File size: 1,138 Bytes
85e396d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 |
import gradio as gr
import matplotlib.pyplot as plt
import numpy as np
def stock_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)
plt.close()
return fig
iface = gr.Interface(
stock_forecast,
[
gr.inputs.Radio([2025, 2030, 2035, 2040], label="Project to:"),
gr.inputs.CheckboxGroup(["Google", "Microsoft", "Gradio"]),
gr.inputs.Slider(1, 100),
"checkbox",
gr.inputs.Dropdown(["cross", "line", "circle"], label="Style")],
gr.outputs.Image(plot=True, label="forecast"))
iface.test_launch()
if __name__ == "__main__":
iface.launch(inline=False) |