# app.py
# Interactive MF churn explorer
# - Chart is client-side interactive: clicking a node hides everything except that node + its neighbors (Option A)
# - AMC/company inspect sections remain unchanged
# Requirements: gradio, networkx, plotly, pandas, numpy

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

# ---------------------------
# Sample dataset (same as before)
# ---------------------------
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)

# ---------------------------
# Build edges & infer transfers
# ---------------------------
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)
    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(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
    edge_list = []
    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")
    for c in COMPANIES:
        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(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

# ---------------------------
# Build Plotly figure (Python-side)
# ---------------------------
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,
                        show_labels=True):
    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)

    # edges: one trace per edge to allow individual styling in JS
    edge_traces = []
    edge_source_index = []
    edge_target_index = []
    edge_colors = []
    edge_widths = []
    for u, v, attrs in G.edges(data=True):
        x0, y0 = pos[u]; x1, y1 = pos[v]
        acts = attrs.get("actions", [])
        weight = attrs.get("weight", 1)
        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 = edge_thickness_base * (1 + np.log1p(weight))

        # create trace for this edge
        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_index.append(node_names.index(u))
        edge_target_index.append(node_names.index(v))
        edge_colors.append(color)
        edge_widths.append(width)

    # single node trace
    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_names if show_labels else None,
        textposition="top center",
        hoverinfo="text"
    )

    # assemble traces: edges first, nodes last
    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)
    )

    # We package helper arrays for JS (node names, edge source/target indices, original edge colors/widths)
    meta = {
        "node_names": node_names,
        "edge_source_index": edge_source_index,
        "edge_target_index": edge_target_index,
        "edge_colors": edge_colors,
        "edge_widths": edge_widths,
        "node_colors": node_color,
        "node_sizes": node_size
    }
    return fig, meta

# ---------------------------
# Helper to produce embeddable HTML with JS click handlers
# ---------------------------
def make_network_html(fig, meta, div_id="network-plot-div"):
    # serialize plotly figure and metadata
    fig_json = fig.to_plotly_json()
    fig_json_text = json.dumps(fig_json)  # safe to embed
    meta_text = json.dumps(meta)

    # Build HTML string that:
    # - creates a div with id
    # - loads Plotly (cdn)
    # - creates the plot via Plotly.newPlot
    # - sets up click handler that: when a node is clicked, only the node + its neighbors remain visible
    # - adds a reset button
    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_text};
const meta = {meta_text};

// create plot
const container = document.getElementById("{div_id}");
Plotly.newPlot(container, fig.data, fig.layout, {{responsive: true}});

// identify traces: node trace is last
const nodeTraceIndex = fig.data.length - 1;
const edgeCount = fig.data.length - 1;

// helper: get node name -> index
const nameToIndex = {{}};
meta.node_names.forEach((n,i) => nameToIndex[n] = i);

// helper: when focusing nodeName, hide all traces/nodes not connected
function focusNode(nodeName) {{
    const idx = nameToIndex[nodeName];
    // neighbors = nodes that are sources or targets with edges to/from idx
    const keepSet = 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) {{ keepSet.add(t); }}
        if (t === idx) {{ keepSet.add(s); }}
    }}

    // Prepare new marker opacity and text visibility arrays for nodes
    const nodeCount = meta.node_names.length;
    const newMarkerOpacity = Array(nodeCount).fill(0.0);
    const newTextOpacity = Array(nodeCount).fill(0.0);
    for (let i=0;i<nodeCount;i++) {{
        if (keepSet.has(i)) {{
            newMarkerOpacity[i] = 1.0;
            newTextOpacity[i] = 1.0;
        }} else {{
            newMarkerOpacity[i] = 0.0;
            newTextOpacity[i] = 0.0;
        }}
    }}

    // Update node trace opacity and text via single restyle
    Plotly.restyle(container, {{
        'marker.opacity': [newMarkerOpacity],
        'textfont': [{{'color': ['rgba(0,0,0,0)']}}] // optional - hide text for non-kept
    }}, [nodeTraceIndex]);

    // Update each edge trace: show only if both ends in keepSet
    for (let e=0; e < edgeCount; e++) {{
        const s = meta.edge_source_index[e];
        const t = meta.edge_target_index[e];
        const show = (keepSet.has(s) && keepSet.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]);
    }}

    // Optionally zoom to bounding box of kept nodes
    // compute bbox
    let xs = [], ys = [];
    const nodes = fig.data[nodeTraceIndex];
    for (let j=0;j<meta.node_names.length;j++) {{
        if (keepSet.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 + 0.1;
        const padY = (ymax - ymin) * 0.4 + 0.1;
        const newLayout = {{
            xaxis: {{ range: [xmin - padX, xmax + padX] }},
            yaxis: {{ range: [ymin - padY, ymax + padY] }}
        }};
        Plotly.relayout(container, newLayout);
    }}
}}

// Reset function: restore original colors/widths/opacities
function resetView() {{
    // restore nodes opacity to 1
    const nodeCount = meta.node_names.length;
    const fullOpacity = Array(nodeCount).fill(1.0);
    Plotly.restyle(container, {{ 'marker.opacity': [fullOpacity] }}, [nodeTraceIndex]);

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

    // restore axes auto-range
    Plotly.relayout(container, {{ xaxis: {{autorange: true}}, yaxis: {{autorange: true}} }} );
}}

// attach click handler on plot: if a node is clicked, focus that node
container.on('plotly_click', function(eventData) {{
    // eventData.points[0].curveNumber is trace index, pointNumber is marker index for node trace
    const p = eventData.points[0];
    if (p.curveNumber === nodeTraceIndex) {{
        const nodeIndex = p.pointNumber;
        const nodeName = meta.node_names[nodeIndex];
        focusNode(nodeName);
    }}
}});

// attach reset button
document.getElementById("{div_id}-reset").addEventListener('click', function() {{
    resetView();
}});

</script>
"""
    return html

# ---------------------------
# Company / AMC inspection helpers (unchanged)
# ---------------------------
def company_trade_summary(company_name):
    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),
        "AMC": buyers + sellers + fresh + exits
    })

    if df.empty:
        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}", autosize=True, margin=dict(t=30,b=10))
    return fig, df

def amc_transfer_summary(amc_name):
    sold = SELL_MAP.get(amc_name, [])
    transfers = []
    for s in sold:
        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}", autosize=True, margin=dict(t=30,b=10))
    return fig, df

# ---------------------------
# Initial graph HTML (server builds figure & meta, client handles clicks)
# ---------------------------
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,
                                   show_labels=True)
    html = make_network_html(fig, meta, div_id="network-plot-div")
    return html

initial_html = build_network_html()

# ---------------------------
# Mobile-friendly CSS (embed)
# ---------------------------
responsive_css = """
/* remove iframe padding inside HF spaces */
.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 only screen and (max-width: 780px) {
    .js-plotly-plot { height: 420px !important; }
}
body, html { overflow-x: hidden !important; }
"""

# ---------------------------
# Gradio UI
# ---------------------------
with gr.Blocks(css=responsive_css, title="MF Churn Explorer (interactive chart)") as demo:
    gr.Markdown("## Mutual Fund Churn Explorer — Interactive Chart (click nodes)")

    # HTML-based interactive Plotly (client-side click handling)
    network_html = gr.HTML(value=initial_html)

    # Controls below (unchanged behaviour)
    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")

    gr.Markdown("### Inspect a Company (buyers / sellers)")
    select_company = gr.Dropdown(choices=COMPANIES, label="Select company (buyers / sellers)")
    company_out_plot = gr.Plot(label="Company trade summary")
    company_out_table = gr.DataFrame(label="Company trade table")

    gr.Markdown("### Inspect an AMC (inferred transfers)")
    # AMC inspect unchanged; kept for server-side analysis below chart
    select_amc = gr.Dropdown(choices=AMCS, label="Select AMC (inferred transfers)")
    amc_out_plot = gr.Plot(label="AMC transfer summary")
    amc_out_table = gr.DataFrame(label="AMC transfer table")

    # ---------------------------
    # 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):
        html = 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)
        return html

    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_out_plot, company_out_table])
    select_amc.change(fn=on_amc_select, inputs=[select_amc], outputs=[amc_out_plot, amc_out_table])

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