1 | """Compare selected timeseries from model outputs |
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2 | |
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3 | Usage: |
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4 | python compare_model_timeseries.py swwfile1 swwfile2 |
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5 | |
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6 | Return 0 if timeseries are 'close enough', otherwise return non zero error code |
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7 | |
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8 | Typically swwfile1 would be model output from unit test and swwfile2 would |
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9 | be a reference model. |
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10 | """ |
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11 | |
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12 | from anuga.abstract_2d_finite_volumes.util import file_function |
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13 | from anuga.utilities.numerical_tools import cov, get_machine_precision |
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14 | |
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15 | |
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16 | import pylab |
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17 | import numpy as num |
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18 | import sys, os |
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19 | |
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20 | # Model specific data |
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21 | gauges = {'g10a': [422233.4, 874380.2], |
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22 | 'g10b': [422107.9, 873556.8], |
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23 | 'g10c': [421966.8, 872890.3], |
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24 | 'g10d': [421606.1, 872106.2], |
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25 | 'g11a': [422628.2, 873933.2], |
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26 | 'g11b': [422716.2, 873420.6], |
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27 | 'g11c': [422689.1, 872859.8], |
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28 | 'g11d': [422408.7, 871940.3], |
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29 | 'g11e': [421751.7, 871097.8], |
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30 | 'north': [422572.4, 873992.6], |
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31 | 'south': [422004.4, 872014.4]} |
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32 | |
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33 | |
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34 | #--------------------------------------- |
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35 | |
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36 | def usage(): |
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37 | print 'Usage:' |
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38 | print 'python compare_model_timeseries.py swwfile1 swwfile2 epsilon' |
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39 | |
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40 | |
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41 | |
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42 | def get_timeseries(sww_filename, gauges): |
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43 | """Generate time series for sww file based on gauges |
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44 | """ |
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45 | |
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46 | gauge_locations = gauges.values() |
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47 | gauge_names = gauges.keys() |
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48 | |
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49 | tempfile = 'xyz1234tempfile.sww' # Has to end with sww |
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50 | |
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51 | os.system('cp %s %s' % (sww_filename, tempfile)) |
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52 | f = file_function(tempfile, |
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53 | quantities='stage', |
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54 | interpolation_points=gauge_locations, |
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55 | use_cache=True, |
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56 | verbose=True) |
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57 | |
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58 | timevector = f.get_time() |
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59 | |
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60 | timeseries = {} |
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61 | for k, name in enumerate(gauge_names): |
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62 | model = timeseries[name] = [] |
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63 | |
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64 | for t in timevector: |
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65 | model.append(f(t, point_id=k)[0]) |
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66 | |
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67 | |
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68 | return num.array(timevector), timeseries |
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69 | |
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70 | |
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71 | |
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72 | def compare_timeseries(timevector, |
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73 | timeseries1, |
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74 | timeseries2, |
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75 | name='', |
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76 | legend = ('Time series 1', 'Time series 2'), |
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77 | eps=1.0e-6): |
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78 | """Compare and plot two timeseries |
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79 | """ |
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80 | |
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81 | |
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82 | timeseries1 = num.array(timeseries1) |
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83 | timeseries2 = num.array(timeseries2) |
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84 | N = timevector.shape[0] |
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85 | assert timeseries1.shape[0] == N |
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86 | assert timeseries2.shape[0] == N |
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87 | |
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88 | print 'epsilon', eps |
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89 | # Covariance measure |
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90 | res = cov(timeseries1-timeseries2) |
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91 | print '2 norm diff', res |
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92 | msg = '2-norm of timeseries difference was too large: %e' % res |
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93 | assert res < eps, msg |
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94 | |
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95 | # Maximum norm |
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96 | nominator = max(abs(timeseries1-timeseries2)) |
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97 | denominator = max(abs(timeseries1)) |
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98 | if denominator > 0: |
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99 | # Relative measure |
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100 | res = nominator/denominator |
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101 | else: |
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102 | # Absolute measure |
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103 | res = nominator/N |
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104 | |
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105 | print 'Max abs diff', res |
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106 | msg = '%s: Difference between timeseries was too large: %e' % (name, res) |
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107 | assert res < eps, msg |
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108 | |
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109 | |
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110 | nominator = sum(abs(timeseries1-timeseries2)) |
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111 | denominator = sum(abs(timeseries1)) |
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112 | if denominator > 0: |
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113 | # Relative measure |
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114 | res = nominator/denominator |
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115 | else: |
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116 | # Absolute measure |
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117 | res = nominator/N |
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118 | |
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119 | print 'Sum abs diff', res |
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120 | msg = '%s: Difference between timeseries was too large: %e' % (name, res) |
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121 | assert res < eps, msg |
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122 | |
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123 | # Extrema |
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124 | max1 = max(timeseries1) |
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125 | max2 = max(timeseries2) |
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126 | print 'Max diff', abs(max1-max2) |
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127 | |
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128 | min1 = min(timeseries1) |
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129 | min2 = min(timeseries2) |
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130 | print 'Min diff', abs(min1-min2) |
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131 | |
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132 | # Locations of extrema |
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133 | i1 = num.argmax(timeseries1) |
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134 | i2 = num.argmax(timeseries2) |
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135 | |
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136 | res = abs(reference_time[i1]-reference_time[i2]) |
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137 | print 'Max loc diff', res |
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138 | |
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139 | |
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140 | i1 = num.argmin(timeseries1) |
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141 | i2 = num.argmin(timeseries2) |
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142 | |
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143 | res = abs(reference_time[i1]-reference_time[i2]) |
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144 | print 'Min loc diff', res |
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145 | |
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146 | |
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147 | |
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148 | # Generate plots |
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149 | pylab.ion() # No plotting on screen |
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150 | pylab.hold(False) |
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151 | |
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152 | pylab.plot(timevector, timeseries1, 'r-', |
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153 | timevector, timeseries2, 'k-') |
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154 | |
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155 | pylab.title('Gauge %s' % name) |
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156 | pylab.xlabel('time(s)') |
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157 | pylab.ylabel('stage (m)') |
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158 | pylab.legend(legend, shadow=True, loc='upper left') |
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159 | pylab.savefig(name, dpi = 300) |
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160 | |
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161 | # Error vector |
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162 | pylab.ion() # No plotting on screen |
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163 | pylab.hold(False) |
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164 | pylab.plot(timevector, timeseries1-timeseries2, 'b-') |
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165 | pylab.title('Gauge %s (difference)' % name) |
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166 | pylab.xlabel('time(s)') |
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167 | pylab.ylabel('stage difference (m)') |
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168 | pylab.savefig(name + '_diff', dpi = 300) |
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169 | |
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170 | |
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171 | |
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172 | def compare_all_timeseries(swwfile1, swwfile2, eps=1.0e-6): |
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173 | |
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174 | timevector1, timeseries1 = get_timeseries(swwfile1, gauges) |
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175 | timevector2, timeseries2 = get_timeseries(swwfile2, gauges) |
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176 | |
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177 | msg = 'Time vectors were different in models %s and %s' %\ |
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178 | (swwfile1, swwfile2) |
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179 | assert num.allclose(timevector1, timevector2), msg |
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180 | timevector = timevector1 |
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181 | |
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182 | # Check that both timeseries exist for all gauges |
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183 | for name in timeseries2: |
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184 | assert name in timeseries1 |
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185 | |
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186 | for name in timeseries1: |
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187 | assert name in timeseries2 |
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188 | |
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189 | # Compare all timeseries data individually |
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190 | for name in timeseries1: |
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191 | compare_timeseries(timevector, |
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192 | timeseries1[name], |
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193 | timeseries2[name], |
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194 | name=name, |
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195 | eps=eps) |
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196 | |
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197 | |
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198 | |
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199 | |
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200 | |
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201 | print 'OK' |
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202 | |
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203 | |
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204 | |
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205 | if __name__ == '__main__': |
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206 | |
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207 | if len(sys.argv) != 4: |
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208 | usage() |
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209 | import sys; sys.exit(-1) |
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210 | |
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211 | eps = float(sys.argv[3]) # Get tolerance to be used in comparisons |
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212 | try: |
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213 | res = compare_all_timeseries(sys.argv[1], sys.argv[2], eps=eps) |
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214 | except: |
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215 | sys.exit(-1) |
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216 | else: |
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217 | sys.exit(0) |
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