This blog is dedicated to the first week of Google Summer of Code (i.e June 1 - June 7). The target of the first week according to my timeline was to get conversant with the code structure and implement the derivative using statsmodels and partly by numdifftools.
Status of Week 1 :
I tried to stick to the plan. I have concentrated only on finite differences, complex methods are for latter part of the project. I have implemented the following :
Derivatives using statsmodels:
I have implemented a vectorized code for derivatives using statsmodels along with docstrings and tests. It is present in scipy.diff.statsmodels._derivative.Derivaitve.
Gradient using statsdmodels:
I have implemented a vectorized code for gradients using statsmodels along with docstrings and tests. It is present in scipy.diff.statsmodels._derivative.Gradient.
Jacobian using statsmodels:
I have implemented a vectorized code for jacobians using statsmodels along with docstrings and tests. It is present in scipy.diff.statsmodels._derivative.Jacobian.
Derivatives using numdifftools:
I was understanding the numdifftools and side by side trying to implement it. I have successfully implemented the code for derivatives, however, the code is not clean and needs modularization and refactoring. I will be doing this work in the second week.
Link to the implemented code : here
Next week is dedicated to computation of derivatives, gradients and jacobian using finite differences from numdifftools.