Get EUSTACE data sample to plot as stripes

#!/usr/bin/env python

# Get a climate-stripes sample from Eustace
# Monthly, resolved in latitude, sampling in longitude, 
#   sampling across the ensemble.

import os
import sys
import numpy
import datetime
import pickle


start=datetime.datetime(1851,1,1,0,0)
end=datetime.datetime(2018,12,31,23,59)

sys.path.append('%s/../../../EUSTACE/ensemble-monthly/' % 
                                  os.path.dirname(__file__))
from get_sample import get_sample_cube

(ndata,dts) = get_sample_cube(start,end)

pickle.dump( (ndata,dts), open( "EUSTACE.pkl", "wb" ) )

# Get the sample cube for EUSTACE
# Monthly, resolved in latitude, sampling in longitude, sampling the ensemble.

# Delegates making the slices to the parallelisable make_slice script.
# This script only puts the slices together.

import os
import iris
import numpy
import datetime
import pickle

def get_sample_cube(start=datetime.datetime(1851,1,1,0,0),
                    end=datetime.datetime(2018,12,31,23,59)):

    slice_dir = "%s/EUSTACE/derived/ensemble-monthly" % \
                                    os.getenv('SCRATCH')

    # Array to store the sample in
    ndata=numpy.ma.array(numpy.zeros(((2016-1850)*12,720)),mask=False)
    dts=[]
    # Assemble the sample slice by slice
    for year in range(1850,2016):
        for month in range(1,13):
            t=(year-1850)*12+month-1
            dfile = "%s/%04d%02d.pkl" % (slice_dir,year,month)
            with open(dfile, "rb") as f:
                dslice = pickle.load(f)
            ndata[t,:]=dslice[0,:]
            dts.append(datetime.datetime(year,month,15))
            
    return (ndata,dts)