[Numpy-discussion] dtype

Colin J. Williams cjw at sympatico.ca
Wed Feb 22 07:29:05 CST 2006


I've been trying to gain some understanding of dtype from the builtin 
documentation and would appreciate advice.

I don't find anything in http://projects.scipy.org/scipy/numpy or 
http://wiki.python.org/moin/NumPy

Chapter 2.1 of the book has a good overview, but little reference material.

In the following, dt= numpy.dtype

Some specific problems are flagged ** below.

Colin W.

[Dbg]>>> h(dt)
Help on class dtype in module numpy:

class dtype(__builtin__.object)
 |  Methods defined here:
 | 
 |  __cmp__(...)
 |      x.__cmp__(y) <==> cmp(x,y)
 | 
 |  __getitem__(...)
 |      x.__getitem__(y) <==> x[y]
 | 
 |  __len__(...)
 |      x.__len__() <==> len(x)
 | 
 |  __reduce__(...)
 |      self.__reduce__()  for pickling.
 | 
 |  __repr__(...)
 |      x.__repr__() <==> repr(x)
 | 
 |  __setstate__(...)
 |      self.__setstate__()  for pickling.
 | 
 |  __str__(...)
 |      x.__str__() <==> str(x)
 | 
 |  newbyteorder(...)
 |      self.newbyteorder(<endian>) returns a copy of the dtype object
 |      with altered byteorders.  If <endian> is not given all byteorders
 |      are swapped.  Otherwise endian can be '>', '<', or '=' to force
 |      a byteorder.  Descriptors in all fields are also updated in the
 |      new dtype object.
 | 
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 | 
 |  __new__ = <built-in method __new__ of type object>   
 |      T.__new__(S, ...) -> a new object with type S, a subtype of 
T               ** What are the parameters?  In other words,
 |                                                                                                                         
what does ... stand for?  **
 | 
 |  alignment = <member 'alignment' of 'numpy.dtype' objects>
 | 
 | 
 |  base = <attribute 'base' of 'numpy.dtype' objects>
 |      The base data-type or self if no subdtype
 | 
 |  byteorder = <member 'byteorder' of 'numpy.dtype' objects>
 | 
 | 
 |  char = <member 'char' of 'numpy.dtype' objects>
 | 
 | 
 |  descr = <attribute 'descr' of 'numpy.dtype' objects>
 |      The array_protocol type descriptor.
 | 
 |  fields = <attribute 'fields' of 'numpy.dtype' objects>
 | 
 | 
 |  hasobject = <member 'hasobject' of 'numpy.dtype' objects>
 | 
 | 
 |  isbuiltin = <attribute 'isbuiltin' of 'numpy.dtype' objects>
 |      Is this a buillt-in data-type descriptor?
 | 
 |  isnative = <attribute 'isnative' of 'numpy.dtype' objects>
 |      Is the byte-order of this descriptor native?
 | 
 |  itemsize = <member 'itemsize' of 'numpy.dtype' objects>
 | 
 | 
 |  kind = <member 'kind' of 'numpy.dtype' objects>
 | 
 | 
 |  name = <attribute 'name' of 'numpy.dtype' objects>
 |      The name of the true data-type
 | 
 |  num = <member 'num' of 'numpy.dtype' objects>
 | 
 | 
 |  shape = <attribute 'shape' of 'numpy.dtype' objects>
 |      The shape of the subdtype or (1,)
 | 
 |  str = <attribute 'str' of 'numpy.dtype' objects>
 |      The array_protocol typestring.
 | 
 |  subdtype = <attribute 'subdtype' of 'numpy.dtype' objects>
 |      A tuple of (descr, shape) or None.
 | 
 |  type = <member 'type' of 'numpy.dtype' objects>

[Dbg]>>> 
dt.num.__doc__                                                        ** 
no doc string   **
[Dbg]>>> help(dt.num)
Help on member_descriptor object:

num = class member_descriptor(object)
 |  Methods defined here:
 | 
 |  __delete__(...)
 |      descr.__delete__(obj)
 | 
 |  __get__(...)
 |      descr.__get__(obj[, type]) -> value
 | 
 |  __getattribute__(...)
 |      x.__getattribute__('name') <==> x.name
 | 
 |  __repr__(...)
 |      x.__repr__() <==> repr(x)
 | 
 |  __set__(...)
 |      descr.__set__(obj, value)
 | 
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 | 
 |  __objclass__ = <member '__objclass__' of 'member_descriptor' objects>

[Dbg]>>> help(dt.num)
Help on member_descriptor object:

num = class member_descriptor(object)
 |  Methods defined here:
 | 
 |  __delete__(...)
 |      descr.__delete__(obj)
 | 
 |  __get__(...)
 |      descr.__get__(obj[, type]) -> value
 | 
 |  __getattribute__(...)
 |      x.__getattribute__('name') <==> x.name
 | 
 |  __repr__(...)
 |      x.__repr__() <==> repr(x)
 | 
 |  __set__(...)
 |      descr.__set__(obj, value)
 | 
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 | 
 |  __objclass__ = <member '__objclass__' of 'member_descriptor' objects>

[Dbg]>>> help(dt.num.__objclass__)
Help on class dtype in module numpy:

class dtype(__builtin__.object)
 |  Methods defined here:
 | 
 |  __cmp__(...)
 |      x.__cmp__(y) <==> cmp(x,y)
 | 
 |  __getitem__(...)
 |      x.__getitem__(y) <==> x[y]
 | 
 |  __len__(...)
 |      x.__len__() <==> len(x)
 | 
 |  __reduce__(...)
 |      self.__reduce__()  for pickling.
 | 
 |  __repr__(...)
 |      x.__repr__() <==> repr(x)
 | 
 |  __setstate__(...)
 |      self.__setstate__()  for pickling.
 | 
 |  __str__(...)
 |      x.__str__() <==> str(x)
 | 
 |  newbyteorder(...)
 |      self.newbyteorder(<endian>) returns a copy of the dtype object
 |      with altered byteorders.  If <endian> is not given all byteorders
 |      are swapped.  Otherwise endian can be '>', '<', or '=' to force
 |      a byteorder.  Descriptors in all fields are also updated in the
 |      new dtype object.
 | 
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 | 
 |  __new__ = <built-in method __new__ of type object>
 |      T.__new__(S, ...) -> a new object with type S, a subtype of T
 | 
 |  alignment = <member 'alignment' of 'numpy.dtype' objects>
 | 
 | 
 |  base = <attribute 'base' of 'numpy.dtype' objects>
 |      The base data-type or self if no subdtype
 | 
 |  byteorder = <member 'byteorder' of 'numpy.dtype' objects>
 | 
 | 
 |  char = <member 'char' of 'numpy.dtype' objects>
 | 
 | 
 |  descr = <attribute 'descr' of 'numpy.dtype' objects>
 |      The array_protocol type descriptor.
 | 
 |  fields = <attribute 'fields' of 'numpy.dtype' objects>
 | 
 | 
 |  hasobject = <member 'hasobject' of 'numpy.dtype' objects>
 | 
 | 
 |  isbuiltin = <attribute 'isbuiltin' of 'numpy.dtype' objects>
 |      Is this a buillt-in data-type descriptor?
 | 
 |  isnative = <attribute 'isnative' of 'numpy.dtype' objects>
 |      Is the byte-order of this descriptor native?
 | 
 |  itemsize = <member 'itemsize' of 'numpy.dtype' objects>
 | 
 | 
 |  kind = <member 'kind' of 'numpy.dtype' objects>
 | 
 | 
 |  name = <attribute 'name' of 'numpy.dtype' objects>
 |      The name of the true 
data-type                                                   **     How 
does this differ from what, in common
 |                                                                                                                 
Python usage, is a class.__name__?  **
 | 
 |  num = <member 'num' of 'numpy.dtype' 
objects>                           **      What does this mean?    **
 | 
 | 
 |  shape = <attribute 'shape' of 'numpy.dtype' objects>
 |      The shape of the subdtype or (1,)
 | 
 |  str = <attribute 'str' of 'numpy.dtype' objects>
 |      The array_protocol typestring.
 | 
 |  subdtype = <attribute 'subdtype' of 'numpy.dtype' objects>
 |      A tuple of (descr, shape) or None.
 | 
 |  type = <member 'type' of 'numpy.dtype' objects>

[Dbg]>>>
**  There is no __module__ attribute.  How does one identify the modules 
holding the code?  **




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