[Mne_analysis] test_filter.py value mismatch error
Alexandre Gramfort
alexandre.gramfort at inria.fr
Thu Sep 28 15:13:04 EDT 2017
Dear Kyuhwa,
this is really strange. All continuous integration systems we use
don't report this issue.
DId you try with latest master ?
Alex
On Wed, Sep 27, 2017 at 7:30 PM, Lee, KyuHwa <lee.kyuh at gmail.com> wrote:
> Hi Alex, here's the result:
>
> Platform: Windows-10-10.0.15063-SP0
> Python: 3.6.1 |Anaconda custom (64-bit)| (default, May 11 2017,
> 13:25:24) [MSC v.1900 64 bit (AMD64)]
> Executable: C:\Anaconda3\python.exe
> CPU: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel: 4 cores
> Memory: 7.9 GB
>
> mne: 0.15.dev0
> numpy: 1.13.1 {blas=mkl_core_dll, lapack=mkl_core_dll}
> scipy: 0.19.1
> matplotlib: 2.0.2
>
> sklearn: 0.19.0
> nibabel: Not found
> mayavi: Not found
> pycuda: 2017.1.1
> skcuda: 0.5.1
> pandas: 0.20.3
>
> Best,
> Kyuhwa
>
> On Sun, Sep 24, 2017 at 1:38 PM, Alexandre Gramfort <
> alexandre.gramfort at inria.fr> wrote:
>
>> hi Kyuhwa,
>>
>> can you tell me what this gives for you
>>
>> import mne
>> mne.sys_info()
>>
>> Alex
>>
>>
>> On Sat, Sep 23, 2017 at 7:22 PM, Lee, KyuHwa <lee.kyuh at gmail.com> wrote:
>>
>>> Hello,
>>>
>>> I installed MNE 0.15-dev from git with CUDA 8.0 and Anaconda 4.4 (Python
>>> 3.6), following this manual:
>>> http://martinos.org/mne/dev/advanced_setup.html?highlight=dev%20install
>>>
>>> When I run:
>>> mne.utils.set_config('MNE_USE_CUDA', 'true'); mne.cuda.init_cuda()
>>> I get the correct result:
>>> Enabling CUDA with 761.0 MB available memory
>>>
>>> When I run test_filter.py, I get the following error:
>>>
>>> AssertionError:
>>> Not equal to tolerance rtol=0.001, atol=0.001
>>>
>>> (mismatch 0.9333333333333371%)
>>> x: array([[ -2.558717e-16, -1.525432e-01, -2.835838e-01, ...,
>>> 4.634404e-01, 2.543413e-01, -6.938894e-17],
>>> [ -2.532696e-16, 1.745948e-01, 3.111300e-01, ...,
>>> 6.255135e-01, 3.478937e-01, -2.775558e-17]])
>>> y: array([[ 8.933826e-17, -1.527561e-01, -2.836241e-01, ...,
>>> 4.634049e-01, 2.543312e-01, -2.428613e-16],
>>> [ 1.565588e-16, 1.746173e-01, 3.108850e-01, ...,
>>> 6.256731e-01, 3.481433e-01, -3.053113e-16]])
>>>
>>> It was caused by line 332 of test_filter.py:
>>> assert_allclose(hp, bp, rtol=1e-3, atol=1e-3)
>>>
>>> I tried increasing the tolerence to 1e-2, and now it throws another
>>> error caused by line 336 (FFT calculation):
>>> AssertionError:
>>> Not equal to tolerance rtol=1e-07, atol=0.02
>>>
>>> (mismatch 100.0%)
>>> x: array(1.0259702184926076)
>>> y: array(1.0)
>>>
>>> Seems like there's a serious numerical problem with the computation.
>>> What should I do in this case?
>>> Weird thing is, even if I set MNE_USE_CUDA to 'false', it still gives me
>>> exactly the same error, which might suggest it's independent of CUDA
>>> setting?
>>>
>>> Best wishes,
>>> Kyuhwa
>>>
>>>
>>>
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