Duplicate from johngoad/stock_forecast

Co-authored-by: JohnGoad <[email protected]>

.gitattributes

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README.md

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+---
+title: stock_forecast
+emoji: 🔥
+colorFrom: indigo
+colorTo: indigo
+sdk: gradio
+sdk_version: 3.3.1
+app_file: app.py
+pinned: false
+duplicated_from: johngoad/stock_forecast
+---

app.py

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+import matplotlib
+matplotlib.use('Agg')
+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"),
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+numpy
+matplotlib