mirror of
https://github.com/CartoDB/crankshaft.git
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Add upgrade file from 0.1.0 to 0.2.0
As compatibility was checked with CI tests, this is simply a copy: ``` cp release/crankshaft--0.2.0.sql release/crankshaft--0.1.0--0.2.0.sql ``` To be automated in `make release` command.
This commit is contained in:
Rafa de la Torre
parent
1bad568fbf
commit
9ada8d12ca
827
release/crankshaft--0.1.0--0.2.0.sql
Normal file
827
release/crankshaft--0.1.0--0.2.0.sql
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@ -0,0 +1,827 @@
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--DO NOT MODIFY THIS FILE, IT IS GENERATED AUTOMATICALLY FROM SOURCES
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-- Complain if script is sourced in psql, rather than via CREATE EXTENSION
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\echo Use "CREATE EXTENSION crankshaft" to load this file. \quit
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-- Version number of the extension release
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CREATE OR REPLACE FUNCTION cdb_crankshaft_version()
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RETURNS text AS $$
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SELECT '0.2.0'::text;
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$$ language 'sql' STABLE STRICT;
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-- Internal identifier of the installed extension instence
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-- e.g. 'dev' for current development version
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CREATE OR REPLACE FUNCTION _cdb_crankshaft_internal_version()
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RETURNS text AS $$
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SELECT installed_version FROM pg_available_extensions where name='crankshaft' and pg_available_extensions IS NOT NULL;
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$$ language 'sql' STABLE STRICT;
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-- Internal function.
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-- Set the seeds of the RNGs (Random Number Generators)
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-- used internally.
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CREATE OR REPLACE FUNCTION
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_cdb_random_seeds (seed_value INTEGER) RETURNS VOID
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AS $$
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from crankshaft import random_seeds
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random_seeds.set_random_seeds(seed_value)
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$$ LANGUAGE plpythonu;
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CREATE OR REPLACE FUNCTION
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CDB_PyAggS(current_state Numeric[], current_row Numeric[])
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returns NUMERIC[] as $$
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BEGIN
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if array_upper(current_state,1) is null then
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RAISE NOTICE 'setting state %',array_upper(current_row,1);
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current_state[1] = array_upper(current_row,1);
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end if;
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return array_cat(current_state,current_row) ;
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END
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$$ LANGUAGE plpgsql;
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-- Create aggregate if it did not exist
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DO $$
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BEGIN
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IF NOT EXISTS (
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SELECT *
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FROM pg_catalog.pg_proc p
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LEFT JOIN pg_catalog.pg_namespace n ON n.oid = p.pronamespace
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WHERE n.nspname = 'cdb_crankshaft'
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AND p.proname = 'cdb_pyagg'
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AND p.proisagg)
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THEN
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CREATE AGGREGATE CDB_PyAgg(NUMERIC[]) (
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SFUNC = CDB_PyAggS,
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STYPE = Numeric[],
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INITCOND = "{}"
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);
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END IF;
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END
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$$ LANGUAGE plpgsql;
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CREATE OR REPLACE FUNCTION
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CDB_CreateAndPredictSegment(
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target NUMERIC[],
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features NUMERIC[],
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target_features NUMERIC[],
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target_ids NUMERIC[],
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n_estimators INTEGER DEFAULT 1200,
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max_depth INTEGER DEFAULT 3,
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subsample DOUBLE PRECISION DEFAULT 0.5,
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learning_rate DOUBLE PRECISION DEFAULT 0.01,
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min_samples_leaf INTEGER DEFAULT 1)
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RETURNS TABLE(cartodb_id NUMERIC, prediction NUMERIC, accuracy NUMERIC)
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AS $$
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import numpy as np
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import plpy
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from crankshaft.segmentation import create_and_predict_segment_agg
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model_params = {'n_estimators': n_estimators,
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'max_depth': max_depth,
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'subsample': subsample,
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'learning_rate': learning_rate,
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'min_samples_leaf': min_samples_leaf}
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def unpack2D(data):
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dimension = data.pop(0)
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a = np.array(data, dtype=float)
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return a.reshape(len(a)/dimension, dimension)
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return create_and_predict_segment_agg(np.array(target, dtype=float),
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unpack2D(features),
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unpack2D(target_features),
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target_ids,
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model_params)
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$$ LANGUAGE plpythonu;
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CREATE OR REPLACE FUNCTION
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CDB_CreateAndPredictSegment (
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query TEXT,
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variable_name TEXT,
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target_table TEXT,
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n_estimators INTEGER DEFAULT 1200,
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max_depth INTEGER DEFAULT 3,
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subsample DOUBLE PRECISION DEFAULT 0.5,
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learning_rate DOUBLE PRECISION DEFAULT 0.01,
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min_samples_leaf INTEGER DEFAULT 1)
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RETURNS TABLE (cartodb_id TEXT, prediction NUMERIC, accuracy NUMERIC)
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AS $$
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from crankshaft.segmentation import create_and_predict_segment
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model_params = {'n_estimators': n_estimators, 'max_depth':max_depth, 'subsample' : subsample, 'learning_rate': learning_rate, 'min_samples_leaf' : min_samples_leaf}
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return create_and_predict_segment(query,variable_name,target_table, model_params)
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$$ LANGUAGE plpythonu;
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CREATE OR REPLACE FUNCTION CDB_Gravity(
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IN target_query text,
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IN weight_column text,
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IN source_query text,
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IN pop_column text,
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IN target bigint,
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IN radius integer,
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IN minval numeric DEFAULT -10e307
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)
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RETURNS TABLE(
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the_geom geometry,
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source_id bigint,
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target_id bigint,
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dist numeric,
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h numeric,
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hpop numeric) AS $$
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DECLARE
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t_id bigint[];
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t_geom geometry[];
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t_weight numeric[];
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s_id bigint[];
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s_geom geometry[];
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s_pop numeric[];
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BEGIN
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EXECUTE 'WITH foo as('+target_query+') SELECT array_agg(cartodb_id), array_agg(the_geom), array_agg(' || weight_column || ') FROM foo' INTO t_id, t_geom, t_weight;
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EXECUTE 'WITH foo as('+source_query+') SELECT array_agg(cartodb_id), array_agg(the_geom), array_agg(' || pop_column || ') FROM foo' INTO s_id, s_geom, s_pop;
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RETURN QUERY
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SELECT g.* FROM t, s, CDB_Gravity(t_id, t_geom, t_weight, s_id, s_geom, s_pop, target, radius, minval) g;
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END;
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$$ language plpgsql;
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CREATE OR REPLACE FUNCTION CDB_Gravity(
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IN t_id bigint[],
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IN t_geom geometry[],
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IN t_weight numeric[],
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IN s_id bigint[],
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IN s_geom geometry[],
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IN s_pop numeric[],
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IN target bigint,
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IN radius integer,
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IN minval numeric DEFAULT -10e307
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)
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RETURNS TABLE(
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the_geom geometry,
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source_id bigint,
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target_id bigint,
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dist numeric,
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h numeric,
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hpop numeric) AS $$
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DECLARE
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t_type text;
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s_type text;
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t_center geometry[];
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s_center geometry[];
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BEGIN
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t_type := GeometryType(t_geom[1]);
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s_type := GeometryType(s_geom[1]);
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IF t_type = 'POINT' THEN
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t_center := t_geom;
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ELSE
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WITH tmp as (SELECT unnest(t_geom) as g) SELECT array_agg(ST_Centroid(g)) INTO t_center FROM tmp;
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END IF;
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IF s_type = 'POINT' THEN
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s_center := s_geom;
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ELSE
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WITH tmp as (SELECT unnest(s_geom) as g) SELECT array_agg(ST_Centroid(g)) INTO s_center FROM tmp;
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END IF;
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RETURN QUERY
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with target0 as(
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SELECT unnest(t_center) as tc, unnest(t_weight) as tw, unnest(t_id) as td
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),
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source0 as(
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SELECT unnest(s_center) as sc, unnest(s_id) as sd, unnest (s_geom) as sg, unnest(s_pop) as sp
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),
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prev0 as(
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SELECT
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source0.sg,
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source0.sd as sourc_id,
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coalesce(source0.sp,0) as sp,
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target.td as targ_id,
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coalesce(target.tw,0) as tw,
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GREATEST(1.0,ST_Distance(geography(target.tc), geography(source0.sc)))::numeric as distance
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FROM source0
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CROSS JOIN LATERAL
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(
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SELECT
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*
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FROM target0
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WHERE tw > minval
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AND ST_DWithin(geography(source0.sc), geography(tc), radius)
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) AS target
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),
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deno as(
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SELECT
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sourc_id,
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sum(tw/distance) as h_deno
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FROM
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prev0
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GROUP BY sourc_id
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)
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SELECT
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p.sg as the_geom,
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p.sourc_id as source_id,
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p.targ_id as target_id,
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case when p.distance > 1 then p.distance else 0.0 end as dist,
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100*(p.tw/p.distance)/d.h_deno as h,
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p.sp*(p.tw/p.distance)/d.h_deno as hpop
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FROM
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prev0 p,
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deno d
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WHERE
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p.targ_id = target AND
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p.sourc_id = d.sourc_id;
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END;
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$$ language plpgsql;
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-- 0: nearest neighbor
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-- 1: barymetric
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-- 2: IDW
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CREATE OR REPLACE FUNCTION CDB_SpatialInterpolation(
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IN query text,
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IN point geometry,
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IN method integer DEFAULT 1,
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IN p1 numeric DEFAULT 0,
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IN p2 numeric DEFAULT 0
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)
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RETURNS numeric AS
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$$
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DECLARE
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gs geometry[];
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vs numeric[];
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output numeric;
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BEGIN
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EXECUTE 'WITH a AS('||query||') SELECT array_agg(the_geom), array_agg(attrib) FROM a' INTO gs, vs;
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SELECT CDB_SpatialInterpolation(gs, vs, point, method, p1,p2) INTO output FROM a;
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RETURN output;
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END;
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$$
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language plpgsql IMMUTABLE;
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CREATE OR REPLACE FUNCTION CDB_SpatialInterpolation(
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IN geomin geometry[],
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IN colin numeric[],
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IN point geometry,
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IN method integer DEFAULT 1,
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IN p1 numeric DEFAULT 0,
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IN p2 numeric DEFAULT 0
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)
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RETURNS numeric AS
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$$
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DECLARE
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gs geometry[];
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vs numeric[];
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gs2 geometry[];
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vs2 numeric[];
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g geometry;
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vertex geometry[];
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sg numeric;
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sa numeric;
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sb numeric;
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sc numeric;
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va numeric;
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vb numeric;
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vc numeric;
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output numeric;
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BEGIN
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output := -999.999;
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-- nearest
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IF method = 0 THEN
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WITH a as (SELECT unnest(geomin) as g, unnest(colin) as v)
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SELECT a.v INTO output FROM a ORDER BY point<->a.g LIMIT 1;
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RETURN output;
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-- barymetric
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ELSIF method = 1 THEN
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WITH a as (SELECT unnest(geomin) AS e),
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b as (SELECT ST_DelaunayTriangles(ST_Collect(a.e),0.001, 0) AS t FROM a),
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c as (SELECT (ST_Dump(t)).geom as v FROM b),
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d as (SELECT v FROM c WHERE ST_Within(point, v))
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SELECT v INTO g FROM d;
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IF g is null THEN
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-- out of the realm of the input data
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RETURN -888.888;
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END IF;
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-- vertex of the selected cell
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WITH a AS (SELECT (ST_DumpPoints(g)).geom AS v)
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SELECT array_agg(v) INTO vertex FROM a;
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-- retrieve the value of each vertex
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WITH a AS(SELECT unnest(vertex) as geo, unnest(colin) as c)
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SELECT c INTO va FROM a WHERE ST_Equals(geo, vertex[1]);
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WITH a AS(SELECT unnest(vertex) as geo, unnest(colin) as c)
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SELECT c INTO vb FROM a WHERE ST_Equals(geo, vertex[2]);
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WITH a AS(SELECT unnest(vertex) as geo, unnest(colin) as c)
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SELECT c INTO vc FROM a WHERE ST_Equals(geo, vertex[3]);
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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;
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output := (coalesce(sa,0) * coalesce(va,0) + coalesce(sb,0) * coalesce(vb,0) + coalesce(sc,0) * coalesce(vc,0)) / coalesce(sg);
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RETURN output;
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-- IDW
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-- p1: limit the number of neighbors, 0->no limit
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-- p2: order of distance decay, 0-> order 1
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ELSIF method = 2 THEN
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IF p2 = 0 THEN
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p2 := 1;
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END IF;
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WITH a as (SELECT unnest(geomin) as g, unnest(colin) as v),
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b as (SELECT a.g, a.v FROM a ORDER BY point<->a.g)
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SELECT array_agg(b.g), array_agg(b.v) INTO gs, vs FROM b;
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IF p1::integer>0 THEN
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gs2:=gs;
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vs2:=vs;
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FOR i IN 1..p1
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LOOP
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gs2 := gs2 || gs[i];
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vs2 := vs2 || vs[i];
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END LOOP;
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ELSE
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gs2:=gs;
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vs2:=vs;
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END IF;
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WITH a as (SELECT unnest(gs2) as g, unnest(vs2) as v),
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b as (
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SELECT
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(1/ST_distance(point, a.g)^p2::integer) as k,
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(a.v/ST_distance(point, a.g)^p2::integer) as f
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FROM a
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)
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SELECT sum(b.f)/sum(b.k) INTO output FROM b;
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RETURN output;
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END IF;
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RETURN -777.777;
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END;
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$$
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language plpgsql IMMUTABLE;
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-- Moran's I Global Measure (public-facing)
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CREATE OR REPLACE FUNCTION
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CDB_AreasOfInterestGlobal(
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subquery TEXT,
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column_name TEXT,
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w_type TEXT DEFAULT 'knn',
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num_ngbrs INT DEFAULT 5,
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permutations INT DEFAULT 99,
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geom_col TEXT DEFAULT 'the_geom',
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id_col TEXT DEFAULT 'cartodb_id')
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RETURNS TABLE (moran NUMERIC, significance NUMERIC)
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AS $$
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from crankshaft.clustering import moran_local
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# TODO: use named parameters or a dictionary
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return moran(subquery, column_name, w_type, num_ngbrs, permutations, geom_col, id_col)
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$$ LANGUAGE plpythonu;
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-- Moran's I Local (internal function)
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CREATE OR REPLACE FUNCTION
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_CDB_AreasOfInterestLocal(
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subquery TEXT,
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column_name TEXT,
|
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w_type TEXT,
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num_ngbrs INT,
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||||
permutations INT,
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geom_col TEXT,
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id_col TEXT)
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RETURNS TABLE (moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
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AS $$
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from crankshaft.clustering import moran_local
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# TODO: use named parameters or a dictionary
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return moran_local(subquery, column_name, w_type, num_ngbrs, permutations, geom_col, id_col)
|
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$$ LANGUAGE plpythonu;
|
||||
|
||||
-- Moran's I Local (public-facing function)
|
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CREATE OR REPLACE FUNCTION
|
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CDB_AreasOfInterestLocal(
|
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subquery TEXT,
|
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column_name TEXT,
|
||||
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 (moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
|
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SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocal(subquery, column_name, w_type, num_ngbrs, permutations, geom_col, id_col);
|
||||
|
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$$ LANGUAGE SQL;
|
||||
|
||||
-- Moran's I only for HH and HL (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
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CDB_GetSpatialHotspots(
|
||||
subquery TEXT,
|
||||
column_name TEXT,
|
||||
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 (moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
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AS $$
|
||||
|
||||
SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocal(subquery, column_name, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
WHERE quads IN ('HH', 'HL');
|
||||
|
||||
$$ LANGUAGE SQL;
|
||||
|
||||
-- Moran's I only for LL and LH (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
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CDB_GetSpatialColdspots(
|
||||
subquery TEXT,
|
||||
attr TEXT,
|
||||
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 (moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
|
||||
SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocal(subquery, attr, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
WHERE quads IN ('LL', 'LH');
|
||||
|
||||
$$ LANGUAGE SQL;
|
||||
|
||||
-- Moran's I only for LH and HL (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_GetSpatialOutliers(
|
||||
subquery TEXT,
|
||||
attr TEXT,
|
||||
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 (moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
|
||||
SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocal(subquery, attr, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
WHERE quads IN ('HL', 'LH');
|
||||
|
||||
$$ LANGUAGE SQL;
|
||||
|
||||
-- Moran's I Global Rate (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_AreasOfInterestGlobalRate(
|
||||
subquery TEXT,
|
||||
numerator TEXT,
|
||||
denominator TEXT,
|
||||
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 (moran FLOAT, significance FLOAT)
|
||||
AS $$
|
||||
from crankshaft.clustering import moran_local
|
||||
# TODO: use named parameters or a dictionary
|
||||
return moran_rate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
$$ LANGUAGE plpythonu;
|
||||
|
||||
|
||||
-- Moran's I Local Rate (internal function)
|
||||
CREATE OR REPLACE FUNCTION
|
||||
_CDB_AreasOfInterestLocalRate(
|
||||
subquery TEXT,
|
||||
numerator TEXT,
|
||||
denominator TEXT,
|
||||
w_type TEXT,
|
||||
num_ngbrs INT,
|
||||
permutations INT,
|
||||
geom_col TEXT,
|
||||
id_col TEXT)
|
||||
RETURNS
|
||||
TABLE(moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
from crankshaft.clustering import moran_local_rate
|
||||
# TODO: use named parameters or a dictionary
|
||||
return moran_local_rate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
$$ LANGUAGE plpythonu;
|
||||
|
||||
-- Moran's I Local Rate (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_AreasOfInterestLocalRate(
|
||||
subquery TEXT,
|
||||
numerator TEXT,
|
||||
denominator TEXT,
|
||||
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(moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
|
||||
SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocalRate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col);
|
||||
|
||||
$$ LANGUAGE SQL;
|
||||
|
||||
-- Moran's I Local Rate only for HH and HL (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_GetSpatialHotspotsRate(
|
||||
subquery TEXT,
|
||||
numerator TEXT,
|
||||
denominator TEXT,
|
||||
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(moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
|
||||
SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocalRate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
WHERE quads IN ('HH', 'HL');
|
||||
|
||||
$$ LANGUAGE SQL;
|
||||
|
||||
-- Moran's I Local Rate only for LL and LH (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_GetSpatialColdspotsRate(
|
||||
subquery TEXT,
|
||||
numerator TEXT,
|
||||
denominator TEXT,
|
||||
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(moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
|
||||
SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocalRate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
WHERE quads IN ('LL', 'LH');
|
||||
|
||||
$$ LANGUAGE SQL;
|
||||
|
||||
-- Moran's I Local Rate only for LH and HL (public-facing function)
|
||||
CREATE OR REPLACE FUNCTION
|
||||
CDB_GetSpatialOutliersRate(
|
||||
subquery TEXT,
|
||||
numerator TEXT,
|
||||
denominator TEXT,
|
||||
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(moran NUMERIC, quads TEXT, significance NUMERIC, rowid INT, vals NUMERIC)
|
||||
AS $$
|
||||
|
||||
SELECT moran, quads, significance, rowid, vals
|
||||
FROM cdb_crankshaft._CDB_AreasOfInterestLocalRate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col)
|
||||
WHERE quads IN ('HL', 'LH');
|
||||
|
||||
$$ LANGUAGE SQL;
|
||||
CREATE OR REPLACE FUNCTION CDB_KMeans(query text, no_clusters integer,no_init integer default 20)
|
||||
RETURNS table (cartodb_id integer, cluster_no integer) as $$
|
||||
|
||||
from crankshaft.clustering import kmeans
|
||||
return kmeans(query,no_clusters,no_init)
|
||||
|
||||
$$ language plpythonu;
|
||||
|
||||
|
||||
CREATE OR REPLACE FUNCTION CDB_WeightedMeanS(state Numeric[],the_geom GEOMETRY(Point, 4326), weight NUMERIC)
|
||||
RETURNS Numeric[] AS
|
||||
$$
|
||||
DECLARE
|
||||
newX NUMERIC;
|
||||
newY NUMERIC;
|
||||
newW NUMERIC;
|
||||
BEGIN
|
||||
IF weight IS NULL OR the_geom IS NULL THEN
|
||||
newX = state[1];
|
||||
newY = state[2];
|
||||
newW = state[3];
|
||||
ELSE
|
||||
newX = state[1] + ST_X(the_geom)*weight;
|
||||
newY = state[2] + ST_Y(the_geom)*weight;
|
||||
newW = state[3] + weight;
|
||||
END IF;
|
||||
RETURN Array[newX,newY,newW];
|
||||
|
||||
END
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
CREATE OR REPLACE FUNCTION CDB_WeightedMeanF(state Numeric[])
|
||||
RETURNS GEOMETRY AS
|
||||
$$
|
||||
BEGIN
|
||||
IF state[3] = 0 THEN
|
||||
RETURN ST_SetSRID(ST_MakePoint(state[1],state[2]), 4326);
|
||||
ELSE
|
||||
RETURN ST_SETSRID(ST_MakePoint(state[1]/state[3], state[2]/state[3]),4326);
|
||||
END IF;
|
||||
END
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
-- Create aggregate if it did not exist
|
||||
DO $$
|
||||
BEGIN
|
||||
IF NOT EXISTS (
|
||||
SELECT *
|
||||
FROM pg_catalog.pg_proc p
|
||||
LEFT JOIN pg_catalog.pg_namespace n ON n.oid = p.pronamespace
|
||||
WHERE n.nspname = 'cdb_crankshaft'
|
||||
AND p.proname = 'cdb_weightedmean'
|
||||
AND p.proisagg)
|
||||
THEN
|
||||
CREATE AGGREGATE CDB_WeightedMean(geometry(Point, 4326), NUMERIC) (
|
||||
SFUNC = CDB_WeightedMeanS,
|
||||
FINALFUNC = CDB_WeightedMeanF,
|
||||
STYPE = Numeric[],
|
||||
INITCOND = "{0.0,0.0,0.0}"
|
||||
);
|
||||
END IF;
|
||||
END
|
||||
$$ LANGUAGE plpgsql;
|
||||
-- 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;
|
||||
|
||||
-- input table format: identical to above but in a predictable format
|
||||
-- Sample function call:
|
||||
-- SELECT cdb_spatial_markov('SELECT * FROM real_estate',
|
||||
-- 'date_1')
|
||||
|
||||
|
||||
-- CREATE OR REPLACE FUNCTION
|
||||
-- cdb_spatial_markov (
|
||||
-- subquery TEXT,
|
||||
-- time_col_min text,
|
||||
-- time_col_max text,
|
||||
-- date_format text, -- '_YYYY_MM_DD'
|
||||
-- num_time_per_bin INT DEFAULT 1,
|
||||
-- permutations INT DEFAULT 99,
|
||||
-- geom_column TEXT DEFAULT 'the_geom',
|
||||
-- id_col TEXT DEFAULT 'cartodb_id',
|
||||
-- w_type TEXT DEFAULT 'knn',
|
||||
-- num_ngbrs int DEFAULT 5)
|
||||
-- RETURNS TABLE (moran FLOAT, quads TEXT, significance FLOAT, ids INT)
|
||||
-- AS $$
|
||||
-- plpy.execute('SELECT cdb_crankshaft._cdb_crankshaft_activate_py()')
|
||||
-- from crankshaft.clustering import moran_local
|
||||
-- # TODO: use named parameters or a dictionary
|
||||
-- return spatial_markov(subquery, time_cols, permutations, geom_column, id_col, w_type, num_ngbrs)
|
||||
-- $$ LANGUAGE plpythonu;
|
||||
--
|
||||
-- -- input table format:
|
||||
-- -- id | geom | date | measurement
|
||||
-- -- 1 | Pt1 | 12/3 | 13.2
|
||||
-- -- 2 | Pt2 | 11/5 | 11.3
|
||||
-- -- 3 | Pt1 | 11/13 | 12.9
|
||||
-- -- 4 | Pt3 | 12/19 | 10.1
|
||||
-- -- ...
|
||||
--
|
||||
-- CREATE OR REPLACE FUNCTION
|
||||
-- cdb_spatial_markov (
|
||||
-- subquery TEXT,
|
||||
-- time_col text,
|
||||
-- num_time_per_bin INT DEFAULT 1,
|
||||
-- permutations INT DEFAULT 99,
|
||||
-- geom_column TEXT DEFAULT 'the_geom',
|
||||
-- id_col TEXT DEFAULT 'cartodb_id',
|
||||
-- w_type TEXT DEFAULT 'knn',
|
||||
-- num_ngbrs int DEFAULT 5)
|
||||
-- RETURNS TABLE (moran FLOAT, quads TEXT, significance FLOAT, ids INT)
|
||||
-- AS $$
|
||||
-- plpy.execute('SELECT cdb_crankshaft._cdb_crankshaft_activate_py()')
|
||||
-- from crankshaft.clustering import moran_local
|
||||
-- # TODO: use named parameters or a dictionary
|
||||
-- return spatial_markov(subquery, time_cols, permutations, geom_column, id_col, w_type, num_ngbrs)
|
||||
-- $$ LANGUAGE plpythonu;
|
||||
-- Function by Stuart Lynn for a simple interpolation of a value
|
||||
-- from a polygon table over an arbitrary polygon
|
||||
-- (weighted by the area proportion overlapped)
|
||||
-- Aereal weighting is a very simple form of aereal interpolation.
|
||||
--
|
||||
-- Parameters:
|
||||
-- * geom a Polygon geometry which defines the area where a value will be
|
||||
-- estimated as the area-weighted sum of a given table/column
|
||||
-- * target_table_name table name of the table that provides the values
|
||||
-- * target_column column name of the column that provides the values
|
||||
-- * schema_name optional parameter to defina the schema the target table
|
||||
-- belongs to, which is necessary if its not in the search_path.
|
||||
-- Note that target_table_name should never include the schema in it.
|
||||
-- Return value:
|
||||
-- Aereal-weighted interpolation of the column values over the geometry
|
||||
CREATE OR REPLACE
|
||||
FUNCTION cdb_overlap_sum(geom geometry, target_table_name text, target_column text, schema_name text DEFAULT NULL)
|
||||
RETURNS numeric AS
|
||||
$$
|
||||
DECLARE
|
||||
result numeric;
|
||||
qualified_name text;
|
||||
BEGIN
|
||||
IF schema_name IS NULL THEN
|
||||
qualified_name := Format('%I', target_table_name);
|
||||
ELSE
|
||||
qualified_name := Format('%I.%s', schema_name, target_table_name);
|
||||
END IF;
|
||||
EXECUTE Format('
|
||||
SELECT sum(%I*ST_Area(St_Intersection($1, a.the_geom))/ST_Area(a.the_geom))
|
||||
FROM %s AS a
|
||||
WHERE $1 && a.the_geom
|
||||
', target_column, qualified_name)
|
||||
USING geom
|
||||
INTO result;
|
||||
RETURN result;
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
--
|
||||
-- Creates N points randomly distributed arround the polygon
|
||||
--
|
||||
-- @param g - the geometry to be turned in to points
|
||||
--
|
||||
-- @param no_points - the number of points to generate
|
||||
--
|
||||
-- @params max_iter_per_point - the function generates points in the polygon's bounding box
|
||||
-- and discards points which don't lie in the polygon. max_iter_per_point specifies how many
|
||||
-- misses per point the funciton accepts before giving up.
|
||||
--
|
||||
-- Returns: Multipoint with the requested points
|
||||
CREATE OR REPLACE FUNCTION cdb_dot_density(geom geometry , no_points Integer, max_iter_per_point Integer DEFAULT 1000)
|
||||
RETURNS GEOMETRY AS $$
|
||||
DECLARE
|
||||
extent GEOMETRY;
|
||||
test_point Geometry;
|
||||
width NUMERIC;
|
||||
height NUMERIC;
|
||||
x0 NUMERIC;
|
||||
y0 NUMERIC;
|
||||
xp NUMERIC;
|
||||
yp NUMERIC;
|
||||
no_left INTEGER;
|
||||
remaining_iterations INTEGER;
|
||||
points GEOMETRY[];
|
||||
bbox_line GEOMETRY;
|
||||
intersection_line GEOMETRY;
|
||||
BEGIN
|
||||
extent := ST_Envelope(geom);
|
||||
width := ST_XMax(extent) - ST_XMIN(extent);
|
||||
height := ST_YMax(extent) - ST_YMIN(extent);
|
||||
x0 := ST_XMin(extent);
|
||||
y0 := ST_YMin(extent);
|
||||
no_left := no_points;
|
||||
|
||||
LOOP
|
||||
if(no_left=0) THEN
|
||||
EXIT;
|
||||
END IF;
|
||||
yp = y0 + height*random();
|
||||
bbox_line = ST_MakeLine(
|
||||
ST_SetSRID(ST_MakePoint(yp, x0),4326),
|
||||
ST_SetSRID(ST_MakePoint(yp, x0+width),4326)
|
||||
);
|
||||
intersection_line = ST_Intersection(bbox_line,geom);
|
||||
test_point = ST_LineInterpolatePoint(st_makeline(st_linemerge(intersection_line)),random());
|
||||
points := points || test_point;
|
||||
no_left = no_left - 1 ;
|
||||
END LOOP;
|
||||
RETURN ST_Collect(points);
|
||||
END;
|
||||
$$
|
||||
LANGUAGE plpgsql VOLATILE;
|
||||
-- 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_crankshaft 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_crankshaft FROM PUBLIC, publicuser;
|
||||
Loading…
Reference in New Issue
Block a user