The truth value of an array with more than one element is ambiguous. use a.any() or a.all().
For boolean arrays – and comparisons like <, <=, ==, !=, >= and > on NumPy arrays return boolean NumPy arrays – you can also use the element-wise bitwise functions (and operators): np.bitwise_and (& operator)
import numpy as np first = np.array([1, 2, 3]) second = bool(first) print(second)
The output will be this error message:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
The element-wise equivalent for and would be the np.logical_and function, similarly you could use np.logical_or as equivalent for or.
Logical_and() function
import numpy as np arr = np.array([1, 2, 3]) print(np.logical_and(arr > 1, arr < 3))
[False True False]
Logical_or() function
import numpy as np arr1 = np.arange(5) arr2 = np.arange(5, 10) arr3 = np.array(['First', 'Second', 'Third', 'Fourth', 'Fifth']) mask = np.logical_or(arr1 >= 3, arr2 < 3) print(arr3[mask])
['Fourth' 'Fifth']
import numpy as np np1 = np.zeros((3,)) np2 = np.ones((3,)) np1 in (np1, np2) # True
The Truth Value of an array with more than one element is ambiguous.
np1 in (np2, np1) ValueError Traceback (most recent call last) <gfd.py> in <module> 1 np1 in (np2, np1) ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
np1 == np1 array([ True, True, True]) np1 is np1 or np1 == np1 # True np1 is np2 or np1 == np2 # False
any(np1 is e or np1 == e for e in (np2, np1) ValueError Traceback (most recent call last) <gfd.py> in <module> 1 any(np1 is e or np1 == e for e in (np2, np1)) ValueError: The truth value of an array with more than one element is ambiguous. Use `a.any()` or `a.all()`.The issue does not occur when == is never broadcasted.
np1 in (np3, np1) # True