dask.array.diff — Dask documentation (original) (raw)

Calculate the n-th discrete difference along the given axis.

This docstring was copied from numpy.diff.

Some inconsistencies with the Dask version may exist.

The first difference is given by out[i] = a[i+1] - a[i] along the given axis, higher differences are calculated by using diffrecursively.

Parameters

aarray_like

Input array

nint, optional

The number of times values are differenced. If zero, the input is returned as-is.

axisint, optional

The axis along which the difference is taken, default is the last axis.

prepend, appendarray_like, optional

Values to prepend or append to a along axis prior to performing the difference. Scalar values are expanded to arrays with length 1 in the direction of axis and the shape of the input array in along all other axes. Otherwise the dimension and shape must match a except along axis.

Returns

diffndarray

The n-th differences. The shape of the output is the same as aexcept along axis where the dimension is smaller by n. The type of the output is the same as the type of the difference between any two elements of a. This is the same as the type ofa in most cases. A notable exception is datetime64, which results in a timedelta64 output array.

Notes

Type is preserved for boolean arrays, so the result will containFalse when consecutive elements are the same and True when they differ.

For unsigned integer arrays, the results will also be unsigned. This should not be surprising, as the result is consistent with calculating the difference directly:

u8_arr = np.array([1, 0], dtype=np.uint8)
np.diff(u8_arr)
array([255], dtype=uint8) u8_arr[1,...] - u8_arr[0,...]
np.uint8(255)

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

i16_arr = u8_arr.astype(np.int16)
np.diff(i16_arr)
array([-1], dtype=int16)

Examples

import numpy as np
x = np.array([1, 2, 4, 7, 0])
np.diff(x)
array([ 1, 2, 3, -7]) np.diff(x, n=2)
array([ 1, 1, -10])

x = np.array([[1, 3, 6, 10], [0, 5, 6, 8]])
np.diff(x)
array([[2, 3, 4], [5, 1, 2]]) np.diff(x, axis=0)
array([[-1, 2, 0, -2]])

x = np.arange('1066-10-13', '1066-10-16', dtype=np.datetime64)
np.diff(x)
array([1, 1], dtype='timedelta64[D]')