--- a/test_dataset.py	Wed Jun 04 17:49:28 2008 -0400
+++ b/test_dataset.py	Wed Jun 04 18:48:50 2008 -0400
@@ -421,7 +421,7 @@
 
     test_all(a2,ds)
 
-    del a2, ds #removes from list of active objects in debugger
+    del a2, ds
 
 def test_LookupList():
     #test only the example in the doc???
@@ -544,8 +544,6 @@
     f_array_iter(array)
 
     f_ds_index(ds)
-    f_ds_index(ds)
-    f_ds_iter(ds)
     f_ds_iter(ds)
 
     f_ds_mb1(ds,10)
@@ -558,92 +556,8 @@
     f_ds_mb2(ds,10000)
 
 
-
-
-
-
-#****************************************************************
-# dummy tests, less powerful than the previous tests, but can work with any new weird dataset.
-# Basically, emphasis is put on consistency, but it never checks the actual values.
-# To be used as a checklist, or a first test, when creating a new dataset
-
-def dummytest_all(ds) :
-    """ Launches all the dummytests with a given dataset. """
-
-    dummytest1_basicstats(ds)
-    dummytest2_slicing(ds)
-    dummytest3_fields_iterator_consistency(ds)
-
-
-def dummytest1_basicstats(ds) :
-    """print basics stats on a dataset, like length"""
-
-    print 'len(ds) = ',len(ds)
-    print 'num fields = ', len(ds.fieldNames())
-    print 'types of field: ',
-    for k in ds.fieldNames() :
-        print type(ds[0](k)[0]),
-    print ''
-
-def dummytest2_slicing(ds) :
-    """test if slicing seems to works properly"""
-    print 'testing slicing...',
-    sys.stdout.flush()
-        
-    middle = len(ds) / 2
-    tenpercent = int(len(ds) * .1)
-    set1 = ds[:middle+tenpercent]
-    set2 = ds[middle-tenpercent:]
-    for k in range(tenpercent + tenpercent -1):
-        for k2 in ds.fieldNames() :
-            if type(set1[middle-tenpercent+k](k2)[0]) == N.ndarray :
-                for k3 in range(len(set1[middle-tenpercent+k](k2)[0])) :
-                    assert set1[middle-tenpercent+k](k2)[0][k3] == set2[k](k2)[0][k3]
-            else :
-                assert set1[middle-tenpercent+k](k2)[0] == set2[k](k2)[0]
-    assert tenpercent > 1
-    set3 = ds[middle-tenpercent:middle+tenpercent:2]
-    for k2 in ds.fieldNames() :
-        if type(set2[2](k2)[0]) == N.ndarray :
-            for k3 in range(len(set2[2](k2)[0])) :
-                assert set2[2](k2)[0][k3] == set3[1](k2)[0][k3]
-        else :
-            assert set2[2](k2)[0] == set3[1](k2)[0]
-
-    print 'done'
-
-
-def dummytest3_fields_iterator_consistency(ds) :
-    """test if the number of iterator corresponds to the number of fields, also do it for minibatches"""
-    print 'testing fields/iterator consistency...',
-    sys.stdout.flush()
-
-    # basic test
-    maxsize = min(len(ds)-1,100)
-    for iter in ds[:maxsize] :
-        assert len(iter) == len(ds.fieldNames())
-    if len(ds.fieldNames()) == 1 :
-        print 'done'
-        return
-
-    # with minibatches iterator
-    ds2 = ds[:maxsize].minibatches([ds.fieldNames()[0],ds.fieldNames()[1]],minibatch_size=2)
-    for iter in ds2 :
-        assert len(iter) == 2
-
-    print 'done'
-
-
-
-
-
-
-
-
-
 if __name__=='__main__':
-    if 0:
-        test1()
+    test1()
     test_LookupList()
     test_ArrayDataSet()
     test_CachedDataSet()