使用PyCharm建议的PEP8‘if cond is False’写法结合Numpy逻辑函数出现异常的问题

Hey there, let's break down why this confusing behavior pops up when you use PyCharm's PEP8-recommended if cond is False alongside Numpy's boolean array functions like np.isinf or np.isnan.

First off, the core issue is a mismatch between what you're checking and what Numpy returns. Functions like np.isinf() and np.isnan() don't spit out a single Python boolean—they return a Numpy boolean array (even if you pass a single scalar value, it's still a 0-dimensional array under the hood).

When you use is False, you're doing an object identity check: you're asking "is this array object exactly the same as Python's built-in False object?" This will never be true, because an array and a single boolean are completely different types of objects.

Example of the problem #

Take this code snippet:

import numpy as np

arr = np.array([1.0, np.inf, 3.0])
cond = np.isinf(arr)

# This will always hit the else branch, regardless of the array contents
if cond is False:
    print("No inf values found!")
else:
    print("Wait, why is this running?")

Even though cond holds values that include True, the condition cond is False is checking object identity, not the actual boolean values in the array. So it will always evaluate to False.

The correct approaches #

Depending on what you're trying to do, here's how to fix it:

• Check if any element in the array is inf/nan: Use np.any() to test if there's at least one True in the boolean array:

  if np.any(np.isinf(arr)):
      print("Found inf values in the array!")
  

• Check if no elements are inf/nan: Use not np.any() or np.all() with the negated condition:

  if not np.any(np.isinf(arr)):
      print("No inf values present!")
  # Or equivalently
  if np.all(~np.isinf(arr)):
      print("No inf values present!")
  

• Working with a single scalar value: Even if you're dealing with a single element (not an array), PEP8 actually prefers if not cond over if cond is False—it's cleaner and avoids identity check quirks:

  x = np.inf
  cond = np.isinf(x)
  if not cond:
      print("x is not infinite")
  

PyCharm's recommendation for if cond is False is intended for simple single-boolean variable scenarios, not for Numpy's array-based boolean results. Once you're working with array outputs, you need to use Numpy's built-in aggregation functions to check the array's overall boolean state.

内容的提问来源于stack exchange，提问作者P-Gn