#!/usr/bin/env python

import os

field_tests = [
        #    ["CHD", "CSMOKING", "CANCER", "svi_minority", "Estbeds"],
        #    [],
        #    ['Population'],
        #    ['Insurance'],
            ['Nbeds'],
            ['Nbeds_per1000'],
            ['Nhosp'],
            ['Estbeds'],
            ['senior_percent'],
            ['black_percent'],
            ['Percentblacks'],
            ['Percenthispanics'],
            ['pop_density_2010'],
            ['poverty_percent'],
            ['svi_minority'],
            ['svi_overall'],
            ['CASTHMA'],
            ['HIGHCHOL'],
            ['DIABETES'],
            ['OBESITY'],
            ['CANCER'],
            ['STROKE'],
            ['MHLTH'],
            ['CSMOKING'],
            ['CHOLSCREEN'],
            ['INSURANCE'],
            ['CHD'],
            ['CHECKUP'],
            ['KIDNEY'],
            ['BINGE'],
            ['LPA'],
            ['ARTHRITIS'],
            ['BPMED'],
            ['PHLTH'],
            ['BPHIGH'],
            ['COPD'],
            ['PVI']
    ]

for fields in field_tests:
    fnames = ",".join(fields)

    for days in range(1,15):
        os.system (f"./cloudmesh/timeseries/predict/lstm-predict-n.py --fields={fnames} --daysin={days}")

