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cadCAD-v0.4.23-Model-Upgrade-Guide.md

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Feature ver. 0.4.23 ver. 0.3.1 (Deprecated)
Experiments 
from cadCAD.configuration import Experiment
exp = Experiment()
exp.append_configs(...) 
from cadCAD.configuration import append_configs
append_configs(…)
Local Execution Mode 
          
from cadCAD.engine import ExecutionMode, ExecutionContext
exec_mode = ExecutionMode()
local_ctx = ExecutionContext(context=exec_mode.local_mode)

Multi-Threaded

from cadCAD.engine import ExecutionMode, ExecutionContext
exec_mode = ExecutionMode()
single_ctx = ExecutionContext(context=exec_mode.multi_proc)

Single-Threaded

from cadCAD.engine import ExecutionMode, ExecutionContext
exec_mode = ExecutionMode()
multi_ctx = ExecutionContext(context=exec_mode.single_proc)
cadCAD Post-Processing Enhancements / Modifications 
import pandas as pd
from tabulate import tabulate
from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
import system_model_A, system_model_B
from cadCAD import configs
exec_mode = ExecutionMode()
local_ctx = ExecutionContext(context=exec_mode.local_mode)
simulation = Executor(exec_context=local_ctx, configs=configs)
raw_result, sys_model, _ = simulation.execute()
result = pd.DataFrame(raw_result)
print(tabulate(result, headers='keys', tablefmt='psql'))
 
import pandas as pd
from tabulate import tabulate
from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
import system_model_A, system_model_B
from cadCAD import configs
exec_mode = ExecutionMode()
multi_ctx = ExecutionContext(context=exec_mode.multi_proc)
simulation = Executor(exec_context=multi_ctx, configs=configs)
i = 0
config_names = ['sys_model_A', 'sys_model_B']
for raw_result, _ in simulation.execute():
result = pd.DataFrame(raw_result)
print()
print(f"{config_names[i]} Result: System Events DataFrame:")
print(tabulate(result, headers='keys', tablefmt='psql'))
print()
i += 1
Expandable state and policy update parameter 
def state_update(_params, substep, sH, s, _input, **kwargs):
…
return 'state_variable_name', new_value
def policy(_params, substep, sH, s, **kwargs):
…
return {'signal_1': value_1, …, 'signal_N': value_N}
   
     
def state_update(_params, substep, sH, s, _input):
…
return 'state_variable_name', new_value
def policy(_params, substep, sH, s):
…
return {'signal_1': value_1, …, 'signal_N': value_N}