--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test_dataset.py	Fri May 02 18:19:35 2008 -0400
@@ -0,0 +1,114 @@
+#!/bin/env python
+from dataset import *
+from math import *
+import numpy
+
+def 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"]
+
+def test_ArrayDataSet():
+    #don't test stream
+    #tested only with float value
+    a = numpy.random.rand(10,4)
+    print a
+    ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]})
+    assert len(ds)==10
+    #assert ds==a? should this work?
+    for i in range(len(ds)):
+        assert ds[i]['x'].all()==a[i][:2].all()
+        assert ds[i]['y']==a[i][3]
+        assert ds[i]['z'].all()==a[i][0:3:2].all()
+    print "x=",ds["x"]
+    print "x|y"
+    i=0
+    for x in ds('x','y'):
+        assert numpy.append(x['x'],x['y']).all()==a[i].all()
+        i+=1
+#    i=0
+#    for x in ds['x','y']: # don't work
+#        assert numpy.append(x['x'],x['y']).all()==a[i].all()
+#        i+=1
+#    for (x,y) in (ds('x','y'),a): #don't work # haven't found a variant that work.
+#        assert numpy.append(x,y)==z
+    i=0
+    for x,y in ds('x','y'):
+        assert numpy.append(x,y).all()==a[i].all()
+        i+=1
+    for minibatch in ds.minibatches(['x','z'], minibatch_size=3):
+        assert minibatch[0][:,0:3:2].all()==minibatch[1].all()
+    for x,z in ds.minibatches(['x','z'], minibatch_size=3):
+        assert x[:,0:3:2].all()==z.all()
+
+#    for minibatch in ds.minibatches(['z','y'], minibatch_size=3):
+#        print minibatch
+#    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"]
+    have_thrown = False
+    try:
+        ds['h'] # h is not defined...
+    except :
+        have_thrown = True
+    assert have_thrown == True
+    assert len(ds.fields())==3
+    for field in ds.fields():
+        for field_value in field: # iterate over the values associated to that field for all the ds examples
+            pass
+    for field in ds('x','z').fields():
+        pass
+    for field in ds.fields('x','y'):
+        pass
+    for field_examples in ds.fields():
+        for example_value in field_examples:
+            pass
+
+    assert ds == ds.fields().examples()
+
+
+    #test missing value
+
+    assert len(ds[:3])==3
+    i=0
+    for x,z in ds[:3]('x','z'):
+        assert ds[i]['z'].all()==a[i][0:3:2].all()
+        i+=1
+    #ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s.
+
+    #ds[i]# returns an Example.
+
+    #ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in.
+
+    #ds[fieldname]# an iterable over the values of the field fieldname across
+      #the ds (the iterable is obtained by default by calling valuesVStack
+      #over the values for individual examples).
+
+    #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])
+    #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])
+
+
+test_ArrayDataSet()
+