glucose-dashboard/pdf_export.py

"""
PDF-rapportgeneratie voor geselecteerde rapportageonderdelen (FR10).

Gebruikt fpdf2 (puur Python, geen systeemdependencies) voor de PDF-opbouw en
matplotlib voor een eenvoudige statische AGP-grafiek specifiek voor de PDF —
bewust niet dezelfde Plotly-figuren als op de pagina's zelf (die zouden
kaleido vereisen, met een ingebakken Chromium-build: een groter image en meer
Trivy-oppervlak, voor dit doel niet nodig).
"""

from __future__ import annotations

import io

import matplotlib

matplotlib.use("Agg")
import matplotlib.pyplot as plt
import pandas as pd
from fpdf import FPDF
from fpdf.enums import XPos, YPos

from reporting import (
    agp_percentile_bands,
    completeness_warning,
    gmi_percent,
    percent_cv,
    sensor_active_percent,
    tir_breakdown_5band,
)

SECTION_SUMMARY = "Samenvatting"
SECTION_AGP = "AGP profiel"
SECTION_EVENTS = "Hypo-/hyperevents"

AVAILABLE_SECTIONS = [SECTION_SUMMARY, SECTION_AGP, SECTION_EVENTS]

_LINE_KWARGS = {"new_x": XPos.LMARGIN, "new_y": YPos.NEXT}


def _agp_figure_png(glucose: pd.DataFrame) -> bytes:
    bands = agp_percentile_bands(glucose)
    fig, ax = plt.subplots(figsize=(7, 3))
    hours = bands["minute_of_day"] / 60
    ax.fill_between(hours, bands["p5"], bands["p95"], alpha=0.15, color="#2a78d6", label="5e-95e pct")
    ax.fill_between(hours, bands["p25"], bands["p75"], alpha=0.3, color="#2a78d6", label="25e-75e pct")
    ax.plot(hours, bands["p50"], color="#2a78d6", linewidth=2, label="Mediaan")
    ax.set_xlabel("Uur van de dag")
    ax.set_ylabel("mmol/L")
    ax.set_xlim(0, 24)
    ax.legend(loc="upper right", fontsize=8)
    fig.tight_layout()

    buf = io.BytesIO()
    fig.savefig(buf, format="png", dpi=150)
    plt.close(fig)
    buf.seek(0)
    return buf.getvalue()


def _add_summary_section(pdf: FPDF, glucose: pd.DataFrame, start, end) -> None:
    mean_mmol = glucose["mmol"].mean()
    tir = tir_breakdown_5band(glucose)
    active_pct = sensor_active_percent(glucose, start, end)

    pdf.set_font("Helvetica", "B", 13)
    pdf.cell(0, 8, "Samenvatting", **_LINE_KWARGS)

    warning = completeness_warning(glucose, start, end)
    if warning:
        pdf.set_font("Helvetica", "BI", 10)
        pdf.multi_cell(0, 5, warning)
        pdf.ln(2)

    pdf.set_font("Helvetica", "", 11)
    pdf.cell(0, 6, f"Sensordekking: {active_pct:.0f}%", **_LINE_KWARGS)
    pdf.cell(0, 6, f"Gemiddelde glucose: {mean_mmol:.1f} mmol/L", **_LINE_KWARGS)
    pdf.cell(0, 6, f"Geschat HbA1c (GMI): {gmi_percent(mean_mmol):.1f}%", **_LINE_KWARGS)
    pdf.cell(0, 6, f"Variabiliteit (%CV): {percent_cv(glucose):.0f}%", **_LINE_KWARGS)
    pdf.ln(2)
    pdf.cell(0, 6, f"Zeer laag (<3.0 mmol/L): {tir['very_low']:.0f}%", **_LINE_KWARGS)
    pdf.cell(0, 6, f"Laag (3.0-3.9 mmol/L): {tir['low']:.0f}%", **_LINE_KWARGS)
    pdf.cell(0, 6, f"In bereik (3.9-10.0 mmol/L): {tir['in_range']:.0f}%", **_LINE_KWARGS)
    pdf.cell(0, 6, f"Hoog (10.0-13.9 mmol/L): {tir['high']:.0f}%", **_LINE_KWARGS)
    pdf.cell(0, 6, f"Zeer hoog (>13.9 mmol/L): {tir['very_high']:.0f}%", **_LINE_KWARGS)
    pdf.ln(4)


def _add_agp_section(pdf: FPDF, glucose: pd.DataFrame) -> None:
    pdf.set_font("Helvetica", "B", 13)
    pdf.cell(0, 8, "AGP profiel", **_LINE_KWARGS)
    png_bytes = _agp_figure_png(glucose)
    pdf.image(io.BytesIO(png_bytes), w=180)
    pdf.ln(4)


def _add_events_section(pdf: FPDF, events_summary: dict[str, dict]) -> None:
    pdf.set_font("Helvetica", "B", 13)
    pdf.cell(0, 8, "Hypo-/hyperevents", **_LINE_KWARGS)
    pdf.set_font("Helvetica", "", 11)
    for label, summary in events_summary.items():
        pdf.cell(
            0,
            6,
            f"{label}: {summary['count']} events, gemiddeld {summary['avg_duration_minutes']:.0f} min, "
            f"{summary['events_per_week']:.1f}/week",
            **_LINE_KWARGS,
        )
    pdf.ln(4)


def build_report_pdf(
    sections: list[str],
    glucose: pd.DataFrame,
    events_summary: dict[str, dict],
    start,
    end,
) -> bytes:
    """Bouw een PDF met de geselecteerde onderdelen.

    `events_summary` bevat vooraf berekende hypo/hyper-samenvattingen (label ->
    resultaat van reporting.summarize_events), zodat deze module geen
    event-detectie hoeft te herhalen.
    """
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Helvetica", "B", 16)
    pdf.cell(0, 10, "Glucoserapport", **_LINE_KWARGS)
    pdf.set_font("Helvetica", "", 11)
    pdf.cell(0, 8, f"Periode: {start.strftime('%d-%m-%Y')} t/m {end.strftime('%d-%m-%Y')}", **_LINE_KWARGS)
    pdf.ln(4)

    if not glucose.empty:
        if SECTION_SUMMARY in sections:
            _add_summary_section(pdf, glucose, start, end)
        if SECTION_AGP in sections:
            _add_agp_section(pdf, glucose)

    if SECTION_EVENTS in sections and events_summary:
        _add_events_section(pdf, events_summary)

    return bytes(pdf.output())