Changeset 33e475a in sasmodels


Ignore:
Timestamp:
Aug 26, 2017 8:17:30 PM (7 years ago)
Author:
paperspace <paperspace@…>
Branches:
master, core_shell_microgels, costrafo411, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
Children:
573ffab
Parents:
d439007 (diff), bedb9b0 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.
Message:

Merge branch 'master' of ​https://github.com/SasView/sasmodels.git

Files:
14 added
5 deleted
17 edited
8 moved

Legend:

Unmodified
Added
Removed

  • .gitignore

    r8a5f021 rc26897a  
    1111/doc/api/ 
    1212/doc/model/ 
    13 /doc/ref/models 
     13/doc/guide/models 
    1414.mplconfig 
    1515/pylint_violations.txt 

  • .travis.yml

    r24cd982 rb419c2d  
    88      env: 
    99        - PY=2.7 
    10         - NUMPYSPEC=numpy 
    1110    - os: linux 
    1211      env: 
    13         - PY=3 
    14         - NUMPYSPEC=numpy 
     12        - PY=3.6 
    1513    - os: osx 
    1614      language: generic 
    1715      env: 
    1816        - PY=2.7 
    19         - NUMPYSPEC=numpy 
    2017    - os: osx 
    2118      language: generic 
    2219      env: 
    23         - PY=3 
    24         - NUMPYSPEC=numpy 
     20        - PY=3.5 
    2521 
    2622# whitelist 
    … …  
    5248  - conda info -a 
    5349 
    54   - conda install --yes python=$PY $NUMPYSPEC scipy cython mako cffi 
     50  - conda install --yes python=$PY numpy scipy cython mako cffi 
    5551 
    56   - if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then 
    57       pip install pyopencl; 
    58     fi; 
     52  # Not testing with opencl below, so don't need to install it 
     53  #- if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then 
     54  #    pip install pyopencl; 
     55  #  fi; 
    5956 
    6057install: 
    … …  
    6360 
    6461script: 
    65 - export WORKSPACE=/home/travis/build/SasView/sasmodels/ 
    66 - python -m sasmodels.model_test dll all 
     62- python --version 
     63- python -m sasmodels.model_test -v dll all 
    6764 
    6865notifications: 

  • doc/conf.py

    r39674a0 r8ae8532  
    4242             ] 
    4343 
     44# Redirect mathjax to a different CDN 
     45mathjax_path = "https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-MML-AM_CHTML" 
     46 
    4447# Add any paths that contain templates here, relative to this directory. 
    4548templates_path = ['_templates'] 

  • doc/developer/calculator.rst

    re822c97 r870a2f4  
    11.. currentmodule:: sasmodels 
     2 
     3.. _Calculator_Interface: 
    24 
    35Calculator Interface 
    … …  
    79model calculator which implements the polydispersity and magnetic SLD 
    810calculations.  There are three separate implementations of this layer, 
    9 *kernelcl.py* for OpenCL, which operates on a single Q value at a time, 
    10 *kerneldll.c* for the DLL, which loops over a vector of Q values, and 
    11 *kernelpy.py* for python models which operates on vector Q values. 
     11:mod:`kernelcl` for OpenCL, which operates on a single Q value at a time, 
     12:mod:`kerneldll` for the DLL, which loops over a vector of Q values, and 
     13:mod:`kernelpy` for python models which operates on vector Q values. 
    1214 
    1315Each implementation provides three different calls *Iq*, *Iqxy* and *Imagnetic* 

  • doc/developer/index.rst

    rb85be2d r2e66ef5  
    77   :maxdepth: 4 
    88 
     9   overview.rst 
    910   calculator.rst 

  • doc/genapi.py

    ra5b8477 r2e66ef5  
    22import os.path 
    33 
    4 MODULE_TEMPLATE=""".. Autogenerated by genmods.py 
     4MODULE_TEMPLATE = """.. Autogenerated by genmods.py 
    55 
    66****************************************************************************** 
    … …  
    1919""" 
    2020 
    21 INDEX_TEMPLATE=""".. Autogenerated by genmods.py 
     21INDEX_TEMPLATE = """.. Autogenerated by genmods.py 
    2222 
    2323.. _api-index: 
    … …  
    4646        os.makedirs(dir) 
    4747 
    48     for module,name in modules: 
    49         with open(os.path.join(dir,module+'.rst'), 'w') as f: 
     48    for module, name in modules: 
     49        with open(os.path.join(dir, module+'.rst'), 'w') as f: 
    5050            f.write(MODULE_TEMPLATE%locals()) 
    5151 
    52     rsts = "\n   ".join(module+'.rst' for module,name in modules) 
    53     with open(os.path.join(dir,'index.rst'),'w') as f: 
     52    rsts = "\n   ".join(module+'.rst' for module, name in modules) 
     53    with open(os.path.join(dir, 'index.rst'), 'w') as f: 
    5454        f.write(INDEX_TEMPLATE%locals()) 
    5555 
    5656 
    57 modules=[ 
    58     #('__init__', 'Top level namespace'), 
     57modules = [ 
     58    ('__init__', 'Sasmodels package'), 
    5959    #('alignment', 'GPU data alignment [unused]'), 
    6060    ('bumps_model', 'Bumps interface'), 
     61    ('compare_many', 'Batch compare models on different compute engines'), 
    6162    ('compare', 'Compare models on different compute engines'), 
    6263    ('convert', 'Sasview to sasmodel converter'), 
    … …  
    6667    ('direct_model', 'Simple interface'), 
    6768    ('exception', 'Annotate exceptions'), 
    68     #('frozendict', 'Freeze a dictionary to make it immutable'), 
    6969    ('generate', 'Model parser'), 
    7070    ('kernel', 'Evaluator type definitions'), 
    … …  
    7979    ('resolution', '1-D resolution functions'), 
    8080    ('resolution2d', '2-D resolution functions'), 
     81    ('rst2html', 'Convert doc strings the web pages'), 
    8182    ('sasview_model', 'Sasview interface'), 
    8283    ('sesans', 'SESANS calculation routines'), 
    83     #('transition', 'Model stepper for automatic model selection'), 
    8484    ('weights', 'Distribution functions'), 
    8585] 
    86 package='sasmodels' 
    87 package_name='Reference' 
     86package = 'sasmodels' 
     87package_name = 'Reference' 
    8888genfiles(package, package_name, modules) 

  • doc/gentoc.py

    r40a87fa r990d8df  
    1616    from sasmodels.modelinfo import ModelInfo 
    1717 
    18 TEMPLATE="""\ 
     18TEMPLATE = """\ 
    1919.. 
    2020    Generated from doc/gentoc.py -- DO NOT EDIT -- 
    … …  
    3030""" 
    3131 
    32 MODEL_TOC_PATH = "ref/models" 
     32MODEL_TOC_PATH = "guide/models" 
    3333 
    3434def _make_category(category_name, label, title, parent=None): 
    … …  
    6565        # assume model is in sasmodels/models/name.py, and ignore the full path 
    6666        model_name = basename(item)[:-3] 
    67         if model_name.startswith('_'): continue 
     67        if model_name.startswith('_'): 
     68            continue 
    6869        model_info = load_model_info(model_name) 
    6970        if model_info.category is None: 
    7071            print("Missing category for", item, file=sys.stderr) 
    7172        else: 
    72             category.setdefault(model_info.category,[]).append(model_name) 
     73            category.setdefault(model_info.category, []).append(model_name) 
    7374 
    7475    # Check category names 
    75     for k,v in category.items(): 
     76    for k, v in category.items(): 
    7677        if len(v) == 1: 
    77             print("Category %s contains only %s"%(k,v[0]), file=sys.stderr) 
     78            print("Category %s contains only %s"%(k, v[0]), file=sys.stderr) 
    7879 
    7980    # Generate category files for the table of contents. 
    … …  
    8687    # alphabetical order before them. 
    8788 
    88     if not exists(MODEL_TOC_PATH): mkdir(MODEL_TOC_PATH) 
     89    if not exists(MODEL_TOC_PATH): 
     90        mkdir(MODEL_TOC_PATH) 
    8991    model_toc = _make_category( 
    90         'index',  'Models', 'Model Functions') 
     92        'index', 'Models', 'Model Functions') 
    9193    #shape_toc = _make_category( 
    9294    #    'shape',  'Shapes', 'Shape Functions', model_toc) 
    9395    free_toc = _make_category( 
    94         'shape-independent',  'Shape-independent', 
     96        'shape-independent', 'Shape-independent', 
    9597        'Shape-Independent Functions') 
    9698    struct_toc = _make_category( 
    97         'structure-factor',  'Structure-factor', 'Structure Factors') 
    98     custom_toc = _make_category( 
    99         'custom-models', 'Custom-models', 'Custom Models') 
     99        'structure-factor', 'Structure-factor', 'Structure Factors') 
     100    #custom_toc = _make_category( 
     101    #    'custom-models', 'Custom-models', 'Custom Models') 
    100102 
    101103    # remember to top level categories 
    … …  
    105107        'shape-independent':free_toc, 
    106108        'structure-factor': struct_toc, 
    107         'custom': custom_toc, 
     109        #'custom': custom_toc, 
    108110        } 
    109111 
    110112    # Process the model lists 
    111     for k,v in sorted(category.items()): 
     113    for k, v in sorted(category.items()): 
    112114        if ':' in k: 
    113             cat,subcat = k.split(':') 
     115            cat, subcat = k.split(':') 
    114116            _maybe_make_category(cat, v, cat_files, model_toc) 
    115117            cat_file = cat_files[cat] 
    116             label = "-".join((cat,subcat)) 
     118            label = "-".join((cat, subcat)) 
    117119            filename = label 
    118             title = subcat.capitalize()+" Functions" 
     120            title = subcat.capitalize() + " Functions" 
    119121            sub_toc = _make_category(filename, label, title, cat_file) 
    120122            for model in sorted(v): 
    … …  
    130132    _add_subcategory('shape-independent', model_toc) 
    131133    _add_subcategory('structure-factor', model_toc) 
    132     _add_subcategory('custom-models', model_toc) 
     134    #_add_subcategory('custom-models', model_toc) 
    133135 
    134136    # Close the top-level category files 
    135137    #model_toc.close() 
    136     for f in cat_files.values(): f.close() 
     138    for f in cat_files.values(): 
     139        f.close() 
    137140 
    138141 

  • doc/guide/index.rst

    rbb6f0f3 r2e66ef5  
    1 ********** 
    2 SAS Models 
    3 ********** 
     1**************** 
     2SAS Models Guide 
     3**************** 
    44 
    5 Small angle X-ray and Neutron (SAXS and SANS) scattering examines the 
    6 scattering patterns produced by a beam travelling through the sample 
    7 and scattering at low angles.  The scattering is computed as a function 
    8 of $q_x$ and $q_y$, which for a given beam wavelength corresponds to 
    9 particular scattering angles. Each pixel on the detector corresponds to 
    10 a different scattering angle. If the sample is unoriented, the scattering 
    11 pattern will appear as rings on the detector.  In this case, a circular 
    12 average can be taken with 1-dimension data at $q = \surd (q_x^2 + q_y^2)$ 
    13 compared to the orientationally averaged SAS scattering pattern. 
     5.. toctree:: 
     6   :numbered: 4 
     7   :maxdepth: 4 
    148 
    15 Models have certain features in common. 
    16  
    17 Every model has a *scale* and a *background*. 
    18  
    19 Talk about orientation, with diagrams for orientation so that we don't need 
    20 a link on every model page? 
    21  
    22 .. _orientation: 
    23  
    24 .. figure: img/orientation1.jpg 
    25  
    26     Orientation in 3D 
    27  
    28 .. figure: img/orientation2.jpg 
    29  
    30     Orientation cross sections 
    31  
    32 Talk about polydispersity. 
    33  
    34 Talk about magnetism, converting the magnetism help file to inline text here, 
    35 with links so that models can point back to it. 
    36  
    37 Need to talk about structure factors even though we don't have any 
    38 implemented yet. 
     9   intro.rst 
     10   install.rst 
     11   pd/polydispersity.rst 
     12   resolution.rst 
     13   magnetism/magnetism.rst 
     14   sesans/sans_to_sesans.rst 
     15   sesans/sesans_fitting.rst 
     16   plugin.rst 
     17   scripting.rst 
     18   refs.rst 

  • doc/guide/magnetism/magnetism.rst

    rdeb854f r990d8df  
    22 
    33Polarisation/Magnetic Scattering 
    4 ======================================================= 
     4================================ 
    55 
    6 In earlier versions of SasView magnetic scattering was implemented in just five  
    7 (2D) models 
    8  
    9 *  :ref:`sphere` 
    10 *  :ref:`core-shell-sphere` 
    11 *  :ref:`core-multi-shell` 
    12 *  :ref:`cylinder` 
    13 *  :ref:`parallelepiped` 
    14  
    15 From SasView 4.x it is implemented on most models in the 'shape' category. 
    16  
    17 In general, the scattering length density (SLD = $\beta$) in each region where the 
    18 SLD is uniform, is a combination of the nuclear and magnetic SLDs and, for polarised 
    19 neutrons, also depends on the spin states of the neutrons. 
     6Models which define a scattering length density parameter can be evaluated 
     7 as magnetic models. In general, the scattering length density (SLD = 
     8 $\beta$) in each region where the SLD is uniform, is a combination of the 
     9 nuclear and magnetic SLDs and, for polarised neutrons, also depends on the 
     10 spin states of the neutrons. 
    2011 
    2112For magnetic scattering, only the magnetization component $\mathbf{M_\perp}$ 
    … …  
    9889.. note:: 
    9990    This help document was last changed by Steve King, 02May2015 
     91 
     92* Document History * 
     93 
     94| 2017-05-08 Paul Kienzle 

  • doc/guide/sesans/sesans_fitting.rst

    r3330bb4 r8ae8532  
    77=================== 
    88 
    9 .. note:: A proper installation of the developers setup of SasView (http://trac.sasview.org/wiki/AnacondaSetup) is a prerequisite for using these instructions. 
     9.. note:: 
     10 
     11    A proper installation of the developers setup of SasView 
     12    (http://trac.sasview.org/wiki/AnacondaSetup) is a prerequisite for 
     13    using these instructions. 
    1014 
    1115It is possible to fit SESANS measurements from the command line in Python. 
    … …  
    1317Simple Fits 
    1418........... 
    15 In the folder sasmodels/example the file sesans_sphere_2micron.py gives an example of how to fit a shape to a measurement. 
     19In the folder sasmodels/example the file sesans_sphere_2micron.py gives 
     20an example of how to fit a shape to a measurement. 
    1621 
    1722The command:: 
    … …  
    2328.. image:: sesans_img/SphereLineFitSasView.png 
    2429 
    25 All the parameters and names in sesans_sphere_2micron.py (shown below) can be adjusted to fit your own problem:: 
     30All the parameters and names in sesans_sphere_2micron.py (shown below) can 
     31be adjusted to fit your own problem:: 
    2632 
    2733  """ 
    … …  
    6470  # Constraints 
    6571  # model.param_name = f(other params) 
    66   # EXAMPLE: model.scale = model.radius*model.radius*(1 - phi) - where radius and scale are model functions and phi is 
    67   # a custom parameter 
     72  # EXAMPLE: model.scale = model.radius*model.radius*(1 - phi) - where radius 
     73  # and scale are model functions and phi is a custom parameter 
    6874  model.scale = phi*(1-phi) 
    6975 
    … …  
    7480Incorporating a Structure Factor 
    7581................................ 
    76 An example of how to also include a structure factor can be seen in the following example taken from Washington et al.,  
    77 *Soft Matter*\, (2014), 10, 3016 (dx.doi.org/10.1039/C3SM53027B). These are time-of-flight measurements, which is the  
    78 reason that not the polarisation is plotted, but the :math:`\frac{log(P/P_0)}{\lambda^2}` . The sample is a dispersion  
    79 of core-shell colloids at a high volume fraction with hard sphere interactions. 
     82An example of how to also include a structure factor can be seen in the 
     83following example taken from Washington et al., *Soft Matter*\, (2014), 10, 3016 
     84(dx.doi.org/10.1039/C3SM53027B). These are time-of-flight measurements, which 
     85is the reason that not the polarisation is plotted, but the 
     86:math:`\frac{log(P/P_0)}{\lambda^2}` . The sample is a dispersion of 
     87core-shell colloids at a high volume fraction with hard sphere interactions. 
    8088 
    8189The fit can be started by:: 
    … …  
    8795.. image:: sesans_img/HardSphereLineFitSasView.png 
    8896 
    89 The code sesans_parameters_css-hs.py can then be used as a template for a fitting problem with a structure factor:: 
     97The code sesans_parameters_css-hs.py can then be used as a template for a 
     98fitting problem with a structure factor:: 
    9099 
    91100 """ 
    … …  
    131140 # Constraints 
    132141 # model.param_name = f(other params) 
    133  # EXAMPLE: model.scale = model.radius*model.radius*(1 - phi) - where radius and scale are model functions and phi is 
    134  # a custom parameter 
     142 # EXAMPLE: model.scale = model.radius*model.radius*(1 - phi) - where radius 
     143 # and scale are model functions and phi is a custom parameter 
    135144 model.scale = phi*(1-phi) 
    136145 model.volfraction = phi 

  • doc/index.rst

    r7bb290c r8ae8532  
    1 Introduction 
    2 ============ 
     1sasmodels 
     2========= 
     3Small angle X-ray and Neutron scattering (SAXS and SANS) examines the 
     4scattering patterns produced by a beam travelling through the sample 
     5and scattering at low angles.  The scattering is computed as a function 
     6of reciprocal space $q$, which arises from a combination of beam wavelength 
     7and scattering angles. Each pixel on the detector corresponds to 
     8a different scattering angle, and has a distinct $q_x$ and $q_y$. If the 
     9sample is unoriented, the scattering pattern will appear as rings on the 
     10detector.  In this case, a circular average can be taken with 1-dimension 
     11data at $q = \surd (q_x^2 + q_y^2)$ compared to the orientationally 
     12averaged SAS scattering pattern. 
     13 
    314The sasmodels package provides theory functions for small angle scattering 
    4 calculations. 
     15calculations for different shapes, including the effects of resolution, 
     16polydispersity and orientational dispersion. 
    517 
    618.. htmlonly:: 
    … …  
    1527 
    1628   guide/index.rst 
     29   guide/models/index.rst 
    1730   developer/index.rst 
    18    ref/index.rst 
    19    ref/models/index.rst 
    2031   api/index.rst 
    2132 
    … …  
    2839.. htmlonly:: 
    2940  * :ref:`search` 
    30  
    31  
    32  
    33  
    34    
    35  

  • example/model.py

    r1182da5 r2e66ef5  
    1717model = Model(kernel, 
    1818    scale=0.08, 
    19     r_polar=15, r_equatorial=800, 
     19    radius_polar=15, radius_equatorial=800, 
    2020    sld=.291, sld_solvent=7.105, 
    2121    background=0, 
    2222    theta=90, phi=0, 
    2323    theta_pd=15, theta_pd_n=40, theta_pd_nsigma=3, 
    24     r_polar_pd=0.222296, r_polar_pd_n=1, r_polar_pd_nsigma=0, 
    25     r_equatorial_pd=.000128, r_equatorial_pd_n=1, r_equatorial_pd_nsigma=0, 
     24    radius_polar_pd=0.222296, radius_polar_pd_n=1, radius_polar_pd_nsigma=0, 
     25    radius_equatorial_pd=.000128, radius_equatorial_pd_n=1, radius_equatorial_pd_nsigma=0, 
    2626    phi_pd=0, phi_pd_n=20, phi_pd_nsigma=3, 
    2727    ) 
    2828 
    2929# SET THE FITTING PARAMETERS 
    30 model.r_polar.range(15, 1000) 
    31 model.r_equatorial.range(15, 1000) 
     30model.radius_polar.range(15, 1000) 
     31model.radius_equatorial.range(15, 1000) 
    3232model.theta_pd.range(0, 360) 
    3333model.background.range(0,1000) 

  • sasmodels/alignment.py

    r7ae2b7f r870a2f4  
    4242    view[:] = x 
    4343    return view 
    44  

  • sasmodels/core.py

    r650c6d2 r2e66ef5  
    117117    Load model info and build model. 
    118118 
    119     *model_name* is the name of the model as used by :func:`load_model_info`. 
    120     Additional keyword arguments are passed directly to :func:`build_model`. 
     119    *model_name* is the name of the model, or perhaps a model expression 
     120    such as sphere*hardsphere or sphere+cylinder. 
     121 
     122    *dtype* and *platform* are given by :func:`build_model`. 
    121123    """ 
    122124    return build_model(load_model_info(model_name), 
    … …  
    128130    """ 
    129131    Load a model definition given the model name. 
     132 
     133    *model_name* is the name of the model, or perhaps a model expression 
     134    such as sphere*hardsphere or sphere+cylinder. 
    130135 
    131136    This returns a handle to the module defining the model.  This can be 
    … …  
    227232 
    228233    Possible types include 'half', 'single', 'double' and 'quad'.  If the 
    229     type is 'fast', then this is equivalent to dtype 'single' with the 
    230     fast flag set to True. 
     234    type is 'fast', then this is equivalent to dtype 'single' but using 
     235    fast native functions rather than those with the precision level guaranteed 
     236    by the OpenCL standard. 
     237 
     238    Platform preference can be specfied ("ocl" vs "dll"), with the default 
     239    being OpenCL if it is availabe.  If the dtype name ends with '!' then 
     240    platform is forced to be DLL rather than OpenCL. 
     241 
     242    This routine ignores the preferences within the model definition.  This 
     243    is by design.  It allows us to test models in single precision even when 
     244    we have flagged them as requiring double precision so we can easily check 
     245    the performance on different platforms without having to change the model 
     246    definition. 
    231247    """ 
    232248    # Assign default platform, overriding ocl with dll if OpenCL is unavailable 

  • sasmodels/model_test.py

    rbb4b509 rbedb9b0  
    4747import sys 
    4848import unittest 
     49 
     50try: 
     51    from StringIO import StringIO 
     52except ImportError: 
     53    # StringIO.StringIO renamed to io.StringIO in Python 3 
     54    # Note: io.StringIO exists in python 2, but using unicode instead of str 
     55    from io import StringIO 
    4956 
    5057import numpy as np  # type: ignore 
    … …  
    337344 
    338345def run_one(model): 
    339     # type: (str) -> None 
     346    # type: (str) -> str 
    340347    """ 
    341348    Run the tests for a single model, printing the results to stdout. 
    … …  
    350357 
    351358    # Build a object to capture and print the test results 
    352     stream = _WritelnDecorator(sys.stdout)  # Add writeln() method to stream 
     359    stream = _WritelnDecorator(StringIO())  # Add writeln() method to stream 
    353360    verbosity = 2 
    354361    descriptions = True 
    … …  
    388395    else: 
    389396        stream.writeln("Note: no test suite created --- this should never happen") 
     397 
     398    output = stream.getvalue() 
     399    stream.close() 
     400    return output 
    390401 
    391402 

  • sasmodels/models/multilayer_vesicle.py

    r5d23de2 r870a2f4  
    7171  sufficiently fine grained in certain cases. Please report any such occurences 
    7272  to the SasView team. Generally, for the best possible experience: 
    73  * Start with the best possible guess 
    74  * Using a priori knowledge, hold as many parameters fixed as possible 
    75  * if N=1, tw (water thickness) must by definition be zero. Both N and tw should 
     73 
     74 - Start with the best possible guess 
     75 - Using a priori knowledge, hold as many parameters fixed as possible 
     76 - if N=1, tw (water thickness) must by definition be zero. Both N and tw should 
    7677   be fixed during fitting. 
    77  * If N>1, use constraints to keep N > 1 
    78  * Because N only really moves in integer steps, it may get "stuck" if the 
     78 - If N>1, use constraints to keep N > 1 
     79 - Because N only really moves in integer steps, it may get "stuck" if the 
    7980   optimizer step size is too small so care should be taken 
    8081   If you experience problems with this please contact the SasView team and let 

  • sasmodels/resolution.py

    rb32caab r990d8df  
    437437    .. math:: 
    438438 
    439          \log \Delta q = (\log q_n - log q_1) / (n - 1) 
     439         \log \Delta q = (\log q_n - \log q_1) / (n - 1) 
    440440 
    441441    From this we can compute the number of steps required to extend $q$ 
    … …  
    451451 
    452452         n_\text{extend} = (n-1) (\log q_\text{max} - \log q_n) 
    453             / (\log q_n - log q_1) 
     453            / (\log q_n - \log q_1) 
    454454    """ 
    455455    q = np.sort(q) 
    … …  
    459459        log_delta_q = log(10.) / points_per_decade 
    460460    if q_min < q[0]: 
    461         if q_min < 0: q_min = q[0]*MINIMUM_ABSOLUTE_Q 
     461        if q_min < 0: 
     462            q_min = q[0]*MINIMUM_ABSOLUTE_Q 
    462463        n_low = log_delta_q * (log(q[0])-log(q_min)) 
    463464        q_low = np.logspace(log10(q_min), log10(q[0]), np.ceil(n_low)+1)[:-1] 

  • sasmodels/rst2html.py

    rf2f5413 r870a2f4  
    3838    - mathml 
    3939    - mathjax 
    40     See `http://docutils.sourceforge.net/docs/user/config.html#math-output`_ 
     40    See `<http://docutils.sourceforge.net/docs/user/config.html#math-output>`_ 
    4141    for details. 
    4242 
    … …  
    176176        from PyQt5.QtCore import QUrl 
    177177    except ImportError: 
    178         from PyQt4.QtWebkit import QWebView 
     178        from PyQt4.QtWebKit import QWebView 
    179179        from PyQt4.QtCore import QUrl 
    180180    helpView = QWebView() 
    … …  
    204204        from PyQt5.QtCore import QUrl 
    205205    except ImportError: 
    206         from PyQt4.QtWebkit import QWebView 
     206        from PyQt4.QtWebKit import QWebView 
    207207        from PyQt4.QtCore import QUrl 
    208208    frame = QWebView() 
    … …  
    211211    sys.exit(app.exec_()) 
    212212 
     213def can_use_qt(): 
     214    """ 
     215    Return True if QWebView exists. 
     216 
     217    Checks first in PyQt5 then in PyQt4 
     218    """ 
     219    try: 
     220        from PyQt5.QtWebKitWidgets import QWebView 
     221        return True 
     222    except ImportError: 
     223        try: 
     224            from PyQt4.QtWebKit import QWebView 
     225            return True 
     226        except ImportError: 
     227            return False 
     228 
    213229def view_help(filename, qt=False): 
    214230    import os 
    215     url="file:///"+os.path.abspath(filename).replace("\\","/") 
     231 
     232    if qt: 
     233        qt = can_use_qt() 
     234 
     235    url = "file:///"+os.path.abspath(filename).replace("\\", "/") 
    216236    if filename.endswith('.rst'): 
    217237        html = load_rst_as_html(filename) 

  • sasmodels/models/star_polymer.py

    r40a87fa rd439007  
    11r""" 
    2 The Benoit model for a simple star polymer, with Gaussian coils arms from 
    3 a common point. 
    4  
    52Definition 
    63---------- 
     4 
     5Calcuates the scattering from a simple star polymer with f equal Gaussian coil 
     6arms. A star being defined as a branched polymer with all the branches 
     7emanating from a common central (in the case of this model) point.  It is 
     8derived as a special case of on the Benoit model for general branched 
     9polymers\ [#CITBenoit]_ as also used by Richter ''et. al.''\ [#CITRichter]_ 
    710 
    811For a star with $f$ arms the scattering intensity $I(q)$ is calculated as 
    … …  
    1518where 
    1619 
    17 .. math:: v=\frac{u^2f}{(3f-2)} 
     20.. math:: v=\frac{uf}{(3f-2)} 
    1821 
    1922and 
    … …  
    2124.. math:: u = \left\langle R_{g}^2\right\rangle q^2 
    2225 
    23 contains the square of the ensemble average radius-of-gyration of an arm. 
     26contains the square of the ensemble average radius-of-gyration of the full 
     27polymer while v contains the radius of gyration of a single arm $R_{arm}$. 
     28The two are related as: 
     29 
     30.. math:: R_{arm}^2 = \frac{f}{3f-2} R_{g}^2 
     31 
    2432Note that when there is only one arm, $f = 1$, the Debye Gaussian coil 
    25 equation is recovered. Star polymers in solutions tend to have strong 
    26 interparticle and osmotic effects, so the Benoit equation may not work well. 
    27 At small $q$ the Guinier term and hence $I(q=0)$ is the same as for $f$ arms 
    28 of radius of gyration $R_g$, as described for the :ref:`mono-gauss-coil` model. 
     33equation is recovered. 
     34 
     35.. note:: 
     36   Star polymers in solutions tend to have strong interparticle and osmotic 
     37   effects. Thus the Benoit equation may not work well for many real cases. 
     38   At small $q$ the Guinier term and hence $I(q=0)$ is the same as for $f$ arms 
     39   of radius of gyration $R_g$, as described for the :ref:`mono-gauss-coil` 
     40   model. A newer model for star polymer incorporating excluded volume has been 
     41   developed by Li et al in arXiv:1404.6269 [physics.chem-ph]. 
    2942 
    3043References 
    3144---------- 
    3245 
    33 H Benoit *J. Polymer Science*, 11, 596-599 (1953) 
     46.. [#CITBenoit] H Benoit *J. Polymer Science*, 11, 507-510 (1953) 
     47.. [#CITRichter] D Richter, B. Farago, J. S. Huang, L. J. Fetters, 
     48   B Ewen *Macromolecules*, 22, 468-472 (1989) 
     49 
     50Authorship and Verification 
     51---------------------------- 
     52 
     53* **Author:** Kieran Campbell **Date:** July 24, 2012 
     54* **Last Modified by:** Paul Butler **Date:** Auguts 26, 2017 
     55* **Last Reviewed by:** Ziang Li and Richard Heenan **Date:** May 17, 2017 
    3456""" 
    3557 
    … …  
    4567        - v = u^2f/(3f-2) 
    4668        - u = <R_g^2>q^2, where <R_g^2> is the ensemble average radius of 
    47         gyration squared of an arm 
     69        gyration squared of the entire polymer 
    4870        - f is the number of arms on the star 
     71        - the radius of gyration of an arm is given b 
     72        Rg_arm^2 = R_g^2 * f/(3f-2) 
    4973        """ 
    5074category = "shape-independent" 
    … …  
    5276# pylint: disable=bad-whitespace, line-too-long 
    5377#             ["name", "units", default, [lower, upper], "type","description"], 
    54 parameters = [["rg_squared", "Ang^2", 100.0, [0.0, inf], "", "Ensemble radius of gyration SQUARED of an arm"], 
     78parameters = [["rg_squared", "Ang^2", 100.0, [0.0, inf], "", "Ensemble radius of gyration SQUARED of the full polymer"], 
    5579              ["arms",    "",      3,   [1.0, 6.0], "", "Number of arms in the model"], 
    5680             ] 
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