Changeset ba2ed54 in sasmodels for doc


Ignore:
Timestamp:
Aug 17, 2017 9:23:31 AM (7 years ago)
Author:
GitHub <noreply@…>
Branches:
master, core_shell_microgels, costrafo411, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
Children:
7a3f840
Parents:
b419c2d (diff), f8a2baa (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.
git-author:
Paul Kienzle <pkienzle@…> (08/17/17 09:23:31)
git-committer:
GitHub <noreply@…> (08/17/17 09:23:31)
Message:

Merge pull request #44 from SasView?/doc_update

806: move plugin, resolution, magnetism and polydispersity docs to sasmodels

Location:
doc
Files:
13 added
5 deleted
7 edited
8 moved

Legend:

Unmodified
Added
Removed
  • 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  
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