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40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
import gradio as gr
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import random
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import matplotlib.pyplot as plt
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import numpy as np
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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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plt.close()
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return fig
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iface = gr.Interface(plot_forecast,
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[
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gr.inputs.Radio([2025, 2030, 2035, 2040],
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label="Project to:"),
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gr.inputs.CheckboxGroup(
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["Google", "Microsoft", "Gradio"], label="Company Selection"),
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gr.inputs.Slider(1, 100, label="Noise Level"),
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gr.inputs.Checkbox(label="Show Legend"),
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gr.inputs.Dropdown(["cross", "line", "circle"], label="Style"),
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],
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gr.outputs.Image(plot=True, label="forecast")
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)
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if __name__ == "__main__":
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iface.launch()
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