Changes in / [c036ddb:7e923c2] in sasmodels


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  • doc/guide/gpu_setup.rst

    r59485a4 r63602b1  
    139139the compiler. 
    140140 
    141 On Windows, set *SASCOMPILER=tinycc* for the tinycc compiler, 
    142 *SASCOMPILER=msvc* for the Microsoft Visual C compiler, 
    143 or *SASCOMPILER=mingw* for the MinGW compiler. If TinyCC is available 
     141On Windows, set *SAS_COMPILER=tinycc* for the tinycc compiler, 
     142*SAS_COMPILER=msvc* for the Microsoft Visual C compiler, 
     143or *SAS_COMPILER=mingw* for the MinGW compiler. If TinyCC is available 
    144144on the python path (it is provided with SasView), that will be the 
    145145default. If you want one of the other compilers, be sure to have it 

  • example/model_ellipsoid_hayter_msa.py

    r8a5f021 r9a99993  
    1616 
    1717# DEFINE THE MODEL 
    18 kernel = load_model('ellipsoid*hayter_msa') 
     18kernel = load_model('ellipsoid@hayter_msa') 
    1919 
    2020pars = dict(scale=6.4, background=0.06, sld=0.33, sld_solvent=2.15, radius_polar=14.0, 

  • sasmodels/compare.py

    r1e7b202a raf7a97c  
    112112    -edit starts the parameter explorer 
    113113    -help/-html shows the model docs instead of running the model 
     114 
     115    === environment variables === 
     116    -DSAS_MODELPATH=path sets directory containing custom models 
     117    -DSAS_OPENCL=vendor:device|none sets the target OpenCL device 
     118    -DXDG_CACHE_HOME=~/.cache sets the pyopencl cache root (linux only) 
     119    -DSAS_COMPILER=tinycc|msvc|mingw|unix sets the DLL compiler 
     120    -DSAS_OPENMP=1 turns on OpenMP for the DLLs 
     121    -DSAS_DLL_PATH=path sets the path to the compiled modules 
    114122 
    115123The interpretation of quad precision depends on architecture, and may 
    … …  
    11131121 
    11141122    invalid = [o[1:] for o in flags 
    1115                if o[1:] not in NAME_OPTIONS 
    1116                and not any(o.startswith('-%s='%t) for t in VALUE_OPTIONS)] 
     1123               if not (o[1:] in NAME_OPTIONS 
     1124                       or any(o.startswith('-%s='%t) for t in VALUE_OPTIONS) 
     1125                       or o.startswith('-D'))] 
    11171126    if invalid: 
    11181127        print("Invalid options: %s"%(", ".join(invalid))) 
    … …  
    12151224        elif arg == '-html':    opts['html'] = True 
    12161225        elif arg == '-help':    opts['html'] = True 
     1226        elif arg.startswith('-D'): 
     1227            var, val = arg[2:].split('=') 
     1228            os.environ[var] = val 
    12171229    # pylint: enable=bad-whitespace,C0321 
    12181230 

  • sasmodels/core.py

    rc036ddb rc036ddb  
    3737if CUSTOM_MODEL_PATH == "": 
    3838    CUSTOM_MODEL_PATH = joinpath(os.path.expanduser("~"), ".sasmodels", "custom_models") 
    39     if not os.path.isdir(CUSTOM_MODEL_PATH): 
    40         os.makedirs(CUSTOM_MODEL_PATH) 
     39    #if not os.path.isdir(CUSTOM_MODEL_PATH): 
     40    #    os.makedirs(CUSTOM_MODEL_PATH) 
    4141 
    4242# TODO: refactor composite model support 
    … …  
    232232        if not callable(model_info.Iq): 
    233233            source = generate.make_source(model_info)['dll'] 
    234             old_path = kerneldll.DLL_PATH 
     234            old_path = kerneldll.SAS_DLL_PATH 
    235235            try: 
    236                 kerneldll.DLL_PATH = path 
     236                kerneldll.SAS_DLL_PATH = path 
    237237                dll = kerneldll.make_dll(source, model_info, dtype=numpy_dtype) 
    238238            finally: 
    239                 kerneldll.DLL_PATH = old_path 
     239                kerneldll.SAS_DLL_PATH = old_path 
    240240            compiled_dlls.append(dll) 
    241241    return compiled_dlls 

  • sasmodels/data.py

    rc036ddb rc036ddb  
    502502            # Note: masks merge, so any masked theory points will stay masked, 
    503503            # and the data mask will be added to it. 
    504             mtheory = masked_array(theory, data.mask.copy()) 
     504            #mtheory = masked_array(theory, data.mask.copy()) 
     505            theory_x = data.x[data.mask == 0] 
     506            mtheory = masked_array(theory) 
    505507            mtheory[~np.isfinite(mtheory)] = masked 
    506508            if view is 'log': 
    507509                mtheory[mtheory <= 0] = masked 
    508             plt.plot(data.x, scale*mtheory, '-') 
     510            plt.plot(theory_x, scale*mtheory, '-') 
    509511            all_positive = all_positive and (mtheory > 0).all() 
    510512            some_present = some_present or (mtheory.count() > 0) 
    … …  
    542544 
    543545    if use_resid: 
    544         mresid = masked_array(resid, data.mask.copy()) 
     546        theory_x = data.x[data.mask == 0] 
     547        mresid = masked_array(resid) 
    545548        mresid[~np.isfinite(mresid)] = masked 
    546549        some_present = (mresid.count() > 0) 
    … …  
    548551        if num_plots > 1: 
    549552            plt.subplot(1, num_plots, use_calc + 2) 
    550         plt.plot(data.x, mresid, '.') 
     553        plt.plot(theory_x, mresid, '.') 
    551554        plt.xlabel("$q$/A$^{-1}$") 
    552555        plt.ylabel('residuals') 

  • sasmodels/direct_model.py

    rd18d6dd r1a8c11c  
    250250            qmax = getattr(data, 'qmax', np.inf) 
    251251            accuracy = getattr(data, 'accuracy', 'Low') 
    252             index = ~data.mask & (q >= qmin) & (q <= qmax) 
     252            index = (data.mask == 0) & (q >= qmin) & (q <= qmax) 
    253253            if data.data is not None: 
    254254                index &= ~np.isnan(data.data) 
    … …  
    263263        elif self.data_type == 'Iq': 
    264264            index = (data.x >= data.qmin) & (data.x <= data.qmax) 
     265            mask = getattr(data, 'mask', None) 
     266            if mask is not None: 
     267                index &= (mask == 0) 
    265268            if data.y is not None: 
    266269                index &= ~np.isnan(data.y) 

  • sasmodels/kerneldll.py

    rc036ddb rc036ddb  
    9999    pass 
    100100# pylint: enable=unused-import 
     101 
     102if "SAS_DLL_PATH" in os.environ: 
     103    SAS_DLL_PATH = os.environ["SAS_DLL_PATH"] 
     104else: 
     105    # Assume the default location of module DLLs is in .sasmodels/compiled_models. 
     106    SAS_DLL_PATH = os.path.join(os.path.expanduser("~"), ".sasmodels", "compiled_models") 
    101107 
    102108if "SAS_COMPILER" in os.environ: 
    … …  
    161167        return CC + [source, "-o", output, "-lm"] 
    162168 
    163 # Assume the default location of module DLLs is in .sasmodels/compiled_models. 
    164 DLL_PATH = os.path.join(os.path.expanduser("~"), ".sasmodels", "compiled_models") 
    165  
    166169ALLOW_SINGLE_PRECISION_DLLS = True 
    167170 
    … …  
    200203        return path 
    201204 
    202     return joinpath(DLL_PATH, basename) 
     205    return joinpath(SAS_DLL_PATH, basename) 
    203206 
    204207 
    … …  
    209212    exist yet if it hasn't been compiled. 
    210213    """ 
    211     return os.path.join(DLL_PATH, dll_name(model_info, dtype)) 
     214    return os.path.join(SAS_DLL_PATH, dll_name(model_info, dtype)) 
    212215 
    213216 
    … …  
    228231    models are not allowed as DLLs. 
    229232 
    230     Set *sasmodels.kerneldll.DLL_PATH* to the compiled dll output path. 
     233    Set *sasmodels.kerneldll.SAS_DLL_PATH* to the compiled dll output path. 
     234    Alternatively, set the environment variable *SAS_DLL_PATH*. 
    231235    The default is in ~/.sasmodels/compiled_models. 
    232236    """ 
    … …  
    247251    if need_recompile: 
    248252        # Make sure the DLL path exists 
    249         if not os.path.exists(DLL_PATH): 
    250             os.makedirs(DLL_PATH) 
     253        if not os.path.exists(SAS_DLL_PATH): 
     254            os.makedirs(SAS_DLL_PATH) 
    251255        basename = splitext(os.path.basename(dll))[0] + "_" 
    252256        system_fd, filename = tempfile.mkstemp(suffix=".c", prefix=basename) 

  • sasmodels/model_test.py

    • Property mode changed from 100644 to 100755
    r3221de0 r012cd34  
    376376        stream.writeln(traceback.format_exc()) 
    377377        return 
    378     # Run the test suite 
    379     suite.run(result) 
    380  
    381     # Print the failures and errors 
    382     for _, tb in result.errors: 
    383         stream.writeln(tb) 
    384     for _, tb in result.failures: 
    385         stream.writeln(tb) 
    386378 
    387379    # Warn if there are no user defined tests. 
    … …  
    393385    # iterator since we don't have direct access to the list of tests in the 
    394386    # test suite. 
     387    # In Qt5 suite.run() will clear all tests in the suite after running 
     388    # with no way of retaining them for the test below, so let's check 
     389    # for user tests before running the suite. 
    395390    for test in suite: 
    396391        if not test.info.tests: 
    … …  
    399394    else: 
    400395        stream.writeln("Note: no test suite created --- this should never happen") 
     396 
     397    # Run the test suite 
     398    suite.run(result) 
     399 
     400    # Print the failures and errors 
     401    for _, tb in result.errors: 
     402        stream.writeln(tb) 
     403    for _, tb in result.failures: 
     404        stream.writeln(tb) 
    401405 
    402406    output = stream.getvalue() 

  • sasmodels/modelinfo.py

    rc036ddb rc036ddb  
    585585                Parameter('up:frac_f', '', 0., [0., 1.], 
    586586                          'magnetic', 'fraction of spin up final'), 
    587                 Parameter('up:angle', 'degress', 0., [0., 360.], 
     587                Parameter('up:angle', 'degrees', 0., [0., 360.], 
    588588                          'magnetic', 'spin up angle'), 
    589589            ]) 

  • sasmodels/models/guinier.py

    r2d81cfe rc9fc873  
    77.. math:: 
    88 
    9     I(q) = \text{scale} \cdot \exp{\left[ \frac{-Q^2R_g^2}{3} \right]} 
     9    I(q) = \text{scale} \cdot \exp{\left[ \frac{-Q^2 R_g^2 }{3} \right]} 
    1010            + \text{background} 
    1111 
    … …  
    1919 
    2020.. math:: q = \sqrt{q_x^2 + q_y^2} 
     21 
     22In scattering, the radius of gyration $R_g$ quantifies the objects's 
     23distribution of SLD (not mass density, as in mechanics) from the objects's 
     24SLD centre of mass. It is defined by 
     25 
     26.. math:: R_g^2 = \frac{\sum_i\rho_i\left(r_i-r_0\right)^2}{\sum_i\rho_i} 
     27 
     28where $r_0$ denotes the object's SLD centre of mass and $\rho_i$ is the SLD at 
     29a point $i$. 
     30 
     31Notice that $R_g^2$ may be negative (since SLD can be negative), which happens 
     32when a form factor $P(Q)$ is increasing with $Q$ rather than decreasing. This 
     33can occur for core/shell particles, hollow particles, or for composite 
     34particles with domains of different SLDs in a solvent with an SLD close to the 
     35average match point. (Alternatively, this might be regarded as there being an 
     36internal inter-domain "structure factor" within a single particle which gives 
     37rise to a peak in the scattering). 
     38 
     39To specify a negative value of $R_g^2$ in SasView, simply give $R_g$ a negative 
     40value ($R_g^2$ will be evaluated as $R_g |R_g|$). Note that the physical radius  
     41of gyration, of the exterior of the particle, will still be large and positive.  
     42It is only the apparent size from the small $Q$ data that will give a small or  
     43negative value of $R_g^2$. 
    2144 
    2245References 
    … …  
    4265 
    4366#             ["name", "units", default, [lower, upper], "type","description"], 
    44 parameters = [["rg", "Ang", 60.0, [0, inf], "", "Radius of Gyration"]] 
     67parameters = [["rg", "Ang", 60.0, [-inf, inf], "", "Radius of Gyration"]] 
    4568 
    4669Iq = """ 
    47     double exponent = rg*rg*q*q/3.0; 
     70    double exponent = fabs(rg)*rg*q*q/3.0; 
    4871    double value = exp(-exponent); 
    4972    return value; 
    … …  
    6689 
    6790# parameters for demo 
    68 demo = dict(scale=1.0, rg=60.0) 
     91demo = dict(scale=1.0,  background=0.001, rg=60.0 ) 
    6992 
    7093# parameters for unit tests 

  • sasmodels/resolution.py

    r0b9c6df r9e7837a  
    2020MINIMUM_RESOLUTION = 1e-8 
    2121MINIMUM_ABSOLUTE_Q = 0.02  # relative to the minimum q in the data 
    22 PINHOLE_N_SIGMA = 2.5 # From: Barker & Pedersen 1995 JAC 
     22# According to (Barker & Pedersen 1995 JAC), 2.5 sigma is a good limit. 
     23# According to simulations with github.com:scattering/sansresolution.git 
     24# it is better to use asymmetric bounds (2.5, 3.0) 
     25PINHOLE_N_SIGMA = (2.5, 3.0) 
    2326 
    2427class Resolution(object): 
    … …  
    9093        # from the geometry, they may appear since we are using a truncated 
    9194        # gaussian to represent resolution rather than a skew distribution. 
    92         cutoff = MINIMUM_ABSOLUTE_Q*np.min(self.q) 
    93         self.q_calc = self.q_calc[self.q_calc >= cutoff] 
     95        #cutoff = MINIMUM_ABSOLUTE_Q*np.min(self.q) 
     96        #self.q_calc = self.q_calc[self.q_calc >= cutoff] 
    9497 
    9598        # Build weight matrix from calculated q values 
    … …  
    188191    cdf = erf((edges[:, None] - q[None, :]) / (sqrt(2.0)*q_width)[None, :]) 
    189192    weights = cdf[1:] - cdf[:-1] 
    190     # Limit q range to +/- 2.5 sigma 
    191     qhigh = q + nsigma*q_width 
    192     #qlow = q - nsigma*q_width  # linear limits 
    193     qlow = q*q/qhigh  # log limits 
     193    # Limit q range to (-2.5,+3) sigma 
     194    try: 
     195        nsigma_low, nsigma_high = nsigma 
     196    except TypeError: 
     197        nsigma_low = nsigma_high = nsigma 
     198    qhigh = q + nsigma_high*q_width 
     199    qlow = q - nsigma_low*q_width  # linear limits 
     200    ##qlow = q*q/qhigh  # log limits 
    194201    weights[q_calc[:, None] < qlow[None, :]] = 0. 
    195202    weights[q_calc[:, None] > qhigh[None, :]] = 0. 
    … …  
    365372 
    366373 
    367 def pinhole_extend_q(q, q_width, nsigma=3): 
     374def pinhole_extend_q(q, q_width, nsigma=PINHOLE_N_SIGMA): 
    368375    """ 
    369376    Given *q* and *q_width*, find a set of sampling points *q_calc* so 
    … …  
    371378    function. 
    372379    """ 
    373     q_min, q_max = np.min(q - nsigma*q_width), np.max(q + nsigma*q_width) 
     380    try: 
     381        nsigma_low, nsigma_high = nsigma 
     382    except TypeError: 
     383        nsigma_low = nsigma_high = nsigma 
     384    q_min, q_max = np.min(q - nsigma_low*q_width), np.max(q + nsigma_high*q_width) 
    374385    return linear_extrapolation(q, q_min, q_max) 
    375386 
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