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numpy.tan () in Python

|

Parameters :

  array:  [array_like] elements are in radians.  out:  [optional] shape same as array. 
 2pi Radians = 360 degrees tan (x) = sin (x) / cos (x) 

Return:

 An array with trignometric sine of x for all x ie array elements 

Code # 1: Work

# Python program explaining
# tan () function

 

import numpy as np

import math

 

in_array = [ 0 , math.pi / 4 , 3 * < / code> np.pi / 2 , math.pi / 6 ]

print ( "Input array:" , in_array)

 

tan_Values = np.tan (in_array)

print ( "Tan values:" , tan_Values)

Output:

 Input array: [0, 0.7853981633974483, 4.71238898038469, 0.5235987755982988] Tan values: [0.00000000e + 00 1.00000000e + 00 5.44374645e + 15 5.77350269e-01] 

Code # 2: Graphical representation

< p>

# Show Python program
# Graphical view
# tan () function

  

import numpy as np

import matplotlib.pyplot as plt

 

in_array = np.linspace ( 0 , np.pi, 12 )

out_array = np.tan (in_array)

 

print ( "in_array:" , in_array)

print ( "out_array:" , out_array)

 
# red for numpy.tan ()

plt.plot (in_array, out_array, color = ’red’ , marker = "o" )

plt.title ( "numpy.tan ()" )

plt.xlabel ( "X" )

plt.ylabel ( "Y" )

plt.show ()

Output:

 in_array: [0. 0.28559933 0.57119866 0.856798 1.14239733 1.42799666 1.71359599 1.99919533 2.28479466 2.57039399 2.85599332 3.14159265] out_array: [0.00000000e + 00 2.93626493e-01 6.42660977e-01 1.15406152e + 00 2.18969456e + 00 6.95515277e + 00 -6.955.100697e + 00.15 6.42660977e-01 -2.93626493e-01 -1.22464680e-16] 

Links:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.tan.html#numpy.tan
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