def load_locations(self):
"""
Reads information on individual suburbs from locations.csv.
"""
cast = Cast("Location")
self.locations = {}
csv_helper = CSVHelper("data", "locations.csv")
for row in csv_helper.data:
uid = cast.to_positive_int(row[0], "Uid")
cast.uid = uid
name = row[2]
longitude = cast.to_float(row[3], "Longitude")
latitude = cast.to_float(row[4], "Latitude")
population = cast.to_positive_int(row[5], "Population")
commute_mean = cast.to_positive_float(row[6], "Commute mean")
commute_std_dev = cast.to_positive_float(row[7], "Commute std dev")
occupant_distribution \
= cast.to_positive_int_list(row[8], "Occupant distribution")
occupant_values \
= cast.to_positive_int_list(row[9], "Occupant values")
pv_capacity_mean \
= cast.to_positive_float(row[10], "PV capacity mean")
pv_capacity_std_dev \
= cast.to_positive_float(row[11], "PV capacity std dev")
battery_capacity_mean \
= cast.to_positive_float(row[12], "Battery capacity mean")
battery_capacity_std_dev\
= cast.to_positive_float(row[13], "Battery capacity std dev")
loc = Location(uid, name, longitude, latitude, population,
commute_mean, commute_std_dev,
occupant_distribution, occupant_values,
pv_capacity_mean, pv_capacity_std_dev,
battery_capacity_mean, battery_capacity_std_dev)
# add public charger
self.cpm.add_company(loc)
self.locations[loc.uid] = loc
def get_parameter(self, parameter_name, parameter_type):
"""
Returns a parameter from self.parameter as a requested type.
Parameters
----------
parameter_name : string
Name of the parameter requested.
parameter_type : string
Type the parameter is requested in. Currently
supported: float, positive_float, int, positive_int, string,
boolean.
Returns
-------
<Type as requested in parameter_type>
Well the parameter request casted as the type requested
"""
if parameter_name not in self.parameters:
sys.exit("No parameter called " + parameter_name \
+ " is defined in parameters.csv")
value_str = self.parameters[parameter_name]
cast = Cast("Get Parameter")
if parameter_type == "float":
return cast.to_float(value_str, parameter_name)
elif parameter_type == "positive_float":
return cast.to_positive_float(value_str, parameter_name)
elif parameter_type == "int":
return cast.to_int(value_str, parameter_name)
elif parameter_type == "positive_int":
return cast.to_positive_int(value_str, parameter_name)
elif parameter_type == "string":
return value_str
elif parameter_type == "boolean":
return cast.to_boolean(value_str, parameter_name)
else:
sys.exit("Type '" + parameter_type + "' for parameter " \
+ parameter_name + " is not recognised")
def load_electricity_plans(self, parameters, clock):
"""
Loads all electricity plans from electricity_plans.csv.
Parameters
----------
clock : Clock
required for time_step parameter
Returns
-------
None.
"""
cast = Cast("Electricity Plan")
self.electricity_plans = dict()
csv_helper = CSVHelper("data", "electricity_plans.csv")
for row in csv_helper.data:
uid = cast.to_positive_int(row[0], "Uid")
cast.uid = uid
classification = row[1]
if not classification in ["res", "com"]:
sys.exit("Classification of electricity plan " + str(uid) \
+ " is ill-defined!")
is_commercial_plan = classification == "com"
base = cast.to_float(row[2], "Base")
feed_in_tariff = parameters.get_parameter("feed_in_tariff",
"float")
# create tariff structure
tariff_str = row[3]
tariff = self.extract_tariffs_from_string(tariff_str)
ep = ElectricityPlan(uid, is_commercial_plan, base, feed_in_tariff,
tariff, clock.time_step)
self.electricity_plans[uid] = ep
if ep.is_commercial_plan:
self.commercial_plan_uids.append(ep.uid)
else:
self.residential_plan_uids.append(ep.uid)
for it, slcted_col in enumerate(slcted_cols):
string = row[slcted_col]
if slcted_col_types[it] == "date":
# remove excess characters
for char in remove_char_from_Date:
string = string.replace(char, '')
# remove seconds
string = string[:-2]
# store
data_point.append(string)
elif slcted_col_types[it] == "int":
data_point.append(
str(cast.to_int(string, slcted_col_names[it])))
elif slcted_col_types[it] == "float":
data_point.append(
str(cast.to_float(string, slcted_col_names[it])))
else:
sys.exit("Data type '" + slcted_col_types[it] \
+ "' not implemented.")
data.append(data_point)
"""
SECTION 2: Store unprocessed data
"""
if store_raw_data == True:
print("Store raw data!")
with open('solar_irradiance.csv', mode='w', newline='') as output_file:
output_file = csv.writer(output_file,
delimiter=',',
quotechar='"',