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* changes * changes * revert changes * changes * add changeset * notebooks script * changes * changes --------- Co-authored-by: Ali Abid <aliabid94@gmail.com> Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> Co-authored-by: Ali Abdalla <ali.si3luwa@gmail.com>
36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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import gradio as gr
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def plot_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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return fig
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demo = gr.Interface(
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plot_forecast,
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[
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gr.Radio([2025, 2030, 2035, 2040], label="Project to:"),
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gr.CheckboxGroup(["Google", "Microsoft", "Gradio"], label="Company Selection"),
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gr.Slider(1, 100, label="Noise Level"),
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gr.Checkbox(label="Show Legend"),
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gr.Dropdown(["cross", "line", "circle"], label="Style"),
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],
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gr.Plot(label="forecast", format="png"),
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)
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if __name__ == "__main__":
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demo.launch()
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