# HG changeset patch
# User Frederic Bastien <bastienf@iro.umontreal.ca>
# Date 1212774757 14400
# Node ID 8e923cb2e8fcefc815c334612a54162dbe32eba1
# Parent  275b92d40ea629fc3ffe132fde736e9101e40d62
renamed file

diff -r 275b92d40ea6 -r 8e923cb2e8fc _test2_dataset.py
--- a/_test2_dataset.py	Fri Jun 06 13:52:13 2008 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,442 +0,0 @@
-#!/bin/env python
-from dataset import *
-from math import *
-import numpy,unittest
-from misc import *
-
-def have_raised(to_eval, **var):
-    have_thrown = False
-    try:
-        eval(to_eval)
-    except :
-        have_thrown = True
-    return have_thrown
-
-def have_raised2(f, *args, **kwargs):
-    have_thrown = False
-    try:
-        f(*args, **kwargs)
-    except :
-        have_thrown = True
-    return have_thrown
-
-def test1():
-    print "test1"
-    global a,ds
-    a = numpy.random.rand(10,4)
-    print a
-    ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]})
-    print "len(ds)=",len(ds)
-    assert(len(ds)==10)
-    print "example 0 = ",ds[0]
-#    assert
-    print "x=",ds["x"]
-    print "x|y"
-    for x,y in ds("x","y"):
-        print x,y
-    minibatch_iterator = ds.minibatches(fieldnames=['z','y'],n_batches=1,minibatch_size=3,offset=4)
-    minibatch = minibatch_iterator.__iter__().next()
-    print "minibatch=",minibatch
-    for var in minibatch:
-        print "var=",var
-    print "take a slice and look at field y",ds[1:6:2]["y"]
-
-    del a,ds,x,y,minibatch_iterator,minibatch,var
-
-def test_iterate_over_examples(array,ds):
-#not in doc!!!
-    i=0
-    for example in range(len(ds)):
-        assert (ds[example]['x']==array[example][:3]).all()
-        assert ds[example]['y']==array[example][3]
-        assert (ds[example]['z']==array[example][[0,2]]).all()
-        i+=1
-    assert i==len(ds)
-    del example,i
-
-#     - for example in dataset:
-    i=0
-    for example in ds:
-        assert len(example)==3
-        assert (example['x']==array[i][:3]).all()
-        assert example['y']==array[i][3]
-        assert (example['z']==array[i][0:3:2]).all()
-        assert (numpy.append(example['x'],example['y'])==array[i]).all()
-        i+=1
-    assert i==len(ds)
-    del example,i
-
-#     - for val1,val2,... in dataset:
-    i=0
-    for x,y,z in ds:
-        assert (x==array[i][:3]).all()
-        assert y==array[i][3]
-        assert (z==array[i][0:3:2]).all()
-        assert (numpy.append(x,y)==array[i]).all()
-        i+=1
-    assert i==len(ds)
-    del x,y,z,i
-
-#     - for example in dataset(field1, field2,field3, ...):
-    i=0
-    for example in ds('x','y','z'):
-        assert len(example)==3
-        assert (example['x']==array[i][:3]).all()
-        assert example['y']==array[i][3]
-        assert (example['z']==array[i][0:3:2]).all()
-        assert (numpy.append(example['x'],example['y'])==array[i]).all()
-        i+=1
-    assert i==len(ds)
-    del example,i
-    i=0
-    for example in ds('y','x'):
-        assert len(example)==2
-        assert (example['x']==array[i][:3]).all()
-        assert example['y']==array[i][3]
-        assert (numpy.append(example['x'],example['y'])==array[i]).all()
-        i+=1
-    assert i==len(ds)
-    del example,i
-
-#     - for val1,val2,val3 in dataset(field1, field2,field3):
-    i=0
-    for x,y,z in ds('x','y','z'):
-        assert (x==array[i][:3]).all()
-        assert y==array[i][3]
-        assert (z==array[i][0:3:2]).all()
-        assert (numpy.append(x,y)==array[i]).all()
-        i+=1
-    assert i==len(ds)
-    del x,y,z,i
-    i=0
-    for y,x in ds('y','x',):
-        assert (x==array[i][:3]).all()
-        assert y==array[i][3]
-        assert (numpy.append(x,y)==array[i]).all()
-        i+=1
-    assert i==len(ds)
-    del x,y,i
-
-    def test_minibatch_size(minibatch,minibatch_size,len_ds,nb_field,nb_iter_finished):
-        ##full minibatch or the last minibatch
-        for idx in range(nb_field):
-            test_minibatch_field_size(minibatch[idx],minibatch_size,len_ds,nb_iter_finished)
-        del idx
-    def test_minibatch_field_size(minibatch_field,minibatch_size,len_ds,nb_iter_finished):
-        assert len(minibatch_field)==minibatch_size or ((nb_iter_finished*minibatch_size+len(minibatch_field))==len_ds and len(minibatch_field)<minibatch_size)
-
-#     - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N):
-    i=0
-    mi=0
-    m=ds.minibatches(['x','z'], minibatch_size=3)
-    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
-    for minibatch in m:
-        assert isinstance(minibatch,DataSetFields)
-        assert len(minibatch)==2
-        test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi)
-        if type(ds)==ArrayDataSet:
-            assert (minibatch[0][:,::2]==minibatch[1]).all()
-        else:
-            for j in xrange(len(minibatch[0])):
-                (minibatch[0][j][::2]==minibatch[1][j]).all()
-        mi+=1
-        i+=len(minibatch[0])
-    assert i==len(ds)
-    assert mi==4
-    del minibatch,i,m,mi
-
-    i=0
-    mi=0
-    m=ds.minibatches(['x','y'], minibatch_size=3)
-    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
-    for minibatch in m:
-        assert len(minibatch)==2
-        test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi)
-        mi+=1
-        for id in range(len(minibatch[0])):
-            assert (numpy.append(minibatch[0][id],minibatch[1][id])==array[i]).all()
-            i+=1
-    assert i==len(ds)
-    assert mi==4
-    del minibatch,i,id,m,mi
-
-#     - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N):
-    i=0
-    mi=0
-    m=ds.minibatches(['x','z'], minibatch_size=3)
-    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
-    for x,z in m:
-        test_minibatch_field_size(x,m.minibatch_size,len(ds),mi)
-        test_minibatch_field_size(z,m.minibatch_size,len(ds),mi)
-        for id in range(len(x)):
-            assert (x[id][::2]==z[id]).all()
-            i+=1
-        mi+=1
-    assert i==len(ds)
-    assert mi==4
-    del x,z,i,m,mi
-    i=0
-    mi=0
-    m=ds.minibatches(['x','y'], minibatch_size=3)
-    for x,y in m:
-        test_minibatch_field_size(x,m.minibatch_size,len(ds),mi)
-        test_minibatch_field_size(y,m.minibatch_size,len(ds),mi)
-        mi+=1
-        for id in range(len(x)):
-            assert (numpy.append(x[id],y[id])==array[i]).all()
-            i+=1
-    assert i==len(ds)
-    assert mi==4
-    del x,y,i,id,m,mi
-
-#not in doc
-    i=0
-    m=ds.minibatches(['x','y'],n_batches=1,minibatch_size=3,offset=4)
-    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
-    for x,y in m:
-        assert len(x)==m.minibatch_size
-        assert len(y)==m.minibatch_size
-        for id in range(m.minibatch_size):
-            assert (numpy.append(x[id],y[id])==array[i+4]).all()
-            i+=1
-    assert i==m.n_batches*m.minibatch_size
-    del x,y,i,id,m
-
-    i=0
-    m=ds.minibatches(['x','y'],n_batches=2,minibatch_size=3,offset=4)
-    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
-    for x,y in m:
-        assert len(x)==m.minibatch_size
-        assert len(y)==m.minibatch_size
-        for id in range(m.minibatch_size):
-            assert (numpy.append(x[id],y[id])==array[i+4]).all()
-            i+=1
-    assert i==m.n_batches*m.minibatch_size
-    del x,y,i,id,m
-
-    i=0
-    m=ds.minibatches(['x','y'],n_batches=20,minibatch_size=3,offset=4)
-    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
-    for x,y in m:
-        assert len(x)==m.minibatch_size
-        assert len(y)==m.minibatch_size
-        for id in range(m.minibatch_size):
-            assert (numpy.append(x[id],y[id])==array[(i+4)%array.shape[0]]).all()
-            i+=1
-    assert i==m.n_batches*m.minibatch_size
-    del x,y,i,id
-
-    #@todo: we can't do minibatch bigger then the size of the dataset???
-    assert have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array)+1,offset=0)
-    assert not have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array),offset=0)
-
-def test_ds_iterator(array,iterator1,iterator2,iterator3):
-    l=len(iterator1)
-    i=0
-    for x,y in iterator1:
-        assert (x==array[i][:3]).all()
-        assert y==array[i][3]
-        assert (numpy.append(x,y)==array[i]).all()
-        i+=1
-    assert i==l
-    i=0
-    for y,z in iterator2:
-        assert y==array[i][3]
-        assert (z==array[i][0:3:2]).all()
-        i+=1
-    assert i==l
-    i=0
-    for x,y,z in iterator3:
-        assert (x==array[i][:3]).all()
-        assert y==array[i][3]
-        assert (z==array[i][0:3:2]).all()
-        assert (numpy.append(x,y)==array[i]).all()
-        i+=1
-    assert i==l
-
-def test_getitem(array,ds):
-    def test_ds(orig,ds,index):
-        i=0
-        assert len(ds)==len(index)
-        for x,z,y in ds('x','z','y'):
-            assert (orig[index[i]]['x']==array[index[i]][:3]).all()
-            assert (orig[index[i]]['x']==x).all()
-            assert orig[index[i]]['y']==array[index[i]][3]
-            assert orig[index[i]]['y']==y
-            assert (orig[index[i]]['z']==array[index[i]][0:3:2]).all()
-            assert (orig[index[i]]['z']==z).all()
-            i+=1
-        del i
-        ds[0]
-        if len(ds)>2:
-            ds[:1]
-            ds[1:1]
-            ds[1:1:1]
-        if len(ds)>5:
-            ds[[1,2,3]]
-        for x in ds:
-            pass
-
-#ds[:n] returns a dataset with the n first examples.
-    ds2=ds[:3]
-    assert isinstance(ds2,DataSet)
-    test_ds(ds,ds2,index=[0,1,2])
-    del ds2
-
-#ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s.
-    ds2=ds[1:7:2]
-    assert isinstance(ds2,DataSet)
-    test_ds(ds,ds2,[1,3,5])
-    del ds2
-
-#ds[i]
-    ds2=ds[5]
-    assert isinstance(ds2,Example)
-    assert have_raised("var['ds']["+str(len(ds))+"]",ds=ds)  # index not defined
-    assert not have_raised("var['ds']["+str(len(ds)-1)+"]",ds=ds)
-    del ds2
-
-#ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in.
-    ds2=ds[[4,7,2,8]]
-    assert isinstance(ds2,DataSet)
-    test_ds(ds,ds2,[4,7,2,8])
-    del ds2
-
-    #ds.<property># returns the value of a property associated with
-      #the name <property>. The following properties should be supported:
-      #    - 'description': a textual description or name for the ds
-      #    - 'fieldtypes': a list of types (one per field)
-
-    #* ds1 | ds2 | ds3 == ds.hstack([ds1,ds2,ds3])#????
-        #assert hstack([ds('x','y'),ds('z')])==ds
-        #hstack([ds('z','y'),ds('x')])==ds
-    assert have_raised2(hstack,[ds('x'),ds('x')])
-    assert have_raised2(hstack,[ds('y','x'),ds('x')])
-    assert not have_raised2(hstack,[ds('x'),ds('y')])
-        
-    #        i=0
-    #        for example in hstack([ds('x'),ds('y'),ds('z')]):
-    #            example==ds[i]
-    #            i+=1 
-    #        del i,example
-    #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])#????
-
-def test_fields_fct(ds):
-    #@todo, fill correctly
-    assert len(ds.fields())==3
-    i=0
-    v=0
-    for field in ds.fields():
-        for field_value in field: # iterate over the values associated to that field for all the ds examples
-            v+=1
-        i+=1
-    assert i==3
-    assert v==3*10
-    del i,v
-    
-    i=0
-    v=0
-    for field in ds('x','z').fields():
-        i+=1
-        for val in field:
-            v+=1
-    assert i==2
-    assert v==2*10
-    del i,v
-    
-    i=0
-    v=0
-    for field in ds.fields('x','y'):
-        i+=1
-        for val in field:
-            v+=1
-    assert i==2
-    assert v==2*10
-    del i,v
-    
-    i=0
-    v=0
-    for field_examples in ds.fields():
-        for example_value in field_examples:
-            v+=1
-        i+=1
-    assert i==3
-    assert v==3*10
-    del i,v
-    
-    assert ds == ds.fields().examples()
-    assert len(ds('x','y').fields()) == 2
-    assert len(ds('x','z').fields()) == 2
-    assert len(ds('y').fields()) == 1
-
-    del field
-def test_all(array,ds):
-    assert len(ds)==10
-
-    test_iterate_over_examples(array, ds)
-    test_getitem(array, ds)
-    test_ds_iterator(array,ds('x','y'),ds('y','z'),ds('x','y','z'))
-    test_fields_fct(ds)
-
-class T_DataSet(unittest.TestCase):
-    def test_ArrayDataSet(self):
-        #don't test stream
-        #tested only with float value
-        #don't always test with y
-        #don't test missing value
-        #don't test with tuple
-        #don't test proterties
-        a2 = numpy.random.rand(10,4)
-        ds = ArrayDataSet(a2,{'x':slice(3),'y':3,'z':[0,2]})###???tuple not tested
-        ds = ArrayDataSet(a2,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested
-        #assert ds==a? should this work?
-
-        test_all(a2,ds)
-
-        del a2, ds
-
-    def test_CachedDataSet(self):
-        a = numpy.random.rand(10,4)
-        ds1 = ArrayDataSet(a,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested
-        ds2 = CachedDataSet(ds1)
-        ds3 = CachedDataSet(ds1,cache_all_upon_construction=True)
-
-        test_all(a,ds2)
-        test_all(a,ds3)
-
-        del a,ds1,ds2,ds3
-
-
-    def test_DataSetFields(self):
-        raise NotImplementedError()
-
-    def test_ApplyFunctionDataSet(self):
-        a = numpy.random.rand(10,4)
-        a2 = a+1
-        ds1 = ArrayDataSet(a,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested
-
-        ds2 = ApplyFunctionDataSet(ds1,lambda x,y,z: (x+1,y+1,z+1), ['x','y','z'],minibatch_mode=False)
-        ds3 = ApplyFunctionDataSet(ds1,lambda x,y,z: (numpy.array(x)+1,numpy.array(y)+1,numpy.array(z)+1),
-                                   ['x','y','z'],
-                                   minibatch_mode=True)
-
-        test_all(a2,ds2)
-        test_all(a2,ds3)
-
-        del a,ds1,ds2,ds3
-
-    def test_FieldsSubsetDataSet(self):
-        raise NotImplementedError()
-    def test_MinibatchDataSet(self):
-        raise NotImplementedError()
-    def test_HStackedDataSet(self):
-        raise NotImplementedError()
-    def test_VStackedDataSet(self):
-        raise NotImplementedError()
-    def test_ArrayFieldsDataSet(self):
-        raise NotImplementedError()
-
-
-if __name__=='__main__':
-    unittest.main()
-
diff -r 275b92d40ea6 -r 8e923cb2e8fc _test_dataset.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/_test_dataset.py	Fri Jun 06 13:52:37 2008 -0400
@@ -0,0 +1,442 @@
+#!/bin/env python
+from dataset import *
+from math import *
+import numpy,unittest
+from misc import *
+
+def have_raised(to_eval, **var):
+    have_thrown = False
+    try:
+        eval(to_eval)
+    except :
+        have_thrown = True
+    return have_thrown
+
+def have_raised2(f, *args, **kwargs):
+    have_thrown = False
+    try:
+        f(*args, **kwargs)
+    except :
+        have_thrown = True
+    return have_thrown
+
+def test1():
+    print "test1"
+    global a,ds
+    a = numpy.random.rand(10,4)
+    print a
+    ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]})
+    print "len(ds)=",len(ds)
+    assert(len(ds)==10)
+    print "example 0 = ",ds[0]
+#    assert
+    print "x=",ds["x"]
+    print "x|y"
+    for x,y in ds("x","y"):
+        print x,y
+    minibatch_iterator = ds.minibatches(fieldnames=['z','y'],n_batches=1,minibatch_size=3,offset=4)
+    minibatch = minibatch_iterator.__iter__().next()
+    print "minibatch=",minibatch
+    for var in minibatch:
+        print "var=",var
+    print "take a slice and look at field y",ds[1:6:2]["y"]
+
+    del a,ds,x,y,minibatch_iterator,minibatch,var
+
+def test_iterate_over_examples(array,ds):
+#not in doc!!!
+    i=0
+    for example in range(len(ds)):
+        assert (ds[example]['x']==array[example][:3]).all()
+        assert ds[example]['y']==array[example][3]
+        assert (ds[example]['z']==array[example][[0,2]]).all()
+        i+=1
+    assert i==len(ds)
+    del example,i
+
+#     - for example in dataset:
+    i=0
+    for example in ds:
+        assert len(example)==3
+        assert (example['x']==array[i][:3]).all()
+        assert example['y']==array[i][3]
+        assert (example['z']==array[i][0:3:2]).all()
+        assert (numpy.append(example['x'],example['y'])==array[i]).all()
+        i+=1
+    assert i==len(ds)
+    del example,i
+
+#     - for val1,val2,... in dataset:
+    i=0
+    for x,y,z in ds:
+        assert (x==array[i][:3]).all()
+        assert y==array[i][3]
+        assert (z==array[i][0:3:2]).all()
+        assert (numpy.append(x,y)==array[i]).all()
+        i+=1
+    assert i==len(ds)
+    del x,y,z,i
+
+#     - for example in dataset(field1, field2,field3, ...):
+    i=0
+    for example in ds('x','y','z'):
+        assert len(example)==3
+        assert (example['x']==array[i][:3]).all()
+        assert example['y']==array[i][3]
+        assert (example['z']==array[i][0:3:2]).all()
+        assert (numpy.append(example['x'],example['y'])==array[i]).all()
+        i+=1
+    assert i==len(ds)
+    del example,i
+    i=0
+    for example in ds('y','x'):
+        assert len(example)==2
+        assert (example['x']==array[i][:3]).all()
+        assert example['y']==array[i][3]
+        assert (numpy.append(example['x'],example['y'])==array[i]).all()
+        i+=1
+    assert i==len(ds)
+    del example,i
+
+#     - for val1,val2,val3 in dataset(field1, field2,field3):
+    i=0
+    for x,y,z in ds('x','y','z'):
+        assert (x==array[i][:3]).all()
+        assert y==array[i][3]
+        assert (z==array[i][0:3:2]).all()
+        assert (numpy.append(x,y)==array[i]).all()
+        i+=1
+    assert i==len(ds)
+    del x,y,z,i
+    i=0
+    for y,x in ds('y','x',):
+        assert (x==array[i][:3]).all()
+        assert y==array[i][3]
+        assert (numpy.append(x,y)==array[i]).all()
+        i+=1
+    assert i==len(ds)
+    del x,y,i
+
+    def test_minibatch_size(minibatch,minibatch_size,len_ds,nb_field,nb_iter_finished):
+        ##full minibatch or the last minibatch
+        for idx in range(nb_field):
+            test_minibatch_field_size(minibatch[idx],minibatch_size,len_ds,nb_iter_finished)
+        del idx
+    def test_minibatch_field_size(minibatch_field,minibatch_size,len_ds,nb_iter_finished):
+        assert len(minibatch_field)==minibatch_size or ((nb_iter_finished*minibatch_size+len(minibatch_field))==len_ds and len(minibatch_field)<minibatch_size)
+
+#     - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N):
+    i=0
+    mi=0
+    m=ds.minibatches(['x','z'], minibatch_size=3)
+    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
+    for minibatch in m:
+        assert isinstance(minibatch,DataSetFields)
+        assert len(minibatch)==2
+        test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi)
+        if type(ds)==ArrayDataSet:
+            assert (minibatch[0][:,::2]==minibatch[1]).all()
+        else:
+            for j in xrange(len(minibatch[0])):
+                (minibatch[0][j][::2]==minibatch[1][j]).all()
+        mi+=1
+        i+=len(minibatch[0])
+    assert i==len(ds)
+    assert mi==4
+    del minibatch,i,m,mi
+
+    i=0
+    mi=0
+    m=ds.minibatches(['x','y'], minibatch_size=3)
+    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
+    for minibatch in m:
+        assert len(minibatch)==2
+        test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi)
+        mi+=1
+        for id in range(len(minibatch[0])):
+            assert (numpy.append(minibatch[0][id],minibatch[1][id])==array[i]).all()
+            i+=1
+    assert i==len(ds)
+    assert mi==4
+    del minibatch,i,id,m,mi
+
+#     - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N):
+    i=0
+    mi=0
+    m=ds.minibatches(['x','z'], minibatch_size=3)
+    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
+    for x,z in m:
+        test_minibatch_field_size(x,m.minibatch_size,len(ds),mi)
+        test_minibatch_field_size(z,m.minibatch_size,len(ds),mi)
+        for id in range(len(x)):
+            assert (x[id][::2]==z[id]).all()
+            i+=1
+        mi+=1
+    assert i==len(ds)
+    assert mi==4
+    del x,z,i,m,mi
+    i=0
+    mi=0
+    m=ds.minibatches(['x','y'], minibatch_size=3)
+    for x,y in m:
+        test_minibatch_field_size(x,m.minibatch_size,len(ds),mi)
+        test_minibatch_field_size(y,m.minibatch_size,len(ds),mi)
+        mi+=1
+        for id in range(len(x)):
+            assert (numpy.append(x[id],y[id])==array[i]).all()
+            i+=1
+    assert i==len(ds)
+    assert mi==4
+    del x,y,i,id,m,mi
+
+#not in doc
+    i=0
+    m=ds.minibatches(['x','y'],n_batches=1,minibatch_size=3,offset=4)
+    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
+    for x,y in m:
+        assert len(x)==m.minibatch_size
+        assert len(y)==m.minibatch_size
+        for id in range(m.minibatch_size):
+            assert (numpy.append(x[id],y[id])==array[i+4]).all()
+            i+=1
+    assert i==m.n_batches*m.minibatch_size
+    del x,y,i,id,m
+
+    i=0
+    m=ds.minibatches(['x','y'],n_batches=2,minibatch_size=3,offset=4)
+    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
+    for x,y in m:
+        assert len(x)==m.minibatch_size
+        assert len(y)==m.minibatch_size
+        for id in range(m.minibatch_size):
+            assert (numpy.append(x[id],y[id])==array[i+4]).all()
+            i+=1
+    assert i==m.n_batches*m.minibatch_size
+    del x,y,i,id,m
+
+    i=0
+    m=ds.minibatches(['x','y'],n_batches=20,minibatch_size=3,offset=4)
+    assert isinstance(m,DataSet.MinibatchWrapAroundIterator)
+    for x,y in m:
+        assert len(x)==m.minibatch_size
+        assert len(y)==m.minibatch_size
+        for id in range(m.minibatch_size):
+            assert (numpy.append(x[id],y[id])==array[(i+4)%array.shape[0]]).all()
+            i+=1
+    assert i==m.n_batches*m.minibatch_size
+    del x,y,i,id
+
+    #@todo: we can't do minibatch bigger then the size of the dataset???
+    assert have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array)+1,offset=0)
+    assert not have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array),offset=0)
+
+def test_ds_iterator(array,iterator1,iterator2,iterator3):
+    l=len(iterator1)
+    i=0
+    for x,y in iterator1:
+        assert (x==array[i][:3]).all()
+        assert y==array[i][3]
+        assert (numpy.append(x,y)==array[i]).all()
+        i+=1
+    assert i==l
+    i=0
+    for y,z in iterator2:
+        assert y==array[i][3]
+        assert (z==array[i][0:3:2]).all()
+        i+=1
+    assert i==l
+    i=0
+    for x,y,z in iterator3:
+        assert (x==array[i][:3]).all()
+        assert y==array[i][3]
+        assert (z==array[i][0:3:2]).all()
+        assert (numpy.append(x,y)==array[i]).all()
+        i+=1
+    assert i==l
+
+def test_getitem(array,ds):
+    def test_ds(orig,ds,index):
+        i=0
+        assert len(ds)==len(index)
+        for x,z,y in ds('x','z','y'):
+            assert (orig[index[i]]['x']==array[index[i]][:3]).all()
+            assert (orig[index[i]]['x']==x).all()
+            assert orig[index[i]]['y']==array[index[i]][3]
+            assert orig[index[i]]['y']==y
+            assert (orig[index[i]]['z']==array[index[i]][0:3:2]).all()
+            assert (orig[index[i]]['z']==z).all()
+            i+=1
+        del i
+        ds[0]
+        if len(ds)>2:
+            ds[:1]
+            ds[1:1]
+            ds[1:1:1]
+        if len(ds)>5:
+            ds[[1,2,3]]
+        for x in ds:
+            pass
+
+#ds[:n] returns a dataset with the n first examples.
+    ds2=ds[:3]
+    assert isinstance(ds2,DataSet)
+    test_ds(ds,ds2,index=[0,1,2])
+    del ds2
+
+#ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s.
+    ds2=ds[1:7:2]
+    assert isinstance(ds2,DataSet)
+    test_ds(ds,ds2,[1,3,5])
+    del ds2
+
+#ds[i]
+    ds2=ds[5]
+    assert isinstance(ds2,Example)
+    assert have_raised("var['ds']["+str(len(ds))+"]",ds=ds)  # index not defined
+    assert not have_raised("var['ds']["+str(len(ds)-1)+"]",ds=ds)
+    del ds2
+
+#ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in.
+    ds2=ds[[4,7,2,8]]
+    assert isinstance(ds2,DataSet)
+    test_ds(ds,ds2,[4,7,2,8])
+    del ds2
+
+    #ds.<property># returns the value of a property associated with
+      #the name <property>. The following properties should be supported:
+      #    - 'description': a textual description or name for the ds
+      #    - 'fieldtypes': a list of types (one per field)
+
+    #* ds1 | ds2 | ds3 == ds.hstack([ds1,ds2,ds3])#????
+        #assert hstack([ds('x','y'),ds('z')])==ds
+        #hstack([ds('z','y'),ds('x')])==ds
+    assert have_raised2(hstack,[ds('x'),ds('x')])
+    assert have_raised2(hstack,[ds('y','x'),ds('x')])
+    assert not have_raised2(hstack,[ds('x'),ds('y')])
+        
+    #        i=0
+    #        for example in hstack([ds('x'),ds('y'),ds('z')]):
+    #            example==ds[i]
+    #            i+=1 
+    #        del i,example
+    #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])#????
+
+def test_fields_fct(ds):
+    #@todo, fill correctly
+    assert len(ds.fields())==3
+    i=0
+    v=0
+    for field in ds.fields():
+        for field_value in field: # iterate over the values associated to that field for all the ds examples
+            v+=1
+        i+=1
+    assert i==3
+    assert v==3*10
+    del i,v
+    
+    i=0
+    v=0
+    for field in ds('x','z').fields():
+        i+=1
+        for val in field:
+            v+=1
+    assert i==2
+    assert v==2*10
+    del i,v
+    
+    i=0
+    v=0
+    for field in ds.fields('x','y'):
+        i+=1
+        for val in field:
+            v+=1
+    assert i==2
+    assert v==2*10
+    del i,v
+    
+    i=0
+    v=0
+    for field_examples in ds.fields():
+        for example_value in field_examples:
+            v+=1
+        i+=1
+    assert i==3
+    assert v==3*10
+    del i,v
+    
+    assert ds == ds.fields().examples()
+    assert len(ds('x','y').fields()) == 2
+    assert len(ds('x','z').fields()) == 2
+    assert len(ds('y').fields()) == 1
+
+    del field
+def test_all(array,ds):
+    assert len(ds)==10
+
+    test_iterate_over_examples(array, ds)
+    test_getitem(array, ds)
+    test_ds_iterator(array,ds('x','y'),ds('y','z'),ds('x','y','z'))
+    test_fields_fct(ds)
+
+class T_DataSet(unittest.TestCase):
+    def test_ArrayDataSet(self):
+        #don't test stream
+        #tested only with float value
+        #don't always test with y
+        #don't test missing value
+        #don't test with tuple
+        #don't test proterties
+        a2 = numpy.random.rand(10,4)
+        ds = ArrayDataSet(a2,{'x':slice(3),'y':3,'z':[0,2]})###???tuple not tested
+        ds = ArrayDataSet(a2,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested
+        #assert ds==a? should this work?
+
+        test_all(a2,ds)
+
+        del a2, ds
+
+    def test_CachedDataSet(self):
+        a = numpy.random.rand(10,4)
+        ds1 = ArrayDataSet(a,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested
+        ds2 = CachedDataSet(ds1)
+        ds3 = CachedDataSet(ds1,cache_all_upon_construction=True)
+
+        test_all(a,ds2)
+        test_all(a,ds3)
+
+        del a,ds1,ds2,ds3
+
+
+    def test_DataSetFields(self):
+        raise NotImplementedError()
+
+    def test_ApplyFunctionDataSet(self):
+        a = numpy.random.rand(10,4)
+        a2 = a+1
+        ds1 = ArrayDataSet(a,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested
+
+        ds2 = ApplyFunctionDataSet(ds1,lambda x,y,z: (x+1,y+1,z+1), ['x','y','z'],minibatch_mode=False)
+        ds3 = ApplyFunctionDataSet(ds1,lambda x,y,z: (numpy.array(x)+1,numpy.array(y)+1,numpy.array(z)+1),
+                                   ['x','y','z'],
+                                   minibatch_mode=True)
+
+        test_all(a2,ds2)
+        test_all(a2,ds3)
+
+        del a,ds1,ds2,ds3
+
+    def test_FieldsSubsetDataSet(self):
+        raise NotImplementedError()
+    def test_MinibatchDataSet(self):
+        raise NotImplementedError()
+    def test_HStackedDataSet(self):
+        raise NotImplementedError()
+    def test_VStackedDataSet(self):
+        raise NotImplementedError()
+    def test_ArrayFieldsDataSet(self):
+        raise NotImplementedError()
+
+
+if __name__=='__main__':
+    unittest.main()
+