o
&i @ sd d dl Z d dlZd dlZd dlZd dlZd dlZd dlZd dlmZm Z m
Z
d dl m Z d dl
mZmZmZ d dlZg dZdd Zdd ZG d
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Zdd Zdd Zdd Zd1ddZdd Z da da d2ddZ d1dd Z e dd3d d Z!e dej"fd d!Z#i Z$e%d"ej&Z'e d $ d4d%d&Z(d'd( Z)d)d* Z*d+d, Z+d-d. Z,d/d0 Z-dS )5 N) issubclass_ issubsctype
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set_module)ndarrayufuncasarray)
r r r deprecatedeprecate_with_doc get_includeinfosourcewholookfor byte_bounds safe_eval show_runtimec C s ddl m} m}m} ddlm} g }g g }}|D ]}| | r%|| q|| q|d|||di zddlm} || W n
t yQ t
d Y nw || dS ) a
Print information about various resources in the system
including available intrinsic support and BLAS/LAPACK library
in use
See Also
--------
show_config : Show libraries in the system on which NumPy was built.
Notes
-----
1. Information is derived with the help of `threadpoolctl `_
library.
2. SIMD related information is derived from ``__cpu_features__``,
``__cpu_baseline__`` and ``__cpu_dispatch__``
Examples
--------
>>> import numpy as np
>>> np.show_runtime()
[{'simd_extensions': {'baseline': ['SSE', 'SSE2', 'SSE3'],
'found': ['SSSE3',
'SSE41',
'POPCNT',
'SSE42',
'AVX',
'F16C',
'FMA3',
'AVX2'],
'not_found': ['AVX512F',
'AVX512CD',
'AVX512_KNL',
'AVX512_KNM',
'AVX512_SKX',
'AVX512_CLX',
'AVX512_CNL',
'AVX512_ICL']}},
{'architecture': 'Zen',
'filepath': '/usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so',
'internal_api': 'openblas',
'num_threads': 12,
'prefix': 'libopenblas',
'threading_layer': 'pthreads',
'user_api': 'blas',
'version': '0.3.20'}]
r __cpu_features____cpu_baseline____cpu_dispatch__)pprintZsimd_extensions)Zbaselinefound not_found)threadpool_infozWARNING: `threadpoolctl` not found in system! Install it by `pip install threadpoolctl`. Once installed, try `np.show_runtime` again for more detailed build informationN) numpy.core._multiarray_umathr r r r appendZ
threadpoolctlr extend ImportErrorprint) r r r r Z config_foundZfeatures_foundZfeatures_not_foundfeaturer r! :C:\wamp64\www\opt\env\Lib\site-packages\numpy/lib/utils.pyr s, /
r c C sX ddl } | jdu rtjtj| jdd}|S ddlm} tjtj|jd}|S )a
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()])
...
r Ncoreinclude) numpyZ show_configospathjoindirname__file__
numpy.corer# )r% dr# r! r! r" r a s
r c @ s" e Zd ZdZdddZdd ZdS )
_Deprecatez
Decorator class to deprecate old functions.
Refer to `deprecate` for details.
See Also
--------
deprecate
Nc C s || _ || _|| _d S N)old_namenew_namemessage)selfr/ r0 r1 r! r! r" __init__ s
z_Deprecate.__init__c
s2 | j }| j}| j}|du rj}|du rd| nd||f |dur) d| 7 t fdd}||_j}|du rB }nR| d} t | dd }
| d
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d | }n't | d d } | dd D ]} t | |
krv n | t | d 7 } ql|| d }t
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Decorator call. Refer to ``decorate``.
Nz`%s` is deprecated!z%`%s` is deprecated, use `%s` instead!
c s t j tdd | i |S )N )
stacklevel)warningswarnDeprecationWarning)argskwdsZdepdocfuncr! r" newfunc s z$_Deprecate.__call__..newfunc r z
)r/ r0 r1 __name__ functoolswraps__doc__
expandtabssplit _get_indentlstriplentextwrapindentr( )
r2 r= r: kwargsr/ r0 r1 r> doclinesrK skipliner! r< r" __call__ s@
z_Deprecate.__call__)NNN)rA
__module__ __qualname__rD r3 rQ r! r! r! r" r- ~ s
r- c C sD t j}| D ]}t| }|rt|t|| }q|t jkr d}|S )zU
Determines the leading whitespace that could be removed from all the lines.
r )sysmaxsizerI rH min)rN rK rP contentr! r! r" rG s
rG c O s8 | r| d }| dd } t | i ||S t | i |S )a
Issues a DeprecationWarning, adds warning to `old_name`'s
docstring, rebinds ``old_name.__name__`` and returns the new
function object.
This function may also be used as a decorator.
Parameters
----------
func : function
The function to be deprecated.
old_name : str, optional
The name of the function to be deprecated. Default is None, in
which case the name of `func` is used.
new_name : str, optional
The new name for the function. Default is None, in which case the
deprecation message is that `old_name` is deprecated. If given, the
deprecation message is that `old_name` is deprecated and `new_name`
should be used instead.
message : str, optional
Additional explanation of the deprecation. Displayed in the
docstring after the warning.
Returns
-------
old_func : function
The deprecated function.
Examples
--------
Note that ``olduint`` returns a value after printing Deprecation
Warning:
>>> olduint = np.deprecate(np.uint)
DeprecationWarning: `uint64` is deprecated! # may vary
>>> olduint(6)
6
r r? Nr- )r: rL fnr! r! r" r s
, r c C s
t | dS )a
Deprecates a function and includes the deprecation in its docstring.
This function is used as a decorator. It returns an object that can be
used to issue a DeprecationWarning, by passing the to-be decorated
function as argument, this adds warning to the to-be decorated function's
docstring and returns the new function object.
See Also
--------
deprecate : Decorate a function such that it issues a `DeprecationWarning`
Parameters
----------
msg : str
Additional explanation of the deprecation. Displayed in the
docstring after the warning.
Returns
-------
obj : object
)r1 rX )msgr! r! r" r
s
r
c
C s | j }|d d }|d }|d }t| jj}| }}|du r*|| j| 7 }||fS t||D ]\}} | dk r@||d | 7 }q/||d | 7 }q/||7 }||fS )a#
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); I.dtype
dtype('float64')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
datar stridesshapeNr? )Z__array_interface__r dtypeitemsizesizezip)
aZaiZa_dataZastridesZashapeZbytes_aZa_lowZa_highr] Zstrider! r! r" r $ s r c
C s | du r t j}|j} g }i }| D ]D}t| | trX| | }t|}|| v r6|d|| }d}n|||< |}d}dt t
|j } t
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|
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|jj|g qd} d} d}
d}|D ]8}| t|d k rst|d } | t|d k rt|d } |
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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 80 int64
b 20 160 float64
Upper bound on total bytes = 240
>>> d = {'x': np.arange(2.0), 'y': np.arange(3.0), 'txt': 'Some str',
... 'idx':5}
>>> np.who(d)
Name Shape Bytes Type
===========================================================
x 2 16 float64
y 3 24 float64
Upper bound on total bytes = 40
Nz (%s)r r? z x r5
z Name %s Shape %s Bytes %s Typer@ r4 = z%s %s %s %s %s %s %s z'
Upper bound on total bytes = %d)rT _getframef_back f_globalskeys
isinstancer idr( mapstrr] nbytesr r^ namerI intmaxr )vardictframeZstacacherq varZidvnamestroriginalZshapestrZbytestrZmaxnameZmaxshapeZmaxbyteZ
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C s d}d}dd }t | dt| }t |d|}| j}| jj}|du r$tj}td||d td | j|d td
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j
|d tdt| jjj|f |d tdd|d |dv rtd|tj|f |d d} n#|dkrtd||f |d tjdk} ntd||f |d tjdk} td|| |d td | j |d dS ) aO Provide information about ndarray obj.
Parameters
----------
obj : ndarray
Must be ndarray, not checked.
output
Where printed output goes.
Notes
-----
Copied over from the numarray module prior to its removal.
Adapted somewhat as only numpy is an option now.
Called by info.
r{ c S s | S r. r! )r r! r! r" s z_info.. __class__rA Nzclass: filezshape: z strides: z
itemsize: z aligned: z contiguous: z fortran: zdata pointer: %s%sz byteorder: r@ )endr )|re z%s%s%sF>z%sbig%sbigz
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objoutputextraZticbpclsnmr\ Zendianbyteswapr! r! r" _info s>
r L c C sT ddl }ddl}t| dst| dr| j} nt| dr | j} |du r%tj}| du r/tt dS t| t r>> 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. ***
r NZ_ppimport_importer_ppimport_module_ppimport_attr)r z+
*** Repeat reference found in %s *** r z *** Found in %s ***-r? zHelp for %s not found.z+
*** Total of %d references found. ***z()r@ r4 r3 c S s g | ]
}|d dkr|qS )r _r! ).0methr! r! r"
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Methods:
Nonez %s -- %srD ) pydocinspecthasattrr r rT r r rl r r ro _namedictr _dictlistrm r r KeyError
isfunctionismethodrA signature ExceptionrI r getdocisclassr3 Z
allmethodsr Zsplitdoc)objectZmaxwidthr toplevelr r ZnumfoundZobjlistrx r rq r| ZargstrZdoc1methodsZpublic_methodsr ZthisobjZmethstrotherr! r! r" r & s 5
r c C sX ddl }ztd|| |d t|| |d W dS ty+ td|d Y dS w )a
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) #doctest: +SKIP
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) #doctest: +SKIP
Not available for this object.
r Nz In file: %s
r z Not available for this object.)r r
getsourcefile getsourcer )r r r r! r! r" r
s ) r
z[a-z0-9_]+\(.*[,=].*\)TFc s ddl }t||| g }t| sdS D ] \}\}} }
| dv r(q | tfddD r<|| q dddddfd d
fd d } |j| d
dd } | dt
| g}
|ddd D ]=} | \} }dd dD }z|d }t
|r|d }W n ty d}Y nw |
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Do a keyword search on docstrings.
A list 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') # doctest: +SKIP
Search results for 'binary representation'
------------------------------------------
numpy.binary_repr
Return the binary representation of the input number as a string.
numpy.core.setup_common.long_double_representation
Given a binary dump as given by GNU od -b, look for long double
numpy.base_repr
Return a string representation of a number in the given base system.
...
r N)r r c 3 s | ]}| v V qd S r. r! r w)rM r! r" 7 s zlookfor..i )r= classr r c s d}d | dd d |t fddD 7 }|tfddD 7 }|t d 7 }||d7 }|d d
7 }|t| d d 7 }|S )
Nr r4 rg c g | ]}| v rd qS ) r! r ) first_docr! r" r E z.lookfor..relevance..c r ) r! r )rq r! r" r G r rf r .rd d i) r( lowerstriprF sumrI getcountrs )rq Zdocstrkindindexr)kind_relevancewhats)r rq r" relevanceA s zlookfor..relevancec s | g | R S r. r! )rb )rv r r! r" relevance_valueQ s z lookfor..relevance_value)keyzSearch results for '%s'r@ r c S s g | ]
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%szNothing found.rd )r _lookfor_generate_cachero r rF itemsallr sortr( rI r _function_signature_research
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Generate docstring cache for given module.
Parameters
----------
module : str, None, module
Module for which to generate docstring cache
import_modules : bool
Whether to import sub-modules in packages.
regenerate : bool
Re-generate the docstring cache
Returns
-------
cache : dict {obj_full_name: (docstring, kind, index), ...}
Docstring cache for the module, either cached one (regenerate=False)
or newly generated.
r N)StringIOr% Tr? r r __path__z __init__.pyz.pyr3 z%s.%srA rR r r rQ r= )(r ior rl ro r r rT moduleslisttupleupdater rm _lookfor_cachesrA r ismodule__all__AttributeErrorr r r& listdirr' r( isfileendswithr stderrKeyboardInterrupt
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startswithr r r r )r r r r r rv modseenr stackrq itemr Z_allpthZmod_pathZthis_pyZinit_pyZ to_importZ
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Wr c sD dd l }z| }W |S ty! fddt D }Y |S w )Nr c s$ g | ]}t |r|t |fqS r! )r r )r r r r! r" r s z _getmembers..)r
getmembersr dir)r r membersr! r r" r s r c C s ddl }|| S )au
Protected string evaluation.
Evaluate a string containing a Python literal expression without
allowing the execution of arbitrary non-literal code.
.. warning::
This function is identical to :py:meth:`ast.literal_eval` and
has the same security implications. It may not always be safe
to evaluate large input strings.
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
>>> np.safe_eval('open("/home/user/.ssh/id_dsa").read()')
Traceback (most recent call last):
...
ValueError: malformed node or string: <_ast.Call object at 0x...>
r N)ast literal_eval)r
r r! r! r" r s 2
r c C sr | j dkr|S t| jd|d}tj|r |d}t| dkr7t |tj
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Utility function to check median result from data for NaN values at the end
and return NaN in that case. Input result can also be a MaskedArray.
Parameters
----------
data : array
Sorted input data to median function
result : Array or MaskedArray
Result of median function.
axis : int
Axis along which the median was computed.
Returns
-------
result : scalar or ndarray
Median or NaN in axes which contained NaN in the input. If the input
was an array, NaN will be inserted in-place. If a scalar, either the
input itself or a scalar NaN.
r r )axisF)r` npisnanZtakemaZ
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r c C sr ddl m} m}m} t|dkrt|dkrdS d|}|D ]}| | r.|d| d7 }q |d| d7 }q |S )a
Returns a string contains the supported CPU features by the current build.
The string format can be explained as follows:
- dispatched features that are supported by the running machine
end with `*`.
- dispatched features that are "not" supported by the running machine
end with `?`.
- remained features are representing the baseline.
r r r{ r@ *?)r r r r rI r( )r r r Zenabled_featuresr r! r! r" _opt_infob s
r r. )r% )Nr Nr% )NTFN).r& rT rJ r rer7 rB Znumpy.core.numerictypesr r r Znumpy.core.overridesr r+ r r r r% r r r r r- rG r r
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