Given a two numpy arrays, the task is to multiply 2d numpy array with 1d numpy array each row corresponding to one element in numpy. Let’s discuss a few methods for a given task.
Method #1: Using np.newaxis()
# Python code to demonstrate # multiplication of 2d array # with 1d array import numpy as np ini_array1 = np.array([[1, 2, 3], [2, 4, 5], [1, 2, 3]]) ini_array2 = np.array([0, 2, 3]) # printing initial arrays print("initial array", str(ini_array1)) # Multiplying arrays result = ini_array1 * ini_array2[:, np.newaxis] # printing result print("New resulting array: ", result) |
Output:
initial array [[1 2 3] [2 4 5] [1 2 3]] New resulting array: [[ 0 0 0] [ 4 8 10] [ 3 6 9]]
Method #2: Using axis as none
# Python code to demonstrate # multiplication of 2d array # with 1d array import numpy as np ini_array1 = np.array([[1, 2, 3], [2, 4, 5], [1, 2, 3]]) ini_array2 = np.array([0, 2, 3]) # printing initial arrays print("initial array", str(ini_array1)) # Multiplying arrays result = ini_array1 * ini_array2[:, None] # printing result print("New resulting array: ", result) |
Output:
initial array [[1 2 3] [2 4 5] [1 2 3]] New resulting array: [[ 0 0 0] [ 4 8 10] [ 3 6 9]]
Method #3: Using transpose()
# python code to demonstrate # multiplication of 2d array # with 1d array import numpy as np ini_array1 = np.array([[1, 2, 3], [2, 4, 5], [1, 2, 3]]) ini_array2 = np.array([0, 2, 3]) # printing initial arrays print("initial array", str(ini_array1)) # Multiplying arrays result = (ini_array1.T * ini_array2).T # printing result print("New resulting array: ", result) |
Output:
initial array [[1 2 3] [2 4 5] [1 2 3]] New resulting array: [[ 0 0 0] [ 4 8 10] [ 3 6 9]]
