def sim_sir_filtered():
params = read_params('./data/params/params.csv')
params['filtering'] = True
sir = SIR(params)
sir.predict_with_filter()
pprint(sir.scores)
return sir.score
def sim_sir_filtered():
params = read_params('./data/params/params.csv')
params['filtering'] = True
sir = SIR(params)
sir.predict_with_filter()
pprint(sir.scores)
return sir.score
def sim_psir_filtered(ens, year, date, params=None):
if not params:
params = read_params('./data/params/params%s.csv' % year)
params['filtering'] = True
params['time_varying'] = False
sir = ParticleSIR(ens, params)
sir.predict_with_filter()
out_str = ','.join(map(str, sir.IS))
pprint(sir.scores)
path = '%s_%s_predictions_example' % (date[0], date[1])
write_file(path, year, sir, out_str)
def sim_easir_filtered(ens, year, cov_type, params):
if not params:
params = read_params('./data/params/params%s.csv' % year)
params['filtering'] = True
sir = EnsembleAdjustmentSIR(ens, params)
sir.filter.cov_type = cov_type
sir.predict_with_filter()
out_str = ','.join(map(str, sir.IS))
path = 'centered_eakf' if cov_type == 'c' else 'uncentered_eakf'
write_file(path, year, sir, out_str)
return sir.score
def sim_psir_filtered(ens, year, params=None):
if not params:
params = read_params('./data/params/params%s.csv' % year)
params['filtering'] = True
params['time_varying'] = False
sir = ParticleSIR(ens, params)
sir.predict_with_filter()
out_str = ','.join(map(str, sir.IS))
pprint(sir.scores)
path = 'centered_pkf'
write_file(path, year, sir, out_str)
def sim_easir_filtered(ens, year, cov_type, params):
if not params:
params = read_params('./data/params/params%s.csv' % year)
params['filtering'] = True
sir = EnsembleAdjustmentSIR(ens, params)
sir.filter.cov_type = cov_type
sir.predict_with_filter()
out_str = ','.join(map(str, sir.IS))
path = 'centered_eakf' if cov_type == 'c' else 'uncentered_eakf'
write_file(path, year, sir, out_str)
return sir.score
def sim_basssir_filtered(ens, year, cov_type, params=None):
if not params:
params = read_params('./data/params/params%s.csv' % year)
params['filtering'] = True
params['time_varying'] = False
sir = BassSIR(ens, params)
sir.err_bnd = 0.00001
sir.filter.cov_type = cov_type
sir.predict_with_filter()
out_str = ','.join(map(str, sir.IS))
path = 'centered_bass' if cov_type == 'c' else 'uncentered_bass'
pprint(sir.scores)
write_file(path, year, sir, out_str)
return sir.score
def sim_basssir_filtered(ens, year, cov_type, params=None):
if not params:
params = read_params('./data/params/params%s.csv' % year)
params['filtering'] = True
params['time_varying'] = False
sir = BassSIR(ens, params)
sir.err_bnd = 0.00001
sir.filter.cov_type = cov_type
sir.predict_with_filter()
out_str = ','.join(map(str, sir.IS))
path = 'centered_bass' if cov_type == 'c' else 'uncentered_bass'
pprint(sir.scores)
write_file(path, year, sir, out_str)
return sir.score
def sim_sir():
params = read_params('./data/params/params2013-14-sir.csv')
sir = SIR(params)
sir.predict()
return sir.scores
def sim_sir():
params = read_params('./data/params/params2013-14-sir.csv')
sir = SIR(params)
sir.predict()
return sir.scores