| Current File : //proc/self/root/proc/self/root/lib64/python2.7/site-packages/numpy/testing/utils.pyo |
�
E�`Qc @ s� d Z d d l Z d d l Z d d l Z d d l Z d d l Z d d l Z d d l m Z d d d d d d d
d d d
d d d d d d d d d d d d d d d g Z d Z
d d � Z d � Z d! � Z
d" � Z d# � Z e j d$ d% k r*d& e j � g d' � Z d& e j � d( � Z n g d) � Z d* � Z e j d+ k r�e j d, d- k r�d d d d d. � Z d/ d d0 � Z n d1 e dU d4 � Z d e d5 � Z d6 � Z d7 d e d8 � Z d7 d e d9 � Z d e d d: � Z d e d; � Z d< d e d= � Z d e d> � Z! d? � Z" d@ � Z# d e dA � Z$ dB � Z% dC � Z& d dD � Z' dE d dF � Z( dG � Z) dH d d e dI � Z* dE dJ � Z+ dE d dK � Z, d dL � Z- dM � Z. dN � Z/ dO e0 f dP � � YZ1 dQ e0 f dR � � YZ2 dS � Z3 dT � Z4 d S(V s)
Utility function to facilitate testing.
i����N( t import_noset assert_equalt assert_almost_equalt assert_approx_equalt assert_array_equalt assert_array_lesst assert_string_equalt assert_array_almost_equalt
assert_raisest
build_err_msgt decorate_methodst jiffiest memusaget print_assert_equalt raisest randt rundocst runstringt verboset measuret assert_t assert_array_almost_equal_nulpt assert_array_max_ulpt assert_warnst assert_no_warningst assert_allclosei t c C s | s t | � � n d S( s
Assert that works in release mode.
The Python built-in ``assert`` does not work when executing code in
optimized mode (the ``-O`` flag) - no byte-code is generated for it.
For documentation on usage, refer to the Python documentation.
N( t AssertionError( t valt msg( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR s
c C sA d d l m } | | � } t | t j � r= t d � � n | S( s� like isnan, but always raise an error if type not supported instead of
returning a TypeError object.
Notes
-----
isnan and other ufunc sometimes return a NotImplementedType object instead
of raising any exception. This function is a wrapper to make sure an
exception is always raised.
This should be removed once this problem is solved at the Ufunc level.i����( t isnans! isnan not supported for this type( t
numpy.coreR t
isinstancet typest NotImplementedTypet TypeError( t xR t st( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt gisnan% s
c C sh d d l m } m } | d d � } z1 | | � } t | t j � rU t d � � n Wd | | � X| S( s� like isfinite, but always raise an error if type not supported instead of
returning a TypeError object.
Notes
-----
isfinite and other ufunc sometimes return a NotImplementedType object instead
of raising any exception. This function is a wrapper to make sure an
exception is always raised.
This should be removed once this problem is solved at the Ufunc level.i����( t isfinitet seterrt invalidt ignores$ isfinite not supported for this typeN( R R' R( R R! R" R# ( R$ R' R( t errR% ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt gisfinite6 s c C sh d d l m } m } | d d � } z1 | | � } t | t j � rU t d � � n Wd | | � X| S( s� like isinf, but always raise an error if type not supported instead of
returning a TypeError object.
Notes
-----
isinf and other ufunc sometimes return a NotImplementedType object instead
of raising any exception. This function is a wrapper to make sure an
exception is always raised.
This should be removed once this problem is solved at the Ufunc level.i����( t isinfR( R) R* s! isinf not supported for this typeN( R R- R( R R! R" R# ( R$ R- R( R+ R% ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt gisinfK s c G sk d d l } d d l m } m } | | | � } | j } x* t t | � � D] } | j � | | <qM W| S( s� Returns an array of random numbers with the given shape.
This only uses the standard library, so it is useful for testing purposes.
i����N( t zerost float64( t randomR R/ R0 t flatt ranget len( t argsR1 R/ R0 t resultst ft i( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR ` s i t linuxs
/proc/%s/statc C s� d d l } | s( | j | j � � n y@ t | d � } | j � j d � } | j � t | d � SWn t d | j � | d � SXd S( sx Return number of jiffies (1/100ths of a second) that this
process has been scheduled in user mode. See man 5 proc. i����Nt rt i
id i ( t timet appendt opent readlinet splitt closet int( t _proc_pid_statt
_load_timeR< R7 t l( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR n s
c C sO y@ t | d � } | j � j d � } | j � t | d � SWn d SXd S( sD Return virtual memory size in bytes of the running python.
R: R; i N( R> R? R@ RA RB ( RC R7 RE ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR } s
c C sD d d l } | s( | j | j � � n t d | j � | d � S( s� Return number of jiffies (1/100ths of a second) that this
process has been scheduled in user mode. [Emulation with time.time]. i����Nid i ( R< R= RB ( RD R< ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s c C s
t � d S( s9 Return memory usage of running python. [Not implemented]N( t NotImplementedError( ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s t nti s 2.3c C s� d d l } | d k r$ | j } n | j | | | d | | f � } | j � } zT | j | | � } z- | j | � | j | | � \ }
} | SWd | j | � XWd | j | � Xd S( Ni����(
t win32pdht Nonet PDH_FMT_LONGt MakeCounterPatht OpenQueryt
AddCountert CollectQueryDatat GetFormattedCounterValuet
RemoveCountert
CloseQuery( t objectt countert instancet inumt formatt machineRH t patht hqt hct typeR ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt GetPerformanceAttributes� s
!
t pythonc C s( d d l } t d d | | | j d � S( Ni����t Processs
Virtual Bytes( RH R\ RJ RI ( t processNameRT RH ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s s Items are not equal:t ACTUALt DESIREDc C s d | g } | rl | j d � d k r\ t | � d t | � k r\ | d d | g } ql | j | � n | rx� t | � D]� \ } } y t | � } Wn
d } n X| j d � d k r� d j | j � d � } | d 7} n | j d | | | f � q Wn d j | � S(
Ns
i����iO i R; s
[repr failed]i s ...s %s: %s( t findR4 R= t enumeratet reprt countt joint
splitlines( t arrayst err_msgt headerR t namesR R8 t aR: ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s
1
"c
C s� t | t � r� t | t � s9 t t t | � � � � n t t | � t | � | | � x` | j � D]R \ } } | | k r� t t | � � � n t | | | | d | | f | � qe Wd St | t t f � rNt | t t f � rNt t | � t | � | | � x? t
t | � � D]+ } t | | | | d | | f | � qWd Sd d l m } m
} m } d d l m } m }
m } t | | � s�t | | � r�t | | | | � St | | g | d | �} y | | � p�| | � }
Wn t k
rt }
n X|
r�| | � r5|
| � } | | � } n | } d } | | � rh|
| � } | | � } n | } d } y t | | � t | | � Wq�t k
r�t | � � q�Xn y� | | � | | � k r�t | � � n t | � o�t | � sXt | � } t | � } | s| r9| o$| sTt | � � qTn | | k sTt | � � n d S| d k r�| d k r�| | � | | � k s�t | � � q�n Wn t t t f k
r�n X| | k r�t | � � n d S( s[
Raise an assertion if two objects are not equal.
Given two objects (scalars, lists, tuples, dictionaries or numpy arrays),
check that all elements of these objects are equal. An exception is raised
at the first conflicting values.
Parameters
----------
actual : array_like
The object to check.
desired : array_like
The expected object.
err_msg : str, optional
The error message to be printed in case of failure.
verbose : bool, optional
If True, the conflicting values are appended to the error message.
Raises
------
AssertionError
If actual and desired are not equal.
Examples
--------
>>> np.testing.assert_equal([4,5], [4,6])
...
<type 'exceptions.AssertionError'>:
Items are not equal:
item=1
ACTUAL: 5
DESIRED: 6
s key=%r
%sNs
item=%r
%si����( t ndarrayt isscalart signbit( t iscomplexobjt realt imagR i ( R t dictR Rd R[ R R4 t itemst listt tupleR3 R Rm Rn Ro t numpy.libRp Rq Rr R R t
ValueErrort FalseR, R& R# RF ( t actualt desiredRi R t kR8 Rm Rn Ro Rp Rq Rr R t
usecomplext actualrt actualit desiredrt desiredit isdesnant isactnan( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � st # )* )
c C s� d d l } | | k s� d d l } | j � } | j | � | j d � | j | | � | j d � | j | | � t | j � � � n d S( s�
Test if two objects are equal, and print an error message if test fails.
The test is performed with ``actual == desired``.
Parameters
----------
test_string : str
The message supplied to AssertionError.
actual : object
The object to test for equality against `desired`.
desired : object
The expected result.
Examples
--------
>>> np.testing.print_assert_equal('Test XYZ of func xyz', [0, 1], [0, 1])
>>> np.testing.print_assert_equal('Test XYZ of func xyz', [0, 1], [0, 2])
Traceback (most recent call last):
...
AssertionError: Test XYZ of func xyz failed
ACTUAL:
[0, 1]
DESIRED:
[0, 2]
i����Ns failed
ACTUAL:
s
DESIRED:
( t pprintt cStringIOt StringIOt writeR t getvalue( t test_stringRz R{ R� R� R ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR
< s
i c C sL d d l m } d d l m } m } m } y | | � pD | | � } Wn t k
ra t } n Xt | | g | d | d d | �}
| r@| | � r� | | � } | | � } n | } d } | | � r� | | � }
| | � } n | }
d } y* t | |
d | �t | | d | �Wq@t
k
r<t
|
� � q@Xn t | | t t
f � spt | | t t
f � r�t | | | | � Sy} t | � o�t | � s�t | � s�t | � r�t | � o�t | � s�t
|
� � q�n | | k s�t
|
� � n d SWn t t f k
rn Xt t | | � | � d k rHt
|
� � n d S(
s�
Raise an assertion if two items are not equal up to desired precision.
.. note:: It is recommended to use one of `assert_allclose`,
`assert_array_almost_equal_nulp` or `assert_array_max_ulp`
instead of this function for more consistent floating point
comparisons.
The test is equivalent to ``abs(desired-actual) < 0.5 * 10**(-decimal)``.
Given two objects (numbers or ndarrays), check that all elements of these
objects are almost equal. An exception is raised at conflicting values.
For ndarrays this delegates to assert_array_almost_equal
Parameters
----------
actual : array_like
The object to check.
desired : array_like
The expected object.
decimal : int, optional
Desired precision, default is 7.
err_msg : str, optional
The error message to be printed in case of failure.
verbose : bool, optional
If True, the conflicting values are appended to the error message.
Raises
------
AssertionError
If actual and desired are not equal up to specified precision.
See Also
--------
assert_allclose: Compare two array_like objects for equality with desired
relative and/or absolute precision.
assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
Examples
--------
>>> import numpy.testing as npt
>>> npt.assert_almost_equal(2.3333333333333, 2.33333334)
>>> npt.assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)
...
<type 'exceptions.AssertionError'>:
Items are not equal:
ACTUAL: 2.3333333333333002
DESIRED: 2.3333333399999998
>>> npt.assert_almost_equal(np.array([1.0,2.3333333333333]),
... np.array([1.0,2.33333334]), decimal=9)
...
<type 'exceptions.AssertionError'>:
Arrays are not almost equal
<BLANKLINE>
(mismatch 50.0%)
x: array([ 1. , 2.33333333])
y: array([ 1. , 2.33333334])
i����( Rm ( Rp Rq Rr R Rj s* Arrays are not almost equal to %d decimalsi t decimalN( R Rm Rw Rp Rq Rr Rx Ry R R R R Rv Ru R R, R& RF R# t roundt abs( Rz R{ R� Ri R Rm Rp Rq Rr R} R R~ R R� R� ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR d sN =
c C s� d d l } t t | | f � \ } } | | k r7 d S| j d d � } zH d | j | � | j | � } | j d | j | j | � � � } Wd | j | � Xy | | } Wn t k
r� d } n Xy | | } Wn t k
r� d } n Xt | | g | d d | d
| �}
y} t
| � o/t
| � s�t | � sJt | � rtt | � o_t | � s�t |
� � q�n | | k s�t |
� � n d SWn t
t f k
r�n X| j | | � | j d | d � k r�t |
� � n d S(
sK
Raise an assertion if two items are not equal up to significant digits.
.. note:: It is recommended to use one of `assert_allclose`,
`assert_array_almost_equal_nulp` or `assert_array_max_ulp`
instead of this function for more consistent floating point
comparisons.
Given two numbers, check that they are approximately equal.
Approximately equal is defined as the number of significant digits
that agree.
Parameters
----------
actual : scalar
The object to check.
desired : scalar
The expected object.
significant : int, optional
Desired precision, default is 7.
err_msg : str, optional
The error message to be printed in case of failure.
verbose : bool, optional
If True, the conflicting values are appended to the error message.
Raises
------
AssertionError
If actual and desired are not equal up to specified precision.
See Also
--------
assert_allclose: Compare two array_like objects for equality with desired
relative and/or absolute precision.
assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
Examples
--------
>>> np.testing.assert_approx_equal(0.12345677777777e-20, 0.1234567e-20)
>>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345671e-20,
significant=8)
>>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345672e-20,
significant=8)
...
<type 'exceptions.AssertionError'>:
Items are not equal to 8 significant digits:
ACTUAL: 1.234567e-021
DESIRED: 1.2345672000000001e-021
the evaluated condition that raises the exception is
>>> abs(0.12345670e-20/1e-21 - 0.12345672e-20/1e-21) >= 10**-(8-1)
True
i����NR) R* g �?i
g Rj s- Items are not equal to %d significant digits:R g $@i ( t numpyt mapt floatR( R� t powert floort log10t ZeroDivisionErrorR R, R& R R# RF ( Rz R{ t significantRi R t npR+ t scalet
sc_desiredt sc_actualR ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � sB 8 (
*c s� d d l m } m } m } m } m }
m } | � d t d t �� | � d t d t �� d � } d � � � � � f d � }
y�� j d k p� � j d k p� � j � j k } | st
� � g � d � j � j f d � d
� d d �} | st | � � qn | � � rQ| � � rQ| � � | � � } } | � � | � � } } | | � ss| | � r�|
| | d d �n | | � s�| | � r�|
� |
k � |
k d d �|
� | k � | k d d �n | | } } | | O} | | O} |
| � rd S| | � r?| � | � | � } q`| � � � } n | � � � } t | t
� r�| } d g } n$ | j � } | j � } | j � } | sd d | j d � t | � } t
� � g � d | f d � d
� d d �} | st | � � qn Wnn t k
r�} d d l } | j � } d | � f � t
� � g � d � d
� d d �} t | � � n Xd S( Ni����( t arrayR R- t anyt allt inft copyt subokc S s | j j d k S( Ns ?bhilqpBHILQPefdgFDG( t dtypet char( R$ ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt isnumber? s t nanc
sd y t | | � WnL t k
r_ t � � g � d | d � d � d d �} t | � � n Xd S( sT Handling nan/inf: check that x and y have the nan/inf at the same
locations.s
x and y %s location mismatch:R Rj Rk R$ t yN( R$ R� ( R R R ( t x_idt y_idt hasvalR ( Ri Rj R R$ R� ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt chk_same_positionB s
s
(shapes %s, %s mismatch)R Rj Rk R$ R� R� s +infs -infi id g Y@i s
(mismatch %s%%)s error during assertion:
%s
%s( ( ( R$ R� ( R$ R� ( R$ R� ( R R� R R- R� R� R� Ry t Truet shapeR R R t boolt ravelt tolistRe R4 Rx t tracebackt
format_exc( t
comparisonR$ R� Ri R Rj R� R R- R� R� R� R� R� t condR t x_isnant y_isnant x_isinft y_isinfR� R� R t reducedt matcht eR� t efmt( ( Ri Rj R R$ R� s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt assert_array_compare9 sn . 0 !$
! c
C s) t t j | | d | d | d d �d S( s&
Raise an assertion if two array_like objects are not equal.
Given two array_like objects, check that the shape is equal and all
elements of these objects are equal. An exception is raised at
shape mismatch or conflicting values. In contrast to the standard usage
in numpy, NaNs are compared like numbers, no assertion is raised if
both objects have NaNs in the same positions.
The usual caution for verifying equality with floating point numbers is
advised.
Parameters
----------
x : array_like
The actual object to check.
y : array_like
The desired, expected object.
err_msg : str, optional
The error message to be printed in case of failure.
verbose : bool, optional
If True, the conflicting values are appended to the error message.
Raises
------
AssertionError
If actual and desired objects are not equal.
See Also
--------
assert_allclose: Compare two array_like objects for equality with desired
relative and/or absolute precision.
assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
Examples
--------
The first assert does not raise an exception:
>>> np.testing.assert_array_equal([1.0,2.33333,np.nan],
... [np.exp(0),2.33333, np.nan])
Assert fails with numerical inprecision with floats:
>>> np.testing.assert_array_equal([1.0,np.pi,np.nan],
... [1, np.sqrt(np.pi)**2, np.nan])
...
<type 'exceptions.ValueError'>:
AssertionError:
Arrays are not equal
<BLANKLINE>
(mismatch 50.0%)
x: array([ 1. , 3.14159265, NaN])
y: array([ 1. , 3.14159265, NaN])
Use `assert_allclose` or one of the nulp (number of floating point values)
functions for these cases instead:
>>> np.testing.assert_allclose([1.0,np.pi,np.nan],
... [1, np.sqrt(np.pi)**2, np.nan],
... rtol=1e-10, atol=0)
Ri R Rj s Arrays are not equalN( R� t operatort __eq__( R$ R� Ri R ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s ?i c s� d d l m � m � m � d d l m � d d l m � � � � � � � f d � } t | | | d | d | d d � �d
S( s�
Raise an assertion if two objects are not equal up to desired precision.
.. note:: It is recommended to use one of `assert_allclose`,
`assert_array_almost_equal_nulp` or `assert_array_max_ulp`
instead of this function for more consistent floating point
comparisons.
The test verifies identical shapes and verifies values with
``abs(desired-actual) < 0.5 * 10**(-decimal)``.
Given two array_like objects, check that the shape is equal and all
elements of these objects are almost equal. An exception is raised at
shape mismatch or conflicting values. In contrast to the standard usage
in numpy, NaNs are compared like numbers, no assertion is raised if
both objects have NaNs in the same positions.
Parameters
----------
x : array_like
The actual object to check.
y : array_like
The desired, expected object.
decimal : int, optional
Desired precision, default is 6.
err_msg : str, optional
The error message to be printed in case of failure.
verbose : bool, optional
If True, the conflicting values are appended to the error message.
Raises
------
AssertionError
If actual and desired are not equal up to specified precision.
See Also
--------
assert_allclose: Compare two array_like objects for equality with desired
relative and/or absolute precision.
assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
Examples
--------
the first assert does not raise an exception
>>> np.testing.assert_array_almost_equal([1.0,2.333,np.nan],
[1.0,2.333,np.nan])
>>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
... [1.0,2.33339,np.nan], decimal=5)
...
<type 'exceptions.AssertionError'>:
AssertionError:
Arrays are not almost equal
<BLANKLINE>
(mismatch 50.0%)
x: array([ 1. , 2.33333, NaN])
y: array([ 1. , 2.33339, NaN])
>>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
... [1.0,2.33333, 5], decimal=5)
<type 'exceptions.ValueError'>:
ValueError:
Arrays are not almost equal
x: array([ 1. , 2.33333, NaN])
y: array([ 1. , 2.33333, 5. ])
i����( t aroundt numbert float_( t
issubdtype( R� c s� y� � t | � � s' � t | � � r� t | � } t | � } | | k sO t S| j | j k ol d k n r{ | | k S| | } | | } n Wn t t f k
r� n Xt | | � } � | j � � s� | j � � } n � | � � d � k S( Ni g $@( R. Ry t sizeR# RF R� R� t astype( R$ R� t xinfidt yinfidt z( R� R� R� R� t npanyR� ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt compare s $ "
Ri R Rj s* Arrays are not almost equal to %d decimalsN( R R� R� R� t numpy.core.numerictypesR� t numpy.core.fromnumericR� R� ( R$ R� R� Ri R R� ( ( R� R� R� R� R� R� s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s E c
C s) t t j | | d | d | d d �d S( s<
Raise an assertion if two array_like objects are not ordered by less than.
Given two array_like objects, check that the shape is equal and all
elements of the first object are strictly smaller than those of the
second object. An exception is raised at shape mismatch or incorrectly
ordered values. Shape mismatch does not raise if an object has zero
dimension. In contrast to the standard usage in numpy, NaNs are
compared, no assertion is raised if both objects have NaNs in the same
positions.
Parameters
----------
x : array_like
The smaller object to check.
y : array_like
The larger object to compare.
err_msg : string
The error message to be printed in case of failure.
verbose : bool
If True, the conflicting values are appended to the error message.
Raises
------
AssertionError
If actual and desired objects are not equal.
See Also
--------
assert_array_equal: tests objects for equality
assert_array_almost_equal: test objects for equality up to precision
Examples
--------
>>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1.1, 2.0, np.nan])
>>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1, 2.0, np.nan])
...
<type 'exceptions.ValueError'>:
Arrays are not less-ordered
(mismatch 50.0%)
x: array([ 1., 1., NaN])
y: array([ 1., 2., NaN])
>>> np.testing.assert_array_less([1.0, 4.0], 3)
...
<type 'exceptions.ValueError'>:
Arrays are not less-ordered
(mismatch 50.0%)
x: array([ 1., 4.])
y: array(3)
>>> np.testing.assert_array_less([1.0, 2.0, 3.0], [4])
...
<type 'exceptions.ValueError'>:
Arrays are not less-ordered
(shapes (3,), (1,) mismatch)
x: array([ 1., 2., 3.])
y: array([4])
Ri R Rj s Arrays are not less-orderedN( R� R� t __lt__( R$ R� Ri R ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR . s Ac B s | | Ud S( N( ( t astrRs ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR s s c
C s* d d l } t | t � s1 t t | �
� � n t | t � sV t t | �
� � n t j d | d | t j � rz d St | j � j
| j d � | j d � � � } g } x5| r�| j d � } | j
d � r� q� n | j
d � r�| g } | j d � } | j
d � r2| j | � | j d � } n | j
d
� sQt |
� � n | j | � | j d � } | j
d � r�| j | � n | j d | � t j d | d d | d � r�q� n | j | � q� n t |
� � q� W| s�d Sd d
j | � j � } | | k r&t | � � n d S( s�
Test if two strings are equal.
If the given strings are equal, `assert_string_equal` does nothing.
If they are not equal, an AssertionError is raised, and the diff
between the strings is shown.
Parameters
----------
actual : str
The string to test for equality against the expected string.
desired : str
The expected string.
Examples
--------
>>> np.testing.assert_string_equal('abc', 'abc')
>>> np.testing.assert_string_equal('abc', 'abcd')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
...
AssertionError: Differences in strings:
- abc+ abcd? +
i����Ns \As \Zi i s s - s ? s + i s Differences in strings:
%sR ( t difflibR t strR R[ t reR� t MRu t DifferR� Rg t popt
startswithR= t insertt extendRf t rstrip(
Rz R{ R� t difft diff_listt d1RE t d2t d3R ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR v sH 0
"
c sc d d l } d d l } | d k rC t j d � } | j d } n t j j t j j | � � d } t j j
| � g } | j | | � \ } } } z | j | | | | � }
Wd | j
� X| j � j |
� } | j d t � } g � | r� f d � }
n d }
x! | D] } | j | d |
�qW| j d k r_| r_t d d
j � � � � n d S( sT
Run doctests found in the given file.
By default `rundocs` raises an AssertionError on failure.
Parameters
----------
filename : str
The path to the file for which the doctests are run.
raise_on_error : bool
Whether to raise an AssertionError when a doctest fails. Default is
True.
Notes
-----
The doctests can be run by the user/developer by adding the ``doctests``
argument to the ``test()`` call. For example, to run all tests (including
doctests) for `numpy.lib`:
>>> np.lib.test(doctests=True) #doctest: +SKIP
i����Ni t __file__i R c s
� j | � S( N( R= ( t s( R ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt <lambda>� s t outs Some doctests failed:
%ss
( t doctestt impRI t syst _getframet f_globalst osRX t splitextt basenamet dirnamet find_modulet load_moduleRA t
DocTestFinderRb t
DocTestRunnerRy t runt failuresR Rf ( t filenamet raise_on_errorR� R� R7 t nameRX t filet pathnamet descriptiont mt testst runnerR� t test( ( R s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s( "
c O s t � } | j j | | � S( N( R t toolsR ( R5 t kwargst nose( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s c O s t � } | j j | | � S( s�
assert_raises(exception_class, callable, *args, **kwargs)
Fail unless an exception of class exception_class is thrown
by callable when invoked with arguments args and keyword
arguments kwargs. If a different type of exception is
thrown, it will not be caught, and the test case will be
deemed to have suffered an error, exactly as for an
unexpected exception.
( R R� R ( R5 R� R� ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s c C s� | d k r% t j d t j � } n t j | � } | j } d d l m } t | | j � � } x� | D]} } y( t
| d � r� | j } n | j } Wn t
k
r� qi n X| j | � ri | j d � ri t | | | | � � qi qi Wd S( s
Apply a decorator to all methods in a class matching a regular expression.
The given decorator is applied to all public methods of `cls` that are
matched by the regular expression `testmatch`
(``testmatch.search(methodname)``). Methods that are private, i.e. start
with an underscore, are ignored.
Parameters
----------
cls : class
Class whose methods to decorate.
decorator : function
Decorator to apply to methods
testmatch : compiled regexp or str, optional
The regular expression. Default value is None, in which case the
nose default (``re.compile(r'(?:^|[\b_\.%s-])[Tt]est' % os.sep)``)
is used.
If `testmatch` is a string, it is compiled to a regular expression
first.
s (?:^|[\\b_\\.%s-])[Tt]esti����( t
isfunctiont compat_func_namet _N( RI R� t compileR� t sept __dict__t inspectR� t filtert valuest hasattrR� t __name__t AttributeErrort searchR� t setattr( t clst decoratort testmatcht cls_attrR� t methodst functiont funcname( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR
� s
i c B s� e j d � } | j | j } } e | d | d � } d } e � } x$ | | k rm | d 7} | | | UqJ We � | } d | S( sD
Return elapsed time for executing code in the namespace of the caller.
The supplied code string is compiled with the Python builtin ``compile``.
The precision of the timing is 10 milli-seconds. If the code will execute
fast on this timescale, it can be executed many times to get reasonable
timing accuracy.
Parameters
----------
code_str : str
The code to be timed.
times : int, optional
The number of times the code is executed. Default is 1. The code is
only compiled once.
label : str, optional
A label to identify `code_str` with. This is passed into ``compile``
as the second argument (for run-time error messages).
Returns
-------
elapsed : float
Total elapsed time in seconds for executing `code_str` `times` times.
Examples
--------
>>> etime = np.testing.measure('for i in range(1000): np.sqrt(i**2)',
... times=times)
>>> print "Time for a single execution : ", etime / times, "s"
Time for a single execution : 0.005 s
i s Test name: %s t execi g{�G�z�?( R� R� t f_localsR� R� R ( t code_strt timest labelt framet locst globst codeR8 t elapsed( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR , s !
c C s� d d l } | j d � } | j d � j d d � } | } d } t j | � } x# t d � D] } | | | � } q^ Wt t j | � | k � d S( sg
Check that ufuncs don't mishandle refcount of object `1`.
Used in a few regression tests.
i����Nid i i i' i' ( R� t aranget reshapeR� t getrefcountR3 R ( t opR� Rl t bt cR8 t rct jt d( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt _assert_valid_refcount[ s gH�����z>c
s| d d l � � � � f d � } � j | � � j | � } } d � � f } t | | | d t | � d | d | �d S( s
Raise an assertion if two objects are not equal up to desired tolerance.
The test is equivalent to ``allclose(actual, desired, rtol, atol)``.
It compares the difference between `actual` and `desired` to
``atol + rtol * abs(desired)``.
Parameters
----------
actual : array_like
Array obtained.
desired : array_like
Array desired.
rtol : float, optional
Relative tolerance.
atol : float, optional
Absolute tolerance.
err_msg : str, optional
The error message to be printed in case of failure.
verbose : bool, optional
If True, the conflicting values are appended to the error message.
Raises
------
AssertionError
If actual and desired are not equal up to specified precision.
See Also
--------
assert_array_almost_equal_nulp, assert_array_max_ulp
Examples
--------
>>> x = [1e-5, 1e-3, 1e-1]
>>> y = np.arccos(np.cos(x))
>>> assert_allclose(x, y, rtol=1e-5, atol=0)
i����Nc s � j | | d � d � �S( Nt rtolt atol( t allclose( R$ R� ( R$ R� R# ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR� � s s' Not equal to tolerance rtol=%g, atol=%gRi R Rj ( R� t
asanyarrayR� R� ( Rz R{ R# R$ Ri R R� Rj ( ( R$ R� R# s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR m s ( c C s� d d l } | j | � } | j | � } | | j | j | | k | | � � } | j | j | | � | k � s� | j | � s� | j | � r� d | } n( | j t | | � � } d | | f } t | � � n d S( s
Compare two arrays relatively to their spacing.
This is a relatively robust method to compare two arrays whose amplitude
is variable.
Parameters
----------
x, y : array_like
Input arrays.
nulp : int, optional
The maximum number of unit in the last place for tolerance (see Notes).
Default is 1.
Returns
-------
None
Raises
------
AssertionError
If the spacing between `x` and `y` for one or more elements is larger
than `nulp`.
See Also
--------
assert_array_max_ulp : Check that all items of arrays differ in at most
N Units in the Last Place.
spacing : Return the distance between x and the nearest adjacent number.
Notes
-----
An assertion is raised if the following condition is not met::
abs(x - y) <= nulps * spacing(max(abs(x), abs(y)))
Examples
--------
>>> x = np.array([1., 1e-10, 1e-20])
>>> eps = np.finfo(x.dtype).eps
>>> np.testing.assert_array_almost_equal_nulp(x, x*eps/2 + x)
>>> np.testing.assert_array_almost_equal_nulp(x, x*eps + x)
------------------------------------------------------------
Traceback (most recent call last):
...
AssertionError: X and Y are not equal to 1 ULP (max is 2)
i����Ns X and Y are not equal to %d ULPs+ X and Y are not equal to %d ULP (max is %g)( R� R� t spacingt whereR� Rp t maxt nulp_diffR ( R$ R� t nulpR� t axt ayt refR t max_nulp( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s 2 ("
c C sJ d d l } t | | | � } | j | | k � sF t d | � � n | S( s�
Check that all items of arrays differ in at most N Units in the Last Place.
Parameters
----------
a, b : array_like
Input arrays to be compared.
maxulp : int, optional
The maximum number of units in the last place that elements of `a` and
`b` can differ. Default is 1.
dtype : dtype, optional
Data-type to convert `a` and `b` to if given. Default is None.
Returns
-------
ret : ndarray
Array containing number of representable floating point numbers between
items in `a` and `b`.
Raises
------
AssertionError
If one or more elements differ by more than `maxulp`.
See Also
--------
assert_array_almost_equal_nulp : Compare two arrays relatively to their
spacing.
Examples
--------
>>> a = np.linspace(0., 1., 100)
>>> res = np.testing.assert_array_max_ulp(a, np.arcsin(np.sin(a)))
i����Ns( Arrays are not almost equal up to %g ULP( R� R* R� R ( Rl R t maxulpR� R� t ret( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s $
c s. d d l � | r? � j | d | �} � j | d | �} n � j | � } � j | � } � j | | � } � j | � s� � j | � r� t d � � n � j | d | �} � j | d | �} | j | j k s� t d | j | j f � � n � f d � } t | � } t | � } | | | | � S( sD For each item in x and y, return the number of representable floating
points between them.
Parameters
----------
x : array_like
first input array
y : array_like
second input array
Returns
-------
nulp: array_like
number of representable floating point numbers between each item in x
and y.
Examples
--------
# By definition, epsilon is the smallest number such as 1 + eps != 1, so
# there should be exactly one ULP between 1 and 1 + eps
>>> nulp_diff(1, 1 + np.finfo(x.dtype).eps)
1.0
i����NR� s' _nulp not implemented for complex arrays+ x and y do not have the same shape: %s - %sc s& � j | | d | �} � j | � S( NR� ( R� R� ( t rxt ryt vdtR� ( R� ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt _diff1 s ( R� R� t common_typeRp RF R� Rx t integer_repr( R$ R� R� t tR5 R2 R3 ( ( R� s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR* s$ c C s\ | j | � } | j d k s? | | | d k | | d k <n | d k rX | | } n | S( Ni i ( t viewR� ( R$ R4 t compR2 ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt
_integer_repr9 s !
c C s d d l } | j | j k r: t | | j | j d � � S| j | j k rh t | | j | j d
� � St d | j � � d S( sQ Return the signed-magnitude interpretation of the binary representation of
x.i����Ni i i? s Unsupported dtype %sI � i �l l���� ( R� R� t float32R; t int32R0 t int64Rx ( R$ R� ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR7 G s t WarningMessagec B s, e Z d Z d Z d
d
d � Z d � Z RS( s�
Holds the result of a single showwarning() call.
Notes
-----
`WarningMessage` is copied from the Python 2.6 warnings module,
so it can be used in NumPy with older Python versions.
t messaget categoryR� t linenoR� t linec C sS t � } x% | j D] } t | | | | � q W| rF | j | _ n d | _ d S( N( t localst _WARNING_DETAILSR R t _category_nameRI ( t selfR@ RA R� RB R� RC t local_valuest attr( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt __init__c s c C s& d | j | j | j | j | j f S( NsD {message : %r, category : %r, filename : %r, lineno : %s, line : %r}( R@ RF R� RB RC ( RG ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt __str__m s ( s messages categorys filenames linenos files lineN( R t
__module__t __doc__RE RI RJ RK ( ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR? T s
t WarningManagerc B s/ e Z d Z e d d � Z d � Z d � Z RS( s�
A context manager that copies and restores the warnings filter upon
exiting the context.
The 'record' argument specifies whether warnings should be captured by a
custom implementation of ``warnings.showwarning()`` and be appended to a
list returned by the context manager. Otherwise None is returned by the
context manager. The objects appended to the list are arguments whose
attributes mirror the arguments to ``showwarning()``.
The 'module' argument is to specify an alternative module to the module
named 'warnings' and imported under that name. This argument is only useful
when testing the warnings module itself.
Notes
-----
`WarningManager` is a copy of the ``catch_warnings`` context manager
from the Python 2.6 warnings module, with slight modifications.
It is copied so it can be used in NumPy with older Python versions.
c C s> | | _ | d k r( t j d | _ n | | _ t | _ d S( Nt warnings( t _recordRI R� t modulest _moduleRy t _entered( RG t recordt module( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyRJ � s
c s� | j r t d | � � n t | _ | j j | _ | j | j _ | j j | _ | j r� g � � f d � } | | j _ � Sd Sd S( Ns Cannot enter %r twicec s � j t | | � � d S( N( R= R? ( R5 R� ( t log( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt showwarning� s (
RS t RuntimeErrorR� RR t filterst _filtersRW t _showwarningRP RI ( RG RW ( ( RV s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt __enter__� s c C s> | j s t d | � � n | j | j _ | j | j _ d S( Ns% Cannot exit %r without entering first( RS RX RZ RR RY R[ RW ( RG ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt __exit__� s N( R RL RM Ry RI RJ R\ R] ( ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyRN r s c O s� t d t � } | j � } t j d � zq | | | � } t | � d k sb t d | j � � n | d j | k r� t d | j | | d f � � n Wd | j � X| S( s�
Fail unless the given callable throws the specified warning.
A warning of class warning_class should be thrown by the callable when
invoked with arguments args and keyword arguments kwargs.
If a different type of warning is thrown, it will not be caught, and the
test case will be deemed to have suffered an error.
Parameters
----------
warning_class : class
The class defining the warning that `func` is expected to throw.
func : callable
The callable to test.
\*args : Arguments
Arguments passed to `func`.
\*\*kwargs : Kwargs
Keyword arguments passed to `func`.
Returns
-------
The value returned by `func`.
RT t alwaysi s! No warning raised when calling %ss( First warning for %s is not a %s( is %s)N(
RN R� R\ RO t simplefilterR4 R R RA R] ( t
warning_classt funcR5 t kwt ctxRE t result( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s
! c O s{ t d t � } | j � } t j d � zA | | | � } t | � d k rh t d | j | f � � n Wd | j � X| S( sK
Fail if the given callable produces any warnings.
Parameters
----------
func : callable
The callable to test.
\*args : Arguments
Arguments passed to `func`.
\*\*kwargs : Kwargs
Keyword arguments passed to `func`.
Returns
-------
The value returned by `func`.
RT R^ i s Got warnings when calling %s: %sN( RN R� R\ RO R_ R4 R R R] ( Ra R5 Rb Rc RE Rd ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyR � s
( R` Ra (5 RM R� R� R� R� R! RO t
nosetesterR t __all__R R R& R, R. R t platformt getpidR R R� t versionRI R\ R� R R R
R R R� R R R R R R R R R
R R" R R R R* R; R7 RR R? RN R R ( ( ( s9 /usr/lib64/python2.7/site-packages/numpy/testing/utils.pyt <module> s|
" o (sb UB]E B2 // / >+ 3
4 +