Refactoring ts_generator.py (adding link capacity class)

README.md

@@ -41,9 +41,10 @@ rng = MersenneTwisterRNG()
 ```
 
 Then perform the timeseries generation:
+
 ```python
 generator = ThermalDataGenerator(rng=rng, days=days)
-results = generator.generate_time_series(cluster, 1)
+results = generator.generate_time_series_for_clusters(cluster, 1)
 ```
 
 The actual timeseries for the total available power of the cluster are available in

src/antares/tsgen/cluster_import.py

@@ -14,7 +14,7 @@
 
 import numpy as np
 
-from .ts_generator import ProbabilityLaw, ThermalCluster
+from .ts_generator import ProbabilityLaw, ThermalCluster, OutageGenerationParameters
 
 
 def import_thermal_cluster(path: Path, days_per_year: int = 365) -> ThermalCluster:
@@ -24,18 +24,21 @@ def import_thermal_cluster(path: Path, days_per_year: int = 365) -> ThermalClust
     }
     array = np.genfromtxt(path, delimiter=",", dtype=str)
     hourly_modulation = np.tile(array[3][1 : 24 + 1].astype(int), 365)
-    return ThermalCluster(
+    outage_gen_params = OutageGenerationParameters(
         unit_count=int(array[1][1]),
-        nominal_power=float(array[2][1]),
-        modulation=hourly_modulation,
         fo_law=law_dict[array[4][1]],
         fo_volatility=float(array[5][1]),
         po_law=law_dict[array[6][1]],
         po_volatility=float(array[7][1]),
-        fo_duration=array[8][1 : days_per_year + 1].astype(int),
-        fo_rate=array[9][1 : days_per_year + 1].astype(float),
-        po_duration=array[10][1 : days_per_year + 1].astype(int),
-        po_rate=array[11][1 : days_per_year + 1].astype(float),
-        npo_min=array[12][1 : days_per_year + 1].astype(int),
-        npo_max=array[13][1 : days_per_year + 1].astype(int),
+        fo_duration=array[8][1: days_per_year + 1].astype(int),
+        fo_rate=array[9][1: days_per_year + 1].astype(float),
+        po_duration=array[10][1: days_per_year + 1].astype(int),
+        po_rate=array[11][1: days_per_year + 1].astype(float),
+        npo_min=array[12][1: days_per_year + 1].astype(int),
+        npo_max=array[13][1: days_per_year + 1].astype(int),
+    )
+    return ThermalCluster(
+        outage_gen_params,
+        nominal_power=float(array[2][1]),
+        modulation=hourly_modulation,
     )