middle ground pt. 3
This commit is contained in:
Joshua E. Jodesty
parent
f9b3b1ea18
commit
c58f2d65a6
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@ -3,11 +3,12 @@ from decimal import Decimal
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from copy import deepcopy
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from fn.func import curried
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import pandas as pd
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import inspect
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from SimCAD.utils import rename
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from SimCAD.utils import dict_filter, contains_type, curry_pot
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from funcy import curry
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import pprint
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@ -125,104 +126,3 @@ def exo_update_per_ts(ep):
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return (y, s[y])
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return {es: ep_decorator(f, es) for es, f in ep.items()}
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def sweep(params, sweep_f):
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return [rename("sweep_"+sweep_f.__name__+"_"+str(i), curry(sweep_f)(param)) for param, i in zip(params, range(len(params)))]
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def zip_sweep_functions(sweep_lists):
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zipped_sweep_lists = []
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it = iter(sweep_lists)
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the_len = len(next(it))
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same_len_ind = all(len(l) == the_len for l in it)
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count_ind = len(sweep_lists) >= 2
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if same_len_ind == True and count_ind == True:
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return list(map(lambda x: list(x), list(zip(*sweep_lists))))
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elif same_len_ind == False or count_ind == False:
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return sweep_lists
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else:
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raise ValueError('lists have different lengths!')
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# ToDo: Not producing multiple dicts.
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def create_sweep_config_list(zipped_sweep_lists, states_dict, state_type_ind='mechs'):
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configs = []
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for f_lists in zipped_sweep_lists:
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new_states_dict = deepcopy(states_dict)
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for f_dict in f_lists:
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if state_type_ind == 'mechs':
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updates = list(f_dict.values()).pop()
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functs = list(updates.values()).pop()
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mech = list(f_dict.keys()).pop()
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update_type = list(updates.keys()).pop()
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sk = list(functs.keys()).pop()
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vf = list(functs.values()).pop()
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new_states_dict[mech][update_type][sk] = vf
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elif state_type_ind == 'exo_proc':
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sk = list(f_dict.keys()).pop()
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vf = list(f_dict.values()).pop()
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new_states_dict[sk] = vf
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else:
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raise ValueError("Incorrect \'state_type_ind\'")
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configs.append(new_states_dict)
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del new_states_dict
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return configs
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def parameterize_states(exo_states):
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# pp.pprint(exo_states)
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# print()
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sweep_lists = []
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for sk, vfs in exo_states.items():
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id_sweep_lists = []
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if isinstance(vfs, list):
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for vf in vfs:
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id_sweep_lists.append({sk: vf})
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if len(id_sweep_lists) != 0:
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sweep_lists.append(id_sweep_lists)
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if len(sweep_lists) == 0:
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return [exo_states]
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# pp.pprint(sweep_lists)
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# print()
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zipped_sweep_lists = zip_sweep_functions(sweep_lists)
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states_configs = create_sweep_config_list(zipped_sweep_lists, exo_states, "exo_proc")
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return states_configs
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def parameterize_mechanism(mechanisms):
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sweep_lists = []
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for mech, update_types in mechanisms.items():
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for update_type, fkv in update_types.items():
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for sk, vfs in fkv.items():
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id_sweep_lists = []
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if isinstance(vfs, list):
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for vf in vfs:
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id_sweep_lists.append({mech: {update_type: {sk: vf}}})
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if len(id_sweep_lists) != 0:
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sweep_lists.append(id_sweep_lists)
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if len(sweep_lists) == 0:
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return [mechanisms]
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zipped_sweep_lists = zip_sweep_functions(sweep_lists)
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mechanisms_configs = create_sweep_config_list(zipped_sweep_lists, mechanisms, "mechs")
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return mechanisms_configs
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# def ep_decorator(f, y, step, sL, s, _input):
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# if s['mech_step'] + 1 == 1:
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# return f(step, sL, s, _input)
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# else:
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# return (y, s[y])
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# return {es: ep_decorator(f, es) for es, f in ep.items()}
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@ -0,0 +1,148 @@
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import inspect
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from copy import deepcopy
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from funcy import curry
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from SimCAD.utils import rename
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from SimCAD.configuration.utils import exo_update_per_ts
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class ParamSweep:
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def __init__(self, sweep_list, mechs=None, raw_exogenous_states=None):
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self.sweep_list = sweep_list
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self.mechs = mechs
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self.raw_exogenous_states = raw_exogenous_states
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def mechanisms(self):
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swept_mechanisms = mech_sweep_identifier(self.sweep_list, self.mechs)
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return parameterize_mechanism(swept_mechanisms)
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def exogenous_states(self):
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swept_raw_exogenous_states = exo_sweep_identifier(self.sweep_list, self.raw_exogenous_states)
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return parameterize_states(swept_raw_exogenous_states)
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def sweep(params, sweep_f):
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return [
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rename("sweep_"+sweep_f.__name__+"_"+str(i), curry(sweep_f)(param))
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for param, i in zip(params, range(len(params)))
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]
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def mech_sweep_identifier(sweep_list, mechanisms):
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new_mechanisms = deepcopy(mechanisms)
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for mech, update_types in new_mechanisms.items():
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for update_type, fkv in update_types.items():
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for sk, current_f in fkv.items():
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current_f_arg_len = len(inspect.getfullargspec(current_f).args)
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if update_type == 'behaviors' and current_f_arg_len == 4:
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new_mechanisms[mech][update_type][sk] = sweep(sweep_list, current_f)
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elif update_type == 'states' and current_f_arg_len == 5:
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new_mechanisms[mech][update_type][sk] = sweep(sweep_list, current_f)
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del mechanisms
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return new_mechanisms
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def exo_sweep_identifier(sweep_list, exo_states):
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new_exo_states = deepcopy(exo_states)
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for sk, current_f in exo_states.items():
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current_f_arg_len = len(inspect.getfullargspec(current_f).args)
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if current_f_arg_len == 5:
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new_exo_states[sk] = sweep(sweep_list, current_f)
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del exo_states
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return new_exo_states
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def zip_sweep_functions(sweep_lists):
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zipped_sweep_lists = []
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it = iter(sweep_lists)
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the_len = len(next(it))
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same_len_ind = all(len(l) == the_len for l in it)
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count_ind = len(sweep_lists) >= 2
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if same_len_ind is True and count_ind is True:
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return list(map(lambda x: list(x), list(zip(*sweep_lists))))
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elif same_len_ind is False or count_ind is False:
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return sweep_lists
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else:
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raise ValueError('lists have different lengths!')
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# ToDo: Not producing multiple dicts.
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def create_sweep_config_list(zipped_sweep_lists, states_dict, state_type_ind='mechs'):
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configs = []
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for f_lists in zipped_sweep_lists:
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new_states_dict = deepcopy(states_dict)
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for f_dict in f_lists:
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if state_type_ind == 'mechs':
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updates = list(f_dict.values()).pop()
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functs = list(updates.values()).pop()
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mech = list(f_dict.keys()).pop()
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update_type = list(updates.keys()).pop()
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sk = list(functs.keys()).pop()
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vf = list(functs.values()).pop()
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new_states_dict[mech][update_type][sk] = vf
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elif state_type_ind == 'exo_proc':
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sk = list(f_dict.keys()).pop()
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vf = list(f_dict.values()).pop()
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new_states_dict[sk] = vf
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else:
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raise ValueError("Incorrect \'state_type_ind\'")
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configs.append(new_states_dict)
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del new_states_dict
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return configs
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def parameterize_states(exo_states, exo_update=exo_update_per_ts):
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# pp.pprint(exo_states)
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# print()
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sweep_lists = []
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for sk, vfs in exo_states.items():
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id_sweep_lists = []
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if isinstance(vfs, list):
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for vf in vfs:
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id_sweep_lists.append({sk: vf})
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if len(id_sweep_lists) != 0:
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sweep_lists.append(id_sweep_lists)
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sweep_lists_len = len(sweep_lists)
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if sweep_lists_len != 0:
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zipped_sweep_lists = zip_sweep_functions(sweep_lists)
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states_configs = create_sweep_config_list(zipped_sweep_lists, exo_states, "exo_proc")
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# pp.pprint(sweep_lists)
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# print()
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if exo_update == exo_update_per_ts:
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return list(map(exo_update_per_ts, states_configs))
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elif exo_update != exo_update_per_ts:
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return states_configs
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elif sweep_lists_len == 0 and exo_update == exo_update_per_ts:
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return list(map(exo_update_per_ts, [exo_states]))
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elif sweep_lists_len == 0 and exo_update != exo_update_per_ts:
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return [exo_states]
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def parameterize_mechanism(mechanisms):
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sweep_lists = []
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for mech, update_types in mechanisms.items():
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for update_type, fkv in update_types.items():
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for sk, vfs in fkv.items():
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id_sweep_lists = []
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if isinstance(vfs, list):
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for vf in vfs:
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id_sweep_lists.append({mech: {update_type: {sk: vf}}})
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if len(id_sweep_lists) != 0:
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sweep_lists.append(id_sweep_lists)
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if len(sweep_lists) == 0:
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return [mechanisms]
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zipped_sweep_lists = zip_sweep_functions(sweep_lists)
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mechanisms_configs = create_sweep_config_list(zipped_sweep_lists, mechanisms, "mechs")
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return mechanisms_configs
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@ -8,28 +8,28 @@ from SimCAD import configs
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exec_mode = ExecutionMode()
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print("Simulation Execution 1")
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print()
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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=first_config)
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run1_raw_result, tensor_field = run1.main()
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result = pd.DataFrame(run1_raw_result)
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print()
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print("Tensor Field:")
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print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
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print("Output:")
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print(tabulate(result, headers='keys', tablefmt='psql'))
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print()
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# print("Simulation Execution 1")
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# print()
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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=first_config)
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# run1_raw_result, tensor_field = run1.main()
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# result = pd.DataFrame(run1_raw_result)
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# print()
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# print("Tensor Field:")
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# print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
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# print("Output:")
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# print(tabulate(result, headers='keys', tablefmt='psql'))
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# print()
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# print("Simulation Execution 2: Pairwise Execution")
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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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# for raw_result, tensor_field in run2.main():
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# result = pd.DataFrame(raw_result)
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# print()
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# print("Tensor Field:")
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# print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
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# print("Output:")
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# print(tabulate(result, headers='keys', tablefmt='psql'))
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# print()
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print("Simulation Execution 2: Concurrent Execution")
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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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for raw_result, tensor_field in run2.main():
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result = pd.DataFrame(raw_result)
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print()
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print("Tensor Field:")
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print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
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print("Output:")
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print(tabulate(result, headers='keys', tablefmt='psql'))
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print()
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@ -5,11 +5,10 @@ import pprint
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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, parameterize_mechanism, parameterize_states, sweep
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from SimCAD.utils import rename
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from SimCAD.configuration.utils import proc_trigger, bound_norm_random, \
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ep_time_step
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from SimCAD.configuration.utils.parameterSweep import ParamSweep
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from fn.func import curried
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pp = pprint.PrettyPrinter(indent=4)
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@ -33,8 +32,8 @@ def b2m1(step, sL, s):
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return {'param2': 4}
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# @curried
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def b1m2(param, step, sL, s):
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return {'param1': 'a', 'param2': param}
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def b1m2(_beta, step, sL, s):
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return {'param1': 'a', 'param2': _beta}
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# @curried
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def b2m2(step, sL, s):
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return {'param1': 'b', 'param2': 0}
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@ -54,10 +53,16 @@ def s1m1(step, sL, s, _input):
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return (y, x)
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# @curried
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def s2m1(param, step, sL, s, _input):
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def s2m1(sweep_param, step, sL, s, _input):
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y = 's2'
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x = param
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x = sweep_param
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return (y, x)
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#
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# def s2m1(step, sL, s, _input):
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# y = 's2'
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# x = 0
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# return (y, x)
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# @curried
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def s1m2(step, sL, s, _input):
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y = 's1'
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@ -126,11 +131,10 @@ genesis_states = {
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# remove `exo_update_per_ts` to update every ts
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raw_exogenous_states = {
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"s3": sweep(beta, es3p1), #es3p1, #sweep(beta, es3p1),
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"s4": sweep(beta, es4p2),
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"s3": es3p1, #es3p1, #sweep(beta, es3p1),
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"s4": es4p2,
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"timestamp": es5p2
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}
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exogenous_states_list = list(map(exo_update_per_ts, parameterize_states(raw_exogenous_states)))
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# ToDo: make env proc trigger field agnostic
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@ -147,7 +151,7 @@ env_processes = {
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# pp.pprint(parameterized_env_processes)
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# exit()
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# ToDo: The number of values enteren in sweep should be the # of config objs created,
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# ToDo: The number of values entered in sweep should be the # of config objs created,
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# not dependent on the # of times the sweep is applied
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# sweep exo_state func and point to exo-state in every other funtion
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# param sweep on genesis states
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@ -155,98 +159,71 @@ env_processes = {
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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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#middleware(beta, [(m1, states, s2, s2m1), (m2, behaviors, b1, b1m2)], mechanisms)
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mechanisms_test = {
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mechanisms = {
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"m1": {
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"behaviors": {
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"b1": b1m1,#(0),
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"b2": b2m1#(0)
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"b1": b1m1,
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"b2": b2m1
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},
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"states": {
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"s1": s1m1,#(0),
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"s2": "sweep"
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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": "sweep",
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"b2": b2m2,#(0)
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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,#(0),
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"s2": s2m2#(0)
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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,#(0),
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"b2": b2m3,#(0)
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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,#(0),
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"s2": s2m3#(0)
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"s1": s1m3,
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"s2": s2m3
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
from copy import deepcopy
|
||||
from funcy import curry
|
||||
from inspect import getfullargspec
|
||||
|
||||
|
||||
def sweep_identifier(sweep_list, sweep_id_list, mechanisms):
|
||||
new_mechanisms = deepcopy(mechanisms)
|
||||
for x in sweep_id_list:
|
||||
current_f = new_mechanisms[x[0]][x[1]][x[2]]
|
||||
if current_f is 'sweep':
|
||||
new_mechanisms[x[0]][x[1]][x[2]] = sweep(sweep_list, x[3])
|
||||
|
||||
# for mech, update_types in new_mechanisms.items():
|
||||
# for update_type, fkv in update_types.items():
|
||||
# for sk, current_f in fkv.items():
|
||||
# if current_f != 'sweep' and isinstance(current_f, list) is False:
|
||||
# # new_mechanisms[mech][update_type][sk] = rename("unsweeped", current_f(0))
|
||||
# curried_f = curry(current_f)
|
||||
#
|
||||
# def uncurried_beh_func(a, b, c):
|
||||
# return curried_f(0)(a)(b)(c)
|
||||
#
|
||||
# def uncurried_state_func(a, b, c, d):
|
||||
# return curried_f(0)(a)(b)(c)(d)
|
||||
#
|
||||
# if update_type == 'behaviors':
|
||||
# new_mechanisms[mech][update_type][sk] = uncurried_beh_func
|
||||
# elif update_type == 'states':
|
||||
# new_mechanisms[mech][update_type][sk] = uncurried_state_func
|
||||
|
||||
del mechanisms
|
||||
return new_mechanisms
|
||||
|
||||
|
||||
sweep_id_list = [('m1', 'states', 's2', s2m1), ('m2', 'behaviors', 'b1', b1m2)]
|
||||
# pp.pprint(sweep_identifier(beta, sweep_id_list, mechanisms_test))
|
||||
# exit()
|
||||
|
||||
mechanisms = sweep_identifier(beta, sweep_id_list, mechanisms_test)
|
||||
|
||||
parameterized_mechanism = parameterize_mechanism(mechanisms)
|
||||
pp.pprint(parameterized_mechanism)
|
||||
# exit()
|
||||
# ToDo: inspect ****
|
||||
# ToDo: code block regenerator abstracted from user: input config module with params as convention, output it not as convention,
|
||||
|
||||
# ToDo: make ParamSweep a part of sim_config
|
||||
sim_config = {
|
||||
"N": 2,
|
||||
"T": range(5)
|
||||
# beta
|
||||
}
|
||||
|
||||
for mechanisms, exogenous_states in zip(parameterized_mechanism, exogenous_states_list):
|
||||
# beta = [1,2]
|
||||
# Test
|
||||
# def(beta, a, b, c):
|
||||
# return a + b + beta + beta
|
||||
|
||||
# ToDo: and/or, or not working
|
||||
# ToDo: Abstract ParamSweep away from user
|
||||
param_sweep = ParamSweep(
|
||||
sweep_list=beta,
|
||||
mechs=mechanisms,
|
||||
raw_exogenous_states=raw_exogenous_states
|
||||
)
|
||||
|
||||
# ToDo: Make loop standard by returning single elems from ParamSweep if sweep not specified
|
||||
for mechanisms, exogenous_states in zip(param_sweep.mechanisms(), param_sweep.exogenous_states()):
|
||||
configs.append(
|
||||
Configuration(
|
||||
sim_config=sim_config,
|
||||
state_dict=genesis_states,
|
||||
seed=seed,
|
||||
exogenous_states=exogenous_states, #parameterize_states(raw_exogenous_states)[1],
|
||||
exogenous_states=exogenous_states,
|
||||
env_processes=env_processes,
|
||||
mechanisms=mechanisms #parameterize_mechanism(mechanisms)[1]
|
||||
mechanisms=mechanisms
|
||||
)
|
||||
)
|
||||
|
|
|
|||
Loading…
Reference in New Issue