PyFrensieScripts/elastic_mp_cutoff_hybrid.py at master · lkersting/PyFrensieScripts · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
#! /usr/bin/env python
import PyFrensie.Data.Native as Native
import PyFrensie.DataGen.ElectronPhoton as EP
import PyFrensie.Utility as Utility
import PyFrensie.Utility.Prng as Prng
import PyFrensie.Utility.Interpolation as Interpolation
import PyFrensie.MonteCarlo.Collision as Collision
import PyTrilinos.Teuchos as Teuchos
import numpy
import matplotlib.pyplot as plt

datadir = '/home/software/mcnpdata/'
#datadir = '/home/lkersting/frensie/src/packages/test_files/'

source = Teuchos.FileInputSource( datadir + '/cross_sections.xml' )
xml_obj = source.getObject()
cs_list = Teuchos.XMLParameterListReader().toParameterList( xml_obj )

# -------------------------------------------------------------------------- ##
#  Native Data
# -------------------------------------------------------------------------- ##
data_list = cs_list.get( 'H-Native' )
file_name = datadir + data_list.get( 'electroatomic_file_path' )
native_data = Native.ElectronPhotonRelaxationDataContainer( file_name )
energy_grid = native_data.getElectronEnergyGrid()
elastic_energy_grid = native_data.getElasticAngularEnergyGrid()
cs_reduction = native_data.getMomentPreservingCrossSectionReduction()

hybrid_reaction = Collision.createHybridElasticReaction(native_data, 0.9, False, True, 1e-15)
cutoff_reaction = Collision.createCutoffElasticReaction(native_data, 1.0, False, True, 1e-15)
analog_reaction = Collision.createAnalogElasticReaction(native_data, False, True, 1e-15)

hybrid_dist = Collision.createHybridElasticDistribution(native_data, 0.9, False, True, 1e-15)
cutoff_dist = Collision.createCutoffElasticDistribution(native_data, 1.0, False, True, 1e-15)
analog_dist = Collision.createAnalogElasticDistribution(native_data, False, True, 1e-15)

bin_index = 4
energy = elastic_energy_grid[bin_index]
mp_cs_reduction = cs_reduction[bin_index]

cutoff_cs = native_data.getCutoffElasticCrossSection()
moment_cs = native_data.getMomentPreservingCrossSection()
moment_index = native_data.getMomentPreservingCrossSectionThresholdEnergyIndex()

index = 0
for i in range(0, energy_grid.size ):
        if energy_grid[i] <= energy:
            index = i

cut_cs = cutoff_cs[index]
mp_cs = moment_cs[index]
original_mp_cs = mp_cs/mp_cs_reduction

angles = native_data.getCutoffElasticAngles(energy)
pdfs = native_data.getCutoffElasticPDF(energy)
dcs = [None]*len(pdfs)
hybrid_dcs = [None]*len(pdfs)
hybrid_pdfs = [None]*len(pdfs)
hybrid_eval = [None]*len(pdfs)
hybrid_cs = hybrid_reaction.getCrossSection(energy)
cutoff_cdfs = [None]*len(pdfs)
for i in range(0, len(dcs)):
    dcs[i] = pdfs[i]*cut_cs
    hybrid_dcs[i] = hybrid_reaction.getDifferentialCrossSection(energy, angles[i] )
    hybrid_pdfs[i] = hybrid_dist.evaluatePDF(energy, angles[i] )
    hybrid_eval[i] = hybrid_dist.evaluate(energy, angles[i] )
    cutoff_cdfs[i] = cutoff_dist.evaluateCDF(energy, angles[i] )

size = 0
for i in range(0, angles.size ):
        if angles[i] <= 0.9:
            size = i+1

hybrid_angles = [None]*size
hybrid_cdf = [None]*size
for i in range(0, size-1):
    hybrid_angles[i] = angles[i]
    hybrid_cdf[i] = hybrid_dist.evaluateCDF(energy, angles[i] )

hybrid_angles[size-1] = 0.9
hybrid_cdf[size-1] = hybrid_dist.evaluateCDF(energy, hybrid_angles[size-1] )

discrete_angles = native_data.getMomentPreservingElasticDiscreteAngles(energy)
discrete_weights = native_data.getMomentPreservingElasticWeights(energy)

atomic_number = 1
min_electron_energy = 1e-5
max_electron_energy = 1e5
cutoff_angle_cosine = 0.9
tabular_evaluation_tol = 1e-15
linlinlog_interpolation_mode_on = False

hybrid_generator = EP.createMomentPreservingDataGenerator(
                atomic_number,
                native_data,
                min_electron_energy,
                max_electron_energy,
                cutoff_angle_cosine,
                tabular_evaluation_tol,
                linlinlog_interpolation_mode_on )

nodes, weights = hybrid_generator.evaluateDiscreteAnglesAndWeights( energy, 2 )

full_weights = [None] * 6
full_nodes = [None] * 6
full_nodes[0] = nodes[0]
full_nodes[1] = nodes[0]
full_nodes[2] = nodes[1]
full_nodes[3] = nodes[1]
full_nodes[4] = nodes[2]
full_nodes[5] = nodes[2]
full_weights[0] = 1e-12
full_weights[1] = weights[0]
full_weights[2] = weights[0]
full_weights[3] = weights[0] + weights[1]
full_weights[4] = weights[0] + weights[1]
full_weights[5] = weights[0] + weights[1] + weights[2]

cutoff_dist = Collision.createCutoffElasticDistribution(native_data, 0.9, False, True, 1e-14)
cutoff_cdf = cutoff_dist.evaluateCutoffCrossSectionRatio( energy )

cross_section_ratio = cutoff_cs[index]*cutoff_cdf/moment_cs[index-moment_index]
sampling_ratio = cross_section_ratio/(1.0+cross_section_ratio)
weight_0_ratio = (discrete_weights[0] + cross_section_ratio)/(1.0+cross_section_ratio)
weight_1_ratio = (discrete_weights[0] + discrete_weights[1] + cross_section_ratio)/(1.0+cross_section_ratio)


plot_weights = [None] * 5
plot_nodes = [None] * 5
plot_nodes[0] = cutoff_angle_cosine
plot_nodes[1] = discrete_angles[0]
plot_nodes[2] = discrete_angles[0]
plot_nodes[3] = discrete_angles[1]
plot_nodes[4] = discrete_angles[1]

plot_weights[0] = sampling_ratio
plot_weights[1] = sampling_ratio
plot_weights[2] = weight_0_ratio
plot_weights[3] = weight_0_ratio
plot_weights[4] = weight_1_ratio

fig1 = plt.figure(num=1, figsize=(10,5))
plt.xlabel('Angle Cosine', fontsize=15)
plt.ylabel('CDF', fontsize=15)
plt.title('Elastic Scattering Distributions', fontsize=16)
plt.xlim(0.7,1.005)
plt.ylim(5e-3,1.1)
plt.yscale('log')
plt.plot( angles, cutoff_cdfs, marker='o', linestyle='--', linewidth=2, label='Cutoff')
plt.plot( full_nodes, full_weights, marker='o', linestyle='--', linewidth=2, label='MP(0.9)')
plt.plot( hybrid_angles, hybrid_cdf, color='red', marker='o', linestyle='--', linewidth=2, label='Hybrid')
plt.plot( plot_nodes, plot_weights, color='red', marker='o', linestyle='--', linewidth=2)
plt.legend(loc=2)

fig1.savefig('./hybrid_cdf.pdf', bbox_inches='tight')

plt.show()