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Given the “legs” of a right triangle, return its hypotenuse in Python
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.]]
Updated on: 28-Feb-2022
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