def test_iterops(self):
coords = ((0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0), (0.0, 0.0))
polygon = Polygon(coords)
points = [Point(0.5, 0.5), Point(2.0, 2.0)]
# List of the points contained by the polygon
self.assertTrue(
all([isinstance(x, Point)
for x in iterops.contains(polygon, points, True)]))
# 'True' is the default value
self.assertTrue(
all([isinstance(x, Point)
for x in iterops.contains(polygon, points)]))
# Test a false value
self.assertTrue(
all([isinstance(x, Point)
for x in iterops.contains(polygon, points, False)]))
# If the provided iterator yields tuples, the second value will be
# yielded
self.assertEqual(
list(iterops.contains(polygon, [(p, p.coords[:])
for p in points], False)),
[[(2.0, 2.0)]])
# Just to demonstrate that the important thing is that the second
# parameter is an iterator:
self.assertEqual(
list(iterops.contains(polygon, iter((p, p.coords[:])
for p in points))),
[[(0.5, 0.5)]])
def rastervals_in_unit(unit, lon_min, lat_min, cellsize, data, view='y-x+'):
# For some reason it is MUCH faster to do it this way.
if isinstance(unit, geometry.multipolygon.MultiPolygon):
return np.hstack([rastervals_in_unit(g,lon_min,lat_min,cellsize,data,view) for g in unit.geoms])
llc = unit.bounds[:2]
urc = unit.bounds[2:]
lon_min_in = int((llc[0]-lon_min)/cellsize)
lon_max_in = int((urc[0]-lon_min)/cellsize)+1
lat_min_in = int((llc[1]-lat_min)/cellsize)
lat_max_in = int((urc[1]-lat_min)/cellsize)+1
data_boxed_ = grid_convert(data,view,'x+y+')[lon_min_in:lon_max_in+1,lat_min_in:lat_max_in+1]
flat_shape = (-1,)+data_boxed_.shape[2:]
data_boxed = data_boxed_.reshape(flat_shape)
lon_boxed = np.arange(lon_min_in, lon_max_in+1)*cellsize + lon_min
lat_boxed = np.arange(lat_min_in, lat_max_in+1)*cellsize + lat_min
mlon_boxed, mlat_boxed = np.meshgrid(lon_boxed, lat_boxed)
mlon_boxed = grid_convert(mlon_boxed,'y+x+','x+y+')
mlat_boxed = grid_convert(mlat_boxed,'y+x+','x+y+')
p=[geom.Point(*pair) for pair in zip(mlon_boxed.ravel(), mlat_boxed.ravel())]
if isinstance(unit, geometry.polygon.Polygon):
p_in = set(iterops.contains(geometry.polygon.Polygon(unit.exterior.coords), p, True))
for hole in unit.interiors:
p_in -= set(iterops.contains(geometry.polygon.Polygon(hole.coords), p, True))
else:
p_in = iterops.contains(unit, p, True)
i_in = [p.index(p_in_) for p_in_ in p_in]
out = data_boxed[i_in]
return out
def test_iterops(self):
coords = ((0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0), (0.0, 0.0))
polygon = Polygon(coords)
points = [Point(0.5, 0.5), Point(2.0, 2.0)]
# List of the points contained by the polygon
self.assertTrue(
all([isinstance(x, Point)
for x in iterops.contains(polygon, points, True)]))
# 'True' is the default value
self.assertTrue(
all([isinstance(x, Point)
for x in iterops.contains(polygon, points)]))
# Test a false value
self.assertTrue(
all([isinstance(x, Point)
for x in iterops.contains(polygon, points, False)]))
# If the provided iterator yields tuples, the second value will be
# yielded
self.assertEqual(
list(iterops.contains(polygon, [(p, p.coords[:])
for p in points], False)),
[[(2.0, 2.0)]])
# Just to demonstrate that the important thing is that the second
# parameter is an iterator:
self.assertEqual(
list(iterops.contains(polygon, iter((p, p.coords[:])
for p in points))),
[[(0.5, 0.5)]])
def unit_to_grid(unit, lon_min, lat_min, cellsize):
"""
unit_to_grid(unit, lon_min, lat_min, cellsize)
unit : a shapely polygon or multipolygon
lon_min : The llc longitude of the master raster
lat_min : The llc latitude of the master raster
cellsize: of the master raster
Retruns two arrays, lon and lat, of points on the raster in the unit.
"""
llc = unit.bounds[:2]
urc = unit.bounds[2:]
lon_min_in = int((llc[0]-lon_min)/cellsize)
lon_max_in = int((urc[0]-lon_min)/cellsize)+1
lat_min_in = int((llc[1]-lat_min)/cellsize)
lat_max_in = int((urc[1]-lat_min)/cellsize)+1
x_extent = np.arange(lon_min_in, lon_max_in+1)*cellsize + lon_min
y_extent = np.arange(lat_min_in, lat_max_in+1)*cellsize + lat_min
nx = len(x_extent)
ny = len(y_extent)
xm,ym = np.meshgrid(x_extent, y_extent)
x=xm.ravel()
y=ym.ravel()
p=[geom.Point([x[i],y[i]]) for i in xrange(len(x))]
return iterops.contains(unit, p, True)
def test_iterops_deprecated(self):
coords = ((0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0), (0.0, 0.0))
polygon = Polygon(coords)
points = [Point(0.5, 0.5), Point(2.0, 2.0)]
with pytest.warns(ShapelyDeprecationWarning,
match="'contains' function"):
list(iterops.contains(polygon, points, True))
def multipoly_sample(n, mp):
"""
Returns uniformly-distributed points on the earth's surface
conditioned to be inside a multipolygon.
Not particularly fast.
"""
# b = basemap.Basemap(-180,-90,180,90)
if isinstance(mp, geometry.MultiPolygon):
print 'Breaking down multipolygon'
areas = [shapely_poly_area(p) for p in mp.geoms]
areas = np.array(areas)/np.sum(areas)
# ns = pm.rmultinomial(n, areas)
stair = np.array(np.concatenate(([0],np.cumsum(areas*n))),dtype='int')
ns = np.diff(stair)
locs = [multipoly_sample(ns[i], mp.geoms[i]) for i in np.where(ns>0)[0]]
return np.concatenate([loc[0] for loc in locs]), np.concatenate([loc[1] for loc in locs])
lons = np.empty(n)
lats = np.empty(n)
done = 0
xmin = mp.bounds[0]*np.pi/180
ymin = mp.bounds[1]*np.pi/180
xmax = mp.bounds[2]*np.pi/180
ymax = mp.bounds[3]*np.pi/180
print 'Starting: n=%i'%n
while done < n:
x = np.atleast_1d(pm.runiform(xmin,xmax, size=n))
y = np.atleast_1d(np.arcsin(pm.runiform(np.sin(ymin),np.sin(ymax),size=n)))
points=[geom.Point([x[i]*180./np.pi,y[i]*180./np.pi]) for i in xrange(len(x))]
good = list(iterops.contains(mp, points, True))
n_good = min(n,len(good))
lons[done:done+n_good] = [p.coords[0][0] for p in good][:n-done]
lats[done:done+n_good] = [p.coords[0][1] for p in good][:n-done]
done += n_good
print '\tDid %i, %i remaining.'%(n_good,n-done)
# plot_unit(b,mp)
# b.plot(x*180./np.pi,y*180./np.pi,'r.')
#
# from IPython.Debugger import Pdb
# Pdb(color_scheme='Linux').set_trace()
print 'Filled'
return lons, lats
def exclude_ues(xy, unit, ue_shapefile):
"""
exclude_ues(xy,unit,ue_shapefile)
xy : sequence of points.
unit : The shapely polygon or multipolygon containing xy.
ue_shapefile : A NonSuckyShapeFile object.
Returns x and y filtered to be outside the polygons in the shapefile.
"""
if not unit.is_valid:
raise ValueError, 'invalid unit'
intersect_fracs = []
for ue in ue_shapefile:
if unit.intersects(ue):
xy = iterops.contains(unit, xy, True)
intersect_fracs.append(unit.intersection(ue).area / ue.area)
else:
intersect_fracs.append(0)
return xy, intersect_fracs
def multipoly_sample(n, mp, test=None, verbose=0):
"""
Returns uniformly-distributed points on the earth's surface
conditioned to be inside a multipolygon.
Not particularly fast.
"""
# b = basemap.Basemap(-180,-90,180,90)
if isinstance(mp, geometry.MultiPolygon):
if verbose>0:
print 'Breaking down multipolygon'
areas = [shapely_poly_area(p) for p in mp.geoms]
areas = np.array(areas)
areas /= np.sum(areas)
# ns = pm.rmultinomial(n, areas)
stair = np.round(np.concatenate(([0],np.cumsum(areas*n)))).astype('int')
ns = np.diff(stair)
locs = [multipoly_sample(ns[i], mp.geoms[i], test) for i in np.where(ns>0)[0]]
lons = np.concatenate([loc[0] for loc in locs])
lats = np.concatenate([loc[1] for loc in locs])
if len(lons) != n or len(lats) != n:
raise ValueError
return lons, lats
lons = np.empty(n)
lats = np.empty(n)
done = 0
xmin = mp.bounds[0]*np.pi/180
ymin = mp.bounds[1]*np.pi/180
xmax = mp.bounds[2]*np.pi/180
ymax = mp.bounds[3]*np.pi/180
if verbose>0:
print 'Starting: n=%i'%n
while done < n:
x = np.atleast_1d(pm.runiform(xmin,xmax, size=n))
y = np.atleast_1d(np.arcsin(pm.runiform(np.sin(ymin),np.sin(ymax),size=n)))
points=[geom.Point([x[i]*180./np.pi,y[i]*180./np.pi]) for i in xrange(len(x))]
good = list(iterops.contains(mp, points, True))
if test:
good = filter(lambda p: test(p.coords[0][0], p.coords[0][1]),good)
n_good = min(n,len(good))
lons[done:done+n_good] = [p.coords[0][0] for p in good][:n-done]
lats[done:done+n_good] = [p.coords[0][1] for p in good][:n-done]
done += n_good
if verbose>0:
print '\tDid %i, %i remaining.'%(n_good,n-done)
if verbose>0:
print 'Filled'
if test:
if not np.all([test(lon,lat) for lon,lat in zip(lons,lats)]):
raise ValueError, 'Test failed at some outputs'
if len(lons)!=n or len(lats)!=n:
raise ValueError
return lons, lats
elif count % 25 == 0:
sys.stdout.write('.')
sys.stdout.flush()
print str(count) + " coordinates found"
print "Matching points to regions"
f = open('os.dat', 'r')
count = 0
for line in f:
(region, wkt) = line.split("\t")
polygon = loads(wkt)
for point in iterops.contains(polygon, points, True):
fout.write("<%s> <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/within> <%s> .\n" % (point.uri, region))
fout.write("<%s> <http://data.ordnancesurvey.co.uk/ontology/spatialrelations/contains> <%s> .\n" % (region, point.uri))
count += 1
if count > 0:
if count % 1000 == 0:
print str(count) + " regions checked"
sys.stdout.flush()
elif count % 25 == 0:
sys.stdout.write('.')
sys.stdout.flush()
print str(count) + " regions checked"
f.close()
fout.close()
