source: sasmodels/sasmodels/generate.py @ 5d316e9

core_shell_microgelscostrafo411magnetic_modelrelease_v0.94release_v0.95ticket-1257-vesicle-productticket_1156ticket_1265_superballticket_822_more_unit_tests
Last change on this file since 5d316e9 was 5d316e9, checked in by Paul Kienzle <pkienzle@…>, 7 years ago

support fast and loose single precision and half precision

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1"""
2SAS model constructor.
3
4Small angle scattering models are defined by a set of kernel functions:
5
6    *Iq(q, p1, p2, ...)* returns the scattering at q for a form with
7    particular dimensions averaged over all orientations.
8
9    *Iqxy(qx, qy, p1, p2, ...)* returns the scattering at qx,qy for a form
10    with particular dimensions for a single orientation.
11
12    *Imagnetic(qx, qy, result[], p1, p2, ...)* returns the scattering for the
13    polarized neutron spin states (up-up, up-down, down-up, down-down) for
14    a form with particular dimensions for a single orientation.
15
16    *form_volume(p1, p2, ...)* returns the volume of the form with particular
17    dimension.
18
19    *ER(p1, p2, ...)* returns the effective radius of the form with
20    particular dimensions.
21
22    *VR(p1, p2, ...)* returns the volume ratio for core-shell style forms.
23
24These functions are defined in a kernel module .py script and an associated
25set of .c files.  The model constructor will use them to create models with
26polydispersity across volume and orientation parameters, and provide
27scale and background parameters for each model.
28
29*Iq*, *Iqxy*, *Imagnetic* and *form_volume* should be stylized C-99
30functions written for OpenCL.  All functions need prototype declarations
31even if the are defined before they are used.  OpenCL does not support
32*#include* preprocessor directives, so instead the list of includes needs
33to be given as part of the metadata in the kernel module definition.
34The included files should be listed using a path relative to the kernel
35module, or if using "lib/file.c" if it is one of the standard includes
36provided with the sasmodels source.  The includes need to be listed in
37order so that functions are defined before they are used.
38
39Floating point values should be declared as *double*.  For single precision
40calculations, *double* will be replaced by *float*.  The single precision
41conversion will also tag floating point constants with "f" to make them
42single precision constants.  When using integral values in floating point
43expressions, they should be expressed as floating point values by including
44a decimal point.  This includes 0., 1. and 2.
45
46OpenCL has a *sincos* function which can improve performance when both
47the *sin* and *cos* values are needed for a particular argument.  Since
48this function does not exist in C99, all use of *sincos* should be
49replaced by the macro *SINCOS(value,sn,cn)* where *sn* and *cn* are
50previously declared *double* variables.  When compiled for systems without
51OpenCL, *SINCOS* will be replaced by *sin* and *cos* calls.   If *value* is
52an expression, it will appear twice in this case; whether or not it will be
53evaluated twice depends on the quality of the compiler.
54
55If the input parameters are invalid, the scattering calculator should
56return a negative number. Particularly with polydispersity, there are
57some sets of shape parameters which lead to nonsensical forms, such
58as a capped cylinder where the cap radius is smaller than the
59cylinder radius.  The polydispersity calculation will ignore these points,
60effectively chopping the parameter weight distributions at the boundary
61of the infeasible region.  The resulting scattering will be set to
62background.  This will work correctly even when polydispersity is off.
63
64*ER* and *VR* are python functions which operate on parameter vectors.
65The constructor code will generate the necessary vectors for computing
66them with the desired polydispersity.
67
68The available kernel parameters are defined as a list, with each parameter
69defined as a sublist with the following elements:
70
71    *name* is the name that will be used in the call to the kernel
72    function and the name that will be displayed to the user.  Names
73    should be lower case, with words separated by underscore.  If
74    acronyms are used, the whole acronym should be upper case.
75
76    *units* should be one of *degrees* for angles, *Ang* for lengths,
77    *1e-6/Ang^2* for SLDs.
78
79    *default value* will be the initial value for  the model when it
80    is selected, or when an initial value is not otherwise specified.
81
82    [*lb*, *ub*] are the hard limits on the parameter value, used to limit
83    the polydispersity density function.  In the fit, the parameter limits
84    given to the fit are the limits  on the central value of the parameter.
85    If there is polydispersity, it will evaluate parameter values outside
86    the fit limits, but not outside the hard limits specified in the model.
87    If there are no limits, use +/-inf imported from numpy.
88
89    *type* indicates how the parameter will be used.  "volume" parameters
90    will be used in all functions.  "orientation" parameters will be used
91    in *Iqxy* and *Imagnetic*.  "magnetic* parameters will be used in
92    *Imagnetic* only.  If *type* is the empty string, the parameter will
93    be used in all of *Iq*, *Iqxy* and *Imagnetic*.
94
95    *description* is a short description of the parameter.  This will
96    be displayed in the parameter table and used as a tool tip for the
97    parameter value in the user interface.
98
99The kernel module must set variables defining the kernel meta data:
100
101    *id* is an implicit variable formed from the filename.  It will be
102    a valid python identifier, and will be used as the reference into
103    the html documentation, with '_' replaced by '-'.
104
105    *name* is the model name as displayed to the user.  If it is missing,
106    it will be constructed from the id.
107
108    *title* is a short description of the model, suitable for a tool tip,
109    or a one line model summary in a table of models.
110
111    *description* is an extended description of the model to be displayed
112    while the model parameters are being edited.
113
114    *parameters* is the list of parameters.  Parameters in the kernel
115    functions must appear in the same order as they appear in the
116    parameters list.  Two additional parameters, *scale* and *background*
117    are added to the beginning of the parameter list.  They will show up
118    in the documentation as model parameters, but they are never sent to
119    the kernel functions.
120
121    *category* is the default category for the model.  Models in the
122    *structure-factor* category do not have *scale* and *background*
123    added.
124
125    *source* is the list of C-99 source files that must be joined to
126    create the OpenCL kernel functions.  The files defining the functions
127    need to be listed before the files which use the functions.
128
129    *ER* is a python function defining the effective radius.  If it is
130    not present, the effective radius is 0.
131
132    *VR* is a python function defining the volume ratio.  If it is not
133    present, the volume ratio is 1.
134
135    *form_volume*, *Iq*, *Iqxy*, *Imagnetic* are strings containing the
136    C source code for the body of the volume, Iq, and Iqxy functions
137    respectively.  These can also be defined in the last source file.
138
139    *Iq* and *Iqxy* also be instead be python functions defining the
140    kernel.  If they are marked as *Iq.vectorized = True* then the
141    kernel is passed the entire *q* vector at once, otherwise it is
142    passed values one *q* at a time.  The performance improvement of
143    this step is significant.
144
145    *demo* is a dictionary of parameter=value defining a set of
146    parameters to use by default when *compare* is called.  Any
147    parameter not set in *demo* gets the initial value from the
148    parameter list.  *demo* is mostly needed to set the default
149    polydispersity values for tests.
150
151    *oldname* is the name of the model in sasview before sasmodels
152    was split into its own package, and *oldpars* is a dictionary
153    of *parameter: old_parameter* pairs defining the new names for
154    the parameters.  This is used by *compare* to check the values
155    of the new model against the values of the old model before
156    you are ready to add the new model to sasmodels.
157
158
159An *info* dictionary is constructed from the kernel meta data and
160returned to the caller.
161
162The model evaluator, function call sequence consists of q inputs and the return vector,
163followed by the loop value/weight vector, followed by the values for
164the non-polydisperse parameters, followed by the lengths of the
165polydispersity loops.  To construct the call for 1D models, the
166categories *fixed-1d* and *pd-1d* list the names of the parameters
167of the non-polydisperse and the polydisperse parameters respectively.
168Similarly, *fixed-2d* and *pd-2d* provide parameter names for 2D models.
169The *pd-rel* category is a set of those parameters which give
170polydispersitiy as a portion of the value (so a 10% length dispersity
171would use a polydispersity value of 0.1) rather than absolute
172dispersity such as an angle plus or minus 15 degrees.
173
174The *volume* category lists the volume parameters in order for calls
175to volume within the kernel (used for volume normalization) and for
176calls to ER and VR for effective radius and volume ratio respectively.
177
178The *orientation* and *magnetic* categories list the orientation and
179magnetic parameters.  These are used by the sasview interface.  The
180blank category is for parameters such as scale which don't have any
181other marking.
182
183The doc string at the start of the kernel module will be used to
184construct the model documentation web pages.  Embedded figures should
185appear in the subdirectory "img" beside the model definition, and tagged
186with the kernel module name to avoid collision with other models.  Some
187file systems are case-sensitive, so only use lower case characters for
188file names and extensions.
189
190
191The function :func:`make` loads the metadata from the module and returns
192the kernel source.  The function :func:`doc` extracts the doc string
193and adds the parameter table to the top.  The function :func:`sources`
194returns a list of files required by the model.
195"""
196
197# TODO: identify model files which have changed since loading and reload them.
198
199__all__ = ["make", "doc", "sources", "convert_type"]
200
201import sys
202from os.path import abspath, dirname, join as joinpath, exists, basename, \
203    splitext
204import re
205import string
206
207import numpy as np
208C_KERNEL_TEMPLATE_PATH = joinpath(dirname(__file__), 'kernel_template.c')
209
210F16 = np.dtype('float16')
211F32 = np.dtype('float32')
212F64 = np.dtype('float64')
213try:  # CRUFT: older numpy does not support float128
214    F128 = np.dtype('float128')
215except TypeError:
216    F128 = None
217
218
219# Scale and background, which are parameters common to every form factor
220COMMON_PARAMETERS = [
221    ["scale", "", 1, [0, np.inf], "", "Source intensity"],
222    ["background", "1/cm", 0, [0, np.inf], "", "Source background"],
223    ]
224
225
226# Conversion from units defined in the parameter table for each model
227# to units displayed in the sphinx documentation.
228RST_UNITS = {
229    "Ang": "|Ang|",
230    "1/Ang": "|Ang^-1|",
231    "1/Ang^2": "|Ang^-2|",
232    "1e-6/Ang^2": "|1e-6Ang^-2|",
233    "degrees": "degree",
234    "1/cm": "|cm^-1|",
235    "": "None",
236    }
237
238# Headers for the parameters tables in th sphinx documentation
239PARTABLE_HEADERS = [
240    "Parameter",
241    "Description",
242    "Units",
243    "Default value",
244    ]
245
246# Minimum width for a default value (this is shorter than the column header
247# width, so will be ignored).
248PARTABLE_VALUE_WIDTH = 10
249
250# Documentation header for the module, giving the model name, its short
251# description and its parameter table.  The remainder of the doc comes
252# from the module docstring.
253DOC_HEADER = """.. _%(id)s:
254
255%(name)s
256=======================================================
257
258%(title)s
259
260%(parameters)s
261
262%(returns)s
263
264%(docs)s
265"""
266
267def format_units(par):
268    return RST_UNITS.get(par, par)
269
270def make_partable(pars):
271    """
272    Generate the parameter table to include in the sphinx documentation.
273    """
274    column_widths = [
275        max(len(p[0]) for p in pars),
276        max(len(p[-1]) for p in pars),
277        max(len(format_units(p[1])) for p in pars),
278        PARTABLE_VALUE_WIDTH,
279        ]
280    column_widths = [max(w, len(h))
281                     for w, h in zip(column_widths, PARTABLE_HEADERS)]
282
283    sep = " ".join("="*w for w in column_widths)
284    lines = [
285        sep,
286        " ".join("%-*s" % (w, h) for w, h in zip(column_widths, PARTABLE_HEADERS)),
287        sep,
288        ]
289    for p in pars:
290        lines.append(" ".join([
291            "%-*s" % (column_widths[0], p[0]),
292            "%-*s" % (column_widths[1], p[-1]),
293            "%-*s" % (column_widths[2], format_units(p[1])),
294            "%*g" % (column_widths[3], p[2]),
295            ]))
296    lines.append(sep)
297    return "\n".join(lines)
298
299def _search(search_path, filename):
300    """
301    Find *filename* in *search_path*.
302
303    Raises ValueError if file does not exist.
304    """
305    for path in search_path:
306        target = joinpath(path, filename)
307        if exists(target):
308            return target
309    raise ValueError("%r not found in %s" % (filename, search_path))
310
311def sources(info):
312    """
313    Return a list of the sources file paths for the module.
314    """
315    search_path = [dirname(info['filename']),
316                   abspath(joinpath(dirname(__file__), 'models'))]
317    return [_search(search_path, f) for f in info['source']]
318
319# Pragmas for enable OpenCL features.  Be sure to protect them so that they
320# still compile even if OpenCL is not present.
321_F16_PRAGMA = """\
322#ifdef cl_khr_fp16
323#  pragma OPENCL EXTENSION cl_khr_fp16: enable
324#endif
325"""
326
327_F64_PRAGMA = """\
328#ifdef cl_khr_fp64
329#  pragma OPENCL EXTENSION cl_khr_fp64: enable
330#endif
331"""
332
333def convert_type(source, dtype):
334    """
335    Convert code from double precision to the desired type.
336    """
337    if dtype == F16:
338        source = _F16_PRAGMA + _convert_type(source, "half", "f")
339    elif dtype == F32:
340        source = _convert_type(source, "float", "f")
341    elif dtype == F64:
342        source = _F64_PRAGMA + source  # Source is already double
343    elif dtype == F128:
344        source = _convert_type(source, "long double", "L")
345    else:
346        raise ValueError("Unexpected dtype in source conversion: %s"%dtype)
347    return source
348
349
350def _convert_type(source, type_name, constant_flag):
351    # Convert double keyword to float/long double/half.
352    # Accept an 'n' # parameter for vector # values, where n is 2, 4, 8 or 16.
353    # Assume complex numbers are represented as cdouble which is typedef'd
354    # to double2.
355    source = re.sub(r'(^|[^a-zA-Z0-9_]c?)double(([248]|16)?($|[^a-zA-Z0-9_]))',
356                    r'\1%s\2'%type_name, source)
357    # Convert floating point constants to single by adding 'f' to the end,
358    # or long double with an 'L' suffix.  OS/X complains if you don't do this.
359    source = re.sub(r'[^a-zA-Z_](\d*[.]\d+|\d+[.]\d*)([eE][+-]?\d+)?',
360                    r'\g<0>%s'%constant_flag, source)
361    return source
362
363
364def kernel_name(info, is_2D):
365    """
366    Name of the exported kernel symbol.
367    """
368    return info['name'] + "_" + ("Iqxy" if is_2D else "Iq")
369
370
371def categorize_parameters(pars):
372    """
373    Build parameter categories out of the the parameter definitions.
374
375    Returns a dictionary of categories.
376    """
377    partype = {
378        'volume': [], 'orientation': [], 'magnetic': [], '': [],
379        'fixed-1d': [], 'fixed-2d': [], 'pd-1d': [], 'pd-2d': [],
380        'pd-rel': set(),
381    }
382
383    for p in pars:
384        name, ptype = p[0], p[4]
385        if ptype == 'volume':
386            partype['pd-1d'].append(name)
387            partype['pd-2d'].append(name)
388            partype['pd-rel'].add(name)
389        elif ptype == 'magnetic':
390            partype['fixed-2d'].append(name)
391        elif ptype == 'orientation':
392            partype['pd-2d'].append(name)
393        elif ptype == '':
394            partype['fixed-1d'].append(name)
395            partype['fixed-2d'].append(name)
396        else:
397            raise ValueError("unknown parameter type %r" % ptype)
398        partype[ptype].append(name)
399
400    return partype
401
402def indent(s, depth):
403    """
404    Indent a string of text with *depth* additional spaces on each line.
405    """
406    spaces = " "*depth
407    sep = "\n" + spaces
408    return spaces + sep.join(s.split("\n"))
409
410
411def build_polydispersity_loops(pd_pars):
412    """
413    Build polydispersity loops
414
415    Returns loop opening and loop closing
416    """
417    LOOP_OPEN = """\
418for (int %(name)s_i=0; %(name)s_i < N%(name)s; %(name)s_i++) {
419  const double %(name)s = loops[2*(%(name)s_i%(offset)s)];
420  const double %(name)s_w = loops[2*(%(name)s_i%(offset)s)+1];\
421"""
422    depth = 4
423    offset = ""
424    loop_head = []
425    loop_end = []
426    for name in pd_pars:
427        subst = {'name': name, 'offset': offset}
428        loop_head.append(indent(LOOP_OPEN % subst, depth))
429        loop_end.insert(0, (" "*depth) + "}")
430        offset += '+N' + name
431        depth += 2
432    return "\n".join(loop_head), "\n".join(loop_end)
433
434C_KERNEL_TEMPLATE = None
435def make_model(info):
436    """
437    Generate the code for the kernel defined by info, using source files
438    found in the given search path.
439    """
440    # TODO: need something other than volume to indicate dispersion parameters
441    # No volume normalization despite having a volume parameter.
442    # Thickness is labelled a volume in order to trigger polydispersity.
443    # May want a separate dispersion flag, or perhaps a separate category for
444    # disperse, but not volume.  Volume parameters also use relative values
445    # for the distribution rather than the absolute values used by angular
446    # dispersion.  Need to be careful that necessary parameters are available
447    # for computing volume even if we allow non-disperse volume parameters.
448
449    # Load template
450    global C_KERNEL_TEMPLATE
451    if C_KERNEL_TEMPLATE is None:
452        with open(C_KERNEL_TEMPLATE_PATH) as fid:
453            C_KERNEL_TEMPLATE = fid.read()
454
455    # Load additional sources
456    source = [open(f).read() for f in sources(info)]
457
458    # Prepare defines
459    defines = []
460    partype = info['partype']
461    pd_1d = partype['pd-1d']
462    pd_2d = partype['pd-2d']
463    fixed_1d = partype['fixed-1d']
464    fixed_2d = partype['fixed-1d']
465
466    iq_parameters = [p[0]
467                     for p in info['parameters'][2:] # skip scale, background
468                     if p[0] in set(fixed_1d + pd_1d)]
469    iqxy_parameters = [p[0]
470                       for p in info['parameters'][2:] # skip scale, background
471                       if p[0] in set(fixed_2d + pd_2d)]
472    volume_parameters = [p[0]
473                         for p in info['parameters']
474                         if p[4] == 'volume']
475
476    # Fill in defintions for volume parameters
477    if volume_parameters:
478        defines.append(('VOLUME_PARAMETERS',
479                        ','.join(volume_parameters)))
480        defines.append(('VOLUME_WEIGHT_PRODUCT',
481                        '*'.join(p + '_w' for p in volume_parameters)))
482
483    # Generate form_volume function from body only
484    if info['form_volume'] is not None:
485        if volume_parameters:
486            vol_par_decl = ', '.join('double ' + p for p in volume_parameters)
487        else:
488            vol_par_decl = 'void'
489        defines.append(('VOLUME_PARAMETER_DECLARATIONS',
490                        vol_par_decl))
491        fn = """\
492double form_volume(VOLUME_PARAMETER_DECLARATIONS);
493double form_volume(VOLUME_PARAMETER_DECLARATIONS) {
494    %(body)s
495}
496""" % {'body':info['form_volume']}
497        source.append(fn)
498
499    # Fill in definitions for Iq parameters
500    defines.append(('IQ_KERNEL_NAME', info['name'] + '_Iq'))
501    defines.append(('IQ_PARAMETERS', ', '.join(iq_parameters)))
502    if fixed_1d:
503        defines.append(('IQ_FIXED_PARAMETER_DECLARATIONS',
504                        ', \\\n    '.join('const double %s' % p for p in fixed_1d)))
505    if pd_1d:
506        defines.append(('IQ_WEIGHT_PRODUCT',
507                        '*'.join(p + '_w' for p in pd_1d)))
508        defines.append(('IQ_DISPERSION_LENGTH_DECLARATIONS',
509                        ', \\\n    '.join('const int N%s' % p for p in pd_1d)))
510        defines.append(('IQ_DISPERSION_LENGTH_SUM',
511                        '+'.join('N' + p for p in pd_1d)))
512        open_loops, close_loops = build_polydispersity_loops(pd_1d)
513        defines.append(('IQ_OPEN_LOOPS',
514                        open_loops.replace('\n', ' \\\n')))
515        defines.append(('IQ_CLOSE_LOOPS',
516                        close_loops.replace('\n', ' \\\n')))
517    if info['Iq'] is not None:
518        defines.append(('IQ_PARAMETER_DECLARATIONS',
519                        ', '.join('double ' + p for p in iq_parameters)))
520        fn = """\
521double Iq(double q, IQ_PARAMETER_DECLARATIONS);
522double Iq(double q, IQ_PARAMETER_DECLARATIONS) {
523    %(body)s
524}
525""" % {'body':info['Iq']}
526        source.append(fn)
527
528    # Fill in definitions for Iqxy parameters
529    defines.append(('IQXY_KERNEL_NAME', info['name'] + '_Iqxy'))
530    defines.append(('IQXY_PARAMETERS', ', '.join(iqxy_parameters)))
531    if fixed_2d:
532        defines.append(('IQXY_FIXED_PARAMETER_DECLARATIONS',
533                        ', \\\n    '.join('const double %s' % p for p in fixed_2d)))
534    if pd_2d:
535        defines.append(('IQXY_WEIGHT_PRODUCT',
536                        '*'.join(p + '_w' for p in pd_2d)))
537        defines.append(('IQXY_DISPERSION_LENGTH_DECLARATIONS',
538                        ', \\\n    '.join('const int N%s' % p for p in pd_2d)))
539        defines.append(('IQXY_DISPERSION_LENGTH_SUM',
540                        '+'.join('N' + p for p in pd_2d)))
541        open_loops, close_loops = build_polydispersity_loops(pd_2d)
542        defines.append(('IQXY_OPEN_LOOPS',
543                        open_loops.replace('\n', ' \\\n')))
544        defines.append(('IQXY_CLOSE_LOOPS',
545                        close_loops.replace('\n', ' \\\n')))
546    if info['Iqxy'] is not None:
547        defines.append(('IQXY_PARAMETER_DECLARATIONS',
548                        ', '.join('double ' + p for p in iqxy_parameters)))
549        fn = """\
550double Iqxy(double qx, double qy, IQXY_PARAMETER_DECLARATIONS);
551double Iqxy(double qx, double qy, IQXY_PARAMETER_DECLARATIONS) {
552    %(body)s
553}
554""" % {'body':info['Iqxy']}
555        source.append(fn)
556
557    # Need to know if we have a theta parameter for Iqxy; it is not there
558    # for the magnetic sphere model, for example, which has a magnetic
559    # orientation but no shape orientation.
560    if 'theta' in pd_2d:
561        defines.append(('IQXY_HAS_THETA', '1'))
562
563    #for d in defines: print(d)
564    DEFINES = '\n'.join('#define %s %s' % (k, v) for k, v in defines)
565    SOURCES = '\n\n'.join(source)
566    return C_KERNEL_TEMPLATE % {
567        'DEFINES':DEFINES,
568        'SOURCES':SOURCES,
569        }
570
571def make_info(kernel_module):
572    """
573    Interpret the model definition file, categorizing the parameters.
574    """
575    #print(kernelfile)
576    category = getattr(kernel_module, 'category', None)
577    parameters = COMMON_PARAMETERS + kernel_module.parameters
578    # Default the demo parameters to the starting values for the individual
579    # parameters if an explicit demo parameter set has not been specified.
580    demo_parameters = getattr(kernel_module, 'demo', None)
581    if demo_parameters is None:
582        demo_parameters = dict((p[0],p[2]) for p in parameters)
583    filename = abspath(kernel_module.__file__)
584    kernel_id = splitext(basename(filename))[0]
585    name = getattr(kernel_module, 'name', None)
586    if name is None:
587        name = " ".join(w.capitalize() for w in kernel_id.split('_'))
588    info = dict(
589        id = kernel_id,  # string used to load the kernel
590        filename=abspath(kernel_module.__file__),
591        name=name,
592        title=kernel_module.title,
593        description=kernel_module.description,
594        category=category,
595        parameters=parameters,
596        demo=demo_parameters,
597        source=getattr(kernel_module, 'source', []),
598        oldname=kernel_module.oldname,
599        oldpars=kernel_module.oldpars,
600        )
601    # Fill in attributes which default to None
602    info.update((k, getattr(kernel_module, k, None))
603                for k in ('ER', 'VR', 'form_volume', 'Iq', 'Iqxy'))
604    # Fill in the derived attributes
605    info['limits'] = dict((p[0], p[3]) for p in info['parameters'])
606    info['partype'] = categorize_parameters(info['parameters'])
607    info['defaults'] = dict((p[0], p[2]) for p in info['parameters'])
608    return info
609
610def make(kernel_module):
611    """
612    Build an OpenCL/ctypes function from the definition in *kernel_module*.
613
614    The module can be loaded with a normal python import statement if you
615    know which module you need, or with __import__('sasmodels.model.'+name)
616    if the name is in a string.
617    """
618    info = make_info(kernel_module)
619    # Assume if one part of the kernel is python then all parts are.
620    source = make_model(info) if not callable(info['Iq']) else None
621    return source, info
622
623section_marker = re.compile(r'\A(?P<first>[%s])(?P=first)*\Z'
624                            %re.escape(string.punctuation))
625def _convert_section_titles_to_boldface(lines):
626    prior = None
627    for line in lines:
628        if prior is None:
629            prior = line
630        elif section_marker.match(line):
631            if len(line) >= len(prior):
632                yield "".join( ("**",prior,"**") )
633                prior = None
634            else:
635                yield prior
636                prior = line
637        else:
638            yield prior
639            prior = line
640    if prior is not None:
641        yield prior
642
643def convert_section_titles_to_boldface(string):
644    return "\n".join(_convert_section_titles_to_boldface(string.split('\n')))
645
646def doc(kernel_module):
647    """
648    Return the documentation for the model.
649    """
650    Iq_units = "The returned value is scaled to units of |cm^-1| |sr^-1|, absolute scale."
651    Sq_units = "The returned value is a dimensionless structure factor, $S(q)$."
652    info = make_info(kernel_module)
653    is_Sq = ("structure-factor" in info['category'])
654    #docs = kernel_module.__doc__
655    docs = convert_section_titles_to_boldface(kernel_module.__doc__)
656    subst = dict(id=info['id'].replace('_', '-'),
657                 name=info['name'],
658                 title=info['title'],
659                 parameters=make_partable(info['parameters']),
660                 returns=Sq_units if is_Sq else Iq_units,
661                 docs=docs)
662    return DOC_HEADER % subst
663
664
665
666def demo_time():
667    from .models import cylinder
668    import datetime
669    tic = datetime.datetime.now()
670    make(cylinder)
671    toc = (datetime.datetime.now() - tic).total_seconds()
672    print("time: %g"%toc)
673
674def main():
675    if len(sys.argv) <= 1:
676        print("usage: python -m sasmodels.generate modelname")
677    else:
678        name = sys.argv[1]
679        import sasmodels.models
680        __import__('sasmodels.models.' + name)
681        model = getattr(sasmodels.models, name)
682        source, _ = make(model)
683        print(source)
684
685if __name__ == "__main__":
686    main()
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