Mercurial > pylearn
annotate _test_dataset.py @ 317:14081904d8f3
doc updated regarding __getitem__ returning LookupList and .subset returning a DataSet
author | Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca> |
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date | Wed, 11 Jun 2008 16:40:47 -0400 |
parents | b48cf8dce2bf |
children | 9c08e3af975e 4efb503fd0da |
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 * | |
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4 import numpy, unittest, sys |
229
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5 from misc import * |
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6 from lookup_list import LookupList |
45 | 7 |
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8 def have_raised(to_eval, **var): |
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9 have_thrown = False |
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10 try: |
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11 eval(to_eval) |
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12 except : |
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13 have_thrown = True |
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14 return have_thrown |
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15 |
173 | 16 def have_raised2(f, *args, **kwargs): |
17 have_thrown = False | |
18 try: | |
19 f(*args, **kwargs) | |
20 except : | |
21 have_thrown = True | |
22 return have_thrown | |
23 | |
45 | 24 def test1(): |
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25 print "test1" |
45 | 26 global a,ds |
27 a = numpy.random.rand(10,4) | |
28 print a | |
29 ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]}) | |
30 print "len(ds)=",len(ds) | |
54 | 31 assert(len(ds)==10) |
45 | 32 print "example 0 = ",ds[0] |
54 | 33 # assert |
45 | 34 print "x=",ds["x"] |
35 print "x|y" | |
36 for x,y in ds("x","y"): | |
37 print x,y | |
38 minibatch_iterator = ds.minibatches(fieldnames=['z','y'],n_batches=1,minibatch_size=3,offset=4) | |
39 minibatch = minibatch_iterator.__iter__().next() | |
40 print "minibatch=",minibatch | |
41 for var in minibatch: | |
42 print "var=",var | |
48
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43 print "take a slice and look at field y",ds[1:6:2]["y"] |
45 | 44 |
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45 del a,ds,x,y,minibatch_iterator,minibatch,var |
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46 |
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47 def test_iterate_over_examples(array,ds): |
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48 #not in doc!!! |
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49 i=0 |
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50 for example in range(len(ds)): |
293 | 51 wanted = array[example][:3] |
52 returned = ds[example]['x'] | |
53 if (wanted != returned).all(): | |
54 print 'returned:', returned | |
55 print 'wanted:', wanted | |
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56 assert (ds[example]['x']==array[example][:3]).all() |
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57 assert ds[example]['y']==array[example][3] |
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58 assert (ds[example]['z']==array[example][[0,2]]).all() |
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59 i+=1 |
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60 assert i==len(ds) |
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61 del example,i |
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62 |
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63 # - for example in dataset: |
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64 i=0 |
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65 for example in ds: |
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66 assert len(example)==3 |
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67 assert (example['x']==array[i][:3]).all() |
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68 assert example['y']==array[i][3] |
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69 assert (example['z']==array[i][0:3:2]).all() |
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70 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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71 i+=1 |
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72 assert i==len(ds) |
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73 del example,i |
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74 |
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75 # - for val1,val2,... in dataset: |
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76 i=0 |
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77 for x,y,z in ds: |
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78 assert (x==array[i][:3]).all() |
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79 assert y==array[i][3] |
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80 assert (z==array[i][0:3:2]).all() |
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81 assert (numpy.append(x,y)==array[i]).all() |
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82 i+=1 |
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83 assert i==len(ds) |
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84 del x,y,z,i |
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85 |
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86 # - for example in dataset(field1, field2,field3, ...): |
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87 i=0 |
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88 for example in ds('x','y','z'): |
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89 assert len(example)==3 |
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90 assert (example['x']==array[i][:3]).all() |
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91 assert example['y']==array[i][3] |
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92 assert (example['z']==array[i][0:3:2]).all() |
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93 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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94 i+=1 |
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95 assert i==len(ds) |
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96 del example,i |
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97 i=0 |
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98 for example in ds('y','x'): |
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99 assert len(example)==2 |
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100 assert (example['x']==array[i][:3]).all() |
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101 assert example['y']==array[i][3] |
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102 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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103 i+=1 |
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104 assert i==len(ds) |
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105 del example,i |
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106 |
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107 # - for val1,val2,val3 in dataset(field1, field2,field3): |
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108 i=0 |
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109 for x,y,z in ds('x','y','z'): |
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110 assert (x==array[i][:3]).all() |
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111 assert y==array[i][3] |
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112 assert (z==array[i][0:3:2]).all() |
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113 assert (numpy.append(x,y)==array[i]).all() |
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114 i+=1 |
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115 assert i==len(ds) |
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116 del x,y,z,i |
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117 i=0 |
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118 for y,x in ds('y','x',): |
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119 assert (x==array[i][:3]).all() |
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120 assert y==array[i][3] |
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121 assert (numpy.append(x,y)==array[i]).all() |
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122 i+=1 |
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123 assert i==len(ds) |
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124 del x,y,i |
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125 |
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126 def test_minibatch_size(minibatch,minibatch_size,len_ds,nb_field,nb_iter_finished): |
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127 ##full minibatch or the last minibatch |
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128 for idx in range(nb_field): |
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129 test_minibatch_field_size(minibatch[idx],minibatch_size,len_ds,nb_iter_finished) |
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130 del idx |
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131 def test_minibatch_field_size(minibatch_field,minibatch_size,len_ds,nb_iter_finished): |
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132 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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133 |
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134 # - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N): |
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135 i=0 |
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136 mi=0 |
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137 m=ds.minibatches(['x','z'], minibatch_size=3) |
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138 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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139 for minibatch in m: |
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140 assert isinstance(minibatch,DataSetFields) |
145
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141 assert len(minibatch)==2 |
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142 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
161
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143 if type(ds)==ArrayDataSet: |
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144 assert (minibatch[0][:,::2]==minibatch[1]).all() |
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145 else: |
162
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146 for j in xrange(len(minibatch[0])): |
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147 (minibatch[0][j][::2]==minibatch[1][j]).all() |
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148 mi+=1 |
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149 i+=len(minibatch[0]) |
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150 assert i==len(ds) |
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151 assert mi==4 |
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152 del minibatch,i,m,mi |
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153 |
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154 i=0 |
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155 mi=0 |
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156 m=ds.minibatches(['x','y'], minibatch_size=3) |
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157 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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158 for minibatch in m: |
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159 assert len(minibatch)==2 |
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160 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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161 mi+=1 |
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162 for id in range(len(minibatch[0])): |
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163 assert (numpy.append(minibatch[0][id],minibatch[1][id])==array[i]).all() |
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164 i+=1 |
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165 assert i==len(ds) |
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166 assert mi==4 |
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167 del minibatch,i,id,m,mi |
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168 |
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169 # - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N): |
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170 i=0 |
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171 mi=0 |
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172 m=ds.minibatches(['x','z'], minibatch_size=3) |
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173 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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174 for x,z in m: |
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175 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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176 test_minibatch_field_size(z,m.minibatch_size,len(ds),mi) |
164
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177 for id in range(len(x)): |
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178 assert (x[id][::2]==z[id]).all() |
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179 i+=1 |
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180 mi+=1 |
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181 assert i==len(ds) |
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182 assert mi==4 |
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183 del x,z,i,m,mi |
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184 i=0 |
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185 mi=0 |
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186 m=ds.minibatches(['x','y'], minibatch_size=3) |
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187 for x,y in m: |
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188 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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189 test_minibatch_field_size(y,m.minibatch_size,len(ds),mi) |
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190 mi+=1 |
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191 for id in range(len(x)): |
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192 assert (numpy.append(x[id],y[id])==array[i]).all() |
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193 i+=1 |
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194 assert i==len(ds) |
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195 assert mi==4 |
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196 del x,y,i,id,m,mi |
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197 |
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198 #not in doc |
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199 i=0 |
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200 m=ds.minibatches(['x','y'],n_batches=1,minibatch_size=3,offset=4) |
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201 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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202 for x,y in m: |
239
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203 assert len(x)==m.minibatch_size |
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204 assert len(y)==m.minibatch_size |
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205 for id in range(m.minibatch_size): |
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206 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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207 i+=1 |
239
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208 assert i==m.n_batches*m.minibatch_size |
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209 del x,y,i,id,m |
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210 |
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211 i=0 |
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212 m=ds.minibatches(['x','y'],n_batches=2,minibatch_size=3,offset=4) |
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213 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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214 for x,y in m: |
239
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215 assert len(x)==m.minibatch_size |
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216 assert len(y)==m.minibatch_size |
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217 for id in range(m.minibatch_size): |
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218 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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219 i+=1 |
239
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220 assert i==m.n_batches*m.minibatch_size |
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221 del x,y,i,id,m |
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222 |
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223 i=0 |
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224 m=ds.minibatches(['x','y'],n_batches=20,minibatch_size=3,offset=4) |
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225 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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226 for x,y in m: |
239
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227 assert len(x)==m.minibatch_size |
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228 assert len(y)==m.minibatch_size |
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229 for id in range(m.minibatch_size): |
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230 assert (numpy.append(x[id],y[id])==array[(i+4)%array.shape[0]]).all() |
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231 i+=1 |
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232 assert i==m.n_batches*m.minibatch_size |
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233 del x,y,i,id |
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234 |
293 | 235 assert not have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array)+1,offset=0) |
240
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236 assert not have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array),offset=0) |
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237 |
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238 def test_ds_iterator(array,iterator1,iterator2,iterator3): |
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239 l=len(iterator1) |
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240 i=0 |
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241 for x,y in iterator1: |
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242 assert (x==array[i][:3]).all() |
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243 assert y==array[i][3] |
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244 assert (numpy.append(x,y)==array[i]).all() |
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245 i+=1 |
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246 assert i==l |
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247 i=0 |
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248 for y,z in iterator2: |
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249 assert y==array[i][3] |
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250 assert (z==array[i][0:3:2]).all() |
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251 i+=1 |
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252 assert i==l |
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253 i=0 |
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254 for x,y,z in iterator3: |
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255 assert (x==array[i][:3]).all() |
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256 assert y==array[i][3] |
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257 assert (z==array[i][0:3:2]).all() |
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258 assert (numpy.append(x,y)==array[i]).all() |
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259 i+=1 |
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260 assert i==l |
311
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261 |
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262 def test_getitem(array,ds): |
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263 def test_ds(orig,ds,index): |
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264 i=0 |
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265 assert len(ds)==len(index) |
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266 for x,z,y in ds('x','z','y'): |
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267 assert (orig[index[i]]['x']==array[index[i]][:3]).all() |
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268 assert (orig[index[i]]['x']==x).all() |
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269 assert orig[index[i]]['y']==array[index[i]][3] |
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270 assert (orig[index[i]]['y']==y).all() # why does it crash sometimes? |
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271 assert (orig[index[i]]['z']==array[index[i]][0:3:2]).all() |
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272 assert (orig[index[i]]['z']==z).all() |
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273 i+=1 |
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274 del i |
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275 ds[0] |
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276 if len(ds)>2: |
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277 ds[:1] |
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278 ds[1:1] |
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279 ds[1:1:1] |
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280 if len(ds)>5: |
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281 ds[[1,2,3]] |
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282 for x in ds: |
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283 pass |
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284 |
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285 #ds[:n] returns a dataset with the n first examples. |
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286 ds2=ds[:3] |
311
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287 assert isinstance(ds2,LookupList) |
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288 test_ds(ds,ds2,index=[0,1,2]) |
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289 del ds2 |
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290 |
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291 #ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s. |
312
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292 ds2=ds.subset[1:7:2] |
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293 assert isinstance(ds2,DataSet) |
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294 test_ds(ds,ds2,[1,3,5]) |
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295 del ds2 |
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296 |
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297 #ds[i] |
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298 ds2=ds[5] |
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299 assert isinstance(ds2,Example) |
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300 assert have_raised("var['ds']["+str(len(ds))+"]",ds=ds) # index not defined |
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301 assert not have_raised("var['ds']["+str(len(ds)-1)+"]",ds=ds) |
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302 del ds2 |
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303 |
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304 #ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in. |
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305 ds2=ds.subset[[4,7,2,8]] |
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306 assert isinstance(ds2,DataSet) |
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307 test_ds(ds,ds2,[4,7,2,8]) |
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308 del ds2 |
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309 |
269
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310 #ds.<property># returns the value of a property associated with |
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311 #the name <property>. The following properties should be supported: |
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312 # - 'description': a textual description or name for the ds |
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313 # - 'fieldtypes': a list of types (one per field) |
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314 |
269
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315 #* ds1 | ds2 | ds3 == ds.hstack([ds1,ds2,ds3])#???? |
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316 #assert hstack([ds('x','y'),ds('z')])==ds |
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317 #hstack([ds('z','y'),ds('x')])==ds |
173 | 318 assert have_raised2(hstack,[ds('x'),ds('x')]) |
319 assert have_raised2(hstack,[ds('y','x'),ds('x')]) | |
320 assert not have_raised2(hstack,[ds('x'),ds('y')]) | |
269
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321 |
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322 # i=0 |
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323 # for example in hstack([ds('x'),ds('y'),ds('z')]): |
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324 # example==ds[i] |
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325 # i+=1 |
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326 # del i,example |
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327 #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])#???? |
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328 |
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329 def test_fields_fct(ds): |
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330 #@todo, fill correctly |
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331 assert len(ds.fields())==3 |
168 | 332 i=0 |
333 v=0 | |
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334 for field in ds.fields(): |
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335 for field_value in field: # iterate over the values associated to that field for all the ds examples |
168 | 336 v+=1 |
337 i+=1 | |
338 assert i==3 | |
339 assert v==3*10 | |
340 del i,v | |
341 | |
342 i=0 | |
343 v=0 | |
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344 for field in ds('x','z').fields(): |
168 | 345 i+=1 |
346 for val in field: | |
347 v+=1 | |
348 assert i==2 | |
349 assert v==2*10 | |
350 del i,v | |
351 | |
352 i=0 | |
353 v=0 | |
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354 for field in ds.fields('x','y'): |
168 | 355 i+=1 |
356 for val in field: | |
357 v+=1 | |
358 assert i==2 | |
359 assert v==2*10 | |
360 del i,v | |
361 | |
362 i=0 | |
363 v=0 | |
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364 for field_examples in ds.fields(): |
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365 for example_value in field_examples: |
168 | 366 v+=1 |
367 i+=1 | |
368 assert i==3 | |
369 assert v==3*10 | |
370 del i,v | |
371 | |
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372 assert ds == ds.fields().examples() |
168 | 373 assert len(ds('x','y').fields()) == 2 |
374 assert len(ds('x','z').fields()) == 2 | |
375 assert len(ds('y').fields()) == 1 | |
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376 |
168 | 377 del field |
315
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378 |
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379 def test_overrides(ds) : |
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380 """ Test for examples that an override __getitem__ acts as the one in DataSet """ |
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381 def ndarray_list_equal(nda,l) : |
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382 """ |
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383 Compares if a ndarray is the same as the list. Do it by converting the list into |
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384 an numpy.ndarray, if possible |
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385 """ |
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386 try : |
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387 l = numpy.asmatrix(l) |
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388 except : |
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389 return False |
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390 return smart_equal(nda,l) |
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391 |
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392 def smart_equal(a1,a2) : |
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393 """ |
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394 Handles numpy.ndarray, LookupList, and basic containers |
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395 """ |
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396 if not isinstance(a1,type(a2)) and not isinstance(a2,type(a1)): |
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397 #special case: matrix vs list of arrays |
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398 if isinstance(a1,numpy.ndarray) : |
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399 return ndarray_list_equal(a1,a2) |
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400 elif isinstance(a2,numpy.ndarray) : |
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401 return ndarray_list_equal(a2,a1) |
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402 return False |
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403 # compares 2 numpy.ndarray |
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404 if isinstance(a1,numpy.ndarray): |
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405 if len(a1.shape) != len(a2.shape): |
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406 return False |
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407 for k in range(len(a1.shape)) : |
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408 if a1.shape[k] != a2.shape[k]: |
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409 return False |
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410 return (a1==a2).all() |
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411 # compares 2 lookuplists |
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412 if isinstance(a1,LookupList) : |
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413 if len(a1._names) != len(a2._names) : |
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414 return False |
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415 for k in a1._names : |
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416 if k not in a2._names : |
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417 return False |
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418 if not smart_equal(a1[k],a2[k]) : |
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419 return False |
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420 return True |
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421 # compares 2 basic containers |
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422 if hasattr(a1,'__len__'): |
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423 if len(a1) != len(a2) : |
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424 return False |
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425 for k in range(len(a1)) : |
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426 if not smart_equal(a1[k],a2[k]): |
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427 return False |
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428 return True |
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429 # try basic equals |
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430 return a1 is a2 |
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431 |
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432 def mask(ds) : |
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433 class TestOverride(type(ds)): |
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434 def __init__(self,ds) : |
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435 self.ds = ds |
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436 def __getitem__(self,key) : |
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437 res1 = self.ds[key] |
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438 res2 = DataSet.__getitem__(ds,key) |
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439 assert smart_equal(res1,res2) |
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440 return res1 |
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441 return TestOverride(ds) |
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442 # test getitem |
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443 ds2 = mask(ds) |
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444 for k in range(10): |
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445 res = ds2[k] |
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446 res = ds2[1:len(ds):3] |
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447 |
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448 |
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449 |
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450 |
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451 |
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452 |
194
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453 def test_all(array,ds): |
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454 assert len(ds)==10 |
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455 test_iterate_over_examples(array, ds) |
315
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456 test_overrides(ds) |
194
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457 test_getitem(array, ds) |
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458 test_ds_iterator(array,ds('x','y'),ds('y','z'),ds('x','y','z')) |
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459 test_fields_fct(ds) |
145
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make some function global to reuse them to test other dataset
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460 |
315
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461 |
279
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462 class T_DataSet(unittest.TestCase): |
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463 def test_ArrayDataSet(self): |
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464 #don't test stream |
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465 #tested only with float value |
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466 #don't always test with y |
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467 #don't test missing value |
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468 #don't test with tuple |
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469 #don't test proterties |
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470 a2 = numpy.random.rand(10,4) |
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471 ds = ArrayDataSet(a2,{'x':slice(3),'y':3,'z':[0,2]})###???tuple not tested |
292 | 472 ds = ArrayDataSet(a2,Example(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
279
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473 #assert ds==a? should this work? |
100
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restructuring and added test
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diff
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474 |
279
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475 test_all(a2,ds) |
169
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476 |
279
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|
477 del a2, ds |
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Added test for ArrayDataSet and LookUpList
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diff
changeset
|
478 |
279
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479 def test_CachedDataSet(self): |
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480 a = numpy.random.rand(10,4) |
292 | 481 ds1 = ArrayDataSet(a,Example(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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482 ds2 = CachedDataSet(ds1) |
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483 ds3 = CachedDataSet(ds1,cache_all_upon_construction=True) |
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484 |
279
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|
485 test_all(a,ds2) |
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486 test_all(a,ds3) |
169
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|
487 |
279
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|
488 del a,ds1,ds2,ds3 |
148
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diff
changeset
|
489 |
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changeset
|
490 |
279
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491 def test_DataSetFields(self): |
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492 raise NotImplementedError() |
161
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diff
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|
493 |
279
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494 def test_ApplyFunctionDataSet(self): |
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495 a = numpy.random.rand(10,4) |
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496 a2 = a+1 |
292 | 497 ds1 = ArrayDataSet(a,Example(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
202
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changeset
|
498 |
279
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|
499 ds2 = ApplyFunctionDataSet(ds1,lambda x,y,z: (x+1,y+1,z+1), ['x','y','z'],minibatch_mode=False) |
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|
500 ds3 = ApplyFunctionDataSet(ds1,lambda x,y,z: (numpy.array(x)+1,numpy.array(y)+1,numpy.array(z)+1), |
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|
501 ['x','y','z'], |
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|
502 minibatch_mode=True) |
202
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|
503 |
279
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504 test_all(a2,ds2) |
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505 test_all(a2,ds3) |
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506 |
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507 del a,ds1,ds2,ds3 |
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508 |
279
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509 def test_FieldsSubsetDataSet(self): |
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510 a = numpy.random.rand(10,4) |
297 | 511 ds = ArrayDataSet(a,Example(['x','y','z','w'],[slice(3),3,[0,2],0])) |
289
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512 ds = FieldsSubsetDataSet(ds,['x','y','z']) |
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513 |
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514 test_all(a,ds) |
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515 |
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516 del a, ds |
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517 |
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518 def test_MinibatchDataSet(self): |
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519 raise NotImplementedError() |
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520 def test_HStackedDataSet(self): |
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521 raise NotImplementedError() |
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522 def test_VStackedDataSet(self): |
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523 raise NotImplementedError() |
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524 def test_ArrayFieldsDataSet(self): |
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525 raise NotImplementedError() |
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526 |
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527 |
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528 class T_Exotic1(unittest.TestCase): |
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529 class DataSet(DataSet): |
295
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530 """ Dummy dataset, where one field is a ndarray of variables size. """ |
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531 def __len__(self) : |
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532 return 100 |
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533 def fieldNames(self) : |
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534 return 'input','target','name' |
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535 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset): |
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536 class MultiLengthDataSetIterator(object): |
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537 def __init__(self,dataset,fieldnames,minibatch_size,n_batches,offset): |
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538 if fieldnames is None: fieldnames = dataset.fieldNames() |
297 | 539 self.minibatch = Example(fieldnames,range(len(fieldnames))) |
295
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540 self.dataset, self.minibatch_size, self.current = dataset, minibatch_size, offset |
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541 def __iter__(self): |
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542 return self |
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543 def next(self): |
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544 for k in self.minibatch._names : |
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545 self.minibatch[k] = [] |
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546 for ex in range(self.minibatch_size) : |
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547 if 'input' in self.minibatch._names: |
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548 self.minibatch['input'].append( numpy.array( range(self.current + 1) ) ) |
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549 if 'target' in self.minibatch._names: |
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550 self.minibatch['target'].append( self.current % 2 ) |
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551 if 'name' in self.minibatch._names: |
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552 self.minibatch['name'].append( str(self.current) ) |
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553 self.current += 1 |
295
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554 return self.minibatch |
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555 return MultiLengthDataSetIterator(self,fieldnames,minibatch_size,n_batches,offset) |
298
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556 |
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557 def test_ApplyFunctionDataSet(self): |
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558 ds = T_Exotic1.DataSet() |
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559 dsa = ApplyFunctionDataSet(ds,lambda x,y,z: (x[-1],y*10,int(z)),['input','target','name'],minibatch_mode=False) #broken!!!!!! |
298
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560 for k in range(len(dsa)): |
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561 res = dsa[k] |
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562 self.failUnless(ds[k]('input')[0][-1] == res('input')[0] , 'problem in first applied function') |
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563 res = dsa[33:96:3] |
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564 |
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565 def test_CachedDataSet(self): |
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566 ds = T_Exotic1.DataSet() |
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567 dsc = CachedDataSet(ds) |
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568 for k in range(len(dsc)) : |
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569 self.failUnless(numpy.all( dsc[k]('input')[0] == ds[k]('input')[0] ) , (dsc[k],ds[k]) ) |
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570 res = dsc[:] |
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571 |
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572 if __name__=='__main__': |
289
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573 if len(sys.argv)==2: |
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574 if sys.argv[1]=="--debug": |
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575 module = __import__("_test_dataset") |
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576 tests = unittest.TestLoader().loadTestsFromModule(module) |
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577 tests.debug() |
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578 print "bad argument: only --debug is accepted" |
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579 elif len(sys.argv)==1: |
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580 unittest.main() |
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581 else: |
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582 print "bad argument: only --debug is accepted" |
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583 |