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merge heaven: working

This commit is contained in:
Joshua E. Jodesty 2019-02-14 10:29:45 -05:00
parent 8d56cf2939
commit ed2f31cffc
5 changed files with 72 additions and 81 deletions
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1
SimCAD/configuration/utils/parameterSweep.py
View File

@ -16,4 +16,5 @@ def config_sim(d):
for M in process_variables(d["M"])
]
else:
d["M"] = [{}]
return d

1
SimCAD/engine/__init__.py
View File

@ -55,7 +55,6 @@ class Executor:
Ts.append(x.sim_config['T'])
Ns.append(x.sim_config['N'])
var_dict_list.append(x.sim_config['M'])
states_lists.append([x.state_dict])
eps.append(list(x.exogenous_states.values()))
configs_structs.append(config_proc.generate_config(x.state_dict, x.mechanisms, eps[config_idx]))

2
simulations/example_run.py
View File

@ -2,7 +2,7 @@ import pandas as pd
from tabulate import tabulate
# The following imports NEED to be in the exact order
from SimCAD.engine import ExecutionMode, ExecutionContext, Executor
from simulations.validation import sweep_config
from simulations.validation import config1, config2 # sweep_config
from SimCAD import configs
exec_mode = ExecutionMode()

74
simulations/validation/config1.py
View File

@ -2,10 +2,9 @@ from decimal import Decimal
import numpy as np
from datetime import timedelta
from SimCAD import configs
from SimCAD.configuration import Configuration
from SimCAD.configuration.utils import exo_update_per_ts, proc_trigger, bound_norm_random, \
ep_time_step
from SimCAD.configuration import append_configs
from SimCAD.configuration.utils import proc_trigger, bound_norm_random, ep_time_step
from SimCAD.configuration.utils.parameterSweep import config_sim
seed = {
@ -17,46 +16,46 @@ seed = {
# Behaviors per Mechanism
def b1m1(step, sL, s):
def b1m1(_g, step, sL, s):
return {'param1': 1}
def b2m1(step, sL, s):
def b2m1(_g, step, sL, s):
return {'param2': 4}
def b1m2(step, sL, s):
def b1m2(_g, step, sL, s):
return {'param1': 'a', 'param2': 2}
def b2m2(step, sL, s):
def b2m2(_g, step, sL, s):
return {'param1': 'b', 'param2': 4}
def b1m3(step, sL, s):
def b1m3(_g, step, sL, s):
return {'param1': ['c'], 'param2': np.array([10, 100])}
def b2m3(step, sL, s):
def b2m3(_g, step, sL, s):
return {'param1': ['d'], 'param2': np.array([20, 200])}
# Internal States per Mechanism
def s1m1(step, sL, s, _input):
def s1m1(_g, step, sL, s, _input):
y = 's1'
x = _input['param1']
return (y, x)
def s2m1(step, sL, s, _input):
def s2m1(_g, step, sL, s, _input):
y = 's2'
x = _input['param2']
return (y, x)
def s1m2(step, sL, s, _input):
def s1m2(_g, step, sL, s, _input):
y = 's1'
x = _input['param1']
return (y, x)
def s2m2(step, sL, s, _input):
def s2m2(_g, step, sL, s, _input):
y = 's2'
x = _input['param2']
return (y, x)
def s1m3(step, sL, s, _input):
def s1m3(_g, step, sL, s, _input):
y = 's1'
x = _input['param1']
return (y, x)
def s2m3(step, sL, s, _input):
def s2m3(_g, step, sL, s, _input):
y = 's2'
x = _input['param2']
return (y, x)
@ -66,19 +65,19 @@ def s2m3(step, sL, s, _input):
proc_one_coef_A = 0.7
proc_one_coef_B = 1.3
def es3p1(step, sL, s, _input):
def es3p1(_g, 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):
def es4p2(_g, 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):
def es5p2(_g, 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)
@ -103,14 +102,11 @@ genesis_states = {
}
# remove `exo_update_per_ts` to update every ts
exogenous_states = exo_update_per_ts(
{
raw_exogenous_states = {
"s3": es3p1,
"s4": es4p2,
"timestamp": es5p2
}
)
}
env_processes = {
@ -153,19 +149,19 @@ mechanisms = {
}
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
)
sim_config = config_sim(
{
"N": 2,
"T": range(5),
}
)
append_configs(
sim_configs=sim_config,
state_dict=genesis_states,
seed=seed,
raw_exogenous_states=raw_exogenous_states,
env_processes=env_processes,
mechanisms=mechanisms
)

75
simulations/validation/config2.py
View File

@ -2,11 +2,9 @@ from decimal import Decimal
import numpy as np
from datetime import timedelta
from SimCAD import configs
from SimCAD.configuration import Configuration
from SimCAD.configuration.utils import exo_update_per_ts, proc_trigger, bound_norm_random, \
ep_time_step
from SimCAD.configuration import append_configs
from SimCAD.configuration.utils import proc_trigger, bound_norm_random, ep_time_step
from SimCAD.configuration.utils.parameterSweep import config_sim
seed = {
'z': np.random.RandomState(1),
@ -17,46 +15,46 @@ seed = {
# Behaviors per Mechanism
def b1m1(step, sL, s):
def b1m1(_g, step, sL, s):
return {'param1': 1}
def b2m1(step, sL, s):
def b2m1(_g, step, sL, s):
return {'param2': 4}
def b1m2(step, sL, s):
def b1m2(_g, step, sL, s):
return {'param1': 'a', 'param2': 2}
def b2m2(step, sL, s):
def b2m2(_g, step, sL, s):
return {'param1': 'b', 'param2': 4}
def b1m3(step, sL, s):
def b1m3(_g, step, sL, s):
return {'param1': ['c'], 'param2': np.array([10, 100])}
def b2m3(step, sL, s):
def b2m3(_g, step, sL, s):
return {'param1': ['d'], 'param2': np.array([20, 200])}
# Internal States per Mechanism
def s1m1(step, sL, s, _input):
def s1m1(_g, step, sL, s, _input):
y = 's1'
x = _input['param1']
return (y, x)
def s2m1(step, sL, s, _input):
def s2m1(_g, step, sL, s, _input):
y = 's2'
x = _input['param2']
return (y, x)
def s1m2(step, sL, s, _input):
def s1m2(_g, step, sL, s, _input):
y = 's1'
x = _input['param1']
return (y, x)
def s2m2(step, sL, s, _input):
def s2m2(_g, step, sL, s, _input):
y = 's2'
x = _input['param2']
return (y, x)
def s1m3(step, sL, s, _input):
def s1m3(_g, step, sL, s, _input):
y = 's1'
x = _input['param1']
return (y, x)
def s2m3(step, sL, s, _input):
def s2m3(_g, step, sL, s, _input):
y = 's2'
x = _input['param2']
return (y, x)
@ -66,19 +64,19 @@ def s2m3(step, sL, s, _input):
proc_one_coef_A = 0.7
proc_one_coef_B = 1.3
def es3p1(step, sL, s, _input):
def es3p1(_g, 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):
def es4p2(_g, 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):
def es5p2(_g, 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)
@ -103,14 +101,11 @@ genesis_states = {
}
# remove `exo_update_per_ts` to update every ts
exogenous_states = exo_update_per_ts(
{
raw_exogenous_states = {
"s3": es3p1,
"s4": es4p2,
"timestamp": es5p2
}
)
}
env_processes = {
@ -153,19 +148,19 @@ mechanisms = {
}
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
)
sim_config = config_sim(
{
"N": 2,
"T": range(5),
}
)
append_configs(
sim_configs=sim_config,
state_dict=genesis_states,
seed=seed,
raw_exogenous_states=raw_exogenous_states,
env_processes=env_processes,
mechanisms=mechanisms
)