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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()
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