cf.BoundedVariable

class cf.BoundedVariable(properties={}, attributes={}, data=None, bounds=None, source=None, copy=True)

Bases: cf.variable.Variable

Base class for CF dimension coordinate, auxiliary coordinate and domain ancillary objects.

Initialization

Parameters:

properties: dict, optional

Initialize a new instance with CF properties from a dictionary’s key/value pairs.

attributes: dict, optional

Provide the new instance with attributes from a dictionary’s key/value pairs.

data: cf.Data, optional

Provide the new instance with an N-dimensional data array.

bounds: cf.Data or cf.Bounds, optional

Provide the new instance with cell bounds.

copy: bool, optional

If False then do not copy arguments prior to initialization. By default arguments are deep copied.

CF Properties

add_offset	The add_offset CF property.
calendar	The calendar CF property.
comment	The comment CF property.
_FillValue	The _FillValue CF property.
history	The history CF property.
leap_month	The leap_month CF property.
leap_year	The leap_year CF property.
long_name	The long_name CF property.
missing_value	The missing_value CF property.
month_lengths	The month_lengths CF property.
scale_factor	The scale_factor CF property.
standard_name	The standard_name CF property.
units	The units CF property.
valid_max	The valid_max CF property.
valid_min	The valid_min CF property.
valid_range	The valid_range CF property.

Attributes

Data	The cf.Data object containing the data array.
T	Always False.
Units	The Units object containing the units of the data array.
X	Always False.
Y	Always False.
Z	Always False.
add_offset	The add_offset CF property.
array	A numpy array deep copy of the data array.
binary_mask	A binary (0 and 1) missing data mask of the data array.
bounds	The cf.Bounds object containing the cell bounds.
calendar	The calendar CF property.
cellsize	A cf.Data object containing the variable cell sizes.
comment	The comment CF property.
data	The cf.Data object containing the data array.
day	The day of each date-time data array element.
dtarray	An independent numpy array of date-time objects.
dtvarray	A numpy array view the data array converted to date-time objects.
dtype	Numpy data-type of the data array.
hardmask	Whether the mask is hard (True) or soft (False).
hasbounds	True if there are cell bounds.
hasdata	True if there is a data array.
history	The history CF property.
hour	The hour of each date-time data array element.
isauxiliary	True if the variable is an auxiliary coordinate object.
isdimension	True if the variable is a dimension coordinate object.
isdomainancillary	True if the variable is a domain ancillary object.
isfieldancillary	True if the variable is a field ancillary object.
ismeasure	True if the variable is a cell measure object.
isperiodic	New in version 2.0.
isscalar	True if the data array is scalar.
leap_month	The leap_month CF property.
leap_year	The leap_year CF property.
long_name	The long_name CF property.
lower_bounds	The lower cell bounds.
mask	The mask of the data array.
minute	The minute of each date-time data array element.
missing_value	The missing_value CF property.
month	The month of each date-time data array element.
month_lengths	The month_lengths CF property.
ndim	The number of dimensions in the data array.
reference_datetime
scale_factor	The scale_factor CF property.
second	The second of each date-time data array element.
shape	A tuple of the data array’s dimension sizes.
size	The number of elements in the data array.
standard_name	The standard_name CF property.
subspace	Return a new bounded variable whose data and bounds are subspaced in a consistent manner.
units	The units CF property.
unsafe_array
upper_bounds	The upper cell bounds.
valid_max	The valid_max CF property.
valid_min	The valid_min CF property.
valid_range	The valid_range CF property.
varray	A numpy array view of the data array.
year	The year of each date-time data array element.

Methods

HDF_chunks(*chunksizes)	Specify HDF5 chunks for the data array.
__init__([properties, attributes, data, …])	Initialization
all()	Test whether all data array elements evaluate to True.
allclose(y[, atol, rtol])	Returns True if two broadcastable bounded variables have equal array values to within numerical tolerance.
any()	Return True if any data array elements evaluate to True.
asdatetime([i])	Convert the internal representation of data array elements to date-time objects.
asreftime([i])	Convert the internal representation of data array elements to numeric reference times.
attributes([attrs, copy])	Inspect or change attributes which are not CF properties.
ceil([i])	The ceiling of the data array.
chunk([chunksize])	Partition the data array.
clip(a_min, a_max[, units, bounds, i])	Limit the values in the data array.
close()	Close all files referenced by the bounded variable.
concatenate(variables[, axis, _preserve])	Join a sequence of variables together.
contiguous([overlap])	Return True if a {+variable} has contiguous cells.
convert_reference_time([units, …])	Convert reference time data values to have new units.
copy([_omit_Data, _only_Data, …])	Return a deep copy.
cos([bounds, i])	Take the trigonometric cosine of the data array.
cyclic([axes, iscyclic])	Set the cyclicity of axes of the data array.
datum(*index)	Return an element of the data array as a standard Python scalar.
delprop(prop)	Delete a CF property.
direction()	Return None, indicating that it is not specified whether the values are increasing or decreasing.
dump([display, omit, field, key, _level, _title])	Return a string containing a full description of the variable.
equals(other[, rtol, atol, …])	True if two bounded variables are equal, False otherwise.
equivalent(other[, rtol, atol, traceback])	True if two bounded variables are equal, False otherwise.
exp([bounds, i])	The exponential of the data array.
expand_dims([position, i])	Insert a size 1 axis into the data array.
files()	Return the names of any files containing parts of the data array.
fill_value([default])	Return the data array missing data value.
flip([axes, i])	Flip dimensions of the data array and bounds in place.
floor([bounds, i])	Floor the data array.
getprop(prop, *default)	Get a CF property.
hasprop(prop)	Return True if a CF property exists, otherise False.
identity([default, relaxed_identity])	Return the identity of the bounded variable.
cf.BoundedVariable.insert
insert_bounds(bounds[, copy])	Insert cell bounds.
insert_data(data[, bounds, copy])	Insert a new data array.
inspect()	Inspect the object for debugging.
log([base, bounds, i])	The logarithm of the data array.
mask_invalid([i])	Mask the array where invalid values occur.
match([description, ndim, exact, match_and, …])	Determine whether or not a variable satisfies conditions.
max()	The maximum of the data array.
mean()	The unweighted mean the data array.
mid_range()	The unweighted average of the maximum and minimum of the data array.
min()	The minimum of the data array.
name([default, identity, ncvar, …])	Return a name for the bounded variable.
override_calendar(calendar[, i])	Override the calendar of date-time units.
override_units(new_units[, i])	New in version 2.0.
properties([props, clear, copy])	Inspect or change the CF properties.
range()	The absolute difference between the maximum and minimum of the data array.
remove_data()	Remove and return the data array.
rint([bounds, i])	Round data array.
roll(iaxis, shift[, i])	Roll the bounded variable along an axis.
round([decimals, bounds, i])	Round the data array.
sample_size()	The number of non-missing data elements in the data array.
sd()	The unweighted sample standard deviation of the data array.
select(*args, **kwargs)	cf.BoundedVariable.select has been deprecated.
setprop(prop, value)	Set a CF property.
sin([bounds, i])	The trigonometric sine of the data array.
squeeze([axes, i])	Remove size 1 dimensions from the data array
sum()	The sum of the data array.
tan([bounds, i])	The trigonometric tangent of the data array.
transpose([axes, i])	Permute the dimensions of the data.
trunc([bounds, i])	Truncate the data array.
unique()	The unique elements of the data array.
var()	The unweighted sample variance of the data array.
where(condition[, x, y, i])	Set data array elements depending on a condition.