import gradio as gr from pyvis.network import Network import networkx as nx import numpy as np import pandas as pd import os from datasets import load_dataset from datasets import Features from datasets import Value from datasets import Dataset import matplotlib.pyplot as plt import re pattern = r'"(.*?)"' Secret_token = os.getenv('HF_token') dataset = load_dataset('FDSRashid/hadith_info',data_files = 'Basic_Edge_Information.csv', token = Secret_token, split = 'train') edge_info = dataset.to_pandas() features = Features({'Rawi ID': Value('int32'), 'Famous Name': Value('string'), 'Narrator Rank': Value('string'), 'Number of Narrations': Value('string')}) narrator_bios = load_dataset("FDSRashid/hadith_info", data_files = 'Teacher_Bios.csv', token = Secret_token,features=features ) narrator_bios = narrator_bios['train'].to_pandas() narrator_bios.loc[49845, 'Narrator Rank'] = 'رسول الله' narrator_bios.loc[49845, 'Number of Narrations'] = 0 narrator_bios['Number of Narrations'] = narrator_bios['Number of Narrations'].astype(int) narrator_bios.loc[49845, 'Number of Narrations'] = 443471 features = Features({'matn': Value('string'), 'taraf_ID': Value('string'), 'bookid_hadithid': Value('string')}) dataset = load_dataset("FDSRashid/hadith_info", data_files = 'All_Matns.csv',token = Secret_token, features = features) matn_info = dataset['train'].to_pandas() matn_info = matn_info.drop(97550) matn_info = matn_info.drop(307206) matn_info['taraf_ID'] = matn_info['taraf_ID'].replace('KeyAbsent', -1) matn_info['taraf_ID'] = matn_info['taraf_ID'].astype(int) isnad_info = load_dataset('FDSRashid/hadith_info',token = Secret_token, data_files = 'isnad_info.csv', split = 'train').to_pandas() isnad_info['Hadiths Cleaned'] = isnad_info['Hadiths'].apply(lambda x: [re.findall(pattern, string)[0].split("_") for string in x[1:-1].split(',')]) tarafs = np.max(matn_info['taraf_ID'].unique()) cmap = plt.colormaps['cool'] def value_to_hex(value): rgba_color = cmap(value) return "#{:02X}{:02X}{:02X}".format(int(rgba_color[0] * 255), int(rgba_color[1] * 255), int(rgba_color[2] * 255)) #edge_info, matn_info, narrator_bios, isnad_info def visualize_isnad(taraf_num, yaxis): taraf_hadith = matn_info[matn_info['taraf_ID'] == taraf_num]['bookid_hadithid'].to_list() taraf_hadith_split = [i.split('_') for i in taraf_hadith] hadith_cleaned = isnad_info['Hadiths Cleaned'].apply(lambda x: any(i in x for i in taraf_hadith_split) ) isnad_hadith = isnad_info[hadith_cleaned][['Source', 'Destination']] narrators = isnad_hadith.applymap(lambda x: narrator_bios[narrator_bios['Rawi ID'] == int(x)]['Famous Name'].to_list()).rename(columns={"Source": "Teacher", "Destination": "Student"}) isnad_hadith["Student"] = narrators['Student'] isnad_hadith["Teacher"] = narrators['Teacher'] filtered = isnad_hadith[(isnad_hadith['Teacher'].apply(lambda x: len(x)) == 1) & (isnad_hadith['Student'].apply(lambda x: len(x)) == 1)] filtered['Student'] = filtered['Student'].apply(lambda x: x[0]) filtered['Teacher'] = filtered['Teacher'].apply(lambda x: x[0]) net = Network(directed =True) for _, row in filtered.iterrows(): source = row['Teacher'] target = row['Student'] teacher_info = narrator_bios[narrator_bios['Rawi ID'] == int(row['Source'])] student_info = narrator_bios[narrator_bios['Rawi ID'] == int(row['Destination'])] isnad = isnad_info[(isnad_info['Source'] == row['Source']) & (isnad_info['Destination'] == row['Destination'])] teacher_narrations = teacher_info['Number of Narrations'].to_list()[0] student_narrations = student_info['Number of Narrations'].to_list()[0] if row['Source'] == '99999': net.add_node(source, font = {'size':50, 'color': 'Black'}, color = '#000000') else: net.add_node(source, font = {'size':30, 'color': 'red'}, color = value_to_hex(teacher_narrations), label = f'{source} \n {teacher_info["Narrator Rank"].to_list()[0]}') net.add_node(target, font = {'size': 30, 'color': 'red'}, color = value_to_hex(student_narrations), label = f'{target} \n{student_info["Narrator Rank"].to_list()[0]}') net.add_edge(source, target, color = value_to_hex(int(isnad['Hadith Count'].to_list()[0])), label = f"{isnad['Hadith Count'].to_list()[0]}") net.barnes_hut(gravity=-5000, central_gravity=0.3, spring_length=200) html = net.generate_html() html = html.replace("'", "\"") return f"""""" with gr.Blocks() as demo: Yaxis = gr.Dropdown(choices = ['Tarafs', 'Hadiths', 'Isnads', 'Books'], value = 'Tarafs', label = 'Variable to Display', info = 'Choose the variable to visualize.') taraf_number = gr.Slider(1,tarafs , value=10000, label="Taraf", info="Choose the Taraf to Input", step = 1) btn = gr.Button('Submit') btn.click(fn = visualize_isnad, inputs = [taraf_number, Yaxis], outputs = gr.HTML()) demo.launch()