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f10431d24f
Improve reproducibility by documenting the steps needed to run the benchmarks and generate the plots. Also simplify plot generation a bit.
84 lines
2.3 KiB
Python
84 lines
2.3 KiB
Python
import sys
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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import scienceplots # noqa: F401
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plt.style.use(["science"])
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# Get CSV filenames from command line arguments
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if len(sys.argv) < 2:
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print("Usage: python script.py <csv_filename> [<csv_filename> ...]")
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sys.exit(1)
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csv_filenames = sys.argv[1:]
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# Output filename
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output_filename = "thread-scaling.pdf"
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# Read data from all CSV files and concatenate
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dfs = [pd.read_csv(filename) for filename in csv_filenames]
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df = pd.concat(dfs, ignore_index=True)
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# Filter for compute time = 0
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df_filtered = df[df["compute"] == 0].sort_values("threads")
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# Get unique systems and threads
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systems = df_filtered["system"].unique()
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threads = sorted(df_filtered["threads"].unique())
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# Create figure and axis
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fig, ax = plt.subplots(figsize=(10, 6))
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# Set up bar positions
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x_pos = np.arange(len(threads))
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bar_width = 0.35
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# Get colors from the current color cycle
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prop_cycle = plt.rcParams["axes.prop_cycle"]
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colors_list = prop_cycle.by_key()["color"]
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# Plot bars for each system
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for i, system in enumerate(systems):
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system_data = df_filtered[df_filtered["system"] == system].sort_values("threads")
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throughput = system_data["throughput"].tolist()
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offset = (i - len(systems)/2 + 0.5) * bar_width
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bars = ax.bar(x_pos + offset, throughput, bar_width,
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label=system,
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color=colors_list[i % len(colors_list)],
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edgecolor="black", linewidth=1.2)
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# Customize the plot
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ax.set_xlabel("Number of Threads", fontsize=14, fontweight="bold")
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ax.set_ylabel("Throughput (rows/sec)", fontsize=14, fontweight="bold")
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# Set y-axis to start from 0 with dynamic upper limit
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max_throughput = df_filtered["throughput"].max()
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ax.set_ylim(0, max_throughput * 1.15) # Add 15% tolerance for legend space
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# Format y-axis labels
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ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f"{int(x/1000)}k"))
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# Set x-axis ticks to show thread values
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ax.set_xticks(x_pos)
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ax.set_xticklabels(threads)
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# Add legend
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ax.legend(loc="upper left", frameon=True, fontsize=12)
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# Add grid for better readability
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ax.grid(axis="y", alpha=0.3, linestyle="--")
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ax.set_axisbelow(True)
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# Adjust layout
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plt.tight_layout()
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# Save the figure
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plt.savefig(output_filename, dpi=300, bbox_inches="tight")
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print(f"Saved plot to {output_filename}")
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# Display the plot
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plt.show()
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