import gradio as gr
import plotly.graph_objects as go
import pandas as pd
import numpy as np
import json
import spaces

# Load the two exported dashboard files
spend = pd.read_csv("spend.csv").squeeze("columns")
headline = json.load(open("headline.json"))


def gini(x):
    x = np.sort(np.asarray(x, dtype=float))
    n = len(x)

    if n == 0 or x.sum() == 0:
        return float("nan")

    i = np.arange(1, n + 1)
    return (2 * np.sum(i * x) / (n * x.sum())) - (n + 1) / n


def lorenz(x):
    x = np.sort(np.asarray(x, dtype=float))
    cum = np.cumsum(x)

    cum_share = np.insert(cum / cum[-1], 0, 0.0)
    cum_pop = np.insert(
        np.arange(1, len(x) + 1) / len(x),
        0,
        0.0
    )

    return cum_pop, cum_share


G = gini(spend)


def lorenz_fig():
    pop, share = lorenz(spend)

    figure = go.Figure()

    figure.add_trace(
        go.Scatter(
            x=pop,
            y=share,
            name="Actual",
            fill="tozeroy"
        )
    )

    figure.add_trace(
        go.Scatter(
            x=[0, 1],
            y=[0, 1],
            name="Equality",
            line=dict(dash="dash")
        )
    )

    figure.update_layout(
        title=f"Spend concentration (Gini {G:.2f})",
        xaxis_title="Share of patients",
        yaxis_title="Share of dollars",
        margin=dict(l=10, r=10, t=40, b=10),
        height=320
    )

    return figure


def kpis():
    ratio = (
        headline["mean_spend"]
        / max(headline["median_spend"], 1)
    )

    return (
        f"Median patient: USD {headline['median_spend']:,}\n"
        f"Mean patient: USD {headline['mean_spend']:,} "
        f"({ratio:.1f}x median)\n"
        f"Top 10% drive: "
        f"{headline['top10_pct_of_dollars']}% of all dollars\n"
        f"Top-decile line: USD "
        f"{headline['top_decile_cutoff']:,}\n"
        f"This week's exemplar: USD "
        f"{headline['patient_spend']:,} "
        f"({headline['patient_percentile']}th percentile)"
    )


@spaces.GPU
def refresh_dashboard():
    return kpis(), lorenz_fig()


with gr.Blocks() as demo:
    gr.Markdown("# Healthcare Spend - 30-Second Decision View")

    with gr.Row():
        numbers = gr.Textbox(
            value=kpis(),
            label="The numbers that change the decision",
            lines=6
        )

        concentration = gr.Plot(
            value=lorenz_fig(),
            label="Concentration"
        )

    refresh = gr.Button("Refresh dashboard")

    refresh.click(
        fn=refresh_dashboard,
        outputs=[numbers, concentration]
    )

    gr.Markdown(
        "*Design rule: if it is not on this screen, "
        "it is not a headline. Detail lives one click deeper.*"
    )


demo.launch()