Apply np.sin, np.cos, and np.tan ufuncs to angles in NumPy

NumPy: Universal Functions Exercise-5 with Solution

Applying Multiple ufuncs:

Write a NumPy program that applies np.sin, np.cos, and np.tan ufuncs to a 1D NumPy array of angles (in radians) and print the results.

Sample Solution:

Python Code:

import numpy as np

# Create a 1D NumPy array of angles in radians
angles = np.array([0, np.pi/6, np.pi/4, np.pi/3, np.pi/2])

# Apply np.sin ufunc to the angles array
sin_values = np.sin(angles)

# Apply np.cos ufunc to the angles array
cos_values = np.cos(angles)

# Apply np.tan ufunc to the angles array
tan_values = np.tan(angles)

# Print the original angles array and the resulting arrays
print('Original angles (radians):\n', angles)
print('Sine values:\n', sin_values)
print('Cosine values:\n', cos_values)
print('Tangent values:\n', tan_values)

Output:

Original angles (radians):
 [0.         0.52359878 0.78539816 1.04719755 1.57079633]
Sine values:
 [0.         0.5        0.70710678 0.8660254  1.        ]
Cosine values:
 [1.00000000e+00 8.66025404e-01 7.07106781e-01 5.00000000e-01
 6.12323400e-17]
Tangent values:
 [0.00000000e+00 5.77350269e-01 1.00000000e+00 1.73205081e+00
 1.63312394e+16]

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Create 1D NumPy Array of Angles:
• Create a 1D NumPy array named angles with values [0, np.pi/6, np.pi/4, np.pi/3, np.pi/2] representing angles in radians.
• Apply np.sin ufunc:
• Apply the np.sin ufunc to the angles array to compute the sine of each angle.
• Apply np.cos ufunc:
• Apply the np.cos "ufunc" to the angles array to compute the cosine of each angle.
• Apply np.tan ufunc:
• Apply the np.tan ufunc to the angles array to compute the tangent of each angle.
• Print Results:
• Print the original angles array and the resulting arrays of sine, cosine, and tangent values.

Python-Numpy Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Element-wise Multiplication of 2D arrays using np.multiply in NumPy.
Next: Create array using np.where based on condition in NumPy.