Mercurial > pylearn

annotate _test_dataset.py @ 24:2e8be9f5412b

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added nnet_ops
author bergstrj@iro.umontreal.ca
date Thu, 10 Apr 2008 17:25:13 -0400
parents b6b36f65664f
children 672fe4b23032
rev   line source
4
f7dcfb5f9d5b Added test for dataset.
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diff changeset
1 from dataset import *
f7dcfb5f9d5b Added test for dataset.
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2 from math import *
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3 import unittest
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4
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5 def _sum_all(a):
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6 s=a
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7 while isinstance(s,numpy.ndarray):
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8 s=sum(s)
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9 return s
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10
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11 class T_arraydataset(unittest.TestCase):
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12 def setUp(self):
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13 numpy.random.seed(123456)
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14
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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]))
fdf0abc490f7 Adapted _test_dataset.py to changes in LookupList
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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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6f8f338686db Moved iterating counter into a FiniteDataSetIterator to allow embedded iterations and multiple threads iterating at the same time on a dataset.
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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_asarray(self):
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52 arr = numpy.random.rand(3,4)
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b6b36f65664f Created virtual sub-classes of DataSet: {Finite{Length,Width},Sliceable}DataSet,
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53 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(2,4)})
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54 a_arr = numpy.asarray(a)
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55 self.failUnless(a_arr.shape[1] == 2 + 2)
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56 self.failUnless(numpy.sum(numpy.square(a_arr-a.data))==0)
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57 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,4)})
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58 a_arr = numpy.asarray(a)
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59 self.failUnless(a_arr.shape[1] == 2 + 3)
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60
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61 def test_minibatch_wraparound_even(self):
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62 arr = numpy.random.rand(10,4)
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63 arr2 = ArrayDataSet.Iterator.matcat(arr,arr)
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64
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65 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,4)})
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66
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67 #print arr
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68 for i, x in enumerate(a.minibatches(["x"], minibatch_size=2, n_batches=8)):
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69 #print 'x' , x
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70 self.failUnless(numpy.all( x == arr2[i*2:i*2+2,0:2]))
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71
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72 def test_minibatch_wraparound_odd(self):
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73 arr = numpy.random.rand(10,4)
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74 arr2 = ArrayDataSet.Iterator.matcat(arr,arr)
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75
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76 a=ArrayDataSet(data=arr,fields={"x":slice(2),"y":slice(1,4)})
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77
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78 for i, x in enumerate(a.minibatches(["x"], minibatch_size=3, n_batches=6)):
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79 self.failUnless(numpy.all( x == arr2[i*3:i*3+3,0:2]))
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57f4015e2e09 Iterators extend LookupList
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80
4
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81 if __name__ == '__main__':
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82 unittest.main()
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83