Updated On : Jul-15,2020 Time Investment : ~10 mins

Learning NumPy - Mathematical Functions - Part 14

Quite understandably, NumPy contains a large number of various mathematical operations. NumPy provides standard trigonometric functions, functions for arithmetic operations, handling complex numbers, etc.

Trigonometric Functions NumPy has standard trigonometric functions which return trigonometric ratios for a given angle in radians.

Example

import numpy as np
a = np.array([0,30,45,60,90])

print ('Sine of different angles:')
# Convert to radians by multiplying with pi/180 
print (np.sin(a*np.pi/180))
print ('\n')

print ('Cosine values for angles in array:')
print (np.cos(a*np.pi/180))
print ('\n')

print ('Tangent values for given angles:')
print (np.tan(a*np.pi/180))
Sine of different angles:
[0.         0.5        0.70710678 0.8660254  1.        ]


Cosine values for angles in array:
[1.00000000e+00 8.66025404e-01 7.07106781e-01 5.00000000e-01
 6.12323400e-17]


Tangent values for given angles:
[0.00000000e+00 5.77350269e-01 1.00000000e+00 1.73205081e+00
 1.63312394e+16]

Point To Understand

  • arcsin, arcos, and arctan functions return the trigonometric inverse of sin, cos, and tan of the given angle. The result of these functions can be verified by numpy.degrees() function by converting radians to degrees.
import numpy as np
a = np.array([0,30,45,60,90])

print ('Array containing sine values:')
sin = np.sin(a*np.pi/180)
print (sin)
print ('\n')

print ('Compute sine inverse of angles. Returned values are in radians.')
inv = np.arcsin(sin)
print (inv)
print ('\n')

print ('Check result by converting to degrees:')
print (np.degrees(inv))
print ('\n')

print ('arccos and arctan functions behave similarly:')
cos = np.cos(a*np.pi/180)
print (cos)
print ('\n')

print ('Inverse of cos:')
inv = np.arccos(cos)
print (inv)
print ('\n')

print ('In degrees:')
print (np.degrees(inv))
print ('\n')

print ('Tan function:')
tan = (np.tan(a*np.pi/180))
print (tan)
print ('\n')

print ('Inverse of tan:')
inv = (np.arctan(tan))
print (inv)
print ('\n')

print ('In degrees:')
print (np.degrees(inv))
Array containing sine values:
[0.         0.5        0.70710678 0.8660254  1.        ]


Compute sine inverse of angles. Returned values are in radians.
[0.         0.52359878 0.78539816 1.04719755 1.57079633]


Check result by converting to degrees:
[ 0. 30. 45. 60. 90.]


arccos and arctan functions behave similarly:
[1.00000000e+00 8.66025404e-01 7.07106781e-01 5.00000000e-01
 6.12323400e-17]


Inverse of cos:
[0.         0.52359878 0.78539816 1.04719755 1.57079633]


In degrees:
[ 0. 30. 45. 60. 90.]


Tan function:
[0.00000000e+00 5.77350269e-01 1.00000000e+00 1.73205081e+00
 1.63312394e+16]


Inverse of tan:
[0.         0.52359878 0.78539816 1.04719755 1.57079633]


In degrees:
[ 0. 30. 45. 60. 90.]

Functions for Rounding

numpy.around()

This is a function that returns the value rounded to the desired precision. The function takes the following parameters.

numpy.around(a,decimals)
Parameter Description
a Input data
decimals The number of decimals to round to. Default is 0. If negative, the integer is rounded to position to the left of the decimal point

Example 1

import numpy as np
a = np.array([1.0,5.55, 123, 0.567, 25.532])

print ('Original array:')
print (a)
print ('\n')

print ('After rounding:')
print (np.around(a))
print (np.around(a, decimals = 1))
print (np.around(a, decimals = -1))
Original array:
[  1.      5.55  123.      0.567  25.532]


After rounding:
[  1.   6. 123.   1.  26.]
[  1.    5.6 123.    0.6  25.5]
[  0.  10. 120.   0.  30.]

numpy.floor()

This function returns the largest integer not greater than the input parameter. The floor of the scalar x is the largest integer i, such that i <= x. Note that in Python, flooring always is rounded away from 0.

import numpy as np
a = np.array([-1.7, 1.5, -0.2, 0.6, 10])

print ('The given array:')
print (a)
print ('\n')

print ('The modified array:')
print (np.floor(a))
The given array:
[-1.7  1.5 -0.2  0.6 10. ]


The modified array:
[-2.  1. -1.  0. 10.]

numpy.ceil()

The ceil() function returns the ceiling of an input value, i.e. the ceil of the scalar x is the smallest integer i, such that i >= x.

import numpy as np
a = np.array([-1.7, 1.5, -0.2, 0.6, 10])

print ('The given array:')
print (a)
print ('\n')

print ('The modified array:')
print (np.ceil(a))
The given array:
[-1.7  1.5 -0.2  0.6 10. ]


The modified array:
[-1.  2. -0.  1. 10.]
Dolly Solanki  Dolly Solanki

YouTube Subscribe Comfortable Learning through Video Tutorials?

If you are more comfortable learning through video tutorials then we would recommend that you subscribe to our YouTube channel.

Need Help Stuck Somewhere? Need Help with Coding? Have Doubts About the Topic/Code?

When going through coding examples, it's quite common to have doubts and errors.

If you have doubts about some code examples or are stuck somewhere when trying our code, send us an email at coderzcolumn07@gmail.com. We'll help you or point you in the direction where you can find a solution to your problem.

You can even send us a mail if you are trying something new and need guidance regarding coding. We'll try to respond as soon as possible.

Share Views Want to Share Your Views? Have Any Suggestions?

If you want to

  • provide some suggestions on topic
  • share your views
  • include some details in tutorial
  • suggest some new topics on which we should create tutorials/blogs
Please feel free to contact us at coderzcolumn07@gmail.com. We appreciate and value your feedbacks. You can also support us with a small contribution by clicking DONATE.


Subscribe to Our YouTube Channel

YouTube SubScribe

Newsletter Subscription