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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 standardised_euclidean(x, y, sigma=_mock_ones):
 """Euclidean distance standardised against a vector of standard deviations per coordinate. ..math:: D(x, y) = \sqrt{\sum_i \frac{(x_i - y_i)**2}{v_i}} """

    result = 0.0
    for i in range(x.shape[0]):
        result += ((x[i] - y[i]) ** 2) / sigma[i]

    return np.sqrt(result)