def _kde_support(data, bw, gridsize, cut, clip):
 support_min = max((data.min() - (bw * cut)), clip[0])
 support_max = min((data.max() + (bw * cut)), clip[1])
 return np.linspace(support_min, support_max, gridsize)

def _kde_support ( data , bw , gridsize , cut , clip ) : support_min = max ( ( data . min ( ) - ( bw * cut ) ) , clip [ 0 ] ) support_max = min ( ( data . max ( ) + ( bw * cut ) ) , clip [ 1 ] ) return np . linspace ( support_min , support_max , gridsize )
establish support for a kernel density estimate .