Coverage for examples/OneRoom_CIA/predictor/simple_predictor.py: 100%

1import agentlib as al 

2import numpy as np 

3import pandas as pd 

4 

5 

6class PredictorModuleConfig(al.BaseModuleConfig): 

7 """Module that outputs a prediction of the heat load at a specified 

8 interval.""" 

9 outputs: al.AgentVariables = [ 

10 al.AgentVariable( 

11 name="r_pel", unit="ct/kWh", type="pd.Series", description="Weight for P_el in objective function" 

12 ), 

13 ] 

14 parameters: al.AgentVariables = [ 

15 al.AgentVariable( 

16 name="time_step", value=900, description="Sampling time for prediction." 

17 ), 

18 al.AgentVariable( 

19 name="prediction_horizon", 

20 value=8, 

21 description="Number of sampling points for prediction.", 

22 ) 

23 ] 

24 

25 shared_variable_fields: list[str] = ["outputs"] 

26 

27 

28class PredictorModule(al.BaseModule): 

29 """Module that outputs a prediction of the heat load at a specified 

30 interval.""" 

31 

32 config: PredictorModuleConfig 

33 

34 def register_callbacks(self): 

35 pass 

36 

37 def process(self): 

38 while True: 

39 sample_time = self.env.config.t_sample 

40 ts = self.get("time_step").value 

41 k = self.get("prediction_horizon").value 

42 now = self.env.now 

43 

44 grid = np.arange(now, now + k * ts + 1, sample_time) 

45 p_traj = pd.Series([1 for i in grid], index=list(grid)) 

46 self.set("r_pel", p_traj) 

47 

48 yield self.env.timeout(sample_time)