""" Compute Rahu / Ketu sidereal transits at each significant life event of O. J. Simpson, and report the natal-house each node was transiting, plus its current sign and aspect to natal points. Uses Lahiri ayanamsa. Houses are determined by *whole-sign* count from the natal Ascendant (the standard Vedic system). """ import swisseph as swe from datetime import datetime, timedelta, timezone swe.set_sid_mode(swe.SIDM_LAHIRI) FLAGS = swe.FLG_SWIEPH | swe.FLG_SIDEREAL | swe.FLG_SPEED SIGNS = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo', 'Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces'] # ---- Natal data (re-computed for self-containment) ---- BIRTH = datetime(1947, 7, 9, 16, 8, 0, tzinfo=timezone.utc) # 08:08 PST LAT, LON = 37.7749, -122.4194 JD0 = swe.julday(BIRTH.year, BIRTH.month, BIRTH.day, BIRTH.hour + BIRTH.minute/60) def slong(jd, pid): return swe.calc_ut(jd, pid, FLAGS)[0][0] % 360 natal = { 'Sun' : slong(JD0, swe.SUN), 'Moon' : slong(JD0, swe.MOON), 'Mars' : slong(JD0, swe.MARS), 'Mercury': slong(JD0, swe.MERCURY), 'Jupiter': slong(JD0, swe.JUPITER), 'Venus' : slong(JD0, swe.VENUS), 'Saturn' : slong(JD0, swe.SATURN), 'Rahu' : slong(JD0, swe.MEAN_NODE), } natal['Ketu'] = (natal['Rahu'] + 180) % 360 ayan = swe.get_ayanamsa_ut(JD0) cusps_trop, ascmc_trop = swe.houses(JD0, LAT, LON, b'P') ASC = (ascmc_trop[0] - ayan) % 360 asc_sign = int(ASC // 30) # Leo = 4 print(f"Natal Ascendant: {ASC:.2f}° ({SIGNS[asc_sign]})") print(f"Natal Rahu: {natal['Rahu']:.2f}° ({SIGNS[int(natal['Rahu']//30)]})") print(f"Natal Ketu: {natal['Ketu']:.2f}° ({SIGNS[int(natal['Ketu']//30)]})\n") def whole_sign_house(lon): """Whole-sign Vedic house number 1-12, given a sidereal longitude.""" sign_idx = int(lon // 30) return ((sign_idx - asc_sign) % 12) + 1 # ---- Major life events (UT noon used when only date known) ---- EVENTS = [ ("1947-07-09", "Birth (San Francisco)"), ("1949-07-09", "~Age 2 — diagnosed with rickets, leg braces"), ("1960-07-09", "~Age 13 — joins Persian Warriors gang"), ("1967-06-24", "Marries Marguerite Whitley"), ("1968-12-04", "Wins Heisman Trophy / daughter Arnelle born"), ("1969-01-28", "#1 NFL Draft pick — Buffalo Bills"), ("1973-12-16", "First NFL player to rush 2,000 yards (final game of season)"), ("1977-09-24", "Daughter Aaren born / meets Nicole Brown"), ("1978-03-28", "Traded to San Francisco 49ers"), ("1979-03-15", "Divorces Marguerite (approx)"), ("1979-08-26", "Daughter Aaren dies (drowning)"), ("1979-12-16", "Final NFL game — retires"), ("1985-02-02", "Marries Nicole Brown"), ("1985-08-03", "Inducted into Pro Football Hall of Fame"), ("1989-01-01", "First domestic-violence arrest (NYE 1989 incident)"), ("1992-02-25", "Nicole files for divorce"), ("1992-10-15", "Divorce from Nicole finalized"), ("1994-06-12", "Murders of Nicole Brown & Ron Goldman"), ("1994-06-17", "White Bronco chase / arrest"), ("1995-01-24", "Murder trial begins"), ("1995-10-03", "Acquitted of murder charges"), ("1997-02-04", "Civil trial — found liable, $33.5M"), ("2007-09-13", "Las Vegas hotel-room confrontation"), ("2008-10-03", "Convicted of robbery / kidnapping"), ("2008-12-05", "Sentenced 9–33 years, sent to Lovelock"), ("2013-07-25", "First parole hearing — partial parole granted"), ("2017-07-20", "Parole granted (full)"), ("2017-10-01", "Released from prison"), ("2023-05-01", "Announces undergoing chemotherapy"), ("2024-04-10", "Death (prostate cancer, Las Vegas)"), ] print(f"{'Date':12s} {'Event':50s} " f"{'Rahu':>14s} H {'Ketu':>14s} H") print("-"*112) for date_str, ev in EVENTS: dt = datetime.strptime(date_str, "%Y-%m-%d") jd = swe.julday(dt.year, dt.month, dt.day, 12.0) rahu = slong(jd, swe.MEAN_NODE) ketu = (rahu + 180) % 360 rh = whole_sign_house(rahu) kh = whole_sign_house(ketu) rsig = SIGNS[int(rahu//30)] ksig = SIGNS[int(ketu//30)] print(f"{date_str:12s} {ev[:50]:50s} " f"{rahu%30:5.2f}° {rsig:9s} {rh:2d} " f"{ketu%30:5.2f}° {ksig:9s} {kh:2d}") # Also tag each event with its Vimshottari MD/AD print("\n\nNow with Vimshottari MD/AD context:\n") # Re-build the dasha sequence (copied from the main script) NAKSHATRAS_LORD = ['Ketu','Venus','Sun','Moon','Mars','Rahu','Jupiter','Saturn','Mercury', 'Ketu','Venus','Sun','Moon','Mars','Rahu','Jupiter','Saturn','Mercury', 'Ketu','Venus','Sun','Moon','Mars','Rahu','Jupiter','Saturn','Mercury'] DASHA_YEARS = {'Ketu':7,'Venus':20,'Sun':6,'Moon':10,'Mars':7,'Rahu':18,'Jupiter':16,'Saturn':19,'Mercury':17} DASHA_ORDER = ['Ketu','Venus','Sun','Moon','Mars','Rahu','Jupiter','Saturn','Mercury'] NAK_LEN = 360/27 YEAR_DAYS = 365.2425 moon = natal['Moon'] nak_idx = int(moon // NAK_LEN) lord = NAKSHATRAS_LORD[nak_idx] pos_in_nak = (moon - nak_idx*NAK_LEN) / NAK_LEN consumed = pos_in_nak * DASHA_YEARS[lord] md_full_start = BIRTH - timedelta(days=consumed*YEAR_DAYS) seq = [] # list of (start, end, MD, AD) md_lord = lord md_start = md_full_start total = 0 while total < 130: md_y = DASHA_YEARS[md_lord] md_end = md_start + timedelta(days=md_y*YEAR_DAYS) order = DASHA_ORDER[DASHA_ORDER.index(md_lord):] + DASHA_ORDER[:DASHA_ORDER.index(md_lord)] t = md_start for ad_lord in order: ad_y = md_y * DASHA_YEARS[ad_lord] / 120 ad_end = t + timedelta(days=ad_y*YEAR_DAYS) seq.append((t, ad_end, md_lord, ad_lord)) t = ad_end total += md_y md_start = md_end md_lord = DASHA_ORDER[(DASHA_ORDER.index(md_lord)+1) % 9] def find_dasha(dt): dt_aware = dt.replace(tzinfo=timezone.utc) for s, e, md, ad in seq: if s <= dt_aware < e: return md, ad return None, None print(f"{'Date':12s} {'Event':46s} " f"{'Rahu':>16s} {'Ketu':>16s} {'MD':8s} {'AD':8s}") print("-"*120) for date_str, ev in EVENTS: dt = datetime.strptime(date_str, "%Y-%m-%d") jd = swe.julday(dt.year, dt.month, dt.day, 12.0) rahu = slong(jd, swe.MEAN_NODE) ketu = (rahu + 180) % 360 rh = whole_sign_house(rahu) kh = whole_sign_house(ketu) rsig = SIGNS[int(rahu//30)] ksig = SIGNS[int(ketu//30)] md, ad = find_dasha(dt) print(f"{date_str:12s} {ev[:46]:46s} " f"{rahu%30:5.2f}°{rsig:9s}H{rh:<2d} " f"{ketu%30:5.2f}°{ksig:9s}H{kh:<2d} " f"{md or '':8s} {ad or '':8s}")