Calculate the n-th discrete difference after setting the number of times values are differenced in Numpy

NumpyServer Side ProgrammingProgramming

To calculate the n-th discrete difference along the given axis, use the MaskedArray.diff() method in Python Numpy. The "n" parameter is used to set the number of times values are differenced. If zero, the input is returned as-is.

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 the input 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 the input 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...\n", 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...\n", maskArr)

Get the type of the masked array −

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

Get the dimensions of the Masked Array −

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

Get the shape of the Masked Array −

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

Get the number of elements of the Masked Array −

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

To calculate the n-th discrete difference along the given axis, use the MaskedArray.diff() method in Python Numpy. The "n" parameter is used to set the number of times values are differenced. If zero, the input is returned as-is:

print("\nResult..\n.", np.diff(maskArr, n = 2))

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...\n", 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...\n", maskArr)

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

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

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

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

# To calculate the n-th discrete difference along the given axis, use the MaskedArray.diff() method in Python Nump
# The "n" parameter is used to set the number of times values are differenced.
# If zero, the input is returned as-is.
print("\nResult..\n.", np.diff(maskArr, n = 2))

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..
. [[--]
[103]
[--]
[39]]
raja
Updated on 05-Feb-2022 11:16:30

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