[SciPy-Dev] ANN: SciPy 0.8.0 beta 1

[josef.pktd at gmail.com]

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 ?

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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