## ./

# 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 |