186 lines
6.0 KiB
Python
186 lines
6.0 KiB
Python
import pandas as pd
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from fn.func import curried
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from datetime import timedelta
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import pprint as pp
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from cadCAD.utils import SilentDF #, val_switch
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from cadCAD.configuration import append_configs
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from cadCAD.configuration.utils import time_step, config_sim, var_trigger, var_substep_trigger, env_trigger, psub_list
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from cadCAD.configuration.utils.userDefinedObject import udoPipe, UDO
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from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
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from cadCAD import configs
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DF = SilentDF(pd.read_csv('/Users/jjodesty/Projects/DiffyQ-SimCAD/simulations/external_data/output.csv'))
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class udoExample(object):
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def __init__(self, x, dataset=None):
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self.x = x
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self.mem_id = str(hex(id(self)))
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self.ds = dataset # for setting ds initially or querying
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self.perception = {}
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def anon(self, f):
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return f(self)
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def updateX(self):
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self.x += 1
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return self
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def perceive(self, s):
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self.perception = self.ds[
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(self.ds['run'] == s['run']) & (self.ds['substep'] == s['substep']) & (self.ds['timestep'] == s['timestep'])
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].drop(columns=['run', 'substep']).to_dict()
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return self
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def read(self, ds_uri):
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self.ds = SilentDF(pd.read_csv(ds_uri))
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return self
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def write(self, ds_uri):
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pd.to_csv(ds_uri)
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# ToDo: Generic update function
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pass
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state_udo = UDO(udo=udoExample(0, DF), masked_members=['obj', 'perception'])
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policy_udoA = UDO(udo=udoExample(0, DF), masked_members=['obj', 'perception'])
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policy_udoB = UDO(udo=udoExample(0, DF), masked_members=['obj', 'perception'])
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sim_config = config_sim({
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"N": 2,
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"T": range(4)
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})
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# ToDo: DataFrame Column order
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state_dict = {
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'increment': 0,
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'state_udo': state_udo, 'state_udo_tracker': 0,
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'state_udo_perception_tracker': {"ds1": None, "ds2": None, "ds3": None, "timestep": None},
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'udo_policies': {'udo_A': policy_udoA, 'udo_B': policy_udoB},
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'udo_policy_tracker': (0, 0),
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'timestamp': '2019-01-01 00:00:00'
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}
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psu_steps = ['m1', 'm2', 'm3']
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system_substeps = len(psu_steps)
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var_timestep_trigger = var_substep_trigger([0, system_substeps])
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env_timestep_trigger = env_trigger(system_substeps)
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psu_block = {k: {"policies": {}, "variables": {}} for k in psu_steps}
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def udo_policyA(_g, step, sL, s):
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s['udo_policies']['udo_A'].updateX()
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return {'udo_A': udoPipe(s['udo_policies']['udo_A'])}
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# policies['a'] = udo_policyA
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for m in psu_steps:
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psu_block[m]['policies']['a'] = udo_policyA
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def udo_policyB(_g, step, sL, s):
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s['udo_policies']['udo_B'].updateX()
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return {'udo_B': udoPipe(s['udo_policies']['udo_B'])}
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# policies['b'] = udo_policyB
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for m in psu_steps:
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psu_block[m]['policies']['b'] = udo_policyB
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# policies = {"p1": udo_policyA, "p2": udo_policyB}
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# policies = {"A": udo_policyA, "B": udo_policyB}
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def add(y: str, added_val):
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return lambda _g, step, sL, s, _input: (y, s[y] + added_val)
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# state_updates['increment'] = add('increment', 1)
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for m in psu_steps:
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psu_block[m]["variables"]['increment'] = add('increment', 1)
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@curried
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def perceive(s, self):
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self.perception = self.ds[
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(self.ds['run'] == s['run']) & (self.ds['substep'] == s['substep']) & (self.ds['timestep'] == s['timestep'])
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].drop(columns=['run', 'substep']).to_dict()
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return self
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def state_udo_update(_g, step, sL, s, _input):
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y = 'state_udo'
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# s['hydra_state'].updateX().anon(perceive(s))
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s['state_udo'].updateX().perceive(s)
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x = udoPipe(s['state_udo'])
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return y, x
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for m in psu_steps:
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psu_block[m]["variables"]['state_udo'] = state_udo_update
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def track(destination, source):
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return lambda _g, step, sL, s, _input: (destination, s[source].x)
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state_udo_tracker = track('state_udo_tracker', 'state_udo')
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for m in psu_steps:
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psu_block[m]["variables"]['state_udo_tracker'] = state_udo_tracker
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def track_state_udo_perception(destination, source):
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def id(past_perception):
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if len(past_perception) == 0:
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return state_dict['state_udo_perception_tracker']
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else:
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return past_perception
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return lambda _g, step, sL, s, _input: (destination, id(s[source].perception))
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state_udo_perception_tracker = track_state_udo_perception('state_udo_perception_tracker', 'state_udo')
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for m in psu_steps:
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psu_block[m]["variables"]['state_udo_perception_tracker'] = state_udo_perception_tracker
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def view_udo_policy(_g, step, sL, s, _input):
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return 'udo_policies', _input
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for m in psu_steps:
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psu_block[m]["variables"]['udo_policies'] = view_udo_policy
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def track_udo_policy(destination, source):
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def val_switch(v):
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if isinstance(v, pd.DataFrame) is True or isinstance(v, SilentDF) is True:
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return SilentDF(v)
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else:
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return v.x
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return lambda _g, step, sL, s, _input: (destination, tuple(val_switch(v) for _, v in s[source].items()))
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udo_policy_tracker = track_udo_policy('udo_policy_tracker', 'udo_policies')
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for m in psu_steps:
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psu_block[m]["variables"]['udo_policy_tracker'] = udo_policy_tracker
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def update_timestamp(_g, step, sL, s, _input):
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y = 'timestamp'
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return y, time_step(dt_str=s[y], dt_format='%Y-%m-%d %H:%M:%S', _timedelta=timedelta(days=0, minutes=0, seconds=1))
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for m in psu_steps:
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psu_block[m]["variables"]['timestamp'] = var_timestep_trigger(y='timestamp', f=update_timestamp)
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# psu_block[m]["variables"]['timestamp'] = var_trigger(
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# y='timestamp', f=update_timestamp,
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# pre_conditions={'substep': [0, system_substeps]}, cond_op=lambda a, b: a and b
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# )
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# psu_block[m]["variables"]['timestamp'] = update_timestamp
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# ToDo: Bug without specifying parameters
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# New Convention
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partial_state_update_blocks = psub_list(psu_block, psu_steps)
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append_configs(
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sim_configs=sim_config,
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initial_state=state_dict,
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partial_state_update_blocks=partial_state_update_blocks
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)
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print()
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print("State Updates:")
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pp.pprint(partial_state_update_blocks)
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print()
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exec_mode = ExecutionMode()
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first_config = configs # only contains config1
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single_proc_ctx = ExecutionContext(context=exec_mode.single_proc)
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run = Executor(exec_context=single_proc_ctx, configs=first_config)
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