Update app.py

app.py

@@ -1,4 +1,3 @@
-# app.py (fixed)
 import gradio as gr
 import pandas as pd
 import networkx as nx
@@ -6,9 +5,10 @@ import plotly.graph_objects as go
 import numpy as np
 from collections import defaultdict
 
-# ---------------------------
-# Data (same as before)
-# ---------------------------
+# ============================================================
+# DATA
+# ============================================================
+
 AMCS = [
     "SBI MF", "ICICI Pru MF", "HDFC MF", "Nippon India MF", "Kotak MF",
     "UTI MF", "Axis MF", "Aditya Birla SL MF", "Mirae MF", "DSP MF"
@@ -47,7 +47,7 @@ SELL_MAP = {
 }
 
 COMPLETE_EXIT = {
-    "DSP MF": ["Shriram Finance"],
+    "DSP MF": ["Shriram Finance"]
 }
 
 FRESH_BUY = {
@@ -56,17 +56,23 @@ FRESH_BUY = {
     "Mirae MF": ["HAL"]
 }
 
+
 def sanitize_map(m):
     out = {}
     for k, vals in m.items():
         out[k] = [v for v in vals if v in COMPANIES]
     return out
 
+
 BUY_MAP = sanitize_map(BUY_MAP)
 SELL_MAP = sanitize_map(SELL_MAP)
 COMPLETE_EXIT = sanitize_map(COMPLETE_EXIT)
 FRESH_BUY = sanitize_map(FRESH_BUY)
 
+# ============================================================
+# GRAPH BUILDING
+# ============================================================
+
 company_edges = []
 for amc, comps in BUY_MAP.items():
     for c in comps:
@@ -81,206 +87,296 @@ for amc, comps in FRESH_BUY.items():
     for c in comps:
         company_edges.append((amc, c, {"action": "fresh_buy", "weight": 3}))
 
+
 def infer_amc_transfers(buy_map, sell_map):
     transfers = defaultdict(int)
     company_to_sellers = defaultdict(list)
     company_to_buyers = defaultdict(list)
+
     for amc, comps in sell_map.items():
         for c in comps:
             company_to_sellers[c].append(amc)
+
     for amc, comps in buy_map.items():
         for c in comps:
             company_to_buyers[c].append(amc)
-    for c in set(list(company_to_sellers.keys()) + list(company_to_buyers.keys())):
-        sellers = company_to_sellers.get(c, [])
-        buyers = company_to_buyers.get(c, [])
+
+    for c in set(company_to_sellers.keys()) | set(company_to_buyers.keys()):
+        sellers = company_to_sellers[c]
+        buyers = company_to_buyers[c]
         for s in sellers:
             for b in buyers:
-                transfers[(s,b)] += 1
+                transfers[(s, b)] += 1
+
     edge_list = []
-    for (s,b), w in transfers.items():
-        edge_list.append((s,b, {"action": "transfer", "weight": w, "company_count": w}))
+    for (s, b), w in transfers.items():
+        edge_list.append((s, b, {"action": "transfer", "weight": w}))
     return edge_list
 
+
 transfer_edges = infer_amc_transfers(BUY_MAP, SELL_MAP)
 
+
 def build_graph(include_transfers=True):
     G = nx.DiGraph()
+
     for a in AMCS:
-        G.add_node(a, type="amc", label=a)
+        G.add_node(a, type="amc")
+
     for c in COMPANIES:
-        G.add_node(c, type="company", label=c)
-    for a, c, attrs in company_edges:
-        if not G.has_node(a) or not G.has_node(c):
-            continue
-        if G.has_edge(a,c):
-            G[a][c]["weight"] += attrs.get("weight",1)
-            G[a][c]["actions"].append(attrs["action"])
-        else:
-            G.add_edge(a, c, weight=attrs.get("weight",1), actions=[attrs["action"]])
-    if include_transfers:
-        for s,b,attrs in transfer_edges:
-            if not G.has_node(s) or not G.has_node(b):
-                continue
-            if G.has_edge(s,b):
-                G[s][b]["weight"] += attrs.get("weight",1)
-                G[s][b]["actions"].append("transfer")
+        G.add_node(c, type="company")
+
+    for u, v, attr in company_edges:
+        if u in G.nodes and v in G.nodes:
+            if G.has_edge(u, v):
+                G[u][v]["weight"] += attr["weight"]
+                G[u][v]["actions"].append(attr["action"])
             else:
-                G.add_edge(s, b, weight=attrs.get("weight",1), actions=["transfer"])
+                G.add_edge(u, v, weight=attr["weight"], actions=[attr["action"]])
+
+    if include_transfers:
+        for s, b, attr in transfer_edges:
+            if s in G.nodes and b in G.nodes:
+                if G.has_edge(s, b):
+                    G[s][b]["weight"] += attr["weight"]
+                    G[s][b]["actions"].append("transfer")
+                else:
+                    G.add_edge(s, b, weight=attr["weight"], actions=["transfer"])
+
     return G
 
-# ---------------------------
-# Visualization
-# ---------------------------
-def graph_to_plotly(G,
-                    node_color_amc="#9EC5FF",
-                    node_color_company="#FFCF9E",
-                    node_shape_amc="circle",
-                    node_shape_company="circle",
-                    edge_color_buy="#2ca02c",
-                    edge_color_sell="#d62728",
-                    edge_color_transfer="#888888",
-                    edge_thickness_base=1.2,
-                    show_labels=True):
+# ============================================================
+# PLOTLY NETWORK DRAWING
+# ============================================================
+
+
+def graph_to_plotly(
+        G,
+        node_color_amc="#9EC5FF",
+        node_color_company="#FFCF9E",
+        node_shape_amc="circle",
+        node_shape_company="circle",
+        edge_color_buy="#2ca02c",
+        edge_color_sell="#d62728",
+        edge_color_transfer="#888888",
+        edge_thickness_base=1.4,
+        show_labels=True
+):
     pos = nx.spring_layout(G, seed=42, k=1.2)
+
     node_x, node_y, node_text, node_color, node_size = [], [], [], [], []
+
     for n, d in G.nodes(data=True):
         x, y = pos[n]
-        node_x.append(x); node_y.append(y); node_text.append(n)
+        node_x.append(x)
+        node_y.append(y)
+        node_text.append(n)
+
         if d["type"] == "amc":
-            node_color.append(node_color_amc); node_size.append(40)
+            node_color.append(node_color_amc)
+            node_size.append(40)
         else:
-            node_color.append(node_color_company); node_size.append(60)
+            node_color.append(node_color_company)
+            node_size.append(60)
 
     node_trace = go.Scatter(
         x=node_x, y=node_y,
-        mode='markers+text' if show_labels else 'markers',
-        marker=dict(color=node_color, size=node_size, line=dict(width=2, color="#222")),
-        text=node_text if show_labels else None, textposition="top center", hoverinfo='text'
+        mode="markers+text" if show_labels else "markers",
+        marker=dict(
+            color=node_color,
+            size=node_size,
+            line=dict(width=2, color="#222")
+        ),
+        text=node_text if show_labels else None,
+        textposition="top center"
     )
 
     edge_traces = []
+
     for u, v, attrs in G.edges(data=True):
-        actions = attrs.get("actions",[])
-        weight = attrs.get("weight",1)
-        x0, y0 = pos[u]; x1, y1 = pos[v]
-        if "complete_exit" in actions:
-            color = edge_color_sell; dash = "solid"; width = max(edge_thickness_base * 3, 3)
-        elif "fresh_buy" in actions:
-            color = edge_color_buy; dash = "solid"; width = max(edge_thickness_base * 3, 3)
-        elif "transfer" in actions:
-            color = edge_color_transfer; dash = "dash"; width = max(edge_thickness_base * (1 + np.log1p(weight)), 1.5)
-        elif "sell" in actions:
-            color = edge_color_sell; dash = "dot"; width = max(edge_thickness_base * (1 + np.log1p(weight)), 1)
+        acts = attrs.get("actions", [])
+        weight = attrs.get("weight", 1)
+
+        x0, y0 = pos[u]
+        x1, y1 = pos[v]
+
+        if "complete_exit" in acts:
+            color = edge_color_sell
+            dash = "solid"
+            width = edge_thickness_base * 3
+        elif "fresh_buy" in acts:
+            color = edge_color_buy
+            dash = "solid"
+            width = edge_thickness_base * 3
+        elif "transfer" in acts:
+            color = edge_color_transfer
+            dash = "dash"
+            width = edge_thickness_base * (1 + np.log1p(weight))
+        elif "sell" in acts:
+            color = edge_color_sell
+            dash = "dot"
+            width = edge_thickness_base * (1 + np.log1p(weight))
         else:
-            color = edge_color_buy; dash = "solid"; width = max(edge_thickness_base * (1 + np.log1p(weight)), 1)
-        trace = go.Scatter(x=[x0, x1, None], y=[y0, y1, None],
-                           line=dict(width=width, color=color, dash=dash),
-                           hoverinfo='none', mode='lines')
-        edge_traces.append(trace)
-
-    fig = go.Figure(data=edge_traces + [node_trace],
-                    layout=go.Layout(showlegend=False, margin=dict(b=20,l=5,r=5,t=40),
-                                     xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
-                                     yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
-                                     height=900, width=1400))
+            color = edge_color_buy
+            dash = "solid"
+            width = edge_thickness_base * (1 + np.log1p(weight))
+
+        edge_traces.append(
+            go.Scatter(
+                x=[x0, x1, None],
+                y=[y0, y1, None],
+                mode="lines",
+                line=dict(color=color, width=width, dash=dash),
+                hoverinfo="none"
+            )
+        )
+
+    fig = go.Figure(data=edge_traces + [node_trace])
+    fig.update_layout(
+        showlegend=False,
+        height=900,
+        width=1400,
+        margin=dict(l=5, r=5, t=40, b=20),
+        xaxis=dict(visible=False),
+        yaxis=dict(visible=False)
+    )
     return fig
 
-# ---------------------------
-# Analysis helpers
-# ---------------------------
+# ============================================================
+# COMPANY & AMC INSPECTION
+# ============================================================
+
+
 def company_trade_summary(company_name):
-    buyers = [amc for amc, comps in BUY_MAP.items() if company_name in comps]
-    sellers = [amc for amc, comps in SELL_MAP.items() if company_name in comps]
-    fresh = [amc for amc, comps in FRESH_BUY.items() if company_name in comps]
-    exits = [amc for amc, comps in COMPLETE_EXIT.items() if company_name in comps]
+    buyers = [a for a, comps in BUY_MAP.items() if company_name in comps]
+    sellers = [a for a, comps in SELL_MAP.items() if company_name in comps]
+    fresh = [a for a, comps in FRESH_BUY.items() if company_name in comps]
+    exits = [a for a, comps in COMPLETE_EXIT.items() if company_name in comps]
+
     df = pd.DataFrame({
-        "Role": ["Buyer"]*len(buyers) + ["Seller"]*len(sellers) + ["Fresh buy"]*len(fresh) + ["Complete exit"]*len(exits),
+        "Role": ["Buyer"] * len(buyers) + ["Seller"] * len(sellers)
+                + ["Fresh buy"] * len(fresh) + ["Complete exit"] * len(exits),
         "AMC": buyers + sellers + fresh + exits
     })
+
     if df.empty:
-        return None, pd.DataFrame([], columns=["Role","AMC"])
+        return None, pd.DataFrame([], columns=["Role", "AMC"])
+
     counts = df.groupby("Role").size().reset_index(name="Count")
-    fig = go.Figure(go.Bar(x=counts["Role"], y=counts["Count"], marker_color=["green","red","orange","black"][:len(counts)]))
-    fig.update_layout(title_text=f"Trade summary for {company_name}", height=300, width=600)
+
+    fig = go.Figure(go.Bar(
+        x=counts["Role"],
+        y=counts["Count"],
+        marker_color=["green", "red", "orange", "black"][:len(counts)]
+    ))
+    fig.update_layout(
+        title_text=f"Trade summary for {company_name}",
+        height=300
+    )
     return fig, df
 
+
 def amc_transfer_summary(amc_name):
     sold = SELL_MAP.get(amc_name, [])
     transfers = []
+
     for s in sold:
-        buyers = [amc for amc, comps in BUY_MAP.items() if s in comps]
+        buyers = [a for a, comps in BUY_MAP.items() if s in comps]
         for b in buyers:
             transfers.append({"security": s, "buyer_amc": b})
+
     df = pd.DataFrame(transfers)
+
     if df.empty:
-        return None, pd.DataFrame([], columns=["security","buyer_amc"])
-    counts = df['buyer_amc'].value_counts().reset_index()
-    counts.columns = ['Buyer AMC', 'Count']
-    fig = go.Figure(go.Bar(x=counts['Buyer AMC'], y=counts['Count'], marker_color='lightslategray'))
-    fig.update_layout(title_text=f"Inferred transfers from {amc_name}", height=300, width=600)
+        return None, pd.DataFrame([], columns=["security", "buyer_amc"])
+
+    counts = df["buyer_amc"].value_counts().reset_index()
+    counts.columns = ["Buyer AMC", "Count"]
+
+    fig = go.Figure(go.Bar(
+        x=counts["Buyer AMC"],
+        y=counts["Count"],
+        marker_color="lightslategray"
+    ))
+    fig.update_layout(
+        title_text=f"Inferred transfers from {amc_name}",
+        height=300
+    )
     return fig, df
 
-# Build an initial figure (no transfers by default)
-initial_G = build_graph(include_transfers=True)
-initial_fig = graph_to_plotly(initial_G)
+# ============================================================
+# INITIAL GRAPH
+# ============================================================
+
+initial_graph = build_graph(include_transfers=True)
+initial_fig = graph_to_plotly(initial_graph)
+
+# ============================================================
+# GRADIO UI — CLEAN, FULL-WIDTH LAYOUT
+# ============================================================
 
-# ---------------------------
-# Gradio UI (Blocks)
-# ---------------------------
 with gr.Blocks() as demo:
-    gr.Markdown("## Mutual Fund Churn explorer — interactive network + transfer analysis")
+    gr.Markdown("## Mutual Fund Churn Explorer — Full Network & Transfer Analysis")
 
-    # === LARGE FULL-WIDTH NETWORK GRAPH AT TOP ===
-    network_plot = gr.Plot(value=initial_fig, label="Network graph (drag to zoom)", height=900)
+    # === FULL-WIDTH NETWORK GRAPH AT THE TOP ===
+    network_plot = gr.Plot(
+        value=initial_fig,
+        label="Network graph (drag to zoom)"
+    )
 
-    # === EVERYTHING ELSE BELOW ===
+    # === SETTINGS BELOW THE GRAPH ===
     with gr.Accordion("Network Customization", open=True):
-        with gr.Column():
-            node_color_company = gr.ColorPicker(value="#FFCF9E", label="Company node color")
-            node_color_amc = gr.ColorPicker(value="#9EC5FF", label="AMC node color")
-
-            node_shape_company = gr.Dropdown(
-                choices=["circle","square","diamond"],
-                value="circle",
-                label="Company node shape"
-            )
-            node_shape_amc = gr.Dropdown(
-                choices=["circle","square","diamond"],
-                value="circle",
-                label="AMC node shape"
-            )
+        node_color_company = gr.ColorPicker("#FFCF9E", label="Company node color")
+        node_color_amc = gr.ColorPicker("#9EC5FF", label="AMC node color")
 
-            edge_color_buy = gr.ColorPicker(value="#2ca02c", label="BUY edge color")
-            edge_color_sell = gr.ColorPicker(value="#d62728", label="SELL edge color")
-            edge_color_transfer = gr.ColorPicker(value="#888888", label="Transfer edge color")
+        node_shape_company = gr.Dropdown(["circle", "square", "diamond"], value="circle",
+                                         label="Company node shape")
+        node_shape_amc = gr.Dropdown(["circle", "square", "diamond"], value="circle",
+                                     label="AMC node shape")
 
-            edge_thickness = gr.Slider(
-                minimum=0.5, maximum=6.0, value=1.4, step=0.1,
-                label="Edge thickness base"
-            )
+        edge_color_buy = gr.ColorPicker("#2ca02c", label="BUY edge color")
+        edge_color_sell = gr.ColorPicker("#d62728", label="SELL edge color")
+        edge_color_transfer = gr.ColorPicker("#888888", label="Transfer edge color")
 
-            include_transfers = gr.Checkbox(
-                value=True,
-                label="Infer AMC → AMC transfers (show loops)"
-            )
+        edge_thickness = gr.Slider(0.5, 6.0, value=1.4, step=0.1, label="Edge thickness base")
+        include_transfers = gr.Checkbox(value=True, label="Show AMC→AMC inferred transfers")
 
-            update_button = gr.Button("Update network graph")
+        update_button = gr.Button("Update Network Graph")
 
-    gr.Markdown("### Inspect a Company (who bought / who sold)")
+    gr.Markdown("### Inspect a Company (buyers / sellers)")
     select_company = gr.Dropdown(choices=COMPANIES, label="Select company")
     company_out_plot = gr.Plot(label="Company trade summary")
-    company_out_table = gr.DataFrame(label="Company trade table")
+    company_out_table = gr.DataFrame(label="Company table")
 
-    gr.Markdown("### Inspect an AMC (transfer chains)")
+    gr.Markdown("### Inspect an AMC (transfer analysis)")
     select_amc = gr.Dropdown(choices=AMCS, label="Select AMC")
-    amc_out_plot = gr.Plot(label="AMC inferred transfers")
+    amc_out_plot = gr.Plot(label="AMC transfer summary")
     amc_out_table = gr.DataFrame(label="AMC transfer table")
 
-    # --- Callbacks remain identical ---
+    # === CALLBACKS ===
+
+    def update_network(node_color_company_val, node_color_amc_val,
+                       node_shape_company_val, node_shape_amc_val,
+                       edge_color_buy_val, edge_color_sell_val, edge_color_transfer_val,
+                       edge_thickness_val, include_transfers_val):
+
+        G = build_graph(include_transfers=include_transfers_val)
+        fig = graph_to_plotly(
+            G,
+            node_color_amc=node_color_amc_val,
+            node_color_company=node_color_company_val,
+            node_shape_amc=node_shape_amc_val,
+            node_shape_company=node_shape_company_val,
+            edge_color_buy=edge_color_buy_val,
+            edge_color_sell=edge_color_sell_val,
+            edge_color_transfer=edge_color_transfer_val,
+            edge_thickness_base=edge_thickness_val,
+        )
+        return fig
+
     update_button.click(
-        fn=update_network,
-        inputs=[
+        update_network,
+        [
             node_color_company,
             node_color_amc,
             node_shape_company,
@@ -289,19 +385,22 @@ with gr.Blocks() as demo:
             edge_color_sell,
             edge_color_transfer,
             edge_thickness,
-            include_transfers
+            include_transfers,
         ],
-        outputs=[network_plot]
+        [network_plot]
     )
 
-    select_company.change(
-        fn=on_company_select,
-        inputs=[select_company],
-        outputs=[company_out_plot, company_out_table]
-    )
+    def handle_company(company):
+        fig, df = company_trade_summary(company)
+        return fig, df
 
-    select_amc.change(
-        fn=on_amc_select,
-        inputs=[select_amc],
-        outputs=[amc_out_plot, amc_out_table]
-    )
+    def handle_amc(amc):
+        fig, df = amc_transfer_summary(amc)
+        return fig, df
+
+    select_company.change(handle_company, select_company, [company_out_plot, company_out_table])
+    select_amc.change(handle_amc, select_amc, [amc_out_plot, amc_out_table])
+
+
+if __name__ == "__main__":
+    demo.launch()