Dimension names can be changed using the
-Datatset.renameDimension method of a Dataset or
+Dataset.renameDimension() method of a Dataset or
Group instance.
netCDF variables behave much like python multidimensional array objects @@ -901,7 +901,7 @@
The optional comm keyword may be used to specify a particular
MPI communicator (MPI_COMM_WORLD is used by default).
Each process (or rank)
-can now write to the file indepedently.
+can now write to the file independently.
In this example the process rank is
written to a different variable index on each task
>>> d = nc.createDimension('dim',4)
@@ -1164,7 +1164,7 @@ Functions
Will be converted to a array of strings, where each string has a fixed
length of b.shape[-1] characters.
optional kwarg encoding can be used to specify character encoding (default
-utf-8). If encoding is 'none' or 'bytes', a numpy.string_ btye array is
+utf-8). If encoding is 'none' or 'bytes', a numpy.string_ byte array is
returned.
returns a numpy string array with datatype 'UN' (or 'SN') and shape
b.shape[:-1] where where N=b.shape[-1].
@@ -1173,7 +1173,8 @@ Functions
def date2index(dates, nctime, calendar=None, select='exact', has_year_zero=None)
Return indices of a netCDF time variable corresponding to the given dates.
+date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
+Return indices of a netCDF time variable corresponding to the given dates.
dates: A datetime object or a sequence of datetime objects. The datetime objects should not include a time-zone offset.
nctime: A netCDF time variable object. The nctime object must have a @@ -1212,7 +1213,8 @@
Return numeric time values given datetime objects. The units +
date2num(dates, units, calendar=None, has_year_zero=None, longdouble=False)
+Return numeric time values given datetime objects. The units of the numeric time values are described by the units argument and the calendar keyword. The datetime objects must be in UTC with no time-zone offset. @@ -1292,7 +1294,8 @@
Return datetime objects given numeric time values. The units +
num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
+Return datetime objects given numeric time values. The units of the numeric time values are described by the units argument and the calendar keyword. The returned datetime objects represent UTC with no time-zone offset, even if the specified @@ -1348,14 +1351,18 @@
rc_get(key)
Returns the internal netcdf-c rc table value corresponding to key.
Returns the internal netcdf-c rc table value corresponding to key. +See https://docs.unidata.ucar.edu/netcdf-c/current/md_auth.html +for more information on rc files and values.
def rc_set(key, value)
rc_set(key, value)
Sets the internal netcdf-c rc table value corresponding to key.
Sets the internal netcdf-c rc table value corresponding to key. +See https://docs.unidata.ucar.edu/netcdf-c/current/md_auth.html +for more information on rc files and values.
def set_alignment(threshold, alignment)
@@ -2669,12 +2676,16 @@ Instance variables
Ignored if significant_digts not specified. If 'BitRound' is used, then
significant_digits is interpreted as binary (not decimal) digits.
fill_value:
-If specified, the default netCDF _FillValue (the
+If specified, the default netCDF fill value (the
value that the variable gets filled with before any data is written to it)
-is replaced with this value.
-If fill_value is set to False, then
-the variable is not pre-filled. The default netCDF fill values can be found
-in the dictionary netCDF4.default_fillvals.
+is replaced with this value, and the _FillValue attribute is set.
+If fill_value is set to False, then the variable is not pre-filled.
+The default netCDF fill values can be found in the dictionary netCDF4.default_fillvals.
+If not set, the default fill value will be used but no _FillValue attribute will be created
+(this is the default behavior of the netcdf-c library). If you want to use the
+default fill value, but have the _FillValue attribute set, use
+fill_value='default' (note - this only works for primitive data types). Variable.get_fill_value()
+can be used to retrieve the fill value, even if the _FillValue attribute is not set.
chunk_cache: If specified, sets the chunk cache size for this variable.
Persists as long as Dataset is open. Use set_var_chunk_cache to
change it when Dataset is re-opened.
@@ -2799,6 +2810,15 @@ Methods
return a tuple of Dimension instances associated with this
Variable.
+def get_fill_value(self)
+get_fill_value(self)
return the fill value associated with this Variable (returns None if data is not
+pre-filled). Works even if default fill value was used, and _FillValue attribute
+does not exist.
def get_var_chunk_cache(self)
_Encoding
is the unicode encoding that is used to decode the bytes into strings.
When numpy string data is written to a variable it is converted back to -indiviual bytes, with the number of bytes in each string equalling the +individual bytes, with the number of bytes in each string equalling the rightmost dimension of the variable.
The default value of chartostring() is True
(automatic conversions are performed).
Variablefilters
getValueget_dimsget_fill_valueget_var_chunk_cachegetncattrgroup
+for more information on rc files and values.
"""
cdef int ierr
cdef char *keyc
@@ -1345,6 +1347,8 @@ def rc_set(key, value):
**```rc_set(key, value)```**
Sets the internal netcdf-c rc table value corresponding to key.
+See
+for more information on rc files and values.
"""
cdef int ierr
cdef char *keyc
@@ -2058,10 +2062,11 @@ cdef _get_vars(group, bint auto_complex=False):
endianness = None
with nogil:
ierr = nc_inq_var_endian(_grpid, varid, &iendian)
- if ierr == NC_NOERR and iendian == NC_ENDIAN_LITTLE:
- endianness = '<'
- elif iendian == NC_ENDIAN_BIG:
- endianness = '>'
+ if ierr == NC_NOERR:
+ if iendian == NC_ENDIAN_LITTLE:
+ endianness = '<'
+ elif iendian == NC_ENDIAN_BIG:
+ endianness = '>'
# check to see if it is a supported user-defined type.
try:
datatype = _nctonptype[xtype]
@@ -4030,11 +4035,16 @@ behavior is similar to Fortran or Matlab, but different than numpy.
Ignored if `significant_digts` not specified. If 'BitRound' is used, then
`significant_digits` is interpreted as binary (not decimal) digits.
- **`fill_value`**: If specified, the default netCDF `_FillValue` (the
+ **`fill_value`**: If specified, the default netCDF fill value (the
value that the variable gets filled with before any data is written to it)
- is replaced with this value. If fill_value is set to `False`, then
- the variable is not pre-filled. The default netCDF fill values can be found
- in the dictionary `netCDF4.default_fillvals`.
+ is replaced with this value, and the `_FillValue` attribute is set.
+ If fill_value is set to `False`, then the variable is not pre-filled.
+ The default netCDF fill values can be found in the dictionary `netCDF4.default_fillvals`.
+ If not set, the default fill value will be used but no `_FillValue` attribute will be created
+ (this is the default behavior of the netcdf-c library). If you want to use the
+ default fill value, but have the `_FillValue` attribute set, use
+ `fill_value='default'` (note - this only works for primitive data types). `Variable.get_fill_value`
+ can be used to retrieve the fill value, even if the `_FillValue` attribute is not set.
**`chunk_cache`**: If specified, sets the chunk cache size for this variable.
Persists as long as Dataset is open. Use `set_var_chunk_cache` to
@@ -4398,6 +4408,17 @@ behavior is similar to Fortran or Matlab, but different than numpy.
if ierr != NC_NOERR:
if grp.data_model != 'NETCDF4': grp._enddef()
_ensure_nc_success(ierr, extra_msg=error_info)
+ elif fill_value == 'default':
+ if self._isprimitive:
+ fillval = numpy.array(default_fillvals[self.dtype.str[1:]])
+ if not fillval.dtype.isnative: fillval.byteswap(True)
+ _set_att(self._grp, self._varid, '_FillValue',\
+ fillval, xtype=xtype)
+ else:
+ msg = """
+WARNING: there is no default fill value for this data type, so fill_value='default'
+does not do anything."""
+ warnings.warn(msg)
else:
if self._isprimitive or self._isenum or \
(self._isvlen and self.dtype == str):
@@ -4633,6 +4654,36 @@ behavior is similar to Fortran or Matlab, but different than numpy.
return the group that this `Variable` is a member of."""
return self._grp
+ def get_fill_value(self):
+ """
+**`get_fill_value(self)`**
+
+return the fill value associated with this `Variable` (returns `None` if data is not
+pre-filled). Works even if default fill value was used, and `_FillValue` attribute
+does not exist."""
+ cdef int ierr, no_fill
+ with nogil:
+ ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
+ _ensure_nc_success(ierr)
+ if no_fill == 1: # no filling for this variable
+ return None
+ else:
+ try:
+ fillval = self._FillValue
+ return fillval
+ except AttributeError:
+ # _FillValue attribute not set, see if we can retrieve _FillValue.
+ # for primitive data types.
+ if self._isprimitive:
+ #return numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
+ fillval = numpy.empty((),self.dtype)
+ ierr=nc_inq_var_fill(self._grpid,self._varid,&no_fill,PyArray_DATA(fillval))
+ _ensure_nc_success(ierr)
+ return fillval
+ else:
+ # no default filling for non-primitive data types.
+ return None
+
def ncattrs(self):
"""
**`ncattrs(self)`**
@@ -5621,7 +5672,7 @@ of the the rightmost dimension of the variable). The value of `_Encoding`
is the unicode encoding that is used to decode the bytes into strings.
When numpy string data is written to a variable it is converted back to
-indiviual bytes, with the number of bytes in each string equalling the
+individual bytes, with the number of bytes in each string equalling the
rightmost dimension of the variable.
The default value of `chartostring` is `True`
@@ -6747,7 +6798,7 @@ Will be converted to a array of strings, where each string has a fixed
length of `b.shape[-1]` characters.
optional kwarg `encoding` can be used to specify character encoding (default
-`utf-8`). If `encoding` is 'none' or 'bytes', a `numpy.string_` btye array is
+`utf-8`). If `encoding` is 'none' or 'bytes', a `numpy.string_` byte array is
returned.
returns a numpy string array with datatype `'UN'` (or `'SN'`) and shape
diff --git a/test/test_alignment.py b/test/test_alignment.py
index 3f7333cd6..39c437535 100644
--- a/test/test_alignment.py
+++ b/test/test_alignment.py
@@ -134,7 +134,7 @@ def test_setting_alignment(self):
for line in h5ls_results.split('\n'):
if not line.startswith(' '):
data_variable = line.split(' ')[0]
- # only process the data variables we care to inpsect
+ # only process the data variables we care to inspect
if data_variable not in addresses:
continue
line = line.strip()
diff --git a/test/test_get_fill_value.py b/test/test_get_fill_value.py
new file mode 100644
index 000000000..257a3121e
--- /dev/null
+++ b/test/test_get_fill_value.py
@@ -0,0 +1,43 @@
+import unittest, os, tempfile
+import netCDF4
+from numpy.testing import assert_array_equal
+import numpy as np
+
+fill_val = np.array(9.9e31)
+
+# test Variable.get_fill_value
+
+class TestGetFillValue(unittest.TestCase):
+ def setUp(self):
+ self.testfile = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+ f = netCDF4.Dataset(self.testfile, 'w')
+ dim = f.createDimension('x',10)
+ for dt in netCDF4.default_fillvals.keys():
+ if not dt.startswith('c'):
+ v = f.createVariable(dt+'_var',dt,dim)
+ v = f.createVariable('float_var',np.float64,dim,fill_value=fill_val)
+ # test fill_value='default' option (issue #1374)
+ v2 = f.createVariable('float_var2',np.float64,dim,fill_value='default')
+ f.close()
+
+ def tearDown(self):
+ os.remove(self.testfile)
+
+ def runTest(self):
+ f = netCDF4.Dataset(self.testfile, "r")
+ # no _FillValue set, test that default fill value returned
+ for dt in netCDF4.default_fillvals.keys():
+ if not dt.startswith('c'):
+ fillval = np.array(netCDF4.default_fillvals[dt])
+ if dt == 'S1': fillval = fillval.astype(dt)
+ v = f[dt+'_var']
+ assert_array_equal(fillval, v.get_fill_value())
+ # _FillValue attribute is set.
+ v = f['float_var']
+ assert_array_equal(fill_val, v.get_fill_value())
+ v = f['float_var2']
+ assert_array_equal(np.array(netCDF4.default_fillvals['f8']), v._FillValue)
+ f.close()
+
+if __name__ == '__main__':
+ unittest.main()