Mercurial > pylearn
annotate _test_dataset.py @ 219:5b3afda2f1ad
added a class to test any new dataset
author | Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca> |
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date | Fri, 23 May 2008 13:16:42 -0400 |
parents | 46c5c90019c2 |
children | 1f527fe65e22 |
rev | line source |
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4 | 1 from dataset import * |
2 from math import * | |
3 import unittest | |
4 | |
5 def _sum_all(a): | |
6 s=a | |
7 while isinstance(s,numpy.ndarray): | |
8 s=sum(s) | |
9 return s | |
10 | |
11 class T_arraydataset(unittest.TestCase): | |
12 def setUp(self): | |
13 numpy.random.seed(123456) | |
14 | |
17
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15 |
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16 def test_ctor_len(self): |
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17 n = numpy.random.rand(8,3) |
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18 a=ArrayDataSet(n) |
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19 self.failUnless(a.data is n) |
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20 self.failUnless(a.fields is None) |
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21 |
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22 self.failUnless(len(a) == n.shape[0]) |
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23 self.failUnless(a[0].shape == (n.shape[1],)) |
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24 |
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25 def test_iter(self): |
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26 arr = numpy.random.rand(8,3) |
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27 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,3)}) |
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28 for i, example in enumerate(a): |
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29 self.failUnless(numpy.all( example['x'] == arr[i,:2])) |
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30 self.failUnless(numpy.all( example['y'] == arr[i,1:3])) |
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31 |
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32 def test_zip(self): |
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33 arr = numpy.random.rand(8,3) |
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34 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,3)}) |
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35 for i, x in enumerate(a.zip("x")): |
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36 self.failUnless(numpy.all( x == arr[i,:2])) |
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37 |
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38 def test_minibatch_basic(self): |
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39 arr = numpy.random.rand(10,4) |
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40 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,4)}) |
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41 for i, mb in enumerate(a.minibatches(minibatch_size=2)): #all fields |
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42 self.failUnless(numpy.all( mb['x'] == arr[i*2:i*2+2,0:2])) |
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43 self.failUnless(numpy.all( mb['y'] == arr[i*2:i*2+2,1:4])) |
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44 |
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45 def test_getattr(self): |
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46 arr = numpy.random.rand(10,4) |
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47 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,4)}) |
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48 a_y = a.y |
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49 self.failUnless(numpy.all( a_y == arr[:,1:4])) |
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50 |
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51 def test_minibatch_wraparound_even(self): |
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52 arr = numpy.random.rand(10,4) |
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53 arr2 = ArrayDataSet.Iterator.matcat(arr,arr) |
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54 |
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55 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,4)}) |
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56 |
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57 #print arr |
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58 for i, x in enumerate(a.minibatches(["x"], minibatch_size=2, n_batches=8)): |
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59 #print 'x' , x |
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60 self.failUnless(numpy.all( x == arr2[i*2:i*2+2,0:2])) |
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61 |
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62 def test_minibatch_wraparound_odd(self): |
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63 arr = numpy.random.rand(10,4) |
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64 arr2 = ArrayDataSet.Iterator.matcat(arr,arr) |
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65 |
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66 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,4)}) |
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67 |
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68 for i, x in enumerate(a.minibatches(["x"], minibatch_size=3, n_batches=6)): |
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69 self.failUnless(numpy.all( x == arr2[i*3:i*3+3,0:2])) |
19 | 70 |
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71 |
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72 class T_renamingdataset(unittest.TestCase): |
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73 def setUp(self): |
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74 numpy.random.seed(123456) |
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75 |
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76 |
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77 def test_hasfield(self): |
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78 n = numpy.random.rand(3,8) |
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79 a=ArrayDataSet(data=n,fields={"x":slice(2),"y":slice(1,4),"z":slice(4,6)}) |
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80 b=a.rename({'xx':'x','zz':'z'}) |
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81 self.failUnless(b.hasFields('xx','zz') and not b.hasFields('x') and not b.hasFields('y')) |
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82 |
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83 class T_applyfunctiondataset(unittest.TestCase): |
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84 def setUp(self): |
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85 numpy.random.seed(123456) |
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86 |
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87 def test_function(self): |
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88 n = numpy.random.rand(3,8) |
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89 a=ArrayDataSet(data=n,fields={"x":slice(2),"y":slice(1,4),"z":slice(4,6)}) |
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90 b=a.apply_function(lambda x,y: x+y,x+1, ['x','y'], ['x+y','x+1'], False,False,False) |
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91 print b.fieldNames() |
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92 print b('x+y') |
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93 |
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94 |
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95 # to be used with a any new dataset |
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96 class T_dataset_tester(object): |
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97 """ |
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98 This class' goal is to test any new dataset that is created |
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99 """ |
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100 |
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101 |
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102 def __init__(self,ds,runall=True) : |
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103 """if interested in only a subset of test, init with runall=False""" |
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104 self.ds = ds |
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105 |
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106 if runall : |
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107 self.test1_basicstats(ds) |
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108 self.test2_slicing(ds) |
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109 |
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110 def test1_basicstats(self,ds) : |
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111 """print basics stats on a dataset, like length""" |
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112 |
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113 print 'len(ds) = ',len(ds) |
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114 print 'num fields = ', len(ds.fieldNames()) |
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115 print 'types of field: ', |
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116 for k in ds.fieldNames() : |
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117 print type(ds[0](k)[0]), |
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118 print '' |
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119 |
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120 def test2_slicing(self,ds) : |
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121 """test if slicing works properly""" |
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122 print 'testing slicing...', |
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123 sys.stdout.flush() |
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124 middle = len(ds) / 2 |
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125 tenpercent = int(len(ds) * .1) |
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126 set1 = ds[:middle+tenpercent] |
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127 set2 = ds[middle-tenpercent:] |
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128 |
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129 |
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130 ################################################################### |
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131 # main |
4 | 132 if __name__ == '__main__': |
133 unittest.main() | |
134 |