modify target reliability endpoint

src/calculation_target_reliability/service.py

@@ -95,7 +95,7 @@ from .utils import generate_down_periods
 
     # return filtered_aggregated_result
 
-def get_eaf_timeline(eaf_input: float, oh_session_id: str) -> List[dict]:
+def get_eaf_timeline(eaf_input: float, oh_session_id: str, oh_duration = 8000) -> List[dict]:
     """
     Generate a timeline of EAF values based on input parameters.
 
@@ -112,7 +112,7 @@ def get_eaf_timeline(eaf_input: float, oh_session_id: str) -> List[dict]:
 
     # Dummy OH session dates
     oh_session_start = datetime(2024, 1, 1)
-    oh_session_end = datetime(2025, 12, 30)
+    oh_session_end = oh_session_start + timedelta(hours=oh_duration)
 
     # Initialize result set
     results = []
@@ -130,30 +130,51 @@ def get_eaf_timeline(eaf_input: float, oh_session_id: str) -> List[dict]:
         start_date = oh_session_start
         end_date = oh_session_end - timedelta(days=180)
 
+    total_hours = (end_date - start_date).total_seconds() / 3600
+
     # Generate random down periods
-    down_periods = generate_down_periods(start_date, end_date, 5, min_duration=21, max_duration=90)
+    results = []
+
+    # Generate down periods for each EAF scenario
+    down_periods = {
+        'eaf1': generate_down_periods(start_date, end_date, 5, min_duration=1, max_duration=7),
+        'eaf2': generate_down_periods(start_date, end_date, 5, min_duration=1, max_duration=7),
+        'eaf3': generate_down_periods(start_date, end_date, 5, min_duration=1, max_duration=7),
+        'eaf4': generate_down_periods(start_date, end_date, 5, min_duration=1, max_duration=7)
+    }
+
+    # Define EAF values for downtime periods
+    eaf_downtime_values = {
+        'eaf1': 0.8,
+        'eaf2': 0.65,
+        'eaf3': 0.35,
+        'eaf4': 0
+    }
 
     # Generate daily entries
-    current_date = start_date
-    while current_date <= end_date:
-        # Convert date to string format
-        date_str = current_date.strftime('%Y-%m-%d')
-
-        # Set default EAF value to 1 (system up)
-        eaf_value = 1.0
-
-        # Check if current date is in any down period
-        for period_start, period_end in down_periods:
-            if period_start <= current_date <= period_end:
-                eaf_value = 0.8
+    current_time = start_date
+    while current_time <= end_date:
+        time_str = current_time.strftime('%Y-%m-%d %H:00:00')
+
+        # Initialize dictionary for this hour with default values (system up)
+        hourly_entry = {
+            'date': time_str,
+            'eaf1_value': 1.0,
+            'eaf2_value': 0.75,
+            'eaf3_value': 0.6,
+            'eaf4_value': 0.3
+        }
+
+        # Check each EAF scenario
+        for eaf_key in down_periods:
+            # Check if current hour is in any down period for this EAF
+            for period_start, period_end in down_periods[eaf_key]:
+                if period_start <= current_time <= period_end:
+                    hourly_entry[f'{eaf_key}_value'] = eaf_downtime_values[eaf_key]
                     break
 
-        # Add entry to timeline
-        results.append({
-            'date': date_str,
-            'eaf_value': eaf_value
-        })
+        results.append(hourly_entry)
+        current_time += timedelta(hours=1)
 
-        current_date += timedelta(days=1)
 
     return results