Merge pull request #13 from BlockScience/jj-dev
Bug Fix: Can't use environments without proc_trigger
This commit is contained in:
commit
e3179a6e8e
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@ -46,9 +46,9 @@ exec_mode = ExecutionMode()
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print("Simulation Run 1")
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print()
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single_config = [configs[0]]
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first_config = [configs[0]] # from config1
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single_proc_ctx = ExecutionContext(context=exec_mode.single_proc)
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run1 = Executor(exec_context=single_proc_ctx, configs=single_config)
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run1 = Executor(exec_context=single_proc_ctx, configs=first_config)
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run1_raw_result = run1.main()
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result = pd.DataFrame(run1_raw_result)
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# result.to_csv('~/Projects/DiffyQ-SimCAD/results/config4csv', sep=',')
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@ -40,7 +40,6 @@ class Identity:
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class Processor:
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def __init__(self, id=Identity()):
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self.id = id
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self.b_identity = id.b_identity
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@ -65,7 +64,8 @@ class Processor:
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# Maybe Refactor to only use dictionary BUT I used dfs to fill NAs. Perhaps fill
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def generate_config(self, state_dict, mechanisms, exo_proc):
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# include False / False case
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# ToDo: include False / False case
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# ToDo: Use Range multiplier instead for loop iterator
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def no_update_handler(bdf, sdf):
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if (bdf.empty == False) and (sdf.empty == True):
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bdf_values = bdf.values.tolist()
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@ -88,7 +88,6 @@ class Processor:
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bdf_values = [[self.b_identity] * len(sdf_values)]
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return sdf_values, bdf_values
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# zipped_list = []
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if len(mechanisms) != 0:
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bdf = self.create_matrix_field(mechanisms, 'behaviors')
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sdf = self.create_matrix_field(mechanisms, 'states')
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@ -3,6 +3,7 @@ from decimal import Decimal
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from fn.func import curried
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import pandas as pd
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class TensorFieldReport:
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def __init__(self, config_proc):
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self.config_proc = config_proc
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@ -28,7 +28,6 @@ class ExecutionContext:
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l = list(zip(fs, states_list, configs, env_processes, Ts, Ns))
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with Pool(len(configs)) as p:
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results = p.map(lambda t: t[0](t[1], t[2], t[3], t[4], t[5]), l)
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return results
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if context == 'single_proc':
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@ -1,44 +1,45 @@
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from copy import deepcopy
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from fn.op import foldr, call
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import pprint
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pp = pprint.PrettyPrinter(indent=4)
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from SimCAD.utils import rename
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from SimCAD.engine.utils import engine_exception
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id_exception = engine_exception(KeyError, KeyError, None)
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class Executor:
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def __init__(self, behavior_ops):
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def __init__(self, behavior_ops, behavior_update_exception=id_exception, state_update_exception=id_exception):
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self.behavior_ops = behavior_ops
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self.state_update_exception = state_update_exception
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self.behavior_update_exception = behavior_update_exception
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# Data Type reduction
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def getBehaviorInput(self, step, sL, s, funcs):
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def get_behavior_input(self, step, sL, s, funcs):
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ops = self.behavior_ops[::-1]
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def getColResults(step, sL, s, funcs):
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def get_col_results(step, sL, s, funcs):
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return list(map(lambda f: f(step, sL, s), funcs))
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return foldr(call, getColResults(step, sL, s, funcs))(ops)
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return foldr(call, get_col_results(step, sL, s, funcs))(ops)
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def apply_env_proc(self, env_processes, state_dict, step):
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for state in state_dict.keys():
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if state in list(env_processes.keys()):
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state_dict[state] = env_processes[state](step)(state_dict[state])
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env_state = env_processes[state]
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if env_state.__name__ == '_curried': # might want to change
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state_dict[state] = env_state(step)(state_dict[state])
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else:
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state_dict[state] = env_state(state_dict[state])
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# remove / modify
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def exception_handler(self, f, m_step, sL, last_mut_obj, _input):
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try:
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return f(m_step, sL, last_mut_obj, _input)
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except KeyError:
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print("Exception")
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return f(m_step, sL, sL[-2], _input)
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def mech_step(self, m_step, sL, state_funcs, behavior_funcs, env_processes, t_step, run):
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last_in_obj = sL[-1]
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_input = self.getBehaviorInput(m_step, sL, last_in_obj, behavior_funcs)
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_input = self.state_update_exception(self.get_behavior_input(m_step, sL, last_in_obj, behavior_funcs))
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# print(sL)
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# *** add env_proc value here as wrapper function ***
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last_in_copy = dict([self.exception_handler(f, m_step, sL, last_in_obj, _input) for f in state_funcs])
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# ToDo: add env_proc generator to `last_in_copy` iterator as wrapper function
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last_in_copy = dict([self.behavior_update_exception(f(m_step, sL, last_in_obj, _input)) for f in state_funcs])
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for k in last_in_obj:
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if k not in last_in_copy:
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@ -46,7 +47,7 @@ class Executor:
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del last_in_obj
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# make env proc trigger field agnostic
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# make env proc trigger field agnostic
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self.apply_env_proc(env_processes, last_in_copy, last_in_copy['timestamp']) # mutating last_in_copy
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last_in_copy["mech_step"], last_in_copy["time_step"], last_in_copy['run'] = m_step, t_step, run
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@ -79,10 +80,7 @@ class Executor:
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time_seq = [x + 1 for x in time_seq]
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simulation_list = [states_list]
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for time_step in time_seq:
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# print(run)
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pipe_run = self.mech_pipeline(simulation_list[-1], configs, env_processes, time_step, run)
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# pp.pprint(pipe_run)
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# exit()
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_, *pipe_run = pipe_run
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simulation_list.append(pipe_run)
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@ -93,7 +91,6 @@ class Executor:
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pipe_run = []
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for run in range(runs):
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run += 1
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# print("Run: "+str(run))
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states_list_copy = deepcopy(states_list) # WHY ???
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head, *tail = self.block_pipeline(states_list_copy, configs, env_processes, time_seq, run)
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genesis = head.pop()
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@ -1,4 +1,5 @@
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from datetime import datetime
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from fn.func import curried
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def datetime_range(start, end, delta, dt_format='%Y-%m-%d %H:%M:%S'):
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@ -20,4 +21,21 @@ def last_index(l):
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def retrieve_state(l, offset):
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return l[last_index(l) + offset + 1]
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return l[last_index(l) + offset + 1]
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@curried
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def engine_exception(ErrorType, error_message, exception_function, try_function):
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try:
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return try_function
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except ErrorType:
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print(error_message)
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return exception_function
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# def exception_handler(f, m_step, sL, last_mut_obj, _input):
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# try:
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# return f(m_step, sL, last_mut_obj, _input)
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# except KeyError:
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# print("Exception")
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# return f(m_step, sL, sL[-2], _input)
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@ -1,14 +1,32 @@
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def print_fwd(x):
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# from fn.func import curried
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def pipe(x):
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return x
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def print_pipe(x):
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print(x)
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return x
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flatten = lambda l: [item for sublist in l for item in sublist]
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def flatten(l):
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return [item for sublist in l for item in sublist]
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def flatmap(f, items):
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return list(map(f, items))
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return list(map(f, items))
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def key_filter(l, keyname):
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return [v[keyname] for k, v in l.items()]
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return [v[keyname] for k, v in l.items()]
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# @curried
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def rename(new_name, f):
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f.__name__ = new_name
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return f
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#
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# def rename(newname):
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# def decorator(f):
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# f.__name__ = newname
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# return f
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# return decorator
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@ -4,6 +4,7 @@ from tabulate import tabulate
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# The following imports NEED to be in the exact same order
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from SimCAD.engine import ExecutionMode, ExecutionContext, Executor
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from simulations.validation import config1, config2
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# from simulations.validation import base_config1, base_config2
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# from simulations.barlin import config4
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# from simulations.zx import config_zx
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# from simulations.barlin import config6atemp #config6aworks,
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@ -14,18 +15,18 @@ from SimCAD import configs
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exec_mode = ExecutionMode()
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print("Simulation Run 1")
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print("Simulation Execution 1")
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print()
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single_config = [configs[0]]
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first_config = [configs[0]] # from config1
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single_proc_ctx = ExecutionContext(context=exec_mode.single_proc)
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run1 = Executor(exec_context=single_proc_ctx, configs=single_config)
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run1 = Executor(exec_context=single_proc_ctx, configs=first_config)
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run1_raw_result = run1.main()
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result = pd.DataFrame(run1_raw_result)
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# result.to_csv('~/Projects/DiffyQ-SimCAD/results/config4.csv', sep=',')
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print(tabulate(result, headers='keys', tablefmt='psql'))
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print()
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print("Simulation Run 2: Pairwise Execution")
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print("Simulation Execution 2: Pairwise Execution")
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print()
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multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)
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run2 = Executor(exec_context=multi_proc_ctx, configs=configs)
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@ -0,0 +1,171 @@
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from decimal import Decimal
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import numpy as np
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from datetime import timedelta
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from SimCAD import configs
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from SimCAD.configuration import Configuration
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from SimCAD.configuration.utils import exo_update_per_ts, proc_trigger, bound_norm_random, \
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ep_time_step
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seed = {
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'z': np.random.RandomState(1),
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'a': np.random.RandomState(2),
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'b': np.random.RandomState(3),
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'c': np.random.RandomState(3)
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}
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# Behaviors per Mechanism
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# Different return types per mechanism ?? *** No ***
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def b1m1(step, sL, s):
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return {'param1': 1}
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def b2m1(step, sL, s):
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return {'param1': 1}
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def b1m2(step, sL, s):
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return {'param1': 1, 'param2': 2}
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def b2m2(step, sL, s):
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return {'param1': 1, 'param2': 4}
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def b1m3(step, sL, s):
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return {'param1': 1, 'param2': np.array([10, 100])}
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def b2m3(step, sL, s):
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return {'param1': 1, 'param2': np.array([20, 200])}
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# deff not more than 2
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# Internal States per Mechanism
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def s1m1(step, sL, s, _input):
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y = 's1'
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x = s['s1'] + _input['param1']
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return (y, x)
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def s2m1(step, sL, s, _input):
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y = 's2'
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x = s['s2'] + _input['param1']
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return (y, x)
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def s1m2(step, sL, s, _input):
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y = 's1'
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x = s['s1'] + _input['param1']
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return (y, x)
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def s2m2(step, sL, s, _input):
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y = 's2'
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x = s['s2'] + _input['param1']
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return (y, x)
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def s1m3(step, sL, s, _input):
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y = 's1'
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x = s['s1'] + _input['param1']
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return (y, x)
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def s2m3(step, sL, s, _input):
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y = 's2'
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x = s['s2'] + _input['param1']
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return (y, x)
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# Exogenous States
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proc_one_coef_A = 0.7
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proc_one_coef_B = 1.3
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def es3p1(step, sL, s, _input):
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y = 's3'
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x = s['s3'] * bound_norm_random(seed['a'], proc_one_coef_A, proc_one_coef_B)
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return (y, x)
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def es4p2(step, sL, s, _input):
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y = 's4'
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x = s['s4'] * bound_norm_random(seed['b'], proc_one_coef_A, proc_one_coef_B)
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return (y, x)
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ts_format = '%Y-%m-%d %H:%M:%S'
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t_delta = timedelta(days=0, minutes=0, seconds=1)
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def es5p2(step, sL, s, _input):
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y = 'timestamp'
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x = ep_time_step(s, dt_str=s['timestamp'], fromat_str=ts_format, _timedelta=t_delta)
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return (y, x)
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# Environment States
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def env_a(x):
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return 10
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def env_b(x):
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return 10
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# def what_ever(x):
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# return x + 1
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# Genesis States
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genesis_states = {
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's1': Decimal(0.0),
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's2': Decimal(0.0),
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's3': Decimal(1.0),
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's4': Decimal(1.0),
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'timestamp': '2018-10-01 15:16:24'
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}
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# remove `exo_update_per_ts` to update every ts
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exogenous_states = exo_update_per_ts(
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{
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"s3": es3p1,
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"s4": es4p2,
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"timestamp": es5p2
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}
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)
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# make env proc trigger field agnostic
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# ToDo: Bug - Can't use environments without proc_trigger. TypeError: 'int' object is not callable
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# "/Users/jjodesty/Projects/DiffyQ-SimCAD/SimCAD/engine/simulation.py"
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env_processes = {
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# "s3": env_a,
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# "s4": env_b
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"s3": proc_trigger('2018-10-01 15:16:25', env_a),
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"s4": proc_trigger('2018-10-01 15:16:25', env_b)
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}
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# need at least 1 behaviour and 1 state function for the 1st mech with behaviors
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# mechanisms = {}
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mechanisms = {
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"m1": {
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"behaviors": {
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"b1": b1m1, # lambda step, sL, s: s['s1'] + 1,
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"b2": b2m1
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},
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"states": { # exclude only. TypeError: reduce() of empty sequence with no initial value
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"s1": s1m1,
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"s2": s2m1
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}
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},
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"m2": {
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"behaviors": {
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"b1": b1m2,
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"b2": b2m2
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},
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"states": {
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"s1": s1m2,
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"s2": s2m2
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}
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},
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"m3": {
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"behaviors": {
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"b1": b1m3,
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"b2": b2m3
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},
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"states": {
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"s1": s1m3,
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"s2": s2m3
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}
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}
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}
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sim_config = {
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"N": 2,
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"T": range(5)
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}
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configs.append(
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Configuration(
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sim_config=sim_config,
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state_dict=genesis_states,
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seed=seed,
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exogenous_states=exogenous_states,
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env_processes=env_processes,
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mechanisms=mechanisms
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)
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)
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@ -0,0 +1,180 @@
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from decimal import Decimal
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import numpy as np
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from datetime import timedelta
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from SimCAD import configs
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from SimCAD.configuration import Configuration
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from SimCAD.configuration.utils import exo_update_per_ts, proc_trigger, bound_norm_random, \
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ep_time_step
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seed = {
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'z': np.random.RandomState(1),
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'a': np.random.RandomState(2),
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'b': np.random.RandomState(3),
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'c': np.random.RandomState(3)
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}
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# Behaviors per Mechanism
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# Different return types per mechanism ?? *** No ***
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def b1m1(step, sL, s):
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return {'param1': 1}
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def b2m1(step, sL, s):
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return {'param2': 4}
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def b1m2(step, sL, s):
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return {'param1': 'a', 'param2': 2}
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def b2m2(step, sL, s):
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return {'param1': 'b', 'param2': 4}
|
||||
|
||||
|
||||
def b1m3(step, sL, s):
|
||||
return {'param1': ['c'], 'param2': np.array([10, 100])}
|
||||
def b2m3(step, sL, s):
|
||||
return {'param1': ['d'], 'param2': np.array([20, 200])}
|
||||
|
||||
|
||||
# Internal States per Mechanism
|
||||
def s1m1(step, sL, s, _input):
|
||||
y = 's1'
|
||||
x = _input['param1']
|
||||
return (y, x)
|
||||
def s2m1(step, sL, s, _input):
|
||||
y = 's2'
|
||||
x = _input['param2']
|
||||
return (y, x)
|
||||
|
||||
def s1m2(step, sL, s, _input):
|
||||
y = 's1'
|
||||
x = _input['param1']
|
||||
return (y, x)
|
||||
def s2m2(step, sL, s, _input):
|
||||
y = 's2'
|
||||
x = _input['param2']
|
||||
return (y, x)
|
||||
|
||||
def s1m3(step, sL, s, _input):
|
||||
y = 's1'
|
||||
x = _input['param1']
|
||||
return (y, x)
|
||||
def s2m3(step, sL, s, _input):
|
||||
y = 's2'
|
||||
x = _input['param2']
|
||||
return (y, x)
|
||||
|
||||
# Exogenous States
|
||||
proc_one_coef_A = 0.7
|
||||
proc_one_coef_B = 1.3
|
||||
|
||||
def es3p1(step, sL, s, _input):
|
||||
y = 's3'
|
||||
x = s['s3'] * bound_norm_random(seed['a'], proc_one_coef_A, proc_one_coef_B)
|
||||
return (y, x)
|
||||
|
||||
def es4p2(step, sL, s, _input):
|
||||
y = 's4'
|
||||
x = s['s4'] * bound_norm_random(seed['b'], proc_one_coef_A, proc_one_coef_B)
|
||||
return (y, x)
|
||||
|
||||
ts_format = '%Y-%m-%d %H:%M:%S'
|
||||
t_delta = timedelta(days=0, minutes=0, seconds=1)
|
||||
def es5p2(step, sL, s, _input):
|
||||
y = 'timestamp'
|
||||
x = ep_time_step(s, dt_str=s['timestamp'], fromat_str=ts_format, _timedelta=t_delta)
|
||||
return (y, x)
|
||||
|
||||
|
||||
# Environment States
|
||||
def env_a(x):
|
||||
return 10
|
||||
def env_b(x):
|
||||
return 10
|
||||
# def what_ever(x):
|
||||
# return x + 1
|
||||
|
||||
# Genesis States
|
||||
genesis_states = {
|
||||
's1': Decimal(0.0),
|
||||
's2': Decimal(0.0),
|
||||
's3': Decimal(1.0),
|
||||
's4': Decimal(1.0),
|
||||
'timestamp': '2018-10-01 15:16:24'
|
||||
}
|
||||
|
||||
# remove `exo_update_per_ts` to update every ts
|
||||
# why `exo_update_per_ts` here instead of `env_processes`
|
||||
exogenous_states = exo_update_per_ts(
|
||||
{
|
||||
"s3": es3p1,
|
||||
"s4": es4p2,
|
||||
"timestamp": es5p2
|
||||
}
|
||||
)
|
||||
|
||||
# make env proc trigger field agnostic
|
||||
env_processes = {
|
||||
"s3": proc_trigger('2018-10-01 15:16:25', env_a),
|
||||
"s4": proc_trigger('2018-10-01 15:16:25', env_b)
|
||||
}
|
||||
|
||||
# lambdas
|
||||
# genesis Sites should always be there
|
||||
# [1, 2]
|
||||
# behavior_ops = [ foldr(_ + _), lambda x: x + 0 ]
|
||||
|
||||
|
||||
# [1, 2] = {'b1': ['a'], 'b2', [1]} =
|
||||
# behavior_ops = [behavior_to_dict, print_fwd, sum_dict_values]
|
||||
# behavior_ops = [foldr(dict_elemwise_sum())]
|
||||
# behavior_ops = []
|
||||
|
||||
# need at least 1 behaviour and 1 state function for the 1st mech with behaviors
|
||||
# mechanisms = {}
|
||||
mechanisms = {
|
||||
"m1": {
|
||||
"behaviors": {
|
||||
"b1": b1m1, # lambda step, sL, s: s['s1'] + 1,
|
||||
# "b2": b2m1
|
||||
},
|
||||
"states": { # exclude only. TypeError: reduce() of empty sequence with no initial value
|
||||
"s1": s1m1,
|
||||
# "s2": s2m1
|
||||
}
|
||||
},
|
||||
"m2": {
|
||||
"behaviors": {
|
||||
"b1": b1m2,
|
||||
# "b2": b2m2
|
||||
},
|
||||
"states": {
|
||||
"s1": s1m2,
|
||||
# "s2": s2m2
|
||||
}
|
||||
},
|
||||
"m3": {
|
||||
"behaviors": {
|
||||
"b1": b1m3,
|
||||
"b2": b2m3
|
||||
},
|
||||
"states": {
|
||||
"s1": s1m3,
|
||||
"s2": s2m3
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
sim_config = {
|
||||
"N": 2,
|
||||
"T": range(5)
|
||||
}
|
||||
|
||||
configs.append(
|
||||
Configuration(
|
||||
sim_config=sim_config,
|
||||
state_dict=genesis_states,
|
||||
seed=seed,
|
||||
exogenous_states=exogenous_states,
|
||||
env_processes=env_processes,
|
||||
mechanisms=mechanisms
|
||||
)
|
||||
)
|
||||
|
|
@ -91,7 +91,7 @@ def env_b(x):
|
|||
# return x + 1
|
||||
|
||||
# Genesis States
|
||||
state_dict = {
|
||||
genesis_states = {
|
||||
's1': Decimal(0.0),
|
||||
's2': Decimal(0.0),
|
||||
's3': Decimal(1.0),
|
||||
|
|
@ -167,7 +167,7 @@ sim_config = {
|
|||
configs.append(
|
||||
Configuration(
|
||||
sim_config=sim_config,
|
||||
state_dict=state_dict,
|
||||
state_dict=genesis_states,
|
||||
seed=seed,
|
||||
exogenous_states=exogenous_states,
|
||||
env_processes=env_processes,
|
||||
|
|
|
|||
|
|
@ -93,7 +93,7 @@ def env_b(x):
|
|||
# return x + 1
|
||||
|
||||
# Genesis States
|
||||
state_dict = {
|
||||
genesis_states = {
|
||||
's1': Decimal(0.0),
|
||||
's2': Decimal(0.0),
|
||||
's3': Decimal(1.0),
|
||||
|
|
@ -171,7 +171,7 @@ sim_config = {
|
|||
configs.append(
|
||||
Configuration(
|
||||
sim_config=sim_config,
|
||||
state_dict=state_dict,
|
||||
state_dict=genesis_states,
|
||||
seed=seed,
|
||||
exogenous_states=exogenous_states,
|
||||
env_processes=env_processes,
|
||||
|
|
|
|||
Loading…
Reference in New Issue