from reportlab.lib.pagesizes import A3, landscape
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm, mm
from reportlab.platypus import (
    SimpleDocTemplate, Table, TableStyle, Paragraph,
    Spacer, HRFlowable, KeepTogether
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT
from reportlab.platypus import PageBreak

OUTPUT = "/home/daytona/workspace/gpc-gnb-chart/GPC_vs_GNB_Antibiotic_Susceptibility.pdf"

# ── Colours ──────────────────────────────────────────────────────────────────
DARK_BLUE   = colors.HexColor("#1a3a5c")
MID_BLUE    = colors.HexColor("#2e6da4")
LIGHT_BLUE  = colors.HexColor("#d0e4f7")
PALE_BLUE   = colors.HexColor("#eaf3fb")

DARK_RED    = colors.HexColor("#8b1a1a")
MID_RED     = colors.HexColor("#c0392b")
LIGHT_RED   = colors.HexColor("#fdd5d0")
PALE_RED    = colors.HexColor("#fff0ee")

DARK_GREEN  = colors.HexColor("#1a5c2e")
LIGHT_GREEN = colors.HexColor("#d4edda")

DARK_ORANGE = colors.HexColor("#7d4e00")
LIGHT_ORANGE= colors.HexColor("#fff3cd")

GREY_HEADER = colors.HexColor("#2c3e50")
LIGHT_GREY  = colors.HexColor("#f2f4f6")
WHITE       = colors.white
BLACK       = colors.black

# Susceptibility cell colours
S_COLOR  = colors.HexColor("#27ae60")   # Susceptible  - green
R_COLOR  = colors.HexColor("#e74c3c")   # Resistant    - red
V_COLOR  = colors.HexColor("#f39c12")   # Variable     - amber
I_COLOR  = colors.HexColor("#8e44ad")   # Intermediate - purple
NA_COLOR = colors.HexColor("#95a5a6")   # N/A          - grey

doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=landscape(A3),
    leftMargin=1.2*cm, rightMargin=1.2*cm,
    topMargin=1.5*cm,  bottomMargin=1.5*cm,
    title="GPC vs GNB Antibiotic Susceptibility Chart",
    author="Orris Medical Reference"
)

styles = getSampleStyleSheet()

def style(name, **kw):
    s = ParagraphStyle(name, parent=styles["Normal"], **kw)
    return s

title_style = style("Title2", fontSize=20, fontName="Helvetica-Bold",
                    textColor=WHITE, alignment=TA_CENTER, spaceAfter=4)
subtitle_style = style("Sub", fontSize=11, fontName="Helvetica",
                       textColor=colors.HexColor("#ccddee"), alignment=TA_CENTER)
section_style = style("Sec", fontSize=13, fontName="Helvetica-Bold",
                      textColor=WHITE, alignment=TA_CENTER)
cell_hdr = style("CH", fontSize=8.5, fontName="Helvetica-Bold",
                 textColor=WHITE, alignment=TA_CENTER, leading=10)
cell_body = style("CB", fontSize=7.5, fontName="Helvetica",
                  textColor=BLACK, alignment=TA_LEFT, leading=9)
cell_center = style("CC", fontSize=7.5, fontName="Helvetica",
                    textColor=BLACK, alignment=TA_CENTER, leading=9)
legend_style = style("Leg", fontSize=8, fontName="Helvetica",
                     textColor=BLACK, alignment=TA_LEFT)
note_style = style("Note", fontSize=7.5, fontName="Helvetica-Oblique",
                   textColor=colors.HexColor("#555555"), alignment=TA_CENTER)

# ── Helper: coloured susceptibility cell ─────────────────────────────────────
def sc(text, bg=None):
    """Return a (Paragraph, bg_color) tuple for susceptibility cells."""
    mapping = {
        "S":  (S_COLOR,  WHITE, "S"),
        "R":  (R_COLOR,  WHITE, "R"),
        "V":  (V_COLOR,  WHITE, "V"),
        "I":  (I_COLOR,  WHITE, "I"),
        "S*": (colors.HexColor("#1e8449"), WHITE, "S*"),
        "R*": (colors.HexColor("#b03a2e"), WHITE, "R*"),
        "V*": (colors.HexColor("#d68910"), WHITE, "V*"),
        "-":  (NA_COLOR, WHITE, "-"),
    }
    if text in mapping:
        bg_col, fg_col, label = mapping[text]
        p = Paragraph(f"<b>{label}</b>",
                      style("SC", fontSize=8, fontName="Helvetica-Bold",
                            textColor=fg_col, alignment=TA_CENTER, leading=10))
        return p, bg_col
    p = Paragraph(text, cell_center)
    return p, (bg if bg else WHITE)

# ── Data definition ──────────────────────────────────────────────────────────
# Columns: Antibiotic | Class | S.aureus(MSSA) | S.aureus(MRSA) | S.pyogenes |
#          S.pneumoniae | E.faecalis | E.faecium(VRE) ||
#          E.coli | Klebsiella | Pseudomonas | Acinetobacter | Salmonella | H.influenzae

# Key: S=Susceptible, R=Resistant, V=Variable, I=Intermediate, -=Not applicable / not used
# S* / V* / R* = with caveats (footnote)

ABX_DATA = [
    # [Antibiotic, Drug Class,
    #   MSSA, MRSA, S.pyo, S.pneu, E.fae, E.fae(VRE),
    #   E.coli, Klebsiella, Pseudomonas, Acinetobacter, Salmonella, H.influenzae]
    # ── Beta-lactams ──────────────────────────────────────────────
    ["Penicillin G", "Natural Penicillin",
     "S","R","S","V*","S","-",
     "R","R","R","R","R","R"],
    ["Amoxicillin", "Aminopenicillin",
     "S","R","S","S","S","-",
     "V","R","R","R","V","V"],
    ["Amoxicillin-Clavulanate", "Beta-lactam + Inhibitor",
     "S","R","S","S","S","-",
     "S","S","R","V","V","S"],
    ["Nafcillin / Oxacillin", "Antistaphylococcal PCN",
     "S","R","S","S","R","R",
     "R","R","R","R","R","R"],
    ["Piperacillin-Tazobactam", "Extended PCN + Inhibitor",
     "S","R","S","S","S","-",
     "S","S","V","V","S","S"],
    ["Cefazolin (1st gen)", "1st-Gen Cephalosporin",
     "S","R","S","S","R","R",
     "S","S","R","R","V","V"],
    ["Ceftriaxone (3rd gen)", "3rd-Gen Cephalosporin",
     "S","R","S","S","R","R",
     "S","S","R","R","S","S"],
    ["Ceftazidime (3rd gen)", "3rd-Gen Cephalosporin (anti-Pseudo)",
     "R","R","R","R","R","R",
     "S","S","S","V","S","S"],
    ["Cefepime (4th gen)", "4th-Gen Cephalosporin",
     "S","R","S","S","R","R",
     "S","S","S","V","S","S"],
    ["Ceftaroline (5th gen)", "5th-Gen Cephalosporin (anti-MRSA)",
     "S","S","S","S","R","R",
     "S","S","R","R","S","S"],
    ["Imipenem/Meropenem", "Carbapenem",
     "S","R","S","S","S","R",
     "S","S","V","V","S","S"],
    ["Ertapenem", "Carbapenem (no Pseudo)",
     "S","R","S","S","S","R",
     "S","S","R","V","S","S"],
    ["Aztreonam", "Monobactam",
     "R","R","R","R","R","R",
     "S","S","S","V","S","S"],
    # ── Glycopeptides ──────────────────────────────────────────────
    ["Vancomycin", "Glycopeptide",
     "S","S","S","S","S","R",
     "R","R","R","R","R","R"],
    ["Teicoplanin", "Glycopeptide",
     "S","S","S","S","S","R",
     "R","R","R","R","R","R"],
    # ── Lipopeptide ────────────────────────────────────────────────
    ["Daptomycin", "Lipopeptide",
     "S","S","S","S","S","V",
     "R","R","R","R","R","R"],
    # ── Oxazolidinones ─────────────────────────────────────────────
    ["Linezolid", "Oxazolidinone",
     "S","S","S","S","S","S",
     "R","R","R","R","R","R"],
    ["Tedizolid", "Oxazolidinone (2nd gen)",
     "S","S","S","S","S","S",
     "R","R","R","R","R","R"],
    # ── Aminoglycosides ────────────────────────────────────────────
    ["Gentamicin", "Aminoglycoside",
     "S","V","V","R","V*","V*",
     "S","S","S","V","V","V"],
    ["Amikacin", "Aminoglycoside",
     "S","V","V","R","V*","V*",
     "S","S","S","V","V","S"],
    # ── Fluoroquinolones ───────────────────────────────────────────
    ["Ciprofloxacin", "Fluoroquinolone",
     "S","R","V","R","V","V",
     "S","S","S","V","V","S"],
    ["Levofloxacin", "Respiratory FQ",
     "S","R","S","S","S","V",
     "S","S","S","V","S","S"],
    ["Moxifloxacin", "Respiratory FQ",
     "S","R","S","S","S","V",
     "S","S","R","V","S","S"],
    # ── Macrolides ─────────────────────────────────────────────────
    ["Azithromycin", "Macrolide",
     "V","R","S","V","R","R",
     "R","R","R","R","V","S"],
    ["Erythromycin", "Macrolide",
     "V","R","S","V","R","R",
     "R","R","R","R","R","R"],
    # ── Tetracyclines ──────────────────────────────────────────────
    ["Doxycycline", "Tetracycline",
     "S","V","S","S","V","V",
     "V","V","R","V","V","R"],
    ["Tigecycline", "Glycylcycline",
     "S","S","S","S","S","S",
     "S","S","R","S","S","S"],
    # ── Folate Inhibitors ──────────────────────────────────────────
    ["TMP-SMX", "Sulfonamide Combo",
     "S","V","V","V","R","R",
     "V","V","R","V","V","V"],
    # ── Other ──────────────────────────────────────────────────────
    ["Clindamycin", "Lincosamide",
     "S","V","S","S","R","R",
     "R","R","R","R","R","R"],
    ["Metronidazole", "Nitroimidazole",
     "R","R","R","R","R","R",
     "R","R","R","R","R","R"],
    ["Rifampicin", "Rifamycin",
     "S","S","S","S","V","V",
     "R","R","R","R","R","R"],
    ["Colistin / Polymyxin B", "Polymyxin",
     "R","R","R","R","R","R",
     "S","S","S","S","S","R"],
    ["Nitrofurantoin", "Nitrofuran",
     "S","S","S","V","S","R",
     "S","V","R","R","R","R"],
    ["Fosfomycin", "Phosphonic acid",
     "S","S","V","V","S","V",
     "S","V","V","R","V","V"],
]

# Column widths (landscape A3 = 420 x 297mm, usable ~397mm)
# Antibiotic(90), Class(80), then 12 organism cols each 19mm => 228mm => total 398mm
COL_W = [90, 80] + [19]*12
page_w = sum(COL_W)

# ── Build table rows ─────────────────────────────────────────────────────────
def hdr(txt, bg, fg=WHITE, size=8):
    return Paragraph(f"<b>{txt}</b>",
                     style("H", fontSize=size, fontName="Helvetica-Bold",
                           textColor=fg, alignment=TA_CENTER, leading=9))

# Row 0: mega header
R0 = [
    hdr("ANTIBIOTIC", GREY_HEADER, size=9),
    hdr("DRUG CLASS", GREY_HEADER, size=9),
    hdr("GRAM-POSITIVE COCCI (GPC)", MID_BLUE, size=10),
    Paragraph(""), Paragraph(""), Paragraph(""), Paragraph(""), Paragraph(""),
    hdr("GRAM-NEGATIVE BACILLI (GNB)", MID_RED, size=10),
    Paragraph(""), Paragraph(""), Paragraph(""), Paragraph(""), Paragraph(""),
]

# Row 1: organism names
org_names_gpc = ["S. aureus\n(MSSA)", "S. aureus\n(MRSA)", "S. pyogenes\n(GAS)",
                 "S. pneumoniae", "E. faecalis", "E. faecium\n(VRE)"]
org_names_gnb = ["E. coli", "Klebsiella\npneumoniae", "Pseudomonas\naeruginosa",
                 "Acinetobacter\nbaumannii", "Salmonella\nspp.", "H. influenzae"]

R1 = [hdr("ANTIBIOTIC", DARK_BLUE, size=8),
      hdr("CLASS", DARK_BLUE, size=8)]
for n in org_names_gpc:
    R1.append(hdr(n, MID_BLUE, size=7.5))
for n in org_names_gnb:
    R1.append(hdr(n, MID_RED, size=7.5))

# Data rows
data_rows = []
style_commands = []
row_idx = 2  # rows 0,1 are headers

for i, row in enumerate(ABX_DATA):
    abx, cls = row[0], row[1]
    sus_vals = row[2:]  # 12 values

    tr = [
        Paragraph(f"<b>{abx}</b>",
                  style("A", fontSize=8, fontName="Helvetica-Bold",
                        textColor=DARK_BLUE, alignment=TA_LEFT, leading=10)),
        Paragraph(cls,
                  style("C", fontSize=7.5, fontName="Helvetica-Oblique",
                        textColor=colors.HexColor("#333333"), alignment=TA_LEFT, leading=9)),
    ]
    for j, val in enumerate(sus_vals):
        p, bg = sc(val)
        tr.append(p)
        col = 2 + j
        bg_key = f"bg_{row_idx}_{col}"
        style_commands.append(("BACKGROUND", (col, row_idx), (col, row_idx), bg))

    row_bg = PALE_BLUE if i % 2 == 0 else WHITE
    style_commands.append(("BACKGROUND", (0, row_idx), (1, row_idx), row_bg))
    data_rows.append(tr)
    row_idx += 1

all_rows = [R0, R1] + data_rows

# ── Table style ──────────────────────────────────────────────────────────────
base_style = [
    # Spanning
    ("SPAN", (2, 0), (7, 0)),    # GPC header spans cols 2-7
    ("SPAN", (8, 0), (13, 0)),   # GNB header spans cols 8-13
    ("SPAN", (0, 0), (0, 1)),    # Antibiotic header spans rows 0-1
    ("SPAN", (1, 0), (1, 1)),    # Class header spans rows 0-1

    # Fonts / alignment
    ("VALIGN", (0, 0), (-1, -1), "MIDDLE"),
    ("ALIGN",  (0, 0), (-1, -1), "CENTER"),
    ("ALIGN",  (0, 2), (1, -1),  "LEFT"),

    # Grid
    ("GRID",      (0, 0), (-1, -1), 0.4, colors.HexColor("#aaaaaa")),
    ("LINEBELOW", (0, 1), (-1, 1),  1.2, DARK_BLUE),

    # Row 0 backgrounds
    ("BACKGROUND", (0, 0), (1, 1),   GREY_HEADER),
    ("BACKGROUND", (2, 0), (7, 0),   MID_BLUE),
    ("BACKGROUND", (2, 1), (7, 1),   DARK_BLUE),
    ("BACKGROUND", (8, 0), (13, 0),  MID_RED),
    ("BACKGROUND", (8, 1), (13, 1),  DARK_RED),

    # Vertical separator between GPC and GNB
    ("LINEAFTER", (7, 0), (7, -1), 2, GREY_HEADER),

    # Row heights
    ("ROWBACKGROUNDS", (0, 2), (-1, -1), [PALE_BLUE, WHITE]),

    # Padding
    ("TOPPADDING",    (0, 0), (-1, -1), 4),
    ("BOTTOMPADDING", (0, 0), (-1, -1), 4),
    ("LEFTPADDING",   (0, 0), (-1, -1), 3),
    ("RIGHTPADDING",  (0, 0), (-1, -1), 3),
]

ts = TableStyle(base_style + style_commands)

t = Table(all_rows, colWidths=COL_W, repeatRows=2)
t.setStyle(ts)

# ── Legend ────────────────────────────────────────────────────────────────────
legend_items = [
    (S_COLOR,  "S  = Susceptible (typically effective)"),
    (R_COLOR,  "R  = Resistant (not effective)"),
    (V_COLOR,  "V  = Variable (depends on strain/resistance pattern)"),
    (I_COLOR,  "I   = Intermediate / reduced susceptibility"),
    (NA_COLOR, "-   = Not applicable / not used clinically"),
]

def legend_row(col, label):
    box = Table([[""]], colWidths=[12], rowHeights=[12])
    box.setStyle(TableStyle([("BACKGROUND",(0,0),(0,0),col),
                              ("GRID",(0,0),(0,0),0.5,colors.grey)]))
    return [box, Paragraph(f"  {label}", legend_style)]

leg_data = [legend_row(c, l) for c, l in legend_items]
# Build as a single-row horizontal legend
leg_cells = []
for c, l in legend_items:
    box = Table([[""]], colWidths=[10], rowHeights=[10])
    box.setStyle(TableStyle([("BACKGROUND",(0,0),(0,0),c),
                              ("GRID",(0,0),(0,0),0.5,colors.grey)]))
    leg_cells.append(box)
    leg_cells.append(Paragraph(f" {l}   ", legend_style))

leg_table = Table([leg_cells], colWidths=([12,120]*5))
leg_table.setStyle(TableStyle([
    ("VALIGN",(0,0),(-1,-1),"MIDDLE"),
    ("ALIGN", (0,0),(-1,-1),"LEFT"),
    ("TOPPADDING",(0,0),(-1,-1),3),
    ("BOTTOMPADDING",(0,0),(-1,-1),3),
]))

notes = [
    "* V for penicillin against S. pneumoniae: susceptibility varies by site (meningitis requires higher MIC breakpoints).",
    "* Gentamicin/Amikacin used synergistically with beta-lactams for enterococcal endocarditis (not monotherapy).",
    "* MRSA = Methicillin-Resistant S. aureus; VRE = Vancomycin-Resistant Enterococcus; ESBL/CRKP strains may show further resistance.",
    "* Pseudomonas aeruginosa is intrinsically resistant to many antibiotics; always verify local antibiogram.",
    "* This chart reflects general/typical susceptibility patterns. Always consult local antibiogram and culture/sensitivity results.",
]

# ── Assemble document ─────────────────────────────────────────────────────────
elements = []

# Page title banner
title_table = Table(
    [[Paragraph("GPC vs GNB", title_style)],
     [Paragraph("Comparative Antibiotic Susceptibility Reference Chart", subtitle_style)],
     [Paragraph("Gram-Positive Cocci (GPC)  |  Gram-Negative Bacilli (GNB)  •  Orris Medical Reference 2026", subtitle_style)]],
    colWidths=[page_w]
)
title_table.setStyle(TableStyle([
    ("BACKGROUND", (0,0),(0,2), DARK_BLUE),
    ("TOPPADDING", (0,0),(0,2), 6),
    ("BOTTOMPADDING",(0,0),(0,2), 6),
    ("LEFTPADDING", (0,0),(0,2), 8),
    ("RIGHTPADDING",(0,0),(0,2), 8),
]))

elements.append(title_table)
elements.append(Spacer(1, 6))
elements.append(t)
elements.append(Spacer(1, 6))

# Legend box
leg_outer = Table(
    [[Paragraph("<b>LEGEND:</b>", style("LT", fontSize=8.5, fontName="Helvetica-Bold",
                                        textColor=GREY_HEADER, alignment=TA_LEFT)),
      leg_table]],
    colWidths=[55, page_w - 55]
)
leg_outer.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(-1,-1), LIGHT_GREY),
    ("BOX",(0,0),(-1,-1), 0.8, colors.HexColor("#aaaaaa")),
    ("VALIGN",(0,0),(-1,-1),"MIDDLE"),
    ("TOPPADDING",(0,0),(-1,-1),5),
    ("BOTTOMPADDING",(0,0),(-1,-1),5),
    ("LEFTPADDING",(0,0),(-1,-1),6),
]))
elements.append(leg_outer)
elements.append(Spacer(1, 5))

for note in notes:
    elements.append(Paragraph(f"<i>{note}</i>", note_style))
    elements.append(Spacer(1, 2))

doc.build(elements)
print(f"PDF created: {OUTPUT}")

from reportlab.lib.pagesizes import A3, landscape
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm, mm
from reportlab.platypus import (
    SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT

OUTPUT = "/home/daytona/workspace/gpc-gnb-chart/GNB_Full_Taxonomy_Table.pdf"

# ── Palette ──────────────────────────────────────────────────────────────────
NAVY       = colors.HexColor("#0d2b45")
BLUE_H     = colors.HexColor("#1a5276")
BLUE_L     = colors.HexColor("#d6eaf8")
BLUE_P     = colors.HexColor("#eaf4fb")

RED_H      = colors.HexColor("#922b21")
RED_L      = colors.HexColor("#fadbd8")
RED_P      = colors.HexColor("#fef9f9")

GREEN_H    = colors.HexColor("#1e8449")
GREEN_L    = colors.HexColor("#d5f5e3")
GREEN_P    = colors.HexColor("#f0faf4")

ORANGE_H   = colors.HexColor("#784212")
ORANGE_L   = colors.HexColor("#fdebd0")
ORANGE_P   = colors.HexColor("#fef9f4")

PURPLE_H   = colors.HexColor("#4a235a")
PURPLE_L   = colors.HexColor("#e8daef")
PURPLE_P   = colors.HexColor("#faf5fc")

TEAL_H     = colors.HexColor("#0e6655")
TEAL_L     = colors.HexColor("#d1f2eb")
TEAL_P     = colors.HexColor("#f0faf8")

GREY_H     = colors.HexColor("#2c3e50")
GREY_L     = colors.HexColor("#f2f3f4")
WHITE      = colors.white
BLACK      = colors.black

def st(name, **kw):
    base = getSampleStyleSheet()["Normal"]
    return ParagraphStyle(name, parent=base, **kw)

# Paragraph styles
TH = st("TH", fontSize=8, fontName="Helvetica-Bold",
        textColor=WHITE, alignment=TA_CENTER, leading=10)
TD_L = st("TDL", fontSize=7.5, fontName="Helvetica",
          textColor=BLACK, alignment=TA_LEFT, leading=9)
TD_I = st("TDI", fontSize=7.5, fontName="Helvetica-Oblique",
          textColor=colors.HexColor("#1a3a5c"), alignment=TA_LEFT, leading=9)
TD_C = st("TDC", fontSize=7.5, fontName="Helvetica",
          textColor=BLACK, alignment=TA_CENTER, leading=9)
SEC_H = st("SEC", fontSize=9.5, fontName="Helvetica-Bold",
           textColor=WHITE, alignment=TA_CENTER, leading=12)
NOTE = st("NOTE", fontSize=7, fontName="Helvetica-Oblique",
          textColor=colors.HexColor("#555555"), alignment=TA_LEFT, leading=9)

def p(text, style): return Paragraph(text, style)
def ph(text): return p(text, TH)
def pl(text): return p(text, TD_L)
def pi(text): return p(text, TD_I)
def pc(text): return p(text, TD_C)
def pb(text): return p(f"<b>{text}</b>", TD_L)

# ── Column widths (landscape A3 usable ~397mm) ───────────────────────────────
# Group | Phylum | Class | Order | Family | Species | Key Disease
CW = [38, 45, 60, 52, 58, 65, 110]   # mm
# total = 428 → slightly over; reduce
CW = [35, 42, 58, 50, 55, 62, 108]   # ≈ 410mm

# ── Header row ────────────────────────────────────────────────────────────────
HDR = [ph("GROUP"), ph("PHYLUM"), ph("CLASS"),
       ph("ORDER"), ph("FAMILY"), ph("SPECIES"), ph("KEY DISEASE")]

# ── Section header helper ─────────────────────────────────────────────────────
def sec(label, bg, n_cols=7):
    row = [p(f"<b>{label}</b>", SEC_H)] + [p("", SEC_H)] * (n_cols - 1)
    return row, bg

# ── Data ──────────────────────────────────────────────────────────────────────
# Each tuple: (group, phylum, class_, order, family, species_italic, disease)
# ─── 1. Enterobacteriaceae ────────────────────────────────────────────────────
ENTERO = [
    ("Enteric\nFermenters", "Pseudomonadota\n(Proteobacteria)", "Gamma-\nproteobacteria",
     "Enterobacterales", "Enterobacteriaceae",
     "Escherichia coli", "UTI, neonatal meningitis, diarrhea (ETEC/EHEC), HUS (O157:H7)"),
    ("", "", "", "", "",
     "Klebsiella pneumoniae", "Hospital-acquired pneumonia, UTI, liver abscess; ESBL/CRKP strains"),
    ("", "", "", "", "",
     "Klebsiella oxytoca", "UTI, bacteremia; ESBL-producing strains"),
    ("", "", "", "", "",
     "Proteus mirabilis", "UTI, staghorn kidney calculi; swarming, urease+"),
    ("", "", "", "", "",
     "Proteus vulgaris", "UTI, wound infections; indole+"),
    ("", "", "", "", "",
     "Morganella morganii", "UTI, wound infections; nosocomial"),
    ("", "", "", "", "",
     "Providencia stuartii", "UTI in catheterised patients; aminoglycoside-resistant"),
    ("", "", "", "", "",
     "Enterobacter cloacae", "Nosocomial pneumonia, UTI, bacteremia; AmpC β-lactamase"),
    ("", "", "", "", "",
     "Enterobacter aerogenes\n(Klebsiella aerogenes)", "Hospital infections; AmpC producer"),
    ("", "", "", "", "",
     "Serratia marcescens", "Hospital pneumonia, UTI; red pigment (prodigiosin); IV drug users"),
    ("", "", "", "", "",
     "Citrobacter freundii", "UTI, neonatal meningitis; ESBL producer"),
    ("", "", "", "", "",
     "Citrobacter koseri", "Neonatal brain abscess; meningitis risk"),
    ("", "", "", "", "",
     "Hafnia alvei", "Rare opportunist; gastroenteritis"),
]

SALMONELLA = [
    ("Salmonella /\nShigella\n(Enteric)", "Pseudomonadota", "Gamma-\nproteobacteria",
     "Enterobacterales", "Enterobacteriaceae",
     "Salmonella typhi", "Typhoid fever (enteric fever); rose spots, hepatosplenomegaly"),
    ("", "", "", "", "",
     "Salmonella paratyphi A/B/C", "Paratyphoid fever"),
    ("", "", "", "", "",
     "Salmonella enteritidis", "Foodborne gastroenteritis (poultry/eggs)"),
    ("", "", "", "", "",
     "Salmonella typhimurium", "Foodborne gastroenteritis; bacteremia in sickle cell"),
    ("", "", "", "", "",
     "Shigella dysenteriae", "Severe bloody dysentery; Shiga toxin; HUS risk"),
    ("", "", "", "", "",
     "Shigella flexneri", "Bacillary dysentery; most common in developing countries"),
    ("", "", "", "", "",
     "Shigella sonnei", "Mild diarrhea; most common in developed countries"),
    ("", "", "", "", "",
     "Shigella boydii", "Diarrhea; endemic in Indian subcontinent"),
]

YERSINIA = [
    ("Yersinia", "Pseudomonadota", "Gamma-\nproteobacteria",
     "Enterobacterales", "Yersiniaceae",
     "Yersinia pestis", "PLAGUE: bubonic / pneumonic / septicemic; bioterrorism agent"),
    ("", "", "", "", "",
     "Yersinia enterocolitica", "Enterocolitis, mesenteric adenitis (mimics appendicitis)"),
    ("", "", "", "", "",
     "Yersinia pseudotuberculosis", "Mesenteric adenitis; Kawasaki-like syndrome in children"),
]

# ─── 2. Non-fermenters ────────────────────────────────────────────────────────
NONFERMENT = [
    ("Non-\nFermentative\nGNB", "Pseudomonadota", "Gamma-\nproteobacteria",
     "Pseudomonadales", "Pseudomonadaceae",
     "Pseudomonas aeruginosa", "Burn/wound infections, VAP, CF lung disease, hot-tub folliculitis; oxidase+, pyocyanin"),
    ("", "", "", "", "Pseudomonadaceae",
     "Pseudomonas fluorescens", "Rare opportunist; blood product contamination"),
    ("", "", "Gamma-\nproteobacteria",
     "Pseudomonadales", "Moraxellaceae",
     "Acinetobacter baumannii", "VAP, wound infections; CRAB strains; survives on dry surfaces"),
    ("", "", "", "", "Moraxellaceae",
     "Acinetobacter lwoffii", "Meningitis, bacteremia; rarely pathogenic"),
    ("", "", "Xanthomonadetes",
     "Xanthomonadales", "Xanthomonadaceae",
     "Stenotrophomonas maltophilia", "VAP in ICU, CF; intrinsically carbapenem-resistant; TMP-SMX"),
    ("", "", "Beta-\nproteobacteria",
     "Burkholderiales", "Burkholderiaceae",
     "Burkholderia cepacia complex", "CF lung colonisation; multiple genomovars; hard to treat"),
    ("", "", "", "Burkholderiales", "Burkholderiaceae",
     "Burkholderia pseudomallei", "Melioidosis; SE Asia/N. Australia; mimics TB"),
]

# ─── 3. Fastidious GNB ───────────────────────────────────────────────────────
FASTIDIOUS = [
    ("Fastidious\nGNB", "Pseudomonadota", "Gamma-\nproteobacteria",
     "Pasteurellales", "Pasteurellaceae",
     "Haemophilus influenzae", "Meningitis (type b), epiglottitis, otitis media; requires X & V factors"),
    ("", "", "", "Pasteurellales", "Pasteurellaceae",
     "Haemophilus ducreyi", "Chancroid (painful genital ulcer); STI"),
    ("", "", "", "Pasteurellales", "Pasteurellaceae",
     "Pasteurella multocida", "Animal bite wound infections (cat/dog); cellulitis"),
    ("", "", "", "Legionellales", "Legionellaceae",
     "Legionella pneumophila", "Legionnaire's disease (severe pneumonia); Pontiac fever; water systems"),
    ("", "", "Beta-\nproteobacteria",
     "Burkholderiales", "Alcaligenaceae",
     "Bordetella pertussis", "Whooping cough; pertussis toxin → lymphocytosis"),
    ("", "", "", "Burkholderiales", "Alcaligenaceae",
     "Bordetella parapertussis", "Milder pertussis-like illness"),
    ("", "", "Alpha-\nproteobacteria",
     "Rhizobiales", "Brucellaceae",
     "Brucella melitensis", "Brucellosis (undulant fever); goats; undulating fever"),
    ("", "", "", "Rhizobiales", "Brucellaceae",
     "Brucella abortus", "Brucellosis; cattle; occupational disease"),
    ("", "", "Gamma-\nproteobacteria",
     "Thiotrichales", "Francisellaceae",
     "Francisella tularensis", "Tularemia (rabbit fever); extremely infectious; bioterrorism agent"),
    ("", "", "Alpha-\nproteobacteria",
     "Rhizobiales", "Bartonellaceae",
     "Bartonella henselae", "Cat scratch disease, bacillary angiomatosis (HIV patients)"),
    ("", "", "", "Rhizobiales", "Bartonellaceae",
     "Bartonella quintana", "Trench fever; bacillary angiomatosis in homeless"),
]

# ─── 4. Curved/Microaerophilic ────────────────────────────────────────────────
CURVED = [
    ("Curved /\nMicroaero-\nphilic GNB", "Pseudomonadota", "Epsilon-\nproteobacteria",
     "Campylobacterales", "Campylobacteraceae",
     "Campylobacter jejuni", "Most common bacterial diarrhea worldwide; Guillain-Barré post-infection"),
    ("", "", "", "Campylobacterales", "Campylobacteraceae",
     "Campylobacter fetus", "Bacteremia; meningitis in immunocompromised & elderly"),
    ("", "", "", "Campylobacterales", "Helicobacteraceae",
     "Helicobacter pylori", "Peptic ulcer disease, gastric cancer, MALT lymphoma; urease+"),
    ("", "", "Gamma-\nproteobacteria",
     "Vibrionales", "Vibrionaceae",
     "Vibrio cholerae (O1/O139)", "Cholera (rice-water diarrhea); massive fluid loss"),
    ("", "", "", "Vibrionales", "Vibrionaceae",
     "Vibrio parahaemolyticus", "Seafood-associated gastroenteritis; halophile"),
    ("", "", "", "Vibrionales", "Vibrionaceae",
     "Vibrio vulnificus", "Septicemia from raw oysters; fatal in liver disease"),
]

# ─── 5. GN Cocci/Coccobacilli ────────────────────────────────────────────────
GNCOC = [
    ("GN Cocci /\nCoccobacilli", "Pseudomonadota", "Beta-\nproteobacteria",
     "Neisseriales", "Neisseriaceae",
     "Neisseria meningitidis", "Bacterial meningitis, Waterhouse-Friderichsen syndrome; capsule serogroups A,B,C,W,Y"),
    ("", "", "", "Neisseriales", "Neisseriaceae",
     "Neisseria gonorrhoeae", "Gonorrhea, PID, neonatal ophthalmia, disseminated GC infection"),
    ("", "", "Gamma-\nproteobacteria",
     "Pseudomonadales", "Moraxellaceae",
     "Moraxella catarrhalis", "Otitis media, sinusitis, COPD exacerbation; β-lactamase+"),
]

# ─── 6. Anaerobic GNB ────────────────────────────────────────────────────────
ANAEROB = [
    ("Anaerobic\nGNB", "Bacteroidota\n(Bacteroidetes)", "Bacteroidia",
     "Bacteroidales", "Bacteroidaceae",
     "Bacteroides fragilis", "Intra-abdominal infections, abscesses; most common anaerobe in clinical specimens"),
    ("", "", "", "Bacteroidales", "Prevotellaceae",
     "Prevotella melaninogenica", "Oral infections, aspiration pneumonia, brain abscess"),
    ("", "", "", "Bacteroidales", "Porphyromonadaceae",
     "Porphyromonas gingivalis", "Periodontal disease; implicated in cardiovascular disease"),
    ("", "Fusobacteriota\n(Fusobacteria)", "Fusobacteriia",
     "Fusobacteriales", "Fusobacteriaceae",
     "Fusobacterium nucleatum", "Oral infections, Lemierre syndrome, colorectal cancer association"),
]

# ── Build PDF ─────────────────────────────────────────────────────────────────
doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=landscape(A3),
    leftMargin=1.0*cm, rightMargin=1.0*cm,
    topMargin=1.3*cm, bottomMargin=1.3*cm,
    title="GNB Full Taxonomy Table",
    author="Orris Medical Reference"
)

def build_section(label, bg_h, bg_l, bg_p, data_rows):
    """Returns list of table row lists for one section."""
    rows = []
    # Section header spanning all 7 cols
    sec_row = [p(f"<b>  {label}</b>",
                 st("SH", fontSize=9, fontName="Helvetica-Bold",
                    textColor=WHITE, alignment=TA_LEFT, leading=11))]
    sec_row += [p("", TH)] * 6
    rows.append(("SEC", sec_row, bg_h))

    for i, (grp, phyl, cls, ord_, fam, spp, dis) in enumerate(data_rows):
        row = [
            pb(grp) if grp else p("", TD_L),
            pc(phyl) if phyl else p("", TD_C),
            pc(cls) if cls else p("", TD_C),
            pc(ord_) if ord_ else p("", TD_C),
            pc(fam) if fam else p("", TD_C),
            pi(spp),
            pl(dis),
        ]
        bg = bg_l if i % 2 == 0 else bg_p
        rows.append(("DATA", row, bg))
    return rows

sections = [
    ("GROUP 1 · ENTEROBACTERIACEAE  (Enteric Fermenters + Salmonella/Shigella + Yersinia)",
     BLUE_H, BLUE_L, BLUE_P,
     ENTERO + SALMONELLA + YERSINIA),
    ("GROUP 2 · NON-FERMENTATIVE GNB  (Environmental / Opportunistic)",
     RED_H, RED_L, RED_P,
     NONFERMENT),
    ("GROUP 3 · FASTIDIOUS GNB  (Special Growth Requirements)",
     ORANGE_H, ORANGE_L, ORANGE_P,
     FASTIDIOUS),
    ("GROUP 4 · CURVED / MICROAEROPHILIC GNB",
     PURPLE_H, PURPLE_L, PURPLE_P,
     CURVED),
    ("GROUP 5 · GN COCCI & COCCOBACILLI",
     GREEN_H, GREEN_L, GREEN_P,
     GNCOC),
    ("GROUP 6 · ANAEROBIC GNB",
     TEAL_H, TEAL_L, TEAL_P,
     ANAEROB),
]

# Collect all rows with metadata
all_rows_meta = []  # list of (type, row_data, bg_color)
all_rows_meta.append(("HDR", HDR, GREY_H))

for label, bg_h, bg_l, bg_p, data in sections:
    all_rows_meta.extend(build_section(label, bg_h, bg_l, bg_p, data))

all_rows = [r for _, r, _ in all_rows_meta]

# Build table style
ts_cmds = [
    # Grid
    ("GRID",      (0,0),(-1,-1), 0.35, colors.HexColor("#bbbbbb")),
    ("VALIGN",    (0,0),(-1,-1), "MIDDLE"),
    ("ALIGN",     (0,0),(-1,-1), "CENTER"),
    ("ALIGN",     (0,0),(0,-1),  "LEFT"),
    ("ALIGN",     (5,0),(6,-1),  "LEFT"),
    # Padding
    ("TOPPADDING",    (0,0),(-1,-1), 3),
    ("BOTTOMPADDING", (0,0),(-1,-1), 3),
    ("LEFTPADDING",   (0,0),(-1,-1), 4),
    ("RIGHTPADDING",  (0,0),(-1,-1), 3),
    # Header row
    ("BACKGROUND",    (0,0),(-1,0), GREY_H),
    ("LINEBELOW",     (0,0),(-1,0), 1.2, WHITE),
]

for i, (rtype, row, bg) in enumerate(all_rows_meta):
    if rtype == "SEC":
        ts_cmds.append(("SPAN",       (0,i),(-1,i)))
        ts_cmds.append(("BACKGROUND", (0,i),(-1,i), bg))
        ts_cmds.append(("LINEABOVE",  (0,i),(-1,i), 1.0, colors.HexColor("#888888")))
        ts_cmds.append(("LINEBELOW",  (0,i),(-1,i), 0.8, colors.HexColor("#888888")))
    elif rtype == "DATA":
        ts_cmds.append(("BACKGROUND", (0,i),(-1,i), bg))

# Bold species column
ts_cmds.append(("FONTNAME", (5,1),(5,-1), "Helvetica-Oblique"))

ts = TableStyle(ts_cmds)
tbl = Table(all_rows, colWidths=CW, repeatRows=1)
tbl.setStyle(ts)

# ── Title banner ──────────────────────────────────────────────────────────────
total_w = sum(CW)
title_tbl = Table([
    [p("<b>GRAM-NEGATIVE BACILLI (GNB)</b>",
       st("T1", fontSize=18, fontName="Helvetica-Bold", textColor=WHITE,
          alignment=TA_CENTER))],
    [p("Complete Taxonomic Classification  ·  Group | Phylum | Class | Order | Family | Species | Key Disease",
       st("T2", fontSize=9.5, fontName="Helvetica", textColor=colors.HexColor("#aaccee"),
          alignment=TA_CENTER))],
    [p("6 Groups  ·  40+ Clinically Relevant Species  ·  Orris Medical Reference 2026",
       st("T3", fontSize=8, fontName="Helvetica-Oblique", textColor=colors.HexColor("#88aacc"),
          alignment=TA_CENTER))],
], colWidths=[total_w])
title_tbl.setStyle(TableStyle([
    ("BACKGROUND",    (0,0),(0,2), NAVY),
    ("TOPPADDING",    (0,0),(0,2), 5),
    ("BOTTOMPADDING", (0,0),(0,2), 5),
    ("LEFTPADDING",   (0,0),(0,2), 8),
]))

notes = [
    "Phylum 'Pseudomonadota' is the modern name for Proteobacteria (same organisms). "
    "Class abbreviations: Gamma = Gammaproteobacteria; Beta = Betaproteobacteria; "
    "Alpha = Alphaproteobacteria; Epsilon = Epsilonproteobacteria.",
    "GNB = Gram-Negative Bacilli. All stain pink/red on Gram stain due to thin peptidoglycan + outer membrane with LPS (endotoxin). "
    "Species in italics per standard microbiological nomenclature.",
    "Sources: Henry's Clinical Diagnosis & Laboratory Methods; Red Book 2021; Medical Microbiology 9e (Murray); Jawetz, Melnick & Adelberg's Medical Microbiology 28e.",
]

elements = [title_tbl, Spacer(1, 5), tbl, Spacer(1, 5)]
for n in notes:
    elements.append(Paragraph(n, NOTE))
    elements.append(Spacer(1, 2))

doc.build(elements)
print(f"PDF saved: {OUTPUT}")

from reportlab.lib.pagesizes import A3, landscape
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
from reportlab.platypus import (
    SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, HRFlowable
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_RIGHT

OUTPUT = "/home/daytona/workspace/gpc-gnb-chart/Antibiotic_Resistance_Patterns.pdf"

# ── Palette ───────────────────────────────────────────────────────────────────
NAVY       = colors.HexColor("#0d2b45")
DARK_BLUE  = colors.HexColor("#1a3a5c")
MID_BLUE   = colors.HexColor("#2471a3")
PALE_BLUE  = colors.HexColor("#d6eaf8")
VLIGHT_BLUE= colors.HexColor("#eaf4fb")

DARK_RED   = colors.HexColor("#7b241c")
MID_RED    = colors.HexColor("#c0392b")
PALE_RED   = colors.HexColor("#fadbd8")
VLIGHT_RED = colors.HexColor("#fff5f4")

DARK_GREEN = colors.HexColor("#1d6a3a")
MID_GREEN  = colors.HexColor("#27ae60")
PALE_GREEN = colors.HexColor("#d5f5e3")
VLIGHT_GRN = colors.HexColor("#f0faf4")

DARK_ORNG  = colors.HexColor("#784212")
MID_ORNG   = colors.HexColor("#d35400")
PALE_ORNG  = colors.HexColor("#fdebd0")
VLIGHT_ORG = colors.HexColor("#fef9f4")

DARK_PURP  = colors.HexColor("#4a235a")
MID_PURP   = colors.HexColor("#7d3c98")
PALE_PURP  = colors.HexColor("#e8daef")
VLIGHT_PRP = colors.HexColor("#faf5fc")

DARK_TEAL  = colors.HexColor("#0e6655")
PALE_TEAL  = colors.HexColor("#d1f2eb")
VLIGHT_TEL = colors.HexColor("#f0faf8")

GREY       = colors.HexColor("#2c3e50")
LGREY      = colors.HexColor("#f2f3f4")
WHITE      = colors.white
BLACK      = colors.black

# Cell colours for susceptibility
S_CLR  = colors.HexColor("#27ae60")   # Susceptible
R_CLR  = colors.HexColor("#e74c3c")   # Resistant
V_CLR  = colors.HexColor("#f39c12")   # Variable
I_CLR  = colors.HexColor("#8e44ad")   # Intermediate
N_CLR  = colors.HexColor("#95a5a6")   # N/A

def sty(name, **kw):
    base = getSampleStyleSheet()["Normal"]
    return ParagraphStyle(name, parent=base, **kw)

TH   = sty("TH",   fontSize=8,   fontName="Helvetica-Bold",   textColor=WHITE, alignment=TA_CENTER, leading=10)
THL  = sty("THL",  fontSize=8,   fontName="Helvetica-Bold",   textColor=WHITE, alignment=TA_LEFT,   leading=10)
TD   = sty("TD",   fontSize=7.5, fontName="Helvetica",         textColor=BLACK, alignment=TA_LEFT,   leading=9)
TDC  = sty("TDC",  fontSize=7.5, fontName="Helvetica",         textColor=BLACK, alignment=TA_CENTER, leading=9)
TDB  = sty("TDB",  fontSize=7.5, fontName="Helvetica-Bold",    textColor=BLACK, alignment=TA_LEFT,   leading=9)
TDBR = sty("TDBR", fontSize=7.5, fontName="Helvetica-Bold",    textColor=BLACK, alignment=TA_CENTER, leading=9)
SEC  = sty("SEC",  fontSize=10,  fontName="Helvetica-Bold",    textColor=WHITE, alignment=TA_LEFT,   leading=12)
NOTE = sty("NOTE", fontSize=7,   fontName="Helvetica-Oblique", textColor=colors.HexColor("#555555"), alignment=TA_LEFT, leading=9)
MECH = sty("MECH", fontSize=7.5, fontName="Helvetica",         textColor=colors.HexColor("#1a3a5c"), alignment=TA_LEFT, leading=9)
BOX  = sty("BOX",  fontSize=8,   fontName="Helvetica",         textColor=BLACK, alignment=TA_LEFT,   leading=10)

def ph(t): return Paragraph(t, TH)
def phl(t): return Paragraph(t, THL)
def p(t):  return Paragraph(t, TD)
def pc(t): return Paragraph(t, TDC)
def pb(t): return Paragraph(f"<b>{t}</b>", TDB)
def pbc(t):return Paragraph(f"<b>{t}</b>", TDBR)

def sc_cell(code):
    """Coloured susceptibility cell."""
    MAP = {
        "S":  (S_CLR,  "S"),
        "R":  (R_CLR,  "R"),
        "V":  (V_CLR,  "V"),
        "I":  (I_CLR,  "I"),
        "-":  (N_CLR,  "-"),
        "S*": (colors.HexColor("#1e8449"), "S*"),
        "R*": (colors.HexColor("#b03a2e"), "R*"),
    }
    col, label = MAP.get(code, (N_CLR, code))
    return Paragraph(f"<b>{label}</b>",
                     sty("SC", fontSize=8, fontName="Helvetica-Bold",
                         textColor=WHITE, alignment=TA_CENTER, leading=10)), col

doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=landscape(A3),
    leftMargin=1.0*cm, rightMargin=1.0*cm,
    topMargin=1.2*cm,  bottomMargin=1.2*cm,
    title="Antibiotic Resistance Patterns – ESBL · CRE · MRSA · VRE · MDR-GNB",
    author="Orris Medical Reference"
)

# ═══════════════════════════════════════════════════════════════════════════════
# PAGE 1 — RESISTANCE MECHANISM OVERVIEW TABLE
# ═══════════════════════════════════════════════════════════════════════════════
# Columns: Resistance Type | Organism(s) | Mechanism | Genes/Enzymes |
#          Drugs RESISTANT | Drugs ACTIVE | Detection | Clinical Notes
OV_CW = [40, 70, 75, 62, 75, 75, 45, 68]  # total ~510 → trim
OV_CW = [38, 65, 72, 60, 70, 72, 42, 62]  # ~481mm — fits landscape A3

OV_HDR = [ph("RESISTANCE\nTYPE"), ph("AFFECTED\nORGANISMS"),
          ph("MECHANISM"), ph("GENES /\nENZYMES"),
          ph("RESISTANT TO\n(avoid)"), ph("ACTIVE DRUGS\n(treatment)"),
          ph("DETECTION"), ph("KEY CLINICAL NOTES")]

OV_DATA = [
    # ── ESBL ──
    ["ESBL\n(Extended-Spectrum\nBeta-Lactamase)",
     "E. coli, K. pneumoniae,\nK. oxytoca, P. mirabilis,\nEnterobacter spp.",
     "Plasmid-encoded β-lactamases\nhydroly se extended-spectrum\ncephalosporins; overcome\ninhibitors variably",
     "blaTEM, blaSHV,\nblaCTX-M\n(CTX-M most common\nworldwide)",
     "Penicillins, ALL\ncephalosporins (1st–4th gen),\nAztreonam;\nPiperacillin-tazobactam\n(unreliable)",
     "Carbapenems (DOC):\nErtapenem, Meropenem;\nFosfomycin (UTI);\nNitrofurantoin (UTI);\nFluoroquinolones (if susceptible);\nTMP-SMX (if susceptible)",
     "Double-disk synergy\ntest (DDST);\nCombination disk;\nMIC testing;\nMolecular PCR",
     "Carbapenem superior to\npiperacillin-tazobactam (RCT);\nHigh-risk: hospital, elderly,\nprior antibiotics, travel;\nPlasmid-mediated = rapid spread"],
    # ── CRE ──
    ["CRE\n(Carbapenem-Resistant\nEnterobacterales)",
     "K. pneumoniae (KPC),\nE. coli, Enterobacter,\nSerratia, Proteus",
     "Carbapenemase production\n(KPC, MBL, OXA);\nOR porin loss +\nAmpC/ESBL coproduction",
     "blaKPC (Class A)\nblaNDM, blaVIM,\nblaIMP (Class B MBL)\nblaOXA-48 (Class D)",
     "ALL beta-lactams\nincl. carbapenems;\nOften also: FQ,\naminoglycosides,\nTMP-SMX",
     "Ceftazidime-avibactam (KPC,\nsome OXA);\nMeropenem-vaborbactam (KPC);\nImipenem-cilastatin-relebactam;\nCefiderocol (MBL, OXA-48);\nAztreonam-avibactam (MBL);\nColistin (last resort, nephrotoxic)",
     "Modified Hodge test;\nCarbaNP test;\nMicrobroth dilution;\nMolecular: PCR/\nWGS for gene type",
     "50% of CRE produce\ncarbapenemase;\nKPC dominant in USA;\nNDM dominant in\nS. Asia/Africa;\nMortality 40-50%\nin bloodstream infection"],
    # ── AmpC ──
    ["AmpC β-Lactamase\n(Inducible/\nChromosomal)",
     "SPACE organisms:\nSerratia, Pseudomonas,\nAcinetobacter,\nCitrobacter, Enterobacter\n(+ Morganella, Hafnia)",
     "Inducible chromosomal\nor plasmid AmpC;\ninduced by 3rd-gen\ncephalosporins →\nhydrolyses them",
     "ampC gene\n(chromosomal);\nplasmid AmpC:\nblaCMY, blaDHA,\nblaFOX, blaACT",
     "All penicillins;\nAll cephalosporins\n1st–3rd gen;\nClavulanate combinations;\n(avoid even if in vitro\nsusceptible to 3GC)",
     "Cefepime (4th gen) if\nMIC ≤2 μg/mL;\nCarbapenem if\nMIC ≥4 μg/mL;\nFluoroquinolones;\nPiperacillin-tazobactam\n(limited evidence)",
     "No reliable phenotypic\ntest for inducible AmpC;\nWatch for MIC creep;\nMolecular PCR",
     "3rd-gen cephalosporin\nmay test 'susceptible'\nbut fail clinically;\nCo-production of ESBL\ncommon; use 4th-gen or\ncarbapenem empirically"],
    # ── MDR Pseudomonas ──
    ["MDR Pseudomonas\naeruginosa\n(Non-fermentative)",
     "Pseudomonas aeruginosa\n(especially ICU,\nCF patients)",
     "Multiple: porin loss (OprD),\nefflux pumps (MexAB-OprM),\nbeta-lactamases (IMP/VIM/NDM),\nAmpC upregulation,\nmodified PBPs",
     "blaIMP, blaVIM,\nblaOXA-48;\nOprD mutation;\nMexAB-OprM, MexCD,\nMexXY efflux pumps",
     "Ampicillin (intrinsic R);\nTMP-SMX (intrinsic R);\nAll early gen cephalosporins;\nErtapenem;\n1st/2nd gen FQ",
     "Piperacillin-tazobactam;\nCeftazidime;\nCefepime;\nImipenem/Meropenem;\nCiprofloxacin;\nAmikacin;\nColistin (XDR strains);\nCeftolozane-tazobactam\n(MDR Pseudomonas)",
     "Susceptibility testing\nmandatory;\nCombination therapy\nfor serious infections;\nPDD extended infusion",
     "Intrinsic resistance to\nmany drug classes;\nAlways obtain cultures;\nConsult ID for MDR\nstrains; de-escalate\nbased on C&S"],
    # ── CRAB ──
    ["CRAB\n(Carbapenem-Resistant\nAcinetobacter baumannii)",
     "Acinetobacter baumannii\n(ICU, war wounds,\nhospital environment)",
     "OXA-type carbapenemases\n(OXA-23, OXA-40, OXA-58);\nMBL (NDM, IMP, VIM);\nPorin loss;\nMultiple efflux pumps",
     "blaOXA-23 (dominant);\nblaOXA-40,\nblaOXA-58;\nblaNDM (emerging)",
     "ALL beta-lactams;\nFluoroquinolones;\nAminoglycosides;\nTMP-SMX;\n(pan-resistant strains\nexist)",
     "Colistin/Polymyxin B\n(last resort);\nSulbactam (intrinsic\nactivity vs. Acinetobacter);\nTigecycline;\nMinocycline;\nCefiderocol (emerging);\nRifampicin (combination)",
     "MIC testing essential;\nOXA carbapenemase PCR;\nSurface sampling\nfor outbreak tracing",
     "Survives on dry\nsurfaces for weeks;\nHospital outbreak\npotential is high;\npan-drug resistance\n(PDR) reported;\nBundled infection\ncontrol critical"],
    # ── MRSA ──
    ["MRSA\n(Methicillin-Resistant\nS. aureus)\n[GPC, not GNB]",
     "Staphylococcus aureus\n(HA-MRSA: hospital;\nCA-MRSA: community;\nLA-MRSA: livestock)",
     "mecA gene → altered PBP2a\n(PBP2') with low affinity for\nall beta-lactams;\nCA-MRSA also carries\nPVL (Panton-Valentine\nleukocidin) toxin",
     "mecA, mecC\n(PBP2a);\nPVL (CA-MRSA);\nnuc gene (ID);\nSCCmec types\nI–XI",
     "ALL beta-lactams\n(penicillins, cephalosporins,\ncarbapenems, monobactam);\nErythromycin;\nOften Clindamycin (V/R)",
     "Vancomycin (DOC for\nbacteremia, endocarditis,\nmeningitis);\nLinezolid (skin, pneumonia);\nDaptomycin (bacteremia);\nTedizolid;\nTMP-SMX (skin, SSTI);\nDoxycycline (skin);\nCeftaroline (5th gen β-lac)",
     "Oxacillin/cefoxitin\ndisk screen;\nPBP2a latex\nagglutination;\nMRSA PCR;\nMolecular typing\n(spa, MLST, WGS)",
     "Vancomycin penetrates\npoorly into lung & bone;\nuse linezolid/daptomycin\nfor MRSA pneumonia;\nNasal screening detects\ncarriage (MRSA bundle);\nVRSA/VISA strains rare"],
    # ── VRE ──
    ["VRE\n(Vancomycin-Resistant\nEnterococcus)\n[GPC, not GNB]",
     "Enterococcus faecium\n(VanA/VanB);\nE. faecalis (VanB,\nless common;\nintrinsic low-level\nVanC: E. gallinarum)",
     "Acquired van gene clusters\nmodify D-Ala-D-Ala terminus\nof peptidoglycan precursor\nto D-Ala-D-Lac (VanA,B)\nor D-Ala-D-Ser (VanC) →\nvancomycin cannot bind",
     "vanA (high-level;\nR to vancomycin\n+ teicoplanin);\nvanB (variable;\nR to vancomycin,\nS to teicoplanin);\nvanC (intrinsic,\nlow-level)",
     "Vancomycin;\nTeicoplanin (VanA);\nAmpicillin (E. faecium\nusually resistant);\nAll cephalosporins;\nAll carbapenems (MRSE)",
     "Linezolid (DOC);\nDaptomycin;\nTedizolid;\nQ-D (Quinupristin-\ndalfopristin) – E. faecium\nonly;\nHigh-dose ampicillin\n(if MIC allows, E. faecalis)",
     "Vancomycin MIC;\nVan gene PCR\n(vanA, vanB);\nVRE rectal swab\nscreening in ICU;\nEpidemic strain\ntyping (WGS)",
     "Risk factors: prolonged\nhospitalisation, prior\nvancomycin, GI surgery;\nStrict contact\nprecautions;\nLinezolid resistance\ncan emerge on therapy;\nDaptomycin non-\nsusceptible strains exist"],
    # ── Stenotrophomonas ──
    ["Intrinsic MDR:\nStenotrophomonas\nmaltophilia",
     "Stenotrophomonas\nmaltophilia\n(ICU, CF, immunocomp.)",
     "Intrinsic resistance to\ncarbapenems via\nL1 (MBL) + L2 (cephalosporinase);\nMultiple efflux pumps;\nOuter membrane impermeability",
     "L1 MBL (blaL1);\nL2 cephalosporinase\n(blaL2);\nSmeABC, SmeDEF\nefflux pumps",
     "ALL carbapenems\n(intrinsically resistant);\nAll penicillins;\nMost cephalosporins;\nAminoglycosides;\nMany FQ",
     "TMP-SMX (DOC);\nLevofloxacin;\nMinocycline/Doxycycline;\nTigecycline;\nChloramphenicol;\nCeftazidime-avibactam\n(variable)",
     "Disk diffusion or\nMIC (TMP-SMX);\nMolecular:\nblaL1, blaL2",
     "Carbapenem therapy\ncan select for\nStenotrophomonas;\nConsider in patients\non prolonged carbapenem;\nCF patients: chronic\ncolonisation common"],
]

def build_overview_table(data):
    all_rows = [OV_HDR]
    cmd = [
        ("GRID",      (0,0),(-1,-1), 0.3, colors.HexColor("#aaaaaa")),
        ("BACKGROUND",(0,0),(-1,0),  GREY),
        ("VALIGN",    (0,0),(-1,-1), "TOP"),
        ("ALIGN",     (0,0),(-1,-1), "LEFT"),
        ("ALIGN",     (0,0),(-1,0),  "CENTER"),
        ("TOPPADDING",    (0,0),(-1,-1), 3),
        ("BOTTOMPADDING", (0,0),(-1,-1), 3),
        ("LEFTPADDING",   (0,0),(-1,-1), 4),
        ("RIGHTPADDING",  (0,0),(-1,-1), 3),
        ("LINEBELOW", (0,0),(-1,0), 1.0, WHITE),
    ]
    row_bgs = [
        (PALE_BLUE,  VLIGHT_BLUE),   # ESBL
        (PALE_RED,   VLIGHT_RED),    # CRE
        (PALE_ORNG,  VLIGHT_ORG),    # AmpC
        (PALE_PURP,  VLIGHT_PRP),    # Pseudomonas
        (PALE_RED,   VLIGHT_RED),    # CRAB
        (PALE_BLUE,  VLIGHT_BLUE),   # MRSA
        (PALE_GREEN, VLIGHT_GRN),    # VRE
        (PALE_TEAL,  VLIGHT_TEL),    # Steno
    ]
    for i, row_data in enumerate(data):
        styled_row = []
        for j, cell in enumerate(row_data):
            if j == 0:
                styled_row.append(Paragraph(f"<b>{cell}</b>",
                    sty("R0", fontSize=8, fontName="Helvetica-Bold",
                        textColor=WHITE, alignment=TA_CENTER, leading=10)))
            elif j in (4, 5):  # resistant / active
                styled_row.append(Paragraph(cell, MECH))
            else:
                styled_row.append(Paragraph(cell, TD))
            
        ri = i + 1
        bg0, bg1 = row_bgs[i % len(row_bgs)]
        # col 0 gets distinctive dark bg
        dark_cols = [
            MID_BLUE, MID_RED, MID_ORNG, MID_PURP,
            MID_RED, MID_BLUE, MID_GREEN, DARK_TEAL
        ]
        cmd.append(("BACKGROUND", (0,ri),(0,ri), dark_cols[i % len(dark_cols)]))
        cmd.append(("TEXTCOLOR",  (0,ri),(0,ri), WHITE))
        # Resistant column = pale red
        cmd.append(("BACKGROUND", (4,ri),(4,ri), PALE_RED))
        # Active drugs column = pale green
        cmd.append(("BACKGROUND", (5,ri),(5,ri), PALE_GREEN))
        # rest alternating
        for c in [1,2,3,6,7]:
            cmd.append(("BACKGROUND", (c,ri),(c,ri), bg0 if i%2==0 else bg1))
        
        all_rows.append(styled_row)
    
    cmd.append(("FONTSIZE", (0,1),(0,-1), 8))
    ts = TableStyle(cmd)
    t = Table(all_rows, colWidths=OV_CW, repeatRows=1)
    t.setStyle(ts)
    return t

# ═══════════════════════════════════════════════════════════════════════════════
# PAGE 2 — DRUG-BY-DRUG COMPARISON MATRIX
# Rows = antibiotics, Cols = resistance phenotype
# ═══════════════════════════════════════════════════════════════════════════════
# Cols: Antibiotic | Class | ESBL-E.coli | CRE-Kpn | MDR-Psa | CRAB | MRSA | VRE | AmpC
MAT_CW = [75, 65, 28, 28, 28, 28, 28, 28, 28]   # ~336mm

MAT_ORG_HDR = [
    ph("ANTIBIOTIC"), ph("CLASS"),
    ph("ESBL\nE. coli"), ph("CRE\nK. pneu."),
    ph("MDR\nP. aeru."), ph("CRAB\nA. bau."),
    ph("MRSA\nS. aur."), ph("VRE\nE. fae."),
    ph("AmpC\nEnterob."),
]

# (drug, class, ESBL-Ec, CRE-Kp, MDR-Pa, CRAB, MRSA, VRE, AmpC)
MAT_DATA = [
    # ── Penicillins ────────────────────────────────────────────────────────────
    ("Amoxicillin-Clavulanate",  "Aminopenicillin+BLI",   "R","R","R","R","R","R","R"),
    ("Piperacillin-Tazobactam",  "Ureidopenicillin+BLI",  "V*","R","V","R","R","R","V*"),
    ("Ampicillin-Sulbactam",     "Aminopenicillin+BLI",   "R","R","R","V*","R","R","R"),
    # ── Cephalosporins ────────────────────────────────────────────────────────
    ("Cefazolin (1G)",           "1st Gen Cephalosporin", "R","R","R","R","R","R","R"),
    ("Cefuroxime (2G)",          "2nd Gen Cephalosporin", "R","R","R","R","R","R","R"),
    ("Ceftriaxone (3G)",         "3rd Gen Cephalosporin", "R","R","R","R","R","R","R"),
    ("Ceftazidime (3G anti-Psa)","3rd Gen Cephalosporin", "R","R","V","R","R","R","R"),
    ("Cefepime (4G)",            "4th Gen Cephalosporin", "V*","R","V","R","R","R","V*"),
    ("Ceftaroline (5G)",         "5th Gen Cephalosporin\n(anti-MRSA)", "V","R","R","R","S","R","V"),
    ("Ceftazidime-Avibactam",    "3GC + BLI (non-MBL)",  "S","S*","S","V","R","R","S"),
    ("Ceftolozane-Tazobactam",   "3GC + BLI (Pseudo)",   "S","R","S","R","R","R","S"),
    ("Cefiderocol",              "Siderophore Cephalosporin","S","S","S","S","R","R","S"),
    # ── Carbapenems ──────────────────────────────────────────────────────────
    ("Ertapenem",                "Carbapenem (no Psa)",   "S","R","R","R","R","R","S"),
    ("Meropenem",                "Carbapenem",            "S","V*","V","R","R","R","S"),
    ("Imipenem-Cilastatin",      "Carbapenem",            "S","V*","V","R","R","R","S"),
    ("Meropenem-Vaborbactam",    "Carbapenem+BLI (KPC)",  "S","S*","V","R","R","R","S"),
    ("Imip-Cilastatin-Relebact.","Carbapenem+BLI (KPC)",  "S","S*","S","R","R","R","S"),
    ("Aztreonam-Avibactam",      "Monobactam+BLI (MBL)",  "S","S*","V","R","R","R","S"),
    # ── Glycopeptides ─────────────────────────────────────────────────────────
    ("Vancomycin",               "Glycopeptide",          "R","R","R","R","S","R","R"),
    ("Teicoplanin",              "Glycopeptide",          "R","R","R","R","S","V*","R"),
    # ── Lipopeptide / Oxazolidinone ──────────────────────────────────────────
    ("Daptomycin",               "Lipopeptide",           "R","R","R","R","S","S","R"),
    ("Linezolid",                "Oxazolidinone",         "R","R","R","R","S","S","R"),
    ("Tedizolid",                "Oxazolidinone (2G)",    "R","R","R","R","S","S","R"),
    # ── Aminoglycosides ───────────────────────────────────────────────────────
    ("Gentamicin",               "Aminoglycoside",        "V","V","V","V","R","V*","V"),
    ("Amikacin",                 "Aminoglycoside",        "V","V","S","V","R","V*","V"),
    # ── Fluoroquinolones ──────────────────────────────────────────────────────
    ("Ciprofloxacin",            "Fluoroquinolone",       "V","V","V","V","R","V","V"),
    ("Levofloxacin",             "Respiratory FQ",        "V","V","V","V","R","V","V"),
    # ── Tetracyclines ─────────────────────────────────────────────────────────
    ("Doxycycline",              "Tetracycline",          "V","V","R","V","S*","V","V"),
    ("Tigecycline",              "Glycylcycline",         "S","S","R","S","S","S","S"),
    ("Minocycline",              "Tetracycline",          "V","V","R","S","S","V","V"),
    # ── Folate inhibitors ─────────────────────────────────────────────────────
    ("TMP-SMX",                  "Sulfonamide Combo",     "V","V","R","R","V*","R","V"),
    # ── Polymyxins ────────────────────────────────────────────────────────────
    ("Colistin / Polymyxin B",   "Polymyxin",             "S","S*","S","S","R","R","S"),
    # ── Misc ──────────────────────────────────────────────────────────────────
    ("Nitrofurantoin",           "Nitrofuran (UTI only)", "S","V","R","R","V","V","S"),
    ("Fosfomycin",               "Phosphonic acid",       "S","V","V","R","S","V","S"),
    ("Rifampicin",               "Rifamycin (adjunct)",   "R","R","R","R","S","V","R"),
    ("Chloramphenicol",          "Amphenicol",            "V","V","R","V","V","V","V"),
]

def build_matrix(data):
    # Determine row count (cols for A3 landscape = up to ~520mm usable with narrow cols)
    # We'll split into two halves for readability
    all_rows = [MAT_ORG_HDR]
    cmd = [
        ("GRID",      (0,0),(-1,-1), 0.3, colors.HexColor("#aaaaaa")),
        ("BACKGROUND",(0,0),(-1,0),  GREY),
        ("VALIGN",    (0,0),(-1,-1), "MIDDLE"),
        ("ALIGN",     (0,0),(-1,-1), "CENTER"),
        ("ALIGN",     (0,1),(1,-1),  "LEFT"),
        ("TOPPADDING",    (0,0),(-1,-1), 3),
        ("BOTTOMPADDING", (0,0),(-1,-1), 3),
        ("LEFTPADDING",   (0,0),(-1,-1), 4),
        ("RIGHTPADDING",  (0,0),(-1,-1), 3),
        ("LINEBELOW", (0,0),(-1,0), 1.0, WHITE),
        ("FONTNAME",  (0,1),(1,-1), "Helvetica"),
        ("FONTSIZE",  (0,1),(1,-1), 7.5),
    ]
    # Group separators (by drug class)
    sep_indices_after = [2, 11, 17, 22, 25, 27, 30, 31, 34]  # row indices (0-based data)

    for i, (drug, cls, *sus_vals) in enumerate(data):
        ri = i + 1
        row = [p(drug), p(cls)]
        for j, val in enumerate(sus_vals):
            cell_p, cell_bg = sc_cell(val)
            row.append(cell_p)
            cmd.append(("BACKGROUND", (j+2, ri), (j+2, ri), cell_bg))
        
        row_bg = LGREY if i % 2 == 0 else WHITE
        cmd.append(("BACKGROUND", (0,ri),(1,ri), row_bg))
        all_rows.append(row)
        
        if i in sep_indices_after:
            cmd.append(("LINEBELOW", (0,ri),(-1,ri), 1.0, colors.HexColor("#888888")))

    ts = TableStyle(cmd)
    t = Table(all_rows, colWidths=MAT_CW, repeatRows=1)
    t.setStyle(ts)
    return t

# ═══════════════════════════════════════════════════════════════════════════════
# LEGEND + FOOTNOTES
# ═══════════════════════════════════════════════════════════════════════════════
LEGEND_DATA = [
    (S_CLR,  "S  = Susceptible – drug is effective"),
    (R_CLR,  "R  = Resistant – drug not effective"),
    (V_CLR,  "V  = Variable – depends on local resistance/MIC testing"),
    (I_CLR,  "I   = Intermediate susceptibility"),
    (N_CLR,  "-   = Not applicable"),
]

def legend_box(items):
    cells = []
    for col, label in items:
        box = Table([[""]], colWidths=[10], rowHeights=[10])
        box.setStyle(TableStyle([("BACKGROUND",(0,0),(0,0),col),
                                  ("GRID",(0,0),(0,0),0.5,colors.grey)]))
        cells.extend([box, Paragraph(f" {label}   ", BOX)])
    lt = Table([cells], colWidths=([12,115]*5))
    lt.setStyle(TableStyle([("VALIGN",(0,0),(-1,-1),"MIDDLE"),
                             ("TOPPADDING",(0,0),(-1,-1),3),
                             ("BOTTOMPADDING",(0,0),(-1,-1),3)]))
    return lt

NOTES = [
    "S* = Susceptible with caveats (e.g., ESBL + pip-tazo: inferior to carbapenem per RCT; CRE + meropenem: only if MIC ≤1 and no carbapenemase gene; MRSA + doxycycline/TMP-SMX: skin infections only).",
    "V* = Variable with important caveats (e.g., Gentamicin/Amikacin used synergistically for enterococcal endocarditis only; Piperacillin-tazobactam for ESBL: unreliable, use carbapenem for serious infections).",
    "CRE treatment: drug of choice depends on carbapenemase type — KPC→Ceftazidime-avibactam or Meropenem-vaborbactam; MBL (NDM/VIM/IMP)→Aztreonam-avibactam or Cefiderocol; OXA-48→Ceftazidime-avibactam.",
    "CRAB (Carbapenem-resistant A. baumannii): Sulbactam has intrinsic activity against Acinetobacter spp.; consider sulbactam-based combinations or Cefiderocol for severe infections.",
    "BLI = Beta-Lactamase Inhibitor. GPC = Gram-Positive Cocci (MRSA, VRE included for completeness). GNB = Gram-Negative Bacilli.",
    "Sources: The Harriet Lane Handbook 23e; Red Book 2021; Goldman-Cecil Medicine; Harrison's Principles of Internal Medicine 22e; Medical Microbiology 9e.",
]

# ═══════════════════════════════════════════════════════════════════════════════
# ASSEMBLE DOCUMENT
# ═══════════════════════════════════════════════════════════════════════════════
total_w = sum(OV_CW)

def make_title(text, sub, col=NAVY):
    tt = Table([
        [Paragraph(f"<b>{text}</b>",
                   sty("T1", fontSize=17, fontName="Helvetica-Bold",
                       textColor=WHITE, alignment=TA_CENTER))],
        [Paragraph(sub,
                   sty("T2", fontSize=9, fontName="Helvetica",
                       textColor=colors.HexColor("#aaccee"),
                       alignment=TA_CENTER))],
    ], colWidths=[total_w])
    tt.setStyle(TableStyle([
        ("BACKGROUND", (0,0),(0,1), col),
        ("TOPPADDING",    (0,0),(0,1), 5),
        ("BOTTOMPADDING", (0,0),(0,1), 5),
        ("LEFTPADDING",   (0,0),(0,1), 8),
    ]))
    return tt

def sec_banner(text, bg):
    tt = Table([[Paragraph(f"  <b>{text}</b>",
                           sty("SB", fontSize=9.5, fontName="Helvetica-Bold",
                               textColor=WHITE, alignment=TA_LEFT, leading=12))]],
               colWidths=[total_w])
    tt.setStyle(TableStyle([
        ("BACKGROUND", (0,0),(0,0), bg),
        ("TOPPADDING",    (0,0),(0,0), 4),
        ("BOTTOMPADDING", (0,0),(0,0), 4),
        ("LEFTPADDING",   (0,0),(0,0), 8),
    ]))
    return tt

elements = []

# ── PAGE 1: Mechanism table ───────────────────────────────────────────────────
elements.append(make_title(
    "ANTIBIOTIC RESISTANCE PATTERNS IN COMMON PATHOGENS",
    "ESBL · CRE · AmpC · MDR-Pseudomonas · CRAB · MRSA · VRE  —  Mechanisms, Genes, Treatment & Clinical Notes",
    NAVY))
elements.append(Spacer(1, 5))
elements.append(sec_banner(
    "SECTION 1 — RESISTANCE MECHANISMS: Organisms | Mechanism | Genes | Resistant-to | Active Drugs | Detection | Notes",
    DARK_BLUE))
elements.append(Spacer(1, 4))
elements.append(build_overview_table(OV_DATA))
elements.append(Spacer(1, 6))
elements.append(legend_box(LEGEND_DATA))
elements.append(Spacer(1, 4))
for n in NOTES[:3]:
    elements.append(Paragraph(n, NOTE))
    elements.append(Spacer(1,2))

# ── PAGE 2: Matrix ────────────────────────────────────────────────────────────
from reportlab.platypus import PageBreak
elements.append(PageBreak())

mat_total_w = sum(MAT_CW)
mat_title = Table([
    [Paragraph("<b>SECTION 2 — DRUG × PATHOGEN SUSCEPTIBILITY MATRIX</b>",
               sty("MT", fontSize=14, fontName="Helvetica-Bold",
                   textColor=WHITE, alignment=TA_CENTER))],
    [Paragraph("36 Antibiotics × 7 Resistance Phenotypes  ·  Colour-coded Susceptibility",
               sty("MS", fontSize=9, fontName="Helvetica",
                   textColor=colors.HexColor("#aaccee"), alignment=TA_CENTER))],
], colWidths=[mat_total_w])
mat_title.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(0,1), NAVY),
    ("TOPPADDING",(0,0),(0,1),5),("BOTTOMPADDING",(0,0),(0,1),5),
    ("LEFTPADDING",(0,0),(0,1),8),
]))
elements.append(mat_title)
elements.append(Spacer(1,5))
elements.append(build_matrix(MAT_DATA))
elements.append(Spacer(1,6))
elements.append(legend_box(LEGEND_DATA))
elements.append(Spacer(1,4))
for n in NOTES[3:]:
    elements.append(Paragraph(n, NOTE))
    elements.append(Spacer(1,2))

doc.build(elements)
print(f"PDF saved: {OUTPUT}")

from reportlab.lib.pagesizes import A3, landscape
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
from reportlab.platypus import (
    SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, PageBreak
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT

OUTPUT = "/home/daytona/workspace/gpc-gnb-chart/GNB_LF_vs_NLF.pdf"

# ── Palette ───────────────────────────────────────────────────────────────────
NAVY        = colors.HexColor("#0d2b45")
# LF = pink/red theme (pink colonies on MacConkey)
LF_DARK     = colors.HexColor("#7b1d38")
LF_MID      = colors.HexColor("#c0392b")
LF_LIGHT    = colors.HexColor("#fadbd8")
LF_PALE     = colors.HexColor("#fef5f4")
LF_ALT      = colors.HexColor("#fdecea")
# NLF = colourless/white on MacConkey → use teal/grey-blue
NLF_DARK    = colors.HexColor("#0e4d5c")
NLF_MID     = colors.HexColor("#117a8b")
NLF_LIGHT   = colors.HexColor("#d1ecf1")
NLF_PALE    = colors.HexColor("#f0fafc")
NLF_ALT     = colors.HexColor("#e4f4f8")
# Sub-group headers
SUB_PINK    = colors.HexColor("#922b21")
SUB_TEAL    = colors.HexColor("#0e6655")
SUB_PURPLE  = colors.HexColor("#4a235a")
SUB_OLIVE   = colors.HexColor("#4d4011")
SUB_NAVY2   = colors.HexColor("#1a3a5c")

GREY        = colors.HexColor("#2c3e50")
LGREY       = colors.HexColor("#f2f3f4")
WHITE       = colors.white
BLACK       = colors.black

def sty(name, **kw):
    return ParagraphStyle(name, parent=getSampleStyleSheet()["Normal"], **kw)

TH   = sty("TH",  fontSize=8,   fontName="Helvetica-Bold", textColor=WHITE, alignment=TA_CENTER, leading=10)
THL  = sty("THL", fontSize=8,   fontName="Helvetica-Bold", textColor=WHITE, alignment=TA_LEFT,   leading=10)
TD   = sty("TD",  fontSize=7.5, fontName="Helvetica",       textColor=BLACK, alignment=TA_LEFT,   leading=9)
TDI  = sty("TDI", fontSize=7.5, fontName="Helvetica-Oblique",textColor=colors.HexColor("#1a3a5c"), alignment=TA_LEFT, leading=9)
TDC  = sty("TDC", fontSize=7.5, fontName="Helvetica",       textColor=BLACK, alignment=TA_CENTER, leading=9)
TDB  = sty("TDB", fontSize=7.5, fontName="Helvetica-Bold",  textColor=BLACK, alignment=TA_LEFT,   leading=9)
NOTE = sty("NOTE",fontSize=7,   fontName="Helvetica-Oblique",textColor=colors.HexColor("#555"),    alignment=TA_LEFT, leading=9)

def ph(t): return Paragraph(t, TH)
def p(t):  return Paragraph(t, TD)
def pi(t): return Paragraph(f"<i>{t}</i>", TDI)
def pb(t): return Paragraph(f"<b>{t}</b>", TDB)
def pc(t): return Paragraph(t, TDC)

doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=landscape(A3),
    leftMargin=1.0*cm, rightMargin=1.0*cm,
    topMargin=1.2*cm,  bottomMargin=1.2*cm,
    title="GNB: Lactose Fermenters vs Non-Lactose Fermenters",
    author="Orris Medical Reference"
)

# ─────────────────────────────────────────────────────────────────────────────
# COLUMN DEFINITIONS
# Cols: No. | Genus | Species | MacConkey | O2 Req | Oxidase | Other Tests |
#       Key Disease | Treatment hints
# ─────────────────────────────────────────────────────────────────────────────
CW = [10, 38, 60, 38, 32, 28, 62, 88, 80]   # total ~436mm
HDR_ROW = [ph("#"), ph("GENUS"), ph("SPECIES"),
           ph("MacConkey\nColony"), ph("O₂\nReq."),
           ph("Oxidase"), ph("KEY TESTS /\nDISTINGUISHING FEATURES"),
           ph("KEY DISEASE"), ph("TREATMENT HINTS")]

# ─────────────────────────────────────────────────────────────────────────────
# DATA: (genus, species, macconkey, o2, oxidase, tests, disease, rx)
# ─────────────────────────────────────────────────────────────────────────────

# ══ LACTOSE FERMENTERS ═══════════════════════════════════════════════════════
# MacConkey: PINK to PINK-PURPLE colonies (acid production from lactose)

LF_SUBGROUPS = [
    # (subgroup_label, subgroup_bg, rows_list)
    (
        "▶  FAST LACTOSE FERMENTERS  (Pink/Pink-Purple colonies on MacConkey within 24h)",
        LF_DARK,
        [
            ("Escherichia", "E. coli",
             "Pink-Red\n(flat, dry)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Indole+;\nIMViC: ++-−;\nTSI: A/A, gas+;\nH₂S−",
             "UTI (most common cause);\nNeonatal meningitis;\nTraverler's diarrhea (ETEC);\nBloody diarrhea + HUS (O157:H7);\nBacteremia/Sepsis",
             "UTI: TMP-SMX, FQ, nitrofurantoin;\nSerious/ESBL: Carbapenem;\nO157:H7: supportive only\n(antibiotics worsen HUS)"),

            ("Klebsiella", "K. pneumoniae",
             "Pink, mucoid\n(large, viscous)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Urease+;\nIMViC: −−++;\nMucoid capsule;\nVoges-Proskauer+;\nTSI: A/A, gas+, H₂S−",
             "Hospital pneumonia\n('currant jelly' sputum);\nUTI, liver abscess;\nNeonatal meningitis;\nSepsis (ESBL/CRKP)",
             "Non-MDR: Cephalosporins, FQ;\nESBL: Carbapenem;\nCRKP: Ceftazidime-avibactam;\nMeropenem-vaborbactam"),

            ("Klebsiella", "K. oxytoca",
             "Pink, mucoid", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Indole+;\nUrease+; ONPG+;\nVP+",
             "UTI; antibiotic-associated\nhemorrhagic colitis;\nbacteremia",
             "Similar to K. pneumoniae;\nESBL strains: Carbapenem"),

            ("Enterobacter", "E. cloacae",
             "Pink-Purple\n(mucoid)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Motile;\nVP+; Citrate+;\nAmpC β-lactamase;\nTSI: A/A, gas+",
             "Nosocomial pneumonia;\nUTI; wound infections;\nbacteremia;\nMeningitis (neonates)",
             "Cefepime (if MIC ≤2);\nCarbapenem;\nFluoroquinolones;\nAvoid 3GC (AmpC)"),

            ("Enterobacter", "E. aerogenes\n(K. aerogenes)",
             "Pink, mucoid", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; VP+;\nMotile; Urease V;\nAmpC β-lactamase",
             "Nosocomial infections;\nUTI; pneumonia;\nbacteremia",
             "Same as E. cloacae;\nAvoid 3GC"),

            ("Serratia", "S. marcescens",
             "Pink/Red\n(red pigment)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Gelatinase+;\nDNase+; Lipase+;\nRed pigment (prodigiosin)\non some strains;\nSlate white if non-pigmented",
             "Hospital pneumonia;\nUTI; wound infections;\nEndocarditis (IV drug\nusers); keratitis;\nbacteremia",
             "TMP-SMX, FQ;\nCarbapenem for MDR;\nAvoid aminoglycosides\n(intrinsic resistance)"),

            ("Citrobacter", "C. freundii",
             "Pink\n(late fermenter)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; H₂S+;\nCitrate+; Indole−;\nAmpC + ESBL producer;\nTSI: A/A or K/A, H₂S+",
             "UTI; wound infections;\nneonatal meningitis;\nbrain abscess (neonates);\nbacteremia",
             "Carbapenem preferred;\nAvoid 3GC (AmpC);\nFQ if susceptible"),

            ("Citrobacter", "C. koseri",
             "Pink", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Indole+;\nH₂S−; Citrate+;\nURBAN: neonatal\nbrain abscess marker",
             "Neonatal brain abscess;\nmeningitis; UTI",
             "Carbapenem;\nExtended infusion\nfor serious infections"),
        ]
    ),
    (
        "▶  DELAYED / SLOW LACTOSE FERMENTERS  (Pale pink after 24h; or positive ONPG test)",
        colors.HexColor("#5d1a00"),
        [
            ("Hafnia", "H. alvei",
             "Pale pink\n(delayed)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; VP+ at 22°C;\nONPG+; Indole−;\nCitrate−",
             "Rare opportunist;\ngastroenteritis;\nbacteremia in\nimmunocompromised",
             "FQ; TMP-SMX;\nCarbapenem for serious"),

            ("Cronobacter", "C. sakazakii\n(Enterobacter s.)",
             "Yellow-pink\n(mucoid)", "Fac. Anaerobe",
             "Negative",
             "Yellow pigment;\nONPG+; VP+;\nMotile",
             "Neonatal meningitis\nand sepsis (powdered\nformula contamination);\nBrain abscess",
             "Carbapenem;\nCiprofloxacin;\nHigh mortality in neonates"),
        ]
    ),
]

# ══ NON-LACTOSE FERMENTERS ═══════════════════════════════════════════════════
# MacConkey: COLOURLESS / PALE colonies (no acid from lactose)

NLF_SUBGROUPS = [
    (
        "▶  NLF — ENTEROBACTERALES  (Pale/Colourless on MacConkey; Oxidase−; Fermentative)",
        NLF_DARK,
        [
            ("Salmonella", "S. typhi",
             "Colourless\n(pale, H₂S+)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; H₂S+ on TSI;\nLactose−; Motile;\nTSI: K/A, H₂S+;\nIMViC: −−−+;\nWidal test (serology)",
             "Typhoid fever:\nfever >38.5°C ≥3 days,\nrose spots, relative\nbradycardia, splenomegaly,\nconstipation > diarrhea",
             "Ceftriaxone (DOC);\nAzithromycin (oral);\nFluoroquinolone (check\nresistance);\nNEVER aminoglycosides"),

            ("Salmonella", "S. enteritidis /\ntyphimurium\n(non-typhoidal)",
             "Colourless\n(H₂S+)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; H₂S+;\nMotile; Lactose−;\nTSI: K/A, H₂S+",
             "Foodborne gastroenteritis\n(self-limiting);\nbacteremia in sickle\ncell, HIV patients",
             "Gastro: supportive\n(antibiotics may\nprolong carrier state);\nBacteremia: Ceftriaxone"),

            ("Shigella", "S. dysenteriae\n(most severe)",
             "Colourless", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; H₂S−;\nNon-motile;\nLactose−; Indole V;\nTSI: K/A, no gas;\nShiga toxin (type 1)",
             "Bloody dysentery;\nShiga toxin → HUS;\nhigh mortality without Rx;\nfecal-oral spread",
             "Azithromycin;\nCeftriaxone;\nFluoroquinolone (check\nresistance);\nAmpicillin (if sensitive)"),

            ("Shigella", "S. flexneri / sonnei /\nboydii",
             "Colourless", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Non-motile;\nH₂S−; Gas−;\nNo toxin (flexneri/sonnei)",
             "Bacillary dysentery\n(flexneri, boydii);\nMild watery→bloody\ndiarrhea (sonnei)",
             "Azithromycin;\nCiprofloxacin;\nCeftriaxone"),

            ("Proteus", "P. mirabilis",
             "Colourless\n(swarming haze)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Urease+++;\nSwarming motility;\nIndole−; H₂S+;\nTSI: K/A, H₂S+;\nPhenylpyruvic acid+",
             "UTI (2nd most common);\nstaghorn calculi\n(urease → struvite);\nwound infections",
             "Ampicillin-sulbactam;\nCephalosporins;\nTMP-SMX; FQ;\nCarbapenem if MDR"),

            ("Proteus", "P. vulgaris",
             "Colourless\n(swarming)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Urease+;\nIndole+; H₂S+;\nSwarming less\nprominent",
             "UTI; wound infections;\nbacteremia",
             "Avoid ampicillin\n(intrinsic resistant);\nCephalosporins; FQ;\nCarbapenem for MDR"),

            ("Yersinia", "Y. pestis",
             "Colourless\n(small, grey)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Urease−;\nBipolar 'safety-pin'\nstaining (Wayson);\nGrows at 28°C;\nNon-motile at 37°C;\nFragilin antigen F1",
             "PLAGUE:\nBubonic (bubo);\nPneumonic (droplet);\nSepticemic;\nBioterrorism category A",
             "Streptomycin (DOC);\nGentamicin;\nDoxycycline;\nCiprofloxacin"),

            ("Yersinia", "Y. enterocolitica",
             "Pale pink\n(delayed)", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Urease+;\nMotile at 22°C;\nVP+ at 22°C;\nCold enrichment\n(4°C) for isolation;\nTSI: K/A or A/A",
             "Enterocolitis;\nmesenteric adenitis\n(mimics appendicitis);\nreactive arthritis;\nbacteria in cold meats/\npork products",
             "Mild: self-limiting;\nSevere: TMP-SMX,\nciprofloxacin,\ndoxycycline;\nSepsis: ceftriaxone"),

            ("Morganella", "M. morganii",
             "Colourless", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Urease+;\nIndole+; H₂S−;\nPhenylalanine\ndeaminase+;\nMotile",
             "UTI; wound infections;\nneonatal meningitis;\nnecrotizing fasciitis;\nbacteremia",
             "TMP-SMX; FQ;\nIntrinsic resistant to\npenicillin + colistin;\nCarbapenem for MDR"),

            ("Providencia", "P. stuartii /\nP. rettgeri",
             "Colourless", "Fac. Anaerobe",
             "Negative",
             "Oxidase−; Urease+;\nMotile; Indole+;\nPhenylalanine\ndeaminase+",
             "UTI in long-term\ncatheterised patients;\nwound infections;\nbacteremia;\nburn wound infections",
             "FQ; Carbapenem;\nIntrinsically resistant\nto many agents;\nAmikacin may work"),
        ]
    ),
    (
        "▶  NLF — NON-FERMENTATIVE GNB  (Pale/Colourless on MacConkey; variable Oxidase; Oxidative or non-reactive)",
        NLF_MID,
        [
            ("Pseudomonas", "P. aeruginosa",
             "Colourless/Green\n(blue-green pigment,\ngrape-like odour)", "Strict Aerobe",
             "POSITIVE",
             "Oxidase+; Pyocyanin\n(blue-green pigment);\nPyoverdin (fluorescent);\nNon-fermenter;\nGlucose: oxidative;\nTSI: K/K (no rxn);\nOdour: grape-like",
             "Burn/wound infections;\nVAP (ICU, ventilator);\nCF chronic lung disease;\nHot-tub folliculitis;\nExternal otitis\n('swimmer's ear');\nEcthyma gangrenosum\n(black skin lesions)",
             "Anti-pseudomonal\nβ-lactam (pip-tazo,\nceftazidime, cefepime,\nceftolozane-tazo);\n+ aminoglycoside for\nserious infections;\nColistin for XDR"),

            ("Pseudomonas", "P. fluorescens /\nP. putida",
             "Colourless\n(fluorescent)", "Strict Aerobe",
             "POSITIVE",
             "Oxidase+; Pyoverdin\n(fluorescent);\nNon-fermenter;\nGrows at 4°C",
             "Rare; blood/IV product\ncontamination;\nbacteremia in\nimmunocompromised",
             "Pip-tazo; FQ;\nCarbapenem"),

            ("Acinetobacter", "A. baumannii",
             "Colourless /\nPale grey\n(mucoid)", "Strict Aerobe",
             "NEGATIVE",
             "Oxidase−; Coccobacillus\n(short rods → cocci\nafter 48h);\nNon-motile;\nNon-fermenter;\nGlucose: oxidative\nor non-reactive;\nGrows on MacConkey",
             "VAP (ICU);\nWound infections\n(war wounds);\nbacteremia; UTI;\nSurvives on dry\nsurfaces 3+ weeks;\nHospital outbreaks",
             "Sulbactam-based\n(Amp-sulbactam);\nColistin/Polymyxin B;\nTigecycline;\nCefiderocol;\nMinocycline"),

            ("Stenotrophomonas", "S. maltophilia",
             "Pale yellow\n(lavender odour)", "Strict Aerobe",
             "POSITIVE",
             "Oxidase+/weak;\nDNase+; Lipase+;\nOxidative (not\nfermentative);\nLavender-green odour;\nResistant to\ncarbapenems",
             "VAP in ICU;\nPneumonia in CF;\nbacteremia in\nimmunocompromised;\nBronchiectasis",
             "TMP-SMX (DOC);\nLevofloxacin;\nMinocycline;\nTigecycline;\nCarbapenem: RESISTANT"),

            ("Burkholderia", "B. cepacia complex\n(Bcc)",
             "Pale pink /\nColourless", "Strict Aerobe",
             "POSITIVE",
             "Oxidase+; Motile;\nOxidative; Lysine+;\nONPG+; Oxidase+;\nResistant to\npolymyxins",
             "CF lung colonisation\n(poor prognosis);\nHospital infections;\nbacteremia;\nPneumonia",
             "TMP-SMX;\nMeropenem;\nCeftazidime;\nChloramphenicol;\nIntrinsic polymyxin R"),

            ("Burkholderia", "B. pseudomallei",
             "Colourless\n(wrinkled colony)", "Strict Aerobe",
             "POSITIVE",
             "Oxidase+; Bipolar\nstaining ('safety pin');\nOxidative; Motile;\nArginine+; Grows\n41–42°C;\nBiohazard L3",
             "MELIOIDOSIS:\npneumonia, sepsis,\nliver/spleen abscesses;\nendemic SE Asia,\nN. Australia;\nmimics TB",
             "IV: Ceftazidime or\nMeropenem ×14 days;\nEradication: TMP-SMX\n×3–6 months"),
        ]
    ),
    (
        "▶  NLF — FASTIDIOUS & CURVED GNB  (Require special media; slow/special growth)",
        SUB_PURPLE,
        [
            ("Haemophilus", "H. influenzae",
             "Does not grow on\nMacConkey\n(requires X+V)", "Fac. Anaerobe",
             "POSITIVE",
             "Requires hemin (X factor)\n+ NAD (V factor);\nSatellitism around\nS. aureus on blood agar;\nCapsule type b = PRP;\nOxidase+",
             "Type b: meningitis,\nepiglottitis, sepsis;\nnon-typeable:\notitis media, sinusitis,\nCOPD exacerbation;\npneumonia",
             "Type b meningitis:\nCeftriaxone;\nMild: Amoxicillin-\nclavulanate;\nβ-lactamase strains:\ncephalosporins"),

            ("Legionella", "L. pneumophila",
             "Does not grow on\nMacConkey\n(BCYE agar)", "Strict Aerobe",
             "POSITIVE\n(weak)",
             "Requires L-cysteine;\nBCYE agar only;\nUrinary antigen test\n(serogroup 1);\nSilver stain in tissue;\nDIF smear",
             "Legionnaire's disease\n(severe pneumonia);\nPontiac fever\n(self-limiting)\n(flu-like, no pneumonia);\nSource: water tanks,\nAC systems",
             "Azithromycin (DOC);\nLevofloxacin;\nDoxycycline;\nDuration: 7–10 days\n(21 days if immuno-)"),

            ("Bordetella", "B. pertussis",
             "Does not grow on\nMacConkey\n(Bordet-Gengou)", "Strict Aerobe",
             "POSITIVE",
             "Bordet-Gengou agar;\nRegan-Lowe medium;\nDFA or PCR\n(gold standard);\nLymphocytosis++\n(pertussis toxin);\nFilamentous\nhemagglutinin (FHA)",
             "Whooping cough:\nCatarrhal → Paroxysmal\n(whoop + apnoea) →\nConvalescent;\nMost severe in infants;\nVaccine-preventable",
             "Azithromycin (DOC);\nClarithromycin;\nTMP-SMX (alternative);\nTreat close contacts;\nVaccine: DTaP/Tdap"),

            ("Campylobacter", "C. jejuni",
             "Does not grow on\nstandard MacConkey\n(CCDA/Skirrow)", "Microaerophile\n(5% O₂)",
             "POSITIVE",
             "Skirrow or CCDA\nmedium; 42°C;\nComma/S-shaped rods;\nDarting motility;\nOxidase+; Hippurate+\n(distinguishes from\nC. coli)",
             "Most common bacterial\ndiarrhoea worldwide;\nbloody diarrhoea;\npost-infectious GBS\n(Guillain-Barré);\nReactive arthritis;\nZoonosis (poultry)",
             "Mild: self-limiting;\nSevere: Azithromycin;\nAlternative: FQ\n(but resistance rising);\nNEVER\ncephalosporins"),

            ("Helicobacter", "H. pylori",
             "Does not grow on\nMacConkey\n(Skirrow/CA)", "Microaerophile\n(5% O₂)",
             "POSITIVE",
             "Urease+++ (CLO test);\nOxidase+; Catalase+;\nSpiral rods;\nGrows at 37°C;\nUrea breath test;\nStool antigen test;\nHistology (Giemsa)",
             "Peptic ulcer disease\n(gastric + duodenal);\nGastric adenocarcinoma;\nMALT lymphoma;\nFunctional dyspepsia;\nPresent in ~50% world\npopulation",
             "Triple therapy:\nPPI + Clarithromycin +\nAmoxicillin ×7–14d;\nQuadruple (bismuth):\nPPI+Bismuth+Metronidazole\n+Tetracycline;\nLevo-based for resistant"),

            ("Vibrio", "V. cholerae\n(O1 / O139)",
             "Pale/colourless on\nMacConkey;\nGrows on TCBS\n(yellow colonies)", "Fac. Anaerobe",
             "POSITIVE",
             "Oxidase+; Curved rod;\nRapid darting motility;\nTCBS agar (yellow\ncolonies = cholera);\nO1 antigen: El Tor\n(El Tor biotype\nnow dominant);\nCholeragen toxin",
             "CHOLERA:\nRice-water diarrhoea;\nmassive fluid loss\n(up to 20 L/day);\nHypovolaemic shock;\nmortality without Rx",
             "ORS/IV fluids (main Rx);\nDoxycycline;\nAzithromycin;\nSingle dose cipro"),

            ("Neisseria", "N. meningitidis",
             "Does not grow\non MacConkey\n(chocolate agar)",  "Strict Aerobe",
             "POSITIVE",
             "Oxidase+; Gram-neg\ndiplococcus; Ferments\nglucose AND maltose\n(vs. N. gonorrhoeae);\nPolysaccharide capsule\nserogroups A,B,C,W,Y;\nCSF India ink−",
             "Bacterial meningitis;\nWaterhouse-Friderichsen\nsyndrome (adrenal\nhaemorrhage, DIC);\nMeningococcaemia;\nPetechial/purpuric rash;\nHigh mortality without Rx",
             "Ceftriaxone (DOC);\nPenicillin G (if sens.);\nChemoprophylaxis:\nRifampicin or\nciprofloxacin for\nclose contacts;\nVaccines: MenACWY,\nMenB"),

            ("Neisseria", "N. gonorrhoeae",
             "Does not grow\non MacConkey\n(Thayer-Martin)", "Strict Aerobe",
             "POSITIVE",
             "Oxidase+; Gram-neg\ndiplococcus; Ferments\nglucose ONLY;\nRequires CO₂;\nThayer-Martin medium;\nIntracellular in PMNs\non Gram smear;\nNuclease+",
             "Gonorrhoea (urethritis,\ncervicitis);\nPID; Fitz-Hugh-\nCurtis syndrome;\nSeptic arthritis\n(DGI); Neonatal\nophthalmia neonatorum",
             "Ceftriaxone 500mg IM\n(dual Rx: +\nazithromycin if\nchlamydia not excluded);\nNo fluoroquinolones\n(widespread resistance)"),
        ]
    ),
]

# ── Build tables ──────────────────────────────────────────────────────────────
def make_title():
    total_w = sum(CW)
    tt = Table([
        [Paragraph("<b>GRAM-NEGATIVE BACILLI (GNB)</b>",
                   sty("T1", fontSize=19, fontName="Helvetica-Bold",
                       textColor=WHITE, alignment=TA_CENTER))],
        [Paragraph("LACTOSE FERMENTERS (LF)  ⟵  MacConkey Agar  ⟶  NON-LACTOSE FERMENTERS (NLF)",
                   sty("T2", fontSize=10, fontName="Helvetica",
                       textColor=colors.HexColor("#aaccee"), alignment=TA_CENTER))],
        [Paragraph("Complete Species Reference  ·  Taxonomy · Colony Appearance · Key Tests · Disease · Treatment  ·  Orris Medical Reference 2026",
                   sty("T3", fontSize=8, fontName="Helvetica-Oblique",
                       textColor=colors.HexColor("#88aacc"), alignment=TA_CENTER))],
    ], colWidths=[total_w])
    tt.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(0,2), NAVY),
        ("TOPPADDING",   (0,0),(0,2), 5),
        ("BOTTOMPADDING",(0,0),(0,2), 5),
    ]))
    return tt

def make_macckey_banner(lf=True):
    total_w = sum(CW)
    if lf:
        text  = "🔴  LACTOSE FERMENTERS (LF)  —  PINK to PINK-PURPLE colonies on MacConkey Agar  (acid + bile precipitate = colour change)"
        bg    = LF_DARK
    else:
        text  = "⬜  NON-LACTOSE FERMENTERS (NLF)  —  COLOURLESS / PALE colonies on MacConkey Agar  (no acid from lactose)"
        bg    = NLF_DARK
    tt = Table([[Paragraph(f"  <b>{text}</b>",
                           sty("BN", fontSize=10, fontName="Helvetica-Bold",
                               textColor=WHITE, alignment=TA_LEFT, leading=12))]],
               colWidths=[total_w])
    tt.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(0,0), bg),
        ("TOPPADDING",(0,0),(0,0),5),("BOTTOMPADDING",(0,0),(0,0),5),
        ("LEFTPADDING",(0,0),(0,0),10),
    ]))
    return tt

def make_subgroup_banner(label, bg):
    total_w = sum(CW)
    tt = Table([[Paragraph(f"  <b>{label}</b>",
                           sty("SG", fontSize=8.5, fontName="Helvetica-Bold",
                               textColor=WHITE, alignment=TA_LEFT, leading=11))]],
               colWidths=[total_w])
    tt.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(0,0), bg),
        ("TOPPADDING",(0,0),(0,0),3),("BOTTOMPADDING",(0,0),(0,0),3),
        ("LEFTPADDING",(0,0),(0,0),10),
    ]))
    return tt

def build_data_table(groups, row_offset=0):
    """Build one Table object for a list of subgroups."""
    all_rows  = [HDR_ROW]
    cmd = [
        ("GRID",      (0,0),(-1,-1), 0.3, colors.HexColor("#bbbbbb")),
        ("BACKGROUND",(0,0),(-1,0), GREY),
        ("VALIGN",    (0,0),(-1,-1), "TOP"),
        ("ALIGN",     (0,0),(-1,-1), "LEFT"),
        ("ALIGN",     (0,0),(-1,0), "CENTER"),
        ("TOPPADDING",    (0,0),(-1,-1), 3),
        ("BOTTOMPADDING", (0,0),(-1,-1), 3),
        ("LEFTPADDING",   (0,0),(-1,-1), 4),
        ("RIGHTPADDING",  (0,0),(-1,-1), 3),
        ("LINEBELOW",(0,0),(-1,0), 1.0, WHITE),
    ]

    row_num = 0  # data counter (for numbering)
    table_row_idx = 1  # 0 = header

    for grp_label, grp_bg, rows in groups:
        # Sub-group separator row
        sep_row = [Paragraph(f"<b>  {grp_label}</b>",
                             sty("SR", fontSize=8.5, fontName="Helvetica-Bold",
                                 textColor=WHITE, alignment=TA_LEFT, leading=11))]
        sep_row += [p("")] * (len(CW) - 1)
        all_rows.append(sep_row)
        cmd.append(("SPAN",       (0,table_row_idx),(-1,table_row_idx)))
        cmd.append(("BACKGROUND", (0,table_row_idx),(-1,table_row_idx), grp_bg))
        cmd.append(("LINEABOVE",  (0,table_row_idx),(-1,table_row_idx), 1.0, colors.HexColor("#666")))
        table_row_idx += 1

        for row in rows:
            genus, spp, macconkey, o2, oxidase, tests, disease, rx = row
            tr = [
                pc(str(row_offset + row_num + 1)),
                pb(genus),
                pi(spp),
                p(macconkey),
                pc(o2),
                Paragraph(f"<b>{oxidase}</b>",
                          sty("OX", fontSize=7.5, fontName="Helvetica-Bold",
                              textColor=(colors.HexColor("#1e8449") if "POSITIVE" in oxidase.upper()
                                         else colors.HexColor("#c0392b")),
                              alignment=TA_CENTER, leading=9)),
                p(tests),
                p(disease),
                p(rx),
            ]
            bg = LF_LIGHT if row_num % 2 == 0 else LF_PALE
            all_rows.append(tr)
            cmd.append(("BACKGROUND", (0,table_row_idx),(-1,table_row_idx),
                        bg if "LF" in grp_label else
                        (NLF_LIGHT if row_num % 2 == 0 else NLF_PALE)))
            table_row_idx += 1
            row_num += 1

    ts = TableStyle(cmd)
    t  = Table(all_rows, colWidths=CW, repeatRows=1)
    t.setStyle(ts)
    return t, row_num

# ── Legend ────────────────────────────────────────────────────────────────────
total_w = sum(CW)
def make_legend():
    legend_data = [
        [pb("MacConkey Agar Key:"),
         p("Pink/Pink-Purple = Lactose Fermenters (acid from lactose → colour change with neutral red indicator)"),
         pb("   Colourless/Pale = Non-Lactose Fermenters (no acid production)"),
         p("Yellow on TCBS = Vibrio cholerae")],
    ]
    lt = Table(legend_data, colWidths=[60, 160, 130, 90])
    lt.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(-1,-1), LGREY),
        ("BOX",(0,0),(-1,-1),0.8, colors.grey),
        ("VALIGN",(0,0),(-1,-1),"MIDDLE"),
        ("TOPPADDING",(0,0),(-1,-1),4),("BOTTOMPADDING",(0,0),(-1,-1),4),
        ("LEFTPADDING",(0,0),(-1,-1),5),
    ]))
    return lt

NOTES = [
    "O₂ Req: Fac. Anaerobe = Facultative Anaerobe (grows with or without O₂). Strict Aerobe = requires O₂. Microaerophile = requires 5% O₂.",
    "TSI = Triple Sugar Iron agar: K/A = alkaline slant/acid butt; A/A = acid/acid. H₂S+ = black precipitate. IMViC = Indole, Methyl Red, Voges-Proskauer, Citrate.",
    "Oxidase+/− refers to cytochrome C oxidase test. All Enterobacteriaceae are Oxidase−. Pseudomonas, Campylobacter, Helicobacter, Neisseria, Vibrio are Oxidase+.",
    "ESBL-producing species (E. coli, Klebsiella, Proteus, Enterobacter, Citrobacter): always confirm susceptibility; carbapenem for serious infections.",
    "Sources: Medical Microbiology 9e (Murray et al.), pp. 296-298; Henry's Clinical Diagnosis & Laboratory Methods; Harriet Lane Handbook 23e.",
]

# ── Assemble ──────────────────────────────────────────────────────────────────
elements = []
elements.append(make_title())
elements.append(Spacer(1, 5))

# LF section
elements.append(make_macckey_banner(lf=True))
elements.append(Spacer(1, 4))
lf_table, lf_count = build_data_table(LF_SUBGROUPS, row_offset=0)
elements.append(lf_table)
elements.append(Spacer(1, 8))

# NLF section
elements.append(make_macckey_banner(lf=False))
elements.append(Spacer(1, 4))
nlf_table, nlf_count = build_data_table(NLF_SUBGROUPS, row_offset=lf_count)
elements.append(nlf_table)
elements.append(Spacer(1, 6))

# Legend + notes
elements.append(make_legend())
elements.append(Spacer(1, 5))
for n in NOTES:
    elements.append(Paragraph(n, NOTE))
    elements.append(Spacer(1, 2))

doc.build(elements)
print(f"PDF saved: {OUTPUT}")