# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "marimo",
#     "matplotlib==3.10.1",
#     "numpy==2.2.4",
# ]
# ///

import marimo

__generated_with = "0.14.10"
app = marimo.App(css_file="theme.marimo.css", html_head_file="")


@app.cell
def _():
    import marimo as mo
    return (mo,)


@app.cell
def _(mo):
    get_applicant_count, set_applicant_count = mo.state(500)
    return get_applicant_count, set_applicant_count


@app.cell
def _(get_applicant_count, mo, set_applicant_count):
    applicant_count = mo.ui.number(
        start=1,
        step=1,
        value=get_applicant_count(),
        full_width=True,
        label="Number of applicants",
        on_change=set_applicant_count,
    )
    return (applicant_count,)


@app.cell
def _(get_applicant_count, mo):
    hire_count = mo.ui.number(
        start=1,
        stop=get_applicant_count() - 1,
        step=1,
        value=75,
        full_width=True,
        label="Hire count",
    )
    return (hire_count,)


@app.cell
def _(mo):
    base_rate = mo.ui.slider(
        value=40, start=1, stop=100, step=1, full_width=True, label="Base rate"
    )
    return (base_rate,)


@app.cell
def _(mo):
    validity = mo.ui.slider(
        value=0.18, start=0.01, stop=1.00, step=0.01, full_width=True, label="Validity"
    )
    return (validity,)


@app.cell
def _(applicant_count, base_rate, hire_count, validity):
    import requests

    url = "http://localhost:7860/api/v1/demo/r/demo"
    params = {
        "applicant_count": applicant_count.value,
        "hire_count": hire_count.value,
        "base_rate": base_rate.value,
        "validity": validity.value,
    }
    headers = {"accept": "application/json"}

    response = requests.post(url, params=params, headers=headers)

    return (response,)


@app.cell
def _(response):
    import pandas as pd
    import plotly.graph_objects as go
    from plotly.subplots import make_subplots

    json_data = response.json()

    data = pd.DataFrame(
        {
            "var": list(json_data.keys()),
            "label": [
                "Rightfully hired",
                "Incorrectly hired",
                "Rightfully rejected",
                "Incorrectly rejected",
            ],
            "value": list(json_data.values()),
        }
    )

    data["label_with_value"] = data["label"] + " (" + data["value"].astype(str) + ")"

    fig = make_subplots(
        rows=1,
        cols=2,
        specs=[[{"type": "pie"}, {"type": "pie"}]],
        subplot_titles=("Hiring Outcome", "Rejection Outcome"),
        horizontal_spacing=0.1,
        vertical_spacing=0.15,
    )

    hired_data = data[data["var"].isin(["true_positives", "false_positives"])]
    hired_values = hired_data["value"].tolist()
    hired_labels = hired_data["label_with_value"].tolist()

    rejected_data = data[data["var"].isin(["true_negatives", "false_negatives"])]
    rejected_values = rejected_data["value"].tolist()
    rejected_labels = rejected_data["label_with_value"].tolist()

    fig.add_trace(
        go.Pie(
            values=hired_values,
            labels=hired_labels,
            hole=0.5,
            marker_colors=["#6b71ed", "#403c5d"],
            name="Hiring",
            legendgroup="hiring",
            showlegend=True,
            hoverinfo="none",
        ),
        row=1,
        col=1,
    )

    fig.add_trace(
        go.Pie(
            values=rejected_values,
            labels=rejected_labels,
            hole=0.5,
            marker_colors=["#6b71ed", "#403c5d"],
            name="Rejection",
            legendgroup="rejection",
            showlegend=True,
            hoverinfo="none",
        ),
        row=1,
        col=2,
    )

    fig.update_layout(
        autosize=True,
        margin=dict(l=0, r=0, t=60, b=20),
        legend=dict(
            orientation="h",
            yanchor="top",
            y=-0.1,
            xanchor="center",
            x=0.5,
            font=dict(size=12),
        ),
        title=dict(text=None, x=0.5, font=dict(size=16)),
        height=400,
        paper_bgcolor="rgba(0,0,0,0)",
        plot_bgcolor="rgba(0,0,0,0)",
    )

    fig.update_annotations(font_size=14, y=1.08)

    return (fig,)


@app.cell
def _(applicant_count, base_rate, hire_count, mo, validity):
    with mo.status.spinner(subtitle="Loading data ...") as _spinner:
        mo.vstack([applicant_count, hire_count, base_rate, validity])
    return


@app.cell
def _(applicant_count, base_rate, hire_count, mo, validity):
    mo.vstack([applicant_count, hire_count, base_rate, validity])
    return


@app.cell
def _(fig, mo, response):
    if response.status_code == 200:
        fig.show(
            config={"displayModeBar": False, "staticPlot": True, "responsive": True}
        )
    else:
        error_msg = mo.md(f"{mo.icon('lucide:ban')} Error in server response")
        mo.output.append(error_msg)
    return


if __name__ == "__main__":
    app.run()