1 | #!/usr/bin/env python |
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2 | """ |
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3 | Once submit has finished with the jobs, this function is called to have PUQ |
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4 | process the results. |
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5 | """ |
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6 | from __future__ import print_function |
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7 | import sys |
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8 | import os |
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9 | import numpy as np |
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10 | import h5py |
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11 | import re |
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12 | import puq |
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13 | from puq.jpickle import unpickle |
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14 | import Rappture |
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15 | import StringIO |
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16 | from scipy.spatial import ConvexHull |
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17 | # geometry library |
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18 | from shapely.geometry import Polygon |
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19 | from shapely.ops import unary_union |
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20 | |
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21 | # Redirect stdout and stderr to files for debugging. |
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22 | # Append to the files created in get_params.py |
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23 | sys.stdout = open("uq_debug.out", 'a') |
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24 | sys.stderr = open("uq_debug.err", 'a') |
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25 | |
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26 | |
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27 | # Restore the state of a PUQ session from a HDF5 file. |
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28 | def load_from_hdf5(name): |
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29 | h5 = h5py.File(name, 'r+') |
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30 | sw = unpickle(h5['private/sweep'].value) |
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31 | sw.fname = os.path.splitext(name)[0] |
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32 | h5.close() |
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33 | |
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34 | sw.psweep._sweep = sw |
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35 | |
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36 | if hasattr(sw.psweep, 'reinit'): |
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37 | sw.psweep.reinit() |
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38 | return sw |
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39 | |
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40 | |
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41 | # Plots probability curves |
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42 | def plot_pdf_curve(io, h5, xvals, vname, percent): |
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43 | print('plot_pdf_curve %s %s' % (vname, percent)) |
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44 | # compute upper and lower percentiles |
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45 | pm = (100 - percent)/200.0 |
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46 | pp = 1 - pm |
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47 | |
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48 | label = None |
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49 | |
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50 | # collect data into an array |
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51 | xarr = np.empty(len(xvals[vname])) |
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52 | yp = np.empty(len(xvals[vname])) |
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53 | ym = np.empty(len(xvals[vname])) |
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54 | |
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55 | for vindex in sorted(xvals[vname].keys()): |
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56 | if label is None: |
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57 | label = h5['/output/data/%s[%d]' % (vname, vindex)].attrs['label'] |
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58 | xarr[vindex] = xvals[vname][vindex] |
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59 | yp[vindex] = pcurves[vname][vindex].ppf(pp) |
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60 | ym[vindex] = pcurves[vname][vindex].ppf(pm) |
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61 | |
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62 | curve = io['output.curve(curve_pdf-%s-%s)' % (vname, percent)] |
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63 | if percent == 0: |
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64 | curve['about.label'] = "mean" |
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65 | else: |
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66 | curve['about.label'] = "middle %s%%" % percent |
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67 | curve['about.group'] = label |
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68 | curve['about.uqtype'] = 'Probability' |
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69 | |
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70 | pts = "" |
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71 | for x, y in zip(xarr, yp): |
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72 | pts += "%s %s " % (x, y) |
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73 | if percent == 0: |
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74 | pts += '\n' |
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75 | else: |
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76 | for x, y in reversed(zip(xarr, ym)): |
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77 | pts += "%s %s " % (x, y) |
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78 | pts += "%s %s\n" % (xarr[0], yp[0]) |
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79 | |
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80 | curve['component.xy'] = pts |
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81 | |
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82 | |
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83 | def add_pts(f1, percent): |
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84 | # compute upper and lower percentiles |
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85 | pm = (100 - percent) / 200.0 |
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86 | pp = 1 - pm |
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87 | prob = np.linspace(pm, pp, 31) |
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88 | x, y = f1.eval(prob) |
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89 | return np.array(zip(x, y)) |
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90 | |
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91 | |
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92 | def plot_pdf_acurve(io, h5, acurves, vname, percent): |
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93 | """ |
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94 | This function plots the probability curves for parametric |
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95 | PDFs. |
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96 | """ |
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97 | print('plot_pdf_acurve %s %s' % (vname, percent)) |
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98 | |
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99 | label = None |
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100 | prev_pts = None # last set of points |
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101 | |
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102 | poly = [] |
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103 | for vindex in sorted(acurves[vname].keys()): |
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104 | if label is None: |
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105 | label = h5['/output/data/%s[%d]' % (vname, vindex)].attrs['label'] |
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106 | f1 = unpickle(h5['/output/data/%s[%d]' % (vname, vindex)].attrs['curve']) |
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107 | bpts = add_pts(f1, percent) |
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108 | |
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109 | # first data set? Just remember it. |
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110 | if prev_pts is None: |
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111 | prev_pts = bpts |
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112 | continue |
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113 | |
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114 | pts = np.array((prev_pts, bpts)).ravel().reshape(-1, 2) |
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115 | hull = ConvexHull(pts, qhull_options='Pp') |
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116 | p1 = Polygon([hull.points[v] for v in hull.vertices]) |
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117 | poly.append(p1) |
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118 | prev_pts = bpts |
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119 | |
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120 | u = unary_union(poly) |
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121 | |
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122 | curve = io['output.curve(curve_pdf-%s-%s)' % (vname, percent)] |
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123 | if percent == 0: |
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124 | curve['about.label'] = "mean" |
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125 | else: |
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126 | curve['about.label'] = "middle %s%%" % percent |
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127 | curve['about.group'] = label |
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128 | curve['about.uqtype'] = 'Probability' |
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129 | curve['component.xy'] = np.array(u.exterior.xy) |
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130 | |
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131 | |
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132 | def plot_pdf(io, v, pdf, desc): |
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133 | print("plot_pdf %s desc=%s" % (v, desc)) |
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134 | p = io['output.curve(pdf-%s)' % v] |
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135 | p['about.label'] = desc |
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136 | p['about.uqtype'] = "PDF" |
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137 | p['yaxis.label'] = 'Probability' |
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138 | |
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139 | pts = "%s 0\n" % pdf.x[0] |
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140 | for x, y in zip(pdf.x, pdf.y): |
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141 | pts += "%s %s\n" % (x, y) |
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142 | pts += "%s 0\n" % pdf.x[-1] |
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143 | p['component.xy'] = pts |
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144 | |
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145 | |
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146 | def write_responses(io, h5): |
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147 | uqtype = h5.attrs['UQtype'] |
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148 | for v in h5[uqtype]: |
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149 | print("write_responses", v) |
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150 | if '[' in v: |
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151 | # It is a curve. Ignore. |
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152 | continue |
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153 | try: |
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154 | desc = h5['%s/%s' % (uqtype, v)].attrs['description'] |
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155 | except: |
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156 | desc = '' |
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157 | try: |
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158 | label = h5['%s/%s' % (uqtype, v)].attrs['label'] |
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159 | except: |
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160 | label = '' |
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161 | |
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162 | rsp = h5['/%s/%s/response' % (uqtype, v)].value |
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163 | rout = io['output.response(%s)' % v] |
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164 | rout['value'] = rsp |
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165 | rout['about.description'] = desc |
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166 | rout['about.label'] = label |
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167 | rout['about.uqtype'] = 'Response' |
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168 | |
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169 | rs = unpickle(rsp) |
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170 | rout['variables'] = ' '.join([str(p.name) for p in rs.params]) |
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171 | labels = ' '.join([repr(str(p.label)) for p in rs.params]) |
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172 | rout['labels'] = labels.replace("'", '"') |
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173 | |
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174 | if type(rs) == puq.response.ResponseFunc: |
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175 | rout['equation'] = rs.eqn |
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176 | rout['rmse'] = "{:6.3g}".format(rs.rmse()[1]) |
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177 | |
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178 | rout['data'] = rs.data |
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179 | |
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180 | |
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181 | def write_params(h5, out): |
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182 | params = map(str, h5['/input/params'].keys()) |
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183 | print('#' * 80, file=out) |
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184 | print('INPUT PARAMETERS', file=out) |
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185 | |
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186 | for pname in params: |
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187 | print('-' * 80, file=out) |
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188 | p = puq.unpickle(h5['/input/params/' + pname].value) |
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189 | cname = p.__class__.__name__[:-9] |
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190 | pdf_str = '%s [%s - %s] mean=%s dev=%s mode=%s' % (cname, p.pdf.range[0], p.pdf.range[1], p.pdf.mean, p.pdf.dev, p.pdf.mode) |
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191 | |
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192 | print("Name:", p.name, file=out) |
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193 | try: |
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194 | print("Label:", p.label, file=out) |
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195 | except: |
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196 | pass |
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197 | print("Desc:", p.description, file=out) |
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198 | print('Value:', pdf_str, file=out) |
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199 | print('#' * 80, file=out) |
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200 | print(file=out) |
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201 | |
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202 | |
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203 | def write_summary(io, h5): |
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204 | outstr = StringIO.StringIO() |
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205 | write_params(h5, outstr) |
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206 | uqtype = h5.attrs['UQtype'] |
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207 | for v in h5[uqtype]: |
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208 | if '[' in v: |
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209 | # It is a curve. Ignore. |
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210 | continue |
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211 | desc = h5['%s/%s' % (uqtype, v)].attrs['description'] |
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212 | print("QoI: %s (%s)" % (v, desc), file=outstr) |
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213 | rs = unpickle(h5['/%s/%s/response' % (uqtype, v)].value) |
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214 | if type(rs) == puq.response.ResponseFunc: |
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215 | print("\nv=%s\n" % rs.eqn, file=outstr) |
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216 | print("SURROGATE MODEL ERROR:{:6.3g}%".format(rs.rmse()[1]), file=outstr) |
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217 | sens = puq.unpickle(h5['/%s/%s/sensitivity' % (uqtype, v)].value) |
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218 | max_name_len = max(map(len, [p[0] for p in sens])) |
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219 | print("\nSENSITIVITY:", file=outstr) |
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220 | print("Var%s u* dev" % (' '*(max_name_len)), file=outstr) |
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221 | print('-'*(28+max_name_len), file=outstr) |
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222 | for item in sens: |
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223 | pad = ' '*(max_name_len - len(item[0])) |
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224 | print("{}{} {:10.4g} {:10.4g}".format(pad, item[0], |
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225 | item[1]['ustar'], item[1]['std']), file=outstr) |
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226 | print('-'*(28+max_name_len), file=outstr) |
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227 | print(file=outstr) |
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228 | iostr = io['output.string(UQ Summary)'] |
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229 | iostr['about.label'] = 'UQ Summary' |
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230 | iostr['current'] = outstr.getvalue() |
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231 | outstr.close() |
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232 | |
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233 | |
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234 | def write_sensitivity(io, h5): |
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235 | # If more than one variable, display sensitivity. |
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236 | # Curves have indexed variables, so skip them. |
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237 | if len(h5['/input/params']) > 1 and ['[' in x for x in h5[uqtype]].count(False): |
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238 | for v in h5[uqtype]: |
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239 | if '[' in v: |
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240 | # curve. skip it. |
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241 | continue |
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242 | desc = h5['/output/data/%s' % v].attrs['label'] |
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243 | sens = unpickle(h5['/%s/%s/sensitivity' % (uqtype, v)].value) |
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244 | |
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245 | hist = io['output.histogram(sens-%s)' % v] |
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246 | hist['about.label'] = desc |
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247 | hist['about.uqtype'] = 'Sensitivity' |
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248 | hist['about.type'] = 'scatter' |
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249 | hist['xaxis.label'] = 'Parameters' |
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250 | hist['yaxis.label'] = 'Sensitivity' |
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251 | pts = '' |
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252 | for name in sens: |
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253 | n = name[0] |
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254 | try: |
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255 | n = h5['/input/params/%s' % n].attrs['label'] |
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256 | except: |
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257 | pass |
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258 | pts += "\"%s\" %s\n" % (n, name[1]['ustar']) |
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259 | hist['component.xy'] = pts |
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260 | |
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261 | sw = load_from_hdf5(sys.argv[1]) |
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262 | sw.analyze() |
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263 | |
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264 | h5 = h5py.File(sys.argv[1], 'r+') |
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265 | io = Rappture.PyXml('run_uq.xml') |
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266 | |
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267 | # curves built from pdfs |
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268 | pcurves = {} |
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269 | xvals = {} |
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270 | acurves = {} |
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271 | |
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272 | reg1 = re.compile('([ \da-zA-Z_]+)\[([ \d]+)\]') |
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273 | |
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274 | uqtype = h5.attrs['UQtype'] |
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275 | for v in h5[uqtype]: |
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276 | print('v=', v) |
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277 | rsp = h5['/%s/%s/response' % (uqtype, v)].value |
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278 | rs = unpickle(rsp) |
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279 | pdf = rs.pdf(fit=False) |
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280 | odata = h5['/output/data/%s' % v] |
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281 | |
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282 | # For curves built from pdfs, just put them in a dict for now |
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283 | if 'x' in odata.attrs: |
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284 | matches = reg1.findall(v) |
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285 | vname, vindex = matches[0] |
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286 | print('CURVE: vname=%s vindex=%s' % (vname, vindex)) |
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287 | vindex = int(vindex) |
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288 | if vname not in pcurves: |
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289 | pcurves[vname] = {} |
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290 | xvals[vname] = {} |
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291 | xvals[vname][vindex] = odata.attrs['x'] |
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292 | pcurves[vname][vindex] = pdf |
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293 | elif 'curve' in odata.attrs: |
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294 | matches = reg1.findall(v) |
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295 | vname, vindex = matches[0] |
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296 | print('ACURVE: %s - %s' % (vname, vindex)) |
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297 | if vname not in acurves: |
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298 | acurves[vname] = {} |
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299 | acurves[vname][int(vindex)] = pdf |
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300 | else: |
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301 | desc = h5['/output/data/%s' % v].attrs['label'] |
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302 | plot_pdf(io, v, pdf, desc) |
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303 | |
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304 | # now do probability curves |
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305 | for vname in xvals: |
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306 | plot_pdf_curve(io, h5, xvals, vname, 95) |
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307 | plot_pdf_curve(io, h5, xvals, vname, 50) |
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308 | |
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309 | for vname in acurves: |
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310 | try: |
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311 | plot_pdf_acurve(io, h5, acurves, vname, 95) |
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312 | except: |
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313 | pass |
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314 | try: |
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315 | plot_pdf_acurve(io, h5, acurves, vname, 50) |
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316 | except: |
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317 | pass |
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318 | |
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319 | write_sensitivity(io, h5) |
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320 | write_responses(io, h5) |
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321 | write_summary(io, h5) |
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322 | |
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323 | io.close() |
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324 | h5.close() |
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