app.py

# app.py
# Interactive MF churn explorer — Plotly graph with node click-to-focus
# + Legend
# + Fixed JS (labels hide properly)
# + Mobile-friendly
# + HF iframe safe

import gradio as gr
import pandas as pd
import networkx as nx
import plotly.graph_objects as go
import numpy as np
import json
from collections import defaultdict

# ============================================================
# 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"
]

COMPANIES = [
    "HDFC Bank", "ICICI Bank", "Bajaj Finance", "Bajaj Finserv", "Adani Ports",
    "Tata Motors", "Shriram Finance", "HAL", "TCS", "AU Small Finance Bank",
    "Pearl Global", "Hindalco", "Tata Elxsi", "Cummins India", "Vedanta"
]

BUY_MAP = {
    "SBI MF": ["Bajaj Finance", "AU Small Finance Bank"],
    "ICICI Pru MF": ["HDFC Bank"],
    "HDFC MF": ["Tata Elxsi", "TCS"],
    "Nippon India MF": ["Hindalco"],
    "Kotak MF": ["Bajaj Finance"],
    "UTI MF": ["Adani Ports", "Shriram Finance"],
    "Axis MF": ["Tata Motors", "Shriram Finance"],
    "Aditya Birla SL MF": ["AU Small Finance Bank"],
    "Mirae MF": ["Bajaj Finance", "HAL"],
    "DSP MF": ["Tata Motors", "Bajaj Finserv"]
}

SELL_MAP = {
    "SBI MF": ["Tata Motors"],
    "ICICI Pru MF": ["Bajaj Finance", "Adani Ports"],
    "HDFC MF": ["HDFC Bank"],
    "Nippon India MF": ["Hindalco"],
    "Kotak MF": ["AU Small Finance Bank"],
    "UTI MF": ["Hindalco", "TCS"],
    "Axis MF": ["TCS"],
    "Aditya Birla SL MF": ["Adani Ports"],
    "Mirae MF": ["TCS"],
    "DSP MF": ["HAL", "Shriram Finance"]
}

COMPLETE_EXIT = {"DSP MF": ["Shriram Finance"]}
FRESH_BUY = {"HDFC MF": ["Tata Elxsi"], "UTI MF": ["Adani Ports"], "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:
        company_edges.append((amc, c, {"action": "buy", "weight": 1}))

for amc, comps in SELL_MAP.items():
    for c in comps:
        company_edges.append((amc, c, {"action": "sell", "weight": 1}))

for amc, comps in COMPLETE_EXIT.items():
    for c in comps:
        company_edges.append((amc, c, {"action": "complete_exit", "weight": 3}))

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)
    c2s = defaultdict(list)
    c2b = defaultdict(list)

    for amc, comps in sell_map.items():
        for c in comps:
            c2s[c].append(amc)

    for amc, comps in buy_map.items():
        for c in comps:
            c2b[c].append(amc)

    for c in set(c2s.keys()) | set(c2b.keys()):
        for s in c2s[c]:
            for b in c2b[c]:
                transfers[(s, b)] += 1

    output = []
    for (s, b), w in transfers.items():
        output.append((s, b, {"action": "transfer", "weight": w}))
    return output


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")

    for c in COMPANIES:
        G.add_node(c, type="company")

    # company edges
    for u, v, attr in company_edges:
        if G.has_edge(u, v):
            G[u][v]["weight"] += attr["weight"]
            G[u][v]["actions"].append(attr["action"])
        else:
            G.add_edge(u, v, weight=attr["weight"], actions=[attr["action"]])

    # inferred transfer edges
    if include_transfers:
        for s, b, attr in transfer_edges:
            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

# ============================================================
# PLOTLY FIGURE
# ============================================================

def build_plotly_figure(
    G,
    node_color_amc="#9EC5FF",
    node_color_company="#FFCF9E",
    edge_color_buy="#2ca02c",
    edge_color_sell="#d62728",
    edge_color_transfer="#888888",
    edge_thickness_base=1.4
):
    pos = nx.spring_layout(G, seed=42, k=1.2)

    node_names = []
    node_x = []
    node_y = []
    node_color = []
    node_size = []

    for n, d in G.nodes(data=True):
        node_names.append(n)
        x, y = pos[n]
        node_x.append(x)
        node_y.append(y)

        if d["type"] == "amc":
            node_color.append(node_color_amc)
            node_size.append(36)
        else:
            node_color.append(node_color_company)
            node_size.append(56)

    edge_traces = []
    edge_source = []
    edge_target = []
    edge_colors = []
    edge_widths = []

    for u, v, attrs in G.edges(data=True):
        x0, y0 = pos[u]
        x1, y1 = pos[v]
        acts = attrs["actions"]
        weight = attrs["weight"]

        if "complete_exit" in acts:
            color = edge_color_sell
            width = edge_thickness_base * 3
            dash = "solid"
        elif "fresh_buy" in acts:
            color = edge_color_buy
            width = edge_thickness_base * 3
            dash = "solid"
        elif "transfer" in acts:
            color = edge_color_transfer
            width = edge_thickness_base * (1 + np.log1p(weight))
            dash = "dash"
        elif "sell" in acts:
            color = edge_color_sell
            width = edge_thickness_base * (1 + np.log1p(weight))
            dash = "dot"
        else:
            color = edge_color_buy
            width = edge_thickness_base * (1 + np.log1p(weight))
            dash = "solid"

        edge_traces.append(
            go.Scatter(
                x=[x0, x1],
                y=[y0, y1],
                mode="lines",
                line=dict(color=color, width=width, dash=dash),
                hoverinfo="none",
                opacity=1.0
            )
        )

        edge_source.append(node_names.index(u))
        edge_target.append(node_names.index(v))
        edge_colors.append(color)
        edge_widths.append(width)

    node_trace = go.Scatter(
        x=node_x,
        y=node_y,
        mode="markers+text",
        marker=dict(color=node_color, size=node_size, line=dict(width=2, color="#333")),
        text=node_names,
        textposition="top center",
        hoverinfo="text"
    )

    fig = go.Figure(data=edge_traces + [node_trace])
    fig.update_layout(
        showlegend=False,
        autosize=True,
        margin=dict(l=8, r=8, t=36, b=8),
        xaxis=dict(visible=False),
        yaxis=dict(visible=False)
    )

    meta = {
        "node_names": node_names,
        "edge_source_index": edge_source,
        "edge_target_index": edge_target,
        "edge_colors": edge_colors,
        "edge_widths": edge_widths
    }

    return fig, meta
# ================= PART 2 / 3 =================
# HTML builder and JS (with escaped braces for f-string)
def make_network_html(fig, meta, div_id="network-plot-div"):
    fig_json = json.dumps(fig.to_plotly_json())
    meta_json = json.dumps(meta)

    html = f"""
<div id="{div_id}" style="width:100%;height:520px;"></div>
<div style="margin-top:6px;margin-bottom:8px;">
  <button id="{div_id}-reset" style="padding:8px 12px;border-radius:6px;">Reset view</button>
</div>

<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>

<script>
const fig = {fig_json};
const meta = {meta_json};

const container = document.getElementById("{div_id}");

Plotly.newPlot(container, fig.data, fig.layout, {{responsive:true}});

const nodeTraceIndex = fig.data.length - 1;
const edgeCount = fig.data.length - 1;

const nameToIndex = {{}}; 
meta.node_names.forEach((n,i) => nameToIndex[n]=i);

// focusNode: show only clicked node + its direct neighbors (Option A)
function focusNode(nodeName) {{
    const idx = nameToIndex[nodeName];
    const keep = new Set([idx]);

    for (let e = 0; e < meta.edge_source_index.length; e++) {{
        const s = meta.edge_source_index[e];
        const t = meta.edge_target_index[e];
        if (s === idx) {{ keep.add(t); }}
        if (t === idx) {{ keep.add(s); }}
    }}

    // Update nodes (hide others + hide labels)
    const N = meta.node_names.length;
    const nodeOp = Array(N).fill(0.0);
    const textColors = Array(N).fill("rgba(0,0,0,0)");

    for (let i = 0; i < N; i++) {{
        if (keep.has(i)) {{
            nodeOp[i] = 1.0;
            textColors[i] = "black";
        }}
    }}

    Plotly.restyle(container, {{
        "marker.opacity": [nodeOp],
        "textfont.color": [textColors]
    }}, [nodeTraceIndex]);

    // Update edges: show only edges connecting kept nodes
    for (let e = 0; e < edgeCount; e++) {{
        const s = meta.edge_source_index[e];
        const t = meta.edge_target_index[e];
        const show = (keep.has(s) && keep.has(t));
        const color = show ? meta.edge_colors[e] : 'rgba(0,0,0,0)';
        const width = show ? meta.edge_widths[e] : 0.1;
        Plotly.restyle(container, {{
            'line.color': [color],
            'line.width': [width]
        }}, [e]);
    }}

    // zoom to bounding box of kept nodes
    const nodes = fig.data[nodeTraceIndex];
    const xs = [], ys = [];
    for (let j = 0; j < meta.node_names.length; j++) {{
        if (keep.has(j)) {{
            xs.push(nodes.x[j]); ys.push(nodes.y[j]);
        }}
    }}
    if (xs.length > 0) {{
        const xmin = Math.min(...xs), xmax = Math.max(...xs);
        const ymin = Math.min(...ys), ymax = Math.max(...ys);
        const padX = (xmax - xmin) * 0.4 + 0.05;
        const padY = (ymax - ymin) * 0.4 + 0.05;
        Plotly.relayout(container, {{
            xaxis: {{ range: [xmin - padX, xmax + padX] }},
            yaxis: {{ range: [ymin - padY, ymax + padY] }}
        }});
    }}
}}

// reset view: restore nodes and edges
function resetView() {{
    const N = meta.node_names.length;
    const nodeOp = Array(N).fill(1.0);
    const textColors = Array(N).fill("black");

    Plotly.restyle(container, {{
        "marker.opacity": [nodeOp],
        "textfont.color": [textColors]
    }}, [nodeTraceIndex]);

    for (let e = 0; e < edgeCount; e++) {{
        Plotly.restyle(container, {{
            'line.color': [meta.edge_colors[e]],
            'line.width': [meta.edge_widths[e]]
        }}, [e]);
    }}

    Plotly.relayout(container, {{ xaxis: {{autorange:true}}, yaxis: {{autorange:true}} }});
}}

// attach click handler
container.on('plotly_click', function(eventData) {{
    const p = eventData.points[0];
    if (p.curveNumber === nodeTraceIndex) {{
        const nodeIndex = p.pointNumber;
        const nodeName = meta.node_names[nodeIndex];
        focusNode(nodeName);
    }}
}});

// reset button
document.getElementById("{div_id}-reset").addEventListener('click', function() {{
    resetView();
}});
</script>
"""
    return html

# helper to build final html block
def build_network_html(node_color_company="#FFCF9E",
                       node_color_amc="#9EC5FF",
                       edge_color_buy="#2ca02c",
                       edge_color_sell="#d62728",
                       edge_color_transfer="#888888",
                       edge_thickness=1.4,
                       include_transfers=True):
    G = build_graph(include_transfers=include_transfers)
    fig, meta = build_plotly_figure(
        G,
        node_color_amc=node_color_amc,
        node_color_company=node_color_company,
        edge_color_buy=edge_color_buy,
        edge_color_sell=edge_color_sell,
        edge_color_transfer=edge_color_transfer,
        edge_thickness_base=edge_thickness
    )
    return make_network_html(fig, meta)

# initial HTML
initial_html = build_network_html()
# ================= PART 3 / 3 =================
# company & amc summaries, UI and callbacks

def company_trade_summary(company):
    buyers = [a for a, cs in BUY_MAP.items() if company in cs]
    sellers = [a for a, cs in SELL_MAP.items() if company in cs]
    fresh = [a for a, cs in FRESH_BUY.items() if company in cs]
    exits = [a for a, cs in COMPLETE_EXIT.items() if company in cs]

    df = pd.DataFrame({
        "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"])

    counts = df.groupby("Role").size().reset_index(name="Count")
    colors = ["green", "red", "orange", "black"][:len(counts)]
    fig = go.Figure(go.Bar(x=counts["Role"], y=counts["Count"], marker_color=colors))
    fig.update_layout(title_text=f"Trade summary for {company}", autosize=True, margin=dict(t=30, b=10))
    return fig, df

def amc_transfer_summary(amc):
    sold = SELL_MAP.get(amc, [])
    transfers = []
    for s in sold:
        buyers = [a for a, cs in BUY_MAP.items() if s in cs]
        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}", autosize=True, margin=dict(t=30, b=10))
    return fig, df

# Mobile-friendly CSS (minimal)
responsive_css = """
.gradio-container { padding:0 !important; margin:0 !important; }
.plotly-graph-div, .js-plotly-plot, .output_plot { width:100% !important; max-width:100% !important; }
.js-plotly-plot { height:460px !important; }
@media(max-width:780px){ .js-plotly-plot{ height:420px !important; } }
body, html { overflow-x:hidden !important; }
"""

# Build UI
with gr.Blocks(css=responsive_css, title="MF Churn Explorer") as demo:
    gr.Markdown("## Mutual Fund Churn Explorer — Interactive Graph")

    # Chart HTML (interactive client-side)
    network_html = gr.HTML(value=initial_html)

    # Legend (ONLY addition)
    legend_html = gr.HTML(value="""
<div style='
    font-family: sans-serif;
    font-size: 14px;
    margin-top: 10px;
    line-height: 1.6;
'>
    <b>Legend</b><br>

    <div>
        <span style="display:inline-block;width:28px;
            border-bottom:3px solid #2ca02c;"></span>
        BUY (green solid)
    </div>

    <div>
        <span style="display:inline-block;width:28px;
            border-bottom:3px dotted #d62728;"></span>
        SELL (red dotted)
    </div>

    <div>
        <span style="display:inline-block;width:28px;
            border-bottom:3px dashed #888;"></span>
        TRANSFER (grey dashed)
    </div>

    <div>
        <span style="display:inline-block;width:28px;
            border-bottom:5px solid #2ca02c;"></span>
        FRESH BUY (thick green)
    </div>

    <div>
        <span style="display:inline-block;width:28px;
            border-bottom:5px solid #d62728;"></span>
        COMPLETE EXIT (thick red)
    </div>
</div>
""")

    # Controls (collapsed by default)
    with gr.Accordion("Network Customization — expand to edit", open=False):
        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("#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")
        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")

    # Company inspect (unchanged)
    gr.Markdown("### Inspect Company (buyers / sellers)")
    select_company = gr.Dropdown(choices=COMPANIES, label="Select company")
    company_plot = gr.Plot()
    company_table = gr.DataFrame()

    # AMC inspect (unchanged)
    gr.Markdown("### Inspect AMC (inferred transfers)")
    select_amc = gr.Dropdown(choices=AMCS, label="Select AMC")
    amc_plot = gr.Plot()
    amc_table = gr.DataFrame()

    # Place legend right after the chart (no layout changes beyond that)
    # We add both components so legend appears below the chart area.
    # Note: the order of declaration in Blocks determines visual order.
    # legend_html.update(value=legend_html.value)  # ensure added

    # Callbacks
    def update_network_html(node_color_company_val, node_color_amc_val,
                            edge_color_buy_val, edge_color_sell_val, edge_color_transfer_val,
                            edge_thickness_val, include_transfers_val):
        return build_network_html(node_color_company=node_color_company_val,
                                  node_color_amc=node_color_amc_val,
                                  edge_color_buy=edge_color_buy_val,
                                  edge_color_sell=edge_color_sell_val,
                                  edge_color_transfer=edge_color_transfer_val,
                                  edge_thickness=edge_thickness_val,
                                  include_transfers=include_transfers_val)

    def on_company_select(cname):
        fig, df = company_trade_summary(cname)
        if fig is None:
            return None, pd.DataFrame([], columns=["Role", "AMC"])
        return fig, df

    def on_amc_select(aname):
        fig, df = amc_transfer_summary(aname)
        if fig is None:
            return None, pd.DataFrame([], columns=["security", "buyer_amc"])
        return fig, df

    update_button.click(fn=update_network_html,
                        inputs=[node_color_company, node_color_amc,
                                edge_color_buy, edge_color_sell, edge_color_transfer,
                                edge_thickness, include_transfers],
                        outputs=[network_html])

    select_company.change(fn=on_company_select, inputs=[select_company], outputs=[company_plot, company_table])
    select_amc.change(fn=on_amc_select, inputs=[select_amc], outputs=[amc_plot, amc_table])

# Run
if __name__ == "__main__":
    demo.launch()