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updating to run in crankshaft. Output still wrong but getting there

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Ubuntu
2016-05-20 20:43:31 +00:00
parent a00c8df201
commit 1dbbb5ecaa
2 changed files with 24 additions and 15 deletions
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6
src/pg/sql/50_contours.sql
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@@ -21,10 +21,12 @@ CREATE OR REPLACE FUNCTION
bandwidth NUMERIC DEFAULT 0.0001,
levels NUMERIC[] DEFAULT null
)
RETURNS table (level Numeric, geom text )
RETURNS table (level Numeric, geom geometry )
AS $$
BEGIN
RETURN QUERY
select l as level, ST_GeomFromText(geom_text, 4326) as geom from _CDB_Contours(subquery,grid_size,bandwidth,levels);
select cont.level as level, ST_GeomFromText(cont.geom_text, 4326)::geometry as geom from _CDB_Contours(subquery,grid_size,bandwidth,levels) as cont;
END;
$$ LANGUAGE plpgsql;

33
src/py/crankshaft/crankshaft/contours/contours.py
View File

@@ -5,15 +5,20 @@ from sklearn.neighbors import KernelDensity
from skimage.measure import find_contours
import plpy
def cdb_generate_contours(query, grid_size, bandwidth, levels):
data = plpy.execute( 'select ST_X(the_geom) as x , ST_Y(the_geom) as y from ({query})')
xs, ys = [d['x'], d['y'] from data]
return generate_contours(xs,xy,grid_size,bandwidth,levels)
plpy.notice('one')
data = plpy.execute( 'select ST_X(the_geom) as x , ST_Y(the_geom) as y from ({0}) as a '.format(query))
plpy.notice('two')
xs = [d['x'] for d in data]
ys = [d['y'] for d in data]
plpy.notice('three')
return generate_contours(xs,ys,grid_size,bandwidth,levels)
def scale_coord(coord, x_range,y_range,grid_size):
return [coord[0]*(x_range[1]-x_range[0])/grid_size+x_range[0],
coord[1]*(y_range[1]-y_range[0])/grid_size+y_range[0]]
plpy.notice('ranges %, % ', x_range, y_range)
return [coord[0]*(x_range[1]-x_range[0])/float(grid_size)+x_range[0],
coord[1]*(y_range[1]-y_range[0])/float(grid_size)+y_range[0]]
def make_wkt(data,x_range, y_range, grid_size):
joined = ','.join([' '.join(map(str,scale_coord(coord_pair, x_range, y_range, grid_size))) for coord_pair in data])
@@ -23,15 +28,17 @@ def make_multi_line(data,x_range,y_range, grid_size):
joined = ','.join([ make_wkt(ring,x_range,y_range,grid_size) for ring in data ])
return 'MULTILINESTRING({0})'.format(joined)
def generate_contours(xs,ys, grid_res=100, bandwidth=0.0001, levels=None):
max_y, min_y = ys.max(), ys.min()
max_x, min_x = xs.max(), xs.min()
def generate_contours(xs,ys, grid_res=100, bandwidth=0.001, levels=None):
plpy.notice("HERE")
max_y, min_y = np.max(ys), np.min(ys)
max_x, min_x = np.max(xs), np.min(xs)
positions = np.vstack([ys,xs]).T
grid_x,grid_y = np.meshgrid(np.linspace(min_x, max_x , grid_res), np.linspace(min_y, max_y, grid_res))
xy = np.vstack([grid_y.ravel(), grid_x.ravel()]).T
xy *= np.pi / 180.
kde = KernelDensity(bandwidth=0.0001, metric='haversine',
plpy.notice(" Generating kernel density")
kde = KernelDensity(bandwidth=bandwidth, metric='haversine',
kernel='gaussian', algorithm='ball_tree')
kde.fit(positions*np.pi/180.)
results = np.exp(kde.score_samples(xy))
@@ -39,7 +46,7 @@ def generate_contours(xs,ys, grid_res=100, bandwidth=0.0001, levels=None):
if not levels:
levels = np.linspace(results.min(), results.max(),60)
plpy.notice(' finding contours')
CS = [find_contours(results, level) for level in levels]
vertices = []
@@ -47,5 +54,5 @@ def generate_contours(xs,ys, grid_res=100, bandwidth=0.0001, levels=None):
if len(contours)>0:
multiline = make_multi_line(contours, (min_x,max_x), (min_y, max_y), grid_res)
vertices.append([level, multiline ])
plpy.notice('generated vertices retunring ?')
return vertices