Update docs before new release

docs/guide.rst

@@ -6,10 +6,10 @@ Structure of ``odes`` and User's Guide
 There are a number of different ways of using ``odes`` to solve a system of
 ODEs/DAEs:
 
- * :py:class:`scikits.odes.ode.ode` and :py:class:`scikits.odes.dae.dae` classes, which provides an object oriented interface and significant amount of control of the solver.
- * :py:func:`scikits.odes.odeint.odeint`, a single function alternative to the object
+ * :py:class:`scikits_odes.ode.ode` and :py:class:`scikits_odes.dae.dae` classes, which provides an object oriented interface and significant amount of control of the solver.
+ * :py:func:`scikits_odes.odeint.odeint`, a single function alternative to the object
    oriented interface.
- * Accessing the lower-level solver-specific wrappers, such as the modules in :py:mod:`scikits.odes.sundials`.
+ * Accessing the lower-level solver-specific wrappers, such as the modules in :py:mod:`scikits_odes_sundials`.
 
 In general, a user supplies a function with the signature::
 
@@ -30,7 +30,7 @@ The simplest user program using the ``odeint`` interface, assuming you have
 implemented the ODE ``right_hand_side`` mentioned above, is::
 
     import numpy as np
-    from scikits.odes.odeint import odeint
+    from scikits_odes.odeint import odeint
 
     tout = np.linspace(0, 1)
     initial_values = np.array([0])
@@ -93,7 +93,7 @@ The simplest user program using the ``ode`` interface, assuming you have
 implemented the ODE ``right_hand_side`` mentioned above, is::
 
     import numpy as np
-    from scikits.odes.ode import ode
+    from scikits_odes.ode import ode
 
     SOLVER = 'cvode'
     tout = np.linspace(0, 1)
@@ -132,7 +132,7 @@ The simplest user program using the ``dae`` interface, assuming you have
 implemented the DAE ``right_hand_side`` mentioned above, is::
 
     import numpy as np
-    from scikits.odes.dae import dae
+    from scikits_odes.dae import dae
 
     SOLVER = 'ida'
     tout = np.linspace(0, 1)

docs/index.rst

@@ -8,9 +8,9 @@ Welcome to the ODES scikit documentation!
 
 The ODES scikit provides access to Ordinary Differential Equation (ODE) solvers
 and Differential Algebraic Equation (DAE) solvers not included in `scipy`_. A
-convenience function :py:func:`scikits.odes.odeint.odeint` is available for fast
+convenience function :py:func:`scikits_odes.odeint.odeint` is available for fast
 and fire and forget integration. Object oriented class solvers
-:py:class:`scikits.odes.ode.ode` and :py:class:`scikits.odes.dae.dae` are
+:py:class:`scikits_odes.ode.ode` and :py:class:`scikits_odes.dae.dae` are
 available for fine control. Finally, the low levels solvers are also directly
 exposed for specialised needs.
 

docs/installation.rst

@@ -47,8 +47,10 @@ with ``odes``:
 
     * - SUNDIALS version
       - ``odes`` version
+    * - 7.x
+      - 3.1.x
     * - 6.x
-      - 2.7.x
+      - 2.7.x and 3.0.x
     * - 5.x
       - 2.6.x
     * - 4.x
@@ -67,7 +69,7 @@ Installation
 ------------
 To install ``odes``, use::
 
-    pip install scikits.odes
+    pip install scikits-odes
 
 which will download the latest version from PyPI. This will handle the installation of the additional runtime dependencies of ``odes``. You should then run the tests to make sure everything is set up correctly.
 
@@ -79,7 +81,7 @@ Testing your version of ``odes``
 To test the version in python, use in the python shell::
 
     >>> import pkg_resources
-    >>> pkg_resources.get_distribution("scikits.odes").version
+    >>> pkg_resources.get_distribution("scikits-odes").version
 
 
 Running the Tests
@@ -90,7 +92,7 @@ You need nose to run the tests. To install nose, run::
 
 To run the tests, in the python shell::
 
-    >>> import scikits.odes as od; od.test()
+    >>> import scikits_odes as od; od.test()
 
 Note that the sundials library must be in your ``LD_LIBRARY_PATH``. So, make sure the directory ``$SUNDIALS_INST/lib`` is included. You can do this for example as follows (assuming sundials was installed in ``/usr/local``::
 
@@ -120,7 +122,7 @@ LAPACK Not Found
 ................
 Most issues with using ``odes`` are due to incorrectly setting the LAPACK libraries, resulting in error, typically::
 
-    AttributeError: module 'scikits.odes.sundials.cvode' has no attribute 'CVODE'
+    AttributeError: module 'scikits_odes_sundials.cvode' has no attribute 'CVODE'
 
 or::
 
@@ -189,7 +191,7 @@ You can verify that lapack is available (although the nix install will have
 run many tests to check this already), try the following python snippet in the interpreter::
 
     import numpy as np
-    from scikits.odes.odeint import odeint
+    from scikits_odes.odeint import odeint
 
     tout = np.linspace(0, 1)
     initial_values = np.array([1])

docs/solvers.rst

@@ -5,10 +5,10 @@ Choosing a Solver
 ``odes`` interfaces with a number of different solvers:
 
 `CVODE <https://computation.llnl.gov/projects/sundials/cvode>`_
-    ODE solver with BDF linear multistep method for stiff problems and Adams-Moulton linear multistep method for nonstiff problems. Supports modern features such as: root (event) finding, error control, and (Krylov-)preconditioning. See :py:mod:`scikits.odes.sundials.cvode` for more details and solver specific arguments. Part of SUNDIALS, it is a replacement for the earlier ``vode``/``dvode``.
+    ODE solver with BDF linear multistep method for stiff problems and Adams-Moulton linear multistep method for nonstiff problems. Supports modern features such as: root (event) finding, error control, and (Krylov-)preconditioning. See :py:mod:`scikits_odes_sundials.cvode` for more details and solver specific arguments. Part of SUNDIALS, it is a replacement for the earlier ``vode``/``dvode``.
 
 `IDA <https://computation.llnl.gov/projects/sundials/ida>`_
-    DAE solver with BDF linear multistep method for stiff problems and Adams-Moulton linear multistep method for nonstiff problems. Supports modern features such as: root (event) finding, error control, and (Krylov-)preconditioning. See :py:mod:`scikits.odes.sundials.ida` for more details and solver specific arguments. Part of SUNDIALS.
+    DAE solver with BDF linear multistep method for stiff problems and Adams-Moulton linear multistep method for nonstiff problems. Supports modern features such as: root (event) finding, error control, and (Krylov-)preconditioning. See :py:mod:`scikits_odes_sundials.ida` for more details and solver specific arguments. Part of SUNDIALS.
 
 `dopri5 <https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.ode.html>`_
     Part of :py:mod:`scipy.integrate`, explicit Runge-Kutta method of order (4)5 with stepsize control.
@@ -20,10 +20,10 @@ Choosing a Solver
 
 `lsodi <http://www.netlib.org/odepack/opkd-sum>`_
     Part of `odepack <http://www.netlib.org/odepack/opkd-sum>`_, IDA should be
-    used instead of this. See :py:mod:`scikits.odes.lsodiint` for more details.
+    used instead of this. See :py:mod:`scikits_odes.lsodiint` for more details.
 
 `ddaspk <http://www.netlib.org/ode/>`_
-    Part of `daspk <http://www.netlib.org/ode/>`_, IDA should be used instead of this. See :py:mod:`scikits.odes.ddaspkint` for more details.
+    Part of `daspk <http://www.netlib.org/ode/>`_, IDA should be used instead of this. See :py:mod:`scikits_odes.ddaspkint` for more details.
 
 Support for other SUNDIALS solvers (e.g. ARKODE) is currently not implemented,
 nor is support for non-serial methods (e.g. MPI, OpenMP). Contributions adding