Python | Numpy MaskedArray.__div__

Python | Numpy MaskedArray.__div__

__div__ is a special method in Python 2 that implements division. In Python 3, it's removed in favor of __truediv__ for true division and __floordiv__ for floor division.

However, if you're referring to NumPy's MaskedArray, especially in the context of Python 2, the __div__ method would handle element-wise division of the masked array, while considering the mask.

When you divide two MaskedArray instances, any position that is masked in either of the arrays would be masked in the result.

Here's an example for illustration:

import numpy as np # Creating masked arrays a = np.ma.array([2.0, 2.0, 2.0, 2.0], mask=[False, True, False, False]) b = np.ma.array([1.0, 1.0, 0.0, 1.0], mask=[False, False, True, False]) # Dividing the two masked arrays result = a.__div__(b) print(result)

However, remember:

  1. If you're using Python 3, you'd likely be using __truediv__ instead of __div__.
  2. Explicitly calling special methods like __div__ or __truediv__ is usually not idiomatic in Python. They're meant to be invoked by the corresponding operators (/ in this case).

If you're working with masked arrays and considering division, always be cautious about potential division by zero issues. Ensure that you handle these cases appropriately.

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