Changes in / [2ed7de0:d8e81f7] in sasmodels


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sasmodels
Files:
4 edited

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  • sasmodels/direct_model.py

    r2ed7de0 rb39bf3b  
    6161    #print("in call_kernel: pars:", list(zip(*mesh))[0]) 
    6262    call_details, values, is_magnetic = make_kernel_args(calculator, mesh) 
    63     #print("in call_kernel: values:", values) 
     63    print("in call_kernel: values:", values) 
    6464    return calculator(call_details, values, cutoff, is_magnetic) 
    6565 
  • sasmodels/model_test.py

    r2ed7de0 rb39bf3b  
    247247                                           platform=self.platform) 
    248248                    # run the tests 
     249<<<<<<< HEAD 
     250                    #self.info = ps_model.info 
     251                    #print("SELF.INFO PARAMS!!!",[p.id for p in self.info.parameters.call_parameters]) 
     252                    #print("PS MODEL PARAMETERS:",[p.id for p in ps_model.info.parameters.call_parameters]) 
     253======= 
     254>>>>>>> 2ed7de04217c5103c5fd8d7c14e29e04923269d5 
    249255                    results.append(self.run_one(ps_model, ps_test)) 
    250256 
     
    304310            """Run a single test case.""" 
    305311            user_pars, x, y = test[:3] 
     312            print("PS MODEL PARAMETERS:",[p.id for p in model.info.parameters.call_parameters]) 
    306313            pars = expand_pars(model.info.parameters, user_pars) 
    307314            invalid = invalid_pars(model.info.parameters, pars) 
  • sasmodels/models/sphere.py

    r2ed7de0 rb39bf3b  
    7575              ["sld_solvent", "1e-6/Ang^2", 6, [-inf, inf], "sld", 
    7676               "Solvent scattering length density"], 
    77               ["radius", "Ang", 50, [0, inf], "volume", 
     77              ["radius", "Ang", 45, [0, inf], "volume", 
    7878               "Sphere radius"], 
    7979             ] 
     
    9292 
    9393tests = [ 
    94     [{}, 0.2, 0.726362], 
    95     [{"scale": 1., "background": 0., "sld": 6., "sld_solvent": 1., 
    96       "radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, 
    97      0.2, 0.2288431], 
    98     [{"radius": 120., "radius_pd": 0.02, "radius_pd_n":45}, 0.2, 
    99      # F1, F2, R_eff, volume, volume_ratio = call_Fq(kernel, pars) at q=0.2 
    100      792.0646662454202, 1166737.0473152, 120.0, 7246723.820358589, 1.0], 
    101     #  But note P(Q) = F2/volume+background,  F1 and F2 are vectors 
    102     #  BUT what is scaling of F1 ???  At low Pd F2 ~ F1^2 ? 
    103    [{"radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, 0.2, 
    104      # F1, F2, R_eff, volume, volume_ratio = call_Fq(kernel, pars) at q=0.2 
    105      1.233304061, 1850806.119736, 120.0, 8087664.1226, 1.0], 
    106     [{"@S": "hardsphere"}, 
    107        0.01, 55.881884232102124], # current value, not verified elsewhere yet 
    108     [{"@S": "hardsphere"}, 
    109        0.2, 0.14730859242492958], # current value, not verified elsewhere yet 
    110     [{"@S": "hardsphere"}, 
    111        0.1, 0.7940350343811906], # current value, not verified elsewhere yet 
    112     [{"@S": "hardsphere",        # hard sphere structure factor 
    113      "structure_factor_mode": 1, # decoupling approximation 
    114      "radius_effective_mode": 1, 
    115      # Currently have hardwired model_test to accept radius_effective 
    116      "radius_effective": 27.0, # equivalent sphere 
    117      # direct_model has the name & value BUT does it get passed to S(Q)??? 
    118      # What about volfracion, plus the many parameters used by other S(Q) ? 
     94   #  [{}, 0.2, 0.726362], 
     95   #  [{"scale": 1., "background": 0., "sld": 6., "sld_solvent": 1., 
     96   #    "radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, 
     97   #   0.2, 0.2288431], 
     98   # [{"radius": 120., "radius_pd": 0.02, "radius_pd_n":45}, 
     99   #   0.2, 792.0646662454202, [1166737.0473152], 120.0, 7246723.820358589, 1.0], # the longer list here checks  F1, F2, R_eff, volume, volume_ratio = call_Fq(kernel, pars) 
     100   #  #          But note P(Q) = F2/volume,  F1 and F2 are vectors, for some reason only F2 needs square brackets 
     101   #  #          BUT what is scaling of F1 ???  At low Pd F2 ~ F1^2 ? 
     102   # [{"@S": "hardsphere"}, 
     103   #    0.01, 55.881884232102124], # this is current value, not verified elsewhere yet 
     104   # [{"radius": 120., "radius_pd": 0.2, "radius_pd_n":45}, 
     105   #   0.2, 1.233304061, [1850806.119736], 120.0, 8087664.1226, 1.0], # the longer list here checks  F1, F2, R_eff, volume, volume_ratio = call_Fq(kernel, pars) 
     106   # [{"@S": "hardsphere"}, 
     107   #     0.2, 0.14730859242492958], #  this is current value, not verified elsewhere yet 
     108    # [{"@S": "hardsphere"}, 
     109    #    0.1, 0.7940350343811906], #  this is current value, not verified elsewhere yet 
     110    [{"@S": "hardsphere", 
     111     "radius": 120., "radius_pd": 0.2, "radius_pd_n":45, 
     112     "volfraction":0.2, 
     113     "radius_effective":45.0,        # hard sphere structure factor 
     114     "structure_factor_mode": 1,  # decoupling approximation 
     115     #"effective_radius_type": 1 # equivalent sphere   Currently have hardwired model_test to accept radius_effective 
     116     # direct_model has the name & value BUT does it get passed to S(Q)???  What about volfracion, plus the many parameters used by other S(Q) ? 
    119117     # effective_radius_type does NOT appear in the list, has it been stripped out??? 
    120      }, 0.1, 0.7940350343881906], 
    121 #    [{"@S": "hardsphere",          # hard sphere structure factor 
    122 #     "structure_factor_mode": 3,  #  -  WHY same result? 
    123 #     "effective_radius_type": 3, "radius_effective": 23.0    # 
    124 #     }, 0.1, 0.7940350343881906] 
     118     }, 0.01, 0.7940350343881906], 
     119        # [{"@S": "hardsphere",          # hard sphere structure factor 
     120    # "structure_factor_mode": 2,  #  -  WHY same result? 
     121    # "effective_radius_type": 2, "radius_effective":23.0    # 
     122        #  }, 0.1, 0.7940350343881906] 
    125123] 
    126 # putting None for expected result will pass the test if there are no errors 
    127 # from the routine, but without any check on the value of the result 
     124# putting None for expected result will pass the test if there are no errors from the routine, but without any check on the value of the result 
  • sasmodels/product.py

    r2ed7de0 rb39bf3b  
    282282        # unless the model doesn't support beta mode, in which case it is first 
    283283        have_radius_type = p_info.effective_radius_type is not None 
     284        #print(p_npars,s_npars) 
    284285        radius_type_offset = 2+p_npars+s_npars + (1 if have_beta_mode else 0) 
     286        print(values[radius_type_offset]) 
    285287        radius_type = int(values[radius_type_offset]) if have_radius_type else 0 
    286288 
     
    340342        # polydispersity distribution slot in the values array due to 
    341343        # implementation details in kernel_iq.c. 
    342         #print("R_eff=%d:%g, volfrac=%g, volume ratio=%g" 
    343         #      % (radius_type, effective_radius, volfrac, volume_ratio)) 
     344        print("R_eff=%d:%g, volfrac=%g, volume ratio=%g" 
     345              % (radius_type, effective_radius, volfrac, volume_ratio)) 
    344346        if radius_type > 0: 
    345347            # set the value to the model R_eff and set the weight to 1 
     
    356358 
    357359        # Combine form factor and structure factor 
    358         #print("beta", beta_mode, F1, F2, S) 
     360        print("beta", beta_mode, F1, F2, S) 
    359361        PS = F2 + F1**2*(S-1) if beta_mode else F2*S 
    360362        final_result = combined_scale*PS + background 
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