SicVar instances should be automatically initialized with the get()
function. When importing a variable, get() calls the instance creator
SicVar() with three arguments: SIC variable name (as a Python string), its level
(as an integer), and memory address of its descriptor (Python integer). It is the own
responsibility of the get() function to assign this instance to the correct
Python variable name.
During the initialization, SicVar() defines three attributes to the instance:
__sicname__, __siclevel__, and __sicdata__. By convention the '__' delimiters denote objects that are
hidden to the user, but still accessible. __sicname__ and __siclevel__ are a Python string and an integer,
and are used to keep a trace of what the original SIC variable is. __sicdata__ is a numpy.ndarray initialized with the informations provided by the descriptor (data address, dimensions,
type,...).
>>> Sic.define('real a')
A is a REAL*4, 0D (RW) -> a
>>> vars(a) # vars() displays attributes names and values
{'__sicdata__': array(0.0, dtype=float32), '__sicname__': 'A', '__siclevel__': 0}
>>> type(a.__sicdata__)
<type 'numpy.ndarray'> # A NumPy array
>>> type(a.__sicname__)
<type 'str'> # A Python string
>>> type(a.__siclevel__)
<type 'int'> # A Python integer
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SicVar instances are used to import SIC standard variables (scalars or arrays). Due
to its class type, it can also accept new attributes, and thus be used to import
images (for example in an instance named ima). In this case, the image (the
array component) is imported through the __sicdata__ attribute (ima.__sicdata__), and can be
directly accessed from ima (ima[0,0]). Header variables are imported
into other attributes (ima.naxis1, ima.naxis2,...), provided they do
not attempt to overwrite a numpy.ndarray attribute or method. As any other imported SIC
variables, these header attributes are themselves SicVar instances. See subsection
2.4.4 for details and example on importing SIC images.
All attributes of a SicVar instance are write-protected against deletion or
overwriting. This is a first importance for __sicdata__, because deleting it would be
dramatic. Remember that the command a.__sicdata__ = 0 do not modify its content
but bounds it to the 0 integer, loosing data and all information about the
corresponding SIC variable. But end-user should never have to deal with the __sicdata__ attribute, and have to work on the instance itself instead (for example
a[0] = 0).
These warnings also apply to images attributes: do not try ima.naxis1 = 0
but ima.naxis1[0] = 0 instead.
SicVar instances come with a set of methods and attributes, for one part inherited from the numpy.ndarray type, and for the other part (re)defined at instance initialization. For example the addition (__add__ and __radd__) is redefined to add numbers or concatenate character strings.
>>> dir(a) # All attributes and methods. ['__add__', '__copy__', '__deepcopy__', '__delattr__', '__div__', '__doc__', '__eq__', '__ge__', '__getattr__', '__getitem__', '__gt__', '__iadd__', '__idiv__', '__imul__', '__init__', '__int__', '__isub__', '__le__', '__len__', '__lt__', '__module__', '__mul__', '__ne__', '__nonzero__', '__radd__', '__rdiv__', '__repr__', '__rmul__', '__rsub__', '__setattr__', '__setitem__', '__sicdata__', '__sicname__', '__str__', '__sub__', 'astype', 'byteswapped', 'copy', 'iscontiguous', 'itemsize', 'resize', 'savespace', 'spacesaver', 'tolist', 'toscalar', 'tostring', 'typecode'] |