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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_threshold(dat, s_freq, method, value, nbins=120):
 """Return the value of the threshold based on relative values. Parameters dat : ndarray (dtype='float') vector with the data after selection-transformation s_freq : float sampling frequency method : str one of 'mean', 'median', 'std', 'mean+std', 'median+std', 'histmax' value : float value to multiply the values for nbins : int for histmax method, number of bins in the histogram Returns ------- float threshold in useful units. """

    if method == 'mean':
        value = value * mean(dat)
    elif method == 'median':
        value = value * median(dat)
    elif method == 'std':
        value = value * std(dat)
    elif method == 'mean+std':
        value = mean(dat) + value * std(dat)
    elif method == 'median+std':
        value = median(dat) + value * std(dat)
    elif method == 'histmax':
        hist = histogram(dat, bins=nbins)
        idx_maxbin = argmax(hist[0])
        maxamp = mean((hist[1][idx_maxbin], hist[1][idx_maxbin + 1]))
        value = value * maxamp

    return value