1 | #!/usr/bin/env python |
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2 | """ |
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3 | |
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4 | Provide F(x)= P(x)*S(x) + bkd |
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5 | Fractal as a BaseComponent model |
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6 | """ |
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7 | |
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8 | from sans.models.BaseComponent import BaseComponent |
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9 | import math |
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10 | from scipy.special import gamma |
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11 | |
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12 | class FractalModel(BaseComponent): |
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13 | |
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14 | """ |
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15 | Class that evaluates a Fractal function. |
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16 | |
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17 | F(x)= P(x)*S(x) + bkd |
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18 | The model has Seven parameters: |
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19 | scale = Volume fraction |
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20 | radius = Block radius |
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21 | fractal_dim = Fractal dimension |
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22 | corr_length = correlation Length |
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23 | block_sld = SDL block |
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24 | solvent_sld = SDL solvent |
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25 | background = background |
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26 | |
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27 | """ |
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28 | |
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29 | def __init__(self): |
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30 | """ Initialization """ |
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31 | |
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32 | # Initialize BaseComponent first, then sphere |
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33 | BaseComponent.__init__(self) |
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34 | |
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35 | ## Name of the model |
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36 | self.name = "Number Density Fractal" |
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37 | |
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38 | ## Define parameters |
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39 | self.params = {} |
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40 | self.params['scale'] = 0.05 |
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41 | self.params['radius'] = 5.0 |
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42 | self.params['fractal_dim'] = 2.0 |
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43 | self.params['corr_length'] = 100.0 |
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44 | self.params['block_sld'] = 2.0e-6 |
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45 | self.params['solvent_sld'] = 6.0e-6 |
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46 | self.params['background'] = 0.0 |
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47 | |
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48 | |
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49 | ## Parameter details [units, min, max] |
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50 | self.details = {} |
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51 | self.details['scale'] = ['', None, None] |
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52 | self.details['radius'] = ['A', None, None] |
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53 | self.details['fractal_dim'] = ['', 0, None] |
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54 | self.details['corr_length'] = ['A', None, None] |
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55 | self.details['block_sld'] = ['A-2', None, None] |
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56 | self.details['solvent_sld'] = ['A-2', None, None] |
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57 | self.details['background'] = ['cm-1', None, None] |
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58 | |
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59 | |
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60 | def _Fractal(self, x): |
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61 | """ |
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62 | Evaluate |
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63 | F(x) = p(x) * s(x) + bkd |
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64 | """ |
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65 | if x<0 and self.params['fractal_dim']>0: |
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66 | raise ValueError, "negative number cannot be raised to a fractional power" |
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67 | |
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68 | return self.params['background']+ self._scatterRanDom(x)* self._Block(x) |
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69 | |
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70 | |
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71 | def _Block(self,x): |
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72 | return 1.0 + (math.sin((self.params['fractal_dim']-1.0) * math.atan(x * self.params['corr_length']))\ |
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73 | * self.params['fractal_dim'] * gamma(self.params['fractal_dim']-1.0))\ |
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74 | /( math.pow( (x*self.params['radius']), self.params['fractal_dim'])*\ |
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75 | math.pow( 1.0 + 1.0/((x**2)*(self.params['corr_length']**2)),(self.params['fractal_dim']-1.0)/2.0)) |
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76 | |
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77 | def _Spherical(self,x): |
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78 | """ |
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79 | F(x) = 3*[sin(x)-xcos(x)]/x**3 |
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80 | """ |
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81 | return 3.0*(math.sin(x)-x*math.cos(x))/(math.pow(x,3.0)) |
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82 | |
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83 | def _scatterRanDom(self,x): |
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84 | """ |
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85 | calculate p(x)= scale* V^(2)*delta^(2)* F(x*Radius)^(2) |
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86 | """ |
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87 | V =(4.0/3.0)*math.pi* math.pow(self.params['radius'],3.0) |
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88 | delta = self.params['block_sld']-self.params['solvent_sld'] |
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89 | |
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90 | return 1.0e8*self.params['scale']* V *(delta**2)*\ |
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91 | (self._Spherical(x*self.params['radius'])**2) |
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92 | |
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93 | def run(self, x = 0.0): |
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94 | """ Evaluate the model |
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95 | @param x: input q-value (float or [float, float] as [r, theta]) |
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96 | @return: (Fractal value) |
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97 | """ |
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98 | if x.__class__.__name__ == 'list': |
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99 | # Take absolute value of Q, since this model is really meant to |
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100 | # be defined in 1D for a given length of Q |
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101 | #qx = math.fabs(x[0]*math.cos(x[1])) |
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102 | #qy = math.fabs(x[0]*math.sin(x[1])) |
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103 | |
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104 | return self._Fractal(math.fabs(x[0])) |
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105 | elif x.__class__.__name__ == 'tuple': |
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106 | raise ValueError, "Tuples are not allowed as input to BaseComponent models" |
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107 | else: |
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108 | return self._Fractal(x) |
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109 | |
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110 | def runXY(self, x = 0.0): |
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111 | """ Evaluate the model |
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112 | @param x: input q-value (float or [float, float] as [qx, qy]) |
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113 | @return: Fractal value |
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114 | """ |
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115 | if x.__class__.__name__ == 'list': |
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116 | q = math.sqrt(x[0]**2 + x[1]**2) |
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117 | return self._Fractal(q) |
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118 | elif x.__class__.__name__ == 'tuple': |
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119 | raise ValueError, "Tuples are not allowed as input to BaseComponent models" |
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120 | else: |
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121 | return self._Fractal(x) |
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