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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 find_gamma_params(mode, std):
 """Given a modal value and a standard deviation, compute corresponding parameters for the gamma distribution. Intended to be used to replace normal distributions when the value must be positive and the uncertainty is comparable to the best value. Conversion equations determined from the relations given in the sample_gamma() docs. """

    if mode < 0:
        raise ValueError('input mode must be positive for gamma; got %e' % mode)

    var = std**2
    beta = (mode + np.sqrt(mode**2 + 4 * var)) / (2 * var)
    j = 2 * var / mode**2
    alpha = (j + 1 + np.sqrt(2 * j + 1)) / j

    if alpha <= 1:
        raise ValueError('couldn\'t compute self-consistent gamma parameters: '
                         'mode=%e std=%e alpha=%e beta=%e' % (mode, std, alpha, beta))

    return alpha, beta