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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 log_normal_cdf(x, median=1, sigma=1):
 """Cumulative Log Normal Distribution Function. :param x: scalar or array of real numbers. :type x: numpy.ndarray, float :param median: Median (exp(mean of log(x)). Default 1. :type median: float :param sigma: Log normal standard deviation. Default 1. :type sigma: float :returns: An approximation of the cdf of the normal. :rtype: numpy.ndarray .. note:: CDF of the normal distribution is defined as \frac12 [1 + erf(\frac{x - \mu}{\sigma \sqrt{2}})], x \in \R Source: http://en.wikipedia.org/wiki/Normal_distribution """

    return normal_cdf(numpy.log(x), mu=numpy.log(median), sigma=sigma)