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