def read_elec_data_msoa(path_to_csv):
"""Read in msoa consumption from csv file. The unit
in the original csv is in kWh per region per year.
Arguments
---------
path_to_csv : str
Path to csv file
Returns
-------
national_fuel_data : dict
geocode, total consumption
Info
-----
Source: https://www.gov.uk/government/statistical-data-sets
/regional-and-local-authority-electricity-
consumption-statistics-2005-to-2011
"""
national_fuel_data = {}
with open(path_to_csv, 'r') as csvfile:
rows = csv.reader(csvfile, delimiter=',')
headings = next(rows)
for row in rows:
geocode = str.strip(row[read_data.get_position(headings, 'msoa_code')])
tot_consumption_unclean = row[read_data.get_position(headings, 'tot_conump_kWh')].strip()
national_fuel_data[geocode] = float(tot_consumption_unclean.replace(",", ""))
return national_fuel_data
def read_scenario_data(
path_to_csv,
value_name='value',
region_name='region'
):
"""Function to read in scenario data
"""
data = {}
if not os.path.exists(path_to_csv):
raise FileNotFoundError("Cannot find file {}".format(path_to_csv))
with open(path_to_csv, 'r') as csvfile:
rows = csv.reader(csvfile, delimiter=',')
headings = next(rows) # Skip first row
for row in rows:
region = str(row[read_data.get_position(headings, region_name)])
year = int(float(row[read_data.get_position(headings, 'timestep')]))
value = float(row[read_data.get_position(headings, value_name)])
try:
data[year][region] = value
except KeyError:
data[year] = {}
data[year][region] = value
return data
def load_MOSA_pop(path_to_csv):
"""
Load MPSA population
"""
pop_data = defaultdict(dict)
with open(path_to_csv, 'r') as csvfile:
rows = csv.reader(csvfile, delimiter=',')
headings = next(rows)
for row in rows:
lad_code = str.strip(row[read_data.get_position(headings, 'Local authority code')])
MSOA_code = row[read_data.get_position(headings, 'MSOA Code')].strip()
pop = float(row[read_data.get_position(headings, 'Persons')].strip().replace(",", ""))
pop_data[lad_code][MSOA_code] = pop
return pop_data
def read_lad_demands(path_to_csv):
"""Read in national consumption from csv file. The unit
in the original csv is in GWh per region per year.
Arguments
---------
path_to_csv : str
Path to csv file
Returns
-------
national_fuel_data : dict
geocode, total consumption
Source
-----
https://www.gov.uk/government/statistical-data-sets
/regional-and-local-authority-gas-
consumption-statistics-2005-to-2011
https://www.gov.uk/government/statistical-data-sets
/regional-and-local-authority-electricity-
consumption-statistics-2005-to-2011
"""
national_fuel_data = {}
with open(path_to_csv, 'r') as csvfile:
rows = csv.reader(csvfile, delimiter=',')
headings = next(rows)
for row in rows:
geocode = str.strip(row[read_data.get_position(headings, 'LA Code')])
tot_consumption_unclean = row[read_data.get_position(headings, 'Total consumption')].strip()
if tot_consumption_unclean == '-':
pass
else:
try:
national_fuel_data[geocode] = float(tot_consumption_unclean.replace(",", ""))
except:
# no data provided
logging.debug("No validation data available for region %s", geocode)
return national_fuel_data
def read_scenario_data_gva(path_to_csv, region_name='region', value_name='value', all_dummy_data=False):
"""Function to read in GVA locally
IF no value, provide with dummy value "1"
if all_dummy_data == True, then all is dummy data and
constant over time
"""
out_dict = {}
with open(path_to_csv, 'r') as csvfile:
rows = csv.reader(csvfile, delimiter=',')
headings = next(rows)
for row in rows:
# --------------
# All dummy data
# --------------
if all_dummy_data:
region = str(row[read_data.get_position(headings, region_name)])
for year_dummy in range(2015, 2051):
for sector_dummy in range(1, 47):
dummy_sector_value = 1
try:
out_dict[year_dummy][region][sector_dummy] = dummy_sector_value
except KeyError:
out_dict[year_dummy] = defaultdict(dict)
out_dict[year_dummy][region][sector_dummy] = dummy_sector_value
else:
if row[read_data.get_position(headings, 'timestep')] == '': #No data provided
region = str(row[read_data.get_position(headings, region_name)])
for year_dummy in range(2015, 2051):
for sector_dummy in range(1, 47):
dummy_sector_value = 1
out_dict[year_dummy][region][sector_dummy] = dummy_sector_value
else:
region = str(row[read_data.get_position(headings, region_name)])
year = int(float(row[read_data.get_position(headings, 'timestep')]))
value = float(row[read_data.get_position(headings, value_name)])
economic_sector__gor = float(row[read_data.get_position(headings, 'economic_sector__gor')])
try:
out_dict[year][region][economic_sector__gor] = value
except KeyError:
out_dict[year] = defaultdict(dict)
out_dict[year][region][economic_sector__gor] = value
# Convert to regular dict
for key, value in out_dict.items():
out_dict[key] = dict(value)
return out_dict