Creating cf.Field
objects¶
A new field is created by initializing a new cf.Field
instance:
>>> f = cf.Field()
Some data and metadata may be provided via initialisation parameters, but in general it is preferable to create an empty field and then add data and metadata with the techniques described here.
Inserting data and metadata¶
Inserting attributes¶
An attribute set directly on a cf.Field
instance is either a CF
property, if its name is defined by the CF conventions, or an instance
attribute. For example:
>>> f.foo = 'bar'
>>> f.standard_name = 'air_temperature'
Attributes and CF properties may be also be set with the following methods:
cf.Field.attributes |
Attributes which are not CF properties. |
cf.Field.properties |
Attributes which are CF properties. |
cf.Field.setprop |
Set a CF property. |
For example:
>>> f.attributes({'foo': 'bar'})
>>> f.properties({'foo': 'bar', 'long_name': 'temperature'})
>>> f.setprop('foo', 'bar')
Inserting domain components¶
Domain components may be provided with the following methods:
cf.Field.insert_aux |
Insert an auxiliary coordinate object into the field. |
cf.Field.insert_axis |
Insert an axis into the field. |
cf.Field.insert_cell_methods |
Insert |
cf.Field.insert_dim |
Insert a dimension coordinate object into the field. |
cf.Field.insert_domain_anc |
|
cf.Field.insert_field_anc |
|
cf.Field.insert_measure |
Insert a cell measure object into the field. |
cf.Field.insert_ref |
Insert a coordinate reference object into the field. |
For example:
>>> coord
<CF DimensionCoordinate: latitude(73) degrees_north>,
>>> f.insert_dim(coord)
Inserting data¶
The field’s data array may be provided with the following method:
cf.Field.insert_data |
Insert a data array into the field. |
For example:
>>> data
<CF Data: [[[271.31, ..., 298.56]]] K>
>>> f.insert_data(data)
Removing data and metadata¶
Removing attributes¶
An attribute deleted directly from a cf.Field
instance is either a
CF property, if its name is defined by the CF conventions, or an
instance attribute. For example:
>>> del f.foo = 'bar'
>>> del f.standard_name
CF properties may be also be removed with the following methods:
cf.Field.properties |
Attributes which are CF properties. |
cf.Field.delprop |
Delete a CF property. |
For example:
>>> f.delprop('foo')
>>> f.delprop('standard_name')
>>> f.properties(clear=True)
Removing domain components¶
Removing field components is done with the following methods:
cf.Field.remove_item |
Remove and return an item from the field. |
cf.Field.remove_axis |
Remove and return a unique axis from the field. |
cf.Field.remove_items |
Remove and return items from the field. |
cf.Field.remove_axes |
Remove and return axes from the field. |
For example:
>>> f.remove_item('longitude')
<CF AuxiliaryCoordinate: longitude(111, 106) degrees_east>
Removing data¶
Removing the data is done with the following method:
cf.Field.remove_data |
Remove and return the data array. |
For example:
>>> f.remove_data()
<CF Data: [[[271.31, ..., 298.56]]] K>
Examples¶
Example 2¶
A field with just CF properties:
>>> f = cf.Field()
>>> f.standard_name = 'air_temperature'
>>> f.properties({'long_name': 'temperature of air',
... 'foo' : 'bar'})
>>> print f
air_temperature field summary
-----------------------------
Example 3¶
A field with two dimensionsal data array and a simple domain
comprising two dimension coordinate objects. Note that in this example
the data and coordinates are generated using range
and
numpy.arange
simply for the sake of having some numbers to play
with. In practice it is likely the values would have been read from a
file in some arbitrary format:
>>> import numpy
>>> f = cf.Field()
>>> f.standard_name = 'eastward_wind'
>>> y = cf.DimensionCoordinate(data=cf.Data(range(10), 'degrees_north'),
... properties={'standard_name': 'latitude'})
>>> x = cf.DimensionCoordinate(data=cf.Data(range(9), 'degrees_east'))
>>> x.standard_name = 'longitude'
>>> f.insert_dim(y)
'dim0'
>>> f.insert_dim(x)
'dim1'
>>> data = cf.Data(numpy.arange(90.).reshape(9, 10), 'm s-1')
>>> f.insert_data(data)
>>> print f
eastward_wind field summary
---------------------------
Data : eastward_wind(longitude(9), latitude(10)) m s-1
Axes : latitude(10) = [0, ..., 9] degrees_north
: longitude(9) = [0, ..., 8] degrees_east
Note that when inserting dimension coordinates, domain axes will
automatically be created if there is no ambiguity. Similarly, the data
array dimensions are automatically assigned to domain axes if
possible. The insert_dim
method returns the field’s
internal identifier for the inserted item.
Adding an auxiliary coordinate to the “latitude” axis and a cell method may be done with the relevant method and by simple assignment respectively (note that these coordinate values are just for illustration):
>>> aux = cf.AuxiliaryCoordinate(data=cf.Data(['alpha','beta','gamma','delta','epsilon',
... 'zeta','eta','theta','iota','kappa']))
...
>>> aux.long_name = 'extra'
>>> f.items()
{'dim0': <CF DimensionCoordinate: latitude(10) degrees_north>,
'dim1': <CF DimensionCoordinate: longitude(9) degrees_east>}
>>> f.insert_aux(aux)
'aux0'
>>> f.cell_methods = cf.CellMethods('latitude: point')
>>> print f
eastward_wind field summary
---------------------------
Data : eastward_wind(longitude(9), latitude(10)) m s-1
Cell methods : latitude: point
Axes : latitude(10) = [0, ..., 9] degrees_north
: longitude(9) = [0, ..., 8] degrees_east
Aux coords : long_name:extra(latitude(10)) = ['alpha', ..., 'kappa']
Removing the auxiliary coordinate and the cell method that were just added is also done with the relevant method and by simple deletion respectively:
>>> f.remove_item({'long_name': 'extra'})
<CF AuxiliaryCoordinate: long_name:extra(10)>
>>> del f.cell_methods
>>> print f
eastward_wind field summary
---------------------------
Data : eastward_wind(latitude(10), longitude(9)) m s-1
Dimensions : latitude(10) = [0, ..., 9] degrees_north
: longitude(9) = [0, ..., 8] degrees_east
Example 4¶
A more complicated field is created by the following script. Note that
in this example the data and coordinates are generated using
numpy.arange
simply for the sake of having some numbers to play
with. In practice it is likely the values would have been read from a
file in some arbitrary format:
import cf
import numpy
#---------------------------------------------------------------------
# 1. CREATE the field's domain items
#---------------------------------------------------------------------
# Create a grid_latitude dimension coordinate
Y = cf.DimensionCoordinate(properties={'standard_name': 'grid_latitude'},
data=cf.Data(numpy.arange(10.), 'degrees'))
# Create a grid_longitude dimension coordinate
X = cf.DimensionCoordinate(data=cf.Data(numpy.arange(9.), 'degrees'))
X.standard_name = 'grid_longitude'
# Create a time dimension coordinate (with bounds)
bounds = cf.CoordinateBounds(
data=cf.Data([0.5, 1.5], cf.Units('days since 2000-1-1', calendar='noleap')))
T = cf.DimensionCoordinate(properties=dict(standard_name='time'),
data=cf.Data(1, cf.Units('days since 2000-1-1',
calendar='noleap')),
bounds=bounds)
# Create a longitude auxiliary coordinate
lat = cf.AuxiliaryCoordinate(data=cf.Data(numpy.arange(90).reshape(10, 9),
'degrees_north'))
lat.standard_name = 'latitude'
# Create a latitude auxiliary coordinate
lon = cf.AuxiliaryCoordinate(properties=dict(standard_name='longitude'),
data=cf.Data(numpy.arange(1, 91).reshape(9, 10),
'degrees_east'))
# Create a rotated_latitude_longitude grid mapping coordinate reference
grid_mapping = cf.CoordinateReference('rotated_latitude_longitude',
grid_north_pole_latitude=38.0,
grid_north_pole_longitude=190.0)
# --------------------------------------------------------------------
# 2. Create the field's domain from the previously created items
# --------------------------------------------------------------------
domain = cf.Domain(dim=[T, Y, X],
aux=[lat, lon],
ref=grid_mapping)
#---------------------------------------------------------------------
# 3. Create the field
#---------------------------------------------------------------------
# Create CF properties
properties = {'standard_name': 'eastward_wind',
'long_name' : 'East Wind',
'cell_methods' : cf.CellMethods('latitude: point')}
# Create the field's data array
data = cf.Data(numpy.arange(90.).reshape(9, 10), 'm s-1')
# Finally, create the field
f = cf.Field(properties=properties,
domain=domain,
data=data)
print "The new field:\n"
print f
Running this script produces the following output:
The new field:
eastward_wind field summary
---------------------------
Data : eastward_wind(grid_longitude(9), grid_latitude(10)) m s-1
Cell methods : latitude: point
Axes : time(1) = [2000-01-02 00:00:00] noleap
: grid_longitude(9) = [0.0, ..., 8.0] degrees
: grid_latitude(10) = [0.0, ..., 9.0] degrees
Aux coords : latitude(grid_latitude(10), grid_longitude(9)) = [[0, ..., 89]] degrees_north
: longitude(grid_longitude(9), grid_latitude(10)) = [[1, ..., 90]] degrees_east
Coord refs : <CF CoordinateReference: rotated_latitude_longitude>
Example 5¶
Example 4 would be slightly more complicated if
the grid_longitude
and grid_latitude
axes were to have the
same size. In this case the domain needs be told which axes, and in
which order, are spanned by the two dimensional auxiliary coordinates
(latitude
and longitude
) and the field needs to know which
axes span the data array:
import cf
import numpy
#---------------------------------------------------------------------
# 1. CREATE the field's domain items
#---------------------------------------------------------------------
# Create a grid_latitude dimension coordinate
Y = cf.DimensionCoordinate(properties={'standard_name': 'grid_latitude'},
data=cf.Data(numpy.arange(10.), 'degrees'))
# Create a grid_longitude dimension coordinate
X = cf.DimensionCoordinate(data=cf.Data(numpy.arange(10.), 'degrees'))
X.standard_name = 'grid_longitude'
# Create a time dimension coordinate (with bounds)
bounds = cf.CoordinateBounds(
data=cf.Data([0.5, 1.5], cf.Units('days since 2000-1-1', calendar='noleap')))
T = cf.DimensionCoordinate(properties=dict(standard_name='time'),
data=cf.Data(1, cf.Units('days since 2000-1-1',
calendar='noleap')),
bounds=bounds)
# Create a longitude auxiliary coordinate
lat = cf.AuxiliaryCoordinate(data=cf.Data(numpy.arange(100).reshape(10, 10),
'degrees_north'))
lat.standard_name = 'latitude'
# Create a latitude auxiliary coordinate
lon = cf.AuxiliaryCoordinate(properties=dict(standard_name='longitude'),
data=cf.Data(numpy.arange(1, 101).reshape(10, 10),
'degrees_east'))
# Create a rotated_latitude_longitude grid mapping coordinate reference
grid_mapping = cf.CoordinateReference('rotated_latitude_longitude',
grid_north_pole_latitude=38.0,
grid_north_pole_longitude=190.0)
# --------------------------------------------------------------------
# 2. Create the field's domain from the previously created items
# --------------------------------------------------------------------
domain = cf.Domain(dim=[T, Y, X],
aux={'aux0': lat, 'aux1': lon},
ref=grid_mapping,
assign_axes={'aux0': ['grid_latitude', 'grid_longitude'],
'aux1': ['grid_longitude', 'grid_latitude']})
#---------------------------------------------------------------------
# 3. Create the field
#---------------------------------------------------------------------
# Create CF properties
properties = {'standard_name': 'eastward_wind',
'long_name' : 'East Wind',
'cell_methods' : cf.CellMethods('latitude: point')}
# Create the field's data array
data = cf.Data(numpy.arange(90.).reshape(9, 10), 'm s-1')
# Finally, create the field
f = cf.Field(properties=properties,
domain=domain,
data=data,
axes=['grid_latitude', 'grid_longitude'])
print "The new field:\n"
print f
Running this script produces the following output:
eastward_wind field summary
---------------------------
Data : eastward_wind(grid_latitude(10), grid_longitude(10)) m s-1
Cell methods : latitude: point
Axes : time(1) = [2000-01-02 00:00:00] noleap
: grid_longitude(10) = [0.0, ..., 9.0] degrees
: grid_latitude(10) = [0.0, ..., 9.0] degrees
Aux coords : latitude(grid_latitude(10), grid_longitude(10)) = [[0, ..., 99]] degrees_north
: longitude(grid_longitude(10), grid_latitude(10)) = [[1, ..., 100]] degrees_east
Coord refs : <CF CoordinateReference: rotated_latitude_longitude>