Changeset 0495db8 in sasmodels


Ignore:
Timestamp:
Mar 20, 2016 10:58:14 AM (9 years ago)
Author:
awashington
Branches:
master, core_shell_microgels, costrafo411, magnetic_model, release_v0.94, release_v0.95, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
Children:
42f71da
Parents:
0b499f0 (diff), a154ad16 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.
Message:

Merge branch 'master' into sesans_units

Files:
1 deleted
26 edited

Legend:

Unmodified
Added
Removed

  • doc/conf.py

    r4a21670c r22975f0  
    233233 
    234234numfig = True 
     235#numfig_format = {"figure": "Fig. %s", "table": "Table %s", "code-block": "Program %s"} 

  • example/sesans_parameters_css-hs.py

    r84db7a5 r3415f4f  
    2222# Initial parameter values (if other than defaults) 
    2323initial_vals = { 
    24     "core_sld" : 1.0592, 
    25     "solvent_sld" : 2.88, 
     24    "sld_core" : 1.0592, 
     25    "sld_solvent" : 2.88, 
    2626    "radius" : 890, 
    2727    "thickness" : 130 

  • sasmodels/compare.py

    r72a081d r98d6cfc  
    6969    -accuracy=Low accuracy of the resolution calculation Low, Mid, High, Xhigh 
    7070    -edit starts the parameter explorer 
     71    -default/-demo* use demo vs default parameters 
    7172 
    7273Any two calculation engines can be selected for comparison: 
    … …  
    631632    'hist', 'nohist', 
    632633    'edit', 
     634    'demo', 'default', 
    633635    ]) 
    634636VALUE_OPTIONS = [ 
    … …  
    654656 
    655657 
    656 def get_demo_pars(model_info): 
     658def get_pars(model_info, use_demo=False): 
    657659    """ 
    658660    Extract demo parameters from the model definition. 
    … …  
    670672 
    671673    # Plug in values given in demo 
    672     pars.update(model_info['demo']) 
     674    if use_demo: 
     675        pars.update(model_info['demo']) 
    673676    return pars 
    674677 
    … …  
    727730        'rel_err'   : True, 
    728731        'explore'   : False, 
     732        'use_demo'  : True, 
    729733    } 
    730734    engines = [] 
    … …  
    765769        elif arg == '-sasview': engines.append(arg[1:]) 
    766770        elif arg == '-edit':    opts['explore'] = True 
     771        elif arg == '-demo':    opts['use_demo'] = True 
     772        elif arg == '-default':    opts['use_demo'] = False 
    767773    # pylint: enable=bad-whitespace 
    768774 
    … …  
    782788    # Get demo parameters from model definition, or use default parameters 
    783789    # if model does not define demo parameters 
    784     pars = get_demo_pars(model_info) 
     790    pars = get_pars(model_info, opts['use_demo']) 
     791 
    785792 
    786793    # Fill in parameters given on the command line 

  • sasmodels/compare_many.py

    red048b2 rce346b6  
    2222from . import generate 
    2323from .compare import (MODELS, randomize_pars, suppress_pd, make_data, 
    24                       make_engine, get_demo_pars, columnize, 
     24                      make_engine, get_pars, columnize, 
    2525                      constrain_pars, constrain_new_to_old) 
    2626 
    … …  
    102102    is_2d = hasattr(data, 'qx_data') 
    103103    model_info = core.load_model_info(name) 
    104     pars = get_demo_pars(model_info) 
     104    pars = get_pars(model_info, use_demo=True) 
    105105    header = ('\n"Model","%s","Count","%d","Dimension","%s"' 
    106106              % (name, N, "2D" if is_2d else "1D")) 

  • sasmodels/convert.py

    rbad8b12 r062db5a  
    154154        elif name == 'fractal': 
    155155            del oldpars['volfraction'] 
     156        elif name == 'vesicle': 
     157            del oldpars['volfraction'] 
    156158 
    157159    return oldpars 
    … …  
    191193        elif name == 'fractal': 
    192194            pars['volfraction'] = 1 
     195        elif name == 'vesicle': 
     196            pars['volfraction'] = 1 
    193197             

  • sasmodels/models/binary_hard_sphere.c

    r115d0f0 re481a39  
    1313    ); 
    1414 
    15 int calculate_psfs(double qval, 
     15void calculate_psfs(double qval, 
    1616    double r2, double nf2, 
    1717    double aa, double phi, 
    … …  
    3434    double phi1,phi2,phr,a3; 
    3535    double v1,v2,n1,n2,qr1,qr2,b1,b2,sc1,sc2; 
    36     int err; 
    3736     
    3837    r2 = lg_radius; 
    … …  
    5251    nf2 = phr*a3/(1.0-phr+phr*a3); 
    5352    // calculate the PSF's here 
    54     err = calculate_psfs(q,r2,nf2,aa,phi,&psf11,&psf22,&psf12); 
     53    calculate_psfs(q,r2,nf2,aa,phi,&psf11,&psf22,&psf12); 
    5554     
    5655    // /* do form factor calculations  */ 
    … …  
    103102} 
    104103 
    105 int calculate_psfs(double qval, 
     104void calculate_psfs(double qval, 
    106105    double r2, double nf2, 
    107106    double aa, double phi, 
    … …  
    112111     
    113112    //   calculate constant terms 
    114     double s1,s2,v,a3,v1,v2,g11,g12,g22,wmv,wmv3,wmv4; 
     113    double s2,v,a3,v1,v2,g11,g12,g22,wmv,wmv3,wmv4; 
    115114    double a1,a2i,a2,b1,b2,b12,gm1,gm12; 
    116     double err=0.0,yy,ay,ay2,ay3,t1,t2,t3,f11,y2,y3,tt1,tt2,tt3; 
     115    double yy,ay,ay2,ay3,t1,t2,t3,f11,y2,y3,tt1,tt2,tt3; 
    117116    double c11,c22,c12,f12,f22,ttt1,ttt2,ttt3,ttt4,yl,y13; 
    118117    double t21,t22,t23,t31,t32,t33,t41,t42,yl3,wma3,y1; 
    119118     
    120119    s2 = 2.0*r2; 
    121     s1 = aa*s2; 
     120//    s1 = aa*s2;  why is this never used?  check original paper? 
    122121    v = phi; 
    123122    a3 = aa*aa*aa; 
    … …  
    189188    *s12=-c12/((1.+c11)*(1.+c22)-(c12)*(c12));    
    190189     
    191     return(err); 
     190    return; 
    192191} 
    193192 

  • sasmodels/models/binary_hard_sphere.py

    r115d0f0 rd189429  
    11r""" 
    22 
     3Definition 
     4---------- 
    35The binary hard sphere model provides the scattering intensity, for binary 
    46mixture of hard spheres including hard sphere interaction between those 
    57particles, using rhw Percus-Yevick closure. The calculation is an exact 
    68multi-component solution that properly accounts for the 3 partial structure 
    7 factors. 
    8  
    9 Definition 
    10 ---------- 
     9factors as follows: 
    1110 
    1211.. math:: 
    1312 
    1413    \begin{eqnarray} 
    15     I(q) = (1-x)f_1^2(q) S_{11}(q) + 2[x(1-x)]^{1/2} f_1(q)f_2(q)S_{12}(q) + \\ 
    16     x\,f_2^2(q)S_{22}(q) \\ 
     14    I(q) = (1-x)f_1^2(q) S_{11}(q) + 2[x(1-x)]^{1/2} f_1(q)f_2(q)S_{12}(q) + 
     15    x\,f_2^2(q)S_{22}(q) 
    1716    \end{eqnarray} 
    1817 
    … …  
    2625 
    2726    \begin{eqnarray} 
    28     x &=& \frac{(\phi_2 / \phi)\alpha^3}{(1-(\phi_2/\phi) + (\phi_2/\phi) \\ 
    29     \alpha^3)} \phi &=& \phi_1 + \phi_2 = \text{total volume fraction} \\ 
     27    x &=& \frac{(\phi_2 / \phi)\alpha^3}{(1-(\phi_2/\phi) + (\phi_2/\phi) 
     28    \alpha^3)} \\ 
     29    \phi &=& \phi_1 + \phi_2 = \text{total volume fraction} \\ 
    3030    \alpha &=& R_1/R_2 = \text{size ratio} 
    3131    \end{eqnarray} 
    … …  
    6767S R Kline, *J Appl. Cryst.*, 39 (2006) 895 
    6868 
    69 **Author:** N/A **on:** 
     69**Author:** NIST IGOR/DANSE **on:** pre 2010 
    7070 
    71 **Modified by:** Paul Butler **on:** March 18, 2016 
     71**Last Modified by:** Paul Butler **on:** March 20, 2016 
    7272 
    73 **Reviewed by:** Paul Butler **on:** March 18, 2016 
     73**Last Reviewed by:** Paul Butler **on:** March 20, 2016 
    7474""" 
    7575 
    76 import numpy as np 
    77 from numpy import pi, inf 
     76from numpy import inf 
     77 
     78category = "shape:sphere" 
     79single = False  # double precision only! 
    7880 
    7981name = "binary_hard_sphere" 
    … …  
    9092        sld_solvent: solvent scattering length density. 
    9193""" 
    92 category = "shape:sphere" 
    93  
    9494#             ["name", "units", default, [lower, upper], "type", "description"], 
    9595parameters = [["radius_lg", "Ang", 100, [0, inf], "", 
    … …  
    112112 
    113113# parameters for demo and documentation 
    114 demo = dict(scale=1, background=0, 
    115             sld_lg=3.5, sld_sm=0.5, sld_solvent=6.36, 
     114demo = dict(sld_lg=3.5, sld_sm=0.5, sld_solvent=6.36, 
    116115            radius_lg=100, radius_sm=20, 
    117116            volfraction_lg=0.1, volfraction_sm=0.2) 
    … …  
    125124 
    126125# NOTE: test results taken from values returned by SasView 3.1.2 
    127 tests = [[{'scale':1.0}, 0.001, 25.8927262013]] 
     126tests = [[{}, 0.001, 25.8927262013]] 
    128127 

  • sasmodels/models/correlation_length.py

    raa2edb2 r0cc31e1  
    1515and therefore the thermodynamics. The two multiplicative factors A and C, the 
    1616incoherent background B and the two exponents n and m are used as fitting 
    17 parameters. The final parameter ξ is a correlation length for the polymer 
    18 chains. Note that when m=2 this functional form becomes the familiar Lorentzian 
    19 function. 
     17parameters. (Respectively $porod\_scale$, $lorentz\_scale$, $background$, $exponent\_p$ and  
     18$exponent\_l$ in the parameter list.) The remaining parameter \ |xi|\  is a correlation  
     19length for the polymer chains. Note that when m=2 this functional form becomes the  
     20familiar Lorentzian function. Some interpretation of the values of A and C may be  
     21possible depending on the values of m and n. 
    2022 
    2123For 2D data: The 2D scattering intensity is calculated in the same way as 1D, 
    … …  
    4547              ["lorentz_scale", "", 10.0, [0, inf], "", "Lorentzian Scaling Factor"], 
    4648              ["porod_scale", "", 1e-06, [0, inf], "", "Porod Scaling Factor"], 
    47               ["cor_length", "Ang", 50.0, [0, inf], "", "Correlation length"], 
    48               ["exponent_p", "", 3.0, [0, inf], "", "Porod Exponent"], 
    49               ["exponent_l", "1/Ang^2", 2.0, [0, inf], "", "Lorentzian Exponent"], 
     49              ["cor_length", "Ang", 50.0, [0, inf], "", "Correlation length, xi, in Lorentzian"], 
     50              ["exponent_p", "", 3.0, [0, inf], "", "Porod Exponent, n, in q^-n"], 
     51              ["exponent_l", "1/Ang^2", 2.0, [0, inf], "", "Lorentzian Exponent, m, in 1/( 1 + (q.xi)^m)"], 
    5052             ] 
    5153# pylint: enable=bad-continuation, line-too-long 

  • sasmodels/models/cylinder.py

    r5933c7f r6ef4293  
    3131To provide easy access to the orientation of the cylinder, we define the 
    3232axis of the cylinder using two angles $\theta$ and $\phi$. Those angles 
    33 are defined in :numref:`figure #<cylinder-angle-definition>`. 
     33are defined in :numref:`cylinder-angle-definition`. 
    3434 
    3535.. _cylinder-angle-definition: 

  • sasmodels/models/elliptical_cylinder.py

    r74fd96f r0cc31e1  
    1212.. figure:: img/elliptical_cylinder_geometry.png 
    1313 
    14    Elliptical cylinder geometry $a$ = $r_{minor}$ and \nu = $axis\_ratio$ = $r_{major} / r_{minor}$ 
     14   Elliptical cylinder geometry $a$ = $r_{minor}$ and \ |nu|\ = $axis\_ratio$ = $r_{major} / r_{minor}$ 
    1515 
    1616The function calculated is 

  • sasmodels/models/fractal.py

    rdff1088 r5e29b9d  
    4646J Teixeira, *J. Appl. Cryst.*, 21 (1988) 781-785 
    4747 
    48 **Author:** N/A **on:** 
     48**Author:** NIST IGOR/DANSE **on:** pre 2010 
    4949 
    5050**Last Modified by:** Paul Butler **on:** March 20, 2016 

  • sasmodels/models/fractal_core_shell.c

    r7d4b2ae r6794301  
    4747    double qr = q*radius; 
    4848 
    49     double t1 = frac_dim*exp(lanczos_gamma(frac_1))*sin(frac_1*atan(q*cor_length)); 
     49    double t1 = frac_dim*sas_gamma(frac_1)*sin(frac_1*atan(q*cor_length)); 
    5050    double t2 = (1.0 + 1.0/(q*cor_length)/(q*cor_length)); 
    5151    double t3 = pow(qr, frac_dim) * pow(t2, (frac_1/2.0)); 

  • sasmodels/models/fractal_core_shell.py

    raa2edb2 r6794301  
    7373# pylint: enable=bad-whitespace, line-too-long 
    7474 
    75 source = ["lib/sph_j1c.c", "lib/lanczos_gamma.c", "lib/core_shell.c", "fractal_core_shell.c"] 
     75source = ["lib/sph_j1c.c", "lib/sas_gamma.c", "lib/core_shell.c", "fractal_core_shell.c"] 
    7676 
    7777demo = dict(scale=0.05, 

  • sasmodels/models/fuzzy_sphere.py

    raa2edb2 r0cc31e1  
    1919 
    2020    A(q) = \frac{3\left[\sin(qR) - qR \cos(qR)\right]}{(qR)^3} 
    21            \exp\left(\frac{-(o_{fuzzy}q)^2}{2}\right) 
     21           \exp\left(\frac{-(\sigma_{fuzzy}q)^2}{2}\right) 
    2222 
    2323Here *|A(q)|*:sup:`2`\  is the form factor, *P(q)*. The scale is equivalent to the 
    … …  
    2626solvent. 
    2727 
    28 Poly-dispersion in radius and in fuzziness is provided for. 
     28Poly-dispersion in radius and in fuzziness is provided for, though the fuzziness 
     29must be kept much smaller than the sphere radius for meaningful results. 
    2930 
    3031 
    … …  
    6566or just volume fraction for absolute scale data 
    6667radius: radius of the solid sphere 
    67 fuzziness = the STD of the height of fuzzy interfacial 
     68fuzziness = the standard deviation of the fuzzy interfacial 
    6869thickness (ie., so-called interfacial roughness) 
    6970sld: the SLD of the sphere 
    … …  
    7677# pylint: disable=bad-whitespace,line-too-long 
    7778# ["name", "units", default, [lower, upper], "type","description"], 
    78 parameters = [["sld",         "1e-6/Ang^2",  1, [-inf, inf], "",       "Layer scattering length density"], 
    79               ["solvent_sld", "1e-6/Ang^2",  3, [-inf, inf], "",       "Solvent scattering length density"], 
     79parameters = [["sld",         "1e-6/Ang^2",  1, [-inf, inf], "",       "Particle scattering length density"], 
     80              ["sld_solvent", "1e-6/Ang^2",  3, [-inf, inf], "",       "Solvent scattering length density"], 
    8081              ["radius",      "Ang",        60, [0, inf],    "volume", "Sphere radius"], 
    81               ["fuzziness",   "Ang",        10, [0, inf],    "",       "The STD of the height of fuzzy interfacial"], 
     82              ["fuzziness",   "Ang",        10, [0, inf],    "",       "std deviation of Gaussian convolution for interface (must be << radius)"], 
    8283             ] 
    8384# pylint: enable=bad-whitespace,line-too-long 
    … …  
    9596    const double bes = sph_j1c(qr); 
    9697    const double qf = q*fuzziness; 
    97     const double fq = bes * (sld - solvent_sld) * form_volume(radius) * exp(-0.5*qf*qf); 
     98    const double fq = bes * (sld - sld_solvent) * form_volume(radius) * exp(-0.5*qf*qf); 
    9899    return 1.0e-4*fq*fq; 
    99100    """ 
    … …  
    102103    // never called since no orientation or magnetic parameters. 
    103104    //return -1.0; 
    104     return Iq(sqrt(qx*qx + qy*qy), sld, solvent_sld, radius, fuzziness); 
     105    return Iq(sqrt(qx*qx + qy*qy), sld, sld_solvent, radius, fuzziness); 
    105106    """ 
    106107 
    … …  
    114115 
    115116demo = dict(scale=1, background=0.001, 
    116             sld=1, solvent_sld=3, 
     117            sld=1, sld_solvent=3, 
    117118            radius=60, 
    118119            fuzziness=10, 
    … …  
    121122 
    122123oldname = "FuzzySphereModel" 
    123 oldpars = dict(sld='sldSph', solvent_sld='sldSolv', radius='radius', fuzziness='fuzziness') 
     124oldpars = dict(sld='sldSph', sld_solvent='sldSolv', radius='radius', fuzziness='fuzziness') 
    124125 
    125126 

  • sasmodels/models/mass_fractal.c

    r61fd21d r6794301  
    2828    //calculate S(q) 
    2929    double mmo = mass_dim-1.0; 
    30     double sq = exp(lanczos_gamma(mmo))*sin((mmo)*atan(q*cutoff_length)); 
     30    double sq = sas_gamma(mmo)*sin((mmo)*atan(q*cutoff_length)); 
    3131    sq *= pow(cutoff_length, mmo); 
    3232    sq /= pow((1.0 + (q*cutoff_length)*(q*cutoff_length)),(mmo/2.0)); 

  • sasmodels/models/mass_fractal.py

    raa2edb2 r6794301  
    8585# pylint: enable=bad-whitespace, line-too-long 
    8686 
    87 source = ["lib/sph_j1c.c", "lib/lanczos_gamma.c", "mass_fractal.c"] 
     87source = ["lib/sph_j1c.c", "lib/sas_gamma.c", "mass_fractal.c"] 
    8888 
    8989demo = dict(scale=1, background=0, 

  • sasmodels/models/parallelepiped.py

    r5933c7f r6ef4293  
    77---------- 
    88 
    9 | This model calculates the scattering from a rectangular parallelepiped (:numref:`Figure #<parallelepiped-image>`). 
     9| This model calculates the scattering from a rectangular parallelepiped (:numref:`parallelepiped-image`). 
    1010| If you need to apply polydispersity, see also :ref:`rectangular-prism`. 
    1111 

  • sasmodels/models/raspberry.c

    rbad8b12 ra2d8a67  
    2121double Iq(double q, 
    2222          double sld_lg, double sld_sm, double sld_solvent, 
    23           double volfraction_lg, double volfraction_sm, double surf_fraction, 
     23          double volfraction_lg, double volfraction_sm, double surface_fraction, 
    2424          double radius_lg, double radius_sm, double penetration) 
    2525{ 
    … …  
    3737    sldL = sld_lg; 
    3838    vfS = volfraction_sm; 
     39    fSs = surface_fraction; 
    3940    rS = radius_sm; 
    40     aSs = surf_fraction; 
    4141    sldS = sld_sm; 
    4242    deltaS = penetration; 
    … …  
    4848    VL = M_4PI_3*rL*rL*rL; 
    4949    VS = M_4PI_3*rS*rS*rS; 
    50     Np = aSs*4.0*pow(((rL+deltaS)/rS), 2.0); 
    51     fSs = Np*vfL*VS/vfS/VL; 
    52      
    53     Np2 = aSs*4.0*(rS/(rL+deltaS))*VL/VS;  
    54     fSs2 = Np2*vfL*VS/vfS/VL; 
     50 
     51    //Number of small particles per large particle 
     52    Np = vfS*fSs*VL/vfL/VS; 
     53 
     54    //Total scattering length difference 
    5555    slT = delrhoL*VL + Np*delrhoS*VS; 
    5656 
    57     sfLS = sph_j1c(q*rL)*sph_j1c(q*rS)*sinc(q*(rL+deltaS*rS)); 
    58     sfSS = sph_j1c(q*rS)*sph_j1c(q*rS)*sinc(q*(rL+deltaS*rS))*sinc(q*(rL+deltaS*rS)); 
    59          
    60     f2 = delrhoL*delrhoL*VL*VL*sph_j1c(q*rL)*sph_j1c(q*rL);  
    61     f2 += Np2*delrhoS*delrhoS*VS*VS*sph_j1c(q*rS)*sph_j1c(q*rS);  
    62     f2 += Np2*(Np2-1)*delrhoS*delrhoS*VS*VS*sfSS;  
    63     f2 += 2*Np2*delrhoL*delrhoS*VL*VS*sfLS; 
     57    //Form factors for each particle 
     58    psiL = sph_j1c(q*rL); 
     59    psiS = sph_j1c(q*rS); 
     60 
     61    //Cross term between large and small particles 
     62    sfLS = psiL*psiS*sinc(q*(rL+deltaS*rS)); 
     63    //Cross term between small particles at the surface 
     64    sfSS = psiS*psiS*sinc(q*(rL+deltaS*rS))*sinc(q*(rL+deltaS*rS)); 
     65 
     66    //Large sphere form factor term 
     67    f2 = delrhoL*delrhoL*VL*VL*psiL*psiL; 
     68    //Small sphere form factor term 
     69    f2 += Np*delrhoS*delrhoS*VS*VS*psiS*psiS; 
     70    //Small particle - small particle cross term 
     71    f2 += Np*(Np-1)*delrhoS*delrhoS*VS*VS*sfSS; 
     72    //Large-small particle cross term 
     73    f2 += 2*Np*delrhoL*delrhoS*VL*VS*sfLS; 
     74    //Normalise by total scattering length difference 
    6475    if (f2 != 0.0){ 
    6576        f2 = f2/slT/slT; 
    6677        } 
    6778 
    68     f2 = f2*(vfL*delrhoL*delrhoL*VL + vfS*fSs2*Np2*delrhoS*delrhoS*VS); 
    69  
    70     f2+= vfS*(1.0-fSs)*pow(delrhoS, 2)*VS*sph_j1c(q*rS)*sph_j1c(q*rS); 
     79    //I(q) for large-small composite particles 
     80    f2 = f2*(vfL*delrhoL*delrhoL*VL + vfS*fSs*Np*delrhoS*delrhoS*VS); 
     81    //I(q) for free small particles 
     82    f2+= vfS*(1.0-fSs)*delrhoS*delrhoS*VS*psiS*psiS; 
    7183     
    7284    // normalize to single particle volume and convert to 1/cm 

  • sasmodels/models/raspberry.py

    rbad8b12 r5745f0b  
    33---------- 
    44 
    5 The large and small spheres have their own SLD, as well as the solvent. The 
    6 surface coverage term is a fractional coverage (maximum of approximately 0.9 
    7 for hexagonally-packed spheres on a surface). Since not all of the small 
    8 spheres are necessarily attached to the surface, the excess free (small) 
    9 spheres scattering is also included in the calculation. The function calculate 
    10 follows equations (8)-(12) of the reference below, and the equations are not 
    11 reproduced here. 
    12  
    13 No inter-particle scattering is included in this model. 
    14  
     5The figure below shows a schematic of a large droplet surrounded by several smaller particles 
     6forming a structure similar to that of Pickering emulsions. 
    157 
    168.. figure:: img/raspberry_geometry.jpg 
    179 
    1810    Schematic of the raspberry model 
    19      
    20 where *Ro* is the radius of the large sphere, *Rp* the radius of the smaller  
    21 spheres on the surface and |delta| = the fractional penetration depth. 
    2211 
    23 For 2D data: The 2D scattering intensity is calculated in the same way as 1D, 
    24 where the *q* vector is defined as 
     12In order to calculate the form factor of the entire complex, the self-correlation of the large droplet, 
     13the self-correlation of the particles, the correlation terms between different particles 
     14and the cross terms between large droplet and small particles all need to be calculated. 
     15 
     16Consider two infinitely thin shells of radii R2 and R2 separated by distance r. The general 
     17structure of the equation is then the form factor of the two shells multiplied by the phase 
     18factor that accounts for the separation of their centers. 
    2519 
    2620.. math:: 
    2721 
    28     q = \sqrt{q_x^2 + q_y^2} 
     22    S(q) = \frac{sin(qR_1)}{qR_1}\frac{sin(qR_2)}{qR_2}\frac{sin(qr)}{qr} 
     23 
     24In this case, the large droplet and small particles are solid spheres rather than thin shells. Thus 
     25the two terms must be integrated over $R_L$ and $R_S$ respectively using the weighting function of 
     26a sphere. We then obtain the functions for the form of the two spheres: 
     27 
     28.. math:: 
     29 
     30    \Psi_L = \int_0^{R_L}(4\pi R^2_L)\frac{sin(qR_L)}{qR_L}dR_L = \frac{3[sin(qR_L)-qR_Lcos(qR_L)]}{(qR_L)^2} 
     31 
     32.. math:: 
     33 
     34    \Psi_S = \int_0^{R_S}(4\pi R^2_S)\frac{sin(qR_S)}{qR_S}dR_S = \frac{3[sin(qR_S)-qR_Lcos(qR_S)]}{(qR_S)^2} 
     35 
     36The cross term between the large droplet and small particles is given by: 
     37 
     38.. math:: 
     39    S_{LS} = \Psi_L\Psi_S\frac{sin(q(R_L+\delta R_S))}{q(R_L+\delta\ R_S)} 
     40 
     41and the self term between small particles is given by: 
     42 
     43.. math:: 
     44    S_{SS} = \Psi_S^2\bigl[\frac{sin(q(R_L+\delta R_S))}{q(R_L+\delta\ R_S)}\bigr]^2 
     45 
     46The number of small particles per large droplet, $N_p$, is given by: 
     47 
     48.. math:: 
     49 
     50    N_p = \frac{\phi_S\phi_{surface}V_L}{\phi_L V_S} 
     51 
     52where $\phi_S$ is the volume fraction of small particles in the sample, $\phi_{surface}$ is the 
     53fraction of the small particles that are adsorbed to the large droplets, $\phi_L$ is the volume fraction 
     54of large droplets in the sample, and $V_S$ and $V_L$ are the volumes of individual small particles and 
     55large droplets respectively. 
     56 
     57The form factor of the entire complex can now be calculated including the excess scattering length 
     58densities of the components $\Delta\rho_L$ and $\Delta\rho_S$, where $\Delta\rho_x = |\rho_x-\rho_{solvent}|$ : 
     59 
     60.. math:: 
     61 
     62    P_{LS} = \frac{1}{M^2}\bigl[(\Delta\rho_L)^2V_L^2\Psi_L^2+N_p(\Delta\rho_S)^2V_S^2\Psi_S^2 
     63                + N_p(1-N_p)(\Delta\rho_S)^2V_S^2S_{SS} + 2N_p\Delta\rho_L\Delta\rho_SV_LV_SS_{LS} 
     64 
     65where M is the total scattering length of the whole complex : 
     66 
     67.. math:: 
     68    M = \Delta\rho_LV_L + N_p\Delta\rho_SV_S 
     69 
     70In a real system, there will ususally be an excess of small particles such that some fraction remain unbound. 
     71Therefore the overall scattering intensity is given by: 
     72 
     73.. math:: 
     74    I(Q) = I_{LS}(Q) + I_S(Q) = (\phi_L(\Delta\rho_L)^2V_L + \phi_S\phi_{surface}N_p(\Delta\rho_S)^2V_S)P_{LS} 
     75            + \phi_S(1-\phi_{surface})(\Delta\rho_S)^2V_S\Psi_S^2 
     76 
     77A useful parameter to extract is the fraction of the surface area of the large droplets that is covered by small 
     78particles. This can be calculated from the model parameters as: 
     79 
     80.. math:: 
     81    \chi = \frac{4\phi_L\phi_{surface}(R_L+\delta R_S)}{\phi_LR_S} 
    2982 
    3083 
    … …  
    3588*particles*, *Journal of Colloid and Interface Science*, 343(1) (2010) 36-41 
    3689 
    37 **Author:** Andrew jackson **on:** 2008 
     90**Author:** Andrew Jackson **on:** 2008 
    3891 
    39 **Modified by:** Paul Butler **on:** March 18, 2016 
     92**Modified by:** Andrew Jackson **on:** March 20, 2016 
    4093 
    41 **Reviewed by:** Paul Butler **on:** March 18, 2016 
     94**Reviewed by:** Andrew Jackson **on:** March 20, 2016 
    4295""" 
    4396 
    … …  
    50103description = """ 
    51104                RaspBerryModel: 
    52                 volf_Lsph = volume fraction large spheres 
    53                 radius_Lsph = radius large sphere (A) 
    54                 sld_Lsph = sld large sphere (A-2) 
    55                 volf_Ssph = volume fraction small spheres 
    56                 radius_Ssph = radius small sphere (A) 
    57                 surfrac_Ssph = fraction of small spheres at surface 
    58                 sld_Ssph = sld small sphere 
    59                 delta_Ssph = small sphere penetration (A)  
    60                 sld_solv   = sld solvent 
     105                volfraction_lg = volume fraction large spheres 
     106                radius_lg = radius large sphere (A) 
     107                sld_lg = sld large sphere (A-2) 
     108                volfraction_sm = volume fraction small spheres 
     109                radius_sm = radius small sphere (A) 
     110                surface_fraction = fraction of small spheres at surface 
     111                sld_sm = sld small sphere 
     112                penetration = small sphere penetration (A) 
     113                sld_solvent   = sld solvent 
    61114                background = background (cm-1) 
    62115            Ref: J. coll. inter. sci. (2010) vol. 343 (1) pp. 36-41.""" 
    … …  
    74127              ["volfraction_sm", "", 0.005, [-inf, inf], "", 
    75128               "volume fraction of small spheres"], 
    76               ["surf_fraction", "", 0.4, [-inf, inf], "", 
     129              ["surface_fraction", "", 0.4, [-inf, inf], "", 
    77130               "fraction of small spheres at surface"], 
    78131              ["radius_lg", "Ang", 5000, [0, inf], "volume", 
    … …  
    80133              ["radius_sm", "Ang", 100, [0, inf], "", 
    81134               "radius of small spheres"], 
    82               ["penetration", "Ang", 0.0, [0, inf], "", 
    83                "penetration depth of small spheres into large sphere"], 
     135              ["penetration", "Ang", 0, [-1, 1], "", 
     136               "fractional penetration depth of small spheres into large sphere"], 
    84137             ] 
    85138 
    … …  
    89142demo = dict(scale=1, background=0.001, 
    90143            sld_lg=-0.4, sld_sm=3.5, sld_solvent=6.36, 
    91             volfraction_lg=0.05, volfraction_sm=0.005, surf_fraction=0.4, 
     144            volfraction_lg=0.05, volfraction_sm=0.005, surface_fraction=0.4, 
    92145            radius_lg=5000, radius_sm=100, penetration=0.0, 
    93146            radius_lg_pd=.2, radius_lg_pd_n=10) 
    … …  
    95148# For testing against the old sasview models, include the converted parameter 
    96149# names and the target sasview model name. 
    97 oldname = 'RaspBerryModel' 
    98 oldpars = dict(sld_lg='sld_Lsph', sld_sm='sld_Ssph', sld_solvent='sld_solv', 
    99                volfraction_lg='volf_Lsph', volfraction_sm='volf_Ssph', 
    100                surf_fraction='surfrac_Ssph', 
    101                radius_lg='radius_Lsph', radius_sm='radius_Ssph', 
    102                penetration='delta_Ssph') 
    103  
    104150 
    105151# NOTE: test results taken from values returned by SasView 3.1.2, with 

  • sasmodels/models/surface_fractal.c

    r9c461c7 r6794301  
    2626    //calculate S(q) 
    2727    mmo = 5.0 - surface_dim; 
    28     sq  = exp(lanczos_gamma(mmo))*sin(-(mmo)*atan(q*cutoff_length)); 
     28    sq  = sas_gamma(mmo)*sin(-(mmo)*atan(q*cutoff_length)); 
    2929    sq *= pow(cutoff_length, mmo); 
    3030    sq /= pow((1.0 + (q*cutoff_length)*(q*cutoff_length)),(mmo/2.0)); 

  • sasmodels/models/surface_fractal.py

    raa2edb2 r6794301  
    8787# pylint: enable=bad-whitespace, line-too-long 
    8888 
    89 source = ["lib/sph_j1c.c", "lib/lanczos_gamma.c", "surface_fractal.c"] 
     89source = ["lib/sph_j1c.c", "lib/sas_gamma.c", "surface_fractal.c"] 
    9090 
    9191demo = dict(scale=1, background=0, 

  • sasmodels/models/triaxial_ellipsoid.py

    r5933c7f r6ef4293  
    3636we define the axis of the cylinder using the angles $\theta$, $\phi$ 
    3737and $\psi$. These angles are defined on 
    38 :numref:`figure #<triaxial-ellipsoid-angles>`. 
     38:numref:`triaxial-ellipsoid-angles`. 
    3939The angle $\psi$ is the rotational angle around its own $c$ axis 
    4040against the $q$ plane. For example, $\psi = 0$ when the 

  • sasmodels/models/vesicle.c

    r321736f r062db5a  
    22 
    33double Iq(double q,  
    4           double sld, double solvent_sld, 
     4          double sld, double sld_solvent, double volfraction, 
    55          double radius, double thickness); 
    66 
    77double Iqxy(double qx, double qy, 
    8           double sld, double solvent_sld, 
     8          double sld, double sld_solvent, double volfraction, 
    99          double radius, double thickness); 
    1010 
    … …  
    2020double Iq(double q, 
    2121    double sld, 
    22     double solvent_sld, 
     22    double sld_solvent, 
     23    double volfraction, 
    2324    double radius, 
    2425    double thickness) 
    … …  
    3031*/ 
    3132 
    32 /* 
    33    note that the sph_j1c we are using has been optimized for precision over 
    34    SasView's original implementation. HOWEVER at q==0 that implementation 
    35    set bes=1.0 rather than 0.0 (correct value) on the grounds I believe that  
    36    bes=0.00 causes Iq to have a divide by 0 error (mostly encountered when 
    37    doing a theory curve in 2D?  We should verify this and if necessary fix 
    38      -PDB Feb 7, 2016  
    39 */ 
    4033{ 
    41     double bes,vol,contrast,f,f2; 
     34    double vol,contrast,f,f2; 
    4235 
    4336    // core first, then add in shell 
    44     contrast = solvent_sld-sld; 
    45     bes = sph_j1c(q*radius); 
     37    contrast = sld_solvent-sld; 
    4638    vol = 4.0*M_PI/3.0*radius*radius*radius; 
    47     f = vol*bes*contrast; 
     39    f = vol*sph_j1c(q*radius)*contrast; 
    4840  
    49     //now the shell 
    50     contrast = sld-solvent_sld; 
    51     bes = sph_j1c(q*(radius+thickness)); 
     41    //now the shell. No volume normalization as this is done by the caller 
     42    contrast = sld-sld_solvent; 
    5243    vol = 4.0*M_PI/3.0*(radius+thickness)*(radius+thickness)*(radius+thickness); 
    53     f += vol*bes*contrast; 
     44    f += vol*sph_j1c(q*(radius+thickness))*contrast; 
    5445 
    55     //rescale to [cm-1]. No volume normalization as this is done by the caller 
    56     f2 = f*f*1.0e-4; 
     46    //rescale to [cm-1].  
     47    f2 = volfraction*f*f*1.0e-4; 
    5748     
    5849    return(f2); 
    … …  
    6152 
    6253double Iqxy(double qx, double qy, 
    63           double sld, double solvent_sld, 
     54          double sld, double sld_solvent, double volfraction, 
    6455          double radius, double thickness) 
    6556           
    … …  
    6758    double q = sqrt(qx*qx + qy*qy); 
    6859    return Iq(q, 
    69         sld, solvent_sld, 
     60        sld, sld_solvent, volfraction, 
    7061        radius,thickness); 
    7162 

  • sasmodels/models/vesicle.py

    raa2edb2 r062db5a  
    77.. math:: 
    88 
    9     P(q) = \frac{\text{scale}}{V_\text{shell}} \left[ 
     9    P(q) = \frac{\phi}{V_\text{shell}} \left[ 
    1010           \frac{3V_{\text{core}}({\rho_{\text{solvent}} 
    1111           - \rho_{\text{shell}})j_1(qR_{\text{core}})}}{qR_{\text{core}}} 
    … …  
    1515 
    1616 
    17 where scale is a scale factor equivalent to the volume fraction of shell 
    18 material if the data is on an absolute scale, $V_{shell}$ is the volume of the 
    19 shell, $V_{\text{cor}}$ is the volume of the core, $V_{\text{tot}}$ is the 
    20 total volume, $R_{\text{core}}$ is the radius of the core, $R_{\text{tot}}$ is 
    21 the outer radius of the shell, $\rho_{\text{solvent}}$ is the scattering length 
    22 density of the solvent (which is the same as for the core in this case), 
     17where $\phi$ is the volume fraction of shell material, $V_{shell}$ is the volume 
     18of the shell, $V_{\text{cor}}$ is the volume of the core, $V_{\text{tot}}$ is 
     19the total volume, $R_{\text{core}}$ is the radius of the core, $R_{\text{tot}}$ 
     20is the outer radius of the shell, $\rho_{\text{solvent}}$ is the scattering 
     21length density of the solvent (which is the same as for the core in this case), 
    2322$\rho_{\text{scale}}$ is the scattering length density of the shell, background 
    2423is a flat background level (due for example to incoherent scattering in the 
    … …  
    5655A Guinier and G. Fournet, *Small-Angle Scattering of X-Rays*, John Wiley and 
    5756Sons, New York, (1955) 
     57 
     58**Author:** NIST IGOR/DANSE **on:** pre 2010 
     59 
     60**Last Modified by:** Paul Butler **on:** March 20, 2016 
     61 
     62**Last Reviewed by:** Paul Butler **on:** March 20, 2016 
    5863""" 
    5964 
    … …  
    7075        thickness: the shell thickness 
    7176        sld: the shell SLD 
    72         solvent_sld: the solvent (and core) SLD 
     77        sld_slovent: the solvent (and core) SLD 
    7378        background: incoherent background 
    74         scale : scale factor = shell volume fraction if on absolute scale""" 
     79        volfraction: shell volume fraction 
     80        scale : scale factor = 1 if on absolute scale""" 
    7581category = "shape:sphere" 
    7682 
    … …  
    7884parameters = [["sld", "1e-6/Ang^2", 0.5, [-inf, inf], "", 
    7985               "vesicle shell scattering length density"], 
    80               ["solvent_sld", "1e-6/Ang^2", 6.36, [-inf, inf], "", 
     86              ["sld_solvent", "1e-6/Ang^2", 6.36, [-inf, inf], "", 
    8187               "solvent scattering length density"], 
     88              ["volfraction", "", 0.05, [0, 1.0], "", 
     89               "volume fraction of shell"], 
    8290              ["radius", "Ang", 100, [0, inf], "volume", 
    8391               "vesicle core radius"], 
    … …  
    114122 
    115123# parameters for demo 
    116 demo = dict(scale=1, background=0, 
    117             sld=0.5, solvent_sld=6.36, 
     124demo = dict(sld=0.5, sld_solvent=6.36, 
     125            volfraction=0.05, 
    118126            radius=100, thickness=30, 
    119127            radius_pd=.2, radius_pd_n=10, 
    … …  
    123131# names and the target sasview model name. 
    124132oldname = 'VesicleModel' 
    125 oldpars = dict(sld='shell_sld', solvent_sld='solv_sld') 
     133oldpars = dict(sld='shell_sld', sld_solvent='solv_sld') 
    126134 
    127135 
    128136# NOTE: test results taken from values returned by SasView 3.1.2, with 
    129137# 0.001 added for a non-zero default background. 
    130 tests = [[{}, 0.0010005303255, 17139.8278799], 
    131          [{}, 0.200027832249, 0.131387268704], 
     138tests = [[{}, 0.0005, 859.916526646], 
     139         [{}, 0.100600200401, 1.77063682331], 
     140         [{}, 0.5, 0.00355351388906], 
    132141         [{}, 'ER', 130.], 
    133142         [{}, 'VR', 0.54483386436], 

  • sasmodels/resolution.py

    r2f63032 r8b935d1  
    689689        self.pars = TEST_PARS_PINHOLE_SPHERE 
    690690        from sasmodels import core 
    691         from sasmodels.models import sphere 
    692         self.model = core.load_model(sphere, dtype='double') 
     691        self.model = core.load_model("sphere", dtype='double') 
    693692 
    694693    def _eval_sphere(self, pars, resolution): 

  • sasmodels/sesans.py

    rd554bd7 ra154ad16  
    2626    q_max is determined by the acceptance angle of the SESANS instrument. 
    2727    """ 
     28    from sas.sascalc.data_util.nxsunit import Converter 
     29 
    2830    q_min = dq = 0.1 * 2*pi / Rmax 
    29     return np.arange(q_min, q_max[0], dq) 
     31    return np.arange(q_min, Converter("1/A")(q_max[0], units=q_max[1]), dq) 
    3032     
    3133def make_all_q(data): 
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