[SciPy-Dev] ANN: SciPy 0.8.0 beta 1

Vincent Davis vincent at vincentdavis.net
Sat Jun 12 15:50:00 EDT 2010 

On Sat, Jun 12, 2010 at 1:47 PM,  <josef.pktd at gmail.com> wrote:
> On Sat, Jun 12, 2010 at 3:41 PM, Vincent Davis <vincent at vincentdavis.net> wrote:
>> On Sat, Jun 12, 2010 at 1:37 PM,  <josef.pktd at gmail.com> wrote:
>>> On Sat, Jun 12, 2010 at 3:28 PM, Vincent Davis <vincent at vincentdavis.net> wrote:
>>>> On Sat, Jun 12, 2010 at 1:22 PM,  <josef.pktd at gmail.com> wrote:
>>>>> On Sat, Jun 12, 2010 at 3:02 PM, Vincent Davis <vincent at vincentdavis.net> wrote:
>>>>>> On Fri, Jun 11, 2010 at 6:41 PM,  <josef.pktd at gmail.com> wrote:
>>>>>>> On Fri, Jun 11, 2010 at 7:54 PM, Derek Homeier
>>>>>>> <derek at astro.physik.uni-goettingen.de> wrote:
>>>>>>>> Hi Josef,
>>>>>>>>
>>>>>>>>>> FAIL: test_stats.test_kstest
>>>>>>>>>> ----------------------------------------------------------------------
>>>>>>>>>> Traceback (most recent call last):
>>>>>>>>>>  File "/sw/lib/python2.6/site-packages/nose/case.py", line 186, in runTest
>>>>>>>>>>    self.test(*self.arg)
>>>>>>>>>>  File "/sw/lib/python2.6/site-packages/scipy/stats/tests/test_stats.py", line 1078, in test_kstest
>>>>>>>>>>    np.array((0.0072115233216310994, 0.98531158590396228)), 14)
>>>>>>>>>>  File "/sw/lib/python2.6/site-packages/numpy/testing/utils.py", line 441, in assert_almost_equal
>>>>>>>>>>    return assert_array_almost_equal(actual, desired, decimal, err_msg)
>>>>>>>>>>  File "/sw/lib/python2.6/site-packages/numpy/testing/utils.py", line 765, in assert_array_almost_equal
>>>>>>>>>>    header='Arrays are not almost equal')
>>>>>>>>>>  File "/sw/lib/python2.6/site-packages/numpy/testing/utils.py", line 609, in assert_array_compare
>>>>>>>>>>    raise AssertionError(msg)
>>>>>>>>>> AssertionError:
>>>>>>>>>> Arrays are not almost equal
>>>>>>>>>>
>>>>>>>>>> (mismatch 100.0%)
>>>>>>>>>>  x: array([ 0.007,  0.985])
>>>>>>>>>>  y: array([ 0.007,  0.985])
>>>>>>>>>
>>>>>>>>> maybe the precision (decimal 14) is too high for this test across platforms
>>>>>>>>>
>>>>>>>>> Could you check how large the difference is ?
>>>>>>>>>
>>>>>>>>> np.random.seed(987654321)
>>>>>>>>> x = stats.norm.rvs(loc=0.2, size=100)
>>>>>>>>> np.array(stats.kstest(x,'norm', alternative = 'greater')) -
>>>>>>>>>                np.array((0.0072115233216310994, 0.98531158590396228))
>>>>>>>>>
>>>>>>>>> (my line numbers differ, but this should be the right test given your numbers)
>>>>>>>>
>>>>>>>>
>>>>>>>> yes, just a decimal or two too high, if I got the numbers right:
>>>>>>>> # OS X 10.5 i386 / 10.6 x86_64:
>>>>>>>> array([  8.67361738e-18,   1.66533454e-15])
>>>>>>>>
>>>>>>>> # OS X 10.5 ppc:
>>>>>>>> array([  2.05955045e-13,  -7.16759985e-13])
>>>>>>>
>>>>>>> interesting that there are differences in the calculations, but for
>>>>>>> the test we can just reduce the precision to decimal=12 to avoid the
>>>>>>> test failure.
>>>>>>
>>>>>> I must be doing something wrong here becuase I don't get anything
>>>>>> close that what you have above.
>>>>
>>>>>> In [4]: np.random.seed(987654321)
>>>>>>
>>>>>> In [5]: x = stats.norm.rvs(loc=0.2, size=100)
>>>>>>
>>>>>> In [6]: r1 = np.array(stats.kstest(x,'norm', alternative = 'greater'))
>>>>>>
>>>>>> In [7]: r2 = np.array((0.0072115233216310994, 0.98531158590396228))
>>>>>>
>>>>>> In [8]: r1-r2
>>>>>> Out[8]: array([ 0.03704986, -0.32866092])
>>>>>
>>>>>>>> np.random.seed(987654321)
>>>>>>>> xrvs = stats.norm.rvs(loc=0.2, size=100)
>>>>>>>> r1 = np.array(stats.kstest(xrvs,'norm', alternative = 'greater'))
>>>>>>>> r2 = np.array((0.0072115233216310994, 0.98531158590396228))
>>>>>>>> r1-r2
>>>>> array([  8.67361738e-18,   1.66533454e-15])
>>>>>
>>>>> Can you check mean and var to see if you have the same random  numbers?
>>>>>
>>>>>>>> xrvs.mean()
>>>>> 0.20830662128271851
>>>>>>>> xrvs.var()
>>>>> 1.1210385272356511
>>>>
>>>> In [11]: x.mean()
>>>> Out[11]: 0.054996065027031464
>>>>
>>>> In [12]: x.var()
>>>> Out[12]: 0.92731406990162746
>>>
>>> looks like you have different random numbers
>>>
>>>>
>>>> I am cheating and using the enthought distribution, I just click install.
>>>> How do I run all of the tests for scipy or numpy when they are already
>>>> installed?
>>>
>>> scipy.stats.test()
>>> .test() works for scipy and every subpackage
>>>
>>> is ipython messing with the RandomState ?
>>
>> In [19]: np.random.seed(987654321)
>>
>> In [20]: np.random.rand(3)
>> Out[20]: array([ 0.07298833,  0.2160365 ,  0.46475349])
>>
>> In [21]: np.random.rand(3)
>> Out[21]: array([ 0.62258994,  0.61838812,  0.42737911])
>
> same here
>
>>>> np.random.seed(987654321)
>>>> np.random.rand(3)
> array([ 0.07298833,  0.2160365 ,  0.46475349])
>>>> np.random.rand(3)
> array([ 0.62258994,  0.61838812,  0.42737911])
>
> ??

Gets better, I just ran the test, I need to look above to see how this relates.

FAIL: test_stats.test_kstest
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Library/Frameworks/EPD64.framework/Versions/6.2/lib/python2.6/site-packages/nose/case.py",
line 186, in runTest
    self.test(*self.arg)
  File "/Library/Frameworks/EPD64.framework/Versions/6.2/lib/python2.6/site-packages/scipy/stats/tests/test_stats.py",
line 1228, in test_kstest
    assert_almost_equal( D, 0.12464329735846891, 15)
  File "/Library/Frameworks/EPD64.framework/Versions/6.2/lib/python2.6/site-packages/numpy/testing/utils.py",
line 459, in assert_almost_equal
    raise AssertionError(msg)
AssertionError:
Arrays are not almost equal
 ACTUAL: 0.093893737596468518
 DESIRED: 0.12464329735846891

Vincent

>
> Josef
>>
>> In [22]: np.random.seed(987654321)
>>
>> In [23]: np.random.rand(3)
>> Out[23]: array([ 0.07298833,  0.2160365 ,  0.46475349])
>>
>> Vincent
>>
>>>
>>> Josef
>>>
>>>>
>>>> Vincent
>>>>
>>>>>
>>>>> otherwise I have no clue, (but I guess your scipy.stats tests pass)
>>>>>
>>>>> Josef
>>>>>
>>>>>
>>>>>>
>>>>>> Vincent
>>>>>>
>>>>>>
>>>>>>>
>>>>>>> Thanks,
>>>>>>> Josef
>>>>>>>
>>>>>>>>
>>>>>>>> Cheers,
>>>>>>>>                                                Derek
>>>>>>>>
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