param sweep full spec: identity handling
This commit is contained in:
Joshua E. Jodesty
parent
368fcaa13d
commit
e78bfa3c8a
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@ -3,7 +3,7 @@ from fn.op import foldr
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import pandas as pd
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import pandas as pd
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from SimCAD import configs
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from SimCAD import configs
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from SimCAD.configuration.utils.parameterSweep import ParamSweep
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# from SimCAD.configuration.utils.parameterSweep import ParamSweep
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from SimCAD.utils import key_filter
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from SimCAD.utils import key_filter
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from SimCAD.configuration.utils.behaviorAggregation import dict_elemwise_sum
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from SimCAD.configuration.utils.behaviorAggregation import dict_elemwise_sum
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@ -57,17 +57,17 @@ class Identity:
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def __init__(self, behavior_id={'identity': 0}):
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def __init__(self, behavior_id={'identity': 0}):
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self.beh_id_return_val = behavior_id
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self.beh_id_return_val = behavior_id
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def b_identity(self, step, sL, s):
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def b_identity(self, var_dict, step, sL, s):
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return self.beh_id_return_val
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return self.beh_id_return_val
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def behavior_identity(self, k):
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def behavior_identity(self, k):
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return self.b_identity
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return self.b_identity
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def no_state_identity(self, step, sL, s, _input):
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def no_state_identity(self, var_dict, step, sL, s, _input):
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return None
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return None
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def state_identity(self, k):
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def state_identity(self, k):
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return lambda step, sL, s, _input: (k, s[k])
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return lambda var_dict, step, sL, s, _input: (k, s[k])
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def apply_identity_funcs(self, identity, df, cols):
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def apply_identity_funcs(self, identity, df, cols):
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def fillna_with_id_func(identity, df, col):
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def fillna_with_id_func(identity, df, col):
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@ -1,9 +1,4 @@
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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, flatten_tabulated_dict, tabulate_dict
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from SimCAD.utils import rename, flatten_tabulated_dict, tabulate_dict
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from SimCAD.configuration.utils import exo_update_per_ts
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def process_variables(d):
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def process_variables(d):
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@ -22,139 +17,3 @@ def config_sim(d):
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]
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]
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else:
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else:
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return d
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return d
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class ParamSweep:
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def __init__(self, sweep_list, mechs=None, raw_exogenous_states=None, _exo_update_per_ts=True):
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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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self._exo_update_per_ts = _exo_update_per_ts
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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, self._exo_update_per_ts)
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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_per_ts):
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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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def comp_exo_update(states_configs):
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return [exo_update_per_ts(x) if _exo_update_per_ts is True else x for x in states_configs]
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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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return comp_exo_update(states_configs)
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elif sweep_lists_len == 0:
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return comp_exo_update([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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