Create app.py

app.py

@@ -0,0 +1,52 @@
+import gradio as gr
+import networkx as nx
+import pydot
+import pandas as pd
+from io import BytesIO
+
+def calculate_parameters(file):
+    # Parse dot file using pydot
+    graphs = pydot.graph_from_dot_file(file.name)
+    G = nx.nx_pydot.from_pydot(graphs[0])
+
+    # Initialize the list of lengths and the node-to-index map
+    all_lengths = [0] * len(G.nodes())
+    node_to_index = {node: i for i, node in enumerate(G.nodes())}
+
+    # Calculate absolute depth (Dabs) and depth of each node
+    for node in nx.topological_sort(G):
+        if G.in_degree(node) > 0:  # This node has a predecessor
+            all_lengths[node_to_index[node]] = max(all_lengths[node_to_index[n]]+1 for n in G.predecessors(node))
+    Dabs = sum(all_lengths)
+
+    # Create node depth dictionary
+    node_depth = {node: all_lengths[node_to_index[node]] for node in G.nodes()}
+
+    # Calculate maximum depth (Dmax)
+    Dmax = max(all_lengths)
+
+    # Calculate average depth (Davg)
+    Davg = Dabs / len(all_lengths)
+
+    # Calculate absolute width (Wabs)
+    Wabs = len(G.nodes())
+
+    # Calculate maximum width (Wmax)
+    level_count = [all_lengths.count(i) for i in set(all_lengths)]
+    Wmax = max(level_count)
+
+    # Calculate average width (Wavg)
+    Wavg = Wabs / len(set(all_lengths))
+
+    # Create a DataFrame for node depths
+    df = pd.DataFrame.from_dict(node_depth, orient='index', columns=['Depth'])
+    node_depth_str = df.to_string()
+
+    result = f"Node Depths:\n{node_depth_str}\n\nFinal Calculations:\n"
+    result += f"Dabs = {Dabs}, Dmax = {Dmax}, Davg = {Davg:.3f}\n"
+    result += f"Wabs = {Wabs}, Wmax = {Wmax}, Wavg = {Wavg:.3f}"
+
+    return result
+
+iface = gr.Interface(fn=calculate_parameters, inputs="file", outputs="text")
+iface.launch()