import pandas as pd from tabulate import tabulate # The following imports NEED to be in the exact order from cadCAD.engine import ExecutionMode, ExecutionContext, Executor # from simulations.validation import config1_test_pipe # from simulations.validation import config1 from simulations.validation import write_simulation from cadCAD import configs exec_mode = ExecutionMode() first_config = configs # only contains config1 single_proc_ctx = ExecutionContext(context=exec_mode.single_proc) run = Executor(exec_context=single_proc_ctx, configs=first_config) raw_result, _ = run.main() result = pd.DataFrame(raw_result) result.to_csv('simulations/external_data/output.csv', index=False) print("Output:") print(tabulate(result, headers='keys', tablefmt='psql')) print()
import pandas as pd from tabulate import tabulate # The following imports NEED to be in the exact order from cadCAD.engine import ExecutionMode, ExecutionContext, Executor from cadCAD import configs exec_mode = ExecutionMode() print("Simulation Execution: Single Configuration") print() first_config = configs # only contains config1 single_proc_ctx = ExecutionContext(context=exec_mode.single_proc) run = Executor(exec_context=single_proc_ctx, configs=first_config) raw_result, tensor_field = run.main() result = pd.DataFrame(raw_result) print() print("Tensor Field: config1") print(tabulate(tensor_field, headers='keys', tablefmt='psql')) print("Output:") print(tabulate(result, headers='keys', tablefmt='psql')) print(result[['network']]) print() print(result[['network', 'substep']])
# The configurations above are then packaged into a `Configuration` object config = Configuration( initial_state= initial_conditions, #dict containing variable names and initial values partial_state_update_blocks= partial_state_update_blocks, #dict containing state update functions sim_config=simulation_parameters #dict containing simulation parameters ) # In[25]: exec_mode = ExecutionMode() exec_context = ExecutionContext(exec_mode.single_proc) executor = Executor(exec_context, [config]) # Pass the configuration object inside an array raw_result, tensor = executor.main( ) # The `main()` method returns a tuple; its first elements contains the raw results # In[26]: df = pd.DataFrame(raw_result) # In[172]: df.tail(5) # In[28]: df.supply.plot() # In[29]: