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import gradio as gr |
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from utils import initialize_gmm, generate_grid, generate_contours, generate_intermediate_points, plot_samples_and_contours, create_animation |
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import matplotlib.pyplot as plt |
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def visualize_gmm(mu_list, Sigma_list, pi_list, dx, dtheta, T, N): |
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gmm = initialize_gmm(mu_list, Sigma_list, pi_list) |
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grid_points = generate_grid(dx) |
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std_normal_contours = generate_contours(dtheta) |
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gmm_samples = gmm.sample(500) |
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intermediate_points = generate_intermediate_points(gmm, grid_points, std_normal_contours, gmm_samples, T, N) |
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fig1, ax1 = plot_samples_and_contours(gmm_samples, std_normal_contours, grid_points, "GMM Samples and Contours") |
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fig2, ax2 = plot_samples_and_contours(gmm_samples, std_normal_contours, grid_points, "Standard Normal Samples and Contours") |
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anim1 = create_animation(fig1, ax1, N, *intermediate_points[:3]) |
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anim2 = create_animation(fig2, ax2, N, *intermediate_points[3:]) |
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return fig1, fig2, anim1.to_jshtml(), anim2.to_jshtml() |
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demo = gr.Interface( |
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fn=visualize_gmm, |
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inputs=[ |
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gr.Textbox(label="Mu List", placeholder="Enter means as a list of lists, e.g., [[0,0], [1,1]]"), |
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gr.Textbox(label="Sigma List", placeholder="Enter covariances as a list of lists, e.g., [[[0.2, 0.1], [0.1, 0.3]], [[1.0, -0.1], [-0.1, 0.1]]]"), |
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gr.Textbox(label="Pi List", placeholder="Enter weights as a list, e.g., [0.5, 0.5]"), |
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gr.Slider(minimum=0.01, maximum=1.0, label="dx", default=0.1), |
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gr.Slider(minimum=0.01, maximum=0.1, label="dtheta", default=0.01), |
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gr.Slider(minimum=1, maximum=100, label="T", default=10), |
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gr.Slider(minimum=1, maximum=500, label="N", default=100) |
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], |
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outputs=[ |
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gr.Plot(label="GMM to Normal Flow"), |
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gr.Plot(label="Normal to GMM Flow"), |
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gr.HTML(label="GMM to Normal Animation"), |
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gr.HTML(label="Normal to GMM Animation") |
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], |
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live=True |
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) |
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demo.launch() |
