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import gradio as gr |
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import matplotlib.pyplot as plt |
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import numpy as np |
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def stock_forecast(final_year, companies, noise, show_legend, point_style): |
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start_year = 2020 |
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x = np.arange(start_year, final_year + 1) |
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year_count = x.shape[0] |
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plt_format = ({"cross": "X", "line": "-", "circle": "o--"})[point_style] |
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fig = plt.figure() |
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ax = fig.add_subplot(111) |
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for i, company in enumerate(companies): |
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series = np.arange(0, year_count, dtype=float) |
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series = series ** 2 * (i + 1) |
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series += np.random.rand(year_count) * noise |
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ax.plot(x, series, plt_format) |
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if show_legend: |
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plt.legend(companies) |
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plt.close() |
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return fig |
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iface = gr.Interface( |
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stock_forecast, |
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[ |
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gr.inputs.Radio([2025, 2030, 2035, 2040], label="Project to:"), |
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gr.inputs.CheckboxGroup(["Google", "Microsoft", "Gradio"]), |
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gr.inputs.Slider(1, 100), |
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"checkbox", |
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gr.inputs.Dropdown(["cross", "line", "circle"], label="Style")], |
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gr.outputs.Image(plot=True, label="forecast")) |
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iface.test_launch() |
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if __name__ == "__main__": |
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iface.launch(inline=False) |