This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
0 info it worked if it ends with ok | |
1 verbose cli [ '/usr/bin/node', '/usr/bin/npm', 'install' ] | |
2 info using [email protected] | |
3 info using [email protected] | |
4 verbose node symlink /usr/bin/node | |
5 verbose readDependencies loading dependencies from /opt/package.json | |
6 warn package.json [email protected] No README data | |
7 verbose install where, deps [ '/opt', [ 'express' ] ] | |
8 verbose install where, peers [ '/opt', [] ] | |
9 verbose installManyTop reading for lifecycle /opt/package.json |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
.../database$ psql -d olaf_yr2_paper -f create_crowdflower_init_csv.sql | |
psql:create_crowdflower_init_csv.sql:5: \copy: arguments required | |
psql:create_crowdflower_init_csv.sql:14: ERROR: syntax error at or near "TO" | |
LINE 5: TO '/Users/giacecco/Documents/PhD/GitHub projects/OLAF-yr2... | |
^ | |
.../database$ |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
SELECT lr_town, ST_Union(mbr) AS geom | |
FROM os_open_names_with_towns | |
WHERE type = 'transportNetwork' AND lr_town = 'SOUTHAMPTON' | |
GROUP BY lr_town |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
DROP VIEW IF EXISTS os_open_names_with_towns; | |
CREATE VIEW os_open_names_with_towns AS | |
SELECT a.*, b.town AS lr_town | |
FROM | |
(SELECT * FROM os_open_names WHERE type = 'transportNetwork') AS a, | |
(SELECT town, bounding_box FROM lr_pp_town_definition) AS b | |
WHERE ST_Contains(b.bounding_box, a.mbr) | |
UNION | |
SELECT *, NULL AS lr_town FROM os_open_names WHERE type != 'transportNetwork'; |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
DROP VIEW IF EXISTS lr_pp_town_definition; | |
CREATE VIEW lr_pp_town_definition AS | |
SELECT a.town, ST_MakeEnvelope(MIN(ST_X(b.geom)), MIN(ST_Y(b.geom)), MAX(ST_X(b.geom)), MAX(ST_Y(b.geom)), 4326) AS bounding_box | |
FROM | |
(SELECT DISTINCT town, pcd FROM lr_pp) AS a | |
LEFT JOIN | |
(SELECT pcd, geom FROM ons_pd WHERE doterm IS NULL) AS b | |
ON a.pcd = b.pcd | |
GROUP BY town; |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
[ | |
{ | |
"location" : { | |
"lat" : 50.936847, | |
"lon" : -1.3963189999999486 | |
}, | |
"panoramaId" : "MpgI98E7NEuIe0P0Ypi9-Q", | |
"pov" : { | |
"heading" : 120.97, | |
"pitch" : 13.3, |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# a few useful functions... | |
is.even <- function(x) sum(x %% 2 == 0) == length(x) | |
is.odd <- function(x) sum(x %% 2 != 0) == length(x) | |
# and finally, the calculation | |
can_be_inferred <- sum(apply(lrpp_streets_for_inference, 1, function (row) { | |
aons <- lrpp_addresses_with_numeric_aon[(lrpp_addresses_with_numeric_aon$street == row[1]) & (lrpp_addresses_with_numeric_aon$pcd == row[2]), "aon"] | |
# if all numbers I know are odd or even, I can only infer the missing odd and even numbers, | |
# otherwise I can infer all | |
# TODO: crazy below: why row[3] and row[4] are not numeric any longer? |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# find how many opportunities for applying the inference algorithm are available, and min and max | |
# aon per street | |
lrpp_streets_for_inference <- lrpp_addresses_with_numeric_aon %>% group_by(street, pcd) %>% summarise(minAon = min(aon), maxAon = max(aon), how_many = n()) %>% filter(how_many > 1) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# read from LRPP all addresses whose street names are not NULL and PAON or SAON are numeric; if both | |
# are, take the PAON only the DISTINCT below is important, otherwise down this script the AONs of | |
# properties that have been sold many times will weight more than the others | |
# (we did something similar to this already for | |
# http://sociam-olaf.tumblr.com/post/124663267575/how-many-addresses-in-one-town ) | |
lrpp_addresses_with_numeric_aon <- collect(tbl(src_postgres("olaf"), sql(paste0("SELECT DISTINCT street, aon, pcd FROM ((SELECT street, CAST(SUBSTRING(paon, '^([0-9]+)') AS NUMERIC) AS aon, pcd FROM lr_pp WHERE town = '", target_town, "' AND street IS NOT NULL AND paon ~ '^[0-9]+') UNION (SELECT street, CAST(SUBSTRING(saon, '^([0-9]+)') AS NUMERIC) AS aon, pcd FROM lr_pp WHERE town = '", target_town, "' AND street IS NOT NULL AND paon !~ '^[0-9]+' AND saon ~ '^[0-9]+')) AS a", collapse = "")))) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# calculate the number of unique properties in the target town recorded in LRPP | |
lrpp_addresses_no <- collect(tbl(src_postgres("olaf"), sql(paste0("SELECT COUNT(*) AS no_of_addresses FROM (SELECT DISTINCT paon, saon, street FROM lr_pp WHERE town = '", target_town , "') AS a", collapse = ""))))$no_of_addresses |
NewerOlder