\set ON_ERROR_STOP on

BEGIN;

CREATE TABLE IF NOT EXISTS weather (
    dateTime TIMESTAMP NOT NULL,
    city VARCHAR(255) NOT NULL,
    tempMax DOUBLE PRECISION,
    tempMin DOUBLE PRECISION,
    tempAvg DOUBLE PRECISION,
    precipitation DOUBLE PRECISION,
    windAvg DOUBLE PRECISION,
    windMax DOUBLE PRECISION,
    visibilityMin DOUBLE PRECISION,
    visibilityAvg DOUBLE PRECISION,
    snowAvg DOUBLE PRECISION,
    atmPressure DOUBLE PRECISION,
    dewPoint DOUBLE PRECISION,
    humidity DOUBLE PRECISION,
    sunDuration DOUBLE PRECISION,
    phenomena TEXT[],
    UNIQUE(city, dateTime)
);

WITH
settings AS (
    SELECT
        date_trunc('hour', CURRENT_TIMESTAMP)::timestamp AS end_at,
        (date_trunc('hour', CURRENT_TIMESTAMP) - INTERVAL '18 months')::timestamp AS start_at
),
cities(city, climate_offset) AS (
    VALUES
        ('Ainaži', -0.8), ('Alūksne', -2.3), ('Bauska', 0.7), ('Dagda', -1.7),
        ('Daugavgrīva', 0.6), ('Daugavpils', -0.9), ('Dobele', 0.8), ('Gulbene', -2.0),
        ('Jelgava', 0.9), ('Kalnciems', 0.7), ('Kolka', 0.3), ('Kuldīga', 0.8),
        ('Lielpēči', 0.2), ('Liepāja', 1.1), ('Madona', -1.8), ('Mērsrags', 0.2),
        ('Pāvilosta', 0.9), ('Piedruja', -1.4), ('Priekuļi', -1.6), ('Rēzekne', -1.2),
        ('Rīga', 1.3), ('Rucava', 1.0), ('Rūjiena', -1.0), ('Saldus', 0.3),
        ('Sigulda', -0.8), ('Sīļi', -1.3), ('Skrīveri', -0.5), ('Skulte', 0.0),
        ('Stende', -0.3), ('Valmiera', -1.2), ('Ventspils', 0.9), ('Vičaki', 0.2), ('Zīlāni', -1.1),
        ('Zosēni', -2.1)
),
hours AS (
    SELECT generate_series(settings.start_at, settings.end_at, INTERVAL '1 hour') AS observed_at
    FROM settings
),
base AS (
    SELECT
        hours.observed_at,
        cities.city,
        cities.climate_offset,
        abs(hashtext(cities.city || hours.observed_at::text)) AS sample_hash,
        7.5
            + 12.5 * sin(2 * pi() * (extract(doy FROM hours.observed_at) - 172) / 365.25)
            + 2.8 * sin(2 * pi() * (extract(hour FROM hours.observed_at) - 9) / 24)
            + cities.climate_offset
            + 1.8 * sin(extract(epoch FROM hours.observed_at) / 173000 + cities.climate_offset) AS temperature
    FROM hours
    CROSS JOIN cities
),
weather_values AS (
    SELECT
        *,
        CASE
            WHEN sample_hash % 100 < 13
                THEN round(((sample_hash % 190) / 10.0 + 0.2)::numeric, 1)::double precision
            ELSE 0.0
        END AS rain,
        round((1.2 + (sample_hash % 65) / 10.0)::numeric, 1)::double precision AS wind,
        round((58 + (sample_hash % 34) + 8 * cos(2 * pi() * extract(doy FROM observed_at) / 365.25))::numeric, 1)::double precision AS relative_humidity
    FROM base
),
final_values AS (
    SELECT
        *,
        GREATEST(0.0, LEAST(100.0, relative_humidity)) AS bounded_humidity,
        CASE
            WHEN temperature < 1.0 AND rain > 0
                THEN round((rain * 0.8 + (sample_hash % 25) / 10.0)::numeric, 1)::double precision
            WHEN temperature < -2.0
                THEN round(((sample_hash % 80) / 10.0)::numeric, 1)::double precision
            ELSE 0.0
        END AS snow,
        CASE
            WHEN extract(hour FROM observed_at) BETWEEN 7 AND 18 AND rain = 0
                THEN round((35 + sample_hash % 26)::numeric, 1)::double precision
            ELSE 0.0
        END AS sunshine_minutes
    FROM weather_values
)
INSERT INTO weather (
    dateTime, city, tempMax, tempMin, tempAvg, precipitation, windAvg, windMax,
    visibilityMin, visibilityAvg, snowAvg, atmPressure, dewPoint, humidity,
    sunDuration, phenomena
)
SELECT
    observed_at,
    city,
    CASE WHEN sample_hash % 997 = 0 THEN NULL ELSE round((temperature + 1.8 + (sample_hash % 12) / 10.0)::numeric, 1)::double precision END,
    CASE WHEN sample_hash % 991 = 0 THEN NULL ELSE round((temperature - 1.6 - (sample_hash % 10) / 10.0)::numeric, 1)::double precision END,
    round(temperature::numeric, 1)::double precision,
    rain,
    wind,
    round((wind + 1.5 + (sample_hash % 70) / 10.0)::numeric, 1)::double precision,
    CASE
        WHEN rain > 12 THEN round((0.8 + sample_hash % 20 / 10.0)::numeric, 1)::double precision
        WHEN bounded_humidity > 88 THEN round((1.5 + sample_hash % 40 / 10.0)::numeric, 1)::double precision
        ELSE round((8 + sample_hash % 80 / 10.0)::numeric, 1)::double precision
    END,
    CASE
        WHEN rain > 12 THEN round((3 + sample_hash % 40 / 10.0)::numeric, 1)::double precision
        ELSE round((12 + sample_hash % 90 / 10.0)::numeric, 1)::double precision
    END,
    snow,
    round((1000 + sample_hash % 310 / 10.0 + 5 * sin(extract(epoch FROM observed_at) / 250000))::numeric, 1)::double precision,
    round((temperature - (100 - bounded_humidity) / 5.0)::numeric, 1)::double precision,
    CASE WHEN sample_hash % 983 = 0 THEN NULL ELSE round(bounded_humidity::numeric, 1)::double precision END,
    sunshine_minutes,
    CASE
        WHEN snow > 0.5 THEN ARRAY['snow']::text[]
        WHEN rain > 12 THEN ARRAY['heavy rain', 'overcast']::text[]
        WHEN rain > 0 THEN ARRAY['rain']::text[]
        WHEN bounded_humidity > 88 THEN ARRAY['fog']::text[]
        WHEN wind > 6.5 THEN ARRAY['windy']::text[]
        WHEN sunshine_minutes > 0 THEN ARRAY['clear']::text[]
        ELSE ARRAY['cloudy']::text[]
    END
FROM final_values
ON CONFLICT (city, dateTime) DO UPDATE SET
    tempMax = EXCLUDED.tempMax,
    tempMin = EXCLUDED.tempMin,
    tempAvg = EXCLUDED.tempAvg,
    precipitation = EXCLUDED.precipitation,
    windAvg = EXCLUDED.windAvg,
    windMax = EXCLUDED.windMax,
    visibilityMin = EXCLUDED.visibilityMin,
    visibilityAvg = EXCLUDED.visibilityAvg,
    snowAvg = EXCLUDED.snowAvg,
    atmPressure = EXCLUDED.atmPressure,
    dewPoint = EXCLUDED.dewPoint,
    humidity = EXCLUDED.humidity,
    sunDuration = EXCLUDED.sunDuration,
    phenomena = EXCLUDED.phenomena;

ANALYZE weather;

COMMIT;

SELECT
    count(*) AS synthetic_rows,
    count(DISTINCT city) AS stations,
    min(dateTime) AS first_observation,
    max(dateTime) AS last_observation
FROM weather;