def post_install_setup_minimum(args):
"""If not all data are available, this scripts allows to
create dummy datas (temperature and service sector load profiles)
"""
path_config_file = args.config_file
config = data_loader.read_config_file(path_config_file)
path_local_data = config['PATHS']['path_local_data']
# ==========================================
# Post installation setup witout access to non publicy available data
# ==========================================
print(
"... running initialisation scripts with only publicly available data")
local_paths = data_loader.get_local_paths(path_config_file)
# Create folders to input data
raw_folder = os.path.join(path_local_data, '_raw_data')
basic_functions.create_folder(raw_folder)
basic_functions.create_folder(config['PATHS']['path_processed_data'])
basic_functions.create_folder(local_paths['path_post_installation_data'])
basic_functions.create_folder(local_paths['load_profiles'])
basic_functions.create_folder(local_paths['rs_load_profile_txt'])
basic_functions.create_folder(local_paths['ss_load_profile_txt'])
# Load data
data = {}
data['paths'] = data_loader.load_paths(path_config_file)
data['lookups'] = lookup_tables.basic_lookups()
data['enduses'], data['sectors'], data[
'fuels'], lookup_enduses, lookup_sector_enduses = data_loader.load_fuels(
data['paths'])
# Assumptions
data['assumptions'] = general_assumptions.Assumptions(
lookup_enduses=lookup_enduses,
lookup_sector_enduses=lookup_sector_enduses,
base_yr=2015,
weather_by=config['CONFIG']['user_defined_weather_by'],
simulation_end_yr=config['CONFIG']['user_defined_simulation_end_yr'],
paths=data['paths'],
enduses=data['enduses'],
sectors=data['sectors'])
# Read in residential submodel shapes
run(data['paths'], local_paths, config['CONFIG']['base_yr'])
# --------
# Dummy service sector load profiles
# --------
dummy_sectoral_load_profiles(local_paths, path_config_file)
print(
"Successfully finished post installation setup with open source data")
def test_get_local_paths(config_file):
actual = get_local_paths(config_file)
assert isinstance(actual, dict)
assert actual[
'yaml_parameters_scenario'] == '/vagrant/data/energy_demand/config/yaml_parameters_scenario.yml'
def test_assign_by_fuel_tech_p(config_file):
"""
"""
config = data_loader.read_config_file(config_file)
# Load data
data = {}
data['paths'] = config['CONFIG_DATA']
data['lookups'] = lookup_tables.basic_lookups()
data['enduses'], data['sectors'], data[
'fuels'], _, _ = data_loader.load_fuels(data['paths'])
data['local_paths'] = data_loader.get_local_paths(path_main)
#Load assumptions
base_yr = 2015
data['assumptions'] = general_assumptions.Assumptions(
submodels_names=['a'],
base_yr=base_yr,
curr_yr=None,
sim_yrs=None,
paths=data['paths'],
enduses=data['enduses'],
sectors=data['sectors'],
fueltypes=data['lookups']['fueltypes'],
fueltypes_nr=data['lookups']['fueltypes_nr'])
strategy_vars_def.load_param_assump(data['paths'], data['local_paths'],
data['assumptions'])
fuel_tech_p_by = fuel_shares.assign_by_fuel_tech_p(
data['enduses'], data['sectors'], data['lookups']['fueltypes'],
data['lookups']['fueltypes_nr'])
path_main = os.path.abspath(
os.path.join(os.path.dirname(__file__), '..', "config_data"))
# Configuration paths
config = configparser.ConfigParser()
config.read(os.path.join(path_config, 'wrapperconfig.ini'))
# --------
# Other configuration
# --------
base_yr = 2015
sim_yrs = [2015, 2050]
paths = data_loader.load_paths(path_main)
data_path = os.path.normpath(config['PATHS']['path_local_data'])
local_paths = data_loader.get_local_paths(data_path)
data = {}
data['enduses'], data['sectors'], data['fuels'] = data_loader.load_fuels(paths)
assumptions = general_assumptions.Assumptions(base_yr=user_defined_base_yr,
curr_yr=2015,
sim_yrs=sim_yrs,
paths=paths,
enduses=data['enduses'],
sectors=data['sectors'])
# Write parameters to YAML file
_, _ = strategy_vars_def.load_param_assump(assumptions)
def main(path_data_ed, path_shapefile_input, plot_crit_dict, base_yr,
comparison_year):
"""Read in all results and plot PDFs
Arguments
----------
path_data_ed : str
Path to results
path_shapefile_input : str
Path to shapefile
plot_crit_dict : dict
Criteria to select plots to plot
base_yr : int
Base year
comparison_year : int
Year to generate comparison plots
"""
print("...Start creating plots")
data = {}
# ---------------------------------------------------------
# Iterate folders and read out all weather years and stations
# ---------------------------------------------------------
to_ignores = ['model_run_pop', 'PDF_validation']
endings_to_ignore = ['.pdf', '.txt', '.ini']
all_result_folders = os.listdir(path_data_ed)
paths_folders_result = []
for result_folder in all_result_folders:
if result_folder not in to_ignores and result_folder[
-4:] not in endings_to_ignore:
paths_folders_result.append(
os.path.join(path_data_ed, result_folder))
####################################################################
# Calculate results for every weather year
####################################################################
for path_result_folder in paths_folders_result:
print("-----------------------")
print("path_result_folder: " + str(path_result_folder))
print("-----------------------")
# Simulation information is read in from .ini file for results
data['enduses'], data['assumptions'], data[
'regions'] = data_loader.load_ini_param(os.path.join(path_data_ed))
# ------------------
# Load necessary inputs for read in
# ------------------
data = {}
data['local_paths'] = data_loader.get_local_paths(path_result_folder)
data['result_paths'] = basic_functions.get_result_paths(
os.path.join(path_result_folder))
data['lookups'] = lookup_tables.basic_lookups()
# ---------------
# Folder cleaning
# ---------------
basic_functions.del_previous_setup(
data['result_paths']['data_results_PDF'])
basic_functions.del_previous_setup(
data['result_paths']['data_results_shapefiles'])
basic_functions.create_folder(data['result_paths']['data_results_PDF'])
basic_functions.create_folder(
data['result_paths']['data_results_shapefiles'])
basic_functions.create_folder(
data['result_paths']['individual_enduse_lp'])
# Simulation information is read in from .ini file for results
data['enduses'], data['assumptions'], data[
'regions'] = data_loader.load_ini_param(os.path.join(path_data_ed))
# Other information is read in
data['assumptions']['seasons'] = date_prop.get_season(
year_to_model=2015)
data['assumptions']['model_yeardays_daytype'], data['assumptions'][
'yeardays_month'], data['assumptions'][
'yeardays_month_days'] = date_prop.get_yeardays_daytype(
year_to_model=2015)
data['scenario_data'] = {}
data['scenario_data'][
'population'] = read_data.read_scenaric_population_data(
os.path.join(path_data_ed, 'model_run_pop'))
# --------------------------------------------
# Reading in results from different model runs
# --------------------------------------------
results_container = read_data.read_in_results(
data['result_paths']['data_results_model_run_results_txt'],
data['assumptions']['seasons'],
data['assumptions']['model_yeardays_daytype'])
# ------------------------------
# Plotting other results
# ------------------------------
plotting_results.run_all_plot_functions(
results_container,
data['assumptions']['reg_nrs'],
data['regions'],
data['lookups'],
data['result_paths'],
data['assumptions'],
data['enduses'],
plot_crit=plot_crit_dict,
base_yr=base_yr,
comparison_year=comparison_year)
# ------------------------------
# Plotting spatial results
# ------------------------------
if plot_crit_dict['spatial_results']:
result_mapping.spatial_maps(
data,
results_container,
data['result_paths']['data_results_shapefiles'],
data['regions'],
data['lookups']['fueltypes_nr'],
data['lookups']['fueltypes'],
path_shapefile_input,
plot_crit_dict,
base_yr=base_yr)
print("===================================")
print("... finished reading and plotting results")
print("===================================")