routine_engine.py

import numpy as np
from typing import List, Dict, Any

# 8D Vector Schema:
# [f_walk, f_transit, f_bike, f_green, f_gym, f_social, f_errand, f_activity]

NEIGHBORHOOD_DATABASE = [
    # --- NEW YORK CITY ---
    {
        "id": "nyc_williamsburg",
        "city": "NYC",
        "name": "Williamsburg",
        "borough_district": "Brooklyn",
        "description": "Trendy epicenter with vibrant third-wave cafes, rooftop bars, boutique gyms, and waterside parks.",
        "vector": [0.95, 0.90, 0.90, 0.70, 0.90, 0.98, 0.92, 0.95],
        "vibe": "Hip & Energetic",
        "activity_level": 5,
        "avg_commute_mins": 20,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Devoción & Partners Coffee", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Equinox & Brooklyn Boulders", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Whole Foods & Trader Joe's North 3rd", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Radegast Hall & Westlight", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Domino Park & McCarren Park", "icon": "fa-tree"}
        ]
    },
    {
        "id": "nyc_west_village",
        "city": "NYC",
        "name": "West Village",
        "borough_district": "Manhattan",
        "description": "Historic cobblestone charm, world-class dining, intimate cafes, and tree-lined walking streets.",
        "vector": [0.98, 0.95, 0.85, 0.75, 0.85, 0.96, 0.95, 0.88],
        "vibe": "Charming & Historic Chic",
        "activity_level": 4,
        "avg_commute_mins": 15,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Stumptown & Bluestone Lane", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Barry's Bootcamp & SoulCycle", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Citarella Gourmet Market", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "The Ear Inn & Employees Only", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Hudson River Park & Washington Square", "icon": "fa-tree"}
        ]
    },
    {
        "id": "nyc_astoria",
        "city": "NYC",
        "name": "Astoria",
        "borough_district": "Queens",
        "description": "Diverse culinary paradise, community beer gardens, parks along the East River, and great subway access.",
        "vector": [0.90, 0.92, 0.75, 0.75, 0.75, 0.88, 0.90, 0.78],
        "vibe": "Vibrant & Neighborhood-Centric",
        "activity_level": 4,
        "avg_commute_mins": 25,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Kinship Coffee & Coffee + Cake", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Club Fitness New York & Astoria Park Track", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Titan Foods & Green Bay Organic", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Bohemian Hall & Sweet Afton", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Astoria Park & Charybdis Playground", "icon": "fa-tree"}
        ]
    },

    # --- WASHINGTON, DC ---
    {
        "id": "dc_dupont_circle",
        "city": "DC",
        "name": "Dupont Circle",
        "borough_district": "NW",
        "description": "Historic rowhouses, embassies, indie bookstores, bustling nightlife along Connecticut Ave, and Red Line transit.",
        "vector": [0.96, 0.92, 0.88, 0.78, 0.85, 0.94, 0.92, 0.85],
        "vibe": "Cosmopolitan & Walkable",
        "activity_level": 4,
        "avg_commute_mins": 18,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Kramerbooks & Emissary Cafe", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "VIDA Fitness & Solidcore", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Trader Joe's & Dupont Farmers Market", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "The Board Room & Madhatter", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Dupont Circle Park & Rock Creek Trails", "icon": "fa-tree"}
        ]
    },
    {
        "id": "dc_adams_morgan",
        "city": "DC",
        "name": "Adams Morgan",
        "borough_district": "NW",
        "description": "Eclectic nightlife hub on 18th St, live music venues, authentic international cuisine, and bohemian character.",
        "vector": [0.92, 0.82, 0.85, 0.80, 0.80, 0.96, 0.85, 0.92],
        "vibe": "Eclectic & Nightlife Hub",
        "activity_level": 5,
        "avg_commute_mins": 25,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Tryst & SoHo Tea & Coffee", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Mint DC & Kalorama Park Yoga", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Streets Market & Harris Teeter", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Madam's Organ & Songbyrd", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Kalorama Park & Rock Creek Park", "icon": "fa-tree"}
        ]
    },
    {
        "id": "dc_navy_yard",
        "city": "DC",
        "name": "Navy Yard / Capitol Riverfront",
        "borough_district": "SE",
        "description": "Modern riverfront high-rises, Nationals Park, boardwalk breweries, waterfront running trails, and trendy dining.",
        "vector": [0.90, 0.88, 0.88, 0.85, 0.95, 0.90, 0.88, 0.88],
        "vibe": "Modern & Riverfront Active",
        "activity_level": 4,
        "avg_commute_mins": 15,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Slipstream & Yellow the Cafe", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "OneLife Fitness & F45 Training", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Harris Teeter & Whole Foods Navy Yard", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Bluejacket Brewery & Dacha Beer Garden", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Yards Park & Anacostia Riverwalk Trail", "icon": "fa-tree"}
        ]
    },

    # --- BALTIMORE, MD ---
    {
        "id": "baltimore_fells_point",
        "city": "Baltimore",
        "name": "Fells Point",
        "borough_district": "Historic Waterfront",
        "description": "Centuries-old cobblestone streets, waterfront taverns, seafood markets, and scenic promenade strolls.",
        "vector": [0.94, 0.65, 0.80, 0.70, 0.75, 0.95, 0.85, 0.85],
        "vibe": "Historic Maritime & Social",
        "activity_level": 4,
        "avg_commute_mins": 18,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Daily Grind & Pitango Bakery Cafe", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Merritt Clubs Fort Ave & Waterfront Yoga", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Broadway Market & Whole Foods Harbor East", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "The Horse You Came In On & Max's Taphouse", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Thames St Waterfront Promenade", "icon": "fa-tree"}
        ]
    },
    {
        "id": "baltimore_charles_village",
        "city": "Baltimore",
        "name": "Charles Village / Hampden",
        "borough_district": "North Baltimore",
        "description": "Painted ladies architecture, Johns Hopkins campus green spaces, indie craft shops, and quirky hipster culture.",
        "vector": [0.90, 0.70, 0.85, 0.85, 0.75, 0.88, 0.80, 0.75],
        "vibe": "Academic & Artistic",
        "activity_level": 3,
        "avg_commute_mins": 20,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Bird in Hand & Artifact Coffee", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Ralph S. O'Connor Center & Movement Gym", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Eddie's of Charles Village & MOM's Organic", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "The Dizz & Bluebird Cocktail Room", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Wyman Park Dell & Stony Run Trail", "icon": "fa-tree"}
        ]
    },

    # --- PHILADELPHIA, PA ---
    {
        "id": "philly_rittenhouse",
        "city": "Philadelphia",
        "name": "Rittenhouse Square",
        "borough_district": "Center City",
        "description": "Prestigious park square, world-class outdoor dining, designer boutiques, and exceptionally high walkability.",
        "vector": [0.98, 0.92, 0.88, 0.85, 0.90, 0.95, 0.95, 0.88],
        "vibe": "Refined & Cosmopolitan",
        "activity_level": 4,
        "avg_commute_mins": 12,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "La Colombe Torrefaction & Elixr Coffee", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "City Fitness Rittenhouse & Rumble Boxing", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Trader Joe's & Di Bruno Bros", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Parc Brasserie & The Franklin Mortgage & Investment Co.", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Rittenhouse Square Park & Schuylkill River Trail", "icon": "fa-tree"}
        ]
    },
    {
        "id": "philly_fishtown",
        "city": "Philadelphia",
        "name": "Fishtown",
        "borough_district": "Riverwards",
        "description": "Philly's creative core with renowned craft breweries, indie music venues (The Fillmore), and artisan bakeries.",
        "vector": [0.92, 0.88, 0.90, 0.65, 0.82, 0.98, 0.85, 0.92],
        "vibe": "Indie Music & Culinary Hub",
        "activity_level": 5,
        "avg_commute_mins": 22,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "ReAnimator Coffee & La Colombe Flagship", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Bespoke Athletic Club & Tula Yoga", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Riverwards Produce & Giant Heirloom Market", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Johnny Brenda's & Frankford Hall", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Penn Treaty Park & Palmer Park", "icon": "fa-tree"}
        ]
    },

    # --- BOSTON, MA ---
    {
        "id": "boston_back_bay",
        "city": "Boston",
        "name": "Back Bay",
        "borough_district": "Central Boston",
        "description": "Victorian brownstones, Newbury St shopping, the Esplanade on the Charles River, and central subway access.",
        "vector": [0.98, 0.95, 0.88, 0.85, 0.90, 0.92, 0.96, 0.85],
        "vibe": "Historic Elegance & Active",
        "activity_level": 4,
        "avg_commute_mins": 14,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Thinking Cup & Pavement Coffeehouse", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Equinox Dartmouth & Boston Sports Club", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Trader Joe's Boylston & Star Market", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "The Salty Pig & Bukowski Tavern", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Charles River Esplanade & Boston Public Garden", "icon": "fa-tree"}
        ]
    },
    {
        "id": "boston_cambridge_kendall",
        "city": "Boston",
        "name": "Cambridge / Kendall Square & Central",
        "borough_district": "Cambridge",
        "description": "Global tech & biotech capital with MIT campus, vibrant beer gardens, rowing clubs, and Red Line rapid transit.",
        "vector": [0.95, 0.94, 0.96, 0.80, 0.88, 0.89, 0.90, 0.82],
        "vibe": "Innovative & Active Cyclist",
        "activity_level": 4,
        "avg_commute_mins": 16,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Barismo & 1369 Coffee House", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Central Rock Gym (Climbing) & MIT Z-Center", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "H Mart Central & Whole Foods River St", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "The Muddy Charles & Cambridge Brewing Co.", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Charles River Bike Path & Killian Court", "icon": "fa-tree"}
        ]
    },

    # --- ATLANTA, GA ---
    {
        "id": "atlanta_midtown",
        "city": "Atlanta",
        "name": "Midtown Atlanta",
        "borough_district": "Midtown",
        "description": "High-density cultural heart, direct Piedmont Park access, BeltLine cycling, and MARTA rail connectivity.",
        "vector": [0.88, 0.78, 0.90, 0.92, 0.92, 0.92, 0.88, 0.88],
        "vibe": "Parkside Cultural Metropolis",
        "activity_level": 4,
        "avg_commute_mins": 18,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Dancing Goats Coffee & Octane", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Midtown Athletic Club & Exhale Atlanta", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Whole Foods 14th St (Multi-level flagship)", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "The Vortex Bar & Grill & Cypress Street Pint & Plate", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Piedmont Park & Atlanta BeltLine Eastside Trail", "icon": "fa-tree"}
        ]
    },
    {
        "id": "atlanta_inman_park",
        "city": "Atlanta",
        "name": "Inman Park / Old Fourth Ward",
        "borough_district": "Eastside",
        "description": "Historic Victorian enclave centered on the BeltLine, Krog Street Market, and award-winning patio dining.",
        "vector": [0.90, 0.65, 0.96, 0.88, 0.85, 0.96, 0.86, 0.90],
        "vibe": "BeltLine Epicenter & Foodie",
        "activity_level": 5,
        "avg_commute_mins": 22,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Chrome Yellow Trading Co. & Spiller Park", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "The Daily Pilates & BeltLine Running Club", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Krog Street Market & Savi Provisions", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Ladybird Grove & Mess Hall & Barcelona Wine Bar", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Historic Fourth Ward Park & Springvale Park", "icon": "fa-tree"}
        ]
    },

    # --- ARLINGTON & BETHESDA (DC METRO) ---
    {
        "id": "arlington_clarendon",
        "city": "Arlington",
        "name": "Clarendon / Courthouse",
        "borough_district": "Arlington Corridor",
        "description": "Hyper-walkable Metro corridor packed with fitness studios, dog parks, beer gardens, and young professionals.",
        "vector": [0.94, 0.92, 0.88, 0.78, 0.92, 0.90, 0.95, 0.85],
        "vibe": "Active Urban-Suburban Fusion",
        "activity_level": 4,
        "avg_commute_mins": 15,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Northside Social & Compass Coffee", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "OrangeTheory & Gold's Gym Clarendon", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Trader Joe's & Whole Foods Clarendon", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Whitlow's on Wilson & Spider Kelly's", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Rocky Run Park & Custis Trail", "icon": "fa-tree"}
        ]
    },
    {
        "id": "bethesda_downtown",
        "city": "Bethesda",
        "name": "Downtown Bethesda / Bethesda Row",
        "borough_district": "Montgomery County",
        "description": "High-end shopping, outdoor dining promenades, Capital Crescent Trail cycling, and Red Line transit.",
        "vector": [0.92, 0.88, 0.85, 0.82, 0.88, 0.86, 0.94, 0.78],
        "vibe": "Sophisticated & Trailside",
        "activity_level": 3,
        "avg_commute_mins": 22,
        "matched_stores": [
            {"category": "Coffee / Third Place", "name": "Quartermaine Coffee Roasters & Ceremony Coffee", "icon": "fa-mug-hot"},
            {"category": "Fitness & Wellness", "name": "Equinox Bethesda & Pure Barre", "icon": "fa-dumbbell"},
            {"category": "Groceries / Organic", "name": "Giant & Bethesda Central Farm Market", "icon": "fa-basket-shopping"},
            {"category": "Nightlife & Pubs", "name": "Mon Ami Gabi & Tommy Joe's", "icon": "fa-martini-glass"},
            {"category": "Parks & Outdoors", "name": "Capital Crescent Trail & Elm Street Park", "icon": "fa-tree"}
        ]
    }
]

def calculate_user_vector(answers: Dict[str, Any]) -> np.ndarray:
    """
    Constructs an 8-dimensional user lifestyle vector U from questionnaire answers.
    Dimensions: [f_walk, f_transit, f_bike, f_green, f_gym, f_social, f_errand, f_activity]
    """
    # 1. Transit Mode
    transit = answers.get("transit_mode", "transit")
    f_walk, f_transit, f_bike = 0.7, 0.7, 0.7
    if transit == "walk_bike":
        f_walk, f_bike, f_transit = 0.98, 0.95, 0.70
    elif transit == "transit":
        f_walk, f_transit, f_bike = 0.90, 0.98, 0.75
    elif transit == "car":
        f_walk, f_transit, f_bike = 0.40, 0.30, 0.30

    # 2. Exercise & Outdoors (multi-select)
    exercise = answers.get("exercise_habits", [])
    f_green = 0.4
    f_gym = 0.4
    if "gym" in exercise or "crossfit" in exercise:
        f_gym += 0.5
    if "trails" in exercise or "running" in exercise or "dog_park" in exercise or "strolls" in exercise:
        f_green += 0.5
        f_bike = min(1.0, f_bike + 0.15)
        f_walk = min(1.0, f_walk + 0.15)

    # 3. Social & Evening Habits (multi-select)
    social = answers.get("social_habits", [])
    f_social = 0.3
    f_errand = 0.6
    if "pubs" in social or "bars" in social:
        f_social += 0.3
    if "dining" in social or "foodie" in social:
        f_social += 0.25
        f_errand += 0.2
    if "coffee" in social or "third_places" in social:
        f_social += 0.2
        f_errand += 0.2
    if "arts" in social or "theatres" in social:
        f_social += 0.15

    # 4. Energy & Noise Level (1 to 5)
    noise_level = float(answers.get("energy_level", 4))
    f_activity = (noise_level / 5.0)

    # 5. Work Routine
    work_routine = answers.get("work_routine", "hybrid")
    if work_routine == "wfh":
        f_errand = min(1.0, f_errand + 0.15)  # More local third places & cafes needed
    elif work_routine == "office":
        f_transit = min(1.0, f_transit + 0.15)

    u_vec = np.array([f_walk, f_transit, f_bike, f_green, f_gym, f_social, f_errand, f_activity], dtype=float)
    # Clip between 0.1 and 1.0
    return np.clip(u_vec, 0.1, 1.0)


def match_routine(answers: Dict[str, Any]) -> List[Dict[str, Any]]:
    """
    Executes Cosine Similarity + Commute Decay + Noise Tolerance formula from MVP Spec:
    S_raw = (U · N) / (||U||2 ||N||2)
    gamma_commute = 1.0 if T <= Tmax else exp(-1.5 * (T - Tmax) / Tmax)
    delta_noise = 1.0 - (|Unoise - Nactivity| / 4) * 0.25
    Score_final = S_raw * gamma * delta_noise * 100
    """
    target_city = answers.get("target_city", "").strip()
    source_city = answers.get("source_city", "").strip()
    max_commute = float(answers.get("max_commute", 30))
    user_noise = float(answers.get("energy_level", 4))

    u_vec = calculate_user_vector(answers)
    u_norm = np.linalg.norm(u_vec)

    # Filter neighborhoods by target city (or all if target not specified)
    candidates = NEIGHBORHOOD_DATABASE
    if target_city:
        candidates = [n for n in NEIGHBORHOOD_DATABASE if n["city"].lower() == target_city.lower()]
        if not candidates:
            # Fallback if no exact match
            candidates = NEIGHBORHOOD_DATABASE

    results = []
    for n in candidates:
        n_vec = np.array(n["vector"], dtype=float)
        n_norm = np.linalg.norm(n_vec)
        
        # 1. Cosine similarity
        s_raw = np.dot(u_vec, n_vec) / (u_norm * n_norm) if (u_norm > 0 and n_norm > 0) else 0.0

        # 2. Commute Penalty Factor (gamma)
        t_commute = n.get("avg_commute_mins", 20)
        if t_commute <= max_commute:
            gamma = 1.0
        else:
            gamma = np.exp(-1.5 * (t_commute - max_commute) / max_commute)

        # 3. Noise Divergence Penalty (delta)
        n_activity = float(n.get("activity_level", 4))
        delta_noise = 1.0 - (abs(user_noise - n_activity) / 4.0) * 0.25

        # 4. Final Match Score (0 to 100)
        final_score = float(s_raw * gamma * delta_noise * 100.0)
        final_score = round(min(99.4, max(45.0, final_score)), 1)

        # Dimension breakdown for radar chart
        breakdown = {
            "Walkability": int(n_vec[0] * 100),
            "Public Transit": int(n_vec[1] * 100),
            "Cycling & Micro-mobility": int(n_vec[2] * 100),
            "Parks & Green Spaces": int(n_vec[3] * 100),
            "Fitness & Gyms": int(n_vec[4] * 100),
            "Dining & Nightlife": int(n_vec[5] * 100),
            "Third Places & Cafes": int(n_vec[6] * 100)
        }

        results.append({
            **n,
            "match_score": final_score,
            "cosine_similarity": round(float(s_raw), 3),
            "commute_mins": t_commute,
            "dimension_breakdown": breakdown
        })

    # Sort descending by match score
    results.sort(key=lambda x: x["match_score"], reverse=True)
    return results