Re: [Numpy-discussion] new numpy.org is live
Hi all, Great job!! Congratulations. In the "Ecosystem" -> "Scientific Domains" section, I think the links for "bayesian inference" and "bio informatics" are wrong. The ones in "bayesian inference" should appear in "bio informatics" and vice versa. Also, in the "geographic processing" area appears Numpy. Kind regards. Sent with [ProtonMail](https://protonmail.com) Secure Email. ‐‐‐ Original Message ‐‐‐ On Monday, 25 de May de 2020 7:46, Abdur-Rahmaan Janhangeer wrote: > More than awesome, now i feel that the logo > is a bit outdated. > > Kind Regards, > > Abdur-Rahmaan Janhangeer > > https://www.github.com/Abdur-RahmaanJ > > Mauritius > > sent from gmail client on Android, that's why the signature is so ugly.___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
Why does numpy produce a runtime warning (invalid value encountered in log) when taking the log of a negative number? I noticed that if you coerce the argument to complex by adding 0j to the negative number, the expected result is produced (i.e. ln(-1) = pi*i). I was surprised I couldn't find a discussion on this, as I would have expected others to have come across this before. Packages like Matlab handle negative numbers automatically by doing the complex conversion. ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
One explanation for this behavior is that doing otherwise would be slow. Consider an array like arr = np.array([1]*10**6 + [-1]) ret = np.log(arr) Today, what happens is: - The output array is allocated as np.double - The input array is iterated over, and log evaluated on each element in turn For what you describe to happen, the behavior would have to be either: - The output array is allocated as np.double - The input array is iterated over, and log evaluated on each element in turn - If any negative element is encountered, allocate a new array as np.cdouble, copy all the data over, then continue. This results in the whole array being promoted. or: - The input array is iterated over, and checked to see if all the values are positive - The output array is allocated as np.double or np.cdouble based on this result - The input array is iterated over, and log evaluated on each element in turn In either case, you’ve converted a 1-pass iteration to a 2-pass one. There are static-typing-based explanations for this behavior too, but I’ll let someone else present one of those. Eric On Mon, 25 May 2020 at 14:33, Brian Racey wrote: > Why does numpy produce a runtime warning (invalid value encountered in > log) when taking the log of a negative number? I noticed that if you coerce > the argument to complex by adding 0j to the negative number, the expected > result is produced (i.e. ln(-1) = pi*i). > > I was surprised I couldn't find a discussion on this, as I would have > expected others to have come across this before. Packages like Matlab > handle negative numbers automatically by doing the complex conversion. > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
Thanks. That is for performance and memory which of course is valid for most use cases. Would it really be much different than doing type/size checking of all the np.array arguments to a function to ensure the appropriate final np.array sizes are allocated? I'm not trying to question current practice, just trying to understand as performance will eventually be important to me. Would a "complex default" mode ever make it into numpy, to behave more like Matlab and other packages with respect to complex number handling? Sure it would make it marginally slower if enabled, but it might open the door to better compatibility when porting code to Python. On Mon, May 25, 2020 at 9:49 AM Eric Wieser wrote: > One explanation for this behavior is that doing otherwise would be slow. > > Consider an array like > > arr = np.array([1]*10**6 + [-1]) > ret = np.log(arr) > > Today, what happens is: > >- The output array is allocated as np.double >- The input array is iterated over, and log evaluated on each element >in turn > > For what you describe to happen, the behavior would have to be either: > >- The output array is allocated as np.double >- > >The input array is iterated over, and log evaluated on each element in >turn >- > >If any negative element is encountered, allocate a new array as >np.cdouble, copy all the data over, then continue. This results in the >whole array being promoted. > > or: > >- The input array is iterated over, and checked to see if all the >values are positive >- > >The output array is allocated as np.double or np.cdouble based on this >result >- > >The input array is iterated over, and log evaluated on each element in >turn > > In either case, you’ve converted a 1-pass iteration to a 2-pass one. > > There are static-typing-based explanations for this behavior too, but I’ll > let someone else present one of those. > > Eric > > On Mon, 25 May 2020 at 14:33, Brian Racey wrote: > >> Why does numpy produce a runtime warning (invalid value encountered in >> log) when taking the log of a negative number? I noticed that if you coerce >> the argument to complex by adding 0j to the negative number, the expected >> result is produced (i.e. ln(-1) = pi*i). >> >> I was surprised I couldn't find a discussion on this, as I would have >> expected others to have come across this before. Packages like Matlab >> handle negative numbers automatically by doing the complex conversion. >> ___ >> NumPy-Discussion mailing list >> NumPy-Discussion@python.org >> https://mail.python.org/mailman/listinfo/numpy-discussion >> > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
Being relatively new to numpy, I'm learning as I go. Your typing suggestion helped me come to the conclusion that I need to type and coerce my input arguments as I'm doing complex math. My test arguments were real, and thus numpy was producing real results. Doing .astype(np.complex128) to my input values that are generally complex resolved my issue. On Mon, May 25, 2020 at 10:09 AM Brian Racey wrote: > Thanks. That is for performance and memory which of course is valid for > most use cases. Would it really be much different than doing type/size > checking of all the np.array arguments to a function to ensure the > appropriate final np.array sizes are allocated? I'm not trying to question > current practice, just trying to understand as performance will eventually > be important to me. > > Would a "complex default" mode ever make it into numpy, to behave more > like Matlab and other packages with respect to complex number handling? > Sure it would make it marginally slower if enabled, but it might open the > door to better compatibility when porting code to Python. > > On Mon, May 25, 2020 at 9:49 AM Eric Wieser > wrote: > >> One explanation for this behavior is that doing otherwise would be slow. >> >> Consider an array like >> >> arr = np.array([1]*10**6 + [-1]) >> ret = np.log(arr) >> >> Today, what happens is: >> >>- The output array is allocated as np.double >>- The input array is iterated over, and log evaluated on each element >>in turn >> >> For what you describe to happen, the behavior would have to be either: >> >>- The output array is allocated as np.double >>- >> >>The input array is iterated over, and log evaluated on each element >>in turn >>- >> >>If any negative element is encountered, allocate a new array as >>np.cdouble, copy all the data over, then continue. This results in >>the whole array being promoted. >> >> or: >> >>- The input array is iterated over, and checked to see if all the >>values are positive >>- >> >>The output array is allocated as np.double or np.cdouble based on >>this result >>- >> >>The input array is iterated over, and log evaluated on each element >>in turn >> >> In either case, you’ve converted a 1-pass iteration to a 2-pass one. >> >> There are static-typing-based explanations for this behavior too, but >> I’ll let someone else present one of those. >> >> Eric >> >> On Mon, 25 May 2020 at 14:33, Brian Racey wrote: >> >>> Why does numpy produce a runtime warning (invalid value encountered in >>> log) when taking the log of a negative number? I noticed that if you coerce >>> the argument to complex by adding 0j to the negative number, the expected >>> result is produced (i.e. ln(-1) = pi*i). >>> >>> I was surprised I couldn't find a discussion on this, as I would have >>> expected others to have come across this before. Packages like Matlab >>> handle negative numbers automatically by doing the complex conversion. >>> ___ >>> NumPy-Discussion mailing list >>> NumPy-Discussion@python.org >>> https://mail.python.org/mailman/listinfo/numpy-discussion >>> >> ___ >> NumPy-Discussion mailing list >> NumPy-Discussion@python.org >> https://mail.python.org/mailman/listinfo/numpy-discussion >> > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
On Mon, 2020-05-25 at 10:09 -0400, Brian Racey wrote: > Thanks. That is for performance and memory which of course is valid > for > most use cases. Would it really be much different than doing > type/size > checking of all the np.array arguments to a function to ensure the > appropriate final np.array sizes are allocated? I'm not trying to > question > current practice, just trying to understand as performance will > eventually > be important to me. > > Would a "complex default" mode ever make it into numpy, to behave > more like > Matlab and other packages with respect to complex number handling? > Sure it > would make it marginally slower if enabled, but it might open the > door to > better compatibility when porting code to Python. > I think the SciPy versions may have such a default, or there is such a functionality hidden somewhere (maybe even the switching behaviour). I am not sure anyone actually uses those, so it may not be a good idea to use them to be honest. The type safety aspects are that you do can get float or complex results randomly, which of course is fine for much code... From my side main argument in favor of the current behaviour is that you, as someone working with complex numbers, likely immediately knows that what you want is to use `np.log(..., dtype=...)` or cast the input to complex. But someone not used to complex numbers may be very surprised if they suddenly have a complex result after a long calculation. That said, there is a problem here, since it is a bit clumsy to force a complex result. `np.log(..., dtype=np.complex128)` works, but hard- codes double precision. `np.log(arr + 0j)` works, but may look strange (I will assume that `log` is so slow that the overhead is not very relevant). I am not sure that if the use case is actually big enough to worry about it, i.e. if you work with complex numbers, you may be fine with just converting to complex once early on... - Sebastian > On Mon, May 25, 2020 at 9:49 AM Eric Wieser < > wieser.eric+nu...@gmail.com> > wrote: > > > One explanation for this behavior is that doing otherwise would be > > slow. > > > > Consider an array like > > > > arr = np.array([1]*10**6 + [-1]) > > ret = np.log(arr) > > > > Today, what happens is: > > > >- The output array is allocated as np.double > >- The input array is iterated over, and log evaluated on each > > element > >in turn > > > > For what you describe to happen, the behavior would have to be > > either: > > > >- The output array is allocated as np.double > >- > > > >The input array is iterated over, and log evaluated on each > > element in > >turn > >- > > > >If any negative element is encountered, allocate a new array as > >np.cdouble, copy all the data over, then continue. This results > > in the > >whole array being promoted. > > > > or: > > > >- The input array is iterated over, and checked to see if all > > the > >values are positive > >- > > > >The output array is allocated as np.double or np.cdouble based > > on this > >result > >- > > > >The input array is iterated over, and log evaluated on each > > element in > >turn > > > > In either case, you’ve converted a 1-pass iteration to a 2-pass > > one. > > > > There are static-typing-based explanations for this behavior too, > > but I’ll > > let someone else present one of those. > > > > Eric > > > > On Mon, 25 May 2020 at 14:33, Brian Racey > > wrote: > > > > > Why does numpy produce a runtime warning (invalid value > > > encountered in > > > log) when taking the log of a negative number? I noticed that if > > > you coerce > > > the argument to complex by adding 0j to the negative number, the > > > expected > > > result is produced (i.e. ln(-1) = pi*i). > > > > > > I was surprised I couldn't find a discussion on this, as I would > > > have > > > expected others to have come across this before. Packages like > > > Matlab > > > handle negative numbers automatically by doing the complex > > > conversion. > > > ___ > > > NumPy-Discussion mailing list > > > NumPy-Discussion@python.org > > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > > ___ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] new numpy.org is live
On Sun, May 24, 2020 at 8:19 PM Stephen Waterbury wrote: > This is an absolutely beautiful and very informative site! > It is clear all the work and thought that went into it. > > So please take the following input as a constructive suggestion > from an outsider -- I am a long-time (30-year) Python user, and > I follow this list but do not regularly use NumPy ... so again, > an "outsider" perspective: > > I would prefer to see the beautiful "ECOSYSTEM" section as the > top section of the page, since it is kind of a "gateway" to all > kinds of cool links, etc. -- and it is visually very interesting, as well. > > The "features" boxes at the top of the page, while very good > information, are not nearly as "useful" and they are static, > so I would even suggest providing access to them via a > "Features" menu item among the very top items > (i.e., with "Installation", etc.). > > Very humbly offered, with thanks for all the beautiful work. > Thanks for the feedback Steve. I have added your suggestion to https://github.com/numpy/numpy.org/issues/238. Our strategy for the next while will be: 1. fix any bugs and correctness issues in content (done for everything already reported in this thread so far and on Twitter). 2. review remaining open PRs 3. prioritize from the large set of new ideas and already planned improvements. Tracking issue at https://github.com/numpy/numpy.org/issues/266 Cheers, Ralf Steve > > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
Would a "complex default" mode ever make it into numpy, to behave more like Matlab and other packages with respect to complex number handling? Sure it would make it marginally slower if enabled, but it might open the door to better compatibility when porting code to Python. numpy already has the "complex default" log function: numpy.lib.scimath.log . There are other useful gems in that module, for example a "complex default" sqrt function Ciao, Tiziano ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
On Mon, May 25, 2020 at 10:36 AM Sebastian Berg wrote: > On Mon, 2020-05-25 at 10:09 -0400, Brian Racey wrote: > > Would a "complex default" mode ever make it into numpy, to behave > > more like > > Matlab and other packages with respect to complex number handling? > > Sure it > > would make it marginally slower if enabled, but it might open the > > door to > > better compatibility when porting code to Python. > > > > I think the SciPy versions may have such a default, or there is such a > functionality hidden somewhere (maybe even the switching behaviour). > I am not sure anyone actually uses those, so it may not be a good idea > to use them to be honest. > The versions in `np.lib.scimath` behave like this. Of course, people do use them when they want to deal with real numbers as subsets of the complex numbers. -- Robert Kern ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
On Mon, 2020-05-25 at 11:10 -0400, Robert Kern wrote: > On Mon, May 25, 2020 at 10:36 AM Sebastian Berg < > sebast...@sipsolutions.net> > wrote: > > > On Mon, 2020-05-25 at 10:09 -0400, Brian Racey wrote: > > > Would a "complex default" mode ever make it into numpy, to behave > > > more like > > > Matlab and other packages with respect to complex number > > > handling? > > > Sure it > > > would make it marginally slower if enabled, but it might open the > > > door to > > > better compatibility when porting code to Python. > > > > > > > I think the SciPy versions may have such a default, or there is > > such a > > functionality hidden somewhere (maybe even the switching > > behaviour). > > I am not sure anyone actually uses those, so it may not be a good > > idea > > to use them to be honest. > > > > The versions in `np.lib.scimath` behave like this. Of course, people > do use > them when they want to deal with real numbers as subsets of the > complex > numbers. > True, I guess I just used complex numbers too rarely in programs (i.e. never central to any programming project). It seems this is actually also exposed as `np.emath`, which is maybe a better entry point? And I guess the scipy namespace uses them. - Sebastian > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
My Googling revealed none of this. I don't have anyone to talk to about using numpy, so Google (and this group) is all I have. This was extremely useful: https://numpy.org/devdocs/user/numpy-for-matlab-users.html so perhaps it could be extended to point out those modules and entry points if it isn't documented elsewhere. On Mon, May 25, 2020 at 11:17 AM Sebastian Berg wrote: > On Mon, 2020-05-25 at 11:10 -0400, Robert Kern wrote: > > On Mon, May 25, 2020 at 10:36 AM Sebastian Berg < > > sebast...@sipsolutions.net> > > wrote: > > > > > On Mon, 2020-05-25 at 10:09 -0400, Brian Racey wrote: > > > > Would a "complex default" mode ever make it into numpy, to behave > > > > more like > > > > Matlab and other packages with respect to complex number > > > > handling? > > > > Sure it > > > > would make it marginally slower if enabled, but it might open the > > > > door to > > > > better compatibility when porting code to Python. > > > > > > > > > > I think the SciPy versions may have such a default, or there is > > > such a > > > functionality hidden somewhere (maybe even the switching > > > behaviour). > > > I am not sure anyone actually uses those, so it may not be a good > > > idea > > > to use them to be honest. > > > > > > > The versions in `np.lib.scimath` behave like this. Of course, people > > do use > > them when they want to deal with real numbers as subsets of the > > complex > > numbers. > > > > True, I guess I just used complex numbers too rarely in programs (i.e. > never central to any programming project). > > It seems this is actually also exposed as `np.emath`, which is maybe a > better entry point? And I guess the scipy namespace uses them. > > - Sebastian > > > ___ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
I wasted a good 2 weeks because of that behavior of Matlab back in the day and I think that is one of the cardinal sins that matlab commits. If need be there are alternatives as mentioned before but I definitely do not prefer this coercion at all. On Mon, May 25, 2020 at 5:18 PM Sebastian Berg wrote: > On Mon, 2020-05-25 at 11:10 -0400, Robert Kern wrote: > > On Mon, May 25, 2020 at 10:36 AM Sebastian Berg < > > sebast...@sipsolutions.net> > > wrote: > > > > > On Mon, 2020-05-25 at 10:09 -0400, Brian Racey wrote: > > > > Would a "complex default" mode ever make it into numpy, to behave > > > > more like > > > > Matlab and other packages with respect to complex number > > > > handling? > > > > Sure it > > > > would make it marginally slower if enabled, but it might open the > > > > door to > > > > better compatibility when porting code to Python. > > > > > > > > > > I think the SciPy versions may have such a default, or there is > > > such a > > > functionality hidden somewhere (maybe even the switching > > > behaviour). > > > I am not sure anyone actually uses those, so it may not be a good > > > idea > > > to use them to be honest. > > > > > > > The versions in `np.lib.scimath` behave like this. Of course, people > > do use > > them when they want to deal with real numbers as subsets of the > > complex > > numbers. > > > > True, I guess I just used complex numbers too rarely in programs (i.e. > never central to any programming project). > > It seems this is actually also exposed as `np.emath`, which is maybe a > better entry point? And I guess the scipy namespace uses them. > > - Sebastian > > > ___ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] log of negative real numbers -> RuntimeWarning: invalid value encountered in log
On Mon, May 25, 2020 at 11:17 AM Sebastian Berg wrote: > On Mon, 2020-05-25 at 11:10 -0400, Robert Kern wrote: > > On Mon, May 25, 2020 at 10:36 AM Sebastian Berg < > > sebast...@sipsolutions.net> > > wrote: > > > > > On Mon, 2020-05-25 at 10:09 -0400, Brian Racey wrote: > > > > Would a "complex default" mode ever make it into numpy, to behave > > > > more like > > > > Matlab and other packages with respect to complex number > > > > handling? > > > > Sure it > > > > would make it marginally slower if enabled, but it might open the > > > > door to > > > > better compatibility when porting code to Python. > > > > > > > > > > I think the SciPy versions may have such a default, or there is > > > such a > > > functionality hidden somewhere (maybe even the switching > > > behaviour). > > > I am not sure anyone actually uses those, so it may not be a good > > > idea > > > to use them to be honest. > > > > > > > The versions in `np.lib.scimath` behave like this. Of course, people > > do use > > them when they want to deal with real numbers as subsets of the > > complex > > numbers. > > > > True, I guess I just used complex numbers too rarely in programs (i.e. > never central to any programming project). > > It seems this is actually also exposed as `np.emath`, which is maybe a > better entry point? And I guess the scipy namespace uses them. > Ah, yes, that's the preferred alias, though the documentation page for it seems to be a little buggy (using `np.lib.scimath` instead `np.emath`; telling you to look at the docstrings for the individual functions, but they don't exist in the documentation). -- Robert Kern ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] new numpy.org is live
This is so excellent! What a wonderful upgrade to the web-page. Thank you for all the hard work and effort! -Travis On Sun, May 24, 2020 at 7:12 AM Inessa Pawson wrote: > The NumPy web team is excited to announce the launch of the newly > redesigned numpy.org. To transform the website into a comprehensive, yet > user-centric, resource of all things NumPy was a primary focus of this > months-long effort. We thank Joe LaChance, Ralf Gommers, Shaloo Shalini, > Shekhar Prasad Rajak, Ross Barnowski, and Mars Lee for their extensive > contributions to the project. > > The new site features a curated collection of NumPy related educational > resources for every user level, an overview of the entire Python scientific > computing ecosystem, and several case studies highlighting the importance > of the library to the many advances in scientific research as well as the > industry in recent years. The “Install” and “Get Help” pages offer advice > on how to find answers to installation and usage questions, while those who > are looking to connect with others within our large and diverse community > will find the “Community” page very helpful. > > The new website will be updated on a regular basis with news about the > NumPy project development milestones, community initiatives and events. > Visitors are encouraged to explore the website and sign up for the > newsletter. > > Next, the NumPy web team will focus on updating graphics and project > identity (a new logo is coming!), adding an installation widget and > translations, better integrating the project documentation via the new > Sphinx theme, and improving the interactive terminal experience. Also, we > are looking to expand our portfolio of case studies and would appreciate > any assistance in this matter. > > Best regards, > Inessa Pawson > NumPy web team > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
