numpy.true_divide () in Python

NumPy | Python Methods and Functions

Python traditionally follows gender. Regardless of the type of input, true division corrects the answer at its best. 
"//" — floor subdivision operator. 
"/" Is a true division operator.

Parameters :

  arr1:  [array_like] Input array or object which works as numerator.  arr2:  [array_like] Input array or object which works as denominator.  out:  [ndarray, None, optional] Output array with same dimensions as Input array, placed with result.  ** kwargs:  allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function.  where:  [array_like, optional] True value means to calculate the universal functions (ufunc) at that position, False value means to leave the value in the output alone. 

Return:

 If inputs are scalar then scalar; otherwise array with arr1 / arr2 (element-wise) ie true division 

Code 1: arr1 divides by arr2

# Python program explaining
# true_divide () function

import numpy as np

 
# input_array

arr1 = [ 6 , 7 , 2 , 9 , 1 ]

arr2 = [ 2 , 3 , 4 , 5 , 6 ]

print ( " arr1 : " , arr1)

print ( "arr1 :" , arr2)

 
# output_array

out = np.true_divide (arr1 , arr2)

print ( "Output array: " , out)

< p> Output:

 arr1: [6, 7, 2, 9, 1] arr1: [2, 3, 4, 5, 6] Output array: [3. 2.33333333 0.5 1.8 0.16666667] 

Code 2: arr1 elements separated by divider

# Python program explaining
# true_divide () function

import numpy as np

  
# input_array

arr1 = [ 2 , 7 , 3 , 11 , 4 ] < / p>

divisor = 3

print ( "arr1 :" , arr1)

  
# output_array

out = np.true_divide (arr1, divisor)

print ( "Output array:" , out)

Output:

 arr1: [2, 7, 3, 11, 4] Output array: [0.66666667 2.33333333 1. 3.66666667 1.33333333] 

Code 3: Comparison between floor_division (//) and true-Division (/)

# Python program explaining
# true_divide () function

import numpy as np

 
# input_array

arr1 = np. arange ( 5 )

arr2 = [ 2 , 3 , 4 , 5 , 6 ]

print ( " arr1 : " , arr1)

print ( "arr1 :" , arr2)

 
# output_array

out = np.floor_divide (arr1, arr2)

out_arr = np.true_divide (arr1, arr2) 

print ( "Output array with floor divide:" , out)

print ( "Output array with true divide :" , out_arr)

 

 

print (  "Output array with floor divide (//):" , arr1 / / arr2)

print ( "Output array with true divide (/) :" , arr1 / arr2)

Output:

 arr1: [0 1 2 3 4] arr1: [2, 3, 4, 5, 6] Output array with floor divide: [0 0 0 0 0] Output array with true divide: [0. 0.33333333 0.5 0.6 0.66666667] Output array with floor divide (//): [0 0 0 0 0] Output array with true divide (/): [0. 0.33333333 0.5 0.6 0.66666667] 

Links:
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.floor_divide.html
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