Numdifftools
Suite of tools written in _Python to solve automatic numerical differentiation problems in one or more variables. Finite differences are used in an adaptive manner, coupled with a Romberg extrapolation methodology to provide a maximally accurate result. The user can configure many options like; changing the order of the method or the extrapolation, even allowing the user to specify whether central, forward or backward differences are used.
The methods provided are:
- Derivative: Compute the derivatives of order 1 through 4 on any scalar function.
- Gradient: Compute the gradient vector of a scalar function of one or more variables.
- Jacobian: Compute the Jacobian matrix of a vector valued function of one or more variables.
- Hessian: Compute the Hessian matrix of all 2nd partial derivatives of a scalar function of one or more variables.
- Hessdiag: Compute only the diagonal elements of the Hessian matrix
All of these methods also produce error estimates on the result.
A pdf file is also provided to explain the theory behind these tools. Download the toolbox here: http://pypi.python.org/pypi/Numdifftools
News
2014
December 18
New release of Numdifftools 0.7.7.
December 17
New release of Numdifftools 0.7.3.
February 8
New release of Numdifftools 0.6.0. :
January 10
New release of Numdifftools 0.5.0.
2012
May 5
New release of Numdifftools 0.4.0.
2011
May 19
New release of Numdifftools 0.3.5.
Feb 24
New release of Numdifftools 0.3.4.