From 623983c61ee5ef00000c41e69111bb8b471f2c22 Mon Sep 17 00:00:00 2001
From: Mohamed feroz khan D <cb.en.p2cys21017@cb.students.amrita.edu>
Date: Thu, 6 Jul 2023 18:30:17 +0530
Subject: [PATCH] Python Program for Visualization
---
.../Visualization_without_UTC/visual.py | 121 ++++++++++++++++++
1 file changed, 121 insertions(+)
create mode 100644 Assets/Temporal_Graph/Bitcoin/Visualization/Visualization_without_UTC/visual.py
diff --git a/Assets/Temporal_Graph/Bitcoin/Visualization/Visualization_without_UTC/visual.py b/Assets/Temporal_Graph/Bitcoin/Visualization/Visualization_without_UTC/visual.py
new file mode 100644
index 0000000..de5af88
--- /dev/null
+++ b/Assets/Temporal_Graph/Bitcoin/Visualization/Visualization_without_UTC/visual.py
@@ -0,0 +1,121 @@
+import requests
+import pandas as pd
+import networkx as nx
+import matplotlib.pyplot as plt
+from datetime import datetime
+
+
+def fetch_address_data(address):
+ """
+ Function to fetch address data.
+
+ Parameters:
+ - address: The Bitcoin address to fetch data for.
+ """
+ url = f"https://blockchain.info/address/{address}?format=json"
+ response = requests.get(url)
+ data = response.json()
+ return data
+
+
+def transform_data(data):
+ """
+ Function to transform address data.
+
+ Parameters:
+ - data: The address data to transform.
+ """
+ transactions = []
+ for tx in data["txs"]:
+ for out in tx["out"]:
+ address_a = tx["inputs"][0]["prev_out"]["addr"]
+ address_b = out["addr"]
+ timestamp = datetime.fromtimestamp(tx["time"]).strftime("%m-%d-%Y %H:%M")
+ transaction_id = tx["hash"]
+ transaction = {
+ "Address A": address_a,
+ "Address B": address_b,
+ "Timestamp": timestamp,
+ "Transaction ID": transaction_id
+ }
+ transactions.append(transaction)
+ return transactions
+
+
+def export_to_excel(data, filename):
+ """
+ Function to export data to Excel.
+
+ Parameters:
+ - data: The data to export.
+ - filename: The name of the Excel file to export to.
+ """
+ df = pd.DataFrame(data)
+ df["Timestamp"] = pd.to_datetime(df["Timestamp"]) # Convert Timestamp column to datetime
+ df["Timestamp"] = df["Timestamp"].dt.strftime("%m-%d-%Y %H:%M") # Format Timestamp column
+ df.to_excel(filename, index=False)
+ print(f"Data exported to {filename}")
+
+
+def create_and_visualize_graph(df, user_addresses):
+ """
+ Function to create graph and visualize it.
+
+ Parameters:
+ - df: The DataFrame containing the transaction data.
+ - user_addresses: The list of user addresses.
+ """
+ graph = nx.DiGraph() # Create a networkx graph
+
+ for address in df['Address A'].unique():
+ if address in user_addresses:
+ graph.add_node(address, color='red') # Highlight user address nodes in red
+ else:
+ graph.add_node(address, color='skyblue')
+
+ for _, row in df.iterrows():
+ source = str(row['Address A'])
+ target = str(row['Address B'])
+ timestamp_str = str(row['Timestamp'])
+ transaction_hash = str(row['Transaction ID'])
+
+ if source in user_addresses or target in user_addresses:
+ graph.add_edge(source, target, color='blue') # Highlight edges connected to user address in blue
+ else:
+ graph.add_edge(source, target, color='gray')
+
+ plt.figure(figsize=(10, 6)) # Draw the graph using matplotlib
+ pos = nx.spring_layout(graph)
+ node_colors = [graph.nodes[node].get('color', 'skyblue') for node in graph.nodes]
+ edge_colors = [graph.edges[edge]['color'] for edge in graph.edges]
+
+ nx.draw_networkx(graph, pos, with_labels=True, node_size=500, font_size=8, node_color=node_colors, edge_color=edge_colors)
+
+ plt.tight_layout() # Show the graph
+ plt.show()
+
+
+def main():
+ """
+ Main program.
+ """
+ user_addresses = []
+ for i in range(4):
+ address = input(f"Enter address {i+1} of 4: ")
+ user_addresses.append(address)
+
+ all_transformed_data = []
+
+ for address in user_addresses:
+ address_data = fetch_address_data(address)
+ transformed_data = transform_data(address_data)
+ all_transformed_data.extend(transformed_data)
+
+ export_to_excel(all_transformed_data, "Data.xlsx")
+ df = pd.read_excel('Data.xlsx')
+
+ create_and_visualize_graph(df, user_addresses)
+
+
+if __name__ == "__main__":
+ main()
--
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