_var_dims) :: dimIDs real, dimension(:, :, :), allocatable :: rhValues ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ! How big is the netCDF variable, that is, what are the lengths of ! its constituent dimensions? status = nf90_inquire_variable(ncid, rhVarId, dimids = dimIDs) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_dimension(ncid, dimIDs(1), len = numLons) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_dimension(ncid, dimIDs(2), len = numLats) if(status /= nf90_NoErr) call handle_err(status) status = nf90_inquire_dimension(ncid, dimIDs(3), len = numTimes) if(status /= nf90_NoErr) call handle_err(status) allocate(rhValues(numLons, numLats, numTimes)) ... status = nf90_get_var(ncid, rhVarId, rhValues) if(status /= nf90_NoErr) call handle_err(status)
Here is an example using NF90_GET_VAR to read a section of the variable named rh from an existing netCDF dataset named foo.nc. For simplicity in this example, we assume that we know that rh is dimensioned with lon, lat, and time, that there are ten lon values, five lat values, and three time values, and that we want to replace all the values at the last time.
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 10, numLats = 5, numTimes = 3 real, dimension(numLons, numLats, numTimes) & :: rhValues ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) !Read the values at the last time by passing an array section status = nf90_get_var(ncid, rhVarId, rhValues(:, :, 3), & start = (/ 1, 1, numTimes /), & count = (/ numLats, numLons, 1 /)) if(status /= nf90_NoErr) call handle_err(status)
Here is an example of using NF_GET_VAR to read every other point of a netCDF variable named rh having dimensions (6, 4).
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 6, numLats = 4 real, dimension(numLons, numLats) & :: rhValues ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ... ! Read every other value into an array section status = nf90_get_var(ncid, rhVarId, rhValues(::2, ::2) & stride = (/ 2, 2 /)) if(status /= nf90_NoErr) call handle_err(status)
The following map vector shows the default mapping between a 2x3x4 netCDF variable and an internal array of the same shape:
real, dimension(2, 3, 4):: a ! same shape as netCDF variable integer, dimension(3) :: map = (/ 1, 2, 6 /) ! netCDF dimension inter-element distance ! ---------------- ---------------------- ! most rapidly varying 1 ! intermediate 2 (= map(1)*2) ! most slowly varying 6 (= map(2)*3)
Using the map vector above obtains the same result as simply not passing a map vector at all.
Here is an example of using nf90_get_var to read a netCDF variable named rh whose dimensions are the transpose of the Fortran 90 array:
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 6, numLats = 4 real, dimension(numLons, numLats) :: rhValues ! netCDF variable has dimensions (numLats, numLons) ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ... ! Read transposed values: map vector would be (/ 1, numLats /) for ! no transposition status = nf90_get_var(ncid, rhVarId,rhValues, map = (/ numLons, 1 /)) if(status /= nf90_NoErr) call handle_err(status)
The same effect can be obtained more simply, though using more memory, using Fortran 90 intrinsic functions:
use netcdf implicit none integer :: ncId, rhVarId, status integer, parameter :: numLons = 6, numLats = 4 real, dimension(numLons, numLats) :: rhValues ! netCDF variable has dimensions (numLats, numLons) real, dimension(numLons, numLats) :: tempValues ... status = nf90_open("foo.nc", nf90_NoWrite, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_get_var(ncid, rhVarId, tempValues)) if(status /= nf90_NoErr) call handle_err(status) rhValues(:, :) = transpose(tempValues)
Character strings are not a primitive netCDF external data type, in part because FORTRAN does not support the abstraction of variable-length character strings (the FORTRAN LEN function returns the static length of a character string, not its dynamic length). As a result, a character string cannot be written or read as a single object in the netCDF interface. Instead, a character string must be treated as an array of characters, and array access must be used to read and write character strings as variable data in netCDF datasets. Furthermore, variable-length strings are not supported by the netCDF interface except by convention; for example, you may treat a zero byte as terminating a character string, but you must explicitly specify the length of strings to be read from and written to netCDF variables.
Character strings as attribute values are easier to use, since the strings are treated as a single unit for access. However, the value of a character-string attribute is still an array of characters with an explicit length that must be specified when the attribute is defined.
When you define a variable that will have character-string values, use a character-position dimension as the most quickly varying dimension for the variable (the first dimension for the variable in Fortran 90). The length of the character-position dimension will be the maximum string length of any value to be stored in the character-string variable. Space for maximum-length strings will be allocated in the disk representation of character-string variables whether you use the space or not. If two or more variables have the same maximum length, the same character-position dimension may be used in defining the variable shapes.
To write a character-string value into a character-string variable, use either entire variable access or array access. The latter requires that you specify both a corner and a vector of edge lengths. The character-position dimension at the corner should be one for Fortran 90. If the length of the string to be written is n, then the vector of edge lengths will specify n in the character-position dimension, and one for all the other dimensions: (n, 1, 1, ..., 1).
In Fortran 90, fixed-length strings may be written to a netCDF dataset without a terminating character, to save space. Variable-length strings should follow the C convention of writing strings with a terminating zero byte so that the intended length of the string can be determined when it is later read by either C or Fortran 90 programs.
What happens when you try to read a value that was never written in an open netCDF dataset? You might expect that this should always be an error, and that you should get an error message or an error status returned. You do get an error if you try to read data from a netCDF dataset that is not open for reading, if the variable ID is invalid for the specified netCDF dataset, or if the specified indices are not properly within the range defined by the dimension lengths of the specified variable. Otherwise, reading a value that was not written returns a special fill value used to fill in any undefined values when a netCDF variable is first written.
You may ignore fill values and use the entire range of a netCDF external data type, but in this case you should make sure you write all data values before reading them. If you know you will be writing all the data before reading it, you can specify that no prefilling of variables with fill values will occur by calling writing. This may provide a significant performance gain for netCDF writes.
The variable attribute _FillValue may be used to specify the fill value for a variable. There are default fill values for each type, defined in module netcdf: NF90_FILL_CHAR, NF90_FILL_INT1 (same as NF90_FILL_BYTE), NF90_FILL_INT2 (same as NF90_FILL_SHORT), NF90_FILL_INT, NF90_FILL_REAL (same as NF90_FILL_FLOAT), and NF90_FILL_DOUBLE
The netCDF byte and character types have different default fill values. The default fill value for characters is the zero byte, a useful value for detecting the end of variable-length C character strings. If you need a fill value for a byte variable, it is recommended that you explicitly define an appropriate _FillValue attribute, as generic utilities such as ncdump will not assume a default fill value for byte variables.
Type conversion for fill values is identical to type conversion for other values: attempting to convert a value from one type to another type that can't represent the value results in a range error. Such errors may occur on writing or reading values from a larger type (such as double) to a smaller type (such as float), if the fill value for the larger type cannot be represented in the smaller type.
The function NF90_RENAME_VAR changes the name of a netCDF variable in an open netCDF dataset. If the new name is longer than the old name, the netCDF dataset must be in define mode. You cannot rename a variable to have the name of any existing variable.
function nf90_rename_var(ncid, varid, newname) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: newname integer :: nf90_rename_var
ncid
varid
newname
NF90_RENAME_VAR returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_RENAME_VAR to rename the variable rh to rel_hum in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncId, rhVarId, status ... status = nf90_open("foo.nc", nf90_Write, ncid) if(status /= nf90_NoErr) call handle_err(status) ... status = nf90_inq_varid(ncid, "rh", rhVarId) if(status /= nf90_NoErr) call handle_err(status) status = nf90_redef(ncid) ! Enter define mode to change variable name if(status /= nf90_NoErr) call handle_err(status) status = nf90_rename_var(ncid, rhVarId, "rel_hum") if(status /= nf90_NoErr) call handle_err(status) status = nf90_enddef(ncid) ! Leave define mode if(status /= nf90_NoErr) call handle_err(status)
Attributes may be associated with each netCDF variable to specify such properties as units, special values, maximum and minimum valid values, scaling factors, and offsets. Attributes for a netCDF dataset are defined when the dataset is first created, while the netCDF dataset is in define mode. Additional attributes may be added later by reentering define mode. A netCDF attribute has a netCDF variable to which it is assigned, a name, a type, a length, and a sequence of one or more values. An attribute is designated by its variable ID and name. When an attribute name is not known, it may be designated by its variable ID and number in order to determine its name, using the function NF90_INQ_ATTNAME.
The attributes associated with a variable are typically defined immediately after the variable is created, while still in define mode. The data type, length, and value of an attribute may be changed even when in data mode, as long as the changed attribute requires no more space than the attribute as originally defined.
It is also possible to have attributes that are not associated with any variable. These are called global attributes and are identified by using NF90_GLOBAL as a variable pseudo-ID. Global attributes are usually related to the netCDF dataset as a whole and may be used for purposes such as providing a title or processing history for a netCDF dataset.
Operations supported on attributes are:
Names commencing with underscore ('_') are reserved for use by the netCDF library. Most generic applications that process netCDF datasets assume standard attribute conventions and it is strongly recommended that these be followed unless there are good reasons for not doing so. Below we list the names and meanings of recommended standard attributes that have proven useful. Note that some of these (e.g. units, valid_range, scale_factor) assume numeric data and should not be used with character data. units
A character string that specifies the units used for the variable's data. Unidata has developed a freely-available library of routines to convert between character string and binary forms of unit specifications and to perform various useful operations on the binary forms. This library is used in some netCDF applications. Using the recommended units syntax permits data represented in conformable units to be automatically converted to common units for arithmetic operations. See Appendix A - Units (The NetCDF Users Guide).
long_name
valid_min
valid_max
valid_range
Generic applications should treat values outside the valid range as missing. The type of each valid_range, valid_min and valid_max attribute should match the type of its variable (except that for byte data, these can be of a signed integral type to specify the intended range).
If neither valid_min, valid_max nor valid_range is defined then
generic applications should define a valid range as follows. If the
data type is byte and _FillValue is not explicitly defined, then the
valid range should include all possible values. Otherwise, the valid
range should exclude the _FillValue (whether defined explicitly or by
default) as follows. If the _FillValue is positive then it defines a
valid maximum, otherwise it defines a valid minimum. For integer
types, there should be a difference of 1 between the _FillValue and
this valid minimum or maximum. For floating point types, the
difference should be twice the minimum possible (1 in the least
significant bit) to allow for rounding error.
scale_factor
add_offset
When scale_factor and add_offset are used for packing, the associated
variable (containing the packed data) is typically of type byte or
short, whereas the unpacked values are intended to be of type float or
double. The attributes scale_factor and add_offset should both be of
the type intended for the unpacked data, e.g. float or double.
_FillValue
Generic applications often need to write a value to represent undefined or missing values. The fill value provides an appropriate value for this purpose because it is normally outside the valid range and therefore treated as missing when read by generic applications. It is legal (but not recommended) for the fill value to be within the valid range.
See Fill Values.
missing_value
signedness
C_format
FORTRAN_format
title
history
Conventions
For example, if a group named NUWG agrees upon a set of conventions for dimension names, variable names, required attributes, and netCDF representations for certain discipline-specific data structures, they may store a document describing the agreed-upon conventions in a dataset in the NUWG/ subdirectory of the Conventions directory. Datasets that followed these conventions would contain a global Conventions attribute with value "NUWG".
Later, if the group agrees upon some additional conventions for a specific subset of NUWG data, for example time series data, the description of the additional conventions might be stored in the NUWG/Time_series/ subdirectory, and datasets that adhered to these additional conventions would use the global Conventions attribute with value "NUWG/Time_series", implying that this dataset adheres to the NUWG conventions and also to the additional NUWG time-series conventions.
The function NF90_PUT_ATT adds or changes a variable attribute or global attribute of an open netCDF dataset. If this attribute is new, or if the space required to store the attribute is greater than before, the netCDF dataset must be in define mode.
Although it's possible to create attributes of all types, text and double attributes are adequate for most purposes.
function nf90_put_att(ncid, varid, name, values) integer, intent( in) :: ncid, varid character(len = *), intent( in) :: name any valid type, scalar or array of rank 1, & intent( in) :: values integer :: nf90_put_att
ncid
varid
name
values
NF90_PUT_ATT returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_PUT_ATT to add a variable attribute named valid_range for a netCDF variable named rh and a global attribute named title to an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status, RHVarID ... status = nf90_open("foo.nc", nf90_write, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! Enter define mode so we can add the attribute status = nf90_redef(ncid) if (status /= nf90_noerr) call handle_err(status) ! Get the variable ID for "rh"... status = nf90_inq_varid(ncid, "rh", RHVarID) if (status /= nf90_noerr) call handle_err(status) ! ... put the range attribute, setting it to eight byte reals... status = nf90_put_att(ncid, RHVarID, "valid_range", real((/ 0, 100 /)) ! ... and the title attribute. if (status /= nf90_noerr) call handle_err(status) status = nf90_put_att(ncid, RHVarID, "title", "example netCDF dataset") ) if (status /= nf90_noerr) call handle_err(status) ! Leave define mode status = nf90_enddef(ncid) if (status /= nf90_noerr) call handle_err(status)
The function NF90_INQUIRE_ATTRIBUTE returns information about a netCDF attribute given the variable ID and attribute name. Information about an attribute includes its type, length, name, and number. See NF90_GET_ATT for getting attribute values.
The function NF90_INQ_ATTNAME gets the name of an attribute, given its variable ID and number. This function is useful in generic applications that need to get the names of all the attributes associated with a variable, since attributes are accessed by name rather than number in all other attribute functions. The number of an attribute is more volatile than the name, since it can change when other attributes of the same variable are deleted. This is why an attribute number is not called an attribute ID.
function nf90_inquire_attribute(ncid, varid, name, xtype, len, attnum) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: name integer, intent(out), optional :: xtype, len, attnum integer :: nf90_inquire_attribute function nf90_inq_attname(ncid, varid, attnum, name) integer, intent( in) :: ncid, varid, attnum character (len = *), intent(out) :: name integer :: nf90_inq_attname
ncid
varid
name
xtype
len
attnum
(If you already know an attribute name, knowing its number is not very useful, because accessing information about an attribute requires its name.)
Each function returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_INQUIRE_ATTRIBUTE to inquire about the lengths of an attribute named valid_range for a netCDF variable named rh and a global attribute named title in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid, status integer :: RHVarID ! Variable ID integer :: validRangeLength, titleLength ! Attribute lengths ... status = nf90_open("foo.nc", nf90_nowrite, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! Get the variable ID for "rh"... status = nf90_inq_varid(ncid, "rh", RHVarID) if (status /= nf90_noerr) call handle_err(status) ! ... get the length of the "valid_range" attribute... status = nf90_inquire_attribute(ncid, RHVarID, "valid_range", & len = validRangeLength) if (status /= nf90_noerr) call handle_err(status) ! ... and the global title attribute. status = nf90_inquire_attribute(ncid, nf90_global, "title", len = titleLength) if (status /= nf90_noerr) call handle_err(status)
Function nf90_get_att gets the value(s) of a netCDF attribute, given its variable ID and name.
function nf90_get_att(ncid, varid, name, values) integer, intent( in) :: ncid, varid character(len = *), intent( in) :: name any valid type, scalar or array of rank 1, & intent(out) :: values integer :: nf90_get_att
ncid
varid
name
values
NF90_GET_ATT returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_GET_ATT to determine the values of an attribute named valid_range for a netCDF variable named rh and a global attribute named title in an existing netCDF dataset named foo.nc. In this example, it is assumed that we don't know how many values will be returned, so we first inquire about the length of the attributes to make sure we have enough space to store them:
use netcdf implicit none integer :: ncid, status integer :: RHVarID ! Variable ID integer :: validRangeLength, titleLength ! Attribute lengths real, dimension(:), allocatable, & :: validRange character (len = 80) :: title ... status = nf90_open("foo.nc", nf90_nowrite, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! Find the lengths of the attributes status = nf90_inq_varid(ncid, "rh", RHVarID) if (status /= nf90_noerr) call handle_err(status) status = nf90_inquire_attribute(ncid, RHVarID, "valid_range", & len = validRangeLength) if (status /= nf90_noerr) call handle_err(status) status = nf90_inquire_attribute(ncid, nf90_global, "title", len = titleLength) if (status /= nf90_noerr) call handle_err(status) ... !Allocate space to hold attribute values, check string lengths allocate(validRange(validRangeLength), stat = status) if(status /= 0 .or. len(title) < titleLength) print *, "Not enough space to put attribute values." exit end if ! Read the attributes. status = nf90_get_att(ncid, RHVarID, "valid_range", validRange) if (status /= nf90_noerr) call handle_err(status) status = nf90_get_att(ncid, nf90_global, "title", title) if (status /= nf90_noerr) call handle_err(status)
The function NF90_COPY_ATT copies an attribute from one open netCDF dataset to another. It can also be used to copy an attribute from one variable to another within the same netCDF dataset.
function nf90_copy_att(ncid_in, varid_in, name, ncid_out, varid_out) integer, intent( in) :: ncid_in, varid_in character (len = *), intent( in) :: name integer, intent( in) :: ncid_out, varid_out integer :: nf90_copy_att
ncid_in
varid_in
name
ncid_out
varid_out
NF90_COPY_ATT returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_COPY_ATT to copy the variable attribute units from the variable rh in an existing netCDF dataset named foo.nc to the variable avgrh in another existing netCDF dataset named bar.nc, assuming that the variable avgrh already exists, but does not yet have a units attribute:
use netcdf implicit none integer :: ncid1, ncid2, status integer :: RHVarID, avgRHVarID ! Variable ID ... status = nf90_open("foo.nc", nf90_nowrite, ncid1) if (status /= nf90_noerr) call handle_err(status) status = nf90_open("bar.nc", nf90_write, ncid2) if (status /= nf90_noerr) call handle_err(status) ... ! Find the IDs of the variables status = nf90_inq_varid(ncid1, "rh", RHVarID) if (status /= nf90_noerr) call handle_err(status) status = nf90_inq_varid(ncid1, "avgrh", avgRHVarID) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_redef(ncid2) ! Enter define mode if (status /= nf90_noerr) call handle_err(status) ! Copy variable attribute from "rh" in file 1 to "avgrh" in file 1 status = nf90_copy_att(ncid1, RHVarID, "units", ncid2, avgRHVarID) if (status /= nf90_noerr) call handle_err(status) status = nf90_enddef(ncid2) if (status /= nf90_noerr) call handle_err(status)
The function NF90_RENAME_ATT changes the name of an attribute. If the new name is longer than the original name, the netCDF dataset must be in define mode. You cannot rename an attribute to have the same name as another attribute of the same variable.
function nf90_rename_att(ncid, varid, curname, newname) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: curname, newname integer :: nf90_rename_att
ncid
varid
curname
newname
NF90_RENAME_ATT returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_RENAME_ATT to rename the variable attribute units to Units for a variable rh in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid1, status integer :: RHVarID ! Variable ID ... status = nf90_open("foo.nc", nf90_nowrite, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! Find the IDs of the variables status = nf90_inq_varid(ncid, "rh", RHVarID) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_rename_att(ncid, RHVarID, "units", "Units") if (status /= nf90_noerr) call handle_err(status)
The function NF90_DEL_ATT deletes a netCDF attribute from an open netCDF dataset. The netCDF dataset must be in define mode.
function nf90_del_att(ncid, varid, name) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: name integer :: nf90_del_att
ncid
varid
name
NF90_DEL_ATT returns the value NF90_NOERR if no errors occurred. Otherwise, the returned status indicates an error. Possible causes of errors include:
Here is an example using NF90_DEL_ATT to delete the variable attribute Units for a variable rh in an existing netCDF dataset named foo.nc:
use netcdf implicit none integer :: ncid1, status integer :: RHVarID ! Variable ID ... status = nf90_open("foo.nc", nf90_nowrite, ncid) if (status /= nf90_noerr) call handle_err(status) ... ! Find the IDs of the variables status = nf90_inq_varid(ncid, "rh", RHVarID) if (status /= nf90_noerr) call handle_err(status) ... status = nf90_redef(ncid) ! Enter define mode if (status /= nf90_noerr) call handle_err(status) status = nf90_del_att(ncid, RHVarID, "Units") if (status /= nf90_noerr) call handle_err(status) status = nf90_enddef(ncid) if (status /= nf90_noerr) call handle_err(status)
Dataset Functions
function nf90_inq_libvers() character(len = 80) :: nf90_inq_libvers function nf90_strerror(ncerr) integer, intent( in) :: ncerr character(len = 80) :: nf90_strerror function nf90_create(path, cmode, ncid) character (len = *), intent(in ) :: path integer, intent(in ) :: cmode integer, optional, intent(in ) :: initialsize integer, optional, intent(inout) :: chunksize integer, intent( out) :: ncid integer :: nf90_create function nf90_open(path, mode, ncid, chunksize) character (len = *), intent(in ) :: path integer, intent(in ) :: mode integer, intent( out) :: ncid integer, optional, intent(inout) :: chunksize integer :: nf90_open function nf90_set_fill(ncid, fillmode, old_mode) integer, intent( in) :: ncid, fillmode integer, intent(out) :: old_mode integer :: nf90_set_fill function nf90_redef(ncid) integer, intent( in) :: ncid integer :: nf90_redef function nf90_enddef(ncid, h_minfree, v_align, v_minfree, r_align) integer, intent( in) :: ncid integer, optional, intent( in) :: h_minfree, v_align, v_minfree, r_align integer :: nf90_enddef function nf90_sync(ncid) integer, intent( in) :: ncid integer :: nf90_sync function nf90_abort(ncid) integer, intent( in) :: ncid integer :: nf90_abort function nf90_close(ncid) integer, intent( in) :: ncid integer :: nf90_close function nf90_Inquire(ncid, nDimensions, nVariables, nAttributes, & unlimitedDimId) integer, intent( in) :: ncid integer, optional, intent(out) :: nDimensions, nVariables, nAttributes, & unlimitedDimId integer :: nf90_Inquire
Dimension functions
function nf90_def_dim(ncid, name, len, dimid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent( in) :: len integer, intent(out) :: dimid integer :: nf90_def_dim function nf90_inq_dimid(ncid, name, dimid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent(out) :: dimid integer :: nf90_inq_dimid function nf90_inquire_dimension(ncid, dimid, name, len) integer, intent( in) :: ncid, dimid character (len = *), optional, intent(out) :: name integer, optional, intent(out) :: len integer :: nf90_inquire_dimension function nf90_rename_dim(ncid, dimid, name) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent( in) :: dimid integer :: nf90_rename_dim
Variable functions
function nf90_def_var(ncid, name, xtype, dimids, varid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent( in) :: xtype integer, dimension(:), intent( in) :: dimids ! May be omitted, scalar, ! vector integer :: nf90_def_var function nf90_inq_varid(ncid, name, varid) integer, intent( in) :: ncid character (len = *), intent( in) :: name integer, intent(out) :: varid integer :: nf90_inq_varid function nf90_inquire_variable(ncid, varid, name, xtype, ndims, & dimids, nAtts) integer, intent( in) :: ncid, varid character (len = *), optional, intent(out) :: name integer, optional, intent(out) :: xtype, ndims integer, dimension(*), optional, intent(out) :: dimids integer, optional, intent(out) :: nAtts integer :: nf90_inquire_variable function nf90_put_var(ncid, varid, values, start, stride, map) integer, intent( in) :: ncid, varid any valid type, scalar or array of any rank, & intent( in) :: values integer, dimension(:), optional, intent( in) :: start, count, stride, map integer :: nf90_put_var function nf90_get_var(ncid, varid, values, start, stride, map) integer, intent( in) :: ncid, varid any valid type, scalar or array of any rank, & intent(out) :: values integer, dimension(:), optional, intent( in) :: start, count, stride, map integer :: nf90_get_var function nf90_rename_var(ncid, varid, newname) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: newname integer :: nf90_rename_var
Attribute functions
function nf90_inquire_attribute(ncid, varid, name, xtype, len, attnum) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: name integer, intent(out), optional :: xtype, len, attnum integer :: nf90_inquire_attribute function nf90_inq_attname(ncid, varid, attnum, name) integer, intent( in) :: ncid, varid, attnum character (len = *), intent(out) :: name integer :: nf90_inq_attname function nf90_put_att(ncid, varid, name, values) integer, intent( in) :: ncid, varid character(len = *), intent( in) :: name any valid type, scalar or array of rank 1, & intent( in) :: values integer :: nf90_put_att function nf90_get_att(ncid, varid, name, values) integer, intent( in) :: ncid, varid character(len = *), intent( in) :: name any valid type, scalar or array of rank 1, & intent(out) :: values integer :: nf90_get_att function nf90_copy_att(ncid_in, varid_in, name, ncid_out, varid_out) integer, intent( in) :: ncid_in, varid_in character (len = *), intent( in) :: name integer, intent( in) :: ncid_out, varid_out integer :: nf90_copy_att function nf90_rename_att(ncid, varid, curname, newname) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: curname, newname integer :: nf90_rename_att function nf90_del_att(ncid, varid, name) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: name integer :: nf90_del_att
The Fortran 90 interface to the netCDF library closely follows the FORTRAN 77 interface. In most cases, function and constant names and argument lists are the same, except that nf90_ replaces nf_ in names. The Fortran 90 interface is much smaller than the FORTRAN 77 interface, however. This has been accomplished by using optional arguments and overloaded functions wherever possible.
Because FORTRAN 77 is a subset of Fortran 90, there is no reason to modify working FORTRAN code to use the Fortran 90 interface. New code, however, can easily be patterned after existing FORTRAN while taking advantage of the simpler interface. Some compilers may provide additional support when using Fortran 90. For example, compilers may issue warnings if arguments with intent( in) are not set before they are passed to a procedure.
The Fortran 90 interface is currently implemented as a set of wrappers around the base FORTRAN subroutines in the netCDF distribution. Future versions may be implemented entirely in Fortran 90, adding additional error checking possibilities.
In the Fortran 90 interface there are two inquiry functions each for dimensions, variables, and attributes, and a single inquiry function for datasets. These functions take optional arguments, allowing users to request only the information they need. These functions replace the many-argument and single-argument inquiry functions in the FORTRAN interface.
As an example, compare the attribute inquiry functions in the Fortran 90 interface
function nf90_inquire_attribute(ncid, varid, name, xtype, len, attnum) integer, intent( in) :: ncid, varid character (len = *), intent( in) :: name integer, intent(out), optional :: xtype, len, attnum integer :: nf90_inquire_attribute function nf90_inq_attname(ncid, varid, attnum, name) integer, intent( in) :: ncid, varid, attnum character (len = *), intent(out) :: name integer :: nf90_inq_attname
with those in the FORTRAN interface
INTEGER FUNCTION NF_INQ_ATT (NCID, VARID, NAME, xtype, len) INTEGER FUNCTION NF_INQ_ATTID (NCID, VARID, NAME, attnum) INTEGER FUNCTION NF_INQ_ATTTYPE (NCID, VARID, NAME, xtype) INTEGER FUNCTION NF_INQ_ATTLEN (NCID, VARID, NAME, len) INTEGER FUNCTION NF_INQ_ATTNAME (NCID, VARID, ATTNUM, name)
The biggest simplification in the Fortran 90 is in the nf90_put_var and nf90_get_var functions. Both functions are overloaded: the values argument can be a scalar or an array any rank (7 is the maximum rank allowed by Fortran 90), and may be of any numeric type or the default character type. The netCDF library provides transparent conversion between the external representation of the data and the desired internal representation.
The start, count, stride, and map arguments to nf90_put_var and nf90_get_var are optional. By default, data is read from or written to consecutive values of starting at the origin of the netCDF variable; the shape of the argument determines how many values are read from or written to each dimension. Any or all of these arguments may be supplied to override the default behavior.
Note also that Fortran 90 allows arbitrary array sections to be passed to any procedure, which may greatly simplify programming.


Percentage change in county budget going to policing, 2000 - 2018
Percentage change in Black, Indigenous, & People of Color county residents, 2000 - 2018


We are going to:
We are going to:
1.learn about animals.
2.learn“The animal can...” sentence pattern.
follow me
√
step show
step show
√
follow me
introduce yourself to the students
STEP SHOW
X
STEP1
ask the student's name and greet the student
STEP2
click and say
STEP3
参见animal-hard 封面
step3


Images released of burglary suspect at Fort Myers convenience store in August
by WFTX Digital TeamFORT MYERS, Fla. -- Fort Myers Police are seeking assistance identifying a male involved in a vehicle burglary.
According to Fort Myers Police, it happened at 5150 Martin Luther King, Jr. Boulevard on August 13, 2019. The incident took place at the RaceTrac convenience store on the corner of Six Mile Cypress Boulevard where he broke into the vehicle and stole cash.
The suspect was in a newer model black Lincoln SUV and was accompanied by an unidentified white SUV.
If identified, please contact FMPD Detective Cierra Carter at<PHONE_NUMBER> or email<EMAIL_ADDRESS>Tipsters can also remain anonymous and be eligible for a cash reward of up to $3,000 by contacting Crime Stoppers at 1-800-780-TIPS (8477) or online at www.southwestfloridacrimestoppers.com