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What is "NumPy TypeError: ufunc 'bitwise_and' not supported for the input types" when using a dynamically created boolean mask, how to fix it?

Learn about the "NumPy TypeError: ufunc 'bitwise_and' not supported for the input types" when using a dynamically created boolean mask, and its solution. By Pranit Sharma Last updated : April 05, 2023

Suppose that we are given a numpy array of floats and we are creating a mask from this array where this array equals to a particular value, if yes, we do a bitwise AND (&) operation of this value with some other value.

This can be done in a single-line statement as:

arr == 'some value' & b

But this statement generates a TypeError as "ufunc 'bitwise_and' not supported for the input types", and the inputs could not be safely coerced to any supported types according to the casting rule ''safe'. We get this error because bitwise_and is not defined for a floating-point scalar and a boolean array.

How to fix "ufunc 'bitwise_and' not supported for the input types" TypeError?

To fix NumPy TypeError: ufunc 'bitwise_and' not supported for the input types, we need to separate the expression by adding a parathesis to the statement. We can also do this by converting the float array into an int array.

Let us understand with the help of an example,

Python code to "ufunc 'bitwise_and' not supported for the input types" TypeError

# Import numpy
import numpy as np

# Creating an array
arr = np.array(np.array([1.0, 2.0, 3.0]))

# Display array
print("Original array:\n",arr,"\n")

# masking and bitwise and
arr = (arr == 2.0) & 3

# Display result
print("Result:\n",arr,"\n")

Output

The output of the above program is:

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