Python numpy.true_divide()用法及代碼示例

(arr1，arr22，/，out = None，*，where = True，cast ='same_kind'，order ='K'，dtype = None，ufunc'true_divide')：
將第一個數組中的數組元素除以第二個數組中的元素(所有操作均按元素進行)。 arr1和arr2必須具有相同的形狀。按元素返回真除法。

Python傳統上遵循“樓層劃分”。不管輸入類型如何，真除法都會將答案調整為最佳。
“//”是樓層劃分操作員。
“/”是真正的除法運算符。

參數：

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.

返回：

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

代碼1：arr1除以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 ("\nOutput array : \n", out)

輸出：

arr1         :  [6, 7, 2, 9, 1]
arr1         :  [2, 3, 4, 5, 6]

Output array : 
 [ 3.          2.33333333  0.5         1.8         0.16666667]

代碼2：arr1的元素除以除數

# Python program explaining 
# true_divide() function 
import numpy as np 
  
# input_array 
arr1 = [2, 7, 3, 11, 4] 
divisor = 3
print ("arr1         : ", arr1) 
  
# output_array 
out = np.true_divide(arr1, divisor) 
print ("\nOutput array : ", out)

輸出：

arr1         :  [2, 7, 3, 11, 4]

Output array :  [ 0.66666667  2.33333333  1.          3.66666667  1.33333333]

代碼3：floor_division(/)和true-division(/)之間的比較

# 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 ("\nOutput array with floor divide : \n", out) 
print ("\nOutput array with true divide  : \n", out_arr) 
  
  
print ("\nOutput array with floor divide(//) : \n", arr1//arr2) 
print ("\nOutput array with true divide(/)   : \n", arr1/arr2)

輸出：

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]

參考文獻：
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.floor_divide.html
。