Christian Danielsen chribsen

I hereby claim:

To claim this, I am signing this object:

I hereby claim:

To claim this, I am signing this object:

	CREATE OR REPLACE FUNCTION getIndices(_table_name varchar)
	RETURNS TABLE(table_name varchar, index_name varchar, column_name varchar) AS $$
	BEGIN
	RETURN QUERY
	select
	t.relname::varchar as table_name,
	i.relname::varchar as index_name,
	a.attname::varchar as column_name
	from
	pg_class t,

	<?xml version="1.0" encoding="UTF-8"?>
	<kml xmlns="http://www.opengis.net/kml/2.2" xmlns:gx="http://www.google.com/kml/ext/2.2" xmlns:kml="http://www.opengis.net/kml/2.2" xmlns:atom="http://www.w3.org/2005/Atom">
	<Document>
	<name>Area Calculator</name>
	<description>2814731.04 m² \| 2.81 km² \| 695.54 acres \| 281.47 hectares \| 30297512.88 feet² \|1.09 square miles \| 0.82 square nautical miles</description>
	<gx:balloonVisibility>1</gx:balloonVisibility>
	<StyleMap id="msn_ylw-pushpin">
	<Pair>
	<key>normal</key>
	<styleUrl>#sn_ylw-pushpin</styleUrl>

	select ST_MAKELINE(ARRAY[St_Setsrid(st_centroid(dc1.geom),4326), st_setsrid(st_centroid(dc2.geom),4326)]), dc1.name_2 as source,dc2.name_2 as target, (sum(dd.is_friend_ratio)/(dc1.rf_population+dc2.rf_population)::float) as weight, count(*) as cou
	into presentation_city_connections
	from derived_dyads dd
	inner join user_residence ur1 on dd.user_a=ur1.user_id
	inner join dk_cities dc1 on dc1.gid=ur1.city_id
	inner join user_residence ur2 on dd.user_b=ur2.user_id
	inner join dk_cities dc2 on dc2.gid=ur2.city_id
	where dc1.name_2!=dc2.name_2
	group by dc1.name_2,dc2.name_2,dc1.rf_population, dc2.rf_population,dc1.geom, dc2.geom;

	import psycopg2
	import requests
	import time

	conn_dtu = psycopg2.connect("<connection_string>")
	cur_dtu = conn_dtu.cursor()

	cur_dtu.execute("select artist_name from data_lineup where spotify_id is null")

	search_url = 'https://api.spotify.com/v1/search'

	-- The size Roskilde Festival in Square Kilometers
	-- The points used are taken from the max points received in the dataset from IBM / CBS dataset.
	SELECT (st_distance_sphere(st_makepoint(12.106277, 55.627567), st_makepoint(12.058901,55.627567) ) /1000) *
	(st_distance_sphere(st_makepoint(12.058901,55.627567), st_makepoint(12.058901, 55.609975) )/1000)

	update derived_friend_features set same_genre_score=FALSE;
	update derived_friend_features AS fr set same_genre_score = TRUE
	where (select itunes_genre FROM tmp_user_genre WHERE user_id = fr.user_a limit 1) = (select itunes_genre FROM tmp_user_genre WHERE user_id = fr.user_b limit 1)

	-- Creates the feature same camp score by looking in the table tmp_user_camp, that consists of the most frequent visited camp site.
	update derived_friend_features set same_camp_score=FALSE;
	update derived_friend_features AS fr set same_camp_score = TRUE
	where (select title FROM tmp_user_camp WHERE user_id = fr.user_a limit 1) = (select title FROM tmp_user_camp WHERE user_id = fr.user_b limit 1)
	;

	import psycopg2
	from scipy.spatial.distance import jaccard

	conn_dtu = psycopg2.connect(<connstring>)
	cur_dtu = conn_dtu.cursor()

	# Retrieve places visited for each user in the user pair and aggregate them into an array.
	cur_dtu.execute("""
	select count(*) FROM (select user_a, ( SELECT array_agg(place_id) FROM derived_places_visited WHERE user_id=dff.user_a) as places_a,
	user_b, ( SELECT array_agg(place_id) FROM derived_places_visited WHERE user_id=dff.user_b) as places_b from derived_friend_features as dff