Re: [Numpy-discussion] mail.scipy.org update
If all the SSL certification updates have been done properly, this message should go through. -- Didrik On 14 September 2016 at 13:00, Didrik Pinte wrote: > Hi everyone, > > While updating the scipy SSL certificates yesterday, it appeared that > filesystem of the servers is corrupted (more than likely a hardware > failure). The problem is restricted to one volume and impacts only the web > services. The mailing list/mailman service works as expected. > > We're working on restoring all the different non-functional services. > > Thanks for you patience! > > -- Didrik > -- Didrik Pinte +32 475 665 668 +44 1223 969515 Enthought Inc.dpi...@enthought.com Scientific Computing Solutions http://www.enthought.com The information contained in this message is Enthought confidential & not to be dissiminated to outside parties without explicit prior approval from sender. This message is intended solely for the addressee(s), If you are not the intended recipient, please contact the sender by return e-mail and destroy all copies of the original message. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] guvectorize, a helper for writing generalized ufuncs
I have put a pull request implementing numpy.guvectorize up for review: https://github.com/numpy/numpy/pull/8054 Cheers, Stephan On Tue, Sep 13, 2016 at 10:54 PM, Travis Oliphant wrote: > There has been some discussion on the Numba mailing list as well about a > version of guvectorize that doesn't compile for testing and flexibility. > > Having this be inside NumPy itself seems ideal. > > -Travis > > > On Tue, Sep 13, 2016 at 12:59 PM, Stephan Hoyer wrote: > >> On Tue, Sep 13, 2016 at 10:39 AM, Nathan Goldbaum >> wrote: >> >>> I'm curious whether you have a plan to deal with the python functional >>> call overhead. Numba gets around this by JIT-compiling python functions - >>> is there something analogous you can do in NumPy or will this always be >>> limited by the overhead of repeatedly calling a Python implementation of >>> the "core" operation? >>> >> >> I don't think there is any way to avoid this in NumPy proper, but that's >> OK (it's similar to the existing overhead of vectorize). >> >> Numba already has guvectorize (and it's own version of vectorize as >> well), which already does exactly this. >> >> ___ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> https://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > > -- > > *Travis Oliphant, PhD* > *Co-founder and CEO* > > > @teoliphant > 512-222-5440 > http://www.continuum.io > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] mail.scipy.org update
On Mon, Sep 26, 2016 at 10:20 PM, Didrik Pinte wrote: > If all the SSL certification updates have been done properly, this message > should go through. > It did, thanks Didrik! Ralf > > -- Didrik > > On 14 September 2016 at 13:00, Didrik Pinte wrote: > >> Hi everyone, >> >> While updating the scipy SSL certificates yesterday, it appeared that >> filesystem of the servers is corrupted (more than likely a hardware >> failure). The problem is restricted to one volume and impacts only the web >> services. The mailing list/mailman service works as expected. >> >> We're working on restoring all the different non-functional services. >> >> Thanks for you patience! >> >> -- Didrik >> > > > > -- > Didrik Pinte +32 475 665 668 >+44 1223 969515 > Enthought Inc.dpi...@enthought.com > Scientific Computing Solutions http://www.enthought.com > > The information contained in this message is Enthought confidential & not > to be dissiminated to outside parties without explicit prior approval from > sender. This message is intended solely for the addressee(s), If you are > not the intended recipient, please contact the sender by return e-mail and > destroy all copies of the original message. > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] testing
Testing if this gets posted... Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] [7949] How to handle these deprecation Warning errors
Hi I am working on issue #7949, and need to use "-3" switch while running python 2.7 for my tests. python -3 -c "import numpy as np; np.test()" Several errors are reported and all all of them are DeprecationWarnings, which is ok. (https://travis-ci.org/njase/numpy/jobs/162733502) *But now these errors must be either fixed or skipped. This is where I am facing problem. Pls suggest:* 1. *Identify that python was invoked with -3 and skip these cases*: There seems no way to know if python was invoked with -3 sys.argv only reports about "-c" and ignores other switches 2. *Fix these issues:* All of them are about deprecated APIs and new APIs have been introduced in python 3. Since I am using python 2.x, I don't see a way to fix them What to do? Regards Saurabh ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [7949] How to handle these deprecation Warning errors
On Mo, 2016-09-26 at 15:36 +0200, Saurabh Mehta wrote: > Hi > > I am working on issue #7949, and need to use "-3" switch while > running python 2.7 for my tests. > python -3 -c "import numpy as np; np.test()" > > Several errors are reported and all all of them are > DeprecationWarnings, which is ok. (https://travis-ci.org/njase/numpy/ > jobs/162733502) > OK, most of them seem harmless (i.e. don't use the slice C-slot). I think we should just get rid of the slice C-slot thing globally, the simplest way would be to go to numpy/testing/nosetester.py, look for things like `sup.filter(message='Not importing directory')`. Then, maybe specific `if sys.version_info.major == 2 and sys.py3kwarning`, just add some `sup.filter` such as: ``` if sys.version_info.major == 2 and sys.py3kwarning: sup.filter(DeprecationWarning, message="in 3.x, __setslice__") sup.filter(DeprecationWarning, message="in 3.x, __getslice__") ``` First scrolling through the errors, my guess is that the other errors we can also silence more locally. This silencing might also leek to scipy, but frankly I am not worried about it for those slots. The threading warnings seem also quite noisy (and useless), but not sure right away what the best approach for that would be. - Sebastian > But now these errors must be either fixed or skipped. This is where I > am facing problem. Pls suggest: > > 1. Identify that python was invoked with -3 and skip these cases: > There seems no way to know if python was invoked with -3 > sys.argv only reports about "-c" and ignores other switches > > > 2. Fix these issues: All of them are about deprecated APIs and new > APIs have been introduced in python 3. Since I am using python 2.x, I > don't see a way to fix them > > What to do? > > Regards > Saurabh > > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion signature.asc Description: This is a digitally signed message part ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Parsing a file with dates to datetim64
Hey,
I have a file:
;Eintrittsdatum;;;
;04.03.16;;10,00 €;genehmigt
;04.03.16;;10,00 €;genehmigt
which I try to parse using
def dateToNumpyDate(s):
s = s.decode("utf-8")
ret = datetime.datetime.strptime(s, "%d.%m.%y").isoformat()
return ret
def generateMembers():
members = np.genfromtxt("test_CSC_Mitglieder.csv",
dtype = { "names" : ["EntryDate"],
"formats" : ['datetime64[D]'] },
converters = { 9 : dateToNumpyDate },
skip_header = 1,
delimiter = ";",
usecols = (9))
count = members.shape[0]
y = np.linspace(1, count, count)
print(members)
print(members.dtype)
plt.plot(members["EntryDate"], y)
plt.show()
but the datatype was ignored homehow,
generateMembers()
File "CSC.py", line 76, in generateMembers
plt.plot(members["EntryDate"], y)
IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis
(`None`) and integer or boolean arrays are
valid indices
I also tried to print the return of dateToNumpbyData:
2016-03-04T00:00:00
2016-03-04T00:00:00
2016-03-04T00:00:00
Is there a problem with the dtype argument?
Thanks,
Florian
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[Numpy-discussion] PR 8053 np.random.multinomial tolerance param
Hello, Pull Request: https://github.com/numpy/numpy/pull/8053 I would like to expose a tolerance parameter for the function numpy.random.multinomial. The function `multinomial(n, pvals, size=None)` correctly raises exception when `sum(pvals) > 1 + 1e-12` as these values should sum to 1. However, other libraries often cannot or do not guarantee such level of precision. Specifically, I have encountered issues with tensorflow function tf.nn.softmax, which is expected to output a tensor whose values sum to 1, but often with precision of only 1e-8. I propose to expose the `1e-12` tolerance to a non-negative float parameter with default value `1e-12`. Alex ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] PR 8053 np.random.multinomial tolerance param
I would actually be just as happy to relax the tolerance here to 1e-8 always. I doubt this would catch any fewer bugs than the current default. In contrast, adding new parameters adds cognitive overload for everyone encountering the function. Also, for your use case note that tensorflow has it's own function for generating random values from a multinomial distribution: https://www.tensorflow.org/versions/r0.10/api_docs/python/constant_op.html#multinomial On Mon, Sep 26, 2016 at 11:52 AM, Alex Beloi wrote: > Hello, > > > > Pull Request: https://github.com/numpy/numpy/pull/8053 > > > > I would like to expose a tolerance parameter for the function > numpy.random.multinomial. > > > > The function `multinomial(n, pvals, size=None)` correctly raises exception > when `sum(pvals) > 1 + 1e-12` as these values should sum to 1. However, > other libraries often cannot or do not guarantee such level of precision. > > > > Specifically, I have encountered issues with tensorflow function > tf.nn.softmax, which is expected to output a tensor whose values sum to 1, > but often with precision of only 1e-8. > > > > I propose to expose the `1e-12` tolerance to a non-negative float > parameter with default value `1e-12`. > > > > Alex > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
