- cctbxbb - phenix-online.org

building cctbx with external boost
by Marcin Wojdyr 19 Dec '13

19 Dec '13

Hi I vaguely remember a discussion some time ago about building cctbx with stand-alone boost libraries. Do you know what boost versions are compatible? Is using the --scan-boost option enough? I see that Gentoo has extra patch to unbundle boost from cctbx: http://sources.gentoo.org/cgi-bin/viewvc.cgi/gentoo-x86/sci-libs/cctbx/file… Is it necessary? I'm asking because at this moment we have in CCP4 two versions of boost, one in cctbx and the other for building DSSP (it uses different subset of boost libs than cctbx). It would make sense to use a single version for both, if possible. Cheers Marcin

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Re: [cctbxbb] cctbxbb Digest, Vol 59, Issue 1
by Zhenwei Luo 09 Dec '13

09 Dec '13

Hi Nat, Thanks for your reply! I have tried the first method you mentioned--adding an index value to the return method. It did work if I only needed a single array for future calculation. But I found it's not very convenient for my program. It's convenient and more efficient if other classes in it could process all the one-dimensional arrays at the same time. Otherwise, I needed to write more control code in python, and the c++ part could only deal with a single array now. Therefore, I hoped that I could pass such a multidimensional array in my program. Sincerely, Zhenwei On Sun, Dec 8, 2013 at 2:00 PM, <cctbxbb-request(a)phenix-online.org> wrote: > Send cctbxbb mailing list submissions to > cctbxbb(a)phenix-online.org > > To subscribe or unsubscribe via the World Wide Web, visit > http://phenix-online.org/mailman/listinfo/cctbxbb > or, via email, send a message with subject or body 'help' to > cctbxbb-request(a)phenix-online.org > > You can reach the person managing the list at > cctbxbb-owner(a)phenix-online.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of cctbxbb digest..." > > > Today's Topics: > > 1. Passing array between python and C++ (Zhenwei Luo) > 2. Re: Passing array between python and C++ (Nathaniel Echols) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sat, 7 Dec 2013 22:25:08 -0600 > From: Zhenwei Luo <tluozhenwei(a)gmail.com> > To: cctbxbb(a)phenix-online.org > Subject: [cctbxbb] Passing array between python and C++ > Message-ID: <90518A19-AC1B-493B-8B27-79D31EDDF055(a)gmail.com> > Content-Type: text/plain; charset=us-ascii > > Hello Everyone, > > I am writing a refinement program using the cctbx. I have > encountered with a problem when I wanted to pass an array between c++ and > python. The type of array I used in my c++ source file is > af::shared<af::shared<vec3> >, I would like to pass it into my python > script, thus I could do some other operations to this array. > I wrote a method in my class to return this array. > > af::shared<af::shared<vec3<double> > return_modes( ) { return modes; } > > I wrote another method in the *_ext file to wrap this method to make it > callable from python. > > .def("return_modes", &nm_init::return_modes) > > But when I use it in python, > eigenvector = nm_init_manager.return_modes() > > It gave me an error: > > TypeError: No to_python (by-value) converter found for c++ type: > scitbx::af::shared<scitbx::af::shared<scitbx::vec3<double> > > > > What I want to realize is just creating an two dimensional array using > vec3 as its element. I can also using the select method in this array to > select some elements from its column, just like in the > af::shared<vec3<double> > array. Namely, the column of this array should > have some same properties like af::shared<vec3<double> >. Can anyone help > me figure out what I should do? > > Thank you very much! Any help will be greatly appreciated. > > Sincerely, > Zhenwei Luo > Rice University > > > ------------------------------ > > Message: 2 > Date: Sat, 7 Dec 2013 20:45:10 -0800 > From: Nathaniel Echols <nechols(a)lbl.gov> > To: cctbx mailing list <cctbxbb(a)phenix-online.org> > Subject: Re: [cctbxbb] Passing array between python and C++ > Message-ID: > <CALeAa1MOL1wbW5Vb=M= > jXsnGTaCBQNJjcOzDwMhM27x5PP+XNA(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > On Sat, Dec 7, 2013 at 8:25 PM, Zhenwei Luo <tluozhenwei(a)gmail.com> wrote: > > > I am writing a refinement program using the cctbx. I have > > encountered with a problem when I wanted to pass an array between c++ and > > python. The type of array I used in my c++ source file is > > af::shared<af::shared<vec3> >, I would like to pass it into my python > > script, thus I could do some other operations to this array. > > I wrote a method in my class to return this array. > > > > af::shared<af::shared<vec3<double> > return_modes( ) { return modes; } > > > > I wrote another method in the *_ext file to wrap this method to make it > > callable from python. > > > > .def("return_modes", &nm_init::return_modes) > > > > But when I use it in python, > > eigenvector = nm_init_manager.return_modes() > > It gave me an error: > > TypeError: No to_python (by-value) converter found for c++ type: > > scitbx::af::shared<scitbx::af::shared<scitbx::vec3<double> > > > > > > What that error means is that boost.python doesn't know how to present this > new type to Python. For the data structures that we pass back and forth, > we have to explicitly provide wrappers for them - including new > instantiations of scitbx::array_family templates. > > What I want to realize is just creating an two dimensional array using vec3 > > as its element. I can also using the select method in this array to > select > > some elements from its column, just like in the af::shared<vec3<double> > > > array. Namely, the column of this array should have some same properties > > like af::shared<vec3<double> >. Can anyone help me figure out what I > should > > do? > > > > In general the scitbx::array_family templates aren't really intended to > every be multidimensional; for inherently 2D and 3D data types like images > and maps, we use flex.grid to provide a multi-dimensional accessor on top > of the 1D array. The grid may not be the most appropriate in your case but > if I'm making the correct assumptions about the data you're trying to pass > back and forth, I think it might be easiest to simply define a custom class > that contains a std::vector of af::shared<vec3> arrays, and add an index > parameter to the return_modes method, which would be modified to return > only a single array of modes at a time. You can also do things like > wrapping a method as __getitem__ with boost.python, which would mimic a 2D > array. (I can probably dig up/cook up some code examples tomorrow if this > is unclear, since it was certainly not intuitive to me when I started > working with CCTBX and it would be nice to have documentation for the > future.) > > -Nat >

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Passing array between python and C++
by Zhenwei Luo 08 Dec '13

08 Dec '13

Hello Everyone, I am writing a refinement program using the cctbx. I have encountered with a problem when I wanted to pass an array between c++ and python. The type of array I used in my c++ source file is af::shared<af::shared<vec3> >, I would like to pass it into my python script, thus I could do some other operations to this array. I wrote a method in my class to return this array. af::shared<af::shared<vec3<double> > return_modes( ) { return modes; } I wrote another method in the *_ext file to wrap this method to make it callable from python. .def("return_modes", &nm_init::return_modes) But when I use it in python, eigenvector = nm_init_manager.return_modes() It gave me an error: TypeError: No to_python (by-value) converter found for c++ type: scitbx::af::shared<scitbx::af::shared<scitbx::vec3<double> > > What I want to realize is just creating an two dimensional array using vec3 as its element. I can also using the select method in this array to select some elements from its column, just like in the af::shared<vec3<double> > array. Namely, the column of this array should have some same properties like af::shared<vec3<double> >. Can anyone help me figure out what I should do? Thank you very much! Any help will be greatly appreciated. Sincerely, Zhenwei Luo Rice University

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libtbx.run_tests_parallel
by Graeme.Winter＠diamond.ac.uk 14 Nov '13

14 Nov '13

Folks, Would anyone mind if I added an option to libtbx.run_tests_parallel to automatically make a temporary directory, chdir to there and run? It would mean I could write a little update / build / run tests script more easily. auto_run_dir=true springs to mind as a Phil option. Any thoughts? Thanks & best wishes, Graeme -- This e-mail and any attachments may contain confidential, copyright and or privileged material, and are for the use of the intended addressee only. If you are not the intended addressee or an authorised recipient of the addressee please notify us of receipt by returning the e-mail and do not use, copy, retain, distribute or disclose the information in or attached to the e-mail. Any opinions expressed within this e-mail are those of the individual and not necessarily of Diamond Light Source Ltd. Diamond Light Source Ltd. cannot guarantee that this e-mail or any attachments are free from viruses and we cannot accept liability for any damage which you may sustain as a result of software viruses which may be transmitted in or with the message. Diamond Light Source Limited (company no. 4375679). Registered in England and Wales with its registered office at Diamond House, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, United Kingdom

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iotbx newbie question
by wtempel 07 Nov '13

07 Nov '13

Hello all, please consider the scenario of a manuscript that, among other things, describes 20 crystal structures. Suppose the journal editor requires a Table 1. I now looking for a tool to prepare such table with high accuracy and little effort. My PDB deposition workflow includes the preparation of mmcif coordinates with pdb_extract. The mmcif file is complete in the sense that after upload to RCSB-ADIT, virtually no additional information is required for deposition. My intuition was to combine CSV and IOTBX python modules and produce the table via input of a list of mmcif files. The current phenix table_1 tool provides some, but not all of that functionality, and I thought once familiar with the python modules, I would quickly write the script. After confirming that the example at http://cctbx.sourceforge.net/iotbx_cif/ works with my cctbx installation, I attempted to transform that code to read in PDB mmcif coordinates: <code> test_structure = iotbx.cif.reader( file_path="/tmp/1NXC.cif").build_crystal_structures()["1NXC"] </code> which throws an exception: <output> Traceback (most recent call last): File "1NXC.py", line 3, in <module> test_structure = iotbx.cif.reader(file_path="/tmp/1NXC.cif").build_crystal_structures()["1NXC"] KeyError: '1NXC' </output> How do I need to write the code so that it returns a python object with access to all the cif items? Thank you, Wolfram Tempel

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compiler warning in dxtbx
by Oleg Dolomanov 04 Nov '13

04 Nov '13

Hi guys, there was big change in dxtbx/model/panel.h on the 30th of October (r18499) and apparently the != operator became recursive by calling itself rather than the == operator (line 378) - whoever is responsible - please check/fix, Cheers, Oleg.

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Request for a fix in CC1/2 calculation in phenix.merging_statistics
by Keitaro Yamashita 28 Oct '13

28 Oct '13

Dear CCTBX developers, I found a big difference in CC1/2 value (say, 77.3 vs 68.3) between phenix.merging_statistics and XSCALE when more than one *anomalous* dataset was merged in XSCALE. phenix.merging_statistics seems to assume that equivalent (in case of anomalous, here I do not consider Friedel pairs as equivalent) reflections are sorted (equivalent reflections are not separeted) in the input file. Usually, this assumption should be correct. However, if multiple anomalous datasets were merged in XSCALE, this assumption is not correct. Because Friedel pairs are not necessarily separated. This is a real example (in P43212). These lines are extracted from .HKL file by XSCALE: > 1 -41 1 1.749E+04 1.657E+05 2052.0 2467.7 78.8 -113.23 1 > 41 -1 -1 4.569E+03 6.014E+03 454.1 1112.8 132.2 116.90 1 > 41 1 -1 8.721E+03 2.637E+03 473.0 1064.4 130.4 116.11 2 > 41 1 1 7.634E+03 2.417E+03 498.2 1010.8 135.3 115.65 2 > -1 -41 -1 4.847E+03 1.997E+03 1892.9 2543.0 85.9 -122.78 2 The last number indicates the dataset the reflection belongs to. Here, (1 -41 1), (41 -1 -1), (41, 1, 1), and (-1, -41, -1) are equivalent reflections, but (41, 1, -1) in the middle is not when anomalous data! Therefore, in phenix.merging_statistics, subsets calculation for (41,1,1) is performed twice (for first two and last two). When I changed the cctbx code to sort reflections after mapping to a.s.u., CC1/2 values by phenix.merging_statistics became closer to XSCALE. In merging_stats.__init__() in iotbx/merging_statistics.py, I inserted a line > array = array.sort("packed_indices") after > array = array.customized_copy(anomalous_flag=anomalous).map_to_asu() but I think there would be more correct way to fix this unexpected behavior. Best regards, Keitaro

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correlation function for cctbx.miller.array
by Gabor Bunkoczi 24 Oct '13

24 Oct '13

Hi, I need to calculate the correlation function between two maps, both of them are stored as miller.array objects. There is a map_correlation method, which does something similar to what I want, but this calculates the total correlation coefficient, while what I need is another miller.array with amplitudes = f1*f2 and phases = p2-p1 (where f1, f2 are amplitudes and p1, p2 are phases of map1 and map2, respectively), i.e. not just the sum of these. Is this available somewhere? There is the additional complication that the hkl-list for map1 and map2 may not be fully identical, but the intersect of the two maps could be taken. Thanks, Gabor

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Scipy / cctbx core dump
by Graeme.Winter＠diamond.ac.uk 15 Oct '13

15 Oct '13

Hi Folks, Just trying to use something here which depends on scipy but it seems scipy is not playing nice with flex: from scitbx.array_family import flex import scipy.linalg A tiny and inoffensive script however... cctbx.python boom.py show_stack(1): /home/gw56/svn/cctbx_base_15oct13/cctbx_plus_build/base/lib/python2.7/site-packages/scipy/linalg/blas.py(113) <module> show_stack(2): /home/gw56/svn/cctbx_base_15oct13/cctbx_plus_build/base/lib/python2.7/site-packages/scipy/linalg/misc.py(5) <module> show_stack(3): /home/gw56/svn/cctbx_base_15oct13/cctbx_plus_build/base/lib/python2.7/site-packages/scipy/linalg/__init__.py(147) <module> show_stack(4): /scratch/gw56/2013/OCT/15/multi-lattice/boom/boom.py(2) <module> libc backtrace (2 frames, most recent call last): /home/gw56/svn/cctbx_base_15oct13/cctbx_plus_build/base/lib/python2.7/site-packages/numpy/core/multiarray.so(PyArray_API+0) [0x7fb2064c9940] /lib64/libc.so.6() [0x37b3232920] Segmentation fault (Python and libc call stacks above) This crash may be due to a problem in any imported Python module, including modules which are not part of the cctbx project. To disable the traps leading to this message, define these environment variables (e.g. assign the value 1): BOOST_ADAPTBX_FPE_DEFAULT BOOST_ADAPTBX_SIGNALS_DEFAULT This will NOT solve the problem, just mask it, but may allow you to proceed in case it is not critical. I did a fresh nightly build install just to be sure :o( if I export those naughty env vars I get a core dump: cctbx.python boom.py Segmentation fault (core dumped) RHEL6.4 / scipy 0.12.0 and 0.12.1 any ideas? Thanks, Graeme Dr. Graeme Winter Senior Software Scientist Diamond Light Source +44 1235 778091 (work) +44 7786 662784 (work mobile) -- This e-mail and any attachments may contain confidential, copyright and or privileged material, and are for the use of the intended addressee only. If you are not the intended addressee or an authorised recipient of the addressee please notify us of receipt by returning the e-mail and do not use, copy, retain, distribute or disclose the information in or attached to the e-mail. Any opinions expressed within this e-mail are those of the individual and not necessarily of Diamond Light Source Ltd. Diamond Light Source Ltd. cannot guarantee that this e-mail or any attachments are free from viruses and we cannot accept liability for any damage which you may sustain as a result of software viruses which may be transmitted in or with the message. Diamond Light Source Limited (company no. 4375679). Registered in England and Wales with its registered office at Diamond House, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, United Kingdom

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Model based outlier calculation in mmtbx.scaling.outlier_rejection
by Keitaro Yamashita 09 Sep '13

09 Sep '13

Dear cctbx developers, I am interested in the implementation of model-based reflection outlier rejection. As I read the code mmtbx/scaling/outlier_rejection.py (lines 244-351), I noticed that maybe there was a discrepancy between what log_message explained and the actual code. The log_message in the code says: > Outliers are rejected on the basis of the assumption that a scaled > log likelihood differnce 2(log[P(Fobs)]-log[P(Fmode)])/Q\" is distributed > according to a Chi-square distribution (Q\" is equal to the second > derivative of the log likelihood function of the mode of the > distribution). > The outlier threshold of the p-value relates to the p-value of the > extreme value distribution of the chi-square distribution. while actual p_value is calculated for each hkl as p_value = 1 - erf(sqrt(LLG))**N, where LLG = log p(F=Fbar | Fmodel) - log p(F=Fobs | Fmodel), and N is the number of reflections. Here, Fbar is F which gives the maximum value of p(F | Fmodel). At least, Q (the second derivative of p(F=Fbar | Fmodel)) is not used in the actual calculation. Could someone please explain the meaning of the actual calculation? Why taking square-root and raising erf() result to the power of N? Thank you very much, Keitaro

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