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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_labels(self):
 """ Returns a list of strings representing the values about which the discretization method calculates the probabilty masses. Default value is the points - unless the method is overridden by a subclass. Examples -------- ['x=-5.0', 'x=-4.5', 'x=-4.0', 'x=-3.5', 'x=-3.0', 'x=-2.5', 'x=-2.0', 'x=-1.5', 'x=-1.0', 'x=-0.5', 'x=0.0', 'x=0.5', 'x=1.0', 'x=1.5', 'x=2.0', 'x=2.5', 'x=3.0', 'x=3.5', 'x=4.0', 'x=4.5'] """

        step = (self.high - self.low) / self.cardinality
        labels = ['x={i}'.format(i=str(i)) for i in np.round(
            np.arange(self.low, self.high, step), 3)]
        return labels