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Parent(s):
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Test App
Browse files
app.py
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import streamlit as st
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import streamlit as st
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import random
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import numpy as np
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from bokeh.plotting import figure
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from bokeh.embed import components
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from bokeh.models import ColumnDataSource, HoverTool
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def generate_interactive_plot_html():
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# Generar datos de ejemplo
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N = 10
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x = np.random.rand(N)
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y = np.random.rand(N)
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# Dos im谩genes de ejemplo codificadas en base64:
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red_image = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAF/wK+bNykAAAAAElFTkSuQmCC"
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blue_image = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mN8/f8/AwAI/AL+fB/9AAAAAElFTkSuQmCC"
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# Asignar a cada punto una imagen aleatoria y una etiqueta
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images = [random.choice([red_image, blue_image]) for _ in range(N)]
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labels = ["subset1" if img == red_image else "subset2" for img in images]
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# Crear el ColumnDataSource para Bokeh
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source = ColumnDataSource(data=dict(x=x, y=y, img=images, label=labels))
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# Crear la figura
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p = figure(title="Interactive Plot with Hover Images", tools="hover", width=600, height=600)
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p.scatter('x', 'y', size=15, source=source, fill_color="navy", alpha=0.5)
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# Configurar el HoverTool para mostrar la etiqueta e imagen
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hover = p.select_one(HoverTool)
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hover.tooltips = """
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<div>
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<div>
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<span style="font-size: 12px; font-weight: bold;">Label: @label</span>
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</div>
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<div>
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<img src="@img" alt="Image" style="width:100px;"/>
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</div>
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</div>
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"""
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# Obtener el script y el div del plot
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script, div = components(p)
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# Construir el HTML completo, incluyendo los recursos de BokehJS versi贸n 1.4.0
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html = f"""
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<html>
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<head>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bokehjs@1.4.0/build/css/bokeh.min.css" type="text/css">
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<script src="https://cdn.jsdelivr.net/npm/bokehjs@1.4.0/build/js/lib/bokeh.min.js"></script>
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</head>
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<body>
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{div}
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{script}
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</body>
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</html>
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"""
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return html
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# Genera el HTML del plot interactivo
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plot_html = generate_interactive_plot_html()
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# Usa el componente de Streamlit para incrustar el HTML sin sanitizaci贸n
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st.components.v1.html(plot_html, height=700)
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