Deployed 6a66208 with MkDocs version: 1.6.1

scripts/plots/analyze_comparisons.py

@@ -6,18 +6,17 @@ Rate, Distance Remaining).
 """
 
 import os
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
 
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
 from plot_config import (
-    COLORS,
-    apply_style,
-    BEST_PERFORMER_MARKER,
-    BEST_PERFORMER_TEXT,
     BEST_PERFORMER_COLOR,
-    create_common_parser,
+    BEST_PERFORMER_TEXT,
+    COLORS,
     LEGEND_KWARGS,
+    apply_style,
+    create_common_parser,
 )
 
 
@@ -84,7 +83,8 @@ def plot_grouped_bar(
 
     fig, ax = plt.subplots(figsize=figsize)
     bar_width = 0.35
-    x_indices = np.arange(len(morphologies))
+    group_spacing = 1.3
+    x_indices = np.arange(len(morphologies)) * group_spacing
     all_bars = {}
     all_means = []
 
@@ -118,7 +118,7 @@ def plot_grouped_bar(
         )
         all_bars[arch] = (x_pos, means, stds, bars)
 
-    for m_idx, m in enumerate(morphologies):
+    for m_idx, _ in enumerate(morphologies):
         m_means = {arch: all_bars[arch][1][m_idx] for arch in architectures}
         best_arch = (
             max(m_means, key=m_means.get) if higher_is_better else min(m_means, key=m_means.get)
@@ -144,12 +144,13 @@ def plot_grouped_bar(
 
     x_ticks_pos = (
         x_indices
+        + bar_width  # center the label in the 3 bars
         + (bar_width / 2 if len(architectures) % 2 == 0 else 0)
         - (bar_width / 2 if len(architectures) == 2 else 0)
     )
     ax.set_xticks(x_ticks_pos)
     ax.set_xticklabels([f"{m} Arms" for m in morphologies])
-    ax.tick_params(axis="x", pad=25)  # More padding for the squares
+    ax.tick_params(axis="x")  # More padding for the squares
 
     # X-axis at zero
     ax.axhline(0, color="black", linewidth=1.5)
@@ -172,20 +173,7 @@ def plot_grouped_bar(
             plt.FuncFormatter(lambda x, _: f"{x:.2f}" if abs(x) < 10 else f"{x:.0f}")
         )
 
-    _add_square_placeholders(ax, x_ticks_pos, [f"{m} Arms" for m in morphologies])
-
-    # Add custom legend entry for best performer
-    ax.plot(
-        [],
-        [],
-        marker=BEST_PERFORMER_MARKER,
-        color="w",
-        markerfacecolor=BEST_PERFORMER_COLOR,
-        markersize=15,
-        label="Best Performance",
-        ls="",
-    )
-    ax.legend(**LEGEND_KWARGS, ncol=len(architectures) + 1)
+    ax.legend(**LEGEND_KWARGS, ncol=len(architectures))
     ax.set_facecolor("white")
     fig.patch.set_facecolor("white")
 
@@ -305,22 +293,7 @@ def plot_grouped_bar_alt(
             plt.FuncFormatter(lambda x, _: f"{x:.2f}" if abs(x) < 10 else f"{x:.0f}")
         )
 
-    # In this alt plot, placeholders might be per architecture
-    _add_square_placeholders(
-        ax, x_indices, [arch.replace("_", "\n").title() for arch in architectures]
-    )
-
-    ax.plot(
-        [],
-        [],
-        marker=BEST_PERFORMER_MARKER,
-        color="w",
-        markerfacecolor=BEST_PERFORMER_COLOR,
-        markersize=15,
-        label="Best Performance",
-        ls="",
-    )
-    ax.legend(**LEGEND_KWARGS, ncol=len(morphologies) + 1)
+    ax.legend(**LEGEND_KWARGS, ncol=len(morphologies))
     ax.set_facecolor("white")
     fig.patch.set_facecolor("white")
 
@@ -358,8 +331,8 @@ if __name__ == "__main__":
         plot_grouped_bar(
             df=df,
             metric_col="approx_max_velocity",
-            ylabel="Max Forward Velocity (cm/s)",
-            title="Graceful Degradation: Velocity Across Morphologies",
+            ylabel="",
+            title="Maximal forward velocity (in cm/s)",
             output_filename="poster_plot_velocity.png",
             output_dir=OUTPUT_DIR,
             higher_is_better=True,