240 lines
6.3 KiB
Python
240 lines
6.3 KiB
Python
from copy import deepcopy, copy
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from datetime import timedelta
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from cadCAD.utils import UDC_Wrapper, objectview
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from cadCAD.configuration import append_configs
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from cadCAD.configuration.utils import ep_time_step, config_sim
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from typing import Dict, List, Any
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from collections import namedtuple
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# ToDo: Create member for past value
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class MyClassA(object):
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def __init__(self, x, class_id=None):
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self.class_id = class_id
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self.x = x
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print(f"Instance of MyClass (mem_id {hex(id(self))}) created with value {self.x}")
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def update(self):
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# self.past = copy(self)
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self.x += 1
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print(f"Instance of MyClass (mem_id {hex(id(self))}) has been updated, has now value {self.x}")
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return self.x #self #old_self #self.x
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def getMemID(self):
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return str(hex(id(self)))
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# can be accessed after an update within the same substep and timestep
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# ToDo: id sensitive to lineage, rerepresent
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def __str__(self):
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# return str(self.x)
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return f"{self.__class__.__name__} - {hex(id(self))} - {self.__dict__}"
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class MyClassB:
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def __init__(self, x):
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self.class_id = None
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self.x = x
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print(f"Instance of MyClass (mem_id {hex(id(self))}) created with value {self.x}")
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def update(self):
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# self.past = copy(self)
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self.x += 1
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print(f"Instance of MyClass (mem_id {hex(id(self))}) has been updated, has now value {self.x}")
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return self.x #self #old_self #self.x
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def getMemID(self):
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return str(hex(id(self)))
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# can be accessed after an update within the same substep and timestep
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# ToDo: id sensitive to lineage, rerepresent
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def __str__(self):
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# return str(self.x)
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return f"{hex(id(self))} - {self.x}"
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# a is Correct, and classX's value is Incorrect
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# Expected: a == classX's value
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# b should be tracking classX's value and a:
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# b should be the same value as the previous classX value and the previous a value
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# https://pymotw.com/2/multiprocessing/communication.html
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# ccc = MyClassA
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# udc = ccc(0)
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# print(MyClassA(**udc.__dict__).__dict__)
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g: Dict[str, List[MyClassA]] = {'udc': [MyClassA]}
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# udcB = MyClassB()
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# z = MyClass()
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# pointer(z)
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# separate thread/process for UCD with async calls to this thread/process
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# genesis state
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udc = MyClassA(0)
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# namedtuple("Hydra", self.hybrid_members.keys())(*self.hybrid_members.values())
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# udc_json = {'current': udc, 'past': udc}
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hydra = UDC_Wrapper(udc, udc, current_functions=['update'])
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hydra_members = hydra.get_hybrid_members()
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# hydra_obj = namedtuple("Hydra", hydra_members.keys())(*hydra_members.values())
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hydra_view = objectview(hydra_members)
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state_dict = {
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'a': 0,
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'b': 0,
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'i': 0,
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'j': 0,
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# 'k': 0,
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# "hydra": hydra,
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"hydra_members": hydra_members,
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# "hydra_obj": hydra_obj,
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# 'hydra_view': hydra_view,
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'timestamp': '2019-01-01 00:00:00'
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}
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timestep_duration = timedelta(minutes=1) # In this example, a timestep has a duration of 1 minute.
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ts_format = '%Y-%m-%d %H:%M:%S'
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def time_model(_g, step, sL, s, _input):
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y = 'timestamp'
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x = ep_time_step(s, dt_str=s['timestamp'], fromat_str=ts_format, _timedelta=timestep_duration)
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return (y, x)
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def Hydra(_g, step, sL, s, _input):
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y = 'hydra'
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x = s['hydra']
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return (y, x)
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def HydraMembers(_g, step, sL, s, _input):
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y = 'hydra_members'
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x = s['hydra_members'] #.get_hybrid_members()
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return (y, x)
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def HydraObj(_g, step, sL, s, _input):
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y = 'hydra_obj'
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# x = s['hydra_obj']
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# v = list(map(lambda x: copy(x), list(s['hydra_members'].values())))
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# hydra_members = s['hydra_members']
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# def generate_var_deepcopy(hydra_members):
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# for k, v in hydra_members.items():
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# if k == 'x':
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# yield k, deepcopy(v)
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# else:
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# yield k, v
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#
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# hydra_nt = namedtuple("Hydra", s['hydra_members'].keys())(*s['hydra_members'].values())
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# new_hydra = dict(generate_var_deepcopy(hydra_nt))
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# new_hydra_members = dict(generate_var_deepcopy(hydra_members))
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hm = copy(s['hydra_members'])
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x = namedtuple("Hydra", hm.keys())(*hm.values())
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# x = namedtuple("Hydra", new_hydra.keys())(*new_hydra.values())
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# print(x.x)
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return (y, x)
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def HydraView(_g, step, sL, s, _input):
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y = 'hydra_view'
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# x = objectview(s['hydra_members'])
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x = s['hydra_view'].update()
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return (y, x)
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def A(_g, step, sL, s, _input):
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y = 'a'
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x = s['a'] + 1
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return (y, x)
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def B(_g, step, sL, s, _input):
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y = 'b'
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x = s['hydra_members']['x']
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# x = s['hydra_view'].x
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# x = s['hydra_obj'].x
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return (y, x)
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def I(_g, step, sL, s, _input):
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y = 'i'
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x = s['hydra_members']['update']()
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# Either works
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# x = s['hydra_obj'].update()
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# x = s['hydra_view'].x
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return (y, x)
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def J(_g, step, sL, s, _input):
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y = 'j'
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x = s['hydra_members']['x']
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# x = s['hydra_members'].x
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# x = s['hydra_obj'].x
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# x = s['hydra_view'].x
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return (y, x)
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def K(_g, step, sL, s, _input):
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y = 'k'
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x = s['hydra_obj'].x
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# x = s['hydra_view'].x
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return (y, x)
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partial_state_update_blocks = {
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'PSUB1': {
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'behaviors': {
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},
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'states': {
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# 'ca': CA,
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'a': A,
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'b': B,
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# 'hydra': Hydra,
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'hydra_members': HydraMembers,
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# 'hydra_obj': HydraObj,
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# 'hydra_view': HydraView,
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'i': I,
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'j': J,
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# 'k': K,
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'timestamp': time_model,
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}
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},
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'PSUB2': {
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'behaviors': {
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},
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'states': {
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# 'ca': CA,
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'a': A,
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'b': B,
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# 'hydra': Hydra,
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'hydra_members': HydraMembers,
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# 'hydra_obj': HydraObj,
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# 'hydra_view': HydraView,
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'i': I,
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'j': J,
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# 'k': K,
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}
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},
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'PSUB3': {
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'behaviors': {
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},
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'states': {
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'a': A,
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'b': B,
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# 'hydra': Hydra,
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'hydra_members': HydraMembers,
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# 'hydra_obj': HydraObj,
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# 'hydra_view': HydraView,
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'i': I,
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'j': J,
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# 'k': K,
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}
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}
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}
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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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"M": g
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})
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append_configs(sim_config, state_dict, {}, {}, {}, partial_state_update_blocks)
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