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]: