import pprint from typing import Dict, List import pandas as pd from tabulate import tabulate from cadCAD.configuration import append_configs from cadCAD.configuration.utils import env_trigger, var_substep_trigger, config_sim, psub_list from cadCAD.engine import ExecutionMode, ExecutionContext, Executor from cadCAD import configs pp = pprint.PrettyPrinter(indent=4) def some_function(x): return x g: Dict[str, List[int]] = { 'alpha': [1], 'beta': [2, 5], 'gamma': [3, 4], 'omega': [some_function] } psu_steps = ['1', '2', '3'] system_substeps = len(psu_steps) var_timestep_trigger = var_substep_trigger([0, system_substeps]) env_timestep_trigger = env_trigger(system_substeps) env_process = {} # Policies def gamma(_params, step, sH, s): return {'gamma': _params['gamma']} def omega(_params, step, sH, s): return {'omega': _params['omega'](7)} # Internal States def alpha(_params, step, sH, s, _input): return 'alpha', _params['alpha'] def alpha_plus_gamma(_params, step, sH, s, _input): return 'alpha_plus_gamma', _params['alpha'] + _params['gamma'] def beta(_params, step, sH, s, _input): return 'beta', _params['beta'] def policies(_params, step, sH, s, _input): return 'policies', _input def sweeped(_params, step, sH, s, _input): return 'sweeped', {'beta': _params['beta'], 'gamma': _params['gamma']} genesis_states = { 'alpha_plus_gamma': 0, 'alpha': 0, 'beta': 0, 'policies': {}, 'sweeped': {} } env_process['sweeped'] = env_timestep_trigger(trigger_field='timestep', trigger_vals=[5], funct_list=[lambda _g, x: _g['beta']]) sim_config = config_sim( { "N": 2, "T": range(5), "M": g, } ) psu_block = {k: {"policies": {}, "variables": {}} for k in psu_steps} for m in psu_steps: psu_block[m]['policies']['gamma'] = gamma psu_block[m]['policies']['omega'] = omega psu_block[m]["variables"]['alpha'] = alpha_plus_gamma psu_block[m]["variables"]['alpha_plus_gamma'] = alpha psu_block[m]["variables"]['beta'] = beta psu_block[m]['variables']['policies'] = policies psu_block[m]["variables"]['sweeped'] = var_timestep_trigger(y='sweeped', f=sweeped) psubs = psub_list(psu_block, psu_steps) print() pp.pprint(psu_block) print() append_configs( sim_configs=sim_config, initial_state=genesis_states, env_processes=env_process, partial_state_update_blocks=psubs ) exec_mode = ExecutionMode() multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc) run = Executor(exec_context=multi_proc_ctx, configs=configs) for raw_result, tensor_field in run.execute(): result = pd.DataFrame(raw_result) print() print("Tensor Field:") print(tabulate(tensor_field, headers='keys', tablefmt='psql')) print("Output:") print(tabulate(result, headers='keys', tablefmt='psql')) print()