Mailman 3 April 2019 - NumPy-Discussion

mixed mode arithmetic
by Neal Becker July 11, 2023

July 11, 2023

I've been browsing the numpy source. I'm wondering about mixed-mode arithmetic on arrays. I believe the way numpy handles this is that it never does mixed arithmetic, but instead converts arrays to a common type. Arguably, that might be efficient for a mix of say, double and float. Maybe not. But for a mix of complex and a scalar type (say, CDouble * Double), it's clearly suboptimal in efficiency. So, do I understand this correctly? If so, is that something we should improve?

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Invalid value encoutered : how to prevent numpy.where to do this?
by Eric Emsellem Feb. 18, 2023

Feb. 18, 2023

Dear all, I have a code using lots of "numpy.where" to make some constrained calculations as in: data = arange(10) result = np.where(data == 0, 0., 1./data) # or data1 = arange(10) data2 = arange(10)+1.0 result = np.where(data1 > data2, np.sqrt(data1-data2), np.sqrt(data2-data2)) which then produces warnings like: /usr/bin/ipython:1: RuntimeWarning: invalid value encountered in sqrt or for the first example: /usr/bin/ipython:1: RuntimeWarning: divide by zero encountered in divide How … [View More]

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Re: [Numpy-discussion] example reading binary Fortran file
by Neil Martinsen-Burrell July 22, 2021

July 22, 2021

David Froger <david.froger.info <at> gmail.com> writes: > Hy,My question is about reading Fortran binary file (oh no this question > again...) I've posted this before, but I finally got it cleaned up for the Cookbook. For this purpose I use a subclass of file that has methods for reading unformatted Fortran data. See http://www.scipy.org/Cookbook/FortranIO/FortranFile. I'd gladly see this in numpy or scipy somewhere, but I'm not sure where it belongs. > program … [View More]makeArray > implicit none > integer,parameter:: nx=10,ny=20 > real(4),dimension(nx,ny):: ux,uy,p > integer :: i,j > open(11,file='uxuyp.bin',form='unformatted') > do i = 1,nx > do j = 1,ny > ux(i,j) = real(i*j) > uy(i,j) = real(i)/real(j) > p (i,j) = real(i) + real(j) > enddo > enddo > write(11) ux,uy > write(11) p > close(11) > end program makeArray When I run the above program compiled with gfortran on my Intel Mac, I can read it back with:: >>> import numpy as np >>> from fortranfile import FortranFile >>> f=FortranFile('uxuyp.bin', endian='<') >>> uxuy = f.readReals(prec='f') # 'f' for default reals >>> len(uxuy) 400 >>> ux = np.array(uxuy[:200]).reshape((20,10)).T >>> uy = np.array(uxuy[200:]).reshape((20,10)).T >>> p = f.readReals('f').reshape((20,10)).T >>> ux array([[ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20.], [ 2., 4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24., 26., 28., 30., 32., 34., 36., 38., 40.], [ 3., 6., 9., 12., 15., 18., 21., 24., 27., 30., 33., 36., 39., 42., 45., 48., 51., 54., 57., 60.], [ 4., 8., 12., 16., 20., 24., 28., 32., 36., 40., 44., 48., 52., 56., 60., 64., 68., 72., 76., 80.], [ 5., 10., 15., 20., 25., 30., 35., 40., 45., 50., 55., 60., 65., 70., 75., 80., 85., 90., 95., 100.], [ 6., 12., 18., 24., 30., 36., 42., 48., 54., 60., 66., 72., 78., 84., 90., 96., 102., 108., 114., 120.], [ 7.,Proxy-Connection: keep-alive Cache-Control: max-age=0 14., 21., 28., 35., 42., 49., 56., 63., 70., 77., 84., 91., 98., 105., 112., 119., 126., 133., 140.], [ 8., 16., 24., 32., 40., 48., 56., 64., 72., 80., 88., 96., 104., 112., 120., 128., 136., 144., 152., 160.], [ 9., 18., 27., 36., 45., 54., 63., 72., 81., 90., 99., 108., 117., 126., 135., 144., 153., 162., 171., 180.], [ 10., 20., 30., 40., 50., 60., 70., 80., 90., 100., 110., 120., 130., 140., 150., 160., 170., 180., 190., 200.]]) >>> uy array([[ 1. , 0.5 , 0.33333334, 0.25 , 0.2 , 0.16666667, 0.14285715, 0.125 , 0.11111111, 0.1 , 0.09090909, 0.08333334, 0.07692308, 0.07142857, 0.06666667, 0.0625 , 0.05882353, 0.05555556, 0.05263158, 0.05 ], [ 2. , 1. , 0.66666669, 0.5 , 0.40000001, 0.33333334, 0.2857143 , 0.25 , 0.22222222, 0.2 , 0.18181819, 0.16666667, 0.15384616, 0.14285715, 0.13333334, 0.125 , 0.11764706, 0.11111111, 0.10526316, 0.1 ], [ 3. , 1.5 , 1. , 0.75 , 0.60000002, 0.5 , 0.42857143, 0.375 , 0.33333334, 0.30000001, 0.27272728, 0.25 , 0.23076923, 0.21428572, 0.2 , 0.1875 , 0.17647059, 0.16666667, 0.15789473, 0.15000001], [ 4. , 2. , 1.33333337, 1. , 0.80000001, 0.66666669, 0.5714286 , 0.5 , 0.44444445, 0.40000001, 0.36363637, 0.33333334, 0.30769232, 0.2857143 , 0.26666668, 0.25 , 0.23529412, 0.22222222, 0.21052632, 0.2 ], [ 5. , 2.5 , 1.66666663, 1.25 , 1. , 0.83333331, 0.71428573, 0.625 , 0.55555558, 0.5 , 0.45454547, 0.41666666, 0.38461539, 0.35714287, 0.33333334, 0.3125 , 0.29411766, 0.27777779, 0.2631579 , 0.25 ], [ 6. , 3. , 2. , 1.5 , 1.20000005, 1. , 0.85714287, 0.75 , 0.66666669, 0.60000002, 0.54545456, 0.5 , 0.46153846, 0.42857143, 0.40000001, 0.375 , 0.35294119, 0.33333334, 0.31578946, 0.30000001], [ 7. , 3.5 , 2.33333325, 1.75 , 1.39999998, 1.16666663, 1. , 0.875 , 0.77777779, 0.69999999, 0.63636363, 0.58333331, 0.53846157, 0.5 , 0.46666667, 0.4375 , 0.41176471, 0.3888889 , 0.36842105, 0.34999999], [ 8. , 4. , 2.66666675, 2. , 1.60000002, 1.33333337, 1.14285719, 1. , 0.8888889 , 0.80000001, 0.72727275, 0.66666669, 0.61538464, 0.5714286 , 0.53333336, 0.5 , 0.47058824, 0.44444445, 0.42105263, 0.40000001], [ 9. , 4.5 , 3. , 2.25 , 1.79999995, 1.5 , 1.28571427, 1.125 , 1. , 0.89999998, 0.81818181, 0.75 , 0.69230771, 0.64285713, 0.60000002, 0.5625 , 0.52941179, 0.5 , 0.47368422, 0.44999999], [ 10. , 5. , 3.33333325, 2.5 , 2. , 1.66666663, 1.42857146, 1.25 , 1.11111116, 1. , 0.90909094, 0.83333331, 0.76923078, 0.71428573, 0.66666669, 0.625 , 0.58823532, 0.55555558, 0.52631581, 0.5 ]]) >>> p array([[ 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21.], [ 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22.], [ 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23.], [ 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24.], [ 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25.], [ 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26.], [ 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.], [ 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.], [ 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29.], [ 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30.]]) Note that you have to provide the shape information for ux and uy because fortran writes them together as a stream of 400 numbers. -Neil [View Less]

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Adding to the non-dispatched implementation of NumPy methods
by Stephan Hoyer May 13, 2019

May 13, 2019

Hi everyone, We have a proposed a revision to NEP-18 (__array_function__). The proposal is for an adding an alias to the non-dispatched version of NumPy array functions in the __numpy_implementaiton__ function attribute: https://github.com/numpy/numpy/pull/13305 I believe this attribute improves the protocol in three ways: 1. It provides a hook that __array_function__ methods can use to call implementation intended for NumPy arrays. This allows for "partial implementations" of NumPy's API, … [View More]

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Re: [Numpy-discussion] grant proposal for core scientific Python projects (rejected)
by Joe Harrington May 4, 2019

May 4, 2019

Hi Ralf, The rejection is disappointing, for sure. Some good ammo for next time might be the recommendations in this report from the US National Academies of Science, Engineering, and Medicine: http://sites.nationalacademies.org/SSB/CurrentProjects/SSB_178892 https://www.nap.edu/read/25217/chapter/1#ii You can download a free PDF if you click around and give them an email address. There is some code on the cover that might raise a smile. Lorena Barba, Kelle Cruz, and many … [View More]other community members contributed, both as committee members and as white-paper authors. While it's a report for NASA, the conclusions are strong and there is explicit support of investment in community resources like numpy, scipy, astropy, matplotlib, etc. Other agencies are asking similar questions, so I expect the report to get somewhat of a look at NSF, etc. A note on the Academies' process: A consensus study report must only include statements that no single member of the committee objects to, and the committee generally only includes senior members or people with a lot of relevant experience. There were stakeholders from some large modeling shops for whom openness might be a threat to their business model, in their eyes, and some of the senior members had never experienced the open-source environment and had bad experiences sharing software. This made for an interesting social dynamic, and prevented an all-out recommendation to forcibly open everything immediately. Given all that, I was ultimately pleased that we got full agreement on the recommendations we did make. So, some general thoughts on fundraising, not specific to this proposal: 1. Try NASA. The Administrator for Space Science, Thomas Zurbuchen, is pushing "open" very hard, given the success of open data in NASA Earth Science, and its positive impact on the economy in fields like agriculture and weather forecasting. He paid for the study above. Many grant programs specifically solicit proposals for open-source tools. There are also technology development programs in other parts of NASA than the Science Mission Directorate. Try contacting Dr. Michael New, who is Zurbuchen's deputy, and could direct you to appropriate programs. (Please, let's be coordinated and not all deluge the guy.) 2. As suggested in another message, it's often easier to get support for a specific, targeted item as part of a big project or institute using that item, such as LSST or the black-hole group. There's a certain way to wend into those projects, usually originating from within. STScI has long devoted programmer resources, for example. 3. There's such a thing as a share-in-savings contract at NASA, in which you calculate a savings, such as from avoided costs of licensing IDL or Matlab, and say you'll develop a replacement for that product that costs less, in exchange for a portion of the savings. These are rare and few people know about them, but one presenter to the committee did discuss them and thought they'd be appropriate. I've always felt that we could get a chunk of change this way, and was surprised to find that the approach exists and has a name. About 3 of 4 people I talk to at NASA have no idea this even exists, though, and I haven't pursued it to its logical end to see if it's viable. 4. I mostly lurk here, since being more actively involved in the early days of numpy docs, so maybe this one has been tried already, or is in the works. My apologies if so. Think of development as a product to buy. You could put chunks of development up for sale, advertise them, and coordinate one or more groups buying them together. For something like an efficiency boost, you could price it according to the avoided cost of CPU resources for a project of a given size (e.g., somewhat below the net present value of avoided future AWS cycles for the projects buying it). It would be like buying a custom-built data pipeline, except that once you buy it, everyone gets it. This might mean scoping out a roadmap of improvements, packaging them into fundable projects with teams ready to go, pricing them, advertising them to specific customers and in trade media and shows, and making sales pitches. This sounds really weird to us scientists, but it would work just like a regular purchase for services, which the government and industry are much more used to doing than donations to open-source projects. Don't just sell what the customer is buying, sell in the manner that the customer likes to buy. 5. And, keep trying grant proposals to NSF! --jh-- On 4/18/19 6:36 AM, Ralf Gommers <ralf.gommers(a)gmail.com> wrote: > > A number of core projects (NumPy, SciPy, Matplotlib, Pandas, > scikit-learn) got together and put in a proposal to NSF for a large 5 > year grant, and it was unfortunately just rejected. We now published > the proposal, which may be of interest: > https://figshare.com/articles/Mid-Scale_Research_Infrastructure_-_The_Scien…. [View Less]

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ANN: SciPy 1.3.0rc1 -- please test
by Tyler Reddy May 1, 2019

May 1, 2019

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi all, On behalf of the SciPy development team I'm pleased to announce the release candidate SciPy 1.3.0rc1. Please help us test this pre-release. Sources and binary wheels can be found at:https://pypi.org/project/scipy/ and at:https://github.com/scipy/scipy/releases/tag/v1.3.0rc1 One of a few ways to install the release candidate with pip: pip install scipy==1.3.0rc1 ========================== SciPy 1.3.0 Release Notes =========================… [View More]

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NumPy Community Meeting on May 1/ 2019
by Tyler Reddy April 30, 2019

April 30, 2019

Hi, There will be a NumPy community meeting at 12 pm Pacific Time on May 1/ 2019. Anyone may join & edit the work in progress meeting notes available here: https://hackmd.io/MzSVnXjiR7ykM6ocNKAOxg?view Best wishes, Tyler

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ANN: NumPy and SciPy accepted in Summer of Docs, technical writer exploration phase open
by Ralf Gommers April 30, 2019

April 30, 2019

Hi all, Good news: NumPy and SciPy both were accepted as participating organizations for Google Summer of Docs! This could potentially be very interesting and impactful. If you have any tech writer friends that could be interested or that may have friends, colleagues or a community that may be: please point them to the announcement! Links for program details below. Our ideas pages are at: https://github.com/numfocus/gsod/blob/master/2019/NumPy_ideas_list.md https://github.com/numfocus/gsod/… [View More]blob/master/2019/SciPy_ideas_list.md Cheers, Ralf ---------- Forwarded message --------- From: 'Andrew Chen' via Season of Docs - Announce < season-of-docs-announce(a)googlegroups.com> Date: Tue, Apr 30, 2019 at 2:30 PM Subject: [Season of Docs - Announcements] Participating organizations announced and technical writer exploration phase open To: Season of Docs - Announce <season-of-docs-announce(a)googlegroups.com> Thank you for your enthusiasm and support for Season of Docs. We received nearly 200 organization applications! There were many high quality applications, so the selection of organizations was not easy. The list of 50 participating open source organizations for Season of Docs 2019 is now available at https://developers.google.com/season-of-docs/docs/participants/. Are you a technical writer interested in taking part in Season of Docs? Please explore the list of participating organizations and their project ideas. If any of the projects interest you, you can contact the open source organization now to start fleshing out your project proposal. You can explore more than one project, and when the technical writer application phase opens you can submit more than one project proposal, but only one proposal will be accepted. The exploration phase runs from April 30 to May 28. Take a look at the technical writer guidelines <https://developers.google.com/season-of-docs/docs/tech-writer-guide#tech-wr…> for this phase. You can submit your project proposals to Season of Docs when the technical writer application phase opens on May 29. See the full timeline <https://developers.google.com/season-of-docs/docs/timeline> on the Season of Docs website. We hope you enjoy exploring the available open source projects and choosing the project you’d like to work with! If you have any questions about the program, please email the Season of Docs team at season-of-docs-support(a)googlegroups.com. -- You received this message because you are subscribed to the Google Groups "Season of Docs - Announce" group. To unsubscribe from this group and stop receiving emails from it, send an email to season-of-docs-announce+unsubscribe(a)googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/season-of-docs-announce/aac7c948-d19f-48d… <https://groups.google.com/d/msgid/season-of-docs-announce/aac7c948-d19f-48d…> . For more options, visit https://groups.google.com/d/optout. [View Less]

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how much does binary size matter?
by Ralf Gommers April 30, 2019

April 30, 2019

Hi all, In https://github.com/numpy/numpy/pull/13207 a discussion started about the tradeoff between performance gain for one function vs increasing the size of a NumPy build by a couple of percent. We also discussed that in the community call on Wednesday and concluded that it may be useful to ask here for some more feedback. Beyond disk/memory usage and download bandwidth, are there specific problems that people are struggling with regarding size of numpy binaries? Right now a wheel is 16 … [View More]

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f2py is not recognizing Absoft Fortran Compiler
by Samuel Dupree April 27, 2019

April 27, 2019

I'm attempting to build an interface between a Fortran application I have and Python. The problem I'm having is that f2py is not recognizing my Absoft Fortran compiler. Details follow. I'm running on a iMacPro (2017) under Mac OS X Mojave (ver. 10.14.4). The version of the Absoft Compiler I'm running is 19.0.0. I'm using the Anaconda distribution of Python 3, version 3.6.8, where the version of NumPy used is ver. 1.16.3. The commands I'm using to build the Python interface function and … [View More]there results are: f2py -m DIVA_EphGen_f77 -h DIVA_EphGen_f77.pyf DIVA_EphGen_f77.f --overwrite-signature (base) Samuels-Mac-Pro:2nd_ODE_auto_deriv_cleanup_Rev-07 user$ ./BuildMe_Part-1.sh Reading fortran codes... Reading file 'DIVA_EphGen_f77.f' (format:fix,strict) Post-processing... Block: DIVA_EphGen_f77 Block: diva_ephgen_f77 Post-processing (stage 2)... Saving signatures to file "./DIVA_EphGen_f77.pyf" (base) Samuels-Mac-Pro:2nd_ODE_auto_deriv_cleanup_Rev-07 user$ f2py -c --fcompiler=absoft DIVA_EphGen_f77.pyf DIVA_EphGen_f77.f \ --f77exec=/Applications/Absoft19.0/bin/af77 \ -L/Users/user/2nd_ODE_auto_deriv_cleanup_Rev-07/ -lDIVA_EphGen \ -L/Volumes/Development/AstrodynamicsLib/MacOSX.NAIF.Fortran.v65/toolkit-64-bit/lib/ -lspicelib \ -L/Volumes/Development/AstrodynamicsLib/MacOSX.NAIF.Fortran.v65/toolkit-64-bit/lib/ -lsupport \ -L/Application/Absoft19.0/lib64/ -lblas \ -L/Application/Absoft19.0/lib64/ -lAbsoftlapack \ --verbose (base) Samuels-Mac-Pro:2nd_ODE_auto_deriv_cleanup_Rev-07 user$ ./BuildMe_Part-2.sh running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src build_src building extension "DIVA_EphGen_f77" sources creating /var/folders/65/7cxpqns144q6wx5lyb7zcyh80000gq/T/tmpkv4x9yg7/src.macosx-10.9-x86_64-3.6 f2py options: [] f2py: DIVA_EphGen_f77.pyf Reading fortran codes... Reading file 'DIVA_EphGen_f77.pyf' (format:free) Post-processing... Block: DIVA_EphGen_f77 Block: diva_ephgen_f77 Post-processing (stage 2)... Building modules... Building module "DIVA_EphGen_f77"... Constructing wrapper function "diva_ephgen_f77"... diva_ephgen_f77(cmdline,scale_factor) Wrote C/API module "DIVA_EphGen_f77" to file "/var/folders/65/7cxpqns144q6wx5lyb7zcyh80000gq/T/tmpkv4x9yg7/src.macosx-10.9-x86_64-3.6/DIVA_EphGen_f77module.c" adding '/var/folders/65/7cxpqns144q6wx5lyb7zcyh80000gq/T/tmpkv4x9yg7/src.macosx-10.9-x86_64-3.6/fortranobject.c' to sources. adding '/var/folders/65/7cxpqns144q6wx5lyb7zcyh80000gq/T/tmpkv4x9yg7/src.macosx-10.9-x86_64-3.6' to include_dirs. copying /Users/user/anaconda3/lib/python3.6/site-packages/numpy/f2py/src/fortranobject.c -> /var/folders/65/7cxpqns144q6wx5lyb7zcyh80000gq/T/tmpkv4x9yg7/src.macosx-10.9-x86_64-3.6 copying /Users/user/anaconda3/lib/python3.6/site-packages/numpy/f2py/src/fortranobject.h -> /var/folders/65/7cxpqns144q6wx5lyb7zcyh80000gq/T/tmpkv4x9yg7/src.macosx-10.9-x86_64-3.6 build_src: building npy-pkg config files running build_ext new_compiler returns <class 'distutils.unixccompiler.UnixCCompiler'> customize UnixCCompiler customize UnixCCompiler using build_ext ******************************************************************************** <class 'distutils.unixccompiler.UnixCCompiler'> preprocessor = ['x86_64-apple-darwin13.4.0-clang', '-E', '-D_FORTIFY_SOURCE=2', '-mmacosx-version-min=10.9'] compiler = ['x86_64-apple-darwin13.4.0-clang', '-DNDEBUG', '-fwrapv', '-O2', '-Wall', '-Wstrict-prototypes', '-march=core2', '-mtune=haswell', '-mssse3', '-ftree-vectorize', '-fPIC', '-fPIE', '-fstack-protector-strong', '-O2', '-pipe', '-D_FORTIFY_SOURCE=2', '-mmacosx-version-min=10.9'] compiler_so = ['x86_64-apple-darwin13.4.0-clang', '-DNDEBUG', '-fwrapv', '-O2', '-Wall', '-Wstrict-prototypes', '-march=core2', '-mtune=haswell', '-mssse3', '-ftree-vectorize', '-fPIC', '-fPIE', '-fstack-protector-strong', '-O2', '-pipe', '-D_FORTIFY_SOURCE=2', '-mmacosx-version-min=10.9'] compiler_cxx = ['x86_64-apple-darwin13.4.0-clang++'] linker_so = ['x86_64-apple-darwin13.4.0-clang', '-bundle', '-undefined', 'dynamic_lookup', '-Wl,-pie', '-Wl,-headerpad_max_install_names', '-Wl,-rpath,/Users/user/anaconda3/lib', '-L/Users/user/anaconda3/lib', '-Wl,-pie', '-Wl,-headerpad_max_install_names', '-Wl,-rpath,/Users/user/anaconda3/lib', '-L/Users/user/anaconda3/lib', '-Wl,-export_dynamic', '-Wl,-pie', '-Wl,-headerpad_max_install_names', '-Wl,-dead_strip_dylibs', '-march=core2', '-mtune=haswell', '-mssse3', '-ftree-vectorize', '-fPIC', '-fPIE', '-fstack-protector-strong', '-O2', '-pipe', '-D_FORTIFY_SOURCE=2', '-mmacosx-version-min=10.9'] linker_exe = ['x86_64-apple-darwin13.4.0-clang'] archiver = ['/Users/user/anaconda3/bin/x86_64-apple-darwin13.4.0-ar', 'rc'] ranlib = ['ranlib'] libraries = [] library_dirs = [] include_dirs = ['/Users/user/anaconda3/include/python3.6m'] ******************************************************************************** customize AbsoftFCompiler find_executable('/Users/user/anaconda3/bin/x86_64-apple-darwin13.4.0-gfortran') Found executable /Users/user/anaconda3/bin/x86_64-apple-darwin13.4.0-gfortran find_executable('/Applications/Absoft19.0/bin/af77') Found executable /Applications/Absoft19.0/bin/af77 find_executable('/Users/user/anaconda3/bin/x86_64-apple-darwin13.4.0-ar') Found executable /Users/user/anaconda3/bin/x86_64-apple-darwin13.4.0-ar find_executable('/Users/user/anaconda3/bin/x86_64-apple-darwin13.4.0-ranlib') Found executable /Users/user/anaconda3/bin/x86_64-apple-darwin13.4.0-ranlib x86_64-apple-darwin13.4.0-gfortran: error: unrecognized command line option ‘-V’ Traceback (most recent call last): File "/Users/user/anaconda3/bin/f2py", line 11, in <module> load_entry_point('numpy==1.16.3', 'console_scripts', 'f2py')() File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/f2py/f2py2e.py", line 683, in main run_compile() File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/f2py/f2py2e.py", line 650, in run_compile setup(ext_modules=[ext]) File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/core.py", line 171, in setup return old_setup(**new_attr) File "/Users/user/anaconda3/lib/python3.6/distutils/core.py", line 148, in setup dist.run_commands() File "/Users/user/anaconda3/lib/python3.6/distutils/dist.py", line 955, in run_commands self.run_command(cmd) File "/Users/user/anaconda3/lib/python3.6/distutils/dist.py", line 974, in run_command cmd_obj.run() File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/command/build.py", line 47, in run old_build.run(self) File "/Users/user/anaconda3/lib/python3.6/distutils/command/build.py", line 135, in run self.run_command(cmd_name) File "/Users/user/anaconda3/lib/python3.6/distutils/cmd.py", line 313, in run_command self.distribution.run_command(command) File "/Users/user/anaconda3/lib/python3.6/distutils/dist.py", line 974, in run_command cmd_obj.run() File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/command/build_ext.py", line 226, in run fcompiler.customize(self.distribution) File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/fcompiler/__init__.py", line 479, in customize f77flags = self.flag_vars.f77 File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/fcompiler/environment.py", line 40, in __getattr__ return self._get_var(name, conf_desc) File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/fcompiler/environment.py", line 56, in _get_var var = self._hook_handler(name, hook) File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/fcompiler/__init__.py", line 709, in _environment_hook return hook() File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/fcompiler/absoft.py", line 119, in get_flags_f77 v = self.get_version() File "/Users/user/anaconda3/lib/python3.6/site-packages/numpy/distutils/fcompiler/__init__.py", line 432, in get_version raise CompilerNotFound() numpy.distutils.fcompiler.CompilerNotFound (base) Samuels-Mac-Pro:2nd_ODE_auto_deriv_cleanup_Rev-07 user$ A copy of the Fortran code and its corresponding .pyf file have been attached to this note. Any suggestions as to how to fix this problem. Sam Dupree. [View Less]

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