# Numpy Diff

Oct 18, 2015 numpy.diff ¶ numpy.diff(a, n=1, axis=-1) source ¶ Calculate the n-th order discrete difference along given axis. The first order difference is given by out n = a n+1 - a n along the given axis, higher order differences are calculated by using diff recursively. The NumPy class is a high-level abstraction of NDArray that allows NumSharp to be used in the same way as Python's NumPy, minimizing API differences caused by programming language features, allowing.NET developers to maximize Utilize a wide range of NumPy code resources to seamlessly translate python code into.NET code. Numpy.diff ¶ numpy.diff(a, n=1, axis=-1, prepend=, append=) source ¶ Calculate the n-th discrete difference along the given axis. The first difference is given by out i = a i+1 - a i along the given axis, higher differences are calculated by using diff recursively. The Python numpy comparison operators and functions used to compare the array items and returns Boolean True or false. The Python Numpy comparison functions are greater, greaterequal, less, lessequal, equal, and notequal. The problem is that you have a structured array instead of a regular 2-dimensional array, so numpy does not know how to subtract one tuple from another. Convert your structured array to a regular array (from this SO question): myarray = myarray.view(numpy.uint8).reshape((myarray.shape0, -1)) and then do numpy.diff(myarray, axis=0).

Calculate the n-th discrete difference along given axis.

The first difference is given by `out[n]=a[n+1]-a[n]` alongthe given axis, higher differences are calculated by using `diff`recursively.

Parameters: a : array_liken : int, optionalThe number of times values are differenced.axis : int, optionalThe axis along which the difference is taken, default is the last axis. diff : ndarrayThe n-th differences. The shape of the output is the same as aexcept along axis where the dimension is smaller by n. Thetype of the output is the same as that of the input. Notes

### Numpy Diff

For boolean arrays, the preservation of type means that the resultwill contain False when consecutive elements are the same andTrue when they differ.

### Numpy Differential

For unsigned integer arrays, the results will also be unsigned. This shouldnot be surprising, as the result is consistent with calculating thedifference directly:

### Diff Function In Python

If this is not desirable, then the array should be cast to a larger integertype first:

Examples