Merge c76eda0 into 97532a0

.travis.yml

@@ -12,6 +12,7 @@ notifications:
 branches:
   only:
     - master
+    - develop
 
 before_install:
   - wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh
@@ -21,7 +22,7 @@ before_install:
   - conda update --yes conda
 
 install:
-  - conda install --yes python=$TRAVIS_PYTHON_VERSION numpy scipy nose pandas pip sympy
+  - conda install --yes python=$TRAVIS_PYTHON_VERSION numpy scipy nose pip
   - pip install coveralls coverage
   - python setup.py install
 

README.rst

@@ -1,16 +1,14 @@
 pyCollocation
 =============
 
-|Build Status| |Coverage Status| |Documentation Status| |Codacy Badge| |Scrutinizer Code Quality| |Latest Version| |Downloads| |DOI|
+|Build Status| |Coverage Status| |Documentation Status| |Code Climate| |Latest Version| |Downloads| |DOI|
 
 .. |Build Status| image:: https://travis-ci.org/davidrpugh/pyCollocation.svg?branch=master
    :target: https://travis-ci.org/davidrpugh/pyCollocation
 .. |Coverage Status| image:: https://coveralls.io/repos/davidrpugh/pyCollocation/badge.svg?branch=master
    :target: https://coveralls.io/r/davidrpugh/pyCollocation?branch=master
-.. |Codacy Badge| image:: https://www.codacy.com/project/badge/4838082c243c48afa392aabc7cce54ab
-   :target: https://www.codacy.com/app/drobert-pugh/pyCollocation
-.. |Scrutinizer Code Quality| image:: https://scrutinizer-ci.com/g/davidrpugh/pyCollocation/badges/quality-score.png?b=master
-   :target: https://scrutinizer-ci.com/g/davidrpugh/pyCollocation/?branch=master
+.. |Code Climate| image:: https://codeclimate.com/github/davidrpugh/pyCollocation/badges/gpa.svg
+   :target: https://codeclimate.com/github/davidrpugh/pyCollocation
 .. |Latest Version| image:: https://img.shields.io/pypi/v/pyCollocation.svg
    :target: https://pypi.python.org/pypi/pyCollocation/
 .. |Downloads| image:: https://img.shields.io/pypi/dm/pyCollocation.svg
@@ -23,8 +21,9 @@ pyCollocation
 
 Python package for solving initial value problems (IVP) and two-point boundary value problems (2PBVP) using the collocation method with various basis functions. Currently I have implemented the following basis functions:
 
-- Orthogonal polynomials: Chebyshev_, Laguerre_, Legendre_, and Hermite_.
+- Polynomials: Standard_, Chebyshev_, Laguerre_, Legendre_, and Hermite_.
 
+.. _Standard: https://en.wikipedia.org/wiki/Polynomial
 .. _Chebyshev: http://en.wikipedia.org/wiki/Chebyshev_polynomials
 .. _Laguerre: http://en.wikipedia.org/wiki/Laguerre_polynomials
 .. _Legendre: http://en.wikipedia.org/wiki/Legendre_polynomials
@@ -52,21 +51,31 @@ Economics
 
 There are a number of example notebooks that demonstrate how to use the library to solve seminal models in the economics literature.
 
-- `Solow model of economic growth`_
-- `Ramsey model of optimal savings`_
-- `Spence model of costly signaling`_
-- `Kiyotaki and Moore model of credit cycles`_
+- `Solow model`_ of economic growth
+- `Ramsey-Cass-Koopmans model`_ of optimal savings
 
-.. _`Solow model of economic growth`: http://nbviewer.ipython.org/github/davidrpugh/pyCollocation/blob/master/examples/solow-model.ipynb
-.. _`Ramsey model of optimal savings`: http://nbviewer.ipython.org/github/ramseyPy/ramseyPy/blob/master/examples/ramsey-model.ipynb
-.. _`Spence model of costly signaling`: http://nbviewer.ipython.org/github/davidrpugh/pyCollocation/blob/master/examples/spence-model.ipynb
-.. _`Kiyotaki and Moore model of credit cycles`: http://nbviewer.ipython.org/github/davidrpugh/pyCollocation/blob/master/examples/credit-cycles.ipynb
+.. _`Solow model` : https://github.com/davidrpugh/pyCollocation/blob/master/examples/solow-model.ipynb
+.. _`Ramsey-Cass-Koopmans`: https://github.com/davidrpugh/pyCollocation/blob/master/examples/ramsey-cass-koopmans-model.ipynb
 
 Physics
 ~~~~~~~
 
 - `A simple heat exchanger`_ 
 
-.. _`A simple heat exchanger`: http://nbviewer.ipython.org/github/davidrpugh/pyCollocation/blob/master/examples/heat-exchanger.ipynb
+.. _`A simple heat exchanger`: https://github.com/davidrpugh/pyCollocation/blob/master/examples/heat-exchanger.ipynb
 
-More notebooks will be added in the near future (hopefully!)
+More notebooks will be added in the near future (hopefully!)...and suggestions for example notebooks are very welcome!
+
+Roadmap to 1.0
+--------------
+Ultimately I am hoping to contribute this package to either SciPy or QuantEcon, depending.  Ideally, version 1.0 of pyCollocation would include the following functionality...
+
+- Support for at least two additional classes of basis functions: B-Splines, what else? Next obvious candidate would be some basis functions specifically used to approximate periodic functions.
+
+- Support a solver for over-identified systems of equations.  Currently the Solver class requires the system of equations defined by the collocation residuals to be exactly identified.  Many economic applications, particularly models of optimal bidding functions for various types of auctions, naturally lead to over-identified systems.
+
+- Built-in support for computing Jacobian matrix for the system of equations defined by the collocation residuals.  Given a user-supplied Jacobian for the BVP, one can apply the chain rule to construct the Jacobian matrix for system of equations defined by the collocation residuals.
+
+- Support for solving models with unknown parameters (similar to `scikits.bvp_solver`_). This would allow for the possibility to simultaneously solve and calibrate a model.
+
+.. _`scikits.bvp_solver` : https://github.com/jsalvatier/scikits.bvp_solver 

pycollocation/tests/test_ramsey_model.py

@@ -59,7 +59,6 @@ def generate_random_params(scale, seed):
     lower_bound = delta / (alpha * (g + n + delta) - g)
     theta, = stats.lognorm.rvs(scale, loc=lower_bound, size=1)
     rho = alpha * theta * (g + n + delta) - (delta * theta * g)
-    print theta, lower_bound
     assert rho > 0
 
     # choose k0 so that it is not too far from equilibrium

setup.py

@@ -30,7 +30,7 @@ def read(*paths):
 setup(
     name="pycollocation",
     packages=['pycollocation'],
-    version='0.4.5-alpha',
+    version='0.5-alpha',
     description=DESCRIPTION,
     long_description=read('README.rst'),
     license="MIT License",