Initial commit

research/paper_plot/disk_cache.py

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+import matplotlib
+from matplotlib.axes import Axes
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+from matplotlib.lines import Line2D
+
+# plt.rcParams["font.family"] = "Helvetica"
+plt.rcParams["ytick.direction"] = "in"
+plt.rcParams["hatch.linewidth"] = 1
+plt.rcParams["font.weight"] = "bold"
+plt.rcParams["axes.labelweight"] = "bold"
+plt.rcParams["text.usetex"] = True
+plt.rcParams["font.family"] = "sans-serif"  # Use generic sans-serif family
+plt.rcParams['text.latex.preamble'] = r"""
+\usepackage{helvet} % Use Helvetica font for text
+\usepackage{sfmath} % Use sans-serif font for math
+\renewcommand{\familydefault}{\sfdefault} % Set sans-serif as default text font
+\usepackage[T1]{fontenc} % Recommended for font encoding
+"""
+# plt.rcParams['mathtext.fontset'] = 'dejavusans'
+SAVE_PTH = "./paper_plot/figures"
+font_size = 16
+
+# New data in dictionary format
+datasets = ["NQ", "TriviaQA", "GPQA", "Hotpot"]
+
+cache_ratios = ["4.2G\n (0\%)", "8.7G\n (2.5\%)", "13.2G\n (5\%)", "18.6G\n (8\%)", "22.2G\n (10\%)"]
+latency_data = {
+    "NQ": [4.616, 4.133, 3.826, 3.511, 3.323],
+    "TriviaQA": [5.777, 4.979, 4.553, 4.141, 3.916],
+    "GPQA": [1.733, 1.593, 1.468, 1.336, 1.259],
+    "Hotpot": [15.515, 13.479, 12.383, 11.216, 10.606],
+}
+cache_hit_counts = {
+    "NQ": [0, 14.81, 23.36, 31.99, 36.73],
+    "TriviaQA": [0, 18.55, 27.99, 37.06, 41.86],
+    "GPQA": [0, 10.99, 20.31, 29.71, 35.01],
+    "Hotpot": [0, 17.47, 26.91, 36.2, 41.06]
+}
+
+# Create the figure with 4 subplots in a 2x2 grid
+fig, axes_grid = plt.subplots(2, 2, figsize=(7,6))
+axes = axes_grid.flatten()  # Flatten the 2x2 grid to a 1D array
+
+# Bar style settings
+width = 0.7
+x = np.arange(len(cache_ratios))
+
+# Define hatch patterns for different cache ratios
+hatch_patterns = ['//', '//', '//', '//', '//']
+
+# Find max cache hit value across all datasets for unified y-axis
+all_hit_counts = []
+for dataset in datasets:
+    all_hit_counts.extend(cache_hit_counts[dataset])
+max_unified_hit = max(all_hit_counts) * 1.13
+
+for i, dataset in enumerate(datasets):
+    latencies = latency_data[dataset]
+    hit_counts = cache_hit_counts[dataset]
+
+    for j, val in enumerate(latencies):
+        container = axes[i].bar(
+            x[j],
+            val,
+            width=width,
+            color="white",
+            edgecolor="black",
+            linewidth=1.0,
+            zorder=10,
+        )
+        axes[i].bar_label(
+            container,
+            [f"{val:.2f}"],
+            fontsize=10,
+            zorder=200,
+            fontweight="bold",
+        )
+
+    axes[i].set_title(dataset, fontsize=font_size)
+    axes[i].set_xticks(x)
+    axes[i].set_xticklabels(cache_ratios, fontsize=12, rotation=0, ha='center', fontweight="bold")
+
+    max_val_ratios = [1.35, 1.65, 1.45, 1.75]
+    max_val = max(latencies) * max_val_ratios[i]
+    axes[i].set_ylim(0, max_val)
+    axes[i].tick_params(axis='y', labelsize=12)
+
+    if i % 2 == 0:
+        axes[i].set_ylabel("Latency (s)", fontsize=font_size)
+        axes[i].yaxis.set_major_formatter(matplotlib.ticker.FormatStrFormatter('%.1f'))
+
+    ax2: Axes = axes[i].twinx()
+    ax2.plot(x, hit_counts,
+        linestyle='--',
+        marker='o',
+        markersize=6,
+        linewidth=1.5,
+        color='k',
+        markerfacecolor='none',
+        zorder=20)
+
+    ax2.set_ylim(0, max_unified_hit)
+    ax2.tick_params(axis='y', labelsize=12)
+    if i % 2 == 1:
+        ax2.set_ylabel(r"Cache Hit (\%)", fontsize=font_size)
+
+    for j, val in enumerate(hit_counts):
+        if val > 0:
+            ax2.annotate(f"{val:.1f}%",
+                         (x[j], val),
+                         textcoords="offset points",
+                         xytext=(0, 5),
+                         ha='center',
+                         va='bottom',
+                         fontsize=10,
+                         fontweight='bold')
+
+# Create legend for both plots
+bar_patch = mpatches.Patch(facecolor='white', edgecolor='black', label='Latency')
+line_patch = Line2D([0], [0], color='black', linestyle='--', label='Cache Hit Rate')
+
+# --- MODIFICATION FOR LEGEND AT THE TOP ---
+fig.legend(handles=[bar_patch, line_patch],
+           loc='upper center',        # Position the legend at the upper center
+           bbox_to_anchor=(0.5, 0.995), # Anchor point (0.5 means horizontal center of figure,
+                                      # 0.97 means 97% from the bottom, so near the top)
+           ncol=3,
+           fontsize=font_size-2)
+# --- END OF MODIFICATION ---
+
+# Set common x-axis label - you might want to add this back if needed
+# fig.text(0.5, 0.02, "Disk Cache Size", ha='center', fontsize=font_size, fontweight='bold') # Adjusted y for potential bottom label
+
+# --- MODIFICATION FOR TIGHT LAYOUT ---
+# Adjust rect to make space for the legend at the top.
+# (left, bottom, right, top_for_subplots)
+# We want subplots to occupy space from y=0 up to y=0.93 (or similar)
+# leaving the top portion (0.93 to 1.0) for the legend.
+plt.tight_layout(rect=(0, 0, 1, 0.93)) # Ensure subplots are below the legend
+# --- END OF MODIFICATION ---
+
+# Create directory if it doesn't exist (optional, good practice)
+import os
+if not os.path.exists(SAVE_PTH):
+    os.makedirs(SAVE_PTH)
+
+plt.savefig(f"{SAVE_PTH}/disk_cache_latency.pdf", dpi=300) # Changed filename slightly for testing
+print(f"Save to {SAVE_PTH}/disk_cache_latency.pdf")
+# plt.show() # Optional: to display the plot