statsmodels/statsmodels — pull request #304 by divyanshubandil (2012-06-10 19:40:23+00:00)
Title: Nonlinearls

The code generated for testing NIST nonlinear models. Some points to note:
1. NISTtest_generator.py creates two python modules for each NIST model.
2. The 'modelname_testclass.py' includes the statsmodels nonlinear classes for the model with and without the analytical jacobian feature and also a base class 'TestNonlinearLS' for setup and storing the correct results from the NIST data file.
3. The 'test_modelname.py' uses the above module to create a derived class for adding tests.
4. This way the templated files need not be recreated for adding more tests. Any tests for a NIST model can be added to its respective 'test_modelname.py'

Though most of the tests fail for now, but the objective here was to first get the correct method of writing tests. Also after going through some manual checking, I noticed some of the calculated parameter values match upto 3 decimal places.