To get the hypotenuse, use the numpy.hypot() method in Python Numpy. The method returns the hypotenuse of the triangle(s). This is a scalar if both x1 and x2 are scalars. This method is equivalent to sqrt(x1**2 + x2**2), element-wise. If x1 or x2 is scalar_like, it is broadcast for use with each element of the other argument. The parameters are the leg of the triangle(s). If x1.shape != x2.shape, they must be broadcastable to a common shape.
Steps
At first, import the required library −
import numpy as np
Creating an array with integer elements −
arr = np.ones((3, 3), dtype=int)
Displaying our array −
print("Array...\n",arr)
Get the datatype −
print("\nArray datatype...\n",arr.dtype)
Get the dimensions of the Array −
print("\nArray Dimensions...\n",arr.ndim)
Get the number of elements of the Array −
print("\nNumber of elements in the Array...\n",arr.size)
Get the hypotenuse −
print("\nHypotenuse..\n",np.hypot((3*arr), (4*arr)))
Example
import numpy as np # To get the hypotenuse, use the numpy.hypot() method in Python Numpy. # The method returns the hypotenuse of the triangle(s). This is a scalar if both x1 and x2 are scalars. # This method is equivalent to sqrt(x1**2 + x2**2), element-wise. If x1 or x2 is scalar_like, it is broadcast for use with each element of the other argument. # The parameters are the leg of the triangle(s). If x1.shape != x2.shape, they must be broadcastable to a common shape. # Creating an array with integer elements arr = np.ones((3, 3), dtype=int) # Display the array print("Array...\n", arr) # Get the type of the array print("\nOur Array type...\n", arr.dtype) # Get the dimensions of the Array print("\nOur Array Dimensions...\n",arr.ndim) # Get the number of elements in the Array print("\nNumber of elements...\n", arr.size) # Get the hypotenuse print("\nHypotenuse..\n",np.hypot((3*arr), (4*arr)))
Output
Array... [[1 1 1] [1 1 1] [1 1 1]] Our Array type... int64 Our Array Dimensions... 2 Number of elements... 9 Hypotenuse.. [[5. 5. 5.] [5. 5. 5.] [5. 5. 5.]]