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In NumPy, I can generate a boolean array like this:
>>> arr = np.array([1, 2, 1, 2, 3, 6, 9])
>>> arr > 2
array([False, False, False, False, True, True, True], dtype=bool)
How can we chain comparisons together? For example:
>>> 6 > arr > 2
array([False, False, False, False, True, False, False], dtype=bool)
Attempting to do so results in the error message
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
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Method 1: We generally use the == operator to compare two NumPy arrays to generate a new array object. Call ndarray. all() with the new array object as ndarray to return True if the two NumPy arrays are equivalent.
In Python, comparisons can be chained. You can write a < x and x < b as a < x < b like in mathematics. This article describes the following contents.
Comparing Arrays in NumPy The easiest way to compare two NumPy arrays is to: Create a comparison array by calling == between two arrays. Call . all() method for the result array object to check if the elements are True.
AFAIK the closest you can get is to use &, |, and ^:
>>> arr = np.array([1, 2, 1, 2, 3, 6, 9])
>>> (2 < arr) & (arr < 6)
array([False, False, False, False, True, False, False], dtype=bool)
>>> (2 < arr) | (arr < 6)
array([ True, True, True, True, True, True, True], dtype=bool)
>>> (2 < arr) ^ (arr < 6)
array([ True, True, True, True, False, True, True], dtype=bool)
I don't think you'll be able to get a < b < c-style chaining to work.
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