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pdiv.pro
Routines
result = pdiv(data, dimension [, order=order])This function estimates the partial derivative of a multi-dimensional function, sampled on a regular grid
test
Routine details
toppdiv
result = pdiv(data, dimension [, order=order])
This function estimates the partial derivative of a multi-dimensional function, sampled on a regular grid
Return value
A grid the same size as data, giving the partial derivative along dimension at each data point
Parameters
- data in required
An n-dimensional datacube, representing a function evenly sampled on a grid.
- dimension in required
The dimension (1-n_dimension(data)) over which to calculate the partial derivative (df / d_dim). Defaults to 1.
Keywords
- order in optional
1-3, indicating how to approximate the derivative. All methods implicitly use lagrange interpolation to express each data point as a point on a polynomial, and then differentiate that polynomial. Order=1,2,3 correspond to a (3,5,7) point interpolation scheme. Defaults to 1.
toptest
test
File attributes
| Modifcation date: | Tue Aug 3 15:35:05 2010 |
| Lines: | 130 |