overload the bracket operator with multiple parameters

Question

I have built a wrapper around numpy array for simplification purposes I will display only the necessary part to show the error:

class Matrix(object): """wrap around numpy array """ def __init__(self, shape, fill_value): self.matrix = np.full(shape, fill_value) def __getitem__(self, a, b): return self.matrix[a, b] m = Matrix((10, 10), 5) print(m[5, 5])

the print statement generates the following error:

KeyError: __getitem__() takes exactly 3 arguments (2 given)

what's the fix to access m using the [] operator like the follwing:

m[1, 1]

rachid · Accepted Answer · 2017-11-10 10:31:03Z

the solution is to pass a tuple inside a variable like the following:

class Matrix(object): """wrap around numpy array """ def __init__(self, shape, fill_value): self.matrix = np.full(shape, fill_value) def __getitem__(self, a): # we could do also do return self.matrix[a[0], a[1]] return self.matrix[a] m = Matrix((10, 10), 5) print(m[5, 5])

Mark Hannel · Accepted Answer · 2017-11-09 17:00:29Z

Currently, you have a class Matrix with an attribute matrix which is a numpy array. Therefore you would need to reference the attribute first and then pass the indices:

>>> m.matrix[5,5] 5

At this point, you have not wrapped around a numpy array. Depending on what you want to do, this could be a step in the right direction:

class Matrix(np.ndarray): def __new__(cls, shape, fill_value=0): return np.full(shape, fill_value) >>> m = MyMatrix((10, 10), 5) >>> print(m[5, 5]) >>> 5

However, this essentially does nothing more than m = np.full(shape, fill_value). I suppose you are going to want to add custom attributes and methods to a numpy array, in which you should check out this example in the numpy documentation.

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