cf.Count¶

class
cf.
Count
(properties=None, data=None, source=None, copy=True, _use_data=True)[source]¶ 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
andnc_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
andnc_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
andnc_has_sample_dimension
methods.New in version 3.0.0.
Initialization
Parameters:  properties:
dict
, optional Set descriptive properties. The dictionary keys are property names, with corresponding values. Ignored if the source parameter is set.
 Parameter example:
properties={'long_name': 'number of obs for this station'}
Properties may also be set after initialisation with the
set_properties
andset_property
methods. data:
Data
, optional Set the data array. Ignored if the source parameter is set.
The data array may also be set after initialisation with the
set_data
method. source: optional
Initialize the properties and data from those of source.
 copy:
bool
, optional If False then do not deep copy input parameters prior to initialization. By default arguments are deep copied.
 properties:
Inspection¶
Methods
dump 
A full description of the count variable. 
identity 
Return the canonical identity. 
identities 
Return all possible identities. 
Attributes
id 
A canonical identity. 
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 construct has a netCDF variable name. 
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 datetime 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 
The Data object containing the data array. 
datetime_array 
An independent numpy array of datetime 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 a data has been set. 
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 nonmasked 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. 
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. 
files 
Return the names of any files containing parts of the data array. 
has_bounds 
Whether or not there are cell bounds. 
Miscellaneous¶
Methods
concatenate 
Join a sequence of variables together. 
copy 
Return a deep copy. 
equals 
Whether two instances are the same. 
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 
A canonical identity. 
Mathematical operations¶
Methods
Trigonometrical functions
cos 
Take the trigonometric cosine of the data, elementwise. 
sin 
The trigonometric sine of the data, elementwise. 
tan 
The trigonometric tangent of the data, elementwise. 
Rounding and truncation
ceil 
The ceiling of the data, elementwise. 
clip 
Limit the values in the data. 
floor 
Floor the data array, elementwise. 
rint 
Round the data to the nearest integer, elementwise. 
round 
Round the data to the given number of decimals. 
trunc 
Truncate the data, elementwise. 
Statistical collapses
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. 
range 
The absolute difference between the maximum and minimum of the data array. 
sample_size 
The number of nonmissing data elements in the data array. 
sum 
The sum of the data array. 
sd 
The unweighted sample standard deviation of the data array. 
var 
The unweighted sample variance of the data array. 
Exponential and logarithmic functions
exp 
The exponential of the data, elementwise. 
log 
The logarithm of the data array. 
Datetime operations¶
Attributes
day 
The day of each datetime data array element. 
datetime_array 
An independent numpy array of datetime objects. 
hour 
The hour of each datetime data array element. 
minute 
The minute of each datetime data array element. 
month 
The month of each datetime data array element. 
reference_datetime 
The reference datetime of units of elapsed time. 
second 
The second of each datetime data array element. 
year 
The year of each datetime 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 elementwise 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. 
Arithmetic and comparison operations¶
Arithmetic, bitwise and comparison operations are defined as elementwise operations on the data, which yield a new construct or, for augmented assignments, modify the construct’s data inplace.
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 ~ 
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 builtin function. 
__setitem__ 
Called to implement assignment to x[indices] 
__str__ 
Called by the str builtin function. 
__array__ 
Returns a numpy array representation of the data. 
__data__ 
Returns a new reference to the data. 
__query_set__ 
TODO 
__query_wi__ 
TODO 
__query_wo__ 
TODO 1 