cf.CellMethods

class cf.CellMethods(string=None)

Bases: cf.utils.CfList

A CF cell methods object to describe the characteristic of a field that is represented by cell values.

Each cell method is stored in a dictionary and these dictionaries are stored in a list-like object. Similarly to a CF ‘cell_methods’ string, the order of cell methods in the list is important.

The dictionary representing each cell method recognizes the following keys (where all keys are optional; the referenced sections are from NetCDF Climate and Forecast (CF) Metadata Conventions Version 1.5; and words in double quotes (”...”) refer to CF cell_methods components in the referenced sections):

Key	Value
method	A “method” component. Refer to section 7.3.
name	A list of all of the “name” components involved with the “method” component. Each element is either: The standard_name of the cell method’s dimension The string ‘area’ A netCDF variable name or netCDF dimension name Option 3. only occurs if the cell method’s dimension either has no dimension coordinate or has a dimension coordinate with no standard_name. This is a deviation from the “name” components as described in sections 7.3, 7.3.1 and 7.3.4, in that standard_names are stored whenever possible, rather than only in the special cases described in section 7.3.4. Inspection of the ‘no_coords’ list retains the information required to fully interpret the cell method.
dim	A list of space dimension names corresponding to the ‘name’ list. A ‘name’ list value of ‘area’ always corresponds to a ‘dim’ list value of None.
no_coords	A list of booleans, corresponding to the ‘name’ list, indicating whether or not a particular cell method is relevant to the data in a way which may not be precisely defined by the corresponding dimension or dimensions. Refer to section 7.3.4.
interval	A list of Data objects giving “interval” component values, with their associated units, corresponding to the ‘name’ list. Refer to section 7.3.2.
comment	A “comment” or non-standardised information, component. Refer to sections 7.3.2 and 7.4
within	A “within” climatology component. Refer to section 7.4.
over	An “over” cell portion or “over” climatology component. Refer to sections 7.3.3 and 7.4.
where	A “where” component. Refer to section 7.3.3.

Note that the above table assumes that the cell methods have been constructed in the context of a field, the only way in which the ‘dim’ and ‘no_coords’ keys may take sensible values. If this is not the case, as would happen if the parse method were called without its field keyword, then elements of the ‘dim’ key default to False and elements of the ‘no_coords’ key default to None.

Examples:

>>> c = cf.CellMethods()
>>> c = c.parse('time: minimum within years time: mean over years (ENSO years)')    
>>> print c
Cell methods    : time: minimum within years
                  time: mean over years (ENSO years)
>>> list(c)
[
 {'method'   : 'minimum',
  'name'     : ['time'],     
  'dim'      : [False],
  'no_coords': [None], 
  'within'   : 'years'
 },
 {'method'   : 'mean'
  'name'     : ['time'],
  'dim'      : [False], 
  'no_coords': [None],     
  'comment'  : 'ENSO years', 
  'over'     : 'years'
 }
]

>>> c = c.parse('lat: lon: standard_deviation')
>>> list(c)
[
 {'dim'      : [False, False],
  'method'   : 'standard_deviation'
  'name'     : ['lat', 'lon'],
  'no_coords': [None, None],
 }
]

Methods

Method	Description
append	As for a built-in list.
copy	Create a deep copy.
count	As for a built-in list but using numerically tolerant equality.
dump	Return a string containing a full description of the object.
equals	Determine whether two lists are congruent element-wise.
extend	As for a built-in list.
index	As for a built-in list but using numerically tolerant equality.
insert	As for a built-in list.
parse	Parse a netCDF(CF) cell_methods string.
pop	As for a built-in list.
properties	Return a set of writable, public attributes.
remove	As for a built-in list.
reverse	As for a built-in list.
sort	As for a built-in list.
strings	Convert each element to a string.

Initialization

Parameters :

string : str or None, optional

Initialize new instance from a CF-netCDF-like cell methods string. See the parse method for details.

copy()

Return a deep copy.

Equivalent to copy.deepcopy(x)

Returns :

out :

The deep copy.

Examples

>>> x.copy()

count(value) → integer -- return number of occurrences of value

Uses numerically tolerant equality.

dump(id=None, omit=())

Return a string containing a full description of the cell methods.

If a cell methods ‘name’ is followed by a ‘*’ then that cell method is relevant to the data in a way which may not be precisely defined its corresponding dimension or dimensions.

Parameters:

• id (str) – Optional. Set the common prefix of each line of the output. If None then defaults to the class name.
• omit (sequence) – Optional. Dummy argument required for consistency with the cf.dump function.

Returns :

out : str

A string containing the description of the cell methods.

See also

cf.dump

equals(other, rtol=None, atol=None)

Return True if two lists are congruent in that

1. Each pair of their elements are equal.
2. Both instances have equal attributes.

Numerical equality is to within a tolerance. Refer to cf for details.

Parameters:

• other (object) – The variable to compare against for equality.
• atol (None or float) – Optional. If None then use the default method for setting the absolute tolerance for numerical equality (refer to cf for details). If a number then set the absolute tolerance to this value for all such comparisons.
• rtol (None or float) – Optional. If None then use the default method for setting the relative tolerance for numerical equality (refer to cf for details). If a number then set the relative tolerance to this value for all such comparisons.

Returns:

True if the two objects are congruent, False otherwise.

has_cellmethods(other)

Return True if and only if this cell methods is a super set of another.

Parameters :

other : CellMethods

The other cell methods for comparison.

Returns :

out : bool

Whether or not this cell methods is a super set of the other.

Examples

>>> c = cf.CellMethods('time: mean height: mean area: mean')
>>> d = cf.CellMethods('area: mean time: mean')
>>> c.has_cellmethods(d)
True

index(value[, start[, stop]]) → integer -- return first index of value

Uses numerically tolerant equality.

insert(index, object)

CFL.insert(index, object) – insert object before index

static netCDF_translation(cell_methods, field)

parse(string=None)

Parse a CF cell_methods string into this CellMethods instance in place.

Parameters :

string : str, optional

The CF cell_methods string to be parsed into the CellMethods object. If unset or None then the cell methods will be empty.

Examples:

>>> c = cf.CellMethods()
>>> c = c.parse('time: minimum within years time: mean over years (ENSO years)')    
>>> print c
Cell methods    : time: minimum within years
                  time: mean over years (ENSO years)

strings()

Retun a list of a CF-netCDF-like string of each cell method.

Note that if the intention is to concatenate the output list into a string for creating a netCDF(CF) cell_methods attribute, then the cell methods “name” components may need to be modified, where appropriate, to reflect netCDF variable names.

Returns :

out : list

A string for each cell method.

Examples:

>>> c = cf.CellMethods()
>>> c = c.parse('time: minimum within years time: mean over years (ENSO years)')    
>>> c.strings()
['time: minimum within years',
 'time: mean over years (ENSO years)']