source: sasmodels/sasmodels/generate.py @ 0a4628d

core_shell_microgelscostrafo411magnetic_modelrelease_v0.94release_v0.95ticket-1257-vesicle-productticket_1156ticket_1265_superballticket_822_more_unit_tests
Last change on this file since 0a4628d was 0a4628d, checked in by wojciech, 8 years ago

Scale and background paramters frozen in line model

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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"""
196from __future__ import print_function
197
198# TODO: identify model files which have changed since loading and reload them.
199
200import sys
201from os.path import abspath, dirname, join as joinpath, exists, basename, \
202    splitext
203import re
204import string
205
206import numpy as np
207
208__all__ = ["make", "doc", "sources", "convert_type"]
209
210C_KERNEL_TEMPLATE_PATH = joinpath(dirname(__file__), 'kernel_template.c')
211
212F16 = np.dtype('float16')
213F32 = np.dtype('float32')
214F64 = np.dtype('float64')
215try:  # CRUFT: older numpy does not support float128
216    F128 = np.dtype('float128')
217except TypeError:
218    F128 = None
219
220# Scale and background, which are parameters common to every form factor
221COMMON_PARAMETERS = [
222    ["scale", "", 1, [0, np.inf], "", "Source intensity"],
223    ["background", "1/cm", 0, [0, np.inf], "", "Source background"],
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    "Ang/cm": "|Ang*cm^-1|",
236    "": "None",
237    }
238
239# Headers for the parameters tables in th sphinx documentation
240PARTABLE_HEADERS = [
241    "Parameter",
242    "Description",
243    "Units",
244    "Default value",
245    ]
246
247# Minimum width for a default value (this is shorter than the column header
248# width, so will be ignored).
249PARTABLE_VALUE_WIDTH = 10
250
251# Documentation header for the module, giving the model name, its short
252# description and its parameter table.  The remainder of the doc comes
253# from the module docstring.
254DOC_HEADER = """.. _%(id)s:
255
256%(name)s
257=======================================================
258
259%(title)s
260
261%(parameters)s
262
263%(returns)s
264
265%(docs)s
266"""
267
268def format_units(units):
269    """
270    Convert units into ReStructured Text format.
271    """
272    return "string" if isinstance(units, list) else RST_UNITS.get(units, units)
273
274def make_partable(pars):
275    """
276    Generate the parameter table to include in the sphinx documentation.
277    """
278    column_widths = [
279        max(len(p[0]) for p in pars),
280        max(len(p[-1]) for p in pars),
281        max(len(format_units(p[1])) for p in pars),
282        PARTABLE_VALUE_WIDTH,
283        ]
284    column_widths = [max(w, len(h))
285                     for w, h in zip(column_widths, PARTABLE_HEADERS)]
286
287    sep = " ".join("="*w for w in column_widths)
288    lines = [
289        sep,
290        " ".join("%-*s" % (w, h)
291                 for w, h in zip(column_widths, PARTABLE_HEADERS)),
292        sep,
293        ]
294    for p in pars:
295        lines.append(" ".join([
296            "%-*s" % (column_widths[0], p[0]),
297            "%-*s" % (column_widths[1], p[-1]),
298            "%-*s" % (column_widths[2], format_units(p[1])),
299            "%*g" % (column_widths[3], p[2]),
300            ]))
301    lines.append(sep)
302    return "\n".join(lines)
303
304def _search(search_path, filename):
305    """
306    Find *filename* in *search_path*.
307
308    Raises ValueError if file does not exist.
309    """
310    for path in search_path:
311        target = joinpath(path, filename)
312        if exists(target):
313            return target
314    raise ValueError("%r not found in %s" % (filename, search_path))
315
316def model_sources(info):
317    """
318    Return a list of the sources file paths for the module.
319    """
320    search_path = [dirname(info['filename']),
321                   abspath(joinpath(dirname(__file__), 'models'))]
322    return [_search(search_path, f) for f in info['source']]
323
324# Pragmas for enable OpenCL features.  Be sure to protect them so that they
325# still compile even if OpenCL is not present.
326_F16_PRAGMA = """\
327#if defined(__OPENCL_VERSION__) && !defined(cl_khr_fp16)
328#  pragma OPENCL EXTENSION cl_khr_fp16: enable
329#endif
330"""
331
332_F64_PRAGMA = """\
333#if defined(__OPENCL_VERSION__) && !defined(cl_khr_fp64)
334#  pragma OPENCL EXTENSION cl_khr_fp64: enable
335#endif
336"""
337
338def convert_type(source, dtype):
339    """
340    Convert code from double precision to the desired type.
341
342    Floating point constants are tagged with 'f' for single precision or 'L'
343    for long double precision.
344    """
345    if dtype == F16:
346        source = _F16_PRAGMA + _convert_type(source, "half", "f")
347    elif dtype == F32:
348        source = _convert_type(source, "float", "f")
349    elif dtype == F64:
350        source = _F64_PRAGMA + source  # Source is already double
351    elif dtype == F128:
352        source = _convert_type(source, "long double", "L")
353    else:
354        raise ValueError("Unexpected dtype in source conversion: %s"%dtype)
355    return source
356
357
358def _convert_type(source, type_name, constant_flag):
359    """
360    Replace 'double' with *type_name* in *source*, tagging floating point
361    constants with *constant_flag*.
362    """
363    # Convert double keyword to float/long double/half.
364    # Accept an 'n' # parameter for vector # values, where n is 2, 4, 8 or 16.
365    # Assume complex numbers are represented as cdouble which is typedef'd
366    # to double2.
367    source = re.sub(r'(^|[^a-zA-Z0-9_]c?)double(([248]|16)?($|[^a-zA-Z0-9_]))',
368                    r'\1%s\2'%type_name, source)
369    # Convert floating point constants to single by adding 'f' to the end,
370    # or long double with an 'L' suffix.  OS/X complains if you don't do this.
371    source = re.sub(r'[^a-zA-Z_](\d*[.]\d+|\d+[.]\d*)([eE][+-]?\d+)?',
372                    r'\g<0>%s'%constant_flag, source)
373    return source
374
375
376def kernel_name(info, is_2d):
377    """
378    Name of the exported kernel symbol.
379    """
380    return info['name'] + "_" + ("Iqxy" if is_2d else "Iq")
381
382
383def categorize_parameters(pars):
384    """
385    Build parameter categories out of the the parameter definitions.
386
387    Returns a dictionary of categories.
388    """
389    partype = {
390        'volume': [], 'orientation': [], 'magnetic': [], '': [],
391        'fixed-1d': [], 'fixed-2d': [], 'pd-1d': [], 'pd-2d': [],
392        'pd-rel': set(),
393    }
394
395    for p in pars:
396        name, ptype = p[0], p[4]
397        if ptype == 'volume':
398            partype['pd-1d'].append(name)
399            partype['pd-2d'].append(name)
400            partype['pd-rel'].add(name)
401        elif ptype == 'magnetic':
402            partype['fixed-2d'].append(name)
403        elif ptype == 'orientation':
404            partype['pd-2d'].append(name)
405        elif ptype == '':
406            partype['fixed-1d'].append(name)
407            partype['fixed-2d'].append(name)
408        else:
409            raise ValueError("unknown parameter type %r" % ptype)
410        partype[ptype].append(name)
411
412    return partype
413
414def indent(s, depth):
415    """
416    Indent a string of text with *depth* additional spaces on each line.
417    """
418    spaces = " "*depth
419    sep = "\n" + spaces
420    return spaces + sep.join(s.split("\n"))
421
422
423LOOP_OPEN = """\
424for (int %(name)s_i=0; %(name)s_i < N%(name)s; %(name)s_i++) {
425  const double %(name)s = loops[2*(%(name)s_i%(offset)s)];
426  const double %(name)s_w = loops[2*(%(name)s_i%(offset)s)+1];\
427"""
428def build_polydispersity_loops(pd_pars):
429    """
430    Build polydispersity loops
431
432    Returns loop opening and loop closing
433    """
434    depth = 4
435    offset = ""
436    loop_head = []
437    loop_end = []
438    for name in pd_pars:
439        subst = {'name': name, 'offset': offset}
440        loop_head.append(indent(LOOP_OPEN % subst, depth))
441        loop_end.insert(0, (" "*depth) + "}")
442        offset += '+N' + name
443        depth += 2
444    return "\n".join(loop_head), "\n".join(loop_end)
445
446C_KERNEL_TEMPLATE = None
447def make_model(info):
448    """
449    Generate the code for the kernel defined by info, using source files
450    found in the given search path.
451    """
452    # TODO: need something other than volume to indicate dispersion parameters
453    # No volume normalization despite having a volume parameter.
454    # Thickness is labelled a volume in order to trigger polydispersity.
455    # May want a separate dispersion flag, or perhaps a separate category for
456    # disperse, but not volume.  Volume parameters also use relative values
457    # for the distribution rather than the absolute values used by angular
458    # dispersion.  Need to be careful that necessary parameters are available
459    # for computing volume even if we allow non-disperse volume parameters.
460
461    # Load template
462    global C_KERNEL_TEMPLATE
463    if C_KERNEL_TEMPLATE is None:
464        with open(C_KERNEL_TEMPLATE_PATH) as fid:
465            C_KERNEL_TEMPLATE = fid.read()
466
467    # Load additional sources
468    source = [open(f).read() for f in model_sources(info)]
469
470    # Prepare defines
471    defines = []
472    partype = info['partype']
473    pd_1d = partype['pd-1d']
474    pd_2d = partype['pd-2d']
475    fixed_1d = partype['fixed-1d']
476    fixed_2d = partype['fixed-1d']
477
478    iq_parameters = [p[0]
479                     for p in info['parameters'][2:] # skip scale, background
480                     if p[0] in set(fixed_1d + pd_1d)]
481    iqxy_parameters = [p[0]
482                       for p in info['parameters'][2:] # skip scale, background
483                       if p[0] in set(fixed_2d + pd_2d)]
484    volume_parameters = [p[0]
485                         for p in info['parameters']
486                         if p[4] == 'volume']
487
488    # Fill in defintions for volume parameters
489    if volume_parameters:
490        defines.append(('VOLUME_PARAMETERS',
491                        ','.join(volume_parameters)))
492        defines.append(('VOLUME_WEIGHT_PRODUCT',
493                        '*'.join(p + '_w' for p in volume_parameters)))
494
495    # Generate form_volume function from body only
496    if info['form_volume'] is not None:
497        if volume_parameters:
498            vol_par_decl = ', '.join('double ' + p for p in volume_parameters)
499        else:
500            vol_par_decl = 'void'
501        defines.append(('VOLUME_PARAMETER_DECLARATIONS',
502                        vol_par_decl))
503        fn = """\
504double form_volume(VOLUME_PARAMETER_DECLARATIONS);
505double form_volume(VOLUME_PARAMETER_DECLARATIONS) {
506    %(body)s
507}
508""" % {'body':info['form_volume']}
509        source.append(fn)
510
511    # Fill in definitions for Iq parameters
512    defines.append(('IQ_KERNEL_NAME', info['name'] + '_Iq'))
513    defines.append(('IQ_PARAMETERS', ', '.join(iq_parameters)))
514    if fixed_1d:
515        defines.append(('IQ_FIXED_PARAMETER_DECLARATIONS',
516                        ', \\\n    '.join('const double %s' % p for p in fixed_1d)))
517    if pd_1d:
518        defines.append(('IQ_WEIGHT_PRODUCT',
519                        '*'.join(p + '_w' for p in pd_1d)))
520        defines.append(('IQ_DISPERSION_LENGTH_DECLARATIONS',
521                        ', \\\n    '.join('const int N%s' % p for p in pd_1d)))
522        defines.append(('IQ_DISPERSION_LENGTH_SUM',
523                        '+'.join('N' + p for p in pd_1d)))
524        open_loops, close_loops = build_polydispersity_loops(pd_1d)
525        defines.append(('IQ_OPEN_LOOPS',
526                        open_loops.replace('\n', ' \\\n')))
527        defines.append(('IQ_CLOSE_LOOPS',
528                        close_loops.replace('\n', ' \\\n')))
529    if info['Iq'] is not None:
530        defines.append(('IQ_PARAMETER_DECLARATIONS',
531                        ', '.join('double ' + p for p in iq_parameters)))
532        fn = """\
533double Iq(double q, IQ_PARAMETER_DECLARATIONS);
534double Iq(double q, IQ_PARAMETER_DECLARATIONS) {
535    %(body)s
536}
537""" % {'body':info['Iq']}
538        source.append(fn)
539
540    # Fill in definitions for Iqxy parameters
541    defines.append(('IQXY_KERNEL_NAME', info['name'] + '_Iqxy'))
542    defines.append(('IQXY_PARAMETERS', ', '.join(iqxy_parameters)))
543    if fixed_2d:
544        defines.append(('IQXY_FIXED_PARAMETER_DECLARATIONS',
545                        ', \\\n    '.join('const double %s' % p for p in fixed_2d)))
546    if pd_2d:
547        defines.append(('IQXY_WEIGHT_PRODUCT',
548                        '*'.join(p + '_w' for p in pd_2d)))
549        defines.append(('IQXY_DISPERSION_LENGTH_DECLARATIONS',
550                        ', \\\n    '.join('const int N%s' % p for p in pd_2d)))
551        defines.append(('IQXY_DISPERSION_LENGTH_SUM',
552                        '+'.join('N' + p for p in pd_2d)))
553        open_loops, close_loops = build_polydispersity_loops(pd_2d)
554        defines.append(('IQXY_OPEN_LOOPS',
555                        open_loops.replace('\n', ' \\\n')))
556        defines.append(('IQXY_CLOSE_LOOPS',
557                        close_loops.replace('\n', ' \\\n')))
558    if info['Iqxy'] is not None:
559        defines.append(('IQXY_PARAMETER_DECLARATIONS',
560                        ', '.join('double ' + p for p in iqxy_parameters)))
561        fn = """\
562double Iqxy(double qx, double qy, IQXY_PARAMETER_DECLARATIONS);
563double Iqxy(double qx, double qy, IQXY_PARAMETER_DECLARATIONS) {
564    %(body)s
565}
566""" % {'body':info['Iqxy']}
567        source.append(fn)
568
569    # Need to know if we have a theta parameter for Iqxy; it is not there
570    # for the magnetic sphere model, for example, which has a magnetic
571    # orientation but no shape orientation.
572    if 'theta' in pd_2d:
573        defines.append(('IQXY_HAS_THETA', '1'))
574
575    #for d in defines: print(d)
576    defines = '\n'.join('#define %s %s' % (k, v) for k, v in defines)
577    sources = '\n\n'.join(source)
578    return C_KERNEL_TEMPLATE % {
579        'DEFINES': defines,
580        'SOURCES': sources,
581        }
582
583def make_info(kernel_module):
584    """
585    Interpret the model definition file, categorizing the parameters.
586    """
587    #print(kernelfile)
588    category = getattr(kernel_module, 'category', None)
589    parameters = COMMON_PARAMETERS + kernel_module.parameters
590    # Default the demo parameters to the starting values for the individual
591    # parameters if an explicit demo parameter set has not been specified.
592    demo_parameters = getattr(kernel_module, 'demo', None)
593    if demo_parameters is None:
594        demo_parameters = dict((p[0], p[2]) for p in parameters)
595    filename = abspath(kernel_module.__file__)
596    kernel_id = splitext(basename(filename))[0]
597    name = getattr(kernel_module, 'name', None)
598    if name is None:
599        name = " ".join(w.capitalize() for w in kernel_id.split('_'))
600    info = dict(
601        id=kernel_id,  # string used to load the kernel
602        filename=abspath(kernel_module.__file__),
603        name=name,
604        title=kernel_module.title,
605        description=kernel_module.description,
606        category=category,
607        parameters=parameters,
608        demo=demo_parameters,
609        source=getattr(kernel_module, 'source', []),
610        oldname=kernel_module.oldname,
611        oldpars=kernel_module.oldpars,
612        )
613    # Fill in attributes which default to None
614    info.update((k, getattr(kernel_module, k, None))
615                for k in ('ER', 'VR', 'form_volume', 'Iq', 'Iqxy'))
616    # Fill in the derived attributes
617    info['limits'] = dict((p[0], p[3]) for p in info['parameters'])
618    info['partype'] = categorize_parameters(info['parameters'])
619    info['defaults'] = dict((p[0], p[2]) for p in info['parameters'])
620    return info
621
622def make(kernel_module):
623    """
624    Build an OpenCL/ctypes function from the definition in *kernel_module*.
625
626    The module can be loaded with a normal python import statement if you
627    know which module you need, or with __import__('sasmodels.model.'+name)
628    if the name is in a string.
629    """
630    info = make_info(kernel_module)
631    # Assume if one part of the kernel is python then all parts are.
632    source = make_model(info) if not callable(info['Iq']) else None
633    return source, info
634
635section_marker = re.compile(r'\A(?P<first>[%s])(?P=first)*\Z'
636                            %re.escape(string.punctuation))
637def _convert_section_titles_to_boldface(lines):
638    """
639    Do the actual work of identifying and converting section headings.
640    """
641    prior = None
642    for line in lines:
643        if prior is None:
644            prior = line
645        elif section_marker.match(line):
646            if len(line) >= len(prior):
647                yield "".join(("**", prior, "**"))
648                prior = None
649            else:
650                yield prior
651                prior = line
652        else:
653            yield prior
654            prior = line
655    if prior is not None:
656        yield prior
657
658def convert_section_titles_to_boldface(s):
659    """
660    Use explicit bold-face rather than section headings so that the table of
661    contents is not polluted with section names from the model documentation.
662
663    Sections are identified as the title line followed by a line of punctuation
664    at least as long as the title line.
665    """
666    return "\n".join(_convert_section_titles_to_boldface(s.split('\n')))
667
668def doc(kernel_module):
669    """
670    Return the documentation for the model.
671    """
672    Iq_units = "The returned value is scaled to units of |cm^-1| |sr^-1|, absolute scale."
673    Sq_units = "The returned value is a dimensionless structure factor, $S(q)$."
674    info = make_info(kernel_module)
675    is_Sq = ("structure-factor" in info['category'])
676    #docs = kernel_module.__doc__
677    docs = convert_section_titles_to_boldface(kernel_module.__doc__)
678    subst = dict(id=info['id'].replace('_', '-'),
679                 name=info['name'],
680                 title=info['title'],
681                 parameters=make_partable(info['parameters']),
682                 returns=Sq_units if is_Sq else Iq_units,
683                 docs=docs)
684    return DOC_HEADER % subst
685
686
687
688def demo_time():
689    """
690    Show how long it takes to process a model.
691    """
692    from .models import cylinder
693    import datetime
694    tic = datetime.datetime.now()
695    make(cylinder)
696    toc = (datetime.datetime.now() - tic).total_seconds()
697    print("time: %g"%toc)
698
699def main():
700    """
701    Program which prints the source produced by the model.
702    """
703    if len(sys.argv) <= 1:
704        print("usage: python -m sasmodels.generate modelname")
705    else:
706        name = sys.argv[1]
707        import sasmodels.models
708        __import__('sasmodels.models.' + name)
709        model = getattr(sasmodels.models, name)
710        source, _ = make(model)
711        print(source)
712
713if __name__ == "__main__":
714    main()
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