\Kc @ s d d k Z d d k Z d d k Z d d k Z d d k l Z l Z l Z d d k l Z l
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d d d d d d d
d d d
d d d d d g Z d Z d d Z e i d- j o d d k Z d Z n
d Z d e f d YZ d Z d Z e e d d Z d Z d Z d d Z d Z d a d a d! d" Z d d# e i d! d$ Z e i d% Z h a! e i" d& e i# Z$ d e% e& d d' Z' d( Z( d) Z) d* e f d+ YZ* d, Z+ d S(. iN( t issubclass_t issubsctypet
issubdtype( t productt ndarrayR t get_numpy_includeR R t deprecatet deprecate_with_doct get_numarray_includet get_includet infot sourcet whot lookfort byte_boundst may_share_memoryt safe_evalc C s~ d d k } | i d j o+ t i i t i i | i d d } n4 d d k i } t i i t i i | i d } | S( s
Return the directory that contains the NumPy \*.h header files.
Extension modules that need to compile against NumPy should use this
function to locate the appropriate include directory.
Notes
-----
When using ``distutils``, for example in ``setup.py``.
::
import numpy as np
...
Extension('extension_name', ...
include_dirs=[np.get_include()])
...
iNt coret include(
t numpyt show_configt Nonet ost patht joint dirnamet __file__t
numpy.coreR ( R t dR ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s +$c C sA d d k l } | } | d j o | d S| t g Sd S( s
Return the directory that contains the numarray \*.h header files.
Extension modules that need to compile against numarray should use this
function to locate the appropriate include directory.
Parameters
----------
type : any, optional
If `type` is not None, the location of the NumPy headers is returned
as well.
Returns
-------
dirs : str or list of str
If `type` is None, `dirs` is a string containing the path to the
numarray headers.
If `type` is not None, `dirs` is a list of strings with first the
path(s) to the numarray headers, followed by the path to the NumPy
headers.
Notes
-----
Useful when using ``distutils``, for example in ``setup.py``.
::
import numpy as np
...
Extension('extension_name', ...
include_dirs=[np.get_numarray_include()])
...
i( t get_numarray_include_dirsi N( t numpy.numarrayR R R ( t typeR t include_dirs( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR , s
"
i i c C s+ t i | i | i | | i | i } | S( N( t newt functiont func_codet func_globalst
func_defaultst func_closure( t funct name( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt _set_function_nameY s c C s
| | _ | S( N( t __name__( R' R( ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR) ^ s t
_Deprecatec B s) e Z d Z d d d d Z d Z RS( s
Decorator class to deprecate old functions.
Refer to `deprecate` for details.
See Also
--------
deprecate
c C s | | _ | | _ | | _ d S( N( t old_namet new_namet message( t selfR, R- R. ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt __init__m s c
sG | i } | i } | i } d d k | d j o0 y
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Decorator call. Refer to ``decorate``.
iNs `%s` is deprecated!s% `%s` is deprecated, use `%s` instead!s
c s i t | | S( s1 `arrayrange` is deprecated, use `arange` instead!( t warnt DeprecationWarning( t argst kwds( t depdoct warningsR' ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt newfunc s s
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R, R- R. R6 R t func_namet AttributeErrorR* R) t __doc__R t __dict__t update(
R/ R' R3 t kwargsR, R- R. R7 t docR ( ( R5 R6 R' s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt __call__r s8
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__module__R: R R0 R? ( ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR+ b s
c O s | op | d } | d } d | j o | i d | d >> olduint = np.deprecate(np.uint)
>>> olduint(6)
/usr/lib/python2.5/site-packages/numpy/lib/utils.py:114:
DeprecationWarning: uint32 is deprecated
warnings.warn(str1, DeprecationWarning)
6
i i t newnameR- t oldnameR, N( t popR+ ( R3 R= t fn( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s -
c C s
t d | S( R. ( R+ ( t msg( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt s c C s | i } | d d } | d } | d } t | } t | d d } | } } | d j o | t | d t | 7} n` xR t | | D]A \ } }
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7} q W| | 7} | | f S(
s!
Returns pointers to the end-points of an array.
Parameters
----------
a : ndarray
Input array. It must conform to the Python-side of the array interface.
Returns
-------
(low, high) : tuple of 2 integers
The first integer is the first byte of the array, the second integer is
just past the last byte of the array. If `a` is not contiguous it
will not use every byte between the (`low`, `high`) values.
Examples
--------
>>> I = np.eye(2, dtype='f'); I.dtype
dtype('float32')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
>>> I = np.eye(2, dtype='G'); I.dtype
dtype('complex192')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
t datai t stridest shapet typestri t dtypei N( t __array_interface__t lent intR R t zip( t at ait a_datat astridest ashapet nd_at bytes_at a_lowt a_highRI t stride( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s
c C sG t | \ } } t | \ } } | | j p
| | j o t St S( s
Determine if two arrays can share memory
The memory-bounds of a and b are computed. If they overlap then
this function returns True. Otherwise, it returns False.
A return of True does not necessarily mean that the two arrays
share any element. It just means that they *might*.
Parameters
----------
a, b : ndarray
Returns
-------
out : bool
Examples
--------
>>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
False
( R t Falset True( RP t bRW RX t b_lowt b_high( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s
c C s | d j o t i i } | i } n g } h } x | i D] } t | | t o | | } t | } | | i j o | d | | } d } n | | | <| } d } d i t
t | i } t | i
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| i | | |
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d } x t t | D] } | | } | t | d j o t | d } n | t | d j o t | d } n |
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} d | d | d | d f } | d
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| d d | t | d d | d d | t | d d | d d | t | d d | d f GHqWd | GHd S( s&
Print the Numpy arrays in the given dictionary.
If there is no dictionary passed in or `vardict` is None then returns
Numpy arrays in the globals() dictionary (all Numpy arrays in the
namespace).
Parameters
----------
vardict : dict, optional
A dictionary possibly containing ndarrays. Default is globals().
Returns
-------
out : None
Returns 'None'.
Notes
-----
Prints out the name, shape, bytes and type of all of the ndarrays present
in `vardict`.
Examples
--------
>>> a = np.arange(10)
>>> b = np.ones(20)
>>> np.who()
Name Shape Bytes Type
===========================================================
a 10 40 int32
b 20 160 float64
Upper bound on total bytes = 200
>>> d = {'x': np.arange(2.0), 'y': np.arange(3.0), 'txt': 'Some str',
... 'idx':5}
>>> np.whos(d)
Name Shape Bytes Type
===========================================================
y 3 24 float64
x 2 16 float64
Upper bound on total bytes = 40
s (%s)i i s x i i i
s Name %s Shape %s Bytes %s Typet s
t =i s %s %s %s %s %s %s %si s'
Upper bound on total bytes = %dN( R t syst _getframet f_backt f_globalst keyst
isinstanceR t idR t mapt strRI t nbytest appendRK R( t rangeRM RN t max( t vardictt framet stat cacheR( t vart idvt namestrt originalt shapestrt bytestrt maxnamet maxshapet maxbytet
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d } n | } | t | t | } | | j o2 | d t | } | d d | d | } q4 | | | } q4 W| S( Ns , t i s ,
R_ i ( RM t split(
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R c C s t | t t g } h | i | i 6} | i g } | i g } x t | d j o Pn | i d } x~ | i D]p } t | | t i
oS | | i } | | j o5 | | i } | i | | i | | | | >> np.info(np.polyval) # doctest: +SKIP
polyval(p, x)
Evaluate the polynomial p at x.
...
When using a string for `object` it is possible to get multiple results.
>>> np.info('fft') # doctest: +SKIP
*** Found in numpy ***
Core FFT routines
...
*** Found in numpy.fft ***
fft(a, n=None, axis=-1)
...
*** Repeat reference found in numpy.fft.fftpack ***
*** Total of 3 references found. ***
iNt _ppimport_importert _ppimport_modulet _ppimport_attrt outputR i i s+
*** Repeat reference found in %s *** s *** Found in %s ***t -s Help for %s not found.s+
*** Total of %d references found. ***R_ s
s ()R0 s , t (s
Methods:
t _R s %s -- %ss Instance of class: R? R( s %ss R: () t pydoct inspectt hasattrR R R R
Rf R R t numarrayRi t _namedictR t _dictlistRg Rk t KeyErrort
isfunctionR8 t
formatargspect
getargspecRM R t getdoct isclassR* R0 t im_funcR R t
allmethodst getattrt splitdocR R t InstanceTypet __class__R? R( t ismethod( t objectt maxwidthR t toplevelR R t nnt numfoundt objlistRt t objR( R t argstrR t doc1t methodst metht thisobjt methstrt otherR> ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR
s 2
)
c C sR d d k } y. | d | i | IJ| | i | IJWn | d IJn Xd S( s
Print or write to a file the source code for a Numpy object.
The source code is only returned for objects written in Python. Many
functions and classes are defined in C and will therefore not return
useful information.
Parameters
----------
object : numpy object
Input object. This can be any object (function, class, module, ...).
output : file object, optional
If `output` not supplied then source code is printed to screen
(sys.stdout). File object must be created with either write 'w' or
append 'a' modes.
See Also
--------
lookfor, info
Examples
--------
>>> np.source(np.interp)
In file: /usr/lib/python2.6/dist-packages/numpy/lib/function_base.py
def interp(x, xp, fp, left=None, right=None):
""".... (full docstring printed)"""
if isinstance(x, (float, int, number)):
return compiled_interp([x], xp, fp, left, right).item()
else:
return compiled_interp(x, xp, fp, left, right)
The source code is only returned for objects written in Python.
>>> np.source(np.array)
Not available for this object.
iNs In file: %s
s Not available for this object.( R t
getsourcefilet getsource( R R R ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s ' s [a-z_]+\(.*[,=].*\)c s d d k } t | | | g } t | i i p d Sx i D]| \ } \ } } }
| d j o qU n t } | i } x& D] }
|
| j o t } Pq q W| o | i | qU qU Wh d d 6d d 6d d 6d d 6 f d f d
} | i | d d i
} | d
t | g } x | D] } | \ } } } g } | i i d D]$ } | i o | | i qq~ } y8 | d i } t
i | o | d i } n Wn t j
o
d } n X| i d | | f qXW| p | i d n | d j o | i d i
| nE t | d j o# | i } | d i
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Do a keyword search on docstrings.
A list of of objects that matched the search is displayed,
sorted by relevance. All given keywords need to be found in the
docstring for it to be returned as a result, but the order does
not matter.
Parameters
----------
what : str
String containing words to look for.
module : str or list, optional
Name of module(s) whose docstrings to go through.
import_modules : bool, optional
Whether to import sub-modules in packages. Default is True.
regenerate : bool, optional
Whether to re-generate the docstring cache. Default is False.
output : file-like, optional
File-like object to write the output to. If omitted, use a pager.
See Also
--------
source, info
Notes
-----
Relevance is determined only roughly, by checking if the keywords occur
in the function name, at the start of a docstring, etc.
Examples
--------
>>> np.lookfor('binary representation')
Search results for 'binary representation'
------------------------------------------
numpy.binary_repr
Return the binary representation of the input number as a string.
numpy.base_repr
Return a string representation of a number in the given base system.
...
iNR R i R' t classic s d } d i | i i i d d } | t g } D] } | | j o | d q? q? ~ 7} | t g } D] } | | j o | d q{ q{ ~ 7} | t | d 7} | i | d 7} | | i d d 7} | t | d
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d Z d
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Object to evaluate constant string expressions.
This includes strings with lists, dicts and tuples using the abstract
syntax tree created by ``compiler.parse``.
For an example of usage, see `safe_eval`.
See Also
--------
safe_eval
c K s2 | i } t | d | i | i } | | | S( Nt visit( R R R* t default( R/ t nodet kwt clsR ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s c K s t d | i d S( Ns Unsupported source construct: %s( t SyntaxErrorR ( R/ R R ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s c K s( x! | i D] } | i | | SWd S( N( t
getChildNodesR ( R/ R R t child( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt visitExpression s
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visitConst s c K sF t g } | i D]+ \ } } | | i | | i | f q ~ S( N( t dictt itemsR ( R/ R R R R| R ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt visitDict s c K s1 t g } | i D] } | | i | q ~ S( N( R t nodesR ( R/ R R R t i( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt
visitTuple s c K s+ g } | i D] } | | i | q ~ S( N( R% R ( R/ R R R R& ( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyt visitList s c K s | i | i d
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c C sv d d k } t } y | i | d } Wn t j
o } n Xy | i | SWn t j
o } n Xd S( s
Protected string evaluation.
Evaluate a string containing a Python literal expression without
allowing the execution of arbitrary non-literal code.
Parameters
----------
source : str
The string to evaluate.
Returns
-------
obj : object
The result of evaluating `source`.
Raises
------
SyntaxError
If the code has invalid Python syntax, or if it contains non-literal
code.
Examples
--------
>>> np.safe_eval('1')
1
>>> np.safe_eval('[1, 2, 3]')
[1, 2, 3]
>>> np.safe_eval('{"foo": ("bar", 10.0)}')
{'foo': ('bar', 10.0)}
>>> np.safe_eval('import os')
Traceback (most recent call last):
...
SyntaxError: invalid syntax
>>> safe_eval('open("/home/user/.ssh/id_dsa").read()')
Traceback (most recent call last):
...
SyntaxError: Unsupported source construct: compiler.ast.CallFunc
iNt eval( t compilerR t parseR R ( R R- t walkert astt err( ( s5 /usr/lib64/python2.6/site-packages/numpy/lib/utils.pyR s , ( i i (, R Ra R t ret numpy.core.numerictypesR R R R R R R R R R t version_infoR! R) R R+ R R R R R R R R R R R R
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