def get_undersupply_timesteps(output_file,
commod,
driving_commod=False,
demand_eq='0',
demand_driving=True):
"""
This function returns timeseries dictionaries for existence
undersupply of a commodity and the
absolute value of this undersupply.
INPUT
output_file: sqlite file (str)
commod: commodity name (str)
driving_commod: Boolean, True: driving commod, False: not driving commod
demand_eq: demand equation (str), only used if driving_commod is True
demand_driving: Boolean.
True: demand-driven commodities
False: supply-driven commodities
OUTPUT
dict_dots: timeseries dictionary with 1 and 0 depending if there is
undersupply at a specific time step.
diff_dict_drop: timeseries dictionary with absolute difference between
supply and demand, if supply < demand.
"""
if driving_commod:
all_dict = tester.supply_demand_dict_driving(output_file, demand_eq,
commod)
else:
if demand_driving:
all_dict = tester.supply_demand_dict_nondriving(output_file,
commod,
True,
calc=False)
else:
all_dict = tester.supply_demand_dict_nondriving(output_file,
commod,
False,
calc=False)
diff_dict = supplydemanddiff(all_dict)
dict_dots = {}
diff_dict_drop = {}
for key in diff_dict:
if demand_driving:
if diff_dict[key] < 0:
dict_dots[key] = 1
diff_dict_drop[key] = diff_dict[key]
else:
if diff_dict[key] > 0:
dict_dots[key] = 1
diff_dict_drop[key] = diff_dict[key]
return dict_dots, diff_dict_drop
'power': ['lwr', 'fr'],
'lwrstorageout': ['lwrreprocessing'],
'frstorageout': ['frreprocessing'],
'lwrout': ['lwrstorage'],
'frout': ['frstorage'],
'lwrtru': ['pumixerlwr'],
'frtru': ['pumixerfr'],
'lwrreprocessingwaste': ['lwrsink'],
'frreprocessingwaste': ['frsink']
}
for commod, facility in commod_dict.items():
agent_entry_dict[commod] = tester.get_agent_dict(output_file, facility)
# get supply deamnd dict
all_dict['power'] = tester.supply_demand_dict_driving(output_file, demand_eq,
'power')
plotter.plot_demand_supply_agent(all_dict['power'], agent_entry_dict['power'],
'power', 'eg01-eg24-flatpower-d3ploy_power',
True, True, False, 1)
front_commods = ['sourceout', 'enrichmentout']
back_commods = [
'lwrstorageout', 'frstorageout', 'lwrout', 'frout', 'lwrreprocessingwaste',
'frreprocessingwaste', 'frtru', 'lwrtru'
]
for commod in front_commods:
all_dict[commod] = tester.supply_demand_dict_nondriving(
output_file, commod, True)
name = 'B2000-' + commod
metric_dict = {}
for calc_method in calc_methods:
name = 'scenario_1_input_' + calc_method
input_file = name + '.json'
output_file = name + '.sqlite'
with open(input_file, 'w') as f:
json.dump(scenario_1_input[calc_method], f)
s = subprocess.check_output(['cyclus', '-o', output_file, input_file],
universal_newlines=True, env=ENV)
# Initialize dicts
all_dict_fuel = {}
all_dict_fuel = tester.supply_demand_dict_driving(output_file, demand_eq, 'fuel')
plotter.plot_demand_supply(
all_dict_fuel, 'fuel', name,True)
metric_dict = tester.metrics(all_dict_fuel,metric_dict,calc_method,'fuel',True)
df = pd.DataFrame(metric_dict)
df.to_csv('scenario_1_output.csv')
##########################################################################################
######################################SCENARIO 2##########################################
# scenario 2, source -> reactor (cycle time = 1, refuel time = 0) -> sink
scenario_2_input = {}
demand_eq = "1000*t"
indx = input_path.rfind("d3ploy/")
input = input_path.replace(
input_path[indx + len(find):], "input/%s_transition.xml" % transition_type
)
s = subprocess.check_output(
["cyclus", "-o", output_file, input], universal_newlines=True, env=ENV
)
# Initialize dicts
all_dict_power = {}
all_dict_fuel = {}
all_dict_spent_fuel = {}
agent_entry_dict = {}
metric_dict = {}
all_dict_power = tester.supply_demand_dict_driving(
output_file, demand_eq, "power")
all_dict_fuel = tester.supply_demand_dict_nondriving(output_file, "fuel", True)
all_dict_spent_fuel = tester.supply_demand_dict_nondriving(
output_file, "spent_fuel", False
)
agent_entry_dict["power"] = tester.get_agent_dict(
output_file,
[
"reactor1",
"reactor2",
"reactor3",
"reactor4",
"reactor5",
"reactor6",
"reactor7",