def _split(da, date, period="Y"):
	"""
	args:
		da: xarray data array
			the dataarray containing the values with a time index
		date: pandas datetime
			date of the breakpoint
		period: datetime frequency code
			shift till after the breakpoint, based on temporal frequency of data
	Returns
		y1: Array like y-values for data preceeding the breakpoint
		x1: Array like x-values for data preceeding the breakpoint
		y2: Array like y-values for data occuring after the breakpoint
		x2: Array like x-values for data occuring after the breakpoint
	"""
	# ========== Split the time series ==========
	y1 = da.sel(time=slice(None, date)).values
	y2 = da.sel(time=slice(
		date,None)).values

	x1 = da.sel(time=slice(None, date)).time.values.astype('datetime64[%s]'% period).astype(float)
	x2 = da.sel(time=slice(date,None)).time.values.astype('datetime64[%s]'% period).astype(float)

	return y1, y2, x1, x2