trend analysis in python and r

gistfile1.py

def convert_ts(time_series, start_year=2000, start_pd=4, freq=23):
     """
     Convert a numpy time-series into an rpy2 object, which, in turn,
     is a 'ts' object in R.  The 'ts' object is more wholly specified
     if a start date is provided.  For our applications at 16-day
     intervals for NDVI, this start date is April 2000, with a
     frequency of 23 observations each year.
     input:  numpy time-series
     output: rpy2 ts object

     """
     r_ts = robjects.r.ts(robjects.FloatVector(time_series), 
                          start=robjects.r.c(start_year,start_pd), frequency=freq)
     return r_ts

def seasonal_decomposition_R(time_series):
     """
     Seasonal decomposition of time-series by Loess smoothing ("stl"
     function in R package "stats").  We remove the seasonal component
     using the window option "periodic" whereby smoothing is
     effectively replaced by taking the mean (see documentation for
     "stl").  This is the method used for the BFAST algorithm.
     input:  rpy2 object ('ts' object in R)
     output: numpy array
     """
     stats = importr('stats')
     robjects.globalenv["rts"] = convert_ts(time_series)
     ts = robjects.r('c(rts - stl(rts, "periodic")$time.series[, "seasonal"])')
     return np.array(ts)

def break_statistic(time_series):
     """
     Test whether there exists a break in the time_series.
     input:  numpy array of time-series values
     output: float value to test against, say, p=0.05
     """
     bfast = importr('bfast')
     robjects.globalenv["rts"] = convert_ts(time_series)
     robjects.r('sct <- sctest(efp(rts ~ time(rts), h=0.05, type="OLS-MOSUM"))')
     return robjects.r('sct$statistic')[0]

Hello

thanks!
I am running python 2.7 on anaconda. I added the bfast package to the R libraries in anaconda, but when I load it the script crashes. Any idea what might be happening?
I tried loading bfast from another folder, but it doesn't seem to be recognized...