rename config: sweep_config

simulations/example_run.py

@@ -1,9 +1,8 @@
 import pandas as pd
 from tabulate import tabulate
-from importlib import reload
 # The following imports NEED to be in the exact order
 from SimCAD.engine import ExecutionMode, ExecutionContext, Executor
-from simulations.validation import config1 #, config2
+from simulations.validation import sweep_config
 
 from SimCAD import configs
 

simulations/validation/config2.py

@@ -1,171 +0,0 @@
-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
-
-
-seed = {
-    'z': np.random.RandomState(1),
-    'a': np.random.RandomState(2),
-    'b': np.random.RandomState(3),
-    'c': np.random.RandomState(3)
-}
-
-
-# Behaviors per Mechanism
-def b1m1(step, sL, s):
-    return {'param1': 1}
-def b2m1(step, sL, s):
-    return {'param2': 4}
-
-def b1m2(step, sL, s):
-    return {'param1': 'a', 'param2': 2}
-def b2m2(step, sL, s):
-    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
-exogenous_states = exo_update_per_ts(
-    {
-    "s3": es3p1,
-    "s4": es4p2,
-    "timestamp": es5p2
-    }
-)
-
-
-env_processes = {
-    "s3": proc_trigger('2018-10-01 15:16:25', env_a),
-    "s4": proc_trigger('2018-10-01 15:16:25', env_b)
-}
-
-
-mechanisms = {
-    "m1": {
-        "behaviors": {
-            "b1": b1m1,
-            # "b2": b2m1
-        },
-        "states": {
-            "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
-    )
-)