Re: [Numpy-discussion] how to count Nan occurrence in a ndarray?
Thanks Olivier. Chao 2011/10/7 Olivier Delalleau > You can use numpy.isnan(array).sum() > > -=- Olivier > > 2011/10/7 Chao YUE > >> The data is read from a .mat file. >> >> 2011/10/7 Chao YUE >> >>> Dear all, >>> >>> I have an ndarray with dimension of 4X62500. is there anyway I can count >>> the number of missing value (NaN)? because I want to know how many >>> observations are missing? >>> >>> Thanks for any idea, >>> >>> Chao >>> >>> -- >>> >>> *** >>> Chao YUE >>> Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) >>> UMR 1572 CEA-CNRS-UVSQ >>> Batiment 712 - Pe 119 >>> 91191 GIF Sur YVETTE Cedex >>> Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 >>> >>> >>> >>> >> >> >> -- >> >> *** >> Chao YUE >> Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) >> UMR 1572 CEA-CNRS-UVSQ >> Batiment 712 - Pe 119 >> 91191 GIF Sur YVETTE Cedex >> Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 >> >> >> >> >> ___ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > -- *** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] how to count Nan occurrence in a ndarray?
You can use numpy.isnan(array).sum() -=- Olivier 2011/10/7 Chao YUE > The data is read from a .mat file. > > 2011/10/7 Chao YUE > >> Dear all, >> >> I have an ndarray with dimension of 4X62500. is there anyway I can count >> the number of missing value (NaN)? because I want to know how many >> observations are missing? >> >> Thanks for any idea, >> >> Chao >> >> -- >> >> *** >> Chao YUE >> Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) >> UMR 1572 CEA-CNRS-UVSQ >> Batiment 712 - Pe 119 >> 91191 GIF Sur YVETTE Cedex >> Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 >> >> >> >> > > > -- > > *** > Chao YUE > Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) > UMR 1572 CEA-CNRS-UVSQ > Batiment 712 - Pe 119 > 91191 GIF Sur YVETTE Cedex > Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 > > > > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] how to count Nan occurrence in a ndarray?
The data is read from a .mat file. 2011/10/7 Chao YUE > Dear all, > > I have an ndarray with dimension of 4X62500. is there anyway I can count > the number of missing value (NaN)? because I want to know how many > observations are missing? > > Thanks for any idea, > > Chao > > -- > > *** > Chao YUE > Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) > UMR 1572 CEA-CNRS-UVSQ > Batiment 712 - Pe 119 > 91191 GIF Sur YVETTE Cedex > Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 > > > > -- *** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] how to count Nan occurrence in a ndarray?
Dear all, I have an ndarray with dimension of 4X62500. is there anyway I can count the number of missing value (NaN)? because I want to know how many observations are missing? Thanks for any idea, Chao -- *** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Crash on (un-orthodox) __import__
On 10/6/2011 9:33 PM, Robert Kern wrote:
> On Thu, Oct 6, 2011 at 17:25, Paul Ivanov wrote:
>> Hi Andrea,
>>
>> On Tue, Oct 4, 2011 at 3:04 AM, Andrea Gavana
>> wrote:
>>> Hi All,
>>> I was fiddling here and there with some code doing dynamic import of
>>> stuff, and I noticed that this code:
>>> import os
>>> import sys
>>> init_name = r"C:\Python27\Lib\site-packages\numpy\__init__.py"
>>> directory, module_name = os.path.split(init_name)
>>> main = os.path.splitext(module_name)[0]
>>> sys.path.insert(0, os.path.normpath(directory))
>>> # Crash here...
>>> mainmod = __import__(main)
>>
>>
>> in this case, your main is '__init__' and your directory is
>> 'C:\Python27\Lib\site-packages\numpy' which is probably not what you
>> intended. You should make directory 'C:\Python27\Lib\site-packages'
>> and main into 'numpy'
>
> Still, it shouldn't segfault, and it's worth figuring out why it does.
> gdb has been mostly unenlightening for me since gdb won't let me
> navigate the traceback.
>
This is the same crash that occurs when running `python -v -c"import
__init__"` from within the site-packages/numpy directory. Several numpy
Python and C extension modules are imported/executed twice. Besides
fixing the segfault it might be worth preventing this type of import in
numpy/__init__.py, for example:
import sys as _sys
if '__init__' in _sys.modules and _sys.modules['__init__'].__file__ ==
__file__:
_sys.stderr.write("Use `import numpy` ... .\n") # or raise
ImportError()
else:
...
del _sys
The faulthandler output is:
File "core\numerictypes.py", line 226 in _evalname
File "core\numerictypes.py", line 247 in bitname
File "core\numerictypes.py", line 307 in _add_aliases
File "core\numerictypes.py", line 330 in
File "core\__init__.py", line 8 in
File "__init__.py", line 146 in
File "", line 1 in
The function call that crashes during the second import of
core/numerictypes.py is `int("64")`.
Christoph
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