| import matplotlib.pyplot as plt | |
| import numpy as np | |
| import gradio as gr | |
| def plot_forecast(final_year, companies, noise, show_legend, point_style): | |
| start_year = 2020 | |
| x = np.arange(start_year, final_year + 1) | |
| year_count = x.shape[0] | |
| plt_format = ({"cross": "X", "line": "-", "circle": "o--"})[point_style] | |
| fig = plt.figure() | |
| ax = fig.add_subplot(111) | |
| for i, company in enumerate(companies): | |
| series = np.arange(0, year_count, dtype=float) | |
| series = series**2 * (i + 1) | |
| series += np.random.rand(year_count) * noise | |
| ax.plot(x, series, plt_format) | |
| if show_legend: | |
| plt.legend(companies) | |
| return fig | |
| demo = gr.Interface( | |
| plot_forecast, | |
| [ | |
| gr.Radio([2025, 2030, 2035, 2040], label="Project to:"), | |
| gr.CheckboxGroup(["Google", "Microsoft", "Gradio"], label="Company Selection"), | |
| gr.Slider(1, 100, label="Noise Level"), | |
| gr.Checkbox(label="Show Legend"), | |
| gr.Dropdown(["cross", "line", "circle"], label="Style"), | |
| ], | |
| gr.Plot(label="forecast", format="png"), | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |