--DO NOT MODIFY THIS FILE, IT IS GENERATED AUTOMATICALLY FROM SOURCES
-- Complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "CREATE EXTENSION observatory" to load this file. \quit
-- Version number of the extension release
CREATE OR REPLACE FUNCTION cdb_observatory_version()
RETURNS text AS $$
  SELECT '1.3.3'::text;
$$ language 'sql' STABLE STRICT;

-- Internal identifier of the installed extension instence
-- e.g. 'dev' for current development version
CREATE OR REPLACE FUNCTION _cdb_observatory_internal_version()
RETURNS text AS $$
  SELECT installed_version FROM pg_available_extensions where name='observatory' and pg_available_extensions IS NOT NULL;
$$ language 'sql' STABLE STRICT;

-- Returns the table name with geoms for the given geometry_id
-- TODO probably needs to take in the column_id array to get the relevant
-- table where there is multiple sources for a column from multiple
-- geometries.
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GeomTable(
  geom geometry(Geometry, 4326),
  geometry_id text,
  time_span text DEFAULT NULL
)
  RETURNS TEXT
AS $$
DECLARE
  result text;
BEGIN
  EXECUTE '
    SELECT tablename FROM observatory.OBS_table
    WHERE id IN (
      SELECT table_id
      FROM observatory.OBS_table tab,
           observatory.OBS_column_table coltable,
           observatory.OBS_column col
      WHERE type ILIKE ''geometry''
        AND coltable.column_id = col.id
        AND coltable.table_id = tab.id
        AND col.id = $1
        AND CASE WHEN $3::TEXT IS NOT NULL THEN timespan ILIKE $3::TEXT ELSE TRUE END
      ORDER BY timespan DESC LIMIT 1
    )
    '
  USING geometry_id, geom, time_span
  INTO result;

  return result;

END;
$$ LANGUAGE plpgsql;



-- A function that gets the column data for multiple columns
-- Old: OBS_GetColumnData
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetColumnData(
  geometry_id text,
  column_ids text[],
  timespan text
)
RETURNS SETOF JSON
AS $$
BEGIN

  -- figure out highest-weight geometry_id/timespan pair for the first data column
  -- TODO this should be done for each data column separately
  IF geometry_id IS NULL OR timespan IS NULL THEN
    EXECUTE '
      SELECT data_t.timespan timespan, geom_c.id boundary_id
      FROM observatory.obs_table data_t,
           observatory.obs_column_table data_ct,
           observatory.obs_column data_c,
           observatory.obs_column_table geoid_ct,
           observatory.obs_column_to_column c2c,
           observatory.obs_column geom_c
      WHERE data_c.id = $2
           AND data_ct.column_id = data_c.id
           AND data_ct.table_id = data_t.id
           AND geoid_ct.table_id = data_t.id
           AND geoid_ct.column_id = c2c.source_id
           AND c2c.reltype = ''geom_ref''
           AND geom_c.id = c2c.target_id
           AND CASE WHEN $3 IS NULL THEN True ELSE $3 = timespan END
           AND CASE WHEN $1 IS NULL THEN True ELSE $1 = geom_c.id END
      ORDER BY geom_c.weight DESC,
               data_t.timespan DESC
      LIMIT 1
    ' INTO timespan, geometry_id
    USING geometry_id, (column_ids)[1], timespan;
  END IF;

  RETURN QUERY
  EXECUTE '
  WITH geomref AS (
    SELECT ct.table_id id
    FROM observatory.OBS_column_to_column c2c,
         observatory.OBS_column_table ct
    WHERE c2c.reltype = ''geom_ref''
      AND c2c.target_id = $1
      AND c2c.source_id = ct.column_id
    ),
  column_ids as (
    select row_number() over () as no, a.column_id as column_id from (select unnest($2) as column_id) a
  )
 SELECT row_to_json(a) from (
   select  colname,
            tablename,
            aggregate,
            name,
            type,
            c.description,
            $1 AS boundary_id
           FROM column_ids, observatory.OBS_column c, observatory.OBS_column_table ct, observatory.OBS_table t
           WHERE column_ids.column_id  = c.id
             AND c.id = ct.column_id
             AND t.id = ct.table_id
             AND t.timespan = $3
             AND t.id in (SELECT id FROM geomref)
          order by column_ids.no
    ) a
 '
 USING geometry_id, column_ids, timespan
 RETURN;

END;
$$ LANGUAGE plpgsql;

--Test point cause Stuart always seems to make random points in the water
CREATE OR REPLACE FUNCTION cdb_observatory._TestPoint()
  RETURNS geometry(Point, 4326)
AS $$
BEGIN
  -- new york city
  RETURN ST_SetSRID(ST_Point( -73.936669, 40.704512), 4326);
END;
$$ LANGUAGE plpgsql;

--Test polygon cause Stuart always seems to make random points in the water
-- TODO: remove as it's not used anywhere?
CREATE OR REPLACE FUNCTION cdb_observatory._TestArea()
  RETURNS geometry(Geometry, 4326)
AS $$
BEGIN
  -- Buffer NYC point by 500 meters
  RETURN ST_Buffer(cdb_observatory._TestPoint()::geography, 500)::geometry;

END;
$$ LANGUAGE plpgsql;

--Problematic test area that tends to cause errors
CREATE OR REPLACE FUNCTION cdb_observatory._ProblemTestArea()
  RETURNS geometry(Geometry, 4326)
AS $$
BEGIN
  RETURN ST_Translate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geometry(geometry, 4326), -73.9366690032303 - -104.729102126902, 40.7045120351809 - 39.620441302097);
END;
$$ LANGUAGE plpgsql;

--Used to expand a column based response to a table based one. Give it the desired
--columns and it will return a partial query for rolling them out to a table.
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_BuildSnapshotQuery(names text[])
RETURNS TEXT
AS $$
DECLARE
  q text;
  i numeric;
BEGIN

  q := 'SELECT ';

  FOR i IN 1..array_upper(names,1)
  LOOP
    q = q || format(' vals[%s] As %I', i, names[i]);
    IF i < array_upper(names, 1) THEN
      q= q || ',';
    END IF;
  END LOOP;
  RETURN q;

END;
$$ LANGUAGE plpgsql;

-- Function that replaces all non digits or letters with _ trims and lowercases the
-- passed measure name

CREATE OR REPLACE FUNCTION cdb_observatory._OBS_StandardizeMeasureName(measure_name text)
RETURNS text
AS $$
DECLARE
  result text;
BEGIN
  -- Turn non letter or digits to _
  result = regexp_replace(measure_name, '[^\dA-Za-z]+','_', 'g');
  -- Remove duplicate _'s
  result = regexp_replace(result,'_{2,}','_', 'g');
  -- Trim _'s from beginning and end
  result = trim(both  '_' from result);
  result = lower(result);
  RETURN result;
END;
$$ LANGUAGE plpgsql;

-- Function that returns the currently deployed obs_dump_version from the
-- remote table of the same name.

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_DumpVersion(
)
  RETURNS TEXT
AS $$
DECLARE
  result text;
BEGIN
  EXECUTE '
    SELECT MAX(dump_id) FROM observatory.obs_dump_version
  ' INTO result;
  RETURN result;
END;
$$ LANGUAGE plpgsql;


-- Function we can call to raise an exception in the midst of a SQL statement
CREATE OR REPLACE FUNCTION cdb_observatory._OBS_RaiseNotice(
    message TEXT
) RETURNS TEXT
AS $$
BEGIN
  RAISE NOTICE '%', message;
  RETURN NULL;
END;
$$ LANGUAGE plpgsql;


-- Create a function that always returns the first non-NULL item
CREATE OR REPLACE FUNCTION cdb_observatory.first_agg ( anyelement, anyelement )
RETURNS anyelement LANGUAGE SQL IMMUTABLE STRICT AS $$
        SELECT $1;
$$;

DROP AGGREGATE IF EXISTS cdb_observatory.FIRST (anyelement);

-- And then wrap an aggregate around it
CREATE AGGREGATE cdb_observatory.FIRST (
        sfunc    = cdb_observatory.first_agg,
        basetype = anyelement,
        stype    = anyelement
);

CREATE OR REPLACE FUNCTION cdb_observatory.isnumeric (
  typename varchar
)
RETURNS BOOLEAN LANGUAGE SQL IMMUTABLE STRICT AS $$
  SELECT LOWER(typename) IN (
    'smallint',
    'integer',
    'bigint',
    'decimal',
    'numeric',
    'real',
    'double precision'
  )
$$;

-- Attempt to perform intersection, if there's an exception then buffer
-- https://gis.stackexchange.com/questions/50399/how-best-to-fix-a-non-noded-intersection-problem-in-postgis
CREATE OR REPLACE FUNCTION cdb_observatory.safe_intersection(
  geom_a Geometry(Geometry, 4326),
  geom_b Geometry(Geometry, 4326)
)
RETURNS Geometry(Geometry, 4326) AS
$$
BEGIN
    RETURN ST_MakeValid(ST_Intersection(geom_a, geom_b));
    EXCEPTION
        WHEN OTHERS THEN
            BEGIN
                RETURN ST_MakeValid(ST_Intersection(ST_Buffer(geom_a, 0.0000001), ST_Buffer(geom_b, 0.0000001)));
                EXCEPTION
                    WHEN OTHERS THEN
                        RETURN NULL;
    END;
END
$$
LANGUAGE 'plpgsql' STABLE STRICT;
--Functions for augmenting specific tables
--------------------------------------------------------------------------------

-- Creates a table of demographic snapshot

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetDemographicSnapshot(geom geometry(Geometry, 4326),
  timespan text DEFAULT NULL,
  boundary_id text DEFAULT NULL
) RETURNS SETOF JSON
AS $$
DECLARE
  meta JSON;
BEGIN
  boundary_id = COALESCE(boundary_id, 'us.census.tiger.census_tract');

  EXECUTE $query$ SELECT cdb_observatory.OBS_GetMeta($1,
         ('[ ' ||
'{"numer_id": "us.census.acs.B01003001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B01001002", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B01001026", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B01002001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002003", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002004", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002006", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002012", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002005", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002008", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002009", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B03002002", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B11001001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B15003001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B15003017", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B15003019", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B15003020", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B15003021", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B15003022", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B15003023", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19013001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19083001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19301001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25001001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25002003", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25004002", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25004004", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25058001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25071001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25075001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25075025", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B25081002", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134002", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134003", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134004", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134005", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134006", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134007", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134008", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134009", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08134010", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B08135001", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001002", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001003", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001004", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001005", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001006", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001007", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001008", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001009", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001010", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001011", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001012", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001013", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001014", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001015", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001016", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '},' ||
'{"numer_id": "us.census.acs.B19001017", "numer_timespan": ' || $2 || ', "geom_id": ' || $3 || '}' ||
      ']')::JSON)
  $query$
  INTO meta
  USING geom,
        COALESCE('"' || timespan || '"', 'null'),
        COALESCE('"' || boundary_id || '"', 'null');

  RETURN QUERY EXECUTE $query$
    WITH vals AS (SELECT JSON_Array_Elements(data)->'value' val,
                         JSON_Array_Elements($2) meta
                  FROM cdb_observatory.OBS_GetData( ARRAY[($1, 1)::geomval], $2))
    SELECT JSON_Build_Object(
        'value', val,
        'id', meta->'numer_id',
        'name', meta->'numer_name',
        'type', meta->'numer_type',
        'description', meta->'numer_description'
    ) FROM vals
  $query$
  USING geom, meta
  RETURN;
END;
$$ LANGUAGE plpgsql STABLE;


CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetMeta(
  geom geometry(Geometry, 4326),
  params JSON,
  max_timespan_rank INTEGER DEFAULT NULL, -- cutoff for timespan ranks when there's ambiguity
  max_score_rank INTEGER DEFAULT NULL, -- cutoff for geom ranks when there's ambiguity
  target_geoms INTEGER DEFAULT NULL
)
RETURNS JSON
AS $$
DECLARE
  numer_filters TEXT[];
  geom_filters TEXT[];
  meta_filter_clause TEXT;
  scores_clause TEXT;
  result JSON;
BEGIN
  IF max_timespan_rank IS NULL THEN
    max_timespan_rank := 1;
  END IF;
  IF max_score_rank IS NULL THEN
    max_score_rank := 1;
  END IF;

  numer_filters := (SELECT Array_Agg(val) FILTER (WHERE val IS NOT NULL) FROM (SELECT (JSON_Array_Elements(params))->>'numer_id' val) foo);
  geom_filters := (SELECT Array_Agg(val) FILTER (WHERE val IS NOT NULL) FROM (SELECT (JSON_Array_Elements(params))->>'geom_id' val) bar);
  meta_filter_clause := '(m.numer_id = ANY ($6) OR m.geom_id = ANY ($7))';

  scores_clause := 'SELECT *
                    FROM cdb_observatory._OBS_GetGeometryScores($1,
                    (SELECT Array_Agg(geom_id) FROM meta), $2) scores ';

  IF JSON_Array_Length(params) = 1 THEN
    IF numer_filters IS NULL AND geom_filters IS NOT NULL THEN
      meta_filter_clause := 'm.geom_id = ($7)[1]';
    ELSIF geom_filters IS NULL AND numer_filters IS NOT NULL THEN
      meta_filter_clause := 'm.numer_id = ($6)[1]';
    ELSIF numer_filters IS NOT NULL AND geom_filters IS NOT NULL THEN
      meta_filter_clause := 'm.numer_id = ($6)[1] AND m.geom_id = ($7)[1]';
    ELSE
      RAISE EXCEPTION 'Must pass either numer_id or geom_id to every key in GetMeta';
    END IF;

    IF geom_filters IS NOT NULL AND numer_filters IS NOT NULL THEN
      scores_clause := 'SELECT 1 score, null, geom_tid table_id, geom_id column_id,
                               null, null, null, null, null, null
                        FROM meta ';
    END IF;
  END IF;

  EXECUTE format($string$
    WITH _filters AS (SELECT
        generate_series(1, array_length($3, 1)) id,
        (unnest($3))->>'numer_id' numer_id,
        (unnest($3))->>'denom_id' denom_id,
        (unnest($3))->>'geom_id' geom_id,
        (unnest($3))->>'numer_timespan' numer_timespan,
        (unnest($3))->>'geom_timespan' geom_timespan,
        (unnest($3))->>'normalization' normalization
    ), meta AS (SELECT
        id,
        f.numer_id,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE numer_aggregate END numer_aggregate,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE numer_colname END numer_colname,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE numer_geomref_colname END numer_geomref_colname,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE numer_tablename END numer_tablename,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE numer_type END numer_type,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE numer_name END numer_name,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE m.numer_timespan END numer_timespan,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE m.denom_id END denom_id,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE denom_aggregate END denom_aggregate,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE denom_colname END denom_colname,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE denom_geomref_colname END denom_geomref_colname,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE denom_tablename END denom_tablename,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE denom_name END denom_name,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE denom_type END denom_type,
        CASE WHEN f.numer_id IS NULL THEN NULL ELSE denom_reltype END denom_reltype,
        m.geom_id,
        m.geom_timespan,
        geom_colname,
        geom_tid,
        geom_geomref_colname,
        geom_tablename,
        geom_name,
        geom_type,
        normalization
      FROM observatory.obs_meta m JOIN _filters f
      ON CASE WHEN f.numer_id IS NULL THEN m.geom_id ELSE m.numer_id END =
         CASE WHEN f.numer_id IS NULL THEN f.geom_id ELSE f.numer_id END
      WHERE
        %s
        AND (m.numer_id = f.numer_id OR COALESCE(f.numer_id, '') = '')
        AND (m.denom_id = f.denom_id OR COALESCE(f.denom_id, '') = '')
        AND (m.geom_id = f.geom_id OR COALESCE(f.geom_id, '') = '')
        AND (m.geom_timespan = f.geom_timespan OR COALESCE(f.geom_timespan, '') = '')
        AND (m.numer_timespan = f.numer_timespan OR COALESCE(f.numer_timespan, '') = '')
    ), scores AS (
        %s
    ), groups AS (SELECT
        id,
        scores.score,
        numer_timespan,
        dense_rank() OVER (PARTITION BY id ORDER BY numer_timespan DESC) timespan_rank,
        dense_rank() OVER (PARTITION BY id ORDER BY score DESC) score_rank,
        json_build_object(
          'id', id,
          'numer_id', numer_id,
          'timespan_rank', dense_rank() OVER (PARTITION BY id ORDER BY numer_timespan DESC),
          'score_rank', dense_rank() OVER (PARTITION BY id ORDER BY score DESC),
          'score', scores.score,
          'numer_aggregate', cdb_observatory.FIRST(meta.numer_aggregate),
          'numer_colname', cdb_observatory.FIRST(meta.numer_colname),
          'numer_geomref_colname', cdb_observatory.FIRST(meta.numer_geomref_colname),
          'numer_tablename', cdb_observatory.FIRST(meta.numer_tablename),
          'numer_type', cdb_observatory.FIRST(meta.numer_type),
          --'numer_description', cdb_observatory.FIRST(meta.numer_description),
          --'numer_t_description', cdb_observatory.FIRST(meta.numer_t_description),
          'denom_aggregate', cdb_observatory.FIRST(meta.denom_aggregate),
          'denom_colname', cdb_observatory.FIRST(denom_colname),
          'denom_geomref_colname', cdb_observatory.FIRST(denom_geomref_colname),
          'denom_tablename', cdb_observatory.FIRST(denom_tablename),
          'denom_type', cdb_observatory.FIRST(meta.denom_type),
          'denom_reltype', cdb_observatory.FIRST(meta.denom_reltype),
          --'denom_description', cdb_observatory.FIRST(meta.denom_description),
          --'denom_t_description', cdb_observatory.FIRST(meta.denom_t_description),
          'geom_colname', cdb_observatory.FIRST(geom_colname),
          'geom_geomref_colname', cdb_observatory.FIRST(geom_geomref_colname),
          'geom_tablename', cdb_observatory.FIRST(geom_tablename),
          'geom_type', cdb_observatory.FIRST(meta.geom_type),
          'geom_timespan', cdb_observatory.FIRST(meta.geom_timespan),
          --'geom_description', cdb_observatory.FIRST(meta.geom_description),
          --'geom_t_description', cdb_observatory.FIRST(meta.geom_t_description),
          'numer_timespan', cdb_observatory.FIRST(numer_timespan),
          'numer_name', cdb_observatory.FIRST(numer_name),
          'denom_name', cdb_observatory.FIRST(denom_name),
          'geom_name', cdb_observatory.FIRST(geom_name),
          'normalization', cdb_observatory.FIRST(normalization),
          'denom_id', denom_id,
          'geom_id', meta.geom_id
        ) metadata
      FROM meta, scores
      WHERE meta.geom_id = scores.column_id
        AND meta.geom_tid = scores.table_id
      GROUP BY id, score, numer_id, denom_id, geom_id, numer_timespan
    ) SELECT JSON_AGG(metadata ORDER BY id)
      FROM groups
      WHERE timespan_rank <= $4
        AND score_rank <= $5
  $string$, meta_filter_clause, scores_clause)
  INTO result
  USING
    CASE WHEN ST_GeometryType(geom) = 'ST_Point' THEN
              ST_Buffer(geom::geography, 200)::geometry(geometry, 4326)
         ELSE geom
    END,
    target_geoms,
    (SELECT ARRAY(SELECT json_array_elements_text(params))::json[]),
    max_timespan_rank,
    max_score_rank, numer_filters, geom_filters
    ;
  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;


CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetMeasure(
  geom geometry(Geometry, 4326),
  measure_id TEXT,
  normalize TEXT DEFAULT NULL,
  boundary_id TEXT DEFAULT NULL,
  time_span TEXT DEFAULT NULL,
  simplification NUMERIC DEFAULT 0.00001
)
RETURNS NUMERIC
AS $$
DECLARE
  geom_type TEXT;
  params JSON;
  map_type TEXT;
  result Numeric;
  numer_aggregate TEXT;
BEGIN
  IF geom IS NULL THEN
    RETURN NULL;
  END IF;

  IF simplification IS NOT NULL THEN
    geom := ST_Simplify(geom, simplification);
  END IF;

  IF ST_GeometryType(geom) = 'ST_Point' THEN
    geom_type := 'point';
  ELSIF ST_GeometryType(geom) IN ('ST_Polygon', 'ST_MultiPolygon') THEN
    geom_type := 'polygon';
    geom := ST_CollectionExtract(ST_MakeValid(geom), 3);
  ELSE
    RAISE EXCEPTION 'Invalid geometry type (%), can only handle ''ST_Point'', ''ST_Polygon'', and ''ST_MultiPolygon''',
                    ST_GeometryType(geom);
  END IF;

  params := (SELECT cdb_observatory.OBS_GetMeta(
    geom, JSON_Build_Array(JSON_Build_Object('numer_id', measure_id,
                                             'geom_id', boundary_id,
                                             'numer_timespan', time_span
                                            )), 1, 1, 500));
  numer_aggregate := params->0->>'numer_aggregate';

  IF normalize ILIKE 'area%' AND numer_aggregate ILIKE 'sum' THEN
    map_type := 'areaNormalized';
  ELSIF normalize ILIKE 'denom%' THEN
    map_type := 'denominated';
  ELSIF normalize ILIKE 'pre%' THEN
    map_type := 'predenominated';
  ELSE
    -- defaults: area normalization for point if it's possible and none for
    -- polygon or non-summable point
    IF geom_type = 'point' AND numer_aggregate ILIKE 'sum' THEN
      map_type := 'areaNormalized';
    ELSE
      map_type := 'predenominated';
    END IF;
  END IF;

  params := JSON_Build_Array(JSONB_Set((params::JSONB)->0, '{normalization}', to_jsonb(map_type))::JSON);

  IF params->0->>'geom_id' IS NULL THEN
    RAISE NOTICE 'No boundary found for geom';
    RETURN NULL;
  ELSE
    RAISE NOTICE 'Using boundary %', params->0->>'geom_id';
  END IF;

  EXECUTE $query$
  SELECT (data->0->>'value')::Numeric FROM
    cdb_observatory.OBS_GetData(ARRAY[($1, 1)::geomval], $2)
  $query$
  INTO result
  USING geom, params;

  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetMeasureById(
  geom_ref TEXT,
  measure_id TEXT,
  boundary_id TEXT,
  time_span TEXT DEFAULT NULL
)
RETURNS NUMERIC
AS $$
DECLARE
  result NUMERIC;
BEGIN
  IF geom_ref IS NULL THEN
    RETURN NULL;
  ELSIF boundary_id IS NULL THEN
    RETURN NULL;
  END IF;

  EXECUTE $query$
    SELECT data->0->>'value'
    FROM cdb_observatory.OBS_GetData(Array[$1],
      cdb_observatory.OBS_GetMeta(ST_MakeEnvelope(-180, -90, 180, 90, 4326),
        JSON_Build_Array(JSON_Build_Object(
            'numer_id', $2,
            'geom_id', $3,
            'numer_timespan', $4,
            'normalization', 'predenominated'
          ))))
  $query$
  INTO result
  USING geom_ref, measure_id, boundary_id, time_span;

  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;


-- GetData that obtains data from array of geomrefs
CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetData(
  geomrefs text[],
  params JSON
)
RETURNS TABLE (
  id TEXT,
  data JSON
)
AS $$
DECLARE
  colspecs TEXT;
  tables TEXT;
  obs_wheres TEXT;
  user_wheres TEXT;

  q text;
BEGIN
    IF params IS NULL OR JSON_ARRAY_LENGTH(params) = 0 THEN
      RETURN QUERY EXECUTE $query$ SELECT NULL::TEXT, NULL::JSON LIMIT 0 $query$;
      RETURN;
    END IF;

    EXECUTE
      $query$
        WITH _meta AS (SELECT
          generate_series(1, array_length($1, 1)) colid,
          (unnest($1))->>'id' id,
          (unnest($1))->>'numer_id' numer_id,
          (unnest($1))->>'numer_aggregate' numer_aggregate,
          (unnest($1))->>'numer_colname' numer_colname,
          (unnest($1))->>'numer_geomref_colname' numer_geomref_colname,
          (unnest($1))->>'numer_tablename' numer_tablename,
          (unnest($1))->>'numer_type' numer_type,
          (unnest($1))->>'denom_id' denom_id,
          (unnest($1))->>'denom_aggregate' denom_aggregate,
          (unnest($1))->>'denom_colname' denom_colname,
          (unnest($1))->>'denom_geomref_colname' denom_geomref_colname,
          (unnest($1))->>'denom_tablename' denom_tablename,
          (unnest($1))->>'denom_type' denom_type,
          (unnest($1))->>'denom_reltype' denom_reltype,
          (unnest($1))->>'geom_id' geom_id,
          (unnest($1))->>'geom_colname' geom_colname,
          (unnest($1))->>'geom_geomref_colname' geom_geomref_colname,
          (unnest($1))->>'geom_tablename' geom_tablename,
          (unnest($1))->>'geom_type' geom_type,
          (unnest($1))->>'geom_timespan' geom_timespan,
          (unnest($1))->>'numer_timespan' numer_timespan,
          (unnest($1))->>'normalization' normalization,
          (unnest($1))->>'api_method' api_method,
          (unnest($1))->'api_args' api_args
        )
        SELECT String_Agg(
        -- numeric
        'JSON_Build_Object(' || CASE
        WHEN api_method IS NOT NULL THEN
          '''value'', ' ||
            'ARRAY_AGG( ' ||
              api_method || '.' || numer_colname || ')::' || numer_type || '[]'
        -- numeric internal values
        WHEN cdb_observatory.isnumeric(numer_type) THEN
          '''value'', ' || CASE
          -- denominated
          WHEN LOWER(normalization) LIKE 'denom%' OR (normalization IS NULL AND denom_id IS NOT NULL)
            THEN 'cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname ||
                 ' / NullIf(' || denom_tablename || '.' || denom_colname || ', 0))'
          -- areaNormalized
          WHEN LOWER(normalization) LIKE 'area%' OR (normalization IS NULL AND numer_aggregate ILIKE 'sum')
            THEN 'cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname ||
                 ' / (ST_Area(' || geom_tablename || '.' || geom_colname || '::Geography)/1000000))'
          -- prenormalized
          ELSE 'cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname || ')'
          END || ':: ' || numer_type

        -- categorical/text
        WHEN LOWER(numer_type) LIKE 'text' THEN
          '''value'', ' || 'cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname || ') '

        -- geometry
        WHEN numer_id IS NULL THEN
          '''geomref'', ' || 'cdb_observatory.FIRST(' || geom_tablename ||
            '.' || geom_geomref_colname || '), ' ||
          '''value'', ' || 'cdb_observatory.FIRST(' || geom_tablename ||
              '.' || geom_colname || ')'
        ELSE ''
        END || ')', ', ')
        AS colspecs,

          (SELECT String_Agg(DISTINCT CASE
              -- External API
              WHEN tablename LIKE 'cdb_observatory.%' THEN
                'LATERAL (SELECT * FROM ' || tablename || ') ' ||
                  REPLACE(split_part(tablename, '(', 1), 'cdb_observatory.', '')
              -- Internal obs_ table
              ELSE 'observatory.' || tablename
            END, ', ') FROM (
            SELECT DISTINCT UNNEST(tablenames_ary) tablename FROM (
            SELECT ARRAY_AGG(numer_tablename) ||
                ARRAY_AGG(denom_tablename) ||
                ARRAY_AGG(geom_tablename) ||
                ARRAY_AGG('cdb_observatory.' || api_method || '(_geomrefs.id' || COALESCE(', ' ||
                      (SELECT STRING_AGG(REPLACE(val::text, '"', ''''), ', ')
                       FROM (SELECT json_array_elements(api_args) as val) as vals),
                    '') || ')')
              tablenames_ary
            ) tablenames_inner
          ) tablenames_outer) tablenames,

          String_Agg(DISTINCT array_to_string(ARRAY[
            CASE WHEN numer_tablename != geom_tablename
                 THEN numer_tablename || '.' || numer_geomref_colname || ' = ' ||
                      geom_tablename || '.' || geom_geomref_colname
                 ELSE NULL END,
            CASE WHEN numer_tablename != denom_tablename
                 THEN numer_tablename || '.' || numer_geomref_colname || ' = ' ||
                      denom_tablename || '.' || denom_geomref_colname
                 ELSE NULL END
            ], ' AND '),
           ' AND ') AS obs_wheres,

          String_Agg(geom_tablename || '.' || geom_geomref_colname || ' = ' ||
             '_geomrefs.id', ' AND ')
             AS user_wheres
        FROM _meta
        ;
      $query$
    INTO colspecs, tables, obs_wheres, user_wheres
    USING (SELECT ARRAY(SELECT json_array_elements_text(params))::json[]);

    RETURN QUERY EXECUTE format($query$
      WITH _geomrefs AS (SELECT UNNEST($1) as id)
      SELECT _geomrefs.id, Array_to_JSON(ARRAY[%s]::JSON[])
      FROM _geomrefs, %s
           %s
      GROUP BY _geomrefs.id
      ORDER BY _geomrefs.id
    $query$, colspecs, tables,
             'WHERE ' || NULLIF(ARRAY_TO_STRING(ARRAY[
                    Nullif(obs_wheres, ''), Nullif(user_wheres, '')
                ], ' AND '), '')
        )
    USING geomrefs;
    RETURN;
END;
$$ LANGUAGE plpgsql STABLE;


-- GetData that obtains data from array of (geom, id) geomvals.
CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetData(
  geomvals geomval[],
  params JSON,
  merge BOOLEAN DEFAULT True
)
RETURNS TABLE (
  id INT,
  data JSON
)
AS $$
DECLARE
  geom_colspecs TEXT;
  geom_tables TEXT;
  geomrefs_alias TEXT;
  geomrefs_noalias TEXT;
  data_colspecs TEXT;
  data_tables TEXT;
  obs_wheres TEXT;
  user_wheres TEXT;
  geomtype TEXT;
BEGIN
    IF params IS NULL OR JSON_ARRAY_LENGTH(params) = 0 OR ARRAY_LENGTH(geomvals, 1) IS NULL THEN
      RETURN QUERY EXECUTE $query$ SELECT NULL::INT, NULL::JSON LIMIT 0 $query$;
      RETURN;
    END IF;

    geomtype := ST_GeometryType(geomvals[1].geom);

    EXECUTE
      $query$
        WITH _meta AS (SELECT
          row_number() over () colid,
          meta->>'id' id,
          meta->>'numer_id' numer_id,
          meta->>'numer_aggregate' numer_aggregate,
          meta->>'numer_colname' numer_colname,
          meta->>'numer_geomref_colname' numer_geomref_colname,
          meta->>'numer_tablename' numer_tablename,
          meta->>'numer_type' numer_type,
          meta->>'denom_id' denom_id,
          meta->>'denom_aggregate' denom_aggregate,
          meta->>'denom_colname' denom_colname,
          meta->>'denom_geomref_colname' denom_geomref_colname,
          meta->>'denom_tablename' denom_tablename,
          meta->>'denom_type' denom_type,
          meta->>'denom_reltype' denom_reltype,
          meta->>'geom_id' geom_id,
          meta->>'geom_colname' geom_colname,
          meta->>'geom_geomref_colname' geom_geomref_colname,
          meta->>'geom_tablename' geom_tablename,
          meta->>'geom_type' geom_type,
          meta->>'numer_timespan' numer_timespan,
          meta->>'geom_timespan' geom_timespan,
          meta->>'normalization' normalization,
          meta->>'api_method' api_method,
          meta->'api_args' api_args
          FROM UNNEST($1) AS meta
        )
        SELECT
        String_Agg(DISTINCT
          CASE
          -- pass-through geom if user is requesting it only
          WHEN numer_id IS NULL AND api_method IS NULL THEN
            geom_tablename || '.' || geom_colname || ' AS geom_' || geom_tablename
          WHEN cdb_observatory.isnumeric(numer_type) AND api_method IS NULL THEN
            -- for numeric points with area normalization, include areas of underlying geoms
            CASE
            WHEN $2 = 'ST_Point' AND (LOWER(normalization) LIKE 'area%' OR
               (normalization IS NULL AND numer_aggregate ILIKE 'sum')) THEN
              ' Nullif(ST_Area(' || geom_tablename || '.' || geom_colname || '::Geography), 0)/1000000 ' ||
              ' AS area_' || geom_tablename
            -- for numeric areas, include more complex calcs
            WHEN $2 != 'ST_Point' THEN
            'CASE WHEN ST_Within(_geoms.geom, ' || geom_tablename || '.' || geom_colname || ') ' ||
            '     THEN ST_Area(_geoms.geom) / Nullif(ST_Area(' || geom_tablename || '.' || geom_colname || '), 0)' ||
            '     WHEN ST_Within(' || geom_tablename || '.' || geom_colname || ', _geoms.geom) ' ||
            '     THEN 1 ' ||
            '     ELSE ST_Area(cdb_observatory.safe_intersection(_geoms.geom, ' ||
                               geom_tablename || '.' || geom_colname || ')) / ' ||
                           'Nullif(ST_Area(' || geom_tablename || '.' || geom_colname || '), 0) ' ||
            'END pct_' || geom_tablename
            ELSE NULL
            END
          ELSE NULL END
        , ', ') AS geom_colspecs,
        String_Agg(DISTINCT 'observatory.' || geom_tablename, ', ') AS geom_tables,
        String_Agg(
        'JSON_Build_Object(' || CASE
          -- api-delivered values
          WHEN api_method IS NOT NULL THEN
          '''value'', ' ||
            'ARRAY_AGG( ' ||
              api_method || '.' || numer_colname || ')::' || numer_type || '[]'
          -- numeric internal values
          WHEN cdb_observatory.isnumeric(numer_type) THEN
          '''value'', ' || CASE
          -- denominated
          WHEN LOWER(normalization) LIKE 'denom%' OR
               (normalization IS NULL AND LOWER(denom_reltype) LIKE 'denominator')
            THEN CASE
            -- denominated point-in-poly
            WHEN $2 = 'ST_Point' THEN
            ' cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname ||
            '      / NullIf(' || denom_tablename || '.' || denom_colname || ', 0))'
            -- denominated polygon interpolation
            -- SUM (numer * (% OBS geom in user geom)) / SUM (denom * (% OBS geom in user geom))
            ELSE
            ' SUM(' || numer_tablename || '.' || numer_colname || ' ' ||
            ' * pct_' || geom_tablename ||
            ' ) / NULLIF(SUM(' || denom_tablename || '.' || denom_colname || ' ' ||
            '            * pct_' || geom_tablename || '), 0) ' ||
            ' / (COUNT(*) / COUNT(distinct geomref_' || geom_tablename || ')) '
            END
          -- areaNormalized
          WHEN LOWER(normalization) LIKE 'area%' OR
              (normalization IS NULL AND numer_aggregate ILIKE 'sum')
            THEN CASE
            -- areaNormalized point-in-poly
            WHEN $2 = 'ST_Point' THEN
            ' cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname ||
            '      / area_' || geom_tablename || ')'
            -- areaNormalized polygon interpolation
            -- SUM (numer * (% OBS geom in user geom)) / area of big geom
            ELSE
            --' NULL END '
            ' SUM(' || numer_tablename || '.' || numer_colname || ' ' ||
            ' * pct_' || geom_tablename ||
            ' ) / (Nullif(ST_Area(cdb_observatory.FIRST(_procgeoms.geom)::Geography), 0) / 1000000) ' ||
            ' / (COUNT(*) / COUNT(distinct geomref_' || geom_tablename || ')) '
            END
          -- median/average measures with universe
          WHEN LOWER(numer_aggregate) IN ('median', 'average') AND
              denom_reltype ILIKE 'universe' AND
              (normalization IS NULL OR LOWER(normalization) LIKE 'pre%')
            THEN CASE
            -- predenominated point-in-poly
            WHEN $2 = 'ST_Point' THEN
            ' cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname || ') '
            ELSE
            -- predenominated polygon interpolation weighted by universe
            -- SUM (numer * denom * (% user geom in OBS geom)) / SUM (denom * (% user geom in OBS geom))
            --     (10 * 1000 * 1) / (1000 * 1) = 10
            --     (10 * 1000 * 1 + 50 * 10 * 1) / (1000 + 10) = 10500 / 10000 = 10.5
            ' SUM(' || numer_tablename || '.' || numer_colname ||
            ' * ' || denom_tablename || '.' || denom_colname ||
            ' * pct_' || geom_tablename ||
            ' ) / Nullif(SUM(' || denom_tablename || '.' || denom_colname ||
            ' * pct_' || geom_tablename || '), 0) ' ||
            ' / (COUNT(*) / COUNT(distinct geomref_' || geom_tablename || ')) '
            END
          -- prenormalized for summable measures. point or summable only!
          WHEN numer_aggregate ILIKE 'sum' AND
              (normalization IS NULL OR LOWER(normalization) LIKE 'pre%')
            THEN CASE
            -- predenominated point-in-poly
            WHEN $2 = 'ST_Point' THEN
            ' cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname || ') '
            ELSE
            -- predenominated polygon interpolation
            -- SUM (numer * (% user geom in OBS geom))
            ' SUM(' || numer_tablename || '.' || numer_colname || ' ' ||
            ' * pct_' || geom_tablename ||
            ' ) / (COUNT(*) / COUNT(distinct geomref_' || geom_tablename || ')) '
            END
          -- Everything else. Point only!
          ELSE CASE
            WHEN $2 = 'ST_Point' THEN
            ' cdb_observatory.FIRST(' || numer_tablename || '.' || numer_colname || ') '
            ELSE
            ' cdb_observatory._OBS_RaiseNotice(''Cannot perform calculation over polygon for ' ||
                numer_id || '/' || coalesce(denom_id, '') || '/' || geom_id || '/' || numer_timespan || ''')::Numeric '
            END
          END || '::' || numer_type

          -- categorical/text
        WHEN LOWER(numer_type) LIKE 'text' THEN
          '''value'', ' || 'MODE() WITHIN GROUP (ORDER BY ' || numer_tablename || '.' || numer_colname || ') '

          -- geometry
        WHEN numer_id IS NULL THEN
          '''geomref'', geomref_' || geom_tablename || ', ' ||
          '''value'', ' || 'cdb_observatory.FIRST(geom_' || geom_tablename ||
              ')::TEXT'
          -- code below will return the intersection of the user's geom and the
          -- OBS geom
          --'''value'', ' || 'ST_Union(cdb_observatory.safe_intersection(_geoms.geom, ' || geom_tablename ||
          --    '.' || geom_colname || '))::TEXT'
        ELSE ''
        END || ')', ', ')
        AS colspecs,

        -- geomrefs, used to separate out rows in case we don't want to merge
        -- results by user input IDs
        --
        -- api_method and geom_tablename are interchangeable since when an
        -- api_method is passed, geom_tablename is ignored
        String_Agg(DISTINCT COALESCE(geom_tablename, api_method) || '.' || geom_geomref_colname ||
          ' AS geomref_' || COALESCE(geom_tablename, api_method), ', ') AS geomrefs_alias,

        String_Agg(DISTINCT 'geomref_' || COALESCE(geom_tablename, api_method)
          , ', ') AS geomrefs_noalias,

          (SELECT String_Agg(DISTINCT CASE
              -- External API
              WHEN tablename LIKE 'cdb_observatory.%' THEN
                'LATERAL (SELECT * FROM ' || tablename || ') ' ||
                  REPLACE(split_part(tablename, '(', 1), 'cdb_observatory.', '')
              -- Internal obs_ table
              ELSE 'observatory.' || tablename
            END, ', ') FROM (
            SELECT DISTINCT UNNEST(tablenames_ary) tablename FROM (
            SELECT ARRAY_AGG(numer_tablename) ||
                ARRAY_AGG(denom_tablename) ||
                ARRAY_AGG('cdb_observatory.' || api_method || '(_procgeoms.geom' || COALESCE(', ' ||
                      (SELECT STRING_AGG(REPLACE(val::text, '"', ''''), ', ')
                       FROM (SELECT json_array_elements(api_args) as val) as vals),
                    '') || ')')
              tablenames_ary
            ) tablenames_inner
          ) tablenames_outer) data_tables,

          String_Agg(DISTINCT array_to_string(ARRAY[
            CASE WHEN numer_tablename IS NOT NULL AND geom_tablename IS NOT NULL
                 THEN numer_tablename || '.' || numer_geomref_colname || ' = ' ||
                      '_procgeoms.geomref_' || geom_tablename
                 ELSE NULL END,
            CASE WHEN numer_tablename != denom_tablename
                 THEN numer_tablename || '.' || numer_geomref_colname || ' = ' ||
                      denom_tablename || '.' || denom_geomref_colname
                 ELSE NULL END
            ], ' AND '),
           ' AND ') FILTER (WHERE numer_tablename != denom_tablename OR
                            (numer_tablename IS NOT NULL AND geom_tablename IS NOT NULL)) AS obs_wheres,

          String_Agg(DISTINCT 'ST_Intersects(' || geom_tablename || '.' ||  geom_colname
             || ', _geoms.geom)', ' AND ')
             AS user_wheres
        FROM _meta
        ;
      $query$
    INTO geom_colspecs, geom_tables, data_colspecs, geomrefs_alias,
         geomrefs_noalias, data_tables, obs_wheres, user_wheres
    USING (SELECT ARRAY(SELECT json_array_elements_text(params))::json[]), geomtype;


    RAISE NOTICE '%', format($query$
      WITH _raw_geoms AS (SELECT
                     %L::integer as id,
                     %L::geometry AS geom),
      _geoms AS (SELECT id,
        CASE WHEN (ST_NPoints(geom) > 500)
               THEN ST_CollectionExtract(ST_MakeValid(ST_SimplifyVW(geom, 0.0001)), 3)
             ELSE geom END geom
        FROM _raw_geoms),
      _procgeoms AS (SELECT _geoms.id, _geoms.geom %s %s
        FROM _geoms %s
        %s
      )
      SELECT _procgeoms.id::INT, Array_to_JSON(ARRAY[%s]::JSON[])
      FROM _procgeoms %s
           %s
      GROUP BY _procgeoms.id %s
      ORDER BY _procgeoms.id
    $query$, geomvals[1].val, geomvals[1].geom, ', ' || NullIf(geomrefs_alias, ''),
             ', ' || NullIf(geom_colspecs, ''),
             ', ' || NullIf(geom_tables, ''),
             'WHERE ' || NullIf( user_wheres, ''),
              data_colspecs, ', ' || NullIf(data_tables, ''),
             'WHERE ' || NULLIF(obs_wheres, ''),
             CASE WHEN merge IS False THEN ', ' || geomrefs_noalias ELSE '' END);



    RETURN QUERY EXECUTE format($query$
      WITH _raw_geoms AS (%s),
      _geoms AS (SELECT id,
        CASE WHEN (ST_NPoints(geom) > 500)
               THEN ST_CollectionExtract(ST_MakeValid(ST_SimplifyVW(geom, 0.0001)), 3)
             ELSE geom END geom
        FROM _raw_geoms),
      _procgeoms AS (SELECT _geoms.id, _geoms.geom %s %s
        FROM _geoms %s
        %s
      )
      SELECT _procgeoms.id::INT, Array_to_JSON(ARRAY[%s]::JSON[])
      FROM _procgeoms %s
           %s
      GROUP BY _procgeoms.id %s
      ORDER BY _procgeoms.id
    $query$, CASE WHEN ARRAY_LENGTH(geomvals, 1) = 1 THEN
               ' SELECT $1[1].val as id, $1[1].geom as geom '
             ELSE
               ' SELECT val as id, geom FROM UNNEST($1) '
             END,
             ', ' || NullIf(geomrefs_alias, ''),
             ', ' || NullIf(geom_colspecs, ''),
             ', ' || NullIf(geom_tables, ''),
             'WHERE ' || NullIf( user_wheres, ''),
              data_colspecs, ', ' || NullIf(data_tables, ''),
             'WHERE ' || NULLIF(obs_wheres, ''),
             CASE WHEN merge IS False THEN ', ' || geomrefs_noalias ELSE '' END)
    USING geomvals;
    RETURN;
END;
$$ LANGUAGE plpgsql STABLE;


CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetCategory(
  geom geometry(Geometry, 4326),
  category_id TEXT,
  boundary_id TEXT DEFAULT NULL,
  time_span TEXT DEFAULT NULL,
  simplification NUMERIC DEFAULT 0.00001
)
RETURNS TEXT
AS $$
DECLARE
  geom_type TEXT;
  params JSON;
  map_type TEXT;
  result TEXT;
BEGIN
  IF geom IS NULL THEN
    RETURN NULL;
  END IF;

  IF simplification IS NOT NULL THEN
    geom := ST_Simplify(geom, simplification);
  END IF;

  IF ST_GeometryType(geom) = 'ST_Point' THEN
    geom_type := 'point';
  ELSIF ST_GeometryType(geom) IN ('ST_Polygon', 'ST_MultiPolygon') THEN
    geom_type := 'polygon';
    geom := ST_CollectionExtract(ST_MakeValid(geom), 3);
  ELSE
    RAISE EXCEPTION 'Invalid geometry type (%), can only handle ''ST_Point'', ''ST_Polygon'', and ''ST_MultiPolygon''',
                    ST_GeometryType(geom);
  END IF;

  params := (SELECT cdb_observatory.OBS_GetMeta(
    geom, JSON_Build_Array(JSON_Build_Object('numer_id', category_id,
                                             'geom_id', boundary_id,
                                             'numer_timespan', time_span
                                            )), 1, 1, 500));

  IF params->0->>'geom_id' IS NULL THEN
    RAISE NOTICE 'No boundary found for geom';
    RETURN NULL;
  ELSE
    RAISE NOTICE 'Using boundary %', params->0->>'geom_id';
  END IF;

  EXECUTE $query$
  SELECT data->0->>'value' FROM
    cdb_observatory.OBS_GetData(ARRAY[($1, 1)::geomval], $2)
  $query$
  INTO result
  USING geom, params;

  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;


CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetUSCensusMeasure(
   geom geometry(Geometry, 4326),
   name TEXT,
   normalize TEXT DEFAULT NULL,
   boundary_id TEXT DEFAULT NULL,
   time_span TEXT DEFAULT NULL
 )
RETURNS NUMERIC AS $$
DECLARE
  standardized_name text;
  measure_id text;
  result Numeric;
BEGIN
  standardized_name = cdb_observatory._OBS_StandardizeMeasureName(name);

  EXECUTE $string$
  SELECT c.id
  FROM observatory.obs_column c
       JOIN observatory.obs_column_tag ct
         ON c.id = ct.column_id
       WHERE cdb_observatory._OBS_StandardizeMeasureName(c.name) = $1
         AND ct.tag_id ILIKE 'us.census%'
  $string$
  INTO measure_id
  USING standardized_name;

  EXECUTE 'SELECT cdb_observatory.OBS_GetMeasure($1, $2, $3, $4, $5)'
  INTO result
  USING geom, measure_id, normalize, boundary_id, time_span;
  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;


CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetUSCensusCategory(
   geom geometry(Geometry, 4326),
   name TEXT,
   boundary_id TEXT DEFAULT NULL,
   time_span TEXT DEFAULT NULL
 )
RETURNS TEXT AS $$
DECLARE
  standardized_name TEXT;
  category_id TEXT;
  result TEXT;
BEGIN
  standardized_name = cdb_observatory._OBS_StandardizeMeasureName(name);

  EXECUTE $string$
  SELECT c.id
  FROM observatory.obs_column c
       --JOIN observatory.obs_column_tag ct
       --  ON c.id = ct.column_id
       WHERE cdb_observatory._OBS_StandardizeMeasureName(c.name) = $1
         AND c.type ILIKE 'TEXT'
         AND c.id ILIKE 'us.census%' -- TODO this should be done by tag
         --AND ct.tag_id = 'us.census.acs.demographics'
  $string$
  INTO category_id
  USING standardized_name;

  EXECUTE 'SELECT cdb_observatory.OBS_GetCategory($1, $2, $3, $4)'
  INTO result
  USING geom, category_id, boundary_id, time_span;

  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetPopulation(
  geom geometry(Geometry, 4326),
  normalize TEXT DEFAULT NULL,
  boundary_id TEXT DEFAULT NULL,
  time_span TEXT DEFAULT NULL
)
RETURNS NUMERIC
AS $$
DECLARE
  population_measure_id TEXT;
  result Numeric;
BEGIN
  -- TODO use a super-column for global pop
  population_measure_id := 'us.census.acs.B01003001';

  EXECUTE $query$ SELECT cdb_observatory.OBS_GetMeasure(
      $1, $2, $3, $4, $5
  ) LIMIT 1
  $query$
  INTO result
  USING geom, population_measure_id, normalize, boundary_id, time_span;

  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;


CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetSegmentSnapshot(
  geom geometry(Geometry, 4326),
  boundary_id text DEFAULT NULL
)
RETURNS JSON
AS $$
DECLARE
  meta JSON;
  data JSON;
  result JSON;
BEGIN
  boundary_id = COALESCE(boundary_id, 'us.census.tiger.census_tract');

  EXECUTE $query$
    SELECT cdb_observatory.OBS_GetMeta($1, ('[ ' ||
            '{"numer_id": "us.census.acs.B01003001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B01001002_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B01001026_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B01002001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B03002003_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B03002004_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B03002006_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B03002012_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B05001006_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B08006001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B08006002_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B08301010_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B08006009_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B08006011_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B08006015_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B08006017_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B09001001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B11001001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B14001001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B14001002_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B14001005_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B14001006_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B14001007_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B14001008_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B15003001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B15003017_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B15003022_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B15003023_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B16001001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B16001002_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B16001003_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B17001001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B17001002_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B19013001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B19083001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B19301001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25001001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25002003_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25004002_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25004004_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25058001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25071001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25075001_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.acs.B25075025_quantile", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.spielman_singleton_segments.X10", "geom_id": ' || $2 || '},' ||
            '{"numer_id": "us.census.spielman_singleton_segments.X55", "geom_id": ' || $2 || '}' ||
          ']')::JSON)
  $query$
  INTO meta
  USING geom, COALESCE('"' || boundary_id || '"', 'null');

  EXECUTE $query$
    SELECT data FROM cdb_observatory.OBS_GetData(
      ARRAY[($1, 1)::geomval], $2)
  $query$
  INTO data
  USING geom, meta;

  EXECUTE $query$
    WITH els AS (SELECT
      REPLACE(REPLACE(JSON_Array_Elements($1)->>'numer_id',
        'us.census.spielman_singleton_segments.X55', 'x55_segment'),
        'us.census.spielman_singleton_segments.X10', 'x10_segment') k,
      JSON_Array_Elements($2)->>'value' v)
    SELECT JSON_Object_Agg(k, v) FROM els
  $query$
  INTO result
  USING meta, data;

  RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;

-- TODO: implement search for timespan

CREATE OR REPLACE FUNCTION cdb_observatory._OBS_SearchTables(
  search_term text,
  time_span text DEFAULT NULL
)
RETURNS table(tablename text, timespan text)
As $$
DECLARE
  out_var text[];
BEGIN

  IF time_span IS NULL
  THEN
    RETURN QUERY
    EXECUTE
    'SELECT tablename::text, timespan::text
       FROM observatory.obs_table t
       JOIN observatory.obs_column_table ct
         ON ct.table_id = t.id
       JOIN observatory.obs_column c
         ON ct.column_id = c.id
       WHERE c.type ILIKE ''geometry''
        AND c.id = $1'
    USING search_term;
    RETURN;
  ELSE
    RETURN QUERY
    EXECUTE
    'SELECT tablename::text, timespan::text
       FROM observatory.obs_table t
       JOIN observatory.obs_column_table ct
         ON ct.table_id = t.id
       JOIN observatory.obs_column c
         ON ct.column_id = c.id
       WHERE c.type ILIKE ''geometry''
        AND c.id = $1
        AND t.timespan = $2'
    USING search_term, time_span;
    RETURN;
  END IF;

END;
$$ LANGUAGE plpgsql IMMUTABLE;

-- Functions used to search the observatory for measures
--------------------------------------------------------------------------------
-- TODO allow the user to specify the boundary to search for measures
--

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_Search(
  search_term text,
  relevant_boundary text DEFAULT null
)
RETURNS TABLE(id text, description text, name text, aggregate text, source text)  as $$
DECLARE
  boundary_term text;
BEGIN
  IF relevant_boundary then
    boundary_term = '';
  else
    boundary_term = '';
  END IF;

  RETURN QUERY
  EXECUTE format($string$
              SELECT id::text, description::text,
                name::text,
                  aggregate::text,
                  NULL::TEXT source -- TODO use tags
                  FROM observatory.OBS_column
                  where name ilike     '%%' || %L || '%%'
                  or description ilike '%%' || %L || '%%'
                  %s
                $string$, search_term, search_term,boundary_term);
  RETURN;
END
$$ LANGUAGE plpgsql;


-- Functions to return the geometry levels that a point is part of
--------------------------------------------------------------------------------
-- TODO add test response

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetAvailableBoundaries(
  geom geometry(Geometry, 4326),
  timespan text DEFAULT null)
RETURNS TABLE(boundary_id text, description text, time_span text, tablename text)  as $$
DECLARE
  timespan_query TEXT DEFAULT '';
BEGIN

  IF timespan != NULL
  THEN
    timespan_query = format('AND timespan = %L', timespan);
  END IF;

  RETURN QUERY
  EXECUTE
  $string$
      SELECT
        column_id::text As column_id,
        obs_column.description::text As description,
        timespan::text As timespan,
        tablename::text As tablename
      FROM
        observatory.OBS_table,
        observatory.OBS_column_table,
        observatory.OBS_column
      WHERE
        observatory.OBS_column_table.column_id = observatory.obs_column.id AND
        observatory.OBS_column_table.table_id = observatory.obs_table.id
      AND
        observatory.OBS_column.type = 'Geometry'
      AND
        ST_Intersects($1, st_setsrid(observatory.obs_table.the_geom, 4326))
  $string$ || timespan_query
  USING geom;
  RETURN;
END
$$ LANGUAGE plpgsql;

-- Functions the interface works from to identify available numerators,
-- denominators, geometries, and timespans

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetAvailableNumerators(
  bounds GEOMETRY DEFAULT NULL,
  filter_tags TEXT[] DEFAULT NULL,
  denom_id TEXT DEFAULT NULL,
  geom_id TEXT DEFAULT NULL,
  timespan TEXT DEFAULT NULL
) RETURNS TABLE (
  numer_id TEXT,
  numer_name TEXT,
  numer_description TEXT,
  numer_weight NUMERIC,
  numer_license TEXT,
  numer_source TEXT,
  numer_type TEXT,
  numer_aggregate TEXT,
  numer_extra JSONB,
  numer_tags JSONB,
  valid_denom BOOLEAN,
  valid_geom BOOLEAN,
  valid_timespan BOOLEAN
) AS $$
DECLARE
  geom_clause TEXT;
BEGIN
  filter_tags := COALESCE(filter_tags, (ARRAY[])::TEXT[]);
  denom_id := COALESCE(denom_id, '');
  geom_id := COALESCE(geom_id, '');
  timespan := COALESCE(timespan, '');
  IF bounds IS NULL THEN
    geom_clause := '';
  ELSE
    geom_clause := 'ST_Intersects(the_geom, $5) AND';
  END IF;
  RETURN QUERY
  EXECUTE
  format($string$
    SELECT numer_id::TEXT,
           numer_name::TEXT,
           numer_description::TEXT,
           numer_weight::NUMERIC,
           NULL::TEXT license,
           NULL::TEXT source,
           numer_type numer_type,
           numer_aggregate numer_aggregate,
           numer_extra::JSONB numer_extra,
           numer_tags numer_tags,
    $1 = ANY(denoms) valid_denom,
    $2 = ANY(geoms) valid_geom,
    $3 = ANY(timespans) valid_timespan
    FROM observatory.obs_meta_numer
    WHERE %s (numer_tags ?& $4 OR CARDINALITY($4) = 0)
  $string$, geom_clause)
  USING denom_id, geom_id, timespan, filter_tags, bounds;
  RETURN;
END
$$ LANGUAGE plpgsql;

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetAvailableDenominators(
  bounds GEOMETRY DEFAULT NULL,
  filter_tags TEXT[] DEFAULT NULL,
  numer_id TEXT DEFAULT NULL,
  geom_id TEXT DEFAULT NULL,
  timespan TEXT DEFAULT NULL
) RETURNS TABLE (
  denom_id TEXT,
  denom_name TEXT,
  denom_description TEXT,
  denom_weight NUMERIC,
  denom_license TEXT,
  denom_source TEXT,
  denom_type TEXT,
  denom_aggregate TEXT,
  denom_extra JSONB,
  denom_tags JSONB,
  valid_numer BOOLEAN,
  valid_geom BOOLEAN,
  valid_timespan BOOLEAN
) AS $$
DECLARE
  geom_clause TEXT;
BEGIN
  filter_tags := COALESCE(filter_tags, (ARRAY[])::TEXT[]);
  numer_id := COALESCE(numer_id, '');
  geom_id := COALESCE(geom_id, '');
  timespan := COALESCE(timespan, '');
  IF bounds IS NULL THEN
    geom_clause := '';
  ELSE
    geom_clause := 'ST_Intersects(the_geom, $5) AND';
  END IF;
  RETURN QUERY
  EXECUTE
  format($string$
    SELECT denom_id::TEXT,
           denom_name::TEXT,
           denom_description::TEXT,
           denom_weight::NUMERIC,
           NULL::TEXT license,
           NULL::TEXT source,
           denom_type::TEXT,
           denom_aggregate::TEXT,
           denom_extra::JSONB,
           denom_tags::JSONB,
    $1 = ANY(numers) valid_numer,
    $2 = ANY(geoms) valid_geom,
    $3 = ANY(timespans) valid_timespan
    FROM observatory.obs_meta_denom
    WHERE %s (denom_tags ?& $4 OR CARDINALITY($4) = 0)
  $string$, geom_clause)
  USING numer_id, geom_id, timespan, filter_tags, bounds;
  RETURN;
END
$$ LANGUAGE plpgsql;

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetAvailableGeometries(
  bounds GEOMETRY DEFAULT NULL,
  filter_tags TEXT[] DEFAULT NULL,
  numer_id TEXT DEFAULT NULL,
  denom_id TEXT DEFAULT NULL,
  timespan TEXT DEFAULT NULL
) RETURNS TABLE (
  geom_id TEXT,
  geom_name TEXT,
  geom_description TEXT,
  geom_weight NUMERIC,
  geom_aggregate TEXT,
  geom_license TEXT,
  geom_source TEXT,
  valid_numer BOOLEAN,
  valid_denom BOOLEAN,
  valid_timespan BOOLEAN,
  score NUMERIC,
  numtiles BIGINT,
  notnull_percent NUMERIC,
  numgeoms NUMERIC,
  percentfill NUMERIC,
  estnumgeoms NUMERIC,
  meanmediansize NUMERIC
) AS $$
DECLARE
  geom_clause TEXT;
BEGIN
  filter_tags := COALESCE(filter_tags, (ARRAY[])::TEXT[]);
  numer_id := COALESCE(numer_id, '');
  denom_id := COALESCE(denom_id, '');
  timespan := COALESCE(timespan, '');
  IF bounds IS NULL THEN
    geom_clause := '';
  ELSE
    geom_clause := 'ST_Intersects(the_geom, $5) AND';
  END IF;
  RETURN QUERY
  EXECUTE
  format($string$
    WITH available_geoms AS (
      SELECT geom_id::TEXT,
             geom_name::TEXT,
             geom_description::TEXT,
             geom_weight::NUMERIC,
             NULL::TEXT geom_aggregate,
             NULL::TEXT license,
             NULL::TEXT source,
      $1 = ANY(numers) valid_numer,
      $2 = ANY(denoms) valid_denom,
      $3 = ANY(timespans) valid_timespan
      FROM observatory.obs_meta_geom
      WHERE %s (geom_tags ?& $4 OR CARDINALITY($4) = 0)
    ), scores AS (
      SELECT * FROM cdb_observatory._OBS_GetGeometryScores($5,
        (SELECT ARRAY_AGG(geom_id) FROM available_geoms)
      )
    ) SELECT available_geoms.*, score, numtiles, notnull_percent, numgeoms,
             percentfill, estnumgeoms, meanmediansize
      FROM available_geoms, scores
      WHERE available_geoms.geom_id = scores.column_id
  $string$, geom_clause)
  USING numer_id, denom_id, timespan, filter_tags, bounds;
  RETURN;
END
$$ LANGUAGE plpgsql;

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetAvailableTimespans(
  bounds GEOMETRY DEFAULT NULL,
  filter_tags TEXT[] DEFAULT NULL,
  numer_id TEXT DEFAULT NULL,
  denom_id TEXT DEFAULT NULL,
  geom_id TEXT DEFAULT NULL
) RETURNS TABLE (
  timespan_id TEXT,
  timespan_name TEXT,
  timespan_description TEXT,
  timespan_weight NUMERIC,
  timespan_aggregate TEXT,
  timespan_license TEXT,
  timespan_source TEXT,
  valid_numer BOOLEAN,
  valid_denom BOOLEAN,
  valid_geom BOOLEAN
) AS $$
DECLARE
  geom_clause TEXT;
BEGIN
  filter_tags := COALESCE(filter_tags, (ARRAY[])::TEXT[]);
  numer_id := COALESCE(numer_id, '');
  denom_id := COALESCE(denom_id, '');
  geom_id := COALESCE(geom_id, '');
  IF bounds IS NULL THEN
    geom_clause := '';
  ELSE
    geom_clause := 'ST_Intersects(the_geom, $5) AND';
  END IF;
  RETURN QUERY
  EXECUTE
  format($string$
    SELECT timespan_id::TEXT,
           timespan_name::TEXT,
           timespan_description::TEXT,
           timespan_weight::NUMERIC,
           NULL::TEXT timespan_aggregate,
           NULL::TEXT license,
           NULL::TEXT source,
    $1 = ANY(numers) valid_numer,
    $2 = ANY(denoms) valid_denom,
    $3 = ANY(geoms) valid_geom_id
    FROM observatory.obs_meta_timespan
    WHERE %s (timespan_tags ?& $4 OR CARDINALITY($4) = 0)
  $string$, geom_clause)
  USING numer_id, denom_id, geom_id, filter_tags, bounds;
  RETURN;
END
$$ LANGUAGE plpgsql;


-- Function below should replace SQL in
-- https://github.com/CartoDB/cartodb/blob/ab465cb2918c917940e955963b0cd8a050c06600/lib/assets/javascripts/cartodb3/editor/layers/layer-content-views/analyses/data-observatory-metadata.js
CREATE OR REPLACE FUNCTION cdb_observatory.OBS_LegacyBuilderMetadata(
  aggregate_type TEXT DEFAULT NULL
)
RETURNS TABLE (
  name TEXT,
  subsection JSONB
) AS $$
DECLARE
  aggregate_condition TEXT DEFAULT '';
BEGIN
  IF LOWER(aggregate_type) ILIKE 'sum' THEN
    aggregate_condition := ' AND numer_aggregate IN (''sum'', ''median'', ''average'') ';
  ELSIF aggregate_type IS NOT NULL THEN
    aggregate_condition := format(' AND numer_aggregate ILIKE %L ', aggregate_type);
  END IF;
  RETURN QUERY
  EXECUTE format($string$
    WITH expanded AS (
        SELECT JSONB_Build_Object('id', numer_id, 'name', numer_name) "column",
               SUBSTR((sections).key, 9) section_id, (sections).value section_name,
               SUBSTR((subsections).key, 12) subsection_id, (subsections).value subsection_name
        FROM (
          SELECT numer_id, numer_name,
                 jsonb_each_text(numer_tags) as sections,
                 jsonb_each_text as subsections
          FROM (SELECT numer_id, numer_name, numer_tags,
                       jsonb_each_text(numer_tags)
                FROM cdb_observatory.obs_getavailablenumerators()
                WHERE numer_weight > 0 %s
               ) foo
        ) bar
        WHERE (sections).key LIKE 'section/%%'
          AND (subsections).key LIKE 'subsection/%%'
      ), grouped_by_subsections AS (
        SELECT JSONB_Agg(JSONB_Build_Object('f1', "column")) AS columns,
               section_id, section_name, subsection_id, subsection_name
        FROM expanded
        GROUP BY section_id, section_name, subsection_id, subsection_name
      )
    SELECT section_name as name, JSONB_Agg(
      JSONB_Build_Object(
        'f1', JSONB_Build_Object(
          'name', subsection_name,
          'id', subsection_id,
          'columns', columns
        )
      )
    ) as subsection
    FROM grouped_by_subsections
    GROUP BY section_name
  $string$, aggregate_condition);
  RETURN;
END
$$ LANGUAGE plpgsql;


CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetGeometryScores(
  bounds Geometry(Geometry, 4326) DEFAULT NULL,
  filter_geom_ids TEXT[] DEFAULT NULL,
  desired_num_geoms INTEGER DEFAULT NULL
) RETURNS TABLE (
  score NUMERIC,
  numtiles BIGINT,
  table_id TEXT,
  column_id TEXT,
  notnull_percent NUMERIC,
  numgeoms NUMERIC,
  percentfill NUMERIC,
  estnumgeoms NUMERIC,
  meanmediansize NUMERIC
) AS $$
BEGIN
  IF desired_num_geoms IS NULL THEN
    desired_num_geoms := 3000;
  END IF;
  filter_geom_ids := COALESCE(filter_geom_ids, (ARRAY[])::TEXT[]);
  -- Very complex geometries simply fail.  For a boundary check, we can
  -- comfortably get away with the simplicity of an envelope
  IF ST_Npoints(bounds) > 10000 THEN
    bounds := ST_Envelope(bounds);
  END IF;
  RETURN QUERY
  EXECUTE $string$
    WITH clipped_geom AS (
      SELECT column_id, table_id
        , CASE WHEN $1 IS NOT NULL THEN ST_Clip(tile, $1, True) -- -20
               ELSE tile END clipped_tile
        , tile
      FROM observatory.obs_column_table_tile_simple
      WHERE ($1 IS NULL OR ST_Intersects($1, tile))
        AND (column_id = ANY($2) OR cardinality($2) = 0)
    ), clipped_geom_countagg AS (
      SELECT column_id, table_id
        , BOOL_AND(ST_BandIsNoData(clipped_tile, 1)) nodata
        , ST_CountAgg(clipped_tile, 1, False)::Numeric pixels -- -10
      FROM clipped_geom
      GROUP BY column_id, table_id
    ), clipped_geom_reagg AS (
      SELECT COUNT(*)::BIGINT cnt, a.column_id, a.table_id,
             cdb_observatory.FIRST(nodata) first_nodata,
             cdb_observatory.FIRST(pixels) first_pixel,
             cdb_observatory.FIRST(tile) first_tile,
             (ST_SummaryStatsAgg(clipped_tile, 1, False)).sum::Numeric sum_geoms, -- ND
             (ST_SummaryStatsAgg(clipped_tile, 2, False)).mean::Numeric / 255 mean_fill --ND
      FROM clipped_geom_countagg a, clipped_geom b
      WHERE a.table_id = b.table_id
        AND a.column_id = b.column_id
      GROUP BY a.column_id, a.table_id
    ), final AS (
      SELECT
        cnt, table_id, column_id
        , NULL::Numeric AS notnull_percent
        , (CASE WHEN first_nodata IS FALSE
                THEN sum_geoms
                ELSE COALESCE(ST_Value(first_tile, 1, ST_PointOnSurface($1)), 0)
                  * (ST_Area($1) / ST_Area(ST_PixelAsPolygon(first_tile, 0, 0))
                    * first_pixel) -- -20
          END)::Numeric
        AS numgeoms
        , (CASE WHEN first_nodata IS FALSE
                THEN mean_fill
                ELSE COALESCE(ST_Value(first_tile, 2, ST_PointOnSurface($1))::Numeric / 255, 0) -- -2
          END)::Numeric
        AS percentfill
        , null::numeric estnumgeoms
        , null::numeric meanmediansize
      FROM clipped_geom_reagg
    ) SELECT
      ((100.0 / (1+abs(log(0.0001 + $3) - log(0.0001 + numgeoms::Numeric)))) * percentfill)::Numeric
      AS score, *
      FROM final
  $string$ USING bounds, filter_geom_ids, desired_num_geoms;
  RETURN;
END
$$ LANGUAGE plpgsql IMMUTABLE;
-- Data Observatory -- Welcome to the Future
-- These Data Observatory functions provide access to boundary polyons (and
--   their ids) such as those available through the US Census Tiger, Who's on
--   First, the Spanish Census, and so on


-- OBS_GetBoundary
--
-- Returns the boundary polygon(s) that overlap with the input point geometry.
-- From an input point geometry, find the boundary which intersects with the
--   centroid of the input geometry
-- Inputs:
--   geom geometry: input point geometry
--   boundary_id text: source id of boundaries
--                     see function OBS_ListGeomColumns for all avaiable
--                     boundary ids
--   time_span text: time span that the geometries were collected (optional)
--
-- Output:
--   boundary geometry: geometry boundary that intersects with geom, is at the
--                      resolution requested with boundary_id, and time_span
--

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundary(
  geom geometry(Point, 4326),
  boundary_id text,
  time_span text DEFAULT NULL)
RETURNS geometry(Geometry, 4326)
AS $$
DECLARE
  boundary geometry(Geometry, 4326);
  target_table text;
BEGIN

  -- TODO: Check if SRID = 4326, if not transform?

  -- if not a point, raise error
  IF ST_GeometryType(geom) != 'ST_Point'
  THEN
    RAISE EXCEPTION 'Invalid geometry type (%), expecting ''ST_Point''', ST_GeometryType(geom);
  END IF;

  -- return the first boundary in intersections
  EXECUTE $query$
    SELECT * FROM cdb_observatory._OBS_GetBoundariesByGeometry($1, $2, $3) LIMIT 1
  $query$ INTO boundary
  USING geom, boundary_id, time_span;

  RETURN boundary;

END;
$$ LANGUAGE plpgsql;

-- OBS_GetBoundaryId
--
-- retrieves the boundary identifier (e.g., '36047' = Kings County/Brooklyn, NY)
--   corresponding to the location geom and boundary types (e.g.,
--   us.census.tiger.county)

-- Inputs:
--   geom geometry: location where the boundary is requested to overlap with
--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
--                     see function OBS_ListGeomColumns for all avaiable
--                     boundary ids
--   time_span text: time span that the geometries were collected (optional)
--
-- Output:
--   geometry_id text: identifier of the geometry which overlaps with the input
--                     point geom in the table corresponding to boundary_id and
--                     time_span
--

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundaryId(
  geom geometry(Point, 4326),
  boundary_id text,
  time_span text DEFAULT NULL
)
RETURNS text
AS $$
DECLARE
  result TEXT;
BEGIN

  EXECUTE $query$
    SELECT geom_refs FROM cdb_observatory._OBS_GetBoundariesByGeometry(
      $1, $2, $3) LIMIT 1
  $query$
  INTO result
  USING geom, boundary_id, time_span;

  RETURN result;
END;
$$ LANGUAGE plpgsql;


-- OBS_GetBoundaryById
--
-- Given a geometry reference (e.g., geoid for US Census), and it's geometry
--  level (see OBS_ListGeomColumns() for all available boundary ids), give back
--  the boundary that corresponds to that geometry_id, boundary_id, and
--   time_span

-- Inputs:
--   geometry_id text: geometry id of the requested boundary
--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
--                     see function OBS_ListGeomColumns for all avaiable
--                     boundary ids
--   time_span text: time span that the geometries were collected (optional)
--
-- Output:
--   boundary geometry: geometry boundary that matches geometry_id, is at the
--                      resolution requested with boundary_id, and time_span
--

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundaryById(
  geometry_id text,            -- ex: '36047'
  boundary_id text,            -- ex: 'us.census.tiger.county'
  time_span text DEFAULT NULL  -- ex: '2009'
)
RETURNS geometry(geometry, 4326)
AS $$
DECLARE
  result GEOMETRY;
BEGIN

  EXECUTE $query$
    SELECT (data->0->>'value')::Geometry
    FROM cdb_observatory.OBS_GetData(
      ARRAY[$1],
      cdb_observatory.OBS_GetMeta(
        ST_MakeEnvelope(-180, -90, 180, 90, 4326),
        ('[{"geom_id": "' || $2 || '"}]')::JSON))
  $query$
  INTO result
  USING geometry_id, boundary_id;

  RETURN result;
END;
$$ LANGUAGE plpgsql;

-- _OBS_GetBoundariesByGeometry
-- internal function for retrieving geometries based on an input geometry
--  see OBS_GetBoundariesByGeometry or OBS_GetBoundariesByPointAndRadius for
--  more information

CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetBoundariesByGeometry(
  geom geometry(Geometry, 4326),
  boundary_id text,
  time_span text DEFAULT NULL,
  overlap_type text DEFAULT NULL)
RETURNS TABLE (
  the_geom geometry,
  geom_refs text
) AS $$
DECLARE
  meta JSON;
BEGIN
  overlap_type := COALESCE(overlap_type, 'intersects');
  -- check inputs
  IF lower(overlap_type) NOT IN ('contains', 'intersects', 'within')
  THEN
    -- recognized overlap type (map to ST_Contains, ST_Intersects, and ST_Within)
    RAISE EXCEPTION 'Overlap type ''%'' is not an accepted type (choose intersects, within, or contains)', overlap_type;
  END IF;

  EXECUTE $query$
    SELECT cdb_observatory.OBS_GetMeta($1, JSON_Build_Array(JSON_Build_Object(
                'geom_id', $2, 'geom_timespan', $3)))
  $query$
  INTO meta
  USING geom, boundary_id, time_span;

  IF meta->0->>'geom_id' IS NULL THEN
    RETURN QUERY EXECUTE 'SELECT NULL::Geometry, NULL::Text LIMIT 0';
    RETURN;
  END IF;

  -- return first boundary in intersections
  RETURN QUERY EXECUTE $query$
    SELECT (data->0->>'value')::Geometry the_geom, data->0->>'geomref' geom_refs
    FROM cdb_observatory.OBS_GetData(
      ARRAY[($1, 1)::geomval], $2, False
    )
  $query$ USING geom, meta;
  RETURN;

END;
$$ LANGUAGE plpgsql;

-- OBS_GetBoundariesByGeometry
--
-- Given a bounding box (or a polygon), and it's geometry level (see
--  OBS_ListGeomColumns() for all available boundary ids), give back the
--  boundaries that are contained within the bounding box polygon and the
--  associated geometry ids

-- Inputs:
--   geom geometry: bounding box (or polygon) of the region of interest
--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
--                     see function OBS_ListGeomColumns for all avaiable
--                     boundary ids
--   time_span text: time span that the geometries were collected (optional)
--
-- Output:
--   table with the following columns
--     boundary geometry: geometry boundary that is contained within the input
--                          bounding box at the requested geometry level
--                          with boundary_id, and time_span
--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
--

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundariesByGeometry(
  geom geometry(Geometry, 4326),
  boundary_id text,
  time_span text DEFAULT NULL,
  overlap_type text DEFAULT NULL)
RETURNS TABLE(the_geom geometry, geom_refs text)
AS $$
BEGIN

  RETURN QUERY SELECT *
               FROM cdb_observatory._OBS_GetBoundariesByGeometry(
                          geom,
                          boundary_id,
                          time_span,
                          overlap_type
                        );
  RETURN;

END;
$$ LANGUAGE plpgsql;

-- OBS_GetBoundariesByPointAndRadius
--
-- Given a point and radius, and it's geometry level (see
--  OBS_ListGeomColumns() for all available boundary ids), give back the
--  boundaries that are contained within the point buffered by radius meters and
--  the associated geometry ids

-- Inputs:
--   geom geometry: point geometry centered on area of interest
--   radius numeric: radius (in meters) of a circle centered on geom for
--                   selecting polygons
--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
--                     see function OBS_ListGeomColumns for all avaiable
--                     boundary ids
--   time_span text: time span that the geometries were collected (optional)
--
-- Output:
--   table with the following columns
--     boundary geometry: geometry boundary that is contained within the input
--                          bounding box at the requested geometry level
--                          with boundary_id, and time_span
--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
--
-- TODO: move to ST_DWithin instead of buffer + intersects?
CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundariesByPointAndRadius(
  geom geometry(Point, 4326), -- point
  radius numeric, -- radius in meters
  boundary_id text,
  time_span text DEFAULT NULL,
  overlap_type text DEFAULT NULL)
RETURNS TABLE(the_geom geometry, geom_refs text)
AS $$
DECLARE
  circle_boundary geometry(Geometry, 4326);
BEGIN

  IF ST_GeometryType(geom) != 'ST_Point'
  THEN
    RAISE EXCEPTION 'Input geometry ''%'' is not a point', ST_AsText(geom);
  ELSE
    circle_boundary := ST_Buffer(geom::geography, radius)::geometry;
  END IF;

  RETURN QUERY SELECT *
               FROM cdb_observatory._OBS_GetBoundariesByGeometry(
                        circle_boundary,
                        boundary_id,
                        time_span,
                        overlap_type);
  RETURN;
END;
$$ LANGUAGE plpgsql;

-- _OBS_GetPointsByGeometry


CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetPointsByGeometry(
  geom geometry(Geometry, 4326),
  boundary_id text,
  time_span text DEFAULT NULL,
  overlap_type text DEFAULT NULL)
RETURNS TABLE(the_geom geometry, geom_refs text)
AS $$
DECLARE
  boundary geometry(Geometry, 4326);
  geom_colname text;
  geoid_colname text;
  target_table text;
BEGIN
  overlap_type := COALESCE(overlap_type, 'intersects');

  IF lower(overlap_type) NOT IN ('contains', 'within', 'intersects')
  THEN
    RAISE EXCEPTION 'Overlap type ''%'' is not an accepted type (choose intersects, within, or contains)', overlap_type;
  ELSIF ST_GeometryType(geom) NOT IN ('ST_Polygon', 'ST_MultiPolygon')
  THEN
    RAISE EXCEPTION 'Invalid geometry type (%), expecting ''ST_MultiPolygon'' or ''ST_Polygon''', ST_GeometryType(geom);
  END IF;

  -- return first boundary in intersections
  RETURN QUERY EXECUTE $query$
    SELECT ST_PointOnSurface(the_geom), geom_refs
    FROM cdb_observatory._OBS_GetBoundariesByGeometry($1, $2)
  $query$ USING geom, boundary_id;
  RETURN;

END;
$$ LANGUAGE plpgsql;

-- OBS_GetPointsByGeometry
--
-- Given a polygon, and it's geometry level (see
--  OBS_ListGeomColumns() for all available boundary ids), give back a point
--  which lies in a boundary from the requested geometry level that is contained
--  within the bounding box polygon and the associated geometry ids
--
-- Inputs:
--   geom geometry: bounding box (or polygon) of the region of interest
--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
--                     see function OBS_ListGeomColumns for all avaiable
--                     boundary ids
--   time_span text: time span that the geometries were collected (optional)
--
-- Output:
--   table with the following columns
--     boundary geometry: point that lies on a boundary that is contained within
--                          the input bounding box at the requested geometry
--                          level with boundary_id, and time_span
--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
--

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetPointsByGeometry(
  geom geometry(Geometry, 4326),
  boundary_id text,
  time_span text DEFAULT NULL,
  overlap_type text DEFAULT NULL)
RETURNS TABLE(the_geom geometry, geom_refs text)
AS $$
BEGIN

  RETURN QUERY SELECT *
               FROM cdb_observatory._OBS_GetPointsByGeometry(
                      geom,
                      boundary_id,
                      time_span,
                      overlap_type);
  RETURN;

END;
$$ LANGUAGE plpgsql;

-- OBS_GetBoundariesByPointAndRadius
--
-- Given a point and radius, and it's geometry level (see
--  OBS_ListGeomColumns() for all available boundary ids), give back the
--  boundaries that are contained within the point buffered by radius meters and
--  the associated geometry ids

-- Inputs:
--   geom geometry: point geometry centered on area of interest
--   radius numeric: radius (in meters) of a circle centered on geom for
--                   selecting polygons
--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
--                     see function OBS_ListGeomColumns for all avaiable
--                     boundary ids
--   time_span text: time span that the geometries were collected (optional)
--
-- Output:
--   table with the following columns
--     boundary geometry: geometry boundary that is contained within the input
--                          bounding box at the requested geometry level
--                          with boundary_id, and time_span
--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
--

CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetPointsByPointAndRadius(
  geom geometry(Point, 4326), -- point
  radius numeric, -- radius in meters
  boundary_id text,
  time_span text DEFAULT NULL,
  overlap_type text DEFAULT NULL)
RETURNS TABLE(the_geom geometry, geom_refs text)
AS $$
DECLARE
  circle_boundary geometry(Geometry, 4326);
BEGIN

  IF ST_GeometryType(geom) != 'ST_Point'
  THEN
    RAISE EXCEPTION 'Input geometry ''%'' is not a point', ST_AsText(geom);
  ELSE
    circle_boundary := ST_Buffer(geom::geography, radius)::geometry;
  END IF;

  RETURN QUERY SELECT *
               FROM cdb_observatory._OBS_GetPointsByGeometry(
                        ST_Buffer(geom::geography, radius)::geometry,
                        boundary_id,
                        time_span,
                        overlap_type);
  RETURN;
END;
$$ LANGUAGE plpgsql;
-- Placeholder for permission tweaks at creation time.
-- Make sure by default there are no permissions for publicuser
-- NOTE: this happens at extension creation time, as part of an implicit transaction.
-- REVOKE ALL PRIVILEGES ON SCHEMA cdb_observatory FROM PUBLIC, publicuser CASCADE;

-- Grant permissions on the schema to publicuser (but just the schema)
-- GRANT USAGE ON SCHEMA cdb_crankshaft TO publicuser;

-- Revoke execute permissions on all functions in the schema by default
-- REVOKE EXECUTE ON ALL FUNCTIONS IN SCHEMA cdb_observatory FROM PUBLIC, publicuser;