mirror of
https://github.com/CartoDB/crankshaft.git
synced 2024-11-01 10:20:48 +08:00
Add upgrade and downgrade files for 0.1.0
This commit is contained in:
Rafa de la Torre
parent
78ceb02c22
commit
3d99d1f9bf
258
release/crankshaft--0.0.4--0.1.0.sql
Normal file
258
release/crankshaft--0.0.4--0.1.0.sql
Normal file
@ -0,0 +1,258 @@
|
||||
--DO NOT MODIFY THIS FILE, IT IS GENERATED FROM SOURCES
|
||||
|
||||
-- Complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "CREATE EXTENSION crankshaft" to load this file. \quit
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Version number of the extension release
|
||||
CREATE OR REPLACE FUNCTION cdb_crankshaft_version()
|
||||
RETURNS text AS $$
|
||||
SELECT '0.1.0'::text;
|
||||
$$ language 'sql' STABLE STRICT;
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- PyAgg stuff
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_PyAggS(current_state Numeric[], current_row Numeric[])
|
||||
returns NUMERIC[] as $$
|
||||
BEGIN
|
||||
if array_upper(current_state,1) is null then
|
||||
RAISE NOTICE 'setting state %',array_upper(current_row,1);
|
||||
current_state[1] = array_upper(current_row,1);
|
||||
end if;
|
||||
return array_cat(current_state,current_row) ;
|
||||
END
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
|
||||
CREATE AGGREGATE CDB_PyAgg(NUMERIC[])(
|
||||
SFUNC = CDB_PyAggS,
|
||||
STYPE = Numeric[],
|
||||
INITCOND = "{}"
|
||||
);
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Segmentation stuff
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_CreateAndPredictSegment(
|
||||
target NUMERIC[],
|
||||
features NUMERIC[],
|
||||
target_features NUMERIC[],
|
||||
target_ids NUMERIC[],
|
||||
n_estimators INTEGER DEFAULT 1200,
|
||||
max_depth INTEGER DEFAULT 3,
|
||||
subsample DOUBLE PRECISION DEFAULT 0.5,
|
||||
learning_rate DOUBLE PRECISION DEFAULT 0.01,
|
||||
min_samples_leaf INTEGER DEFAULT 1)
|
||||
RETURNS TABLE(cartodb_id NUMERIC, prediction NUMERIC, accuracy NUMERIC)
|
||||
AS $$
|
||||
import numpy as np
|
||||
import plpy
|
||||
|
||||
from crankshaft.segmentation import create_and_predict_segment_agg
|
||||
model_params = {'n_estimators': n_estimators,
|
||||
'max_depth': max_depth,
|
||||
'subsample': subsample,
|
||||
'learning_rate': learning_rate,
|
||||
'min_samples_leaf': min_samples_leaf}
|
||||
|
||||
def unpack2D(data):
|
||||
dimension = data.pop(0)
|
||||
a = np.array(data, dtype=float)
|
||||
return a.reshape(len(a)/dimension, dimension)
|
||||
|
||||
return create_and_predict_segment_agg(np.array(target, dtype=float),
|
||||
unpack2D(features),
|
||||
unpack2D(target_features),
|
||||
target_ids,
|
||||
model_params)
|
||||
|
||||
$$ LANGUAGE plpythonu;
|
||||
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_CreateAndPredictSegment (
|
||||
query TEXT,
|
||||
variable_name TEXT,
|
||||
target_table TEXT,
|
||||
n_estimators INTEGER DEFAULT 1200,
|
||||
max_depth INTEGER DEFAULT 3,
|
||||
subsample DOUBLE PRECISION DEFAULT 0.5,
|
||||
learning_rate DOUBLE PRECISION DEFAULT 0.01,
|
||||
min_samples_leaf INTEGER DEFAULT 1)
|
||||
RETURNS TABLE (cartodb_id TEXT, prediction NUMERIC, accuracy NUMERIC)
|
||||
AS $$
|
||||
from crankshaft.segmentation import create_and_predict_segment
|
||||
model_params = {'n_estimators': n_estimators, 'max_depth':max_depth, 'subsample' : subsample, 'learning_rate': learning_rate, 'min_samples_leaf' : min_samples_leaf}
|
||||
return create_and_predict_segment(query,variable_name,target_table, model_params)
|
||||
$$ LANGUAGE plpythonu;
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Spatial interpolation
|
||||
|
||||
-- 0: nearest neighbor
|
||||
-- 1: barymetric
|
||||
-- 2: IDW
|
||||
|
||||
CREATE OR REPLACE FUNCTION CDB_SpatialInterpolation(
|
||||
IN query text,
|
||||
IN point geometry,
|
||||
IN method integer DEFAULT 1,
|
||||
IN p1 numeric DEFAULT 0,
|
||||
IN p2 numeric DEFAULT 0
|
||||
)
|
||||
RETURNS numeric AS
|
||||
$$
|
||||
DECLARE
|
||||
gs geometry[];
|
||||
vs numeric[];
|
||||
output numeric;
|
||||
BEGIN
|
||||
EXECUTE 'WITH a AS('||query||') SELECT array_agg(the_geom), array_agg(attrib) FROM a' INTO gs, vs;
|
||||
SELECT CDB_SpatialInterpolation(gs, vs, point, method, p1,p2) INTO output FROM a;
|
||||
|
||||
RETURN output;
|
||||
END;
|
||||
$$
|
||||
language plpgsql IMMUTABLE;
|
||||
|
||||
CREATE OR REPLACE FUNCTION CDB_SpatialInterpolation(
|
||||
IN geomin geometry[],
|
||||
IN colin numeric[],
|
||||
IN point geometry,
|
||||
IN method integer DEFAULT 1,
|
||||
IN p1 numeric DEFAULT 0,
|
||||
IN p2 numeric DEFAULT 0
|
||||
)
|
||||
RETURNS numeric AS
|
||||
$$
|
||||
DECLARE
|
||||
gs geometry[];
|
||||
vs numeric[];
|
||||
gs2 geometry[];
|
||||
vs2 numeric[];
|
||||
g geometry;
|
||||
vertex geometry[];
|
||||
sg numeric;
|
||||
sa numeric;
|
||||
sb numeric;
|
||||
sc numeric;
|
||||
va numeric;
|
||||
vb numeric;
|
||||
vc numeric;
|
||||
output numeric;
|
||||
BEGIN
|
||||
output := -999.999;
|
||||
-- nearest
|
||||
IF method = 0 THEN
|
||||
|
||||
WITH a as (SELECT unnest(geomin) as g, unnest(colin) as v)
|
||||
SELECT a.v INTO output FROM a ORDER BY point<->a.g LIMIT 1;
|
||||
RETURN output;
|
||||
|
||||
-- barymetric
|
||||
ELSIF method = 1 THEN
|
||||
WITH a as (SELECT unnest(geomin) AS e),
|
||||
b as (SELECT ST_DelaunayTriangles(ST_Collect(a.e),0.001, 0) AS t FROM a),
|
||||
c as (SELECT (ST_Dump(t)).geom as v FROM b),
|
||||
d as (SELECT v FROM c WHERE ST_Within(point, v))
|
||||
SELECT v INTO g FROM d;
|
||||
IF g is null THEN
|
||||
-- out of the realm of the input data
|
||||
RETURN -888.888;
|
||||
END IF;
|
||||
-- vertex of the selected cell
|
||||
WITH a AS (SELECT (ST_DumpPoints(g)).geom AS v)
|
||||
SELECT array_agg(v) INTO vertex FROM a;
|
||||
|
||||
-- retrieve the value of each vertex
|
||||
WITH a AS(SELECT unnest(vertex) as geo, unnest(colin) as c)
|
||||
SELECT c INTO va FROM a WHERE ST_Equals(geo, vertex[1]);
|
||||
WITH a AS(SELECT unnest(vertex) as geo, unnest(colin) as c)
|
||||
SELECT c INTO vb FROM a WHERE ST_Equals(geo, vertex[2]);
|
||||
WITH a AS(SELECT unnest(vertex) as geo, unnest(colin) as c)
|
||||
SELECT c INTO vc FROM a WHERE ST_Equals(geo, vertex[3]);
|
||||
|
||||
SELECT ST_area(g), ST_area(ST_MakePolygon(ST_MakeLine(ARRAY[point, vertex[2], vertex[3], point]))), ST_area(ST_MakePolygon(ST_MakeLine(ARRAY[point, vertex[1], vertex[3], point]))), ST_area(ST_MakePolygon(ST_MakeLine(ARRAY[point,vertex[1],vertex[2], point]))) INTO sg, sa, sb, sc;
|
||||
|
||||
output := (coalesce(sa,0) * coalesce(va,0) + coalesce(sb,0) * coalesce(vb,0) + coalesce(sc,0) * coalesce(vc,0)) / coalesce(sg);
|
||||
RETURN output;
|
||||
|
||||
-- IDW
|
||||
-- p1: limit the number of neighbors, 0->no limit
|
||||
-- p2: order of distance decay, 0-> order 1
|
||||
ELSIF method = 2 THEN
|
||||
|
||||
IF p2 = 0 THEN
|
||||
p2 := 1;
|
||||
END IF;
|
||||
|
||||
WITH a as (SELECT unnest(geomin) as g, unnest(colin) as v),
|
||||
b as (SELECT a.g, a.v FROM a ORDER BY point<->a.g)
|
||||
SELECT array_agg(b.g), array_agg(b.v) INTO gs, vs FROM b;
|
||||
IF p1::integer>0 THEN
|
||||
gs2:=gs;
|
||||
vs2:=vs;
|
||||
FOR i IN 1..p1
|
||||
LOOP
|
||||
gs2 := gs2 || gs[i];
|
||||
vs2 := vs2 || vs[i];
|
||||
END LOOP;
|
||||
ELSE
|
||||
gs2:=gs;
|
||||
vs2:=vs;
|
||||
END IF;
|
||||
|
||||
WITH a as (SELECT unnest(gs2) as g, unnest(vs2) as v),
|
||||
b as (
|
||||
SELECT
|
||||
(1/ST_distance(point, a.g)^p2::integer) as k,
|
||||
(a.v/ST_distance(point, a.g)^p2::integer) as f
|
||||
FROM a
|
||||
)
|
||||
SELECT sum(b.f)/sum(b.k) INTO output FROM b;
|
||||
RETURN output;
|
||||
|
||||
END IF;
|
||||
|
||||
RETURN -777.777;
|
||||
|
||||
END;
|
||||
$$
|
||||
language plpgsql IMMUTABLE;
|
||||
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Spatial Markov
|
||||
|
||||
-- input table format:
|
||||
-- id | geom | date_1 | date_2 | date_3
|
||||
-- 1 | Pt1 | 12.3 | 13.1 | 14.2
|
||||
-- 2 | Pt2 | 11.0 | 13.2 | 12.5
|
||||
-- ...
|
||||
-- Sample Function call:
|
||||
-- SELECT CDB_SpatialMarkov('SELECT * FROM real_estate',
|
||||
-- Array['date_1', 'date_2', 'date_3'])
|
||||
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_SpatialMarkovTrend (
|
||||
subquery TEXT,
|
||||
time_cols TEXT[],
|
||||
num_classes INT DEFAULT 7,
|
||||
w_type TEXT DEFAULT 'knn',
|
||||
num_ngbrs INT DEFAULT 5,
|
||||
permutations INT DEFAULT 99,
|
||||
geom_col TEXT DEFAULT 'the_geom',
|
||||
id_col TEXT DEFAULT 'cartodb_id')
|
||||
RETURNS TABLE (trend NUMERIC, trend_up NUMERIC, trend_down NUMERIC, volatility NUMERIC, rowid INT)
|
||||
AS $$
|
||||
|
||||
from crankshaft.space_time_dynamics import spatial_markov_trend
|
||||
|
||||
## TODO: use named parameters or a dictionary
|
||||
return spatial_markov_trend(subquery, time_cols, num_classes, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
$$ LANGUAGE plpythonu;
|
||||
81
release/crankshaft--0.1.0--0.0.4.sql
Normal file
81
release/crankshaft--0.1.0--0.0.4.sql
Normal file
@ -0,0 +1,81 @@
|
||||
--DO NOT MODIFY THIS FILE, IT IS GENERATED FROM SOURCES
|
||||
|
||||
-- Complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "CREATE EXTENSION crankshaft" to load this file. \quit
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Version number of the extension release
|
||||
CREATE OR REPLACE FUNCTION cdb_crankshaft_version()
|
||||
RETURNS text AS $$
|
||||
SELECT '0.0.4'::text;
|
||||
$$ language 'sql' STABLE STRICT;
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- PyAgg stuff
|
||||
DROP FUNCTION CDB_PyAggS(Numeric[], Numeric[]);
|
||||
DROP AGGREGATE CDB_PyAgg(NUMERIC[]);
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Segmentation stuff
|
||||
|
||||
DROP FUNCTION
|
||||
CDB_CreateAndPredictSegment(
|
||||
target NUMERIC[],
|
||||
features NUMERIC[],
|
||||
target_features NUMERIC[],
|
||||
target_ids NUMERIC[],
|
||||
n_estimators INTEGER DEFAULT 1200,
|
||||
max_depth INTEGER DEFAULT 3,
|
||||
subsample DOUBLE PRECISION DEFAULT 0.5,
|
||||
learning_rate DOUBLE PRECISION DEFAULT 0.01,
|
||||
min_samples_leaf INTEGER DEFAULT 1);
|
||||
|
||||
DROP FUNCTION
|
||||
CDB_CreateAndPredictSegment (
|
||||
query TEXT,
|
||||
variable_name TEXT,
|
||||
target_table TEXT,
|
||||
n_estimators INTEGER DEFAULT 1200,
|
||||
max_depth INTEGER DEFAULT 3,
|
||||
subsample DOUBLE PRECISION DEFAULT 0.5,
|
||||
learning_rate DOUBLE PRECISION DEFAULT 0.01,
|
||||
min_samples_leaf INTEGER DEFAULT 1);
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Spatial interpolation
|
||||
|
||||
DROP FUNCTION CDB_SpatialInterpolation(
|
||||
IN query text,
|
||||
IN point geometry,
|
||||
IN method integer DEFAULT 1,
|
||||
IN p1 numeric DEFAULT 0,
|
||||
IN p2 numeric DEFAULT 0
|
||||
);
|
||||
|
||||
DROP FUNCTION CDB_SpatialInterpolation(
|
||||
IN geomin geometry[],
|
||||
IN colin numeric[],
|
||||
IN point geometry,
|
||||
IN method integer DEFAULT 1,
|
||||
IN p1 numeric DEFAULT 0,
|
||||
IN p2 numeric DEFAULT 0
|
||||
);
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
-- Spatial Markov
|
||||
|
||||
DROP FUNCTION
|
||||
CDB_SpatialMarkovTrend (
|
||||
subquery TEXT,
|
||||
time_cols TEXT[],
|
||||
num_classes INT DEFAULT 7,
|
||||
w_type TEXT DEFAULT 'knn',
|
||||
num_ngbrs INT DEFAULT 5,
|
||||
permutations INT DEFAULT 99,
|
||||
geom_col TEXT DEFAULT 'the_geom',
|
||||
id_col TEXT DEFAULT 'cartodb_id');
|
||||
Loading…
Reference in New Issue
Block a user