Unexpected behavior serializing Numpy array

Code

Suppose I have:

import numpy
import pickle


class Test():
    def __init__(self):
        self.base = numpy.zeros(6)
        self.view = self.base[-3:]

    def __len__(self):
        return len(self.view)

    def update(self):
        self.view[0] += 1

    def add(self):
        self.view = self.base[-len(self.view) - 1:]
        self.view[0] = 1

    def __repr__(self):
        return str(self.view)


def serialize_data():
    data = Test()
    return pickle.dumps(data)

Note that class Test is simply a class that contains a view of a NumPy array base. This view is simply a slice of the last N elements in base (N == 3 on initialization).

Test has a method update() which adds 1 to the value at position 0 of the view, and a method add() which modifies the view size (N = N + 1) and sets the value at position 0 to 1.

The function serialize_data simply creates a Test() instance and then returns the serialized object using pickle.

Behavior

If I create a local variable and update it twice and add it once, everything works as expected:

# Local variable
test = Test()
print(test)    # [ 0.  0.  0.]

test.update()
test.update()
print(test)    # [ 2.  0.  0.]

test.add()
print(test)    # [ 1.  2.  0.  0.]

Now, if I create a local variable out of serialized data, then after executing add the value 2 (set after calling update twice) seems to be lost:

# Serialized variable
data = pickle.loads(serialize_data())
print(data)    # [ 0.  0.  0.]

data.update()
data.update()
print(data)    # [ 2.  0.  0.]

data.add()
print(data)    # [ 1.  0.  0.  0.]  <----  This should be [ 1. 2. 0. 0. ] !!!

Question

Why is this happening and how could I avoid this behavior?