def test_order():
df = pd.DataFrame( { 'PRODUCT_ID' : 1 , 'DATE' : pd.date_range('1/1/2011',periods=5, freq='D'), 'SALES' : [2,3,4,1,1],
})
config = {'replenishment': {'quantiles': 70, 'replenishment': {'model': 'replenishment'},
'prediction': {'model': 'simple_prediction', 'window': 0}, 'input_file': 'temp.csv'}}
result = ord.order(df,config)
npt.assert_array_equal(df['ORDER'], [3,4,5,1,1])
parser = argparse.ArgumentParser()
parser.add_argument("-y", "--yaml", help="yaml inputfile to test", type=str)
parser.add_argument("-d", "--orderday", help="date of order", type=str)
parser.add_argument("-o", "--outputfile", help="name of outputfile", type=str)
args = parser.parse_args()
# parse config file
rep_args = parse_yaml(args.yaml)
test_file(rep_args, 'replenishment')
start_time = time.time()
'''
read in file
'''
df = pd.read_csv(rep_args['replenishment']['input_file'],sep=';', parse_dates=['DATE'])
orderday = datetime.datetime.strptime(args.orderday,'%Y-%m-%d')
df = df[df['DATE']<=orderday]
df = df.sort(['PRODUCT_ID','DATE'])
df = df.reset_index()
order_df = rep.order(df,rep_args)
order_df = order_df[order_df['DATE']==orderday]
end_time = time.time()
print "--- %s seconds ---" % (end_time - start_time)
order_df.to_csv(args.outputfile+'.csv', sep=';')