MAINT: restore optional ravel order and add tests and more docstring lines

1 files changed, 29 insertions, 11 deletions

diff --git a/numpy/matrixlib/defmatrix.py b/numpy/matrixlib/defmatrix.py
index 2d785e213..51903e258 100644
--- a/numpy/matrixlib/defmatrix.py
+++ b/numpy/matrixlib/defmatrix.py
@@ -927,24 +927,42 @@ class matrix(N.ndarray):
         return self.__array__().ravel()
 
 
-    def ravel(self):
+    def ravel(self, order='C'):
         """
-        Return a flattened array.
+        Return a flattened matrix.
 
-        Refer to `numpy.ravel` for full documentation.
+        Refer to `numpy.ravel` for more documentation.
 
-        See Also
-        --------
-        numpy.ravel : equivalent function
+        Parameters
+        ----------
+        order : {'C', 'F', 'A', 'K'}, optional
+            The elements of `m` are read using this index order. 'C' means to
+            index the elements in C-like order, with the last axis index
+            changing fastest, back to the first axis index changing slowest.
+            'F' means to index the elements in Fortran-like index order, with
+            the first index changing fastest, and the last index changing
+            slowest. Note that the 'C' and 'F' options take no account of the
+            memory layout of the underlying array, and only refer to the order
+            of axis indexing.  'A' means to read the elements in Fortran-like
+            index order if `m` is Fortran *contiguous* in memory, C-like order
+            otherwise.  'K' means to read the elements in the order they occur
+            in memory, except for reversing the data when strides are negative.
+            By default, 'C' index order is used.
 
-        ndarray.flat : a flat iterator on the array.
+        Returns
+        -------
+        ret : matrix
+            A copy of the matrix, flattened to a `(1, N)` matrix where `N`
+            is the number of elements in the original matrix.
 
-        Notes
-        -----
-        This returns a matrix.
+        See Also
+        --------
+        matrix.flatten : returns a similar output matrix but always a copy
+        matrix.flat : a flat iterator on the array.
+        numpy.ravel : related function which returns an ndarray
 
         """
-        return core.multiarray.ndarray.ravel(self)
+        return core.multiarray.ndarray.ravel(self, order=order)
 
 
     def getT(self):