cf.Count

---

class cf.Count(properties=None, data=None, source=None, copy=True, _use_data=True)

Bases: cf.mixin.propertiesdata.PropertiesData, cfdm.count.Count

A count variable required to uncompress a ragged array.

A collection of features stored using a contiguous ragged array combines all features along a single dimension (the sample dimension) such that each feature in the collection occupies a contiguous block.

The information needed to uncompress the data is stored in a count variable that gives the size of each block.

NetCDF interface

The netCDF variable name of the count variable may be accessed with the nc_set_variable, nc_get_variable, nc_del_variable and nc_has_variable methods.

The name of the netCDF dimension spanned by the count variable’s data may be accessed with the nc_set_dimension, nc_get_dimension, nc_del_dimension and nc_has_dimension methods.

The name of the netCDF sample dimension spanned by the compressed data (that is stored in the “sample_dimension” netCDF attribute and which does not correspond to a domain axis construct) may be accessed with the nc_set_sample_dimension, nc_get_sample_dimension, nc_del_sample_dimension and nc_has_sample_dimension methods.

New in version 3.0.0.

Initialisation

Parameters

properties: dict, optional

Set descriptive properties. The dictionary keys are property names, with corresponding values. Ignored if the source parameter is set.

Properties may also be set after initialisation with the set_properties and set_property methods.

Parameter example:

properties={'long_name': 'number of obs'}

data: data_like, optional

Set the data. Ignored if the source parameter is set.

A data_like object is any object that can be converted to a Data object, i.e. numpy array_like objects, Data objects, and cf instances that contain Data objects.

The data also may be set after initialisation with the set_data method.

A data_like object is any object that can be converted to a Data object, i.e. numpy array_like objects, Data objects, and cf instances that contain Data objects.

source: optional

Initialise the properties and data from those of source.

Note that if source is a Count instance then cf.Count(source=source) is equivalent to source.copy().

copy: bool, optional

If False then do not deep copy input parameters prior to initialisation. By default arguments are deep copied.

Inspection

Methods

dump	A full description of the count variable.
identity	Return the canonical identity.
identities	Return all possible identities.
inspect	Inspect the object for debugging.

Attributes

id	An identity for the Count object.

Selection

Methods

match_by_identity	Whether or not the construct identity satisfies conditions.
match_by_naxes	Whether or not the data has a given dimensionality.
match_by_ncvar	Whether or not the netCDF variable name satisfies conditions.
match_by_property	Whether or not properties satisfy conditions.
match_by_units	Whether or not the construct has given units.

Properties

Methods

del_property	Remove a property.
get_property	Get a CF property.
has_property	Whether a property has been set.
set_property	Set a property.
properties	Return all properties.
clear_properties	Remove all properties.
set_properties	Set properties.

Attributes

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.

Units

Methods

override_units	Override the units.
override_calendar	Override the calendar of date-time units.

Attributes

Units

The cf.Units object containing the units of the data array.

Data

Attributes

array	A numpy array deep copy of the data array.
Data	Deprecated at version 3.0.0, use data attribute or get_data method instead.
data	The Data object containing the data array.
datetime_array	An independent numpy array of date-time objects.
datum	Return an element of the data array as a standard Python scalar.
dtype	The numpy data type of the data array.
isscalar	True if the data array is scalar.
ndim	The number of dimensions in the data array.
shape	A tuple of the data array’s dimension sizes.
size	The number of elements in the data array.
varray	A numpy array view of the data array.

Methods

__getitem__	Return a subspace defined by indices.
del_data	Remove the data.
get_data	Return the data.
has_data	Whether or not the construct has data.
set_data	Set the data.

Rearranging elements

flatten	Flatten axes of the data.
flip	Flip (reverse the direction of) data dimensions.
insert_dimension	Expand the shape of the data array.
roll	Roll the data along an axis.
squeeze	Remove size one axes from the data array.
swapaxes	Interchange two axes of an array.
transpose	Permute the axes of the data array.

Data array mask

fill_value

Return the data array missing data value.

binary_mask	A binary (0 and 1) missing data mask of the data array.
count	Count the non-masked elements of the data.
count_masked	Count the masked elements of the data.
hardmask	Whether the mask is hard (True) or soft (False).
mask	The mask of the data array.
mask_invalid	Mask the array where invalid values occur.
apply_masking	Apply masking as defined by the CF conventions.

Changing data values

__setitem__	Called to implement assignment to x[indices]
mask_invalid	Mask the array where invalid values occur.
subspace	Return a new variable whose data is subspaced.
where	Set data array elements depending on a condition.

Miscellaneous

chunk	Partition the data array.
close	Close all files referenced by the construct.
convert_reference_time	Convert reference time data values to have new units.
cyclic	Set the cyclicity of an axis.
period	Return or set the period of the data.
iscyclic	Whether or not a given axis is cyclic.
isperiodic	True if a given axis is periodic.
get_filenames	Return the name of the file or files containing the data.
has_bounds	Whether or not there are cell bounds.

Miscellaneous

Methods

concatenate	Join a sequence of variables together.
copy	Return a deep copy.
creation_commands	Return the commands that would create the construct.
equals	Whether two instances are the same.
uncompress	Uncompress the construct.

Attributes

T	True if and only if the data are coordinates for a CF ‘T’ axis.
X	Always False.
Y	Always False.
Z	Always False.
id	An identity for the Count object.

Mathematical operations

Methods

Trigonometrical and hyperbolic functions

arccos	Take the trigonometric inverse cosine of the data element- wise.
arccosh	Take the inverse hyperbolic cosine of the data element-wise.
arcsin	Take the trigonometric inverse sine of the data element-wise.
arcsinh	Take the inverse hyperbolic sine of the data element-wise.
arctan	Take the trigonometric inverse tangent of the data element- wise.
arctanh	Take the inverse hyperbolic tangent of the data element-wise.
cos	Take the trigonometric cosine of the data element-wise.
cosh	Take the hyperbolic cosine of the data element-wise.
sin	Take the trigonometric sine of the data element-wise.
sinh	Take the hyperbolic sine of the data element-wise.
tan	Take the trigonometric tangent of the data element-wise.
tanh	Take the hyperbolic tangent of the data array.

Rounding and truncation

ceil	The ceiling of the data, element-wise.
clip	Limit the values in the data.
floor	Floor the data array, element-wise.
rint	Round the data to the nearest integer, element-wise.
round	Round the data to the given number of decimals.
trunc	Truncate the data, element-wise.

Statistical collapses

max	Alias for maximum.
mean	The unweighted mean the data array.
mid_range	The unweighted average of the maximum and minimum of the data array.
min	Alias for minimum.
range	The absolute difference between the maximum and minimum of the data array.
sample_size	The number of non-missing data elements in the data array.
sum	The sum of the data array.
sd	Alias for standard_deviation
var	Alias for variance
standard_deviation	The unweighted sample standard deviation of the data array.
variance	The unweighted sample variance of the data array.
maximum	The maximum of the data array.
minimum	The minimum of the data array.

Exponential and logarithmic functions

exp	The exponential of the data, element-wise.
log	The logarithm of the data array.

Date-time operations

Attributes

day	The day of each date-time data array element.
datetime_array	An independent numpy array of date-time objects.
hour	The hour of each date-time data array element.
minute	The minute of each date-time data array element.
month	The month of each date-time data array element.
reference_datetime	The reference date-time of units of elapsed time.
second	The second of each date-time data array element.
year	The year of each date-time data array element.

Logic functions

Truth value testing

all	Test whether all data elements evaluate to True.
any	Test whether any data elements evaluate to True.

Comparison

allclose	Test whether all data are element-wise equal to other, broadcastable data.
equals	Whether two instances are the same.
equivalent	True if two constructs are equal, False otherwise.

Set operations

unique

The unique elements of the data.

NetCDF

Methods

nc_del_variable	Remove the netCDF variable name.
nc_get_variable	Return the netCDF variable name.
nc_has_variable	Whether the netCDF variable name has been set.
nc_set_variable	Set the netCDF variable name.
nc_del_dimension	Remove the netCDF dimension name.
nc_get_dimension	Return the netCDF dimension name.
nc_has_dimension	Whether the netCDF dimension name has been set.
nc_set_dimension	Set the netCDF dimension name.
nc_del_sample_dimension	Remove the netCDF sample dimension name.
nc_get_sample_dimension	Return the netCDF sample dimension name.
nc_has_sample_dimension	Whether the netCDF sample dimension name has been set.
nc_set_sample_dimension	Set the netCDF sample dimension name.

Aliases

Methods

match

Alias for match_by_identity.

Attributes

dtarray

Alias for datetime_array.

Arithmetic and comparison operations

Arithmetic, bitwise and comparison operations are defined as element-wise operations on the data, which yield a new construct or, for augmented assignments, modify the construct’s data in-place.

Comparison operators

__lt__	The rich comparison operator <
__le__	The rich comparison operator <=
__eq__	The rich comparison operator ==
__ne__	The rich comparison operator !=
__gt__	The rich comparison operator >
__ge__	The rich comparison operator >=

Binary arithmetic operators

__add__	The binary arithmetic operation +
__sub__	The binary arithmetic operation -
__mul__	The binary arithmetic operation *
__div__	The binary arithmetic operation /
__truediv__	The binary arithmetic operation / (true division)
__floordiv__	The binary arithmetic operation //
__pow__	The binary arithmetic operations ** and pow
__mod__	The binary arithmetic operation %

Binary arithmetic operators with reflected (swapped) operands

__radd__	The binary arithmetic operation + with reflected operands.
__rsub__	The binary arithmetic operation - with reflected operands.
__rmul__	The binary arithmetic operation * with reflected operands.
__rdiv__	The binary arithmetic operation / with reflected operands.
__rtruediv__	The binary arithmetic operation / (true division) with reflected operands.
__rfloordiv__	The binary arithmetic operation // with reflected operands.
__rpow__	The binary arithmetic operations ** and pow with reflected operands.
__rmod__	The binary arithmetic operation % with reflected operands.

Augmented arithmetic assignments

__iadd__	The augmented arithmetic assignment +=
__isub__	The augmented arithmetic assignment -=
__imul__	The augmented arithmetic assignment *=
__idiv__	The augmented arithmetic assignment /=
__itruediv__	The augmented arithmetic assignment /= (true division)
__ifloordiv__	The augmented arithmetic assignment //=
__ipow__	The augmented arithmetic assignment **=
__imod__	The binary arithmetic operation %=

Unary arithmetic operators

__neg__	The unary arithmetic operation -
__pos__	The unary arithmetic operation +
__abs__	The unary arithmetic operation abs

Binary bitwise operators

__and__	The binary bitwise operation &
__or__	The binary bitwise operation |
__xor__	The binary bitwise operation ^
__lshift__	The binary bitwise operation <<
__rshift__	The binary bitwise operation >>

Binary bitwise operators with reflected (swapped) operands

__rand__	The binary bitwise operation & with reflected operands.
__ror__	The binary bitwise operation | with reflected operands.
__rxor__	The binary bitwise operation ^ with reflected operands.
__rlshift__	The binary bitwise operation << with reflected operands.
__rrshift__	The binary bitwise operation >> with reflected operands.

Augmented bitwise assignments

__iand__	The augmented bitwise assignment &=
__ior__	The augmented bitwise assignment |=
__ixor__	The augmented bitwise assignment ^=
__ilshift__	The augmented bitwise assignment <<=
__irshift__	The augmented bitwise assignment >>=

Unary bitwise operators

__invert__

The unary bitwise operation ~

Groups

Methods

nc_variable_groups	Return the netCDF variable group hierarchy.
nc_clear_variable_groups	Remove the netCDF variable group hierarchy.
nc_set_variable_groups	Set the netCDF variable group hierarchy.
nc_dimension_groups	Return the netCDF dimension group hierarchy.
nc_clear_dimension_groups	Remove the netCDF dimension group hierarchy.
nc_set_dimension_groups	Set the netCDF dimension group hierarchy.
nc_clear_sample_dimension_groups	Remove the netCDF dimension group hierarchy.
nc_sample_dimension_groups	Return the netCDF dimension group hierarchy.
nc_set_sample_dimension_groups	Set the netCDF dimension group hierarchy.

Special

Methods

__contains__	Called to implement membership test operators.
__deepcopy__	Called by the copy.deepcopy function.
__getitem__	Return a subspace defined by indices.
__repr__	Called by the repr built-in function.
__setitem__	Called to implement assignment to x[indices]
__str__	Called by the str built-in function.
__array__	Returns a numpy array representation of the data.
__data__	Returns a new reference to the data.
__query_set__	Implements the “member of set” condition.
__query_wi__	Implements the “within a range” condition.
__query_wo__	Implements the “without a range” condition.

Deprecated

Methods

asdatetime	Deprecated at version 3.0.0.
asreftime	Deprecated at version 3.0.0.
attributes	Deprecated at version 3.0.0.
delprop	Deprecated at version 3.0.0, use method del_property instead.
dtvarray	Deprecated at version 3.0.0.
expand_dims	Deprecated at version 3.0.0, use insert_dimension method instead.
getprop	Deprecated at version 3.0.0, use method get_property instead.
halo	Expand the data by adding a halo.
hasbounds	Deprecated at version 3.0.0, use has_bounds method instead.
hasdata	Deprecated at version 3.0.0, use has_data method instead.
hasprop	Deprecated at version 3.0.0, use method has_property instead.
insert_data	Deprecated at version 3.0.0, use set_data method instead.
isauxiliary	Deprecated at version 3.7.0, use construct_type attribute instead.
isdimension	Deprecated at version 3.7.0, use construct_type attribute instead.
isdomainancillary	Deprecated at version 3.7.0, use construct_type attribute instead.
isfieldancillary	Deprecated at version 3.7.0, use construct_type attribute instead.
ismeasure	Deprecated at version 3.7.0, use construct_type attribute instead.
name	Deprecated at version 3.0.0, use method ‘identity’ instead.
remove_data	Deprecated at version 3.0.0, use method del_data instead.
select	Deprecated at version 3.0.0.
setprop	Deprecated at version 3.0.0, use method set_property instead.
unsafe_array	Deprecated at version 3.0.0, use array attribute instead.