Module netCDF3 :: Class Variable

Class Variable

object --+
         |
        Variable

Variable(self, dset, name, datatype, dimensions=(), fill_value=None)

A netCDF Variable is used to read and write netCDF data. They are analagous to numpy array objects.

Variable instances should be created using the createVariable method of a Dataset instance, not using this class directly.

Parameters:

dset - Dataset instance.

name - Name of the variable.

datatype - Variable data type. Can be specified by providing a numpy dtype object, or a string that describes a numpy dtype object. Supported values, corresponding to str attribute of numpy dtype objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating point), 'i4' (32-bit signed integer), 'i2' (16-bit signed integer), 'i4' (8-bit singed integer), 'i1' (8-bit signed integer), or 'S1' (single-character string). From compatibility with Scientific.IO.NetCDF, the old Numeric single character typecodes can also be used ('f' instead of 'f4', 'd' instead of 'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of 'i1', 'c' instead of 'S1', and 'i' or 'l' instead of 'i4').

Keywords:

dimensions - a tuple containing the variable's dimension names (defined previously with createDimension). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions).

fill_value - If specified, the default netCDF _FillValue (the value that the variable gets filled with before any data is written to it) is replaced with this value.

Returns:

a Variable instance. All further operations on the netCDF Variable are accomplised via Variable instance methods.

A list of attribute names corresponding to netCDF attributes defined for the variable can be obtained with the ncattrs() method. These attributes can be created by assigning to an attribute of the Variable instance. A dictionary containing all the netCDF attribute name/value pairs is provided by the __dict__ attribute of a Variable instance.

The instance variables dimensions, dtype, ndim, shape are read-only (and should not be modified by the user).

Instance Methods
 
__delattr__(...)
x.__delattr__('name') <==> del x.name
 
__delitem__(x, y)
del x[y]
 
__getattr__(...)
 
__getattribute__(...)
x.__getattribute__('name') <==> x.name
 
__getitem__(...)
 
__init__(self, dset, name, datatype, dimensions=(), fill_value=None)
x.__init__(...) initializes x; see x.__class__.__doc__ for signature
 
__len__(x)
len(x)
a new object with type S, a subtype of T
__new__(T, S, ...)
 
__setattr__(...)
x.__setattr__('name', value) <==> x.name = value
 
__setitem__(x, i, y)
x[i]=y
 
assignValue(self, val)
assign a value to a scalar variable.
 
delncattr(self, name, value)
delete a netCDF variable attribute.
 
getValue(self)
get the value of a scalar variable.
 
getncattr(self, name)
retrievel a netCDF variable attribute.
 
ncattrs(self)
return netCDF attribute names for this Variable in a list.
 
set_auto_maskandscale(self, maskandscale)
turn on or off automatic conversion of variable data to and from masked arrays and automatic packing/unpacking of variable data using scale_factor and add_offset attributes.
 
setncattr(self, name, value)
set a netCDF variable attribute using name,value pair.

Inherited from object: __format__, __hash__, __reduce__, __reduce_ex__, __repr__, __sizeof__, __str__, __subclasshook__

Instance Variables
  dimensions
A tuple containing the names of the dimensions associated with this variable.
  dtype
A numpy dtype object describing the variable's data type.
  ndim
The number of variable dimensions.
  shape
a tuple describing the current size of all the variable's dimensions.
Properties
  maskandscale
  size
Return the number of stored elements.

Inherited from object: __class__

Method Details

__delattr__(...)

 

x.__delattr__('name') <==> del x.name

Overrides: object.__delattr__

__getattribute__(...)

 

x.__getattribute__('name') <==> x.name

Overrides: object.__getattribute__

__init__(self, dset, name, datatype, dimensions=(), fill_value=None)
(Constructor)

 

x.__init__(...) initializes x; see x.__class__.__doc__ for signature

Overrides: object.__init__

__new__(T, S, ...)

 
Returns: a new object with type S, a subtype of T
Overrides: object.__new__

__setattr__(...)

 

x.__setattr__('name', value) <==> x.name = value

Overrides: object.__setattr__

assignValue(self, val)

 

assign a value to a scalar variable. Provided for compatibility with Scientific.IO.NetCDF, can also be done by assigning to a slice ([:]).

delncattr(self, name, value)

 

delete a netCDF variable attribute. Only use if you need to delete a netCDF attribute with the same name as one of the reserved python attributes.

getValue(self)

 

get the value of a scalar variable. Provided for compatibility with Scientific.IO.NetCDF, can also be done by slicing ([:]).

getncattr(self, name)

 

retrievel a netCDF variable attribute. Only use if you need to set a netCDF attribute with the same name as one of the reserved python attributes.

set_auto_maskandscale(self, maskandscale)

 

turn on or off automatic conversion of variable data to and from masked arrays and automatic packing/unpacking of variable data using scale_factor and add_offset attributes.

If maskandscale is set to True, when data is read from a variable it is converted to a masked array if any of the values are exactly equal to the either the netCDF _FillValue or the value specified by the missing_value variable attribute. The fill_value of the masked array is set to the missing_value attribute (if it exists), otherwise the netCDF _FillValue attribute (which has a default value for each data type). When data is written to a variable, the masked array is converted back to a regular numpy array by replacing all the masked values by the fill_value of the masked array.

If maskandscale is set to True, and the variable has a scale_factor and an add_offset attribute, then data read from that variable is unpacked using:

   data = self.scale_factor*data + self.add_offset

When data is written to a variable it is packed using:

   data = (data - self.add_offset)/self.scale_factor

For more information on how scale_factor and add_offset can be used to provide simple compression, see http://www.cdc.noaa.gov/cdc/conventions/cdc_netcdf_standard.shtml.

The default value of maskandscale is True (automatic conversions are performed).

setncattr(self, name, value)

 

set a netCDF variable attribute using name,value pair. Only use if you need to set a netCDF attribute with the same name as one of the reserved python attributes.