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43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import matplotlib.pyplot as plt
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import yaml
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from datetime import datetime
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from matplotlib import rc
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from imgcat import imgcat
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def plot_over_time(yaml_file):
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with open(yaml_file, 'r') as file:
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data = yaml.safe_load(file)
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dates = []
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pass_rates = []
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models = []
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for entry in data:
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if 'released' in entry and 'pass_rate_2' in entry:
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dates.append(entry['released'])
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pass_rates.append(entry['pass_rate_2'])
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models.append(entry['model'])
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plt.rcParams["hatch.linewidth"] = 0.5
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plt.rcParams["hatch.color"] = "#444444"
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rc("font", **{"family": "sans-serif", "sans-serif": ["Helvetica"], "size": 10})
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fig, ax = plt.subplots(figsize=(10, 4))
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ax.grid(axis="y", zorder=0, lw=0.2)
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colors = ['red' if 'gpt-4' in model else 'green' if 'gpt-3.5' in model else 'blue' for model in models]
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ax.scatter(dates, pass_rates, c=colors, alpha=0.5)
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for i, model in enumerate(models):
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ax.annotate(model, (dates[i], pass_rates[i]), fontsize=12, alpha=0.75,
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xytext=(5, 5), textcoords='offset points')
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ax.set_xlabel('Model release date')
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ax.set_ylabel('Aider code editing benchmark,\npercent completed correctly')
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ax.set_title('LLM code editing skill by model release date')
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plt.tight_layout()
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plt.savefig("tmp_over_time.png")
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imgcat(fig)
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# Example usage
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plot_over_time('_data/edit_leaderboard.yml')
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