Minor improvements

.gitattributes

@@ -0,0 +1 @@
+*.ipynb linguist-vendored

CITATION.cff

@@ -24,5 +24,5 @@ keywords:
   - data-science
   - Python
 license: GPL-3.0
-version: 2.1.4
+version: 2.1.5
 date-released: 2025-11-17

docs/source/conf.py

@@ -8,7 +8,7 @@
 project = 'Hill Climber'
 copyright = '2025, Hill Climber Contributors'
 author = 'Hill Climber Contributors'
-release = '2.1.4'
+release = '2.1.5'
 
 # -- General configuration ---------------------------------------------------
 extensions = [

hill_climber/__init__.py

@@ -44,7 +44,7 @@
     >>> plot_optimization_results('checkpoint.pkl', all_replicas=True)
 """
 
-__version__ = '2.1.4'
+__version__ = '2.1.5'
 __author__ = 'gperdrizet'
 
 from .optimizer import HillClimber

hill_climber/dashboard_data.py

@@ -76,26 +76,27 @@ def load_metrics_history(
         return pd.DataFrame()
 
     try:
-        # Check total steps to determine if downsampling is needed
-        count_query = "SELECT MAX(step) as max_step FROM metrics_history"
-        result = pd.read_sql_query(count_query, conn)
-        if result.empty or result['max_step'].iloc[0] is None:
+        # Load all metrics for the requested metric names
+        placeholders = ','.join(['?' for _ in metric_names])
+        query = f"SELECT replica_id, step, metric_name, value FROM metrics_history WHERE metric_name IN ({placeholders}) ORDER BY replica_id, step, metric_name"
+        df = pd.read_sql_query(query, conn, params=metric_names)
+
+        if df.empty:
             return pd.DataFrame()
-
-        total_steps = int(result['max_step'].iloc[0])
 
-        # Build query with optional downsampling
-        if total_steps > max_points_per_replica:
-            step_interval = max(1, total_steps // max_points_per_replica)
-            query = f"SELECT replica_id, step, metric_name, value FROM metrics_history WHERE step % {step_interval} = 0"
-        else:
-            query = "SELECT replica_id, step, metric_name, value FROM metrics_history"
-
-        # Filter by requested metrics
-        placeholders = ','.join(['?' for _ in metric_names])
-        query += f" AND metric_name IN ({placeholders}) ORDER BY replica_id, step, metric_name"
+        # Downsample per replica to ensure all replicas are represented
+        # Group by replica_id and metric_name, then sample rows
+        downsampled_dfs = []
+        for (replica_id, metric_name), group in df.groupby(['replica_id', 'metric_name']):
+            if len(group) > max_points_per_replica:
+                # Sample evenly: keep every Nth row
+                step_size = len(group) / max_points_per_replica
+                indices = [int(i * step_size) for i in range(max_points_per_replica)]
+                downsampled_dfs.append(group.iloc[indices])
+            else:
+                downsampled_dfs.append(group)
 
-        return pd.read_sql_query(query, conn, params=metric_names)
+        return pd.concat(downsampled_dfs, ignore_index=True) if downsampled_dfs else pd.DataFrame()
     except Exception:
         return pd.DataFrame()
 

hill_climber/dashboard_plots.py

@@ -37,6 +37,21 @@ def create_replica_plot(
     Returns:
         go.Figure: Plotly Figure object with replica metrics plot.
     """
+    # Calculate total number of legend entries
+    total_metrics = 1 + len(additional_metrics)  # objective + additional
+    if show_exchanges:
+        total_metrics += 1  # add exchange marker
+
+    # Base height + additional height per metric (beyond 1)
+    base_height = 350
+    height_per_metric = 35
+    plot_height = base_height + (total_metrics - 1) * height_per_metric
+
+    # Calculate top margin based on number of metrics
+    base_top_margin = 90
+    margin_per_metric = 20
+    top_margin = base_top_margin + (total_metrics - 1) * margin_per_metric
+
     fig = make_subplots(specs=[[{"secondary_y": True}]])
 
     # Color palette
@@ -67,7 +82,7 @@ def create_replica_plot(
         fig.add_trace(
             go.Scatter(
                 x=batch_numbers, y=y_values, mode='lines', 
-                name=objective_metric, line=dict(color='#2E86AB', width=3),
+                name='Objective', line=dict(color='#2E86AB', width=3),
                 hovertemplate=hover_template, customdata=customdata
             ),
             secondary_y=False
@@ -124,7 +139,7 @@ def create_replica_plot(
                 go.Scatter(
                     x=[None], y=[None],
                     mode='lines',
-                    name='Temperature exchange',
+                    name='Exchange',
                     line=dict(color='#555', width=1, dash='dash'),
                     showlegend=True
                 ),
@@ -146,9 +161,9 @@ def create_replica_plot(
     fig.update_layout(
         title_text=title,
         title_font_size=20,
-        legend=dict(orientation='h', yanchor='bottom', y=-0.3),
-        margin=dict(l=40, r=20, t=40, b=70),
-        height=400
+        legend=dict(orientation='h', yanchor='bottom', y=1.02, xanchor='center', x=0.5),
+        margin=dict(l=40, r=20, t=top_margin, b=40),
+        height=plot_height
     )
 
     return fig

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "parallel-hill-climber"
-version = "2.1.4"
+version = "2.1.5"
 authors = [
     {name = "gperdrizet", email = "[email protected]"},
 ]