numpy (logical_and vs '&') 语句的顺序导致不同的结果

Question

I have a simple piece of code where I am trying to compare the numpy function logical_and vs the "&" operator.

I encounter a very strange behavior where the order in the which the statements are executed, seem to have an effect on the final result when in fact they shouldn't. Weird!

In the below code , if I interchange the final_mask1 and final_mask statement order, it leads to a different value of the variable "test" as well as a different image as an output. This is for the case where I have final_mask as output. Am I missing something here? How can I resolve this? TIA

import numpy as np
from scipy import misc
import matplotlib.pyplot as plt
photo_data = misc.imread('./sd-3layers.jpg')
red_mask = photo_data[:, : ,0] < 150
green_mask = photo_data[:, : ,1] > 100
blue_mask = photo_data[:, : ,2] < 100

final_mask1 = np.logical_and(red_mask, green_mask, blue_mask)
final_mask = red_mask & green_mask & blue_mask

test = (final_mask1 == final_mask)
print(np.all(test))
photo_data[final_mask] = 0
plt.figure(figsize=(15,15))
plt.imshow(photo_data)

Answer 1

Looking up the documentation of logical_and , one finds that it compares only two arrays, and that the third argument is used for storing results in a different array. You can use reduce to avoid having to write to calls to logical_and , so what you're trying to do ends up looking like

np.logical_and.reduce((red_mask, green_mask, blue_mask))