""" 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, 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) 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())