fixes bug #38; added tests and updated existing ones

datarray/datarray.py

@@ -85,11 +85,13 @@ class AxesManager(object):
     An axis can be indexed by integers or ticks:
 
     >>> np.all(A.axes.stocks['aapl':'goog'] == A.axes.stocks[0:2])
-    DataArray(True, dtype=bool)
-    ('date', 'stocks', 'metric')
+    DataArray(array(True, dtype=bool),
+    ('date', ('stocks', ('aapl', 'ibm')), 'metric'))
+
     >>> np.all(A.axes.stocks[0:2] == A[:,0:2,:])
-    DataArray(True, dtype=bool)
-    ('date', 'stocks', 'metric')
+    DataArray(array(True, dtype=bool),
+    ('date', ('stocks', ('aapl', 'ibm')), 'metric'))
+
 
     Axes can also be accessed numerically:
 
@@ -102,8 +104,8 @@ class AxesManager(object):
 
     >>> Ai = A.axes('stocks', 'date')
     >>> np.all(Ai['aapl':'goog', 100] == A[100, 0:2])
-    DataArray(True, dtype=bool)
-    ('stocks', 'metric')
+    DataArray(array(True, dtype=bool),
+    (('stocks', ('aapl', 'ibm')), 'metric'))
 
     You can also mix axis names and integers when calling AxesManager.
     (Not yet supported.)
@@ -132,11 +134,9 @@ def __getattribute__(self, name):
     def __len__(self):
         return len(object.__getattribute__(self, '_axes'))
 
-    def __str__(self):
+    def __repr__(self):
         return str(tuple(self))
 
-    __repr__ = __str__
-
     def __getitem__(self, n):
         """Return the `n`th axis object of the array.
 
@@ -387,12 +387,10 @@ def __eq__(self, other):
         return self.name == other.name and self.index == other.index and \
                self.labels == other.labels
 
-    def __str__(self):
+    def __repr__(self):
         return 'Axis(name=%r, index=%i, labels=%r)' % \
                (self.name, self.index, self.labels)
 
-    __repr__ = __str__
-
     def __getitem__(self, key):
         """
         Return the item(s) of parent array along this axis as specified by `key`.
@@ -409,15 +407,19 @@ def __getitem__(self, key):
         >>> A = DataArray(np.arange(2*3*2).reshape([2,3,2]), \
                 ('a', ('b', ('b1','b2','b3')), 'c'))
         >>> b = A.axes.b
+       
         >>> np.all(b['b1'] == A[:,0,:])
-        DataArray(True, dtype=bool)
-        ('a', 'c')
-        >>> np.all(b['b1':'b2'] == A[:,0:1,:])
-        DataArray(True, dtype=bool)
-        ('a', 'b', 'c')
+        DataArray(array(True, dtype=bool),
+        ('a', 'c'))
+
         >>> np.all(b['b2':] == A[:,1:,:])
-        DataArray(True, dtype=bool)
-        ('a', 'b', 'c')
+        DataArray(array(True, dtype=bool),
+        ('a', ('b', ('b2', 'b3')), 'c'))
+
+        >>> np.all(b['b1':'b2'] == A[:,0:1,:])
+        DataArray(array(True, dtype=bool),
+        ('a', ('b', ('b1',)), 'c'))
+
         """
         # XXX We don't handle fancy indexing at the moment
         if isinstance(key, (np.ndarray, list)):
@@ -599,8 +601,8 @@ def drop(self, labels):
         >>> arr1 = darr.axes.b.keep(['c','d'])
         >>> arr2 = darr.axes.b.drop(['a','b','e'])
         >>> np.all(arr1 == arr2)
-        DataArray(True, dtype=bool)
-        ('a', 'b')
+        DataArray(array(True, dtype=bool),
+        ('a', ('b', ('c', 'd'))))
         """
 
         if not self.labels:
@@ -735,7 +737,6 @@ def runs_op(*args, **kwargs):
 def is_numpy_scalar(arr):
     return arr.ndim == 0
 
-
 def _apply_accumulation(opname, kwnames):
     super_op = getattr(np.ndarray, opname)
     if 'axis' not in kwnames:
@@ -763,7 +764,6 @@ def runs_op(*args, **kwargs):
     return runs_op
 
 class DataArray(np.ndarray):
-
     # XXX- we need to figure out where in the numpy C code .T is defined!
     @property
     def T(self):
@@ -1003,15 +1003,20 @@ def __getitem__(self, key):
 
         return arr
 
+    def __str_repr_helper(self, ary_repr):
+        """Helper function for __str__ and __repr__. Produce a text
+        representation of the axis suitable for eval() as an argument to a
+        DataArray constructor."""
+        axis_spec = repr(tuple(ax.name if ax.labels is None 
+            else (ax.name, tuple(ax.labels)) for ax in self.axes))
+        return "%s(%s,\n%s)" % \
+                (self.__class__.__name__, ary_repr, axis_spec)
+
     def __str__(self):
-        s = super(DataArray, self).__str__()
-        s = '\n'.join([s, str(self.names)])
-        return s
+        return self.__str_repr_helper(np.asarray(self).__str__())
 
     def __repr__(self):
-        s = super(DataArray, self).__repr__()
-        s = '\n'.join([s, str(self.names)])
-        return s
+        return self.__str_repr_helper(np.asarray(self).__repr__())
 
     # Methods from ndarray
 

datarray/tests/test_bugfixes.py

@@ -33,6 +33,29 @@ def test_bug26():
     a.axes[0].name = "a"
     nt.assert_equal(a.axes[0].name, "a")
 
+def test_bug35():
+    "Bug 35"
+    txt_array = DataArray(['a','b'], axes=['dummy'])
+    #calling datarray_to_string on string arrays used to fail
+    print_grid.datarray_to_string(txt_array)
+    #because get_formatter returned the class not an instance
+    assert isinstance(print_grid.get_formatter(txt_array),
+                      print_grid.StrFormatter)
+
+def test_bug38():
+    "Bug 38: DataArray.__repr__ should parse as a single entity"
+    # Calling repr() on an ndarray prepends array (instead of np.array)
+    array = np.array
+    arys = (
+        DataArray(np.random.randint(0, 10000, size=(1,2,3,4,5)), 'abcde'),
+        DataArray(np.random.randint(0, 10000, size=(3,3,3))), # Try with missing axes
+        DataArray(np.random.randint(0, 10000, (2,4,5,6)), # Try with ticks
+            ('a', ('b', ('b1','b2','b3','b4')), 'c', 'd')),
+        )
+    for A in arys:
+        print A
+        assert_datarray_equal(A, eval(repr(A)))
+
 def test_bug44():
     "Bug 44"
     # In instances where axis=None, the operation runs
@@ -43,16 +66,3 @@ def test_bug44():
     y = np.std(A)
     nt.assert_equal( x.sum(), y.sum() )
 
-def test_bug45():
-    "Bug 45: Support for np.outer()"
-    A = DataArray([1,2,3], 'a'); B = DataArray([2,3,4], 'b'); C = np.outer(A,B)
-    assert_datarray_equal(C,DataArray(C, 'ab'))
-
-def test_bug35():
-    "Bug 35"
-    txt_array = DataArray(['a','b'], axes=['dummy'])
-    #calling datarray_to_string on string arrays used to fail
-    print_grid.datarray_to_string(txt_array)
-    #because get_formatter returned the class not an instance
-    assert isinstance(print_grid.get_formatter(txt_array),
-                      print_grid.StrFormatter)