1 | # Note: model title and parameter table are inserted automatically |
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2 | r"""Calculate the interparticle structure factor for monodisperse |
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3 | spherical particles interacting through hard sphere (excluded volume) |
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4 | interactions. |
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5 | |
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6 | The calculation uses the Percus-Yevick closure where the interparticle |
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7 | potential is |
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8 | |
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9 | .. math:: |
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10 | |
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11 | U(r) = \begin{cases} |
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12 | \infty & r < 2R \\ |
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13 | 0 & r \geq 2R |
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14 | \end{cases} |
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15 | |
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16 | where $r$ is the distance from the center of the sphere of a radius $R$. |
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17 | |
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18 | For a 2D plot, the wave transfer is defined as |
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19 | |
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20 | .. math:: |
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21 | |
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22 | q = \sqrt{q_x^2 + q_y^2} |
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23 | |
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24 | |
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25 | .. figure:: img/hardSphere_1d.jpg |
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26 | |
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27 | 1D plot using the default values (in linear scale). |
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28 | |
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29 | References |
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30 | ---------- |
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31 | |
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32 | J K Percus, J Yevick, *J. Phys. Rev.*, 110, (1958) 1 |
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33 | """ |
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34 | |
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35 | from numpy import inf |
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36 | |
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37 | name = "hardsphere" |
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38 | title = "Hard sphere structure factor, with Percus-Yevick closure" |
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39 | description = """\ |
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40 | [Hard sphere structure factor, with Percus-Yevick closure] |
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41 | Interparticle S(Q) for random, non-interacting spheres. |
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42 | May be a reasonable approximation for other shapes of |
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43 | particles that freely rotate, and for moderately polydisperse |
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44 | systems. Though strictly the maths needs to be modified - |
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45 | which sasview does not do yet. |
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46 | effect_radius is the hard sphere radius |
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47 | volfraction is the volume fraction occupied by the spheres. |
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48 | """ |
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49 | category = "structure-factor" |
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50 | structure_factor = True |
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51 | |
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52 | # ["name", "units", default, [lower, upper], "type","description"], |
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53 | parameters = [["effect_radius", "Ang", 50.0, [0, inf], "volume", |
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54 | "effective radius of hard sphere"], |
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55 | ["volfraction", "", 0.2, [0, 0.74], "", |
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56 | "volume fraction of hard spheres"], |
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57 | ] |
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58 | |
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59 | # No volume normalization despite having a volume parameter |
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60 | # This should perhaps be volume normalized? |
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61 | form_volume = """ |
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62 | return 1.0; |
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63 | """ |
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64 | |
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65 | Iq = """ |
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66 | double D,A,B,G,X,X2,X4,S,C,FF,HARDSPH; |
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67 | |
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68 | if(fabs(effect_radius) < 1.E-12) { |
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69 | HARDSPH=1.0; |
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70 | return(HARDSPH); |
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71 | } |
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72 | // removing use of pow(xxx,2) and rearranging the calcs of A, B & G cut ~40% off execution time ( 0.5 to 0.3 msec) |
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73 | X = 1.0/( 1.0 -volfraction); |
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74 | D= X*X; |
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75 | A= (1.+2.*volfraction)*D; |
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76 | A *=A; |
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77 | X=fabs(q*effect_radius*2.0); |
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78 | |
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79 | if(X < 5.E-06) { |
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80 | HARDSPH=1./A; |
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81 | return(HARDSPH); |
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82 | } |
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83 | X2 =X*X; |
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84 | B = (1.0 +0.5*volfraction)*D; |
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85 | B *= B; |
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86 | B *= -6.*volfraction; |
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87 | G=0.5*volfraction*A; |
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88 | |
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89 | if(X < 0.2) { |
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90 | // RKH Feb 2016, use Taylor series expansion for small X, IT IS VERY PICKY ABOUT THE X CUT OFF VALUE, ought to be lower in double. |
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91 | // else no obvious way to rearrange the equations to avoid needing a very high number of significant figures. |
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92 | // Series expansion found using Mathematica software. Numerical test in .xls showed terms to X^2 are sufficient |
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93 | // for 5 or 6 significant figures, but I put the X^4 one in anyway |
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94 | //FF = 8*A +6*B + 4*G - (0.8*A +2.0*B/3.0 +0.5*G)*X2 +(A/35. +B/40. +G/50.)*X4; |
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95 | // refactoring the polynomial makes it very slightly faster (0.5 not 0.6 msec) |
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96 | //FF = 8*A +6*B + 4*G + ( -0.8*A -2.0*B/3.0 -0.5*G +(A/35. +B/40. +G/50.)*X2)*X2; |
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97 | |
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98 | FF = 8.0*A +6.0*B + 4.0*G + ( -0.8*A -B/1.5 -0.5*G +(A/35. +0.0125*B +0.02*G)*X2)*X2; |
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99 | |
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100 | // combining the terms makes things worse at smallest Q in single precision |
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101 | //FF = (8-0.8*X2)*A +(3.0-X2/3.)*2*B + (4+0.5*X2)*G +(A/35. +B/40. +G/50.)*X4; |
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102 | // note that G = -volfraction*A/2, combining this makes no further difference at smallest Q |
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103 | //FF = (8 +2.*volfraction + ( volfraction/4. -0.8 +(volfraction/100. -1./35.)*X2 )*X2 )*A + (3.0 -X2/3. +X4/40.)*2.*B; |
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104 | HARDSPH= 1./(1. + volfraction*FF ); |
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105 | return(HARDSPH); |
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106 | } |
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107 | X4=X2*X2; |
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108 | SINCOS(X,S,C); |
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109 | |
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110 | // RKH Feb 2016, use version FISH code as is better than original sasview one at small Q in single precision, and more than twice as fast in double. |
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111 | //FF=A*(S-X*C)/X + B*(2.*X*S -(X2-2.)*C -2.)/X2 + G*( (4.*X2*X -24.*X)*S -(X4 -12.*X2 +24.)*C +24. )/X4; |
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112 | // refactoring the polynomial here & above makes it slightly faster |
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113 | |
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114 | FF= (( G*( (4.*X2 -24.)*X*S -(X4 -12.*X2 +24.)*C +24. )/X2 + B*(2.*X*S -(X2-2.)*C -2.) )/X + A*(S-X*C))/X ; |
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115 | HARDSPH= 1./(1. + 24.*volfraction*FF/X2 ); |
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116 | |
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117 | // changing /X and /X2 to *MX1 and *MX2, no significantg difference? |
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118 | //MX=1.0/X; |
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119 | //MX2=MX*MX; |
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120 | //FF= (( G*( (4.*X2 -24.)*X*S -(X4 -12.*X2 +24.)*C +24. )*MX2 + B*(2.*X*S -(X2-2.)*C -2.) )*MX + A*(S-X*C)) ; |
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121 | //HARDSPH= 1./(1. + 24.*volfraction*FF*MX2*MX ); |
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122 | |
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123 | // grouping the terms, was about same as sasmodels for single precision issues |
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124 | // FF=A*(S/X-C) + B*(2.*S/X - C +2.0*(C-1.0)/X2) + G*( (4./X -24./X3)*S -(1.0 -12./X2 +24./X4)*C +24./X4 ); |
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125 | // HARDSPH= 1./(1. + 24.*volfraction*FF/X2 ); |
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126 | // remove 1/X2 from final line, take more powers of X inside the brackets, stil bad |
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127 | // FF=A*(S/X3-C/X2) + B*(2.*S/X3 - C/X2 +2.0*(C-1.0)/X4) + G*( (4./X -24./X3)*S -(1.0 -12./X2 +24./X4)*C +24./X4 )/X2; |
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128 | // HARDSPH= 1./(1. + 24.*volfraction*FF ); |
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129 | return(HARDSPH); |
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130 | """ |
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131 | |
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132 | Iqxy = """ |
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133 | // never called since no orientation or magnetic parameters. |
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134 | return Iq(sqrt(qx*qx+qy*qy), IQ_PARAMETERS); |
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135 | """ |
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136 | |
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137 | # ER defaults to 0.0 |
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138 | # VR defaults to 1.0 |
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139 | |
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140 | demo = dict(effect_radius=200, volfraction=0.2, effect_radius_pd=0.1, effect_radius_pd_n=40) |
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141 | oldname = 'HardsphereStructure' |
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142 | oldpars = dict() |
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143 | # Q=0.001 is in the Taylor series, low Q part, so add Q=0.1, assuming double precision sasview is correct |
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144 | tests = [ |
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145 | [ {'scale': 1.0, 'background' : 0.0, 'effect_radius' : 50.0, 'volfraction' : 0.2, |
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146 | 'effect_radius_pd' : 0}, [0.001,0.1], [0.209128,0.930587]] |
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147 | ] |
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148 | |
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