ncpus = 1 # default, unless otherwise specified in sbatch script
solver = '' # leave blank to let temoa decide which solver to use of those installed
iterations = 2
# =======================================================
# begin script
# =======================================================
try:
ncpus = int(os.getenv(
'NUM_PROCS')) # try to use variable defined in sbatch script
except:
ncpus = ncpus # otherwise default to this number of cores
# combine data files
tt.combine(project_path=project_path,
primary='data_virginia.xlsx',
data_files=['data_emerging_tech.xlsx', 'data_H2_VFB.xlsx'],
output='data_combined.xlsx')
# =======================================================
# Move modelInputs_XLSX to database
# =======================================================
modelInputs = tt.move_data_to_db(modelInputs_XLSX, path=project_path)
# =======================================================
# Create directories - best completed before using multiprocessing
# =======================================================
mc_dir = 'monte_carlo'
tt.create_dir(project_path=project_path, optional_dir=mc_dir)
# ====================================
# Perform Simulations
ncpus = ncpus # otherwise default to this number of cores
# iterate through base_data_files
for base_data_file, base_data_name in zip(base_data_files,
base_data_names):
# iterate through emission_inputs
for emission_input, emission_name in zip(emission_inputs,
emission_names):
# naming convention
combined_name = base_data_name + '_' + emission_name
combined_file = combined_name + '.xlsx'
# combine files
tt.combine(project_path=project_path,
primary=base_data_file,
data_files=[emission_input],
output=combined_file)
# =======================================================
# Move modelInputs_XLSX to database
# =======================================================
modelInputs = tt.move_data_to_db(combined_file, path=project_path)
# ====================================
# Perform Simulations
option = 2 # 1 - Run first, 2 - Run all
# ====================================
if option == 1:
# Perform single simulation
evaluateModel(modelInputs, scenario_inputs, scenario_names[0],
# iterate through emission_inputs
# =======================================================
for emission_input, emission_name in zip(emission_inputs, emission_names):
# naming convention
combined_name = emission_name
combined_file = combined_name + '.xlsx'
# files
files = [emission_input]
for modelInput in modelInputs_secondary:
if len(modelInput) > 0:
files.append(modelInput)
# combine files
tt.combine(project_path=project_path,
primary=modelInputs_primary,
data_files=files,
output=combined_file)
# =======================================================
# Move modelInputs_XLSX to database
# =======================================================
modelInputs = tt.move_data_to_db(combined_file, path=project_path)
# ====================================
# Perform Simulations
# ====================================
for monte_carlo_case in monte_carlo_cases:
for scenarioName, iterations in zip(scenarioNames, n_iterations):
# Create monte carlo cases
os.chdir(os.path.join(project_path, 'data'))
sensitivityMultiplier = 10.0 # percent perturbation
ncpus = 1 # default, unless otherwise specified in sbatch script
solver = '' # leave blank to let temoa decide which solver to use of those installed
# =======================================================
# begin script
# =======================================================
try:
ncpus = int(os.getenv(
'NUM_PROCS')) # try to use variable defined in sbatch script
except:
ncpus = ncpus # otherwise default to this number of cores
# combine data files
tt.combine(project_path=project_path,
primary=data_files[0],
data_files=data_files[1:],
output='data_combined_sensitivity.xlsx')
modelInputs_XLSX = 'data_combined_sensitivity.xlsx'
# =======================================================
# Move modelInputs_XLSX to database
# =======================================================
modelInputs = tt.move_data_to_db(modelInputs_XLSX, path=project_path)
# =======================================================
# Create directories - best completed before using multiprocessing
# =======================================================
sens_dir = 'sensitivity'
tt.create_dir(project_path=project_path, optional_dir=sens_dir)
# ====================================