Calculate the n-th discrete difference in Numpy

To calculate the n-th discrete difference along the given axis, use the MaskedArray.diff() method in Python Numpy. 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 function returns the n-th differences. The shape of the output is the same as a except 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 of a in most cases. A notable exception is datetime64, which results in a timedelta64 output array.

The prepend, append parameter are the 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.

Steps

At first, import the required library −

import numpy as np
import numpy.ma as ma

Create an array with int elements using the numpy.array() method −

arr = np.array([[65, 68, 81], [93, 33, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)

Create a masked array and mask some of them as invalid −

maskArr = ma.masked_array(arr, mask =[[1, 0, 0], [ 0, 0, 0], [0, 1, 0], [0, 0, 0]])
print("\nOur Masked Array...
", maskArr)

Get the type of the masked array −

print("\nOur Masked Array type...
", maskArr.dtype)

Get the dimensions of the Masked Array −

print("\nOur Masked Array Dimensions...
",maskArr.ndim)

Get the shape of the Masked Array −

print("\nOur Masked Array Shape...
",maskArr.shape)

Get the number of elements of the Masked Array −

print("\nNumber of elements in the Masked Array...
",maskArr.size)

To calculate the n-th discrete difference along the given axis, use the MaskedArray.diff() method in Python Numpy −

print("\nResult..
.", np.diff(maskArr))

Example

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[65, 68, 81], [93, 33, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)

# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[1, 0, 0], [ 0, 0, 0], [0, 1, 0], [0, 0, 0]])
print("\nOur Masked Array...
", maskArr)

# Get the type of the masked array
print("\nOur Masked Array type...
", maskArr.dtype)

# Get the dimensions of the Masked Array
print("\nOur Masked Array Dimensions...
",maskArr.ndim)

# Get the shape of the Masked Array
print("\nOur Masked Array Shape...
",maskArr.shape)

# Get the number of elements of the Masked Array
print("\nNumber of elements in the Masked Array...
",maskArr.size)
# To calculate the n-th discrete difference along the given axis, use the MaskedArray.diff() method in Python Nump
print("\nResult..
.", np.diff(maskArr))

Output

Array...
[[65 68 81]
[93 33 76]
[73 88 51]
[62 45 67]]

Our Masked Array...
[[-- 68 81]
[93 33 76]
[73 -- 51]
[62 45 67]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(4, 3)

Number of elements in the Masked Array...
12

Result..
. [[-- 13]
[-60 43]
[-- --]
[-17 22]]