diff --git a/pdf_export.py b/pdf_export.py index 4fd79b2..c32ed9d 100644 --- a/pdf_export.py +++ b/pdf_export.py @@ -21,8 +21,13 @@ from fpdf import FPDF from fpdf.enums import XPos, YPos from reporting import ( + HIGH, + LOW, + VERY_HIGH, + VERY_LOW, agp_percentile_bands, completeness_warning, + detect_events, gmi_percent, percent_cv, sensor_active_percent, @@ -31,12 +36,46 @@ from reporting import ( SECTION_SUMMARY = "Samenvatting" SECTION_AGP = "AGP profiel" +SECTION_DAGOVERZICHT = "Dagoverzicht" SECTION_EVENTS = "Hypo-/hyperevents" -AVAILABLE_SECTIONS = [SECTION_SUMMARY, SECTION_AGP, SECTION_EVENTS] +AVAILABLE_SECTIONS = [SECTION_SUMMARY, SECTION_AGP, SECTION_DAGOVERZICHT, SECTION_EVENTS] _LINE_KWARGS = {"new_x": XPos.LMARGIN, "new_y": YPos.NEXT} +# Zelfde kleuren als het PALETTE["light"] in ui_common.py — bewust hier +# gedupliceerd (5 hex-waarden) in plaats van ui_common.py te importeren, want +# dat zou een streamlit-dependency in deze module trekken die verder bewust +# vrij van UI-framework-imports is (los te unit-testen, zie moduledocstring). +_MUTED = "#898781" +_TIR_BAND_ORDER = ["very_low", "low", "in_range", "high", "very_high"] +_TIR_BAND_LABELS = { + "very_low": "Zeer laag", + "low": "Laag", + "in_range": "In bereik", + "high": "Hoog", + "very_high": "Zeer hoog", +} +_TIR_COLORS = { + "very_low": "#8b1a1a", + "low": "#d03b3b", + "in_range": "#0ca30c", + "high": "#fab219", + "very_high": "#c76f0a", +} +_THRESHOLD_LINES = [VERY_LOW, LOW, HIGH, VERY_HIGH] +DAGOVERZICHT_MAX_DAYS = 14 + + +def _add_threshold_lines(ax) -> None: + """Teken de 4 klinische drempellijnen (3.0/3.9/10.0/13.9 mmol/L) op een matplotlib-as. + + PDF-tegenhanger van ui_common.add_threshold_lines() voor de Plotly-versie + op de dashboardpagina's (gitea #15) — zelfde 4 waarden, zelfde grijstint. + """ + for value in _THRESHOLD_LINES: + ax.axhline(value, color=_MUTED, linewidth=0.7, linestyle=":") + def _agp_figure_png(glucose: pd.DataFrame) -> bytes: bands = agp_percentile_bands(glucose) @@ -45,6 +84,7 @@ def _agp_figure_png(glucose: pd.DataFrame) -> bytes: 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") + _add_threshold_lines(ax) ax.set_xlabel("Uur van de dag") ax.set_ylabel("mmol/L") ax.set_xlim(0, 24) @@ -58,6 +98,69 @@ def _agp_figure_png(glucose: pd.DataFrame) -> bytes: return buf.getvalue() +def _tir_bar_figure_png(tir: dict) -> bytes: + """Gestapelde staafgrafiek van de 5 TIR-banden — PDF-tegenhanger van + ui_common.build_tir_stacked_bar_figure() (gitea #14).""" + fig, ax = plt.subplots(figsize=(7, 1.1)) + left = 0.0 + for band in _TIR_BAND_ORDER: + value = tir[band] + ax.barh(0, value, left=left, color=_TIR_COLORS[band], label=_TIR_BAND_LABELS[band]) + left += value + ax.set_xlim(0, 100) + ax.set_yticks([]) + ax.set_xlabel("%") + ax.legend(loc="upper center", bbox_to_anchor=(0.5, -0.75), ncol=5, fontsize=7, frameon=False) + + buf = io.BytesIO() + # bbox_inches="tight" i.p.v. fig.tight_layout(): de legend zit buiten de + # axes (bbox_to_anchor met negatieve y), waar tight_layout() niet voor + # kan compenseren — savefig's eigen bbox-berekening kan dat wel. + fig.savefig(buf, format="png", dpi=150, bbox_inches="tight") + plt.close(fig) + buf.seek(0) + return buf.getvalue() + + +def _daily_figure_png(day_df: pd.DataFrame, day_label: str) -> bytes: + """Eén dag als kleine lijngrafiek — PDF-tegenhanger van de Dagoverzicht-pagina (gitea #16).""" + hours = day_df["timestamp"].dt.hour + day_df["timestamp"].dt.minute / 60 + fig, ax = plt.subplots(figsize=(7, 1.4)) + ax.plot(hours, day_df["mmol"], color="#2a78d6", linewidth=1.2) + _add_threshold_lines(ax) + ax.set_xlim(0, 24) + ax.set_xticks(range(0, 25, 4)) + ax.set_ylabel("mmol/L", fontsize=8) + ax.set_title(day_label, fontsize=9, loc="left") + ax.tick_params(labelsize=7) + fig.tight_layout() + + buf = io.BytesIO() + fig.savefig(buf, format="png", dpi=150) + plt.close(fig) + buf.seek(0) + return buf.getvalue() + + +def _event_hour_histogram_png(events: pd.DataFrame, color: str) -> bytes: + """Aantal events per uur-van-de-dag — PDF-tegenhanger van render_event_level()'s + histogram op de Hypo/Hyper Events-pagina's (gitea #17, #18).""" + hour_counts = events["start"].dt.hour.value_counts().reindex(range(24), fill_value=0).sort_index() + fig, ax = plt.subplots(figsize=(7, 2)) + ax.bar(hour_counts.index, hour_counts.to_numpy(), color=color) + ax.set_xlabel("Uur van de dag") + ax.set_ylabel("Aantal events") + ax.set_xlim(-0.5, 23.5) + ax.set_xticks(range(0, 24, 2)) + 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) @@ -83,6 +186,9 @@ def _add_summary_section(pdf: FPDF, glucose: pd.DataFrame, start, end) -> None: 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(2) + png_bytes = _tir_bar_figure_png(tir) + pdf.image(io.BytesIO(png_bytes), w=160) pdf.ln(4) @@ -94,7 +200,29 @@ def _add_agp_section(pdf: FPDF, glucose: pd.DataFrame) -> None: pdf.ln(4) -def _add_events_section(pdf: FPDF, events_summary: dict[str, dict]) -> None: +def _add_dagoverzicht_section(pdf: FPDF, glucose: pd.DataFrame) -> None: + """Eén dagelijkse mini-grafiek per kalenderdag (gitea #16), max. de meest + recente DAGOVERZICHT_MAX_DAYS dagen — voor langere periodes zou de PDF + anders onwerkbaar lang worden.""" + pdf.set_font("Helvetica", "B", 13) + pdf.cell(0, 8, "Dagoverzicht", **_LINE_KWARGS) + + df = glucose.copy() + df["date"] = df["timestamp"].dt.date + dates = sorted(df["date"].unique()) + if len(dates) > DAGOVERZICHT_MAX_DAYS: + dates = dates[-DAGOVERZICHT_MAX_DAYS:] + pdf.set_font("Helvetica", "I", 9) + pdf.cell(0, 5, f"Beperkt tot de meest recente {DAGOVERZICHT_MAX_DAYS} dagen.", **_LINE_KWARGS) + + for day in dates: + day_df = df[df["date"] == day] + png_bytes = _daily_figure_png(day_df, day.strftime("%A %d-%m-%Y")) + pdf.image(io.BytesIO(png_bytes), w=180) + pdf.ln(4) + + +def _add_events_section(pdf: FPDF, glucose: pd.DataFrame, 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) @@ -106,6 +234,18 @@ def _add_events_section(pdf: FPDF, events_summary: dict[str, dict]) -> None: f"{summary['events_per_week']:.1f}/week", **_LINE_KWARGS, ) + pdf.ln(2) + + # Alleen Level 1 krijgt een grafiek in het PDF-rapport (gitea #17, #18) — + # geen tabel met losse events, de samenvattende cijfers staan al hierboven. + if not glucose.empty: + hypo_events = detect_events(glucose, LOW, "below") + if not hypo_events.empty: + pdf.image(io.BytesIO(_event_hour_histogram_png(hypo_events, _TIR_COLORS["low"])), w=180) + hyper_events = detect_events(glucose, HIGH, "above") + if not hyper_events.empty: + pdf.image(io.BytesIO(_event_hour_histogram_png(hyper_events, _TIR_COLORS["high"])), w=180) + pdf.ln(4) @@ -135,8 +275,10 @@ def build_report_pdf( _add_summary_section(pdf, glucose, start, end) if SECTION_AGP in sections: _add_agp_section(pdf, glucose) + if SECTION_DAGOVERZICHT in sections: + _add_dagoverzicht_section(pdf, glucose) if SECTION_EVENTS in sections and events_summary: - _add_events_section(pdf, events_summary) + _add_events_section(pdf, glucose, events_summary) return bytes(pdf.output()) diff --git a/tests/test_pdf_export.py b/tests/test_pdf_export.py index 3d3b73d..96b147b 100644 --- a/tests/test_pdf_export.py +++ b/tests/test_pdf_export.py @@ -2,7 +2,14 @@ from datetime import date import pandas as pd -from pdf_export import SECTION_AGP, SECTION_EVENTS, SECTION_SUMMARY, build_report_pdf +from pdf_export import ( + DAGOVERZICHT_MAX_DAYS, + SECTION_AGP, + SECTION_DAGOVERZICHT, + SECTION_EVENTS, + SECTION_SUMMARY, + build_report_pdf, +) def _sample_glucose(): @@ -10,6 +17,15 @@ def _sample_glucose(): return pd.DataFrame({"timestamp": timestamps, "mmol": [6.0 + (i % 5) for i in range(48)]}) +def _glucose_with_hypo_and_hyper_events(): + """3 dagen data met een echte hypo- (<3.9, >=15 min) en hyperepisode (>10.0).""" + timestamps = pd.date_range("2026-01-01", periods=3 * 24 * 12, freq="5min") + values = [7.0] * len(timestamps) + values[10:15] = [3.0] * 5 # 25 min hypo + values[100:106] = [12.0] * 6 # 30 min hyper + return pd.DataFrame({"timestamp": timestamps, "mmol": values}) + + def test_build_report_pdf_produces_valid_pdf_bytes(): glucose = _sample_glucose() events_summary = { @@ -39,3 +55,38 @@ def test_build_report_pdf_handles_no_sections_selected(): glucose = _sample_glucose() pdf_bytes = build_report_pdf([], glucose, {}, date(2026, 1, 1), date(2026, 1, 2)) assert pdf_bytes.startswith(b"%PDF") + + +def test_build_report_pdf_includes_dagoverzicht_section(): + glucose = _sample_glucose() + pdf_bytes = build_report_pdf( + [SECTION_DAGOVERZICHT], glucose, {}, date(2026, 1, 1), date(2026, 1, 2) + ) + assert pdf_bytes.startswith(b"%PDF") + assert len(pdf_bytes) > 500 + + +def test_build_report_pdf_caps_dagoverzicht_at_max_days(): + timestamps = pd.date_range("2026-01-01", periods=(DAGOVERZICHT_MAX_DAYS + 10) * 24, freq="1h") + glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [7.0] * len(timestamps)}) + pdf_bytes = build_report_pdf( + [SECTION_DAGOVERZICHT], + glucose, + {}, + timestamps[0].date(), + timestamps[-1].date(), + ) + assert pdf_bytes.startswith(b"%PDF") + + +def test_build_report_pdf_draws_hypo_and_hyper_charts_when_events_present(): + glucose = _glucose_with_hypo_and_hyper_events() + events_summary = { + "Hypo Level 1": {"count": 1, "avg_duration_minutes": 25.0, "events_per_week": 2.3}, + "Hyper Level 1": {"count": 1, "avg_duration_minutes": 30.0, "events_per_week": 2.3}, + } + pdf_bytes = build_report_pdf( + [SECTION_EVENTS], glucose, events_summary, date(2026, 1, 1), date(2026, 1, 4) + ) + assert pdf_bytes.startswith(b"%PDF") + assert len(pdf_bytes) > 500