[Numpy-discussion] dtype
Colin J. Williams
cjw at sympatico.ca
Wed Feb 22 07:29:05 EST 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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