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bin_centers() and d_star_sq
by James Stroud 09 Apr '13

09 Apr '13

Hello All, I'm genuinely perplexed about what factors should go into choosing an appropriate d_star_sq to calculate bin_centers() in cctbx.miller.binner. This decision may be a nuance because it doesn't seem change the output significantly (except for low resolution bins). But if it doesn't matter significantly, then why have the parameter in the first place? James py> binner = miller.setup_binner(n_bins=10) py> binner.show_summary() unused: - 81.7405 [ 0/0 ] bin 1: 81.7405 - 6.1396 [2341/2341] bin 2: 6.1396 - 4.8734 [2213/2213] bin 3: 4.8734 - 4.2574 [2185/2185] bin 4: 4.2574 - 3.8681 [2168/2168] bin 5: 3.8681 - 3.5909 [2177/2177] bin 6: 3.5909 - 3.3792 [2156/2156] bin 7: 3.3792 - 3.2099 [2137/2137] bin 8: 3.2099 - 3.0702 [2144/2144] bin 9: 3.0702 - 2.9520 [2133/2133] bin 10: 2.9520 - 2.8501 [2135/2135] unused: 2.8501 - [ 0/0 ] py> centers = binner.bin_centers(1) py> list(1 / centers) [11.421375552155686, 5.4336997182888345, 4.544594791289144, 4.053431451445772, 3.7243527058119903, 3.481806175995981, 3.292371389128289, 3.138504394416836, 3.0099330507138475, 2.9001646196929975] py> centers = binner.bin_centers(4) py> list(1 / centers**(1 / 4)) [7.301226942489155, 5.330776416864701, 4.514065417212759, 4.039592121777967, 3.716672320747147, 3.4770032890247498, 3.28912114749567, 3.13617782414047, 3.0081962210988116, 2.8988250671976883]

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match_indices.paired_miller_indices() ungraceful overshoot
by James Stroud 08 Apr '13

08 Apr '13

Hello all, I accidentally gave paired_miller_indices() a value > 1 for i_array, and got a segfault. The problem looks to be in match_indices.cpp, line 94: result.push_back(miller_indices_[i_array][pairs_[i][i_array]]); Maybe there should be a test that raises an exception on the python side, if possible. James

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flex and numpy caveats
by James Stroud 06 Apr '13

06 Apr '13

Hello All, I've noticed some incompatibilities between numpy and cctbx, which is understandable. However, the incompatibilities manifest either as nonsense errors or, worse, not at all. Following are a couple of examples I have found. 1. The first example should really throw an exception, because silent failures like this can be catastrophic: py> from numpy import random py> r = random.randint(2, size=10) py> r array([1, 0, 1, 1, 0, 1, 0, 1, 1, 1]) py> list(flex.bool(r)) [True, False, False, False, False, False, False, False, False, False] This example is clearly due to incorrect assumptions about the internal representations of numpy ndarrays. Much better behavior can be seen when using a sequence of python `int` objects: py> list(flex.bool(range(10))) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /Users/jstroud/Unison/Code/radialx/testdata/<ipython-input-754-dce96b02979e> in <module>() ----> 1 list(flex.bool(range(10))) TypeError: No registered converter was able to produce a C++ rvalue of type bool from this Python object of type int 2. Although not as potentially catastrophic as the first, the second example should (in a perfect world) either work or throw a more meaningful exception: py> flex.int(range(10))[r[0]] --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /Users/jstroud/Unison/Code/radialx/testdata/<ipython-input-753-f14587f0ceeb> in <module>() ----> 1 flex.int(range(10))[r[0]] TypeError: 'numpy.int64' object is not iterable This example is obviously a result of type checking for a python `int`. The usual python approach of duck-type checking would avoid this problem: def __getitem__(self, i): try: i = int(i) except: pass return do_whatever_with_i(i) James

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Wilson Plot
by James Stroud 01 Apr '13

01 Apr '13

Hello All, The docsting for cctbx.miller.array.wilson_plot() does not seem to agree with its function (see below). Am I misinterpreting something? James py> miller.wilson_plot.__doc__ '<data^2>' py> miller.wilson_plot() (0.6109909654097065+4.386371170677923j) py> flex.mean(miller.data()) (0.6109909654097065+4.386371170677923j) py> flex.mean(miller.data() * flex.conj(miller.data())) (366421.87112270086+0j) py> flex.mean(miller.data() * miller.data()) (70775.39818541733-1856.4852414296488j)

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Miller array by index
by James Stroud 28 Mar '13

28 Mar '13

Hello All, I ask this question mostly out of curiosity, but what is the most direct way to access the value for a Miller index? The best I can do is the method below, but it seems rather indirect. James py> miller <cctbx.miller.array at 0x107bfa290> py> idx = (0, 0, 2) py> miller.select_indices([idx]).data()[0] (-26338.974329482127+0j)

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Re: [cctbxbb] [ccp4bb] refinement protein structure
by James Stroud 27 Mar '13

27 Mar '13

On Mar 27, 2013, at 12:32 PM, Anastassis Perrakis wrote: > These said, I am rather easily irritated these days, so I will not comment on the irritable character of the email. ... > we will soon start calling disordered loops > positionally challenged polypeptide segments (*). You might want to embrace the power of positive thinking. Where you see "positionally challenged", an optimist would see "entropically gifted". James

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Rotate & translate a structure
by James Stroud 26 Mar '13

26 Mar '13

Hello all, I have a rotation + translation matrix. Let's say py> mtx array([[ 0.88302225, 0.11697778, 0.45451948, 5. ], [ 0.11697778, 0.88302225, -0.45451948, 10. ], [ -0.45451948, 0.45451948, 0.76604444, 20. ], [ 0. , 0. , 0. , 1. ]]) My usual way of transforming a set of coordinates with a 4x4 matrix is to use numpy: py> xyz_1 array([[ 5., 10., 15., 1.], [ 20., 15., 10., 1.]]) py> numpy.inner(xyz_1, mtx) array([[ 17.40268126, 12.59731919, 33.76326397, 1. ], [ 28.9603065 , 21.03969455, 25.38784698, 1. ]]) What is the equivalent in cctbx? Is there a way to avoid converting coordinates back and fourth between numpy arrays with atoms().extract_xyz() & .set_xyz() (as might be used from a iotbx_pdb_hierarchy_ext.root). Thank you for any help. James

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Left to dry by iotbx_pdb_ext.input.construct_hierarchy()
by James Stroud 25 Mar '13

25 Mar '13

Hello all, This seems like it should qualify as a bug. If I have an instance of iotbx_pdb_ext.input and I create a hierarchy with construct_hierarchy(), then I must retain the reference to that hierarchy or apparently I can never get it back: >>> hierarchy = my_pdb.construct_hierarchy() >>> def some_local_scope_function(a_pdb): local_hierarchy = a_pdb.construct_hierarchy() >>> some_local_scope_function(my_pdb) […] RuntimeError: atom has another parent atom_group already. Wouldn't better behavior just return the previously constructed hierarchy given that multiple hierarchies can't be made? If each atom apparently remembers to which atom_group it belongs (and presumably on up), then shouldn't it make sense that an iotbx_pdb_ext.input be able to remember it's own hierarchy and produce it upon demand? Looking at a iotbx_pdb_hierarchy_ext.root, I don't find a reference to the iotbx_pdb_ext.input from which it was created. So, although passing around a hierarchy might be the obvious work-around, the end-user still needs to do some accounting if said user wants to track which roots belong to which inputs, and vice versa. James

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Build Notes for cctbx on OS X 10.7.5
by James Stroud 22 Mar '13

22 Mar '13

Hello All, I spent some time to build cctbx on an OS X 10.7 box for a non-system interpreter. I ran into some kinks along the way, so I thought I'd share my notes in case anyone wants to do the same. These notes are in reStructuredText, so it was no extra work to turn them into the attached HTML file, which might make reading a little easier. James ==================================== Build Notes for cctbx on OS X 10.7.5 ==================================== These notes describe a successful build of cctbx against a specific python interpreter, namely `Enthought python`_ 7.3-2 for x86_64. Although working, versions of cctbx are available for both the system python or with a dedicated python, these canned solutions are not optimal. First, it's not advisable to modify system utilities. Although cctbx seems well-behaved in this regard, other packages may not be so well behaved. Second, the canned approach requires building many of the numerous packages that come with bundeld python distributions like the Enthought distribution (some such packages exceed even cctbx in their difficulty to build). Third, if every package required its own python, every script would need to fire-up dozens of separate interpreters just to do its job, resulting in significant computational overhead with consummately slower execution times. .. _`Enthought python`: http://www.enthought.com/products/epd.php 1. The default c++ compiler for OS X 10.7 is actually clang (``/usr/bin/c++``). Using clang exposes invalid template code. The first of many errors is:: In file included from /opt/cctbx/cctbx_sources/mmtbx/bulk_solvent/bulk_solvent_ext.cpp:7: /opt/cctbx/cctbx_sources/mmtbx/bulk_solvent/bulk_solvent.h:496:21: error: call to function 'r_factor' that is neither visible in the template definition nor found by argument-dependent lookup r.push_back(r_factor(f_obs, f_model.const_ref())); These types of errors are documented at the page http://clang.llvm.org/compatibility.html#dep_lookup .. note:: The installation directory is ``/opt/cctbx``. 2. I tried to use the HPC compilers at http://hpc.sourceforge.net/, but they do not recognize the ``-no-cpp-precomp`` flag. The web page https://svn.boost.org/trac/boost/ticket/6697 suggests the problem is with boost. However, according to the comments therein, this should have been fixed in boost 1.50. I am building against boost 1.52. Perplexed about the source of this compiler flag, I tracked it down to the file ``cctbx_sources/libtbx/SConscript``, after spending much of a day learning how scons goes about its business. There are two possible fixes: - Comment the following line in ``cctbx_sources/libtbx/SConscript``:: # env_etc.ccflags_base.extend(["-no-cpp-precomp"]) - Link ``/usr/bin/g++`` to ``c++`` in a way that it will be found first in the path. For example:: % ln -s /usr/bin/g++ ${HOME}/bin/c++ 3. I first fixed the ``-no-cpp-precomp`` error by the former, commenting the offending line in ``cctbx_sources/libtbx/SConscript`` but this failed with the error:: /opt/cctbx/cctbx_sources/scitbx/array_family/memory.h:35:47: error: operator '&&' has no right operand #elif defined(_XOPEN_SOURCE) && _XOPEN_SOURCE >= 600 && defined(_POSIX_ADVISORY_INFO) ^ The page http://forums.fedoraforum.org/archive/index.php/t-52929.html suggests that the naked ``_XOPEN_SOURCE`` wrecks the conditional when ``_XOPEN_SOURCE`` is not defined. One possible way to overcome this problem is to change the offending line into a nested if/then, hoping that the comparison never gets evaluated under circumstances when ``_XOPEN_SOURCE`` is not defined:: #elif defined(_XOPEN_SOURCE) #if _XOPEN_SOURCE >= 600 && defined(_POSIX_ADVISORY_INFO) #define SCITBX_AF_HAS_ALIGNED_MALLOC 1 #define SCITBX_AF_USE_POSIX_FOR_ALIGNED_MALLOC 1 #endif #endif However, this was unnecessary because the second fix to the ``-no-cpp-precomp`` error (linking ``/usr/bin/g++`` to ``c++``) worked and avoided changing the preprocessor source. 4. Left to its own devices, scons could not find my ``fftw3.h``, which I have installed (via fink) to ``/sw/include/fftw3.h``. To fix this problem, I inserted the second of the following two lines into the file ``cctbx_sources/libtbx/SConscript``:: env_etc.ccflags_base.extend(["-no-cpp-precomp"]) env_etc.ccflags_base.extend(["-I/sw/include"]) Although this allowed scons to find the header, it could not find the actual library, requiring the insertion of the second of the following lines into the file ``cctbx_sources/libtbx/SConscript``:: env_etc.shlinkflags_bpl = [ "-L/sw/lib", "-w", # suppress "source/lib does not exist" warning "-bundle", "-undefined", "dynamic_lookup"]

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structure_factors() "d_max" equivalent
by James Stroud 21 Mar '13

21 Mar '13

Hello All, I'm new to cctbx and trying to get the most rudimentary understanding. I would like to select all of the reflections within a particular resolution shell. This line from the tutorial: f_calc = quartz_structure.structure_factors(d_min=2).f_calc_array() gets all structure factors through the highest resolution of d_min=2 Å (excluding 0 0 0). My question: is there an equivalent to a d_max argument for this function (i.e. a low resolution limit)? James

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