source: sasmodels/sasmodels/generate.py @ e1ace4d

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Last change on this file since e1ace4d was e1ace4d, checked in by Paul Kienzle <pkienzle@…>, 9 years ago

long doubles not supported in every version of numpy

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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", "use_single", "use_long_double"]
200
201import sys
202from os.path import abspath, dirname, join as joinpath, exists, basename
203import re
204
205import numpy as np
206C_KERNEL_TEMPLATE_PATH = joinpath(dirname(__file__), 'kernel_template.c')
207
208F32 = np.dtype('float32')
209F64 = np.dtype('float64')
210try:  # CRUFT: older numpy does not support float128
211    F128 = np.dtype('float128')
212except TypeError:
213    F128 = None
214
215
216# Scale and background, which are parameters common to every form factor
217COMMON_PARAMETERS = [
218    ["scale", "", 1, [0, np.inf], "", "Source intensity"],
219    ["background", "1/cm", 0, [0, np.inf], "", "Source background"],
220    ]
221
222
223# Conversion from units defined in the parameter table for each model
224# to units displayed in the sphinx documentation.
225RST_UNITS = {
226    "Ang": "|Ang|",
227    "1/Ang": "|Ang^-1|",
228    "1/Ang^2": "|Ang^-2|",
229    "1e-6/Ang^2": "|1e-6Ang^-2|",
230    "degrees": "degree",
231    "1/cm": "|cm^-1|",
232    "": "None",
233    }
234
235# Headers for the parameters tables in th sphinx documentation
236PARTABLE_HEADERS = [
237    "Parameter",
238    "Description",
239    "Units",
240    "Default value",
241    ]
242
243# Minimum width for a default value (this is shorter than the column header
244# width, so will be ignored).
245PARTABLE_VALUE_WIDTH = 10
246
247# Documentation header for the module, giving the model name, its short
248# description and its parameter table.  The remainder of the doc comes
249# from the module docstring.
250DOC_HEADER = """.. _%(id)s:
251
252%(name)s
253=======================================================
254
255%(title)s
256
257%(parameters)s
258
259The returned value is scaled to units of |cm^-1|.
260
261%(docs)s
262"""
263
264def format_units(par):
265    return RST_UNITS.get(par, par)
266
267def make_partable(pars):
268    """
269    Generate the parameter table to include in the sphinx documentation.
270    """
271    column_widths = [
272        max(len(p[0]) for p in pars),
273        max(len(p[-1]) for p in pars),
274        max(len(format_units(p[1])) for p in pars),
275        PARTABLE_VALUE_WIDTH,
276        ]
277    column_widths = [max(w, len(h))
278                     for w, h in zip(column_widths, PARTABLE_HEADERS)]
279
280    sep = " ".join("="*w for w in column_widths)
281    lines = [
282        sep,
283        " ".join("%-*s" % (w, h) for w, h in zip(column_widths, PARTABLE_HEADERS)),
284        sep,
285        ]
286    for p in pars:
287        lines.append(" ".join([
288            "%-*s" % (column_widths[0], p[0]),
289            "%-*s" % (column_widths[1], p[-1]),
290            "%-*s" % (column_widths[2], format_units(p[1])),
291            "%*g" % (column_widths[3], p[2]),
292            ]))
293    lines.append(sep)
294    return "\n".join(lines)
295
296def _search(search_path, filename):
297    """
298    Find *filename* in *search_path*.
299
300    Raises ValueError if file does not exist.
301    """
302    for path in search_path:
303        target = joinpath(path, filename)
304        if exists(target):
305            return target
306    raise ValueError("%r not found in %s" % (filename, search_path))
307
308def sources(info):
309    """
310    Return a list of the sources file paths for the module.
311    """
312    search_path = [dirname(info['filename']),
313                   abspath(joinpath(dirname(__file__), 'models'))]
314    return [_search(search_path, f) for f in info['source']]
315
316def use_single(source):
317    """
318    Convert code from double precision to single precision.
319    """
320    # Convert double keyword to float.  Accept an 'n' parameter for vector
321    # values, where n is 2, 4, 8 or 16. Assume complex numbers are represented
322    # as cdouble which is typedef'd to double2.
323    source = re.sub(r'(^|[^a-zA-Z0-9_]c?)double(([248]|16)?($|[^a-zA-Z0-9_]))',
324                    r'\1float\2', source)
325    # Convert floating point constants to single by adding 'f' to the end.
326    # OS/X driver complains if you don't do this.
327    source = re.sub(r'[^a-zA-Z_](\d*[.]\d+|\d+[.]\d*)([eE][+-]?\d+)?',
328                    r'\g<0>f', source)
329    return source
330
331def use_long_double(source):
332    """
333    Convert code from double precision to long double precision.
334    """
335    # Convert double keyword to float.  Accept an 'n' parameter for vector
336    # values, where n is 2, 4, 8 or 16. Assume complex numbers are represented
337    # as cdouble which is typedef'd to double2.
338    source = re.sub(r'(^|[^a-zA-Z0-9_]c?)double(([248]|16)?($|[^a-zA-Z0-9_]))',
339                    r'\1long double\2', source)
340    # Convert floating point constants to single by adding 'f' to the end.
341    # OS/X driver complains if you don't do this.
342    source = re.sub(r'[^a-zA-Z_](\d*[.]\d+|\d+[.]\d*)([eE][+-]?\d+)?',
343                    r'\g<0>L', source)
344    return source
345
346
347def kernel_name(info, is_2D):
348    """
349    Name of the exported kernel symbol.
350    """
351    return info['name'] + "_" + ("Iqxy" if is_2D else "Iq")
352
353
354def categorize_parameters(pars):
355    """
356    Build parameter categories out of the the parameter definitions.
357
358    Returns a dictionary of categories.
359    """
360    partype = {
361        'volume': [], 'orientation': [], 'magnetic': [], '': [],
362        'fixed-1d': [], 'fixed-2d': [], 'pd-1d': [], 'pd-2d': [],
363        'pd-rel': set(),
364    }
365
366    for p in pars:
367        name, ptype = p[0], p[4]
368        if ptype == 'volume':
369            partype['pd-1d'].append(name)
370            partype['pd-2d'].append(name)
371            partype['pd-rel'].add(name)
372        elif ptype == 'magnetic':
373            partype['fixed-2d'].append(name)
374        elif ptype == 'orientation':
375            partype['pd-2d'].append(name)
376        elif ptype == '':
377            partype['fixed-1d'].append(name)
378            partype['fixed-2d'].append(name)
379        else:
380            raise ValueError("unknown parameter type %r" % ptype)
381        partype[ptype].append(name)
382
383    return partype
384
385def indent(s, depth):
386    """
387    Indent a string of text with *depth* additional spaces on each line.
388    """
389    spaces = " "*depth
390    sep = "\n" + spaces
391    return spaces + sep.join(s.split("\n"))
392
393
394def build_polydispersity_loops(pd_pars):
395    """
396    Build polydispersity loops
397
398    Returns loop opening and loop closing
399    """
400    LOOP_OPEN = """\
401for (int %(name)s_i=0; %(name)s_i < N%(name)s; %(name)s_i++) {
402  const double %(name)s = loops[2*(%(name)s_i%(offset)s)];
403  const double %(name)s_w = loops[2*(%(name)s_i%(offset)s)+1];\
404"""
405    depth = 4
406    offset = ""
407    loop_head = []
408    loop_end = []
409    for name in pd_pars:
410        subst = {'name': name, 'offset': offset}
411        loop_head.append(indent(LOOP_OPEN % subst, depth))
412        loop_end.insert(0, (" "*depth) + "}")
413        offset += '+N' + name
414        depth += 2
415    return "\n".join(loop_head), "\n".join(loop_end)
416
417C_KERNEL_TEMPLATE = None
418def make_model(info):
419    """
420    Generate the code for the kernel defined by info, using source files
421    found in the given search path.
422    """
423    # TODO: need something other than volume to indicate dispersion parameters
424    # No volume normalization despite having a volume parameter.
425    # Thickness is labelled a volume in order to trigger polydispersity.
426    # May want a separate dispersion flag, or perhaps a separate category for
427    # disperse, but not volume.  Volume parameters also use relative values
428    # for the distribution rather than the absolute values used by angular
429    # dispersion.  Need to be careful that necessary parameters are available
430    # for computing volume even if we allow non-disperse volume parameters.
431
432    # Load template
433    global C_KERNEL_TEMPLATE
434    if C_KERNEL_TEMPLATE is None:
435        with open(C_KERNEL_TEMPLATE_PATH) as fid:
436            C_KERNEL_TEMPLATE = fid.read()
437
438    # Load additional sources
439    source = [open(f).read() for f in sources(info)]
440
441    # Prepare defines
442    defines = []
443    partype = info['partype']
444    pd_1d = partype['pd-1d']
445    pd_2d = partype['pd-2d']
446    fixed_1d = partype['fixed-1d']
447    fixed_2d = partype['fixed-1d']
448
449    iq_parameters = [p[0]
450                     for p in info['parameters'][2:] # skip scale, background
451                     if p[0] in set(fixed_1d + pd_1d)]
452    iqxy_parameters = [p[0]
453                       for p in info['parameters'][2:] # skip scale, background
454                       if p[0] in set(fixed_2d + pd_2d)]
455    volume_parameters = [p[0]
456                         for p in info['parameters']
457                         if p[4] == 'volume']
458
459    # Fill in defintions for volume parameters
460    if volume_parameters:
461        defines.append(('VOLUME_PARAMETERS',
462                        ','.join(volume_parameters)))
463        defines.append(('VOLUME_WEIGHT_PRODUCT',
464                        '*'.join(p + '_w' for p in volume_parameters)))
465
466    # Generate form_volume function from body only
467    if info['form_volume'] is not None:
468        if volume_parameters:
469            vol_par_decl = ', '.join('double ' + p for p in volume_parameters)
470        else:
471            vol_par_decl = 'void'
472        defines.append(('VOLUME_PARAMETER_DECLARATIONS',
473                        vol_par_decl))
474        fn = """\
475double form_volume(VOLUME_PARAMETER_DECLARATIONS);
476double form_volume(VOLUME_PARAMETER_DECLARATIONS) {
477    %(body)s
478}
479""" % {'body':info['form_volume']}
480        source.append(fn)
481
482    # Fill in definitions for Iq parameters
483    defines.append(('IQ_KERNEL_NAME', info['name'] + '_Iq'))
484    defines.append(('IQ_PARAMETERS', ', '.join(iq_parameters)))
485    if fixed_1d:
486        defines.append(('IQ_FIXED_PARAMETER_DECLARATIONS',
487                        ', \\\n    '.join('const double %s' % p for p in fixed_1d)))
488    if pd_1d:
489        defines.append(('IQ_WEIGHT_PRODUCT',
490                        '*'.join(p + '_w' for p in pd_1d)))
491        defines.append(('IQ_DISPERSION_LENGTH_DECLARATIONS',
492                        ', \\\n    '.join('const int N%s' % p for p in pd_1d)))
493        defines.append(('IQ_DISPERSION_LENGTH_SUM',
494                        '+'.join('N' + p for p in pd_1d)))
495        open_loops, close_loops = build_polydispersity_loops(pd_1d)
496        defines.append(('IQ_OPEN_LOOPS',
497                        open_loops.replace('\n', ' \\\n')))
498        defines.append(('IQ_CLOSE_LOOPS',
499                        close_loops.replace('\n', ' \\\n')))
500    if info['Iq'] is not None:
501        defines.append(('IQ_PARAMETER_DECLARATIONS',
502                        ', '.join('double ' + p for p in iq_parameters)))
503        fn = """\
504double Iq(double q, IQ_PARAMETER_DECLARATIONS);
505double Iq(double q, IQ_PARAMETER_DECLARATIONS) {
506    %(body)s
507}
508""" % {'body':info['Iq']}
509        source.append(fn)
510
511    # Fill in definitions for Iqxy parameters
512    defines.append(('IQXY_KERNEL_NAME', info['name'] + '_Iqxy'))
513    defines.append(('IQXY_PARAMETERS', ', '.join(iqxy_parameters)))
514    if fixed_2d:
515        defines.append(('IQXY_FIXED_PARAMETER_DECLARATIONS',
516                        ', \\\n    '.join('const double %s' % p for p in fixed_2d)))
517    if pd_2d:
518        defines.append(('IQXY_WEIGHT_PRODUCT',
519                        '*'.join(p + '_w' for p in pd_2d)))
520        defines.append(('IQXY_DISPERSION_LENGTH_DECLARATIONS',
521                        ', \\\n    '.join('const int N%s' % p for p in pd_2d)))
522        defines.append(('IQXY_DISPERSION_LENGTH_SUM',
523                        '+'.join('N' + p for p in pd_2d)))
524        open_loops, close_loops = build_polydispersity_loops(pd_2d)
525        defines.append(('IQXY_OPEN_LOOPS',
526                        open_loops.replace('\n', ' \\\n')))
527        defines.append(('IQXY_CLOSE_LOOPS',
528                        close_loops.replace('\n', ' \\\n')))
529    if info['Iqxy'] is not None:
530        defines.append(('IQXY_PARAMETER_DECLARATIONS',
531                        ', '.join('double ' + p for p in iqxy_parameters)))
532        fn = """\
533double Iqxy(double qx, double qy, IQXY_PARAMETER_DECLARATIONS);
534double Iqxy(double qx, double qy, IQXY_PARAMETER_DECLARATIONS) {
535    %(body)s
536}
537""" % {'body':info['Iqxy']}
538        source.append(fn)
539
540    # Need to know if we have a theta parameter for Iqxy; it is not there
541    # for the magnetic sphere model, for example, which has a magnetic
542    # orientation but no shape orientation.
543    if 'theta' in pd_2d:
544        defines.append(('IQXY_HAS_THETA', '1'))
545
546    #for d in defines: print d
547    DEFINES = '\n'.join('#define %s %s' % (k, v) for k, v in defines)
548    SOURCES = '\n\n'.join(source)
549    return C_KERNEL_TEMPLATE % {
550        'DEFINES':DEFINES,
551        'SOURCES':SOURCES,
552        }
553
554def make_info(kernel_module):
555    """
556    Interpret the model definition file, categorizing the parameters.
557    """
558    #print kernelfile
559    category = getattr(kernel_module, 'category', None)
560    parameters = COMMON_PARAMETERS + kernel_module.parameters
561    # Default the demo parameters to the starting values for the individual
562    # parameters if an explicit demo parameter set has not been specified.
563    demo_parameters = getattr(kernel_module, 'demo', None)
564    if demo_parameters is None:
565        demo_parameters = dict((p[0],p[2]) for p in parameters)
566    filename = abspath(kernel_module.__file__)
567    kernel_id = basename(filename)[:-3]
568    name = getattr(kernel_module, 'name', None)
569    if name is None:
570        name = " ".join(w.capitalize() for w in kernel_id.split('_'))
571    info = dict(
572        id = kernel_id,  # string used to load the kernel
573        filename=abspath(kernel_module.__file__),
574        name=name,
575        title=kernel_module.title,
576        description=kernel_module.description,
577        category=category,
578        parameters=parameters,
579        demo=demo_parameters,
580        source=getattr(kernel_module, 'source', []),
581        oldname=kernel_module.oldname,
582        oldpars=kernel_module.oldpars,
583        )
584    # Fill in attributes which default to None
585    info.update((k, getattr(kernel_module, k, None))
586                for k in ('ER', 'VR', 'form_volume', 'Iq', 'Iqxy'))
587    # Fill in the derived attributes
588    info['limits'] = dict((p[0], p[3]) for p in info['parameters'])
589    info['partype'] = categorize_parameters(info['parameters'])
590    info['defaults'] = dict((p[0], p[2]) for p in info['parameters'])
591    return info
592
593def make(kernel_module):
594    """
595    Build an OpenCL/ctypes function from the definition in *kernel_module*.
596
597    The module can be loaded with a normal python import statement if you
598    know which module you need, or with __import__('sasmodels.model.'+name)
599    if the name is in a string.
600    """
601    info = make_info(kernel_module)
602    # Assume if one part of the kernel is python then all parts are.
603    source = make_model(info) if not callable(info['Iq']) else None
604    return source, info
605
606def doc(kernel_module):
607    """
608    Return the documentation for the model.
609    """
610    info = make_info(kernel_module)
611    subst = dict(id=info['id'].replace('_', '-'),
612                 name=info['name'],
613                 title=info['title'],
614                 parameters=make_partable(info['parameters']),
615                 docs=kernel_module.__doc__)
616    return DOC_HEADER % subst
617
618
619
620def demo_time():
621    from .models import cylinder
622    import datetime
623    tic = datetime.datetime.now()
624    make(cylinder)
625    toc = (datetime.datetime.now() - tic).total_seconds()
626    print "time:", toc
627
628def main():
629    if len(sys.argv) <= 1:
630        print "usage: python -m sasmodels.generate modelname"
631    else:
632        name = sys.argv[1]
633        import sasmodels.models
634        __import__('sasmodels.models.' + name)
635        model = getattr(sasmodels.models, name)
636        source, _ = make(model)
637        print source
638
639if __name__ == "__main__":
640    main()
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