import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from matplotlib.patches import FancyArrowPatch
import warnings
warnings.filterwarnings('ignore')

# ─── ECG paper style ───────────────────────────────────────────────────────────
def ecg_paper(ax, xmax=10, ymin=-1.5, ymax=2.5):
    ax.set_facecolor('#fff8f0')
    for x in np.arange(0, xmax+0.04, 0.04):
        ax.axvline(x, color='#ffcccc', lw=0.3)
    for y in np.arange(ymin, ymax+0.1, 0.1):
        ax.axhline(y, color='#ffcccc', lw=0.3)
    for x in np.arange(0, xmax+0.2, 0.2):
        ax.axvline(x, color='#ff9999', lw=0.7)
    for y in np.arange(ymin, ymax+0.5, 0.5):
        ax.axhline(y, color='#ff9999', lw=0.7)
    ax.set_xlim(0, xmax)
    ax.set_ylim(ymin, ymax)
    ax.axis('off')

# ─── Building blocks ───────────────────────────────────────────────────────────
def p_wave(t, amp=0.2, width=0.08):
    return amp * np.exp(-((t)**2) / (2*(width/2.5)**2))

def qrs_normal(t, amp=1.0):
    q = -0.1 * np.exp(-((t+0.02)**2)/(2*0.008**2))
    r = amp  * np.exp(-((t)    **2)/(2*0.010**2))
    s = -0.3 * np.exp(-((t-0.03)**2)/(2*0.010**2))
    return q + r + s

def t_wave(t, amp=0.3, width=0.07, skew=0):
    return amp * np.exp(-((t-skew)**2)/(2*(width)**2))

def u_wave(t, amp=0.06):
    return amp * np.exp(-((t)**2)/(2*0.04**2))

def single_beat(t_arr, start, pr=0.16, qrs_amp=1.0, st_elev=0.0,
                st_depr=0.0, t_amp=0.3, t_inv=False, delta=False,
                p_amp=0.2, hyperacute_t=False, q_deep=False):
    sig = np.zeros_like(t_arr)
    t = t_arr - start
    # P wave
    mask_p = (t > 0) & (t < 0.12)
    sig[mask_p] += p_wave(t[mask_p] - 0.06, amp=p_amp)
    # Delta wave (WPW)
    if delta:
        mask_d = (t > pr-0.05) & (t < pr)
        sig[mask_d] += 0.3 * (t[mask_d]-(pr-0.05)) / 0.05
    # QRS
    mask_qrs = (t > pr) & (t < pr+0.12)
    q_amp = -0.4 if q_deep else -0.1
    sig[mask_qrs] += qrs_normal(t[mask_qrs]-pr-0.04, amp=qrs_amp)
    if q_deep:
        sig[mask_qrs] += (-0.3)*np.exp(-((t[mask_qrs]-pr-0.01)**2)/(2*0.015**2))
    # ST segment
    mask_st = (t > pr+0.12) & (t < pr+0.28)
    sig[mask_st] += st_elev - st_depr
    # T wave
    t_a = 0.6 if hyperacute_t else t_amp
    t_a = -abs(t_a) if t_inv else abs(t_a)
    mask_t = (t > pr+0.18) & (t < pr+0.45)
    sig[mask_t] += t_wave(t[mask_t]-pr-0.32, amp=t_a,
                          width=(0.05 if hyperacute_t else 0.07))
    return sig

# ═══════════════════════════════════════════════════════════════════════════════
# 1. NORMAL ECG
# ═══════════════════════════════════════════════════════════════════════════════
fig, ax = plt.subplots(figsize=(14, 4))
ecg_paper(ax, xmax=6, ymin=-0.8, ymax=2.0)
t = np.linspace(0, 6, 6000)
sig = np.zeros_like(t)
for s in [0.3, 1.1, 1.9, 2.7, 3.5, 4.3, 5.1]:
    sig += single_beat(t, s)
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('NORMAL ECG - Sab Kuch Theek Hai', fontsize=13, fontweight='bold', color='#1a1a6e', pad=10)

# Annotations
beat_s = 0.3
ax.annotate('P wave\n(Atrial depol.)', xy=(beat_s+0.06, 0.22), xytext=(beat_s-0.2, 0.7),
            arrowprops=dict(arrowstyle='->', color='blue', lw=1.5),
            fontsize=8, color='blue', fontweight='bold')
ax.annotate('Q', xy=(beat_s+0.16+0.14, -0.05), xytext=(beat_s+0.05, -0.5),
            arrowprops=dict(arrowstyle='->', color='darkgreen', lw=1.5),
            fontsize=8, color='darkgreen', fontweight='bold')
ax.annotate('R wave\n(Peak)', xy=(beat_s+0.20, 1.0), xytext=(beat_s+0.45, 1.6),
            arrowprops=dict(arrowstyle='->', color='red', lw=1.5),
            fontsize=8, color='red', fontweight='bold')
ax.annotate('S', xy=(beat_s+0.23, -0.25), xytext=(beat_s+0.5, -0.6),
            arrowprops=dict(arrowstyle='->', color='darkgreen', lw=1.5),
            fontsize=8, color='darkgreen', fontweight='bold')
ax.annotate('ST seg.\n(Isoelectric)', xy=(beat_s+0.34, 0.02), xytext=(beat_s+0.6, 0.5),
            arrowprops=dict(arrowstyle='->', color='purple', lw=1.5),
            fontsize=8, color='purple', fontweight='bold')
ax.annotate('T wave\n(Ventricular repol.)', xy=(beat_s+0.48, 0.3), xytext=(beat_s+0.7, 0.85),
            arrowprops=dict(arrowstyle='->', color='darkorange', lw=1.5),
            fontsize=8, color='darkorange', fontweight='bold')
# PR interval brace
ax.annotate('', xy=(beat_s+0.16, -0.7), xytext=(beat_s, -0.7),
            arrowprops=dict(arrowstyle='<->', color='navy', lw=1.5))
ax.text(beat_s+0.08, -0.75, 'PR 0.12-0.20s', fontsize=7, color='navy', ha='center')
# QRS brace
ax.annotate('', xy=(beat_s+0.28, -0.7), xytext=(beat_s+0.16, -0.7),
            arrowprops=dict(arrowstyle='<->', color='darkred', lw=1.5))
ax.text(beat_s+0.22, -0.75, 'QRS <0.12s', fontsize=7, color='darkred', ha='center')

plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/01_normal_ecg.png', dpi=130, bbox_inches='tight')
plt.close()
print("1. Normal ECG done")

# ═══════════════════════════════════════════════════════════════════════════════
# 2. STEMI (Inferior) - II, III, aVF
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(2, 1, figsize=(14, 8))
fig.patch.set_facecolor('#f0f4ff')

for idx, (label, st_e, t_amp, q_d, title_c) in enumerate([
    ('Lead II / III / aVF  →  INFERIOR MI', 0.35, 0.4, True, '#cc0000'),
    ('Lead V1-V4  →  Reciprocal ST Depression', -0.0, 0.2, False, '#0055aa'),
]):
    ax = axes[idx]
    ecg_paper(ax, xmax=6, ymin=-0.8, ymax=2.2)
    t = np.linspace(0, 6, 6000)
    sig = np.zeros_like(t)
    for s in [0.3, 1.2, 2.1, 3.0, 3.9, 4.8]:
        st_d = 0.25 if idx == 1 else 0
        sig += single_beat(t, s, st_elev=st_e if idx==0 else 0,
                           st_depr=st_d, t_amp=t_amp, q_deep=q_d if idx==0 else False)
    ax.plot(t, sig, 'k', lw=1.5)
    ax.set_title(label, fontsize=11, fontweight='bold', color=title_c, pad=6)

    if idx == 0:
        s = 0.3
        ax.annotate('⬆ ST Elevation\n(Myocardial injury!)', xy=(s+0.34, 0.37),
                    xytext=(s+0.7, 1.1),
                    arrowprops=dict(arrowstyle='->', color='red', lw=2),
                    fontsize=9, color='red', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.8))
        ax.annotate('Pathological Q wave\n(Dead tissue = Necrosis)', xy=(s+0.175, -0.28),
                    xytext=(s+0.5, -0.65),
                    arrowprops=dict(arrowstyle='->', color='darkred', lw=2),
                    fontsize=9, color='darkred', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffdddd', alpha=0.9))
        ax.annotate('Hyperacute T\n(Early ischemia)', xy=(s+0.49, 0.42),
                    xytext=(s+1.1, 0.9),
                    arrowprops=dict(arrowstyle='->', color='darkorange', lw=2),
                    fontsize=9, color='darkorange', fontweight='bold')
    else:
        s = 0.3
        ax.annotate('⬇ Reciprocal ST Depression\n(Mirror image of injury)', xy=(s+0.30, -0.23),
                    xytext=(s+0.8, 0.4),
                    arrowprops=dict(arrowstyle='->', color='blue', lw=2),
                    fontsize=9, color='blue', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))

fig.suptitle('❤ STEMI - INFERIOR MI (RCA Occlusion)\nII, III, aVF mein ST↑ + V1-V4 mein Reciprocal ST↓',
             fontsize=13, fontweight='bold', color='#8b0000', y=1.02)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/02_inferior_stemi.png', dpi=130, bbox_inches='tight')
plt.close()
print("2. Inferior STEMI done")

# ═══════════════════════════════════════════════════════════════════════════════
# 3. STEMI (Anterior) - V1-V4
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(3, 1, figsize=(14, 11))
fig.patch.set_facecolor('#fff0f0')

stages = [
    ('Stage 1: Hyperacute T waves (Minutes)', 0.0, 0.7, False, False, '#ff6600'),
    ('Stage 2: ST Elevation (Hours) - Classic STEMI', 0.45, 0.35, False, False, '#cc0000'),
    ('Stage 3: Q waves + T inversion (Days)', 0.15, -0.2, True, True, '#6600aa'),
]
for idx, (label, st_e, t_a, t_inv, q_d, col) in enumerate(stages):
    ax = axes[idx]
    ecg_paper(ax, xmax=6, ymin=-0.8, ymax=2.0)
    t = np.linspace(0, 6, 6000)
    sig = np.zeros_like(t)
    for s in [0.3, 1.2, 2.1, 3.0, 3.9, 4.8]:
        sig += single_beat(t, s, st_elev=st_e, t_amp=t_a, t_inv=t_inv,
                           q_deep=q_d, hyperacute_t=(idx==0))
    ax.plot(t, sig, 'k', lw=1.5)
    ax.set_title(label, fontsize=10, fontweight='bold', color=col, pad=5)
    s = 0.3
    if idx == 0:
        ax.annotate('TALL PEAKED T wave\n(Hyperacute - very early!)', xy=(s+0.48, 0.65),
                    xytext=(s+1.0, 1.5),
                    arrowprops=dict(arrowstyle='->', color='#ff6600', lw=2),
                    fontsize=8.5, color='#ff6600', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#fff3cc', alpha=0.9))
    elif idx == 1:
        ax.annotate('ST ELEVATION (Tombstone shape)\nConvex upward = INJURY', xy=(s+0.30, 0.47),
                    xytext=(s+0.9, 1.4),
                    arrowprops=dict(arrowstyle='->', color='red', lw=2.5),
                    fontsize=8.5, color='red', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.85))
    elif idx == 2:
        ax.annotate('Deep Q wave (>0.04s, >25% R)\nPermanent Scar (Necrosis)', xy=(s+0.175, -0.35),
                    xytext=(s+0.7, -0.65),
                    arrowprops=dict(arrowstyle='->', color='darkred', lw=2),
                    fontsize=8.5, color='darkred', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffdddd', alpha=0.9))
        ax.annotate('T wave INVERSION\n(Repolarisation abnormality)', xy=(s+0.48, -0.18),
                    xytext=(s+1.1, 0.5),
                    arrowprops=dict(arrowstyle='->', color='purple', lw=2),
                    fontsize=8.5, color='purple', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#eeddff', alpha=0.9))

fig.suptitle('❤ ANTERIOR STEMI (LAD Occlusion)\nV1, V2, V3, V4 leads mein changes - 3 Stages',
             fontsize=13, fontweight='bold', color='#8b0000', y=1.02)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/03_anterior_stemi.png', dpi=130, bbox_inches='tight')
plt.close()
print("3. Anterior STEMI done")

# ═══════════════════════════════════════════════════════════════════════════════
# 4. AV BLOCKS
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(4, 1, figsize=(14, 14))
fig.patch.set_facecolor('#f0fff0')

# 1st degree
ax = axes[0]
ecg_paper(ax, xmax=7, ymin=-0.6, ymax=1.8)
t = np.linspace(0, 7, 7000)
sig = np.zeros_like(t)
for s in [0.3, 1.4, 2.5, 3.6, 4.7, 5.8]:
    sig += single_beat(t, s, pr=0.28)   # long PR
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('1st Degree AV Block  –  PR > 200 ms (1 large box)', fontsize=11, fontweight='bold', color='#006600', pad=5)
s = 0.3
ax.annotate('P wave', xy=(s+0.06, 0.2), xytext=(s-0.1, 0.8),
            arrowprops=dict(arrowstyle='->', color='blue'), fontsize=9, color='blue')
ax.annotate('PROLONGED PR INTERVAL\n(>200ms / >1 large box)\n= AV Node Delay', xy=(s+0.14, 0.0),
            xytext=(s+0.5, 0.8),
            arrowprops=dict(arrowstyle='->', color='darkgreen', lw=2),
            fontsize=8.5, color='darkgreen', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddffdd', alpha=0.9))
ax.annotate('', xy=(s+0.28, -0.4), xytext=(s, -0.4),
            arrowprops=dict(arrowstyle='<->', color='darkgreen', lw=2))
ax.text(s+0.14, -0.5, '← LONG PR →', fontsize=8, color='darkgreen', ha='center', fontweight='bold')

# Mobitz I
ax = axes[1]
ecg_paper(ax, xmax=7, ymin=-0.6, ymax=1.8)
t = np.linspace(0, 7, 7000)
sig = np.zeros_like(t)
starts = [0.3, 1.22, 2.06, 2.82]  # getting closer (RR shortening)
prs =    [0.16, 0.22, 0.28, 0.34] # increasing PR
for s, pr in zip(starts, prs):
    sig += single_beat(t, s, pr=pr)
# Drop beat - only P wave
sig += single_beat(t, 3.5, pr=10, p_amp=0.2)  # P without QRS
for s, pr in zip([4.3, 5.2, 6.0, 6.78], [0.16, 0.22, 0.28, 0.34]):
    sig += single_beat(t, s, pr=pr)
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('2nd Degree Mobitz I (Wenckebach)  –  PR progressively badhta hai, phir QRS DROP!', fontsize=11, fontweight='bold', color='#cc6600', pad=5)
ax.annotate('PR badhta\njaa raha hai ↗', xy=(2.06+0.1, 0.1), xytext=(1.5, 1.2),
            arrowprops=dict(arrowstyle='->', color='darkorange', lw=2),
            fontsize=8.5, color='darkorange', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffe0aa', alpha=0.9))
ax.annotate('DROPPED BEAT!\n(QRS missing - P wave only)', xy=(3.56, 0.18), xytext=(3.8, 1.2),
            arrowprops=dict(arrowstyle='->', color='red', lw=2),
            fontsize=8.5, color='red', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.9))
ax.axvspan(3.4, 4.2, alpha=0.12, color='red')

# Mobitz II
ax = axes[2]
ecg_paper(ax, xmax=7, ymin=-0.6, ymax=1.8)
t = np.linspace(0, 7, 7000)
sig = np.zeros_like(t)
for s in [0.3, 1.3, 2.3, 3.3]:
    sig += single_beat(t, s, pr=0.18)
# dropped beat P
sig += single_beat(t, 4.3, pr=15, p_amp=0.2)
for s in [5.3, 6.3]:
    sig += single_beat(t, s, pr=0.18)
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('2nd Degree Mobitz II  –  PR Fixed raha, Achanak QRS DROP! (Dangerous!)', fontsize=11, fontweight='bold', color='#aa0000', pad=5)
for sx in [0.3, 1.3, 2.3, 3.3, 5.3, 6.3]:
    ax.axvline(sx+0.18, color='green', lw=1, alpha=0.4, ls='--')
ax.annotate('PR FIXED throughout\n(Koi change nahi)', xy=(1.3+0.09, 0.0), xytext=(0.8, 1.2),
            arrowprops=dict(arrowstyle='->', color='green', lw=2),
            fontsize=8.5, color='darkgreen', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddffdd', alpha=0.9))
ax.annotate('SUDDEN DROP!\n(Without warning)\nPACEMAKER CHAHIYE!', xy=(4.36, 0.18), xytext=(4.7, 1.2),
            arrowprops=dict(arrowstyle='->', color='red', lw=2.5),
            fontsize=8.5, color='red', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.9))
ax.axvspan(4.1, 5.1, alpha=0.15, color='red')

# Complete heart block
ax = axes[3]
ecg_paper(ax, xmax=7, ymin=-0.8, ymax=1.8)
t = np.linspace(0, 7, 7000)
sig = np.zeros_like(t)
# P waves at faster rate (atrial - 75/min)
for s in np.arange(0.2, 7.0, 0.8):
    mt = t - s
    mask = (mt > 0) & (mt < 0.12)
    sig[mask] += p_wave(mt[mask] - 0.06, amp=0.25)
# QRS at slower rate (ventricular escape - 35/min) - COMPLETELY INDEPENDENT
for s in [0.8, 2.5, 4.2, 5.9]:
    sig += single_beat(t, s, pr=10, p_amp=0)  # No P, wide QRS
    # make QRS wider
    mask = (t > s+0.16) & (t < s+0.34)
    sig[mask] += 0.4 * np.sin(np.pi*(t[mask]-s-0.16)/0.18)
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('3rd Degree (Complete) Heart Block  –  AV Dissociation = EMERGENCY!', fontsize=11, fontweight='bold', color='#8b0000', pad=5)
for s in np.arange(0.2, 7.0, 0.8):
    ax.axvline(s+0.06, color='blue', lw=1.2, alpha=0.3, ls=':')
for s in [0.8, 2.5, 4.2, 5.9]:
    ax.axvline(s+0.2, color='red', lw=1.2, alpha=0.3, ls=':')
ax.annotate('P waves (Atria)\nRate ~75/min\n(Regular)', xy=(0.26, 0.25), xytext=(0.0, 1.3),
            arrowprops=dict(arrowstyle='->', color='blue', lw=2),
            fontsize=8.5, color='blue', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
ax.annotate('QRS (Ventricles)\nRate ~35/min\nWIDE (Escape rhythm)\nCOMPLETELY INDEPENDENT!', xy=(0.96, 0.9), xytext=(1.6, 1.5),
            arrowprops=dict(arrowstyle='->', color='red', lw=2),
            fontsize=8.5, color='red', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffdddd', alpha=0.9))

fig.suptitle('AV HEART BLOCKS - Sabhi 4 Types with ECG Marks\n(1st → 2nd Mobitz I → 2nd Mobitz II → Complete)',
             fontsize=14, fontweight='bold', color='#003300', y=1.01)
plt.tight_layout(h_pad=2.5)
plt.savefig('/home/daytona/workspace/ecg-guide/04_av_blocks.png', dpi=130, bbox_inches='tight')
plt.close()
print("4. AV Blocks done")

# ═══════════════════════════════════════════════════════════════════════════════
# 5. ATRIAL FIBRILLATION vs FLUTTER
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(2, 1, figsize=(14, 8))
fig.patch.set_facecolor('#f5f0ff')

# AF
ax = axes[0]
ecg_paper(ax, xmax=8, ymin=-0.8, ymax=1.8)
t = np.linspace(0, 8, 8000)
sig = np.zeros_like(t)
# fibrillatory baseline (irregular bumps)
np.random.seed(42)
for _ in range(180):
    pos = np.random.uniform(0, 8)
    amp = np.random.uniform(0.04, 0.12)
    sig += amp * np.exp(-((t-pos)**2)/(2*0.02**2))
# irregularly irregular QRS
qrs_times = [0.4, 1.05, 1.55, 2.4, 2.75, 3.6, 4.1, 4.95, 5.6, 6.0, 6.8, 7.5]
for s in qrs_times:
    sig += single_beat(t, s, pr=10, p_amp=0)
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('ATRIAL FIBRILLATION (AF)  –  Chaotic baseline, No P waves, Irregular-Irregular QRS', fontsize=11, fontweight='bold', color='#5500aa', pad=5)
ax.annotate('Fibrillatory baseline\n(P waves ABSENT)\nChaotic, wavy line', xy=(0.7, 0.1), xytext=(0.2, 1.2),
            arrowprops=dict(arrowstyle='->', color='purple', lw=2),
            fontsize=8.5, color='purple', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#eeddff', alpha=0.9))
ax.annotate('IRREGULAR-IRREGULAR\nQRS spacing\n(Totally unpredictable)', xy=(4.1, 0.9), xytext=(4.8, 1.5),
            arrowprops=dict(arrowstyle='->', color='red', lw=2),
            fontsize=8.5, color='red', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.85))
# mark irregular spacing
for i in range(len(qrs_times)-1):
    ax.annotate('', xy=(qrs_times[i+1]+0.05, -0.55), xytext=(qrs_times[i]+0.05, -0.55),
                arrowprops=dict(arrowstyle='<->', color='darkblue', lw=1))

# Atrial Flutter
ax = axes[1]
ecg_paper(ax, xmax=8, ymin=-0.8, ymax=1.8)
t = np.linspace(0, 8, 8000)
sig = np.zeros_like(t)
# sawtooth flutter waves at 300/min → 0.2s cycle
for ft in np.arange(0.1, 8.0, 0.2):
    mt = t - ft
    mask = (mt >= 0) & (mt < 0.18)
    # sawtooth: negative slope then sharp up
    sig[mask] += -0.18 * mt[mask]/0.18 + 0.09 * np.exp(-((mt[mask]-0.16)**2)/(2*0.012**2))
# QRS every 0.4s (2:1 conduction → 150/min)
for s in np.arange(0.35, 8.0, 0.4):
    sig += single_beat(t, s, pr=10, p_amp=0) * 1.0
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('ATRIAL FLUTTER  –  Sawtooth waves 300/min, 2:1 → Ventricular rate 150/min', fontsize=11, fontweight='bold', color='#006699', pad=5)
ax.annotate('"Sawtooth / Picket fence"\nFlutter waves (F waves)\n~300/min, regular', xy=(1.0, -0.1), xytext=(0.5, -0.6),
            arrowprops=dict(arrowstyle='->', color='navy', lw=2),
            fontsize=8.5, color='navy', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
ax.annotate('QRS: REGULAR\n(2:1 block → 150 bpm)\nHR exactly 150 = THINK FLUTTER!', xy=(1.55, 0.95), xytext=(2.2, 1.5),
            arrowprops=dict(arrowstyle='->', color='red', lw=2),
            fontsize=8.5, color='red', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.85))

fig.suptitle('ATRIAL FIBRILLATION vs ATRIAL FLUTTER\nDono ki ECG mein Key Difference Dekho',
             fontsize=13, fontweight='bold', color='#330066', y=1.02)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/05_af_flutter.png', dpi=130, bbox_inches='tight')
plt.close()
print("5. AF & Flutter done")

# ═══════════════════════════════════════════════════════════════════════════════
# 6. VENTRICULAR TACHYCARDIA + VF
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(2, 1, figsize=(14, 8))
fig.patch.set_facecolor('#fff0f0')

# VT
ax = axes[0]
ecg_paper(ax, xmax=8, ymin=-1.5, ymax=2.5)
t = np.linspace(0, 8, 8000)
sig = np.zeros_like(t)
# Few normal beats first
for s in [0.3, 1.1]:
    sig += single_beat(t, s)
# Then VT: wide bizarre QRS at rate ~160/min
for s in np.arange(2.0, 8.0, 0.375):
    mt = t - s
    mask = (mt >= 0) & (mt < 0.37)
    # Wide, bizarre monophasic QRS
    sig[mask] += 1.8 * np.sin(np.pi * mt[mask] / 0.375) * np.exp(-mt[mask]/0.3)
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('VENTRICULAR TACHYCARDIA (VT)  –  Wide QRS, Rate >100, No P waves', fontsize=11, fontweight='bold', color='#cc0000', pad=5)
ax.axvspan(0, 1.9, alpha=0.1, color='green', label='Normal')
ax.axvspan(2.0, 8.0, alpha=0.1, color='red', label='VT')
ax.text(0.95, 2.2, 'Normal beats', fontsize=9, color='darkgreen', ha='center',
        bbox=dict(boxstyle='round', facecolor='#ddffdd', alpha=0.8))
ax.text(5.0, 2.2, 'VENTRICULAR TACHYCARDIA begins here ⚠', fontsize=9, color='darkred', ha='center',
        bbox=dict(boxstyle='round', facecolor='#ffdddd', alpha=0.8))
ax.annotate('WIDE QRS (>0.12s)\nBizarre shape\nRate ~160/min', xy=(2.2, 1.6), xytext=(3.0, 2.4),
            arrowprops=dict(arrowstyle='->', color='red', lw=2),
            fontsize=8.5, color='red', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.85))
ax.axvline(2.0, color='red', lw=2.5, ls='--')
ax.text(1.95, -1.3, 'Onset', fontsize=9, color='red', fontweight='bold', ha='right')

# VF
ax = axes[1]
ecg_paper(ax, xmax=8, ymin=-1.5, ymax=2.5)
t = np.linspace(0, 8, 8000)
np.random.seed(7)
sig = np.zeros_like(t)
# Chaotic - multiple frequencies
for f in [3, 4, 5, 7, 9, 11, 14]:
    amp = np.random.uniform(0.3, 0.9)
    phase = np.random.uniform(0, 2*np.pi)
    sig += amp * np.sin(2*np.pi*f*t + phase) * np.exp(-0.05*t) * 0.6
sig += 0.3 * np.random.randn(len(t)) * 0.5
ax.plot(t, sig, 'k', lw=1.2)
ax.set_title('VENTRICULAR FIBRILLATION (VF)  –  COMPLETELY CHAOTIC → No cardiac output → DEATH if not defibrillated!', fontsize=11, fontweight='bold', color='#8b0000', pad=5)
ax.annotate('Completely CHAOTIC\nNo QRS, No P wave\nNo T wave\n= No effective heartbeat!', xy=(1.5, 0.8), xytext=(3.0, 1.8),
            arrowprops=dict(arrowstyle='->', color='darkred', lw=2.5),
            fontsize=9, color='darkred', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.9))
ax.text(4.0, 2.2, '⚡ IMMEDIATE DEFIBRILLATION REQUIRED! ⚡', fontsize=11, color='red',
        ha='center', fontweight='bold',
        bbox=dict(boxstyle='round', facecolor='#ffcccc', alpha=0.9))

fig.suptitle('VT & VF - Life-Threatening Ventricular Arrhythmias\n(Dono mein immediate treatment required!)',
             fontsize=13, fontweight='bold', color='#8b0000', y=1.02)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/06_vt_vf.png', dpi=130, bbox_inches='tight')
plt.close()
print("6. VT & VF done")

# ═══════════════════════════════════════════════════════════════════════════════
# 7. LBBB vs RBBB
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(2, 2, figsize=(14, 8))
fig.patch.set_facecolor('#f0f8ff')

def lbbb_qrs(t, start):
    mt = t - start
    sig = np.zeros_like(t)
    # V1: deep W (QS pattern)
    mask = (mt > 0) & (mt < 0.16)
    sig[mask] += -0.6 * np.sin(np.pi*mt[mask]/0.16)
    return sig

def rbbb_qrs(t, start):
    mt = t - start
    sig = np.zeros_like(t)
    # RSR' in V1
    mask = (mt > 0) & (mt < 0.16)
    r1 = 0.7 * np.exp(-((mt[mask]-0.03)**2)/(2*0.015**2))
    s  = -0.4 * np.exp(-((mt[mask]-0.07)**2)/(2*0.015**2))
    r2 = 0.9 * np.exp(-((mt[mask]-0.12)**2)/(2*0.018**2))
    sig[mask] += r1 + s + r2
    return sig

def rbbb_v6(t, start):
    mt = t - start
    sig = np.zeros_like(t)
    mask = (mt > 0) & (mt < 0.16)
    r = 0.9 * np.exp(-((mt[mask]-0.03)**2)/(2*0.015**2))
    s = -0.5 * np.exp(-((mt[mask]-0.12)**2)/(2*0.020**2))
    sig[mask] += r + s
    return sig

configs = [
    (0, 0, 'LBBB - Lead V1\n(Deep W / QS pattern)', lbbb_qrs, '#000088'),
    (0, 1, 'LBBB - Lead V5/V6\n(Broad notched M pattern)', None, '#000088'),
    (1, 0, "RBBB - Lead V1\n(RSR' pattern = 'Bunny Ears')", rbbb_qrs, '#880000'),
    (1, 1, 'RBBB - Lead V6\n(Broad S wave)', rbbb_v6, '#880000'),
]

for r, c, title, func, col in configs:
    ax = axes[r][c]
    ecg_paper(ax, xmax=5, ymin=-1.0, ymax=1.8)
    t = np.linspace(0, 5, 5000)
    sig = np.zeros_like(t)
    for s in [0.3, 1.4, 2.5, 3.6]:
        # P wave
        mt = t - s
        mask = (mt > 0) & (mt < 0.10)
        sig[mask] += p_wave(mt[mask]-0.05, amp=0.2)
        # QRS
        if func:
            sig += func(t, s+0.16)
        else:
            # LBBB V6: broad notched M
            mask2 = (mt > 0.16) & (mt < 0.34)
            sig[mask2] += 0.9*(np.sin(np.pi*(mt[mask2]-0.16)/0.18)
                               + 0.3*np.sin(2*np.pi*(mt[mask2]-0.16)/0.18))
        # T wave
        mt2 = t - s
        mask3 = (mt2 > 0.36) & (mt2 < 0.56)
        t_inv = (r == 0)  # LBBB has discordant T
        ta = -0.25 if t_inv else 0.25
        sig[mask3] += ta * np.exp(-((mt2[mask3]-0.46)**2)/(2*0.05**2))
    ax.plot(t, sig, 'k', lw=1.8)
    ax.set_title(title, fontsize=9, fontweight='bold', color=col, pad=5)

    if (r, c) == (0, 0):
        ax.annotate('DEEP W (QS)\n= No R wave in V1', xy=(0.3+0.16+0.08, -0.58), xytext=(0.3+0.5, -0.8),
                    arrowprops=dict(arrowstyle='->', color='blue', lw=1.8),
                    fontsize=8, color='blue', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.2', facecolor='#ddeeff', alpha=0.9))
    elif (r, c) == (0, 1):
        ax.annotate('Broad NOTCHED M\n(Rabbit ear / bifid R)', xy=(0.3+0.24, 0.85), xytext=(0.3+0.6, 1.4),
                    arrowprops=dict(arrowstyle='->', color='blue', lw=1.8),
                    fontsize=8, color='blue', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.2', facecolor='#ddeeff', alpha=0.9))
    elif (r, c) == (1, 0):
        ax.annotate("RSR' = Bunny Ears!\nR' taller than R", xy=(0.3+0.16+0.12, 0.88), xytext=(0.3+0.6, 1.4),
                    arrowprops=dict(arrowstyle='->', color='red', lw=1.8),
                    fontsize=8, color='red', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.2', facecolor='#ffdddd', alpha=0.9))
    elif (r, c) == (1, 1):
        ax.annotate('Wide TERMINAL S wave\n(Broad & deep)', xy=(0.3+0.16+0.12, -0.48), xytext=(0.3+0.6, -0.75),
                    arrowprops=dict(arrowstyle='->', color='red', lw=1.8),
                    fontsize=8, color='red', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.2', facecolor='#ffdddd', alpha=0.9))

fig.suptitle('BUNDLE BRANCH BLOCKS\nLBBB: WiLLiaM mnemonic (W in V1, M in V6) | RBBB: MaRRoW mnemonic (M in V1, W in V6)',
             fontsize=12, fontweight='bold', color='#003366', y=1.03)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/07_bbb.png', dpi=130, bbox_inches='tight')
plt.close()
print("7. BBB done")

# ═══════════════════════════════════════════════════════════════════════════════
# 8. WPW SYNDROME
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(1, 2, figsize=(14, 5))
fig.patch.set_facecolor('#fffbf0')

for idx, (title, is_wpw) in enumerate([
    ('NORMAL ECG (Comparison)', False),
    ('WPW SYNDROME - Pre-excitation', True),
]):
    ax = axes[idx]
    ecg_paper(ax, xmax=5, ymin=-0.8, ymax=1.8)
    t = np.linspace(0, 5, 5000)
    sig = np.zeros_like(t)
    for s in [0.3, 1.4, 2.5, 3.6]:
        sig += single_beat(t, s, pr=0.07 if is_wpw else 0.16,
                           delta=is_wpw)
    ax.plot(t, sig, 'k', lw=1.8)
    col = '#aa6600' if is_wpw else '#006600'
    ax.set_title(title, fontsize=10, fontweight='bold', color=col, pad=5)
    s = 0.3
    if is_wpw:
        ax.annotate('SHORT PR (<0.12s)\n= Bypasses AV node!', xy=(s+0.04, 0.01), xytext=(s-0.15, 0.8),
                    arrowprops=dict(arrowstyle='->', color='darkblue', lw=2),
                    fontsize=8.5, color='darkblue', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
        ax.annotate('DELTA WAVE\n(Slurred QRS upstroke)\n= Accessory pathway!', xy=(s+0.09, 0.28), xytext=(s+0.4, 1.3),
                    arrowprops=dict(arrowstyle='->', color='darkorange', lw=2),
                    fontsize=8.5, color='darkorange', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#fff3cc', alpha=0.9))
        ax.annotate('Wide QRS\n(Fusion beat)', xy=(s+0.15, 0.6), xytext=(s+0.6, 1.5),
                    arrowprops=dict(arrowstyle='->', color='red', lw=2),
                    fontsize=8.5, color='red', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffdddd', alpha=0.9))
        # Mark short PR
        ax.annotate('', xy=(s+0.07, -0.55), xytext=(s, -0.55),
                    arrowprops=dict(arrowstyle='<->', color='darkblue', lw=2))
        ax.text(s+0.035, -0.68, 'SHORT PR', fontsize=8, color='darkblue', ha='center', fontweight='bold')

fig.suptitle('WPW SYNDROME (Wolff-Parkinson-White)\nShort PR + Delta wave + Wide QRS = Pre-excitation Triad',
             fontsize=13, fontweight='bold', color='#664400', y=1.05)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/08_wpw.png', dpi=130, bbox_inches='tight')
plt.close()
print("8. WPW done")

# ═══════════════════════════════════════════════════════════════════════════════
# 9. PERICARDITIS
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(2, 1, figsize=(14, 8))
fig.patch.set_facecolor('#f5fffa')

for idx, (title, pr_dep, st_type, col) in enumerate([
    ('Stage I Pericarditis – ALL leads mein Concave (Saddle) ST Elevation + PR Depression', True, 'saddle', '#006600'),
    ('Compare: STEMI – Localized Convex (Tombstone) ST Elevation (only specific leads)', False, 'convex', '#cc0000'),
]):
    ax = axes[idx]
    ecg_paper(ax, xmax=6, ymin=-0.8, ymax=2.0)
    t = np.linspace(0, 6, 6000)
    sig = np.zeros_like(t)
    for s in [0.3, 1.3, 2.3, 3.3, 4.3, 5.3]:
        mt = t - s
        # P wave with PR depression
        mask_p = (mt > 0) & (mt < 0.12)
        sig[mask_p] += p_wave(mt[mask_p]-0.06, amp=0.22)
        if pr_dep:
            mask_pr = (mt > 0.12) & (mt < 0.18)
            sig[mask_pr] -= 0.08  # PR depression
        # QRS
        mask_qrs = (mt > 0.18) & (mt < 0.30)
        sig[mask_qrs] += qrs_normal(mt[mask_qrs]-0.24, amp=0.9)
        # ST + T
        if st_type == 'saddle':
            mask_st = (mt > 0.30) & (mt < 0.55)
            sig[mask_st] += 0.22 * (1 - ((mt[mask_st]-0.425)/0.125)**2) + 0.05  # concave saddle
        else:  # convex tombstone
            mask_st = (mt > 0.30) & (mt < 0.55)
            sig[mask_st] += 0.22 * np.exp(-((mt[mask_st]-0.30)**2)/(2*0.15**2)) + 0.18
        # T wave
        mask_t = (mt > 0.42) & (mt < 0.62)
        sig[mask_t] += 0.3 * np.exp(-((mt[mask_t]-0.52)**2)/(2*0.06**2))
    ax.plot(t, sig, 'k', lw=1.5)
    ax.set_title(title, fontsize=10, fontweight='bold', color=col, pad=5)
    s = 0.3
    if idx == 0:
        ax.annotate('CONCAVE / SADDLE shape\n(U shape mein ST↑)\nDIFFUSE - ALL leads mein!', xy=(s+0.40, 0.28),
                    xytext=(s+0.85, 1.2),
                    arrowprops=dict(arrowstyle='->', color='darkgreen', lw=2),
                    fontsize=8.5, color='darkgreen', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddffdd', alpha=0.9))
        ax.annotate('PR DEPRESSION\n(Pericarditis ka\nPathognomonic sign!)', xy=(s+0.14, -0.06),
                    xytext=(s-0.1, -0.55),
                    arrowprops=dict(arrowstyle='->', color='blue', lw=2),
                    fontsize=8.5, color='blue', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
    else:
        ax.annotate('CONVEX / TOMBSTONE shape\n(Dome shape mein ST↑)\nLOCALIZED - Only 1 territory!', xy=(s+0.32, 0.42),
                    xytext=(s+0.85, 1.4),
                    arrowprops=dict(arrowstyle='->', color='red', lw=2),
                    fontsize=8.5, color='red', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffdddd', alpha=0.9))

fig.suptitle('PERICARDITIS vs STEMI\nSabse Important Difference: Shape + Distribution + PR changes',
             fontsize=13, fontweight='bold', color='#003300', y=1.02)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/09_pericarditis.png', dpi=130, bbox_inches='tight')
plt.close()
print("9. Pericarditis done")

# ═══════════════════════════════════════════════════════════════════════════════
# 10. ELECTROLYTES: Hyperkalemia + Hypokalemia
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(4, 1, figsize=(14, 14))
fig.patch.set_facecolor('#fafff0')

stages_k = [
    ('Normal (K+ = 3.5-5 mmol/L) - Reference', 0.3, 0.0, 0.35, False, 0.05, '#333333'),
    ('Mild Hyperkalemia (K+ 5.5-6.5) - PEAKED T waves (Tent shaped)', 0.35, 0.0, 0.7, False, 0.05, '#cc6600'),
    ('Severe Hyperkalemia (K+ 7-8) - Wide QRS + SINE WAVE', 0.30, 0.0, 0.4, False, 0.05, '#cc0000'),
    ('Hypokalemia (K+ < 3.5) - FLAT T wave + PROMINENT U wave', 0.20, 0.0, 0.06, False, 0.18, '#0055cc'),
]

for i, (title, p_a, st_e, t_a, t_inv, u_a, col) in enumerate(stages_k):
    ax = axes[i]
    ecg_paper(ax, xmax=6, ymin=-0.6, ymax=2.2)
    t = np.linspace(0, 6, 6000)
    sig = np.zeros_like(t)
    for s in [0.3, 1.3, 2.3, 3.3, 4.3, 5.3]:
        mt = t - s
        # P
        mask_p = (mt > 0) & (mt < 0.12)
        sig[mask_p] += p_wave(mt[mask_p]-0.06, amp=p_a)
        # QRS - widen in hyperK
        qrs_w = 0.22 if i == 2 else 0.10
        mask_q = (mt > 0.16) & (mt < 0.16+qrs_w)
        if i == 2:  # sine wave
            sig[mask_q] += 1.5 * np.sin(np.pi*(mt[mask_q]-0.16)/qrs_w)
        else:
            sig[mask_q] += qrs_normal(mt[mask_q]-0.16-qrs_w/2, amp=0.9)
        # T
        mask_t = (mt > 0.30) & (mt < 0.55)
        sig[mask_t] += t_a * np.exp(-((mt[mask_t]-0.42)**2)/(2*(0.025 if i==1 else 0.06)**2))
        # U wave
        if u_a > 0.1:
            mask_u = (mt > 0.58) & (mt < 0.72)
            sig[mask_u] += u_a * np.exp(-((mt[mask_u]-0.65)**2)/(2*0.04**2))
    ax.plot(t, sig, 'k', lw=1.5)
    ax.set_title(title, fontsize=9.5, fontweight='bold', color=col, pad=4)
    s = 0.3
    if i == 1:
        ax.annotate('PEAKED T wave (Tent shaped)\nNarrow base, tall peak\nEarliest sign of HyperK!', xy=(s+0.42, 0.68),
                    xytext=(s+0.9, 1.6),
                    arrowprops=dict(arrowstyle='->', color='darkorange', lw=2),
                    fontsize=8.5, color='darkorange', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#fff3cc', alpha=0.9))
    elif i == 2:
        ax.annotate('SINE WAVE pattern!\nP wave disappears\nWide QRS - DANGER!', xy=(s+0.26, 1.4), xytext=(s+1.0, 2.0),
                    arrowprops=dict(arrowstyle='->', color='red', lw=2.5),
                    fontsize=8.5, color='red', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.9))
    elif i == 3:
        ax.annotate('Flat/Absent T wave', xy=(s+0.42, 0.07), xytext=(s+0.1, 0.8),
                    arrowprops=dict(arrowstyle='->', color='blue', lw=2),
                    fontsize=8.5, color='blue', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
        ax.annotate('PROMINENT U wave\n(After T wave)\nBest seen V2-V3', xy=(s+0.65, 0.18), xytext=(s+1.1, 0.7),
                    arrowprops=dict(arrowstyle='->', color='darkblue', lw=2),
                    fontsize=8.5, color='darkblue', fontweight='bold',
                    bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))

fig.suptitle('ELECTROLYTE DISTURBANCES - ECG Changes\nHyperkalemia (K+↑) vs Hypokalemia (K+↓)',
             fontsize=13, fontweight='bold', color='#003300', y=1.01)
plt.tight_layout(h_pad=2.0)
plt.savefig('/home/daytona/workspace/ecg-guide/10_electrolytes.png', dpi=130, bbox_inches='tight')
plt.close()
print("10. Electrolytes done")

# ═══════════════════════════════════════════════════════════════════════════════
# 11. LVH + RVH
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(1, 2, figsize=(14, 5))
fig.patch.set_facecolor('#fff5ee')

# LVH - V5 lead (tall R wave)
ax = axes[0]
ecg_paper(ax, xmax=5, ymin=-1.0, ymax=3.5)
t = np.linspace(0, 5, 5000)
sig = np.zeros_like(t)
for s in [0.3, 1.4, 2.5, 3.6]:
    sig += single_beat(t, s, qrs_amp=2.8, t_amp=-0.4, t_inv=True)  # tall R, ST strain
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('LVH - Lead V5/V6\nTall R wave (>25mm) + ST strain', fontsize=10, fontweight='bold', color='#8b0000', pad=5)
ax.annotate('TALL R wave\n>25 mm in V5\nSokolow criterion:\nS(V1)+R(V5)≥35mm', xy=(0.3+0.20, 2.8), xytext=(0.3+0.7, 3.2),
            arrowprops=dict(arrowstyle='->', color='darkred', lw=2),
            fontsize=8.5, color='darkred', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffdddd', alpha=0.9))
ax.annotate('ST-T "STRAIN" pattern\n(Asymmetric ST depression\n+ T inversion)', xy=(0.3+0.45, -0.38),
            xytext=(0.3+0.9, -0.8),
            arrowprops=dict(arrowstyle='->', color='purple', lw=2),
            fontsize=8.5, color='purple', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#eeddff', alpha=0.9))
# Measure bar
ax.annotate('', xy=(0.3+0.20, 0.0), xytext=(0.3+0.20, 2.8),
            arrowprops=dict(arrowstyle='<->', color='red', lw=2))
ax.text(0.3+0.33, 1.4, '≥35mm\ntotal', fontsize=8, color='red', fontweight='bold')

# RVH - V1 lead (dominant R)
ax = axes[1]
ecg_paper(ax, xmax=5, ymin=-1.0, ymax=2.2)
t = np.linspace(0, 5, 5000)
sig = np.zeros_like(t)
for s in [0.3, 1.4, 2.5, 3.6]:
    mt = t - s
    mask = (mt > 0) & (mt < 0.12)
    sig[mask] += p_wave(mt[mask]-0.05, amp=0.3)  # P pulmonale (tall P)
    mask2 = (mt > 0.16) & (mt < 0.28)
    # Dominant R in V1
    sig[mask2] += 1.5 * np.exp(-((mt[mask2]-0.22)**2)/(2*0.02**2))
    sig[mask2] -= 0.3 * np.exp(-((mt[mask2]-0.26)**2)/(2*0.012**2))  # small S
    mask3 = (mt > 0.32) & (mt < 0.52)
    sig[mask3] -= 0.3 * np.exp(-((mt[mask3]-0.42)**2)/(2*0.06**2))  # T inversion
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('RVH - Lead V1\nDominant R wave + Right axis deviation', fontsize=10, fontweight='bold', color='#0044aa', pad=5)
ax.annotate('P PULMONALE\n(Tall peaked P >2.5mm)\n= RA enlargement', xy=(0.3+0.06, 0.3), xytext=(0.0, 1.5),
            arrowprops=dict(arrowstyle='->', color='blue', lw=2),
            fontsize=8.5, color='blue', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
ax.annotate('DOMINANT R in V1\n(R/S ratio >1)\n= RVH sign!', xy=(0.3+0.22, 1.5), xytext=(0.3+0.7, 1.9),
            arrowprops=dict(arrowstyle='->', color='darkblue', lw=2),
            fontsize=8.5, color='darkblue', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
ax.annotate('T inversion V1-V3\n(RV strain)', xy=(0.3+0.42, -0.29), xytext=(0.3+0.8, -0.7),
            arrowprops=dict(arrowstyle='->', color='navy', lw=2),
            fontsize=8.5, color='navy', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))

fig.suptitle('VENTRICULAR HYPERTROPHY\nLVH (Hypertension, Aortic Stenosis) | RVH (COPD, Pulmonary Hypertension)',
             fontsize=13, fontweight='bold', color='#440000', y=1.05)
plt.tight_layout()
plt.savefig('/home/daytona/workspace/ecg-guide/11_hypertrophy.png', dpi=130, bbox_inches='tight')
plt.close()
print("11. Hypertrophy done")

# ═══════════════════════════════════════════════════════════════════════════════
# 12. LONG QT + BRUGADA + HYPOTHERMIA (Osborn wave)
# ═══════════════════════════════════════════════════════════════════════════════
fig, axes = plt.subplots(3, 1, figsize=(14, 12))
fig.patch.set_facecolor('#f5f5ff')

# Long QT
ax = axes[0]
ecg_paper(ax, xmax=6, ymin=-0.6, ymax=1.8)
t = np.linspace(0, 6, 6000)
sig = np.zeros_like(t)
for s in [0.3, 1.5, 2.7, 3.9, 5.1]:
    sig += single_beat(t, s, t_amp=0.35)
    # extra long QT - extend ST
    mt = t - s
    mask = (mt > 0.28) & (mt < 0.75)
    sig[mask] += 0.02  # prolonged flat ST
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('LONG QT SYNDROME  –  QTc >450ms (Men) / >470ms (Women)', fontsize=11, fontweight='bold', color='#440088', pad=5)
s = 0.3
ax.annotate('', xy=(s+0.73, -0.4), xytext=(s+0.16, -0.4),
            arrowprops=dict(arrowstyle='<->', color='purple', lw=2))
ax.text(s+0.45, -0.55, '← PROLONGED QT interval →', fontsize=9, color='purple', ha='center', fontweight='bold')
ax.annotate('Long flat ST segment\n(Prolonged repolarization)', xy=(s+0.42, 0.03), xytext=(s+0.8, 0.7),
            arrowprops=dict(arrowstyle='->', color='purple', lw=2),
            fontsize=8.5, color='purple', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#eeddff', alpha=0.9))
ax.text(5.0, 1.5, 'Risk: Torsades de Pointes (TdP)!', fontsize=10, color='red',
        bbox=dict(boxstyle='round', facecolor='yellow', alpha=0.8), fontweight='bold')

# Brugada
ax = axes[1]
ecg_paper(ax, xmax=6, ymin=-0.8, ymax=2.0)
t = np.linspace(0, 6, 6000)
sig = np.zeros_like(t)
for s in [0.3, 1.4, 2.5, 3.6, 4.7]:
    mt = t - s
    # P wave
    mask_p = (mt > 0) & (mt < 0.10)
    sig[mask_p] += p_wave(mt[mask_p]-0.05, amp=0.2)
    # RBBB + Coved ST elevation
    mask_q = (mt > 0.16) & (mt < 0.30)
    # RSR' morphology
    sig[mask_q] += (0.7*np.exp(-((mt[mask_q]-0.19)**2)/(2*0.015**2))
                   - 0.3*np.exp(-((mt[mask_q]-0.22)**2)/(2*0.010**2))
                   + 1.0*np.exp(-((mt[mask_q]-0.26)**2)/(2*0.018**2)))
    # Coved ST: downsloping from peak
    mask_st = (mt > 0.30) & (mt < 0.55)
    sig[mask_st] += 0.5 * np.exp(-3*(mt[mask_st]-0.30)) - 0.05
    # T wave inversion
    mask_t = (mt > 0.42) & (mt < 0.60)
    sig[mask_t] -= 0.15 * np.exp(-((mt[mask_t]-0.51)**2)/(2*0.05**2))
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('BRUGADA SYNDROME (Type 1)  –  V1-V2 mein Coved ST Elevation + RBBB pattern', fontsize=11, fontweight='bold', color='#8b0044', pad=5)
s = 0.3
ax.annotate("RSR' (RBBB morphology)\nin V1", xy=(s+0.26, 0.99), xytext=(s+0.6, 1.6),
            arrowprops=dict(arrowstyle='->', color='darkred', lw=2),
            fontsize=8.5, color='darkred', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ffdddd', alpha=0.9))
ax.annotate('COVED ST elevation\n(Downsloping from peak)\n≥2mm in V1-V2\n= Type 1 Brugada!', xy=(s+0.38, 0.44),
            xytext=(s+0.85, 1.3),
            arrowprops=dict(arrowstyle='->', color='#cc0044', lw=2),
            fontsize=8.5, color='#cc0044', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.9))
ax.annotate('T wave INVERSION', xy=(s+0.51, -0.13), xytext=(s+1.0, -0.5),
            arrowprops=dict(arrowstyle='->', color='navy', lw=2),
            fontsize=8.5, color='navy', fontweight='bold')

# Hypothermia - Osborn wave
ax = axes[2]
ecg_paper(ax, xmax=6, ymin=-0.6, ymax=2.0)
t = np.linspace(0, 6, 6000)
sig = np.zeros_like(t)
for s in [0.3, 1.6, 2.9, 4.2, 5.5]:  # bradycardia
    mt = t - s
    mask_p = (mt > 0) & (mt < 0.14)
    sig[mask_p] += p_wave(mt[mask_p]-0.07, amp=0.22)
    mask_q = (mt > 0.22) & (mt < 0.38)
    sig[mask_q] += qrs_normal(mt[mask_q]-0.30, amp=0.85)
    # Osborn / J wave - positive deflection at J point
    mask_j = (mt > 0.38) & (mt < 0.55)
    sig[mask_j] += 0.45 * np.exp(-((mt[mask_j]-0.46)**2)/(2*0.035**2))
    # Long QT with late T
    mask_t = (mt > 0.58) & (mt < 0.85)
    sig[mask_t] += 0.28 * np.exp(-((mt[mask_t]-0.72)**2)/(2*0.07**2))
ax.plot(t, sig, 'k', lw=1.5)
ax.set_title('HYPOTHERMIA  –  Osborn (J) Waves + Bradycardia + Prolonged intervals', fontsize=11, fontweight='bold', color='#0033aa', pad=5)
s = 0.3
ax.annotate('OSBORN (J) WAVE\n(Hump at J point)\nPathognomonic of\nhypothermia!', xy=(s+0.46, 0.44),
            xytext=(s+0.85, 1.5),
            arrowprops=dict(arrowstyle='->', color='darkblue', lw=2),
            fontsize=8.5, color='darkblue', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
ax.annotate('BRADYCARDIA\n(Rate <50 in\nsevere hypothermia)', xy=(1.6+0.3, 0.85), xytext=(2.0, 1.7),
            arrowprops=dict(arrowstyle='->', color='navy', lw=2),
            fontsize=8.5, color='navy', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.3', facecolor='#ddeeff', alpha=0.9))
ax.annotate('Prolonged QT', xy=(s+0.65, 0.03), xytext=(s+1.1, -0.4),
            arrowprops=dict(arrowstyle='->', color='blue', lw=1.5),
            fontsize=8, color='blue', fontweight='bold')

fig.suptitle('SPECIAL ECG PATTERNS\nLong QT | Brugada Syndrome | Hypothermia',
             fontsize=13, fontweight='bold', color='#220055', y=1.01)
plt.tight_layout(h_pad=2.5)
plt.savefig('/home/daytona/workspace/ecg-guide/12_special_patterns.png', dpi=130, bbox_inches='tight')
plt.close()
print("12. Special patterns done")

print("\n✅ ALL 12 ECG diagrams generated successfully!")