crankshaft/pg/test/0.0.1/expected/02_moran_test.out
2016-02-18 16:10:34 +01:00

261 lines
17 KiB
Plaintext

\i test/fixtures/ppoints.sql
-- test table (spanish province centroids with some invented values)
CREATE TABLE ppoints (cartodb_id integer, the_geom geometry, the_geom_webmercator geometry, code text, region_code text, value float);
INSERT INTO ppoints VALUES
( 1,'0101000020E6100000A8306DC0CBC305C051D14B6CE56A4540'::geometry,ST_Transform('0101000020E6100000A8306DC0CBC305C051D14B6CE56A4540'::geometry, 3857),'01','16',0.5),
( 4,'0101000020E6100000E220A4362DC202C0FD8AFA5119994240'::geometry,ST_Transform('0101000020E6100000E220A4362DC202C0FD8AFA5119994240'::geometry, 3857),'04','01',0.1),
( 5,'0101000020E610000004377E573AC813C0CB5871BB17494440'::geometry,ST_Transform('0101000020E610000004377E573AC813C0CB5871BB17494440'::geometry, 3857),'05','07',0.3),
( 2,'0101000020E610000000F49BE19BAFFFBF639958FDA6694340'::geometry,ST_Transform('0101000020E610000000F49BE19BAFFFBF639958FDA6694340'::geometry, 3857),'02','08',0.7),
( 3,'0101000020E61000005D0B7E63C832E2BFDB63EB00443D4340'::geometry,ST_Transform('0101000020E61000005D0B7E63C832E2BFDB63EB00443D4340'::geometry, 3857),'03','10',0.2),
( 6,'0101000020E61000006F3742B7FB9018C0DD967DC4D95A4340'::geometry,ST_Transform('0101000020E61000006F3742B7FB9018C0DD967DC4D95A4340'::geometry, 3857),'06','11',0.05),
( 7,'0101000020E6100000E4BB36995F4C0740EAC0E5CA9FC94340'::geometry,ST_Transform('0101000020E6100000E4BB36995F4C0740EAC0E5CA9FC94340'::geometry, 3857),'07','04',0.4),
( 8,'0101000020E61000003D43CC6CAFBEFF3F6B52E66F91DD4440'::geometry,ST_Transform('0101000020E61000003D43CC6CAFBEFF3F6B52E66F91DD4440'::geometry, 3857),'08','09',0.7),
( 9,'0101000020E61000003CC797BD99AF0CC0495A87FA312F4540'::geometry,ST_Transform('0101000020E61000003CC797BD99AF0CC0495A87FA312F4540'::geometry, 3857),'09','07',0.5),
(13,'0101000020E61000001CAA00A9F19F0EC05DF9267B7A764340'::geometry,ST_Transform('0101000020E61000001CAA00A9F19F0EC05DF9267B7A764340'::geometry, 3857),'13','08',0.4),
(16,'0101000020E6100000D8208F3CBC9001C065638DC1B1F24340'::geometry,ST_Transform('0101000020E6100000D8208F3CBC9001C065638DC1B1F24340'::geometry, 3857),'16','08',0.4),
(17,'0101000020E6100000E9E6A94A71630540AD7A0CB062104540'::geometry,ST_Transform('0101000020E6100000E9E6A94A71630540AD7A0CB062104540'::geometry, 3857),'17','09',0.6),
(18,'0101000020E6100000719792D59E240AC098AC548E00A84240'::geometry,ST_Transform('0101000020E6100000719792D59E240AC098AC548E00A84240'::geometry, 3857),'18','01',0.3),
(19,'0101000020E6100000972C878B50FD04C0123C881D1F684440'::geometry,ST_Transform('0101000020E6100000972C878B50FD04C0123C881D1F684440'::geometry, 3857),'19','08',0.7),
(21,'0101000020E6100000F7893E9934511BC0EAA4BF03E1C94240'::geometry,ST_Transform('0101000020E6100000F7893E9934511BC0EAA4BF03E1C94240'::geometry, 3857),'21','01',0.1),
(22,'0101000020E6100000572C2123B2A8B2BF7ED7FABAFD194540'::geometry,ST_Transform('0101000020E6100000572C2123B2A8B2BF7ED7FABAFD194540'::geometry, 3857),'22','02',0.4),
(25,'0101000020E6100000461B67D688C4F03FD990EEC3A0054540'::geometry,ST_Transform('0101000020E6100000461B67D688C4F03FD990EEC3A0054540'::geometry, 3857),'25','09',0.4),
(26,'0101000020E6100000A139FB06E82204C0539D84F62E234540'::geometry,ST_Transform('0101000020E6100000A139FB06E82204C0539D84F62E234540'::geometry, 3857),'26','17',0.6),
(27,'0101000020E6100000A92E54E618C91DC00D3A947B81814540'::geometry,ST_Transform('0101000020E6100000A92E54E618C91DC00D3A947B81814540'::geometry, 3857),'27','12',0.3),
(28,'0101000020E6100000971DC8B682BC0DC016D0E8055F3F4440'::geometry,ST_Transform('0101000020E6100000971DC8B682BC0DC016D0E8055F3F4440'::geometry, 3857),'28','13',0.8),
(30,'0101000020E6100000A2DC1964A8C5F7BF19299C994D004340'::geometry,ST_Transform('0101000020E6100000A2DC1964A8C5F7BF19299C994D004340'::geometry, 3857),'30','14',0.1),
(31,'0101000020E6100000DCA1FCC87B56FABF9B88E9D866554540'::geometry,ST_Transform('0101000020E6100000DCA1FCC87B56FABF9B88E9D866554540'::geometry, 3857),'31','15',0.9),
(32,'0101000020E6100000E1517AFCD15E1EC0A18D8D4825194540'::geometry,ST_Transform('0101000020E6100000E1517AFCD15E1EC0A18D8D4825194540'::geometry, 3857),'32','12',0.3),
(33,'0101000020E6100000A7FF33825AF917C0FABE7DFB6BA54540'::geometry,ST_Transform('0101000020E6100000A7FF33825AF917C0FABE7DFB6BA54540'::geometry, 3857),'33','03',0.4),
(34,'0101000020E6100000FB4E4EBEB72412C0898E7240982F4540'::geometry,ST_Transform('0101000020E6100000FB4E4EBEB72412C0898E7240982F4540'::geometry, 3857),'34','07',0.3),
(35,'0101000020E6100000224682B01B1A2DC011091656CC5C3C40'::geometry,ST_Transform('0101000020E6100000224682B01B1A2DC011091656CC5C3C40'::geometry, 3857),'35','05',0.3),
(36,'0101000020E6100000F7C9447110EC20C04C5D4823C7374540'::geometry,ST_Transform('0101000020E6100000F7C9447110EC20C04C5D4823C7374540'::geometry, 3857),'36','12',0.2),
(37,'0101000020E610000053D6A26DFB4218C09D58FAE209674440'::geometry,ST_Transform('0101000020E610000053D6A26DFB4218C09D58FAE209674440'::geometry, 3857),'37','07',0.5),
(38,'0101000020E6100000B1D1B5FC910431C03C0C89BA03503C40'::geometry,ST_Transform('0101000020E6100000B1D1B5FC910431C03C0C89BA03503C40'::geometry, 3857),'38','05',0.4),
(39,'0101000020E610000086E6FEE1BD1E10C00417096748994540'::geometry,ST_Transform('0101000020E610000086E6FEE1BD1E10C00417096748994540'::geometry, 3857),'39','06',0.6),
(40,'0101000020E6100000FB51C33F733710C038D01729E4954440'::geometry,ST_Transform('0101000020E6100000FB51C33F733710C038D01729E4954440'::geometry, 3857),'40','07',0.5),
(41,'0101000020E6100000912D6FDA28BB16C031321F08C4B74240'::geometry,ST_Transform('0101000020E6100000912D6FDA28BB16C031321F08C4B74240'::geometry, 3857),'41','01',0.4),
(42,'0101000020E6100000554432EABEB504C069ECD78775CF4440'::geometry,ST_Transform('0101000020E6100000554432EABEB504C069ECD78775CF4440'::geometry, 3857),'42','07',0.2),
(43,'0101000020E6100000157F117C1A2EEA3F027CD1F2368B4440'::geometry,ST_Transform('0101000020E6100000157F117C1A2EEA3F027CD1F2368B4440'::geometry, 3857),'43','09',0.3),
(44,'0101000020E610000051AA5B1BD718EABFEE67613BA4544440'::geometry,ST_Transform('0101000020E610000051AA5B1BD718EABFEE67613BA4544440'::geometry, 3857),'44','02',0.2),
(45,'0101000020E610000022C5C01BB69710C08563BC1499E54340'::geometry,ST_Transform('0101000020E610000022C5C01BB69710C08563BC1499E54340'::geometry, 3857),'45','08',0.3),
(46,'0101000020E6100000D5FCF78A11A0E9BFDEA46F8E64AF4340'::geometry,ST_Transform('0101000020E6100000D5FCF78A11A0E9BFDEA46F8E64AF4340'::geometry, 3857),'46','10',0.2),
(47,'0101000020E61000003AE63525866313C02100050B2BD14440'::geometry,ST_Transform('0101000020E61000003AE63525866313C02100050B2BD14440'::geometry, 3857),'47','07',0.3),
(48,'0101000020E610000030F187FD1FD206C0C767E1496C9E4540'::geometry,ST_Transform('0101000020E610000030F187FD1FD206C0C767E1496C9E4540'::geometry, 3857),'48','16',0.5),
(49,'0101000020E61000009C22867B12EC17C006C5F40C14DD4440'::geometry,ST_Transform('0101000020E61000009C22867B12EC17C006C5F40C14DD4440'::geometry, 3857),'49','07',0.2),
(50,'0101000020E6100000F7D5EFC62D08F1BF69D1231D68CF4440'::geometry,ST_Transform('0101000020E6100000F7D5EFC62D08F1BF69D1231D68CF4440'::geometry, 3857),'50','02',0.6),
(51,'0101000020E61000005B0E1F8DAA5F15C0530BFE285BF24140'::geometry,ST_Transform('0101000020E61000005B0E1F8DAA5F15C0530BFE285BF24140'::geometry, 3857),'51','18',0.01),
(10,'0101000020E61000000FD65D82AEA418C06192D1351FDB4340'::geometry,ST_Transform('0101000020E61000000FD65D82AEA418C06192D1351FDB4340'::geometry, 3857),'10','11',0.04),
(11,'0101000020E6100000B305531DAB0A17C0DEAFCD4EE5464240'::geometry,ST_Transform('0101000020E6100000B305531DAB0A17C0DEAFCD4EE5464240'::geometry, 3857),'11','01',0.08),
(12,'0101000020E610000059721A7297C9C2BF9EBE383BE51E4440'::geometry,ST_Transform('0101000020E610000059721A7297C9C2BF9EBE383BE51E4440'::geometry, 3857),'12','10',0.2),
(14,'0101000020E610000000C86313AF3C13C0E530879C10FF4240'::geometry,ST_Transform('0101000020E610000000C86313AF3C13C0E530879C10FF4240'::geometry, 3857),'14','01',0.2),
(15,'0101000020E61000002A475497B6ED20C06643D4131A904540'::geometry,ST_Transform('0101000020E61000002A475497B6ED20C06643D4131A904540'::geometry, 3857),'15','12',0.3),
(20,'0101000020E6100000F975566FAD8D01C0E840C33F67924540'::geometry,ST_Transform('0101000020E6100000F975566FAD8D01C0E840C33F67924540'::geometry, 3857),'20','16',0.8),
(23,'0101000020E610000025FA13E595880BC022BB07131D024340'::geometry,ST_Transform('0101000020E610000025FA13E595880BC022BB07131D024340'::geometry, 3857),'23','01',0.1),
(24,'0101000020E61000009C5F91C5095C17C0C78784B15A4F4540'::geometry,ST_Transform('0101000020E61000009C5F91C5095C17C0C78784B15A4F4540'::geometry, 3857),'24','07',0.3),
(29,'0101000020E6100000C34D4A5B48E712C092E680892C684240'::geometry,ST_Transform('0101000020E6100000C34D4A5B48E712C092E680892C684240'::geometry, 3857),'29','01',0.3),
(52,'0101000020E6100000406A545EB29A07C04E5F0BDA39A54140'::geometry,ST_Transform('0101000020E6100000406A545EB29A07C04E5F0BDA39A54140'::geometry, 3857),'52','19',0.01)
\i test/fixtures/ppoints2.sql
-- test table (spanish province centroids with some invented values)
CREATE TABLE ppoints2 (cartodb_id integer, the_geom geometry, code text, region_code text, numerator float, denominator float);
INSERT INTO ppoints2 VALUES
( 1,'0101000020E6100000A8306DC0CBC305C051D14B6CE56A4540'::geometry,'01','16',0.5, 1.0),
( 4,'0101000020E6100000E220A4362DC202C0FD8AFA5119994240'::geometry,'04','01',0.1, 1.0),
( 5,'0101000020E610000004377E573AC813C0CB5871BB17494440'::geometry,'05','07',0.3, 1.0),
( 2,'0101000020E610000000F49BE19BAFFFBF639958FDA6694340'::geometry,'02','08',0.7, 1.0),
( 3,'0101000020E61000005D0B7E63C832E2BFDB63EB00443D4340'::geometry,'03','10',0.2, 1.0),
( 6,'0101000020E61000006F3742B7FB9018C0DD967DC4D95A4340'::geometry,'06','11',0.05, 1.0),
( 7,'0101000020E6100000E4BB36995F4C0740EAC0E5CA9FC94340'::geometry,'07','04',0.4, 1.0),
( 8,'0101000020E61000003D43CC6CAFBEFF3F6B52E66F91DD4440'::geometry,'08','09',0.7, 1.0),
( 9,'0101000020E61000003CC797BD99AF0CC0495A87FA312F4540'::geometry,'09','07',0.5, 1.0),
(13,'0101000020E61000001CAA00A9F19F0EC05DF9267B7A764340'::geometry,'13','08',0.4, 1.0),
(16,'0101000020E6100000D8208F3CBC9001C065638DC1B1F24340'::geometry,'16','08',0.4, 1.0),
(17,'0101000020E6100000E9E6A94A71630540AD7A0CB062104540'::geometry,'17','09',0.6, 1.0),
(18,'0101000020E6100000719792D59E240AC098AC548E00A84240'::geometry,'18','01',0.3, 1.0),
(19,'0101000020E6100000972C878B50FD04C0123C881D1F684440'::geometry,'19','08',0.7, 1.0),
(21,'0101000020E6100000F7893E9934511BC0EAA4BF03E1C94240'::geometry,'21','01',0.1, 1.0),
(22,'0101000020E6100000572C2123B2A8B2BF7ED7FABAFD194540'::geometry,'22','02',0.4, 1.0),
(25,'0101000020E6100000461B67D688C4F03FD990EEC3A0054540'::geometry,'25','09',0.4, 1.0),
(26,'0101000020E6100000A139FB06E82204C0539D84F62E234540'::geometry,'26','17',0.6, 1.0),
(27,'0101000020E6100000A92E54E618C91DC00D3A947B81814540'::geometry,'27','12',0.3, 1.0),
(28,'0101000020E6100000971DC8B682BC0DC016D0E8055F3F4440'::geometry,'28','13',0.8, 1.0),
(30,'0101000020E6100000A2DC1964A8C5F7BF19299C994D004340'::geometry,'30','14',0.1, 1.0),
(31,'0101000020E6100000DCA1FCC87B56FABF9B88E9D866554540'::geometry,'31','15',0.9, 1.0),
(32,'0101000020E6100000E1517AFCD15E1EC0A18D8D4825194540'::geometry,'32','12',0.3, 1.0),
(33,'0101000020E6100000A7FF33825AF917C0FABE7DFB6BA54540'::geometry,'33','03',0.4, 1.0),
(34,'0101000020E6100000FB4E4EBEB72412C0898E7240982F4540'::geometry,'34','07',0.3, 1.0),
(35,'0101000020E6100000224682B01B1A2DC011091656CC5C3C40'::geometry,'35','05',0.3, 1.0),
(36,'0101000020E6100000F7C9447110EC20C04C5D4823C7374540'::geometry,'36','12',0.2, 1.0),
(37,'0101000020E610000053D6A26DFB4218C09D58FAE209674440'::geometry,'37','07',0.5, 1.0),
(38,'0101000020E6100000B1D1B5FC910431C03C0C89BA03503C40'::geometry,'38','05',0.4, 1.0),
(39,'0101000020E610000086E6FEE1BD1E10C00417096748994540'::geometry,'39','06',0.6, 1.0),
(40,'0101000020E6100000FB51C33F733710C038D01729E4954440'::geometry,'40','07',0.5, 1.0),
(41,'0101000020E6100000912D6FDA28BB16C031321F08C4B74240'::geometry,'41','01',0.4, 1.0),
(42,'0101000020E6100000554432EABEB504C069ECD78775CF4440'::geometry,'42','07',0.2, 1.0),
(43,'0101000020E6100000157F117C1A2EEA3F027CD1F2368B4440'::geometry,'43','09',0.3, 1.0),
(44,'0101000020E610000051AA5B1BD718EABFEE67613BA4544440'::geometry,'44','02',0.2, 1.0),
(45,'0101000020E610000022C5C01BB69710C08563BC1499E54340'::geometry,'45','08',0.3, 1.0),
(46,'0101000020E6100000D5FCF78A11A0E9BFDEA46F8E64AF4340'::geometry,'46','10',0.2, 1.0),
(47,'0101000020E61000003AE63525866313C02100050B2BD14440'::geometry,'47','07',0.3, 1.0),
(48,'0101000020E610000030F187FD1FD206C0C767E1496C9E4540'::geometry,'48','16',0.5, 1.0),
(49,'0101000020E61000009C22867B12EC17C006C5F40C14DD4440'::geometry,'49','07',0.2, 1.0),
(50,'0101000020E6100000F7D5EFC62D08F1BF69D1231D68CF4440'::geometry,'50','02',0.6, 1.0),
(51,'0101000020E61000005B0E1F8DAA5F15C0530BFE285BF24140'::geometry,'51','18',0.01, 1.0),
(10,'0101000020E61000000FD65D82AEA418C06192D1351FDB4340'::geometry,'10','11',0.04, 1.0),
(11,'0101000020E6100000B305531DAB0A17C0DEAFCD4EE5464240'::geometry,'11','01',0.08, 1.0),
(12,'0101000020E610000059721A7297C9C2BF9EBE383BE51E4440'::geometry,'12','10',0.2, 1.0),
(14,'0101000020E610000000C86313AF3C13C0E530879C10FF4240'::geometry,'14','01',0.2, 1.0),
(15,'0101000020E61000002A475497B6ED20C06643D4131A904540'::geometry,'15','12',0.3, 1.0),
(20,'0101000020E6100000F975566FAD8D01C0E840C33F67924540'::geometry,'20','16',0.8, 1.0),
(23,'0101000020E610000025FA13E595880BC022BB07131D024340'::geometry,'23','01',0.1, 1.0),
(24,'0101000020E61000009C5F91C5095C17C0C78784B15A4F4540'::geometry,'24','07',0.3, 1.0),
(29,'0101000020E6100000C34D4A5B48E712C092E680892C684240'::geometry,'29','01',0.3, 1.0),
(52,'0101000020E6100000406A545EB29A07C04E5F0BDA39A54140'::geometry,'52','19',0.0, 1.01)
-- Moral functions perform some nondeterministic computations
-- (to estimate the significance); we will set the seeds for the RNGs
-- that affect those results to have repeateble results
SELECT cdb_crankshaft._cdb_random_seeds(1234);
_cdb_random_seeds
-------------------
(1 row)
SELECT ppoints.code, m.quads
FROM ppoints
JOIN cdb_crankshaft.cdb_moran_local('ppoints', 'value') m
ON ppoints.cartodb_id = m.ids
ORDER BY ppoints.code;
NOTICE: ** Constructing query
CONTEXT: PL/Python function "cdb_moran_local"
NOTICE: ** Query returned with 52 rows
CONTEXT: PL/Python function "cdb_moran_local"
NOTICE: ** Finished calculations
CONTEXT: PL/Python function "cdb_moran_local"
code | quads
------+-----------------
01 | HH
02 | HL
03 | Not significant
04 | Not significant
05 | Not significant
06 | Not significant
07 | Not significant
08 | Not significant
09 | Not significant
10 | Not significant
11 | LL
12 | Not significant
13 | Not significant
14 | Not significant
15 | Not significant
16 | HH
17 | Not significant
18 | Not significant
19 | Not significant
20 | HH
21 | LL
22 | Not significant
23 | Not significant
24 | Not significant
25 | HH
26 | HH
27 | Not significant
28 | Not significant
29 | LL
30 | Not significant
31 | HH
32 | Not significant
33 | Not significant
34 | Not significant
35 | LL
36 | Not significant
37 | Not significant
38 | HL
39 | Not significant
40 | Not significant
41 | HL
42 | LH
43 | Not significant
44 | Not significant
45 | LH
46 | Not significant
47 | Not significant
48 | HH
49 | Not significant
50 | Not significant
51 | LL
52 | LL
(52 rows)
SELECT cdb_crankshaft._cdb_random_seeds(1234);
_cdb_random_seeds
-------------------
(1 row)
SELECT ppoints2.code, m.quads
FROM ppoints2
JOIN cdb_crankshaft.cdb_moran_local_rate('ppoints2', 'numerator', 'denominator') m
ON ppoints2.cartodb_id = m.ids
ORDER BY ppoints2.code;
NOTICE: ** Constructing query
CONTEXT: PL/Python function "cdb_moran_local_rate"
NOTICE: ** Query returned with 51 rows
CONTEXT: PL/Python function "cdb_moran_local_rate"
NOTICE: ** Finished calculations
CONTEXT: PL/Python function "cdb_moran_local_rate"
code | quads
------+-----------------
01 | LL
02 | Not significant
03 | Not significant
04 | Not significant
05 | Not significant
06 | Not significant
07 | Not significant
08 | Not significant
09 | LL
10 | Not significant
11 | HH
12 | Not significant
13 | Not significant
14 | Not significant
15 | Not significant
16 | Not significant
17 | LL
18 | Not significant
19 | Not significant
20 | LL
21 | Not significant
22 | Not significant
23 | Not significant
24 | Not significant
25 | LL
26 | LL
27 | Not significant
28 | Not significant
29 | LH
30 | Not significant
31 | LL
32 | Not significant
33 | Not significant
34 | Not significant
35 | LH
36 | Not significant
37 | Not significant
38 | LH
39 | Not significant
40 | Not significant
41 | LH
42 | HL
43 | Not significant
44 | Not significant
45 | LL
46 | Not significant
47 | Not significant
48 | LL
49 | Not significant
50 | Not significant
51 | Not significant
(51 rows)