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import ast |
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import os |
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from copy import deepcopy |
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import dhg |
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import gradio as gr |
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import matplotlib.pyplot as plt |
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import pandas as pd |
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from dhg.visualization.structure.defaults import (default_hypergraph_strength, |
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default_hypergraph_style, |
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default_size) |
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from dhg.visualization.structure.layout import force_layout |
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from dhg.visualization.structure.utils import draw_circle_edge, draw_vertex |
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from huggingface_hub import hf_hub_download |
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def draw_hypergraph( |
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hg: "dhg.Hypergraph", |
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e_style="circle", |
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v_label=None, |
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v_size=1.0, |
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v_color="r", |
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v_line_width=1.0, |
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e_color="gray", |
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e_fill_color="whitesmoke", |
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e_line_width=1.0, |
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font_size=1.0, |
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font_family="sans-serif", |
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push_v_strength=1.0, |
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push_e_strength=1.0, |
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pull_e_strength=1.0, |
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pull_center_strength=1.0, |
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): |
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fig, ax = plt.subplots(figsize=(6, 6)) |
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num_v, e_list = hg.num_v, deepcopy(hg.e[0]) |
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v_color, e_color, e_fill_color = default_hypergraph_style( |
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hg.num_v, hg.num_e, v_color, e_color, e_fill_color |
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) |
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v_size, v_line_width, e_line_width, font_size = default_size( |
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num_v, e_list, v_size, v_line_width, e_line_width |
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) |
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( |
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push_v_strength, |
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push_e_strength, |
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pull_e_strength, |
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pull_center_strength, |
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) = default_hypergraph_strength( |
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num_v, |
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e_list, |
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push_v_strength, |
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push_e_strength, |
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pull_e_strength, |
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pull_center_strength, |
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) |
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v_coor = force_layout( |
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num_v, |
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e_list, |
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push_v_strength, |
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push_e_strength, |
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pull_e_strength, |
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pull_center_strength, |
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) |
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draw_circle_edge( |
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ax, |
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v_coor, |
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v_size, |
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e_list, |
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e_color, |
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e_fill_color, |
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e_line_width, |
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) |
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draw_vertex( |
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ax, |
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v_coor, |
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v_label, |
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font_size, |
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font_family, |
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v_size, |
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v_color, |
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v_line_width, |
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) |
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plt.xlim((0, 1.0)) |
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plt.ylim((0, 1.0)) |
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plt.axis("off") |
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fig.tight_layout() |
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return fig |
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def plot_dataset(dataset_choice: str, sampling_choice: str, split_choice: str): |
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os.makedirs("artifacts", exist_ok=True) |
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hf_hub_download( |
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filename=f"processed/{sampling_choice}/{split_choice}_df.csv", |
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local_dir="./artifacts/", |
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repo_id=f"SauravMaheshkar/{dataset_choice}", |
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repo_type="dataset", |
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) |
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df = pd.read_csv(f"artifacts/processed/{sampling_choice}/{split_choice}_df.csv") |
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num_vertices = len(df) |
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edge_list = df["nodes"].values.tolist() |
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edge_list = [ast.literal_eval(edges) for edges in edge_list] |
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hypergraph = dhg.Hypergraph(num_vertices, edge_list) |
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fig = draw_hypergraph(hypergraph) |
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return fig |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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dataset_choices = gr.Dropdown( |
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choices=[ |
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"email-Eu", |
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"email-Enron", |
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"NDC-classes", |
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"tags-math-sx", |
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"email-Eu-25", |
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"NDC-substances", |
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"congress-bills", |
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"tags-ask-ubuntu", |
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"email-Enron-25", |
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"NDC-classes-25", |
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"threads-ask-ubuntu", |
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"contact-high-school", |
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"NDC-substances-25", |
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"congress-bills-25", |
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"contact-primary-school", |
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], |
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value="email-Enron-25", |
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label="Please choose a dataset", |
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interactive=True, |
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) |
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sampling_choice = gr.Dropdown( |
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choices=[ |
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"transductive", |
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"inductive", |
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], |
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value="inductive", |
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label="Choose sampling type", |
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interactive=True, |
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) |
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split_choice = gr.Dropdown( |
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choices=[ |
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"train", |
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"valid", |
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"test", |
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], |
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value="test", |
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label="Choose split", |
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interactive=True, |
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) |
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output_plot = gr.Plot(label="Hypergraph plot") |
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btn = gr.Button("Visualise") |
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btn.click( |
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fn=plot_dataset, |
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inputs=[dataset_choices, sampling_choice, split_choice], |
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outputs=output_plot, |
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) |
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demo.launch() |
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