feat: add initial gradio app

.gitignore

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+**/.DS_Store
+
+.venv/
+artifacts/
+

app.py

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

requirements.txt

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+dhg
+gradio
+huggingface_hub
+matplotlib
+pandas