[ae3ce4e] | 1 | try: |
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| 2 | from sans.models.prototypes.SimCylinder import SimCylinder |
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| 3 | except: |
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| 4 | print "This test uses the prototypes module." |
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| 5 | |
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| 6 | from sans.models.CylinderModel import CylinderModel |
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| 7 | |
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| 8 | import os, sys |
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| 9 | |
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| 10 | def simulate(filename="simul.txt", npts=500): |
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| 11 | output_file = open(filename, 'w') |
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| 12 | #output_file = open("simul_phi=0_theta=1_57_l=400_r=20_9.txt", 'w') |
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| 13 | |
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| 14 | sim = SimCylinder() |
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| 15 | sim.setParam('scale', 1.0) |
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| 16 | #sim.setParam('length', 100.0) |
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| 17 | #sim.setParam('radius', 40.0) |
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| 18 | sim.setParam('length', 400.0) |
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| 19 | sim.setParam('radius', 20.0) |
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| 20 | sim.setParam('theta', 1.57) |
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| 21 | sim.setParam('phi', 0.0) |
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| 22 | sim.setParam('qmax', 0.2) |
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| 23 | |
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| 24 | output_file.write("<q_value> <ana_value> <sim_value>\n") |
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| 25 | norma = 0 |
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| 26 | for i in range(npts): |
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| 27 | q = 1.0/npts*(i+1) |
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| 28 | |
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| 29 | cyl_val = sim.run(q) |
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| 30 | sim_val = sim.run([q, 0.0]) |
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| 31 | if i==0: |
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| 32 | norma = cyl_val/sim_val |
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| 33 | |
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| 34 | #print q, cyl_val, sim_val, sim_val/cyl_val |
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| 35 | output_file.write("%10g %10g %10g\n" % (q, cyl_val, sim_val*norma)) |
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| 36 | |
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| 37 | output_file.close() |
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| 38 | |
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| 39 | def create_model(): |
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| 40 | sim = SimCylinder() |
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| 41 | sim.setParam('scale', 1.0) |
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| 42 | sim.setParam('length', 100.0) |
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| 43 | sim.setParam('radius', 40.0) |
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| 44 | # simul and simul_2 |
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| 45 | #sim.setParam('theta', 1.57) |
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| 46 | #sim.setParam('phi', 0.0) |
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| 47 | sim.setParam('theta', 0.0) |
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| 48 | sim.setParam('phi', 1.0) |
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| 49 | sim.setParam('qmax', 0.2) |
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| 50 | return sim |
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| 51 | |
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| 52 | def comp(): |
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| 53 | """ |
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| 54 | Simple test that should give 1 for the ratio |
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| 55 | of simulated and analytical |
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| 56 | """ |
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| 57 | sim = create_model() |
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| 58 | |
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| 59 | ana_val = sim.run(.05) |
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| 60 | sim_val = sim.run([0.05, 0]) |
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| 61 | print ana_val, sim_val, ana_val/sim_val |
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| 62 | |
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| 63 | |
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| 64 | # ana_val = sim.run(.05) |
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| 65 | # sim_val = sim.run([0.05, 1]) |
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| 66 | # print ana_val, sim_val, ana_val/sim_val |
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| 67 | |
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| 68 | # sim = create_model() |
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| 69 | # sim.setParam('theta', 1.0) |
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| 70 | # sim.setParam('phi', 1.0) |
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| 71 | # ana_val = sim.run(.05) |
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| 72 | # sim_val = sim.run([0.05, 1]) |
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| 73 | # print ana_val, sim_val, ana_val/sim_val |
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| 74 | |
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| 75 | # sim = create_model() |
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| 76 | # sim.setParam('theta', 1.0) |
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| 77 | # sim.setParam('phi', 2.0) |
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| 78 | # ana_val = sim.run(.05) |
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| 79 | # sim_val = sim.run([0.05, 1]) |
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| 80 | # print ana_val, sim_val, ana_val/sim_val |
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| 81 | |
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| 82 | sim = create_model() |
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| 83 | sim.setParam('theta', 1.0) |
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| 84 | sim.setParam('phi', -2.0) |
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| 85 | ana_val = sim.run(.05) |
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| 86 | sim_val = sim.run([0.15, 1]) |
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| 87 | print ana_val, sim_val, ana_val/sim_val |
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| 88 | |
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| 89 | def add_error_to_file(prefix = "", dir = "output"): |
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| 90 | import os, math |
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| 91 | |
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| 92 | # Open standard deviation file |
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| 93 | std_file = open("%s/std_simul.txt" % dir, 'r') |
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| 94 | std_content = std_file.read() |
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| 95 | std_lines = std_content.split('\n') |
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| 96 | |
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| 97 | std_values = {} |
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| 98 | for line in std_lines: |
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| 99 | if line == std_lines[0]: |
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| 100 | continue |
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| 101 | |
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| 102 | toks = line.split() |
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| 103 | if not len(toks) > 3: |
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| 104 | continue |
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| 105 | |
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| 106 | std_values[toks[0]] = float(toks[2]) |
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| 107 | |
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| 108 | std_file.close() |
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| 109 | |
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| 110 | # Read the files |
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| 111 | |
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| 112 | file_list = os.listdir(dir) |
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| 113 | |
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| 114 | for file in file_list: |
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| 115 | if file.count(prefix)>0: |
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| 116 | print "Reading", file |
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| 117 | |
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| 118 | file_obj = open("%s/%s" % (dir, file), 'r') |
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| 119 | |
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| 120 | # open new file |
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| 121 | file_new = open("%s/error-%s" % (dir, file), 'w') |
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| 122 | file_content = file_obj.read() |
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| 123 | lines = file_content.split('\n') |
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| 124 | for line in lines: |
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| 125 | if line == lines[0]: |
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| 126 | file_new.write(line+'\n') |
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| 127 | continue |
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| 128 | |
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| 129 | toks = line.split() |
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| 130 | |
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| 131 | if not len(toks) == 3: |
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| 132 | file_new.write(line+'\n') |
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| 133 | continue |
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| 134 | |
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| 135 | error = 0 |
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| 136 | if toks[0].lower() in std_values: |
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| 137 | error = float(toks[2]) * std_values[toks[0].lower()] |
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| 138 | |
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| 139 | file_new.write(line+" %10g\n" % error) |
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| 140 | |
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| 141 | file_obj.close() |
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| 142 | file_new.close() |
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| 143 | |
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| 144 | |
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| 145 | |
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| 146 | def std_estimate(prefix = "", dir="output"): |
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| 147 | import os, math |
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| 148 | |
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| 149 | file_list = os.listdir(dir) |
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| 150 | output_file = open("%s/std_simul.txt" % dir, 'w') |
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| 151 | output_file.write("<q_value> <std> <frac>\n") |
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| 152 | values = {} |
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| 153 | |
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| 154 | for file in file_list: |
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| 155 | if file.count(prefix)>0: |
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| 156 | print "Reading", file |
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| 157 | file_obj = open("%s/%s" % (dir, file), 'r') |
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| 158 | file_content = file_obj.read() |
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| 159 | lines = file_content.split('\n') |
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| 160 | for line in lines: |
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| 161 | if line == lines[0]: |
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| 162 | continue |
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| 163 | toks = line.split() |
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| 164 | |
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| 165 | if not len(toks) == 3: |
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| 166 | continue |
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| 167 | |
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| 168 | if toks[0] not in values: |
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| 169 | values[toks[0]] = [] |
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| 170 | |
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| 171 | values[toks[0]].append(float(toks[2])) |
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| 172 | |
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| 173 | q_list = values.keys() |
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| 174 | q_list.sort() |
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| 175 | for q in q_list: |
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| 176 | num = len(values[q]) |
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| 177 | sum = 0 |
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| 178 | mean = 0 |
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| 179 | for val in range(num): |
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| 180 | mean += values[q][val] |
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| 181 | mean /= num |
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| 182 | |
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| 183 | for val in range(num): |
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| 184 | diff = values[q][val] - mean |
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| 185 | sum += diff * diff |
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| 186 | sum /= (num-1) |
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| 187 | #print q, math.sqrt(sum) |
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| 188 | |
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| 189 | output_file.write("%10s %10g %10g %10g\n" % (q, math.sqrt(sum), math.sqrt(sum)/mean, math.sqrt(sum)/mean*100.0)) |
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| 190 | |
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| 191 | output_file.close() |
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| 192 | |
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| 193 | |
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| 194 | # sqrt( 1/(N-1) sum[ (x-mean)**2 ] ) |
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| 195 | |
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| 196 | def test_volume_pts(): |
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| 197 | import random, math, time |
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| 198 | |
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| 199 | print "Generating points" |
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| 200 | pt_list = [] |
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| 201 | for i in range(50000): |
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| 202 | x = random.random() |
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| 203 | y = random.random() |
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| 204 | z = random.random() |
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| 205 | pt_list.append([x, y, z]) |
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| 206 | |
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| 207 | # Compute list of closest distance for each point |
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| 208 | print "Computing distances" |
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| 209 | closest_list = [] |
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| 210 | t_init = time.time() |
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| 211 | |
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| 212 | for i in range(len(pt_list)): |
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| 213 | if math.fmod(i,100)==0: |
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| 214 | print i, time.time()-t_init |
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| 215 | t_init = time.time() |
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| 216 | pt = pt_list[i] |
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| 217 | |
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| 218 | min_dist = -1.0 |
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| 219 | for j in range(i+1, len(pt_list)): |
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| 220 | pt_2 = pt_list[j] |
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| 221 | #print pt_2 |
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| 222 | dx = pt[0]-pt_2[0] |
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| 223 | dy = pt[1]-pt_2[1] |
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| 224 | dz = pt[2]-pt_2[2] |
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| 225 | dist = math.sqrt( dx*dx + dy*dy + dz*dz ) |
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| 226 | if min_dist<0 or dist < min_dist: |
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| 227 | min_dist = dist |
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| 228 | |
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| 229 | closest_list.append(min_dist) |
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| 230 | |
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| 231 | # Analyze list of distances |
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| 232 | print "Analyzing" |
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| 233 | sum = 0 |
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| 234 | for d in closest_list: |
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| 235 | sum += d |
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| 236 | average = sum/len(closest_list) |
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| 237 | |
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| 238 | sum = 0 |
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| 239 | for d in closest_list: |
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| 240 | diff = d - average |
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| 241 | sum += diff*diff |
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| 242 | sum /= len(closest_list) |
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| 243 | |
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| 244 | print "%5g +/- %5g)" % (average, math.sqrt(sum)) |
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| 245 | |
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| 246 | |
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| 247 | |
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| 248 | |
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| 249 | if __name__ == '__main__': |
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| 250 | #test_volume_pts() |
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| 251 | #simulate("simul_phi=0_theta=1_57_l=400_r=20_test.txt") |
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| 252 | #std_estimate("simul_phi=0_theta=1_57_l=400_r=20") |
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| 253 | #add_error_to_file("l=400_r=20.txt") |
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| 254 | |
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| 255 | option = "error" |
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| 256 | |
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| 257 | #if len(sys.argv)>1: |
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| 258 | if len(option)>0: |
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| 259 | if option=="gen": |
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| 260 | ifile = 0 |
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| 261 | for i in range(100): |
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| 262 | ifile += 1 |
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| 263 | #print "simul_qmax=1_phi=0_theta=1_57_l=400_r=20_%g.txt" % ifile |
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| 264 | #simulate("simul_phi=0_theta=1_57_l=400_r=20_%g.txt" % ifile) |
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| 265 | print "simul_qmax=1_phi=0_theta=1_57_l=400_r=20_%g.txt" % ifile |
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| 266 | simulate("output/pt5000/simul_phi=0_theta=1_57_l=400_r=20_%g.txt" % ifile) |
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| 267 | elif option=="comp": |
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| 268 | comp() |
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| 269 | elif option=="std": |
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| 270 | #std_estimate("simul_phi=0_theta=1_57_l=400_r=20") |
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| 271 | std_estimate("simul_phi=0_theta=1_57_l=400_r=20", "output/pt5000") |
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| 272 | elif option=="error": |
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| 273 | #add_error_to_file("l=400_r=20.txt") |
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| 274 | add_error_to_file("l=400_r=20_1.txt", "output/pt5000") |
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| 275 | |
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