Mercurial > pylearn
annotate test_dataset.py @ 145:933db7ece663
make some function global to reuse them to test other dataset
author | Frederic Bastien <bastienf@iro.umontreal.ca> |
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date | Mon, 12 May 2008 15:35:18 -0400 |
parents | 0c6fec172ae1 |
children | a5329e719229 |
rev | line source |
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the script can be autorun
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1 #!/bin/env python |
45 | 2 from dataset import * |
3 from math import * | |
4 import numpy | |
5 | |
145
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6 def have_raised(to_eval, **var): |
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7 |
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8 have_thrown = False |
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9 try: |
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10 eval(to_eval) |
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11 except : |
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12 have_thrown = True |
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13 return have_thrown |
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14 |
45 | 15 def test1(): |
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16 print "test1" |
45 | 17 global a,ds |
18 a = numpy.random.rand(10,4) | |
19 print a | |
20 ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]}) | |
21 print "len(ds)=",len(ds) | |
54 | 22 assert(len(ds)==10) |
45 | 23 print "example 0 = ",ds[0] |
54 | 24 # assert |
45 | 25 print "x=",ds["x"] |
26 print "x|y" | |
27 for x,y in ds("x","y"): | |
28 print x,y | |
29 minibatch_iterator = ds.minibatches(fieldnames=['z','y'],n_batches=1,minibatch_size=3,offset=4) | |
30 minibatch = minibatch_iterator.__iter__().next() | |
31 print "minibatch=",minibatch | |
32 for var in minibatch: | |
33 print "var=",var | |
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34 print "take a slice and look at field y",ds[1:6:2]["y"] |
45 | 35 |
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36 def test_iterate_over_examples(array,ds): |
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37 #not in doc!!! |
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38 i=0 |
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39 for example in range(len(ds)): |
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40 assert (ds[example]['x']==array[example][:3]).all() |
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41 assert ds[example]['y']==array[example][3] |
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42 assert (ds[example]['z']==array[example][[0,2]]).all() |
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43 i+=1 |
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44 assert i==len(ds) |
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45 del example,i |
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46 |
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47 # - for example in dataset: |
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48 i=0 |
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49 for example in ds: |
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50 assert len(example)==3 |
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51 assert (example['x']==array[i][:3]).all() |
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52 assert example['y']==array[i][3] |
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53 assert (example['z']==array[i][0:3:2]).all() |
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54 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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55 i+=1 |
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56 assert i==len(ds) |
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57 del example,i |
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58 |
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59 # - for val1,val2,... in dataset: |
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60 i=0 |
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61 for x,y,z in ds: |
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62 assert (x==array[i][:3]).all() |
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63 assert y==array[i][3] |
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64 assert (z==array[i][0:3:2]).all() |
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65 assert (numpy.append(x,y)==array[i]).all() |
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66 i+=1 |
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67 assert i==len(ds) |
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68 del x,y,z,i |
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69 |
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70 # - for example in dataset(field1, field2,field3, ...): |
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71 i=0 |
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72 for example in ds('x','y','z'): |
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73 assert len(example)==3 |
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74 assert (example['x']==array[i][:3]).all() |
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75 assert example['y']==array[i][3] |
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76 assert (example['z']==array[i][0:3:2]).all() |
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77 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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78 i+=1 |
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79 assert i==len(ds) |
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80 del example,i |
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81 i=0 |
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82 for example in ds('y','x'): |
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83 assert len(example)==2 |
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84 assert (example['x']==array[i][:3]).all() |
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85 assert example['y']==array[i][3] |
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86 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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87 i+=1 |
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88 assert i==len(ds) |
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89 del example,i |
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90 |
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91 # - for val1,val2,val3 in dataset(field1, field2,field3): |
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92 i=0 |
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93 for x,y,z in ds('x','y','z'): |
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94 assert (x==array[i][:3]).all() |
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95 assert y==array[i][3] |
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96 assert (z==array[i][0:3:2]).all() |
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97 assert (numpy.append(x,y)==array[i]).all() |
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98 i+=1 |
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99 assert i==len(ds) |
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100 del x,y,z,i |
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101 i=0 |
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102 for y,x in ds('y','x',): |
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103 assert (x==array[i][:3]).all() |
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104 assert y==array[i][3] |
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105 assert (numpy.append(x,y)==array[i]).all() |
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106 i+=1 |
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107 assert i==len(ds) |
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108 del x,y,i |
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109 |
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110 def test_minibatch_size(minibatch,minibatch_size,len_ds,nb_field,nb_iter_finished): |
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111 ##full minibatch or the last minibatch |
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112 for idx in range(nb_field): |
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113 test_minibatch_field_size(minibatch[idx],minibatch_size,len_ds,nb_iter_finished) |
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114 del idx |
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115 def test_minibatch_field_size(minibatch_field,minibatch_size,len_ds,nb_iter_finished): |
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116 assert len(minibatch_field)==minibatch_size or ((nb_iter_finished*minibatch_size+len(minibatch_field))==len_ds and len(minibatch_field)<minibatch_size) |
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117 |
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118 # - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N): |
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119 i=0 |
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120 mi=0 |
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121 m=ds.minibatches(['x','z'], minibatch_size=3) |
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122 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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123 for minibatch in m: |
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124 assert len(minibatch)==2 |
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125 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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126 assert (minibatch[0][:,0:3:2]==minibatch[1]).all() |
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127 mi+=1 |
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128 i+=len(minibatch[0]) |
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129 assert i==len(ds) |
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130 assert mi==4 |
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131 del minibatch,i,m,mi |
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132 |
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133 i=0 |
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134 mi=0 |
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135 m=ds.minibatches(['x','y'], minibatch_size=3) |
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136 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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137 for minibatch in m: |
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138 assert len(minibatch)==2 |
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139 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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140 mi+=1 |
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141 for id in range(len(minibatch[0])): |
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142 assert (numpy.append(minibatch[0][id],minibatch[1][id])==array[i]).all() |
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143 i+=1 |
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144 assert i==len(ds) |
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145 assert mi==4 |
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146 del minibatch,i,id,m,mi |
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147 |
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148 # - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N): |
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149 i=0 |
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150 mi=0 |
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151 m=ds.minibatches(['x','z'], minibatch_size=3) |
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152 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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153 for x,z in m: |
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154 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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155 test_minibatch_field_size(z,m.minibatch_size,len(ds),mi) |
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156 assert (x[:,0:3:2]==z).all() |
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157 i+=len(x) |
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158 mi+=1 |
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159 assert i==len(ds) |
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160 assert mi==4 |
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161 del x,z,i,m,mi |
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162 i=0 |
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163 mi=0 |
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164 m=ds.minibatches(['x','y'], minibatch_size=3) |
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165 for x,y in m: |
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166 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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167 test_minibatch_field_size(y,m.minibatch_size,len(ds),mi) |
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168 mi+=1 |
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169 for id in range(len(x)): |
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170 assert (numpy.append(x[id],y[id])==array[i]).all() |
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171 i+=1 |
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172 assert i==len(ds) |
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173 assert mi==4 |
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174 del x,y,i,id,m,mi |
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175 |
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176 #not in doc |
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177 i=0 |
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178 m=ds.minibatches(['x','y'],n_batches=1,minibatch_size=3,offset=4) |
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179 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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180 for x,y in m: |
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181 assert len(x)==3 |
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182 assert len(y)==3 |
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183 for id in range(3): |
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184 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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185 i+=1 |
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186 assert i==3 |
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187 del x,y,i,id,m |
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188 |
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189 i=0 |
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190 m=ds.minibatches(['x','y'],n_batches=2,minibatch_size=3,offset=4) |
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191 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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192 for x,y in m: |
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193 assert len(x)==3 |
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194 assert len(y)==3 |
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195 for id in range(3): |
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196 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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197 i+=1 |
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198 assert i==6 |
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199 del x,y,i,id,m |
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200 |
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201 i=0 |
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202 m=ds.minibatches(['x','y'],n_batches=20,minibatch_size=3,offset=4) |
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203 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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204 for x,y in m: |
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205 assert len(x)==3 |
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206 assert len(y)==3 |
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207 for id in range(3): |
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208 assert (numpy.append(x[id],y[id])==array[(i+4)%array.shape[0]]).all() |
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209 i+=1 |
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210 assert i==m.n_batches*m.minibatch_size |
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211 del x,y,i,id |
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212 |
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213 |
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214 def test_ds_iterator(array,iterator1,iterator2,iterator3): |
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215 l=len(iterator1) |
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216 i=0 |
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217 for x,y in iterator1: |
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218 assert (x==array[i][:3]).all() |
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219 assert y==array[i][3] |
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220 assert (numpy.append(x,y)==array[i]).all() |
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221 i+=1 |
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222 assert i==l |
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223 i=0 |
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224 for y,z in iterator2: |
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225 assert y==array[i][3] |
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226 assert (z==array[i][0:3:2]).all() |
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227 i+=1 |
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228 assert i==l |
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229 i=0 |
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230 for x,y,z in iterator3: |
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231 assert (x==array[i][:3]).all() |
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232 assert y==array[i][3] |
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233 assert (z==array[i][0:3:2]).all() |
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234 assert (numpy.append(x,y)==array[i]).all() |
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235 i+=1 |
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236 assert i==l |
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237 |
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238 def test_getitem(array,ds): |
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239 def test_ds(orig,ds,index): |
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240 i=0 |
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241 assert len(ds)==len(index) |
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242 for x,z,y in ds('x','z','y'): |
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243 assert (orig[index[i]]['x']==array[index[i]][:3]).all() |
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244 assert (orig[index[i]]['x']==x).all() |
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245 assert orig[index[i]]['y']==array[index[i]][3] |
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246 assert orig[index[i]]['y']==y |
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247 assert (orig[index[i]]['z']==array[index[i]][0:3:2]).all() |
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248 assert (orig[index[i]]['z']==z).all() |
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249 i+=1 |
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250 del i |
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251 ds[0] |
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252 if len(ds)>2: |
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253 ds[:1] |
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254 ds[1:1] |
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255 ds[1:1:1] |
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256 if len(ds)>5: |
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257 ds[[1,2,3]] |
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258 for x in ds: |
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259 pass |
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260 |
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261 #ds[:n] returns a dataset with the n first examples. |
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262 ds2=ds[:3] |
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263 assert isinstance(ds2,DataSet) |
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264 test_ds(ds,ds2,index=[0,1,2]) |
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265 del ds2 |
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266 |
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267 #ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s. |
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268 ds2=ds[1:7:2] |
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269 assert isinstance(ds2,DataSet) |
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270 test_ds(ds,ds2,[1,3,5]) |
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271 del ds2 |
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272 |
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273 #ds[i] |
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274 ds2=ds[5] |
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275 assert isinstance(ds2,Example) |
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276 assert have_raised("var['ds']["+str(len(ds))+"]",ds=ds) # index not defined |
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277 assert not have_raised("var['ds']["+str(len(ds)-1)+"]",ds=ds) |
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278 del ds2 |
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279 |
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280 #ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in. |
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281 ds2=ds[[4,7,2,8]] |
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282 assert isinstance(ds2,DataSet) |
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283 test_ds(ds,ds2,[4,7,2,8]) |
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284 del ds2 |
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285 |
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286 #ds[fieldname]# an iterable over the values of the field fieldname across |
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287 #the ds (the iterable is obtained by default by calling valuesVStack |
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288 #over the values for individual examples). |
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289 assert have_raised("ds['h']") # h is not defined... |
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290 assert have_raised("ds[['x']]") # bad syntax |
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291 assert not have_raised("var['ds']['x']",ds=ds) |
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292 isinstance(ds['x'],DataSetFields) |
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293 ds2=ds['x'] |
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294 assert len(ds['x'])==10 |
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295 assert len(ds['y'])==10 |
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296 assert len(ds['z'])==10 |
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297 i=0 |
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298 for example in ds['x']: |
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299 assert (example==array[i][:3]).all() |
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300 i+=1 |
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301 i=0 |
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302 for example in ds['y']: |
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303 assert (example==array[i][3]).all() |
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304 i+=1 |
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305 i=0 |
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306 for example in ds['z']: |
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307 assert (example==array[i,0:3:2]).all() |
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308 i+=1 |
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309 del ds2,i |
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310 |
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311 #ds.<property># returns the value of a property associated with |
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312 #the name <property>. The following properties should be supported: |
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313 # - 'description': a textual description or name for the ds |
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314 # - 'fieldtypes': a list of types (one per field) |
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315 |
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316 #* ds1 | ds2 | ds3 == ds.hstack([ds1,ds2,ds3])#???? |
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317 #hstack([ds('x','y'),ds('z')] |
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318 #hstack([ds('z','y'),ds('x')] |
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319 #assert have_thrown("hstack([ds('x'),ds('x')]") |
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320 #assert not have_thrown("hstack([ds('x'),ds('x')]") |
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321 #accept_nonunique_names |
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322 #assert have_thrown("hstack([ds('y','x'),ds('x')]") |
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323 # i=0 |
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324 # for example in hstack([ds('x'),ds('y'),ds('z')]): |
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325 # example==ds[i] |
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326 # i+=1 |
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327 # del i,example |
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328 #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])#???? |
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329 |
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330 |
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331 def test_ArrayDataSet(): |
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332 #don't test stream |
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333 #tested only with float value |
106 | 334 #don't always test with y |
335 #don't test missing value | |
336 #don't test with tuple | |
337 #don't test proterties | |
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338 print "test_ArrayDataSet" |
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339 a2 = numpy.random.rand(10,4) |
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340 ds = ArrayDataSet(a2,{'x':slice(3),'y':3,'z':[0,2]})###???tuple not tested |
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341 ds = ArrayDataSet(a2,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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342 assert len(ds)==10 |
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343 #assert ds==a? should this work? |
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344 |
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345 test_iterate_over_examples(a2, ds) |
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346 test_getitem(a2, ds) |
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347 |
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348 # - for val1,val2,val3 in dataset(field1, field2,field3): |
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349 test_ds_iterator(a2,ds('x','y'),ds('y','z'),ds('x','y','z')) |
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350 |
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351 |
63 | 352 assert len(ds.fields())==3 |
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353 for field in ds.fields(): |
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354 for field_value in field: # iterate over the values associated to that field for all the ds examples |
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355 pass |
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356 for field in ds('x','z').fields(): |
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357 pass |
60 | 358 for field in ds.fields('x','y'): |
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359 pass |
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360 for field_examples in ds.fields(): |
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361 for example_value in field_examples: |
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362 pass |
63 | 363 |
364 assert ds == ds.fields().examples() | |
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365 # for ((x,y),a_v) in (ds('x','y'),a): #???don't work # haven't found a variant that work.# will not work |
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366 # assert numpy.append(x,y)==z |
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367 |
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368 def test_LookupList(): |
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369 #test only the example in the doc??? |
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370 print "test_LookupList" |
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371 example = LookupList(['x','y','z'],[1,2,3]) |
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372 example['x'] = [1, 2, 3] # set or change a field |
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373 x, y, z = example |
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374 x = example[0] |
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375 x = example["x"] |
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376 assert example.keys()==['x','y','z'] |
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377 assert example.values()==[[1,2,3],2,3] |
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378 assert example.items()==[('x',[1,2,3]),('y',2),('z',3)] |
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379 example.append_keyval('u',0) # adds item with name 'u' and value 0 |
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380 assert len(example)==4 # number of items = 4 here |
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381 example2 = LookupList(['v','w'], ['a','b']) |
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382 example3 = LookupList(['x','y','z','u','v','w'], [[1, 2, 3],2,3,0,'a','b']) |
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383 assert example+example2==example3 |
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384 assert have_raised("var['x']+var['x']",x=example) |
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385 |
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386 def test_ApplyFunctionDataSet(): |
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387 print "test_ApplyFunctionDataSet" |
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388 raise NotImplementedError() |
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389 def test_CacheDataSet(): |
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390 print "test_CacheDataSet" |
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391 raise NotImplementedError() |
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392 def test_FieldsSubsetDataSet(): |
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393 print "test_FieldsSubsetDataSet" |
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394 raise NotImplementedError() |
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395 def test_DataSetFields(): |
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396 print "test_DataSetFields" |
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397 raise NotImplementedError() |
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398 def test_MinibatchDataSet(): |
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399 print "test_MinibatchDataSet" |
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400 raise NotImplementedError() |
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401 def test_HStackedDataSet(): |
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402 print "test_HStackedDataSet" |
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403 raise NotImplementedError() |
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404 def test_VStackedDataSet(): |
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405 print "test_VStackedDataSet" |
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406 raise NotImplementedError() |
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407 def test_ArrayFieldsDataSet(): |
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408 print "test_ArrayFieldsDataSet" |
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409 raise NotImplementedError() |
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410 |
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411 test1() |
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412 test_LookupList() |
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413 test_ArrayDataSet() |
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414 #test pmat.py |