def run(input_root, simulation_period):
paths.build(input_root)
amf_dict = amf_obs_time_series(BASE_AMF_DICT,
complete_days_only=True,
return_low_err=True)
# get_etrm_time_series(paths.amf_extract, dict_=amf_dict)
for k, v in amf_dict.iteritems():
for kk, vv in v.iteritems():
if isinstance(vv, DataFrame):
p = os.path.join(paths.amf_output_root,
'{}_{}.csv'.format(k, kk))
print 'writing to {}'.format(p)
vv.to_csv(p)
val = amf_dict.values()[0]
cfg = Config()
for runspec in cfg.runspecs:
paths.build(runspec.input_root, runspec.output_root)
etrm = Processes(runspec)
etrm.configure_run(runspec)
etrm.run()
save_run(etrm, val)
def get_ameriflux_data(amf_file_path,
simulation_period,
etrm_extract=None,
static_inputs=None,
initial_path=None,
save_csv=None,
save_cleaned_data=None,
save_combo=False):
amf_dict = amf_obs_time_series(BASE_AMF_DICT,
amf_file_path,
complete_days_only=True,
save_cleaned_data_path=save_cleaned_data,
return_low_err=True)
if save_cleaned_data:
return None
# print 'amf dict w/ AMF time series: \n{}'.format(amf_dict)
get_etrm_time_series(etrm_extract, dict_=amf_dict)
# print 'amf dict w/ etrm input time series: \n{}'.format(amf_dict) # fix this so it appends to all sites
# print 'ameriflux dict: {}'.format(amf_dict)
for key, val in amf_dict.iteritems():
# instantiate for each item to get a clean master dict
etrm = Processes(simulation_period,
save_csv,
static_inputs=static_inputs,
point_dict=amf_dict,
initial_inputs=initial_path)
# print 'amf dict, pre-etrm run {}'.format(amf_dict)
print '\n key : {}'.format(key)
# print 'find etrm dataframe as amf_dict[key][''etrm'']\n{}'.format(amf_dict[key]['etrm'])
tracker = etrm.run(simulation_period,
point_dict=amf_dict,
point_dict_key=key,
modify_soils=True,
apply_rofrac=0.7,
allen_ceff=0.8)
# print 'tracker after etrm run: \n {}'.format(tracker)
csv_path_filename = os.path.join(save_csv,
'{}.csv'.format(val['Name']))
print 'this should be your csv: {}'.format(csv_path_filename)
tracker.to_csv(csv_path_filename, na_rep='nan', index_label='Date')
amf_obs_etrm_combo = DataFrame(
concat((val['AMF_Data'], tracker), axis=1, join='outer'))
obs_etrm_comb_out = os.path.join(save_combo,
'{}_Ceff.csv'.format(val['Name']))
print 'this should be your combo csv: {}'.format(obs_etrm_comb_out)
amf_obs_etrm_combo.to_csv(obs_etrm_comb_out, index_label='Date')
# print 'tracker for {}: {}'.format(key, tracker)
return None
def get_ameriflux_data(amf_file_path, simulation_period, etrm_extract=None,
static_inputs=None, initial_path=None, save_csv=None, save_cleaned_data=None,
save_combo=False):
amf_dict = amf_obs_time_series(BASE_AMF_DICT, amf_file_path, complete_days_only=True,
save_cleaned_data_path=save_cleaned_data, return_low_err=True)
if save_cleaned_data:
return None
# print 'amf dict w/ AMF time series: \n{}'.format(amf_dict)
get_etrm_time_series(etrm_extract, dict_=amf_dict)
# print 'amf dict w/ etrm input time series: \n{}'.format(amf_dict) # fix this so it appends to all sites
# print 'ameriflux dict: {}'.format(amf_dict)
for key, val in amf_dict.iteritems():
# instantiate for each item to get a clean master dict
etrm = Processes(simulation_period, save_csv, static_inputs=static_inputs, point_dict=amf_dict,
initial_inputs=initial_path)
# print 'amf dict, pre-etrm run {}'.format(amf_dict)
print '\n key : {}'.format(key)
# print 'find etrm dataframe as amf_dict[key][''etrm'']\n{}'.format(amf_dict[key]['etrm'])
tracker = etrm.run(simulation_period, point_dict=amf_dict, point_dict_key=key, modify_soils=True,
apply_rofrac=0.7, allen_ceff=0.8)
# print 'tracker after etrm run: \n {}'.format(tracker)
csv_path_filename = os.path.join(save_csv, '{}.csv'.format(val['Name']))
print 'this should be your csv: {}'.format(csv_path_filename)
tracker.to_csv(csv_path_filename, na_rep='nan', index_label='Date')
amf_obs_etrm_combo = DataFrame(concat((val['AMF_Data'], tracker), axis=1, join='outer'))
obs_etrm_comb_out = os.path.join(save_combo, '{}_Ceff.csv'.format(val['Name']))
print 'this should be your combo csv: {}'.format(obs_etrm_comb_out)
amf_obs_etrm_combo.to_csv(obs_etrm_comb_out, index_label='Date')
# print 'tracker for {}: {}'.format(key, tracker)
return None
def amf_observation_analysis(amf_file_path, save_cleaned_data=None):
amf_dict = amf_obs_time_series(BASE_AMF_DICT,
amf_file_path,
complete_days_only=True,
save_cleaned_data_path=save_cleaned_data,
return_low_err=True)