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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 define(cls, start, step, num, dtype=None):
 """Define a new `Index`. The output is basically:: start + numpy.arange(num) * step Parameters start : `Number` The starting value of the index. step : `Number` The step size of the index. num : `int` The size of the index (number of samples). dtype : `numpy.dtype`, `None`, optional The desired dtype of the index, if not given, defaults to the higher-precision dtype from ``start`` and ``step``. Returns ------- index : `Index` A new `Index` created from the given parameters. """

        if dtype is None:
            dtype = max(
                numpy.array(start, subok=True, copy=False).dtype,
                numpy.array(step, subok=True, copy=False).dtype,
            )
        start = start.astype(dtype, copy=False)
        step = step.astype(dtype, copy=False)
        return cls(start + numpy.arange(num, dtype=dtype) * step, copy=False)