use of config

Author: PhilippSchmelter

config.yml

@@ -3,3 +3,7 @@ input:
   timestamp_col: "Zeitstempel"
   value_col: "Messwert"
   factor: 4         # 15-min → kW depends on sampling
+
+model:
+  n_states: 10
+  laplace_alpha: 1.0

src/markov/__init__.py

@@ -2,10 +2,7 @@
 from .transition_counts import build_transition_counts
 from .transitions import build_transition_matrices
 
-N_STATES: int = 10
-
 __all__ = [
-    "N_STATES",
     "bucket_id",
     "NUM_BUCKETS",
     "build_transition_counts",

src/markov/_core.py

@@ -1,9 +1,12 @@
 import numpy as np
 import pandas as pd
 
-from . import N_STATES
+from src.config import CONFIG
+
 from .buckets import NUM_BUCKETS
 
+N_STATES = int(CONFIG["model"]["n_states"])
+
 
 def _transition_counts(
     df: pd.DataFrame, *, state_col="state", bucket_col="bucket", dtype=np.uint32

src/markov/transition_counts.py

@@ -1,9 +1,12 @@
 import numpy as np
 import pandas as pd
 
-from . import N_STATES
+from src.config import CONFIG
+
 from .buckets import NUM_BUCKETS
 
+N_STATES = int(CONFIG["model"]["n_states"])
+
 
 def build_transition_counts(
     df: pd.DataFrame,

src/markov/transitions.py

@@ -1,12 +1,14 @@
 import numpy as np
 import pandas as pd
 
+from src.config import CONFIG
+
 from ._core import _transition_counts
 
+alpha = float(CONFIG["model"]["laplace_alpha"])
+
 
-def build_transition_matrices(
-    df: pd.DataFrame, *, alpha: float = 1.0, dtype=np.float32
-) -> np.ndarray:
+def build_transition_matrices(df: pd.DataFrame, *, dtype=np.float32) -> np.ndarray:
     counts = _transition_counts(df, dtype=dtype)
     counts += alpha
     counts /= counts.sum(axis=2, keepdims=True)