def testSqliteWriting(self):
"""Test that writing a dataset to sqlite works."""
keywords = read_keywords(SHP_BASE + '.keywords')
layer = Vector(data=SHP_BASE + '.shp', keywords=keywords)
test_dir = temp_dir(sub_dir='test')
test_file = unique_filename(suffix='.sqlite', dir=test_dir)
layer.write_to_file(test_file, sublayer='foo')
def write_vector_data(data, projection, geometry, filename, keywords=None):
"""Write point data and any associated attributes to vector file
Input:
data: List of N dictionaries each with M fields where
M is the number of attributes.
A value of None is acceptable.
projection: WKT projection information
geometry: List of points or polygons.
filename: Output filename
keywords: Optional dictionary
Note: The only format implemented is GML and SHP so the extension
must be either .gml or .shp
# FIXME (Ole): When the GML driver is used,
# the spatial reference is not stored.
# I suspect this is a bug in OGR.
Background:
* http://www.gdal.org/ogr/ogr_apitut.html (last example)
* http://invisibleroads.com/tutorials/gdal-shapefile-points-save.html
"""
V = Vector(data, projection, geometry, keywords=keywords)
V.write_to_file(filename)
def testSqliteWriting(self):
"""Test that writing a dataset to sqlite works."""
keywords = read_keywords(SHP_BASE + '.keywords')
layer = Vector(data=SHP_BASE + '.shp', keywords=keywords)
test_dir = temp_dir(sub_dir='test')
test_file = unique_filename(suffix='.sqlite', dir=test_dir)
layer.write_to_file(test_file, sublayer='foo')
def test_sqlite_writing(self):
"""Test that writing a dataset to sqlite works."""
keywords = {}
layer = Vector(data=SHP_BASE + '.shp', keywords=keywords)
test_dir = temp_dir(sub_dir='test')
test_file = unique_filename(suffix='.sqlite', dir=test_dir)
layer.write_to_file(test_file, sublayer='foo')
self.assertTrue(os.path.exists(test_file))
def test_sqlite_writing(self):
"""Test that writing a dataset to sqlite works."""
keywords = read_keywords(SHP_BASE + ".keywords")
layer = Vector(data=SHP_BASE + ".shp", keywords=keywords)
test_dir = temp_dir(sub_dir="test")
test_file = unique_filename(suffix=".sqlite", dir=test_dir)
layer.write_to_file(test_file, sublayer="foo")
self.assertTrue(os.path.exists(test_file))
def test_sqlite_writing(self):
"""Test that writing a dataset to sqlite works."""
keywords = {}
layer = Vector(data=SHP_BASE + '.shp', keywords=keywords)
test_dir = temp_dir(sub_dir='test')
test_file = unique_filename(suffix='.sqlite', dir=test_dir)
layer.write_to_file(test_file, sublayer='foo')
self.assertTrue(os.path.exists(test_file))
def test_clip_points_by_polygons_with_holes0(self):
"""Points can be clipped by polygons with holes
"""
# Define an outer ring
outer_ring = numpy.array([[106.79, -6.233], [106.80, -6.24],
[106.78, -6.23], [106.77, -6.21],
[106.79, -6.233]])
# Define inner rings
inner_rings = [
numpy.array([[106.77827, -6.2252], [106.77775, -6.22378],
[106.78, -6.22311], [106.78017, -6.22530],
[106.77827, -6.2252]])[::-1],
numpy.array([[106.78652, -6.23215], [106.78642, -6.23075],
[106.78746, -6.23143], [106.78831, -6.23307],
[106.78652, -6.23215]])[::-1]
]
v = Vector(
geometry=[Polygon(outer_ring=outer_ring, inner_rings=inner_rings)])
assert v.is_polygon_data
# Write it to file
tmp_filename = unique_filename(suffix='.shp')
v.write_to_file(tmp_filename)
# Read polygon it back
L = read_layer(tmp_filename)
P = L.get_geometry(as_geometry_objects=True)[0]
outer_ring = P.outer_ring
inner_ring0 = P.inner_rings[0]
inner_ring1 = P.inner_rings[1]
# Make some test points
points = generate_random_points_in_bbox(outer_ring, 1000, seed=13)
# Clip to outer ring, excluding holes
indices = inside_polygon(points, P.outer_ring, holes=P.inner_rings)
# Sanity
for point in points[indices, :]:
# Must be inside outer ring
assert is_inside_polygon(point, outer_ring)
# But not in any of the inner rings
assert not is_inside_polygon(point, inner_ring0)
assert not is_inside_polygon(point, inner_ring1)
if False:
# Store for visual check
pol = Vector(geometry=[P])
tmp_filename = unique_filename(suffix='.shp')
pol.write_to_file(tmp_filename)
# print 'Polygon with holes written to %s' % tmp_filename
pts = Vector(geometry=points[indices, :])
tmp_filename = unique_filename(suffix='.shp')
pts.write_to_file(tmp_filename)
#new_geom = []
#new_data = []
#
#for i, d in enumerate(data):
# if d['affected']:
# g = geom[i]
# new_geom.append(g)
# new_data.append(d)
# Keep all polygons
new_geom = res.get_geometry()
new_data = res.get_data()
date = os.path.split(args.filename)[-1].split('_')[0]
v = Vector(geometry=new_geom,
data=new_data,
projection=res.projection,
keywords={
'category':
'hazard',
'subcategory':
'flood',
'title': ('%d hour flood forecast regions '
'in Jakarta at %s' % (args.hours, date))
})
polyforecast_filename = (os.path.splitext(tif_filename)[0] +
'_regions.shp')
v.write_to_file(polyforecast_filename)
print 'Wrote tagged polygons to %s' % polyforecast_filename
def test_tag_regions_by_flood(self):
"""Regions can be tagged correctly with data from flood forecasts
"""
threshold = 0.3
label = 'affected'
tif_filename = convert_netcdf2tif(self.nc_filename, 24, verbose=False)
region_filename = os.path.join(TESTDATA, 'rw_jakarta_singlepart.shp')
grid = read_layer(tif_filename)
polygons = read_layer(region_filename)
res = tag_polygons_by_grid(polygons, grid,
threshold=threshold,
tag=label)
os.remove(tif_filename)
geom = res.get_geometry()
data = res.get_data()
# Check correctness of affected regions
affected_geom = []
affected_data = []
for i, d in enumerate(data):
if d[label]:
g = geom[i]
affected_geom.append(g)
affected_data.append(d)
assert len(affected_geom) == 37
assert len(affected_data) == 37
# Check that every grid point exceeding threshold lies inside
# one of the polygons marked as affected
P, V = grid.to_vector_points()
flooded_points_geom = []
flooded_points_data = []
for i, point in enumerate(P):
val = V[i]
if val > threshold:
# Point that is flooded must be in one of the tagged polygons
found = False
for polygon in affected_geom:
if is_inside_polygon(point, polygon):
found = True
msg = ('No affected polygon was found for point [%f, %f] '
'with value %f' % (point[0], point[1], val))
verify(found, msg)
# Collected flooded points for visualisation
flooded_points_geom.append(point)
flooded_points_data.append({'depth': val})
# To generate files for visual inspection.
# See
# https://raw.github.com/AIFDR/inasafe/master/files/flood_tagging_test.png
# https://github.com/AIFDR/inasafe/blob/master/files/flood_tagging_test.tgz
tmp_filename = unique_filename(prefix='grid', suffix='.tif')
grid.write_to_file(tmp_filename)
#print 'Grid written to ', tmp_filename
tmp_filename = unique_filename(prefix='regions', suffix='.shp')
res.write_to_file(tmp_filename)
#print 'Regions written to ', tmp_filename
tmp_filename = unique_filename(prefix='flooded_points', suffix='.shp')
v = Vector(geometry=flooded_points_geom, data=flooded_points_data)
v.write_to_file(tmp_filename)
# but will reduce overall bounding box for buildings under
# consideration)
# geom = res.get_geometry()
# data = res.get_data()
# new_geom = []
# new_data = []
#
# for i, d in enumerate(data):
# if d['affected']:
# g = geom[i]
# new_geom.append(g)
# new_data.append(d)
# Keep all polygons
new_geom = res.get_geometry()
new_data = res.get_data()
date = os.path.split(args.filename)[-1].split('_')[0]
v = Vector(geometry=new_geom, data=new_data,
projection=res.projection,
keywords={'category': 'hazard',
'subcategory': 'flood',
'title': ('%d hour flood forecast regions '
'in Jakarta at %s' % (args.hours,
date))})
polyforecast_filename = (os.path.splitext(tif_filename)[0] +
'_regions.shp')
v.write_to_file(polyforecast_filename)
print 'Wrote tagged polygons to %s' % polyforecast_filename
def test_clip_points_by_polygons_with_holes0(self):
"""Points can be clipped by polygons with holes
"""
# Define an outer ring
outer_ring = numpy.array([[106.79, -6.233],
[106.80, -6.24],
[106.78, -6.23],
[106.77, -6.21],
[106.79, -6.233]])
# Define inner rings
inner_rings = [numpy.array([[106.77827, -6.2252],
[106.77775, -6.22378],
[106.78, -6.22311],
[106.78017, -6.22530],
[106.77827, -6.2252]])[::-1],
numpy.array([[106.78652, -6.23215],
[106.78642, -6.23075],
[106.78746, -6.23143],
[106.78831, -6.23307],
[106.78652, -6.23215]])[::-1]]
v = Vector(geometry=[Polygon(outer_ring=outer_ring,
inner_rings=inner_rings)])
assert v.is_polygon_data
# Write it to file
tmp_filename = unique_filename(suffix='.shp')
v.write_to_file(tmp_filename)
# Read polygon it back
L = read_layer(tmp_filename)
P = L.get_geometry(as_geometry_objects=True)[0]
outer_ring = P.outer_ring
inner_ring0 = P.inner_rings[0]
inner_ring1 = P.inner_rings[1]
# Make some test points
points = generate_random_points_in_bbox(outer_ring, 1000, seed=13)
# Clip to outer ring, excluding holes
indices = inside_polygon(points, P.outer_ring, holes=P.inner_rings)
# Sanity
for point in points[indices, :]:
# Must be inside outer ring
assert is_inside_polygon(point, outer_ring)
# But not in any of the inner rings
assert not is_inside_polygon(point, inner_ring0)
assert not is_inside_polygon(point, inner_ring1)
if False:
# Store for visual check
pol = Vector(geometry=[P])
tmp_filename = unique_filename(suffix='.shp')
pol.write_to_file(tmp_filename)
print 'Polygon with holes written to %s' % tmp_filename
pts = Vector(geometry=points[indices, :])
tmp_filename = unique_filename(suffix='.shp')
pts.write_to_file(tmp_filename)
print 'Clipped points written to %s' % tmp_filename
def test_clip_points_by_polygons_with_holes_real(self):
"""Points can be clipped by polygons with holes (real data)
"""
# Read real polygon with holes
filename = '%s/%s' % (TESTDATA, 'donut.shp')
L = read_layer(filename)
# --------------------------------------------
# Pick one polygon that has 2 inner rings
P = L.get_geometry(as_geometry_objects=True)[1]
outer_ring = P.outer_ring
inner_ring0 = P.inner_rings[0]
inner_ring1 = P.inner_rings[1]
# Make some test points
points_in_bbox = generate_random_points_in_bbox(outer_ring, 1000)
points_in_inner_ring0 = populate_polygon(inner_ring0, 2, seed=13)
points_in_inner_ring1 = populate_polygon(inner_ring1, 2, seed=17)
points = numpy.concatenate((points_in_bbox,
points_in_inner_ring0,
points_in_inner_ring1))
# Clip
indices = inside_polygon(points, P.outer_ring, holes=P.inner_rings)
# Sanity
for point in points[indices, :]:
# Must be inside outer ring
assert is_inside_polygon(point, outer_ring)
# But not in any of the inner rings
assert not is_inside_polygon(point, inner_ring0)
assert not is_inside_polygon(point, inner_ring1)
# ---------------------------------------------------------
# Pick a polygon that has 1 inner ring (nice visualisation)
P = L.get_geometry(as_geometry_objects=True)[9]
outer_ring = P.outer_ring
inner_ring = P.inner_rings[0]
# Make some test points
points = generate_random_points_in_bbox(outer_ring, 500)
# Clip
indices = inside_polygon(points, P.outer_ring, holes=P.inner_rings)
# Sanity
for point in points[indices, :]:
# Must be inside outer ring
assert is_inside_polygon(point, outer_ring)
# But not in the inner ring
assert not is_inside_polygon(point, inner_ring)
# Store for visual check (nice one!)
# Uncomment os.remove if you want see the layers
pol = Vector(geometry=[P])
tmp_filename = unique_filename(suffix='.shp')
pol.write_to_file(tmp_filename)
# print 'Polygon with holes written to %s' % tmp_filename
os.remove(tmp_filename)
pts = Vector(geometry=points[indices, :])
tmp_filename = unique_filename(suffix='.shp')
pts.write_to_file(tmp_filename)
# print 'Clipped points written to %s' % tmp_filename
os.remove(tmp_filename)
def test_tag_regions_by_flood(self):
"""Regions can be tagged correctly with data from flood forecasts.
"""
threshold = 0.3
label = 'affected'
tif_filename = convert_netcdf2tif(self.nc_filename, 24, verbose=False)
region_filename = os.path.join(TESTDATA, 'rw_jakarta_singlepart.shp')
grid = read_layer(tif_filename)
polygons = read_layer(region_filename)
res = tag_polygons_by_grid(polygons, grid,
threshold=threshold,
tag=label)
os.remove(tif_filename)
geom = res.get_geometry()
data = res.get_data()
# Check correctness of affected regions
affected_geom = []
affected_data = []
for i, d in enumerate(data):
if d[label]:
g = geom[i]
affected_geom.append(g)
affected_data.append(d)
assert len(affected_geom) == 37
assert len(affected_data) == 37
# Check that every grid point exceeding threshold lies inside
# one of the polygons marked as affected
P, V = grid.to_vector_points()
flooded_points_geom = []
flooded_points_data = []
for i, point in enumerate(P):
val = V[i]
if val > threshold:
# Point that is flooded must be in one of the tagged polygons
found = False
for polygon in affected_geom:
if is_inside_polygon(point, polygon):
found = True
msg = ('No affected polygon was found for point [%f, %f] '
'with value %f' % (point[0], point[1], val))
verify(found, msg)
# Collected flooded points for visualisation
flooded_points_geom.append(point)
flooded_points_data.append({'depth': val})
# To generate files for visual inspection.
# See
# https://raw.github.com/AIFDR/inasafe/master/files/flood_tagging_test.png
# https://github.com/AIFDR/inasafe/blob/master/files/flood_tagging_test.tgz
tmp_filename = unique_filename(prefix='grid', suffix='.tif')
grid.write_to_file(tmp_filename)
#print 'Grid written to ', tmp_filename
tmp_filename = unique_filename(prefix='regions', suffix='.shp')
res.write_to_file(tmp_filename)
#print 'Regions written to ', tmp_filename
tmp_filename = unique_filename(prefix='flooded_points', suffix='.shp')
v = Vector(geometry=flooded_points_geom, data=flooded_points_data)
v.write_to_file(tmp_filename)
def processFloodEvent(netcdf_file=None, hours=24):
"""A function to process netcdf_file to a forecast file.
"""
print 'Start flood forecasting'
if netcdf_file is None:
# retrieve data from the web
netcdf_file = download_file_url(netcdf_url, forecast_directory)
else:
netcdf_file = download_file_url(netcdf_url, name=netcdf_file,
download_directory=forecast_directory)
print 'Do flood forecasting for %s ...' % netcdf_file
# # check if a forecasting file has been created or not
# is_exist, polyforecast_filepath = get_result_file_name(netcdf_file, hours)
#
# if is_exist:
# print 'Current flood forecasting has been already created.'
# print 'You can look it at %s' % polyforecast_filepath
# return
# convert to tif
# tif_file = polyforecast_filepath.replace('_regions.shp', '.tif')
tif_filename = convert_netcdf2tif(netcdf_file, hours,
verbose=False, output_dir=flood_directory)
print 'tif_file', tif_filename
tif_file = read_layer(tif_filename)
# check if there is another file with the same name
# if so, do not do the forecasting
polyforecast_filepath = tif_filename.replace('.tif', '_regions.shp')
zip_filename = polyforecast_filepath.replace('.shp', '.zip')
if os.path.isfile(zip_filename):
print ('File %s is exist, so we do not do the forecasting'
% zip_filename)
else:
my_polygons = read_layer(polygons_path)
my_result = tag_polygons_by_grid(my_polygons, tif_file, threshold=0.3,
tag='affected')
new_geom = my_result.get_geometry()
new_data = my_result.get_data()
date = os.path.split(netcdf_file)[-1].split('_')[0]
v = Vector(geometry=new_geom, data=new_data,
projection=my_result.projection,
keywords={'category': 'hazard',
'subcategory': 'flood',
'title': ('%d hour flood forecast regions '
'in Jakarta at %s' % (hours,
date))})
print 'polyforecast_filepath', polyforecast_filepath
v.write_to_file(polyforecast_filepath)
print 'Wrote tagged polygons to %s' % polyforecast_filepath
# zip all file
if os.path.isfile(zip_filename):
print 'Has been zipped to %s' % zip_filename
else:
zip_shp(polyforecast_filepath, extra_ext=['.keywords'],
remove_file=True)
print 'Zipped to %s' % zip_filename
def test_clip_raster_by_polygons(self):
"""Raster grids can be clipped by polygon layers
# See qgis project in test data: raster_point_and_clipping_test.qgs
"""
# Name input files
poly = join(TESTDATA, 'kabupaten_jakarta_singlepart.shp')
grid = join(TESTDATA, 'population_5x5_jakarta.asc')
# Get layers using API
P = read_layer(poly)
R = read_layer(grid)
M = len(P)
N = len(R)
assert N == 56
# Clip
C = clip_raster_by_polygons(R, P)
assert len(C) == M
# Check points inside polygon
tot = 0
for c in C:
tot += len(c)
assert tot == 14
# Check that points are inside the right polygon
for i, polygon in enumerate(P.get_geometry()):
points = C[i][0]
values = C[i][1]
# Sanity first
for point in points:
assert is_inside_polygon(point, polygon)
# Specific tests against raster pixel values inside polygons
# The values are read from qgis
if i == 0:
assert len(points) == 6
assert numpy.allclose(values[0], 200951)
assert numpy.allclose(values[1], 283237)
assert numpy.allclose(values[2], 278385)
assert numpy.allclose(values[3], 516061)
assert numpy.allclose(values[4], 207414)
assert numpy.allclose(values[5], 344466)
elif i == 1:
assert len(points) == 2
msg = ('Got wrong coordinates %s, expected %s' %
(str(points[0, :]), str([106.8125, -6.1875])))
assert numpy.allclose(points[0, :], [106.8125, -6.1875]), msg
assert numpy.allclose(points[1, :], [106.8541667, -6.1875])
assert numpy.allclose(values[0], 331942)
assert numpy.allclose(values[1], 496446)
elif i == 2:
assert len(points) == 7
assert numpy.allclose(values[0], 268579)
assert numpy.allclose(values[1], 155795)
assert numpy.allclose(values[2], 403674)
assert numpy.allclose(values[3], 259280)
assert numpy.allclose(values[4], 284526)
assert numpy.allclose(values[5], 334370)
assert numpy.allclose(values[6], 143325)
elif i == 3:
assert len(points) == 0 # Degenerate
elif i == 4:
assert len(points) == 0 # Degenerate
elif i == 5:
assert len(points) == 8
assert numpy.allclose(values[0], 279103)
assert numpy.allclose(values[1], 205762)
assert numpy.allclose(values[2], 428705)
assert numpy.allclose(values[3], 331093)
assert numpy.allclose(values[4], 227514)
assert numpy.allclose(values[5], 249308)
assert numpy.allclose(values[6], 215739)
assert numpy.allclose(values[7], 147447)
elif i == 6:
assert len(points) == 6
assert numpy.allclose(values[0], 61836.4)
assert numpy.allclose(values[1], 165723)
assert numpy.allclose(values[2], 151307)
assert numpy.allclose(values[3], 343787)
assert numpy.allclose(values[4], 303627)
assert numpy.allclose(values[5], 225232)
# Generate layer objects
values = [{'value': x} for x in C[i][1]]
point_layer = Vector(data=values,
geometry=points,
projection=P.get_projection())
if len(point_layer) > 0:
# Geometry is only defined for layers that are not degenerate
assert point_layer.is_point_data
polygon_layer = Vector(geometry=[polygon],
projection=P.get_projection())
assert polygon_layer.is_polygon_data
# Generate spatial data for visualisation with e.g. QGIS
if False:
point_layer.write_to_file('points_%i.shp' % i)
polygon_layer.write_to_file('polygon_%i.shp' % i)
def process_flood_event(netcdf_file=None, hours=24):
"""A function to process this_netcdf_file to a forecast file.
:param netcdf_file: The netcdf file. If it's None the download it.
:param hours: Positive integer determining how many bands to use.
:type hours: int
"""
print 'Start flood forecasting'
if netcdf_file is None:
# retrieve data from the web
netcdf_file = download_file_url(netcdf_url, forecast_directory)
else:
netcdf_file = download_file_url(netcdf_url,
name=netcdf_file,
download_directory=forecast_directory)
print 'Do flood forecasting for %s ...' % netcdf_file
## check if a forecasting file has been created or not
# is_exist, polyforecast_filepath = get_result_file_name(this_netcdf_file,
# hours)
#
#if is_exist:
# print 'Current flood forecasting has been already created.'
# print 'You can look it at %s' % polyforecast_filepath
# return
# convert to tif
# tif_file = polyforecast_filepath.replace('_regions.shp', '.tif')
tif_filename = convert_netcdf2tif(netcdf_file,
hours,
verbose=False,
output_dir=flood_directory)
print 'tif_file', tif_filename
tif_file = read_layer(tif_filename)
# check if there is another file with the same name
# if so, do not do the forecasting
polyforecast_filepath = tif_filename.replace('.tif', '_regions.shp')
zip_filename = polyforecast_filepath.replace('.shp', '.zip')
if os.path.isfile(zip_filename):
print('File %s is exist, so we do not do the forecasting' %
zip_filename)
else:
polygons = read_layer(polygons_path)
result = tag_polygons_by_grid(polygons,
tif_file,
threshold=0.3,
tag='affected')
new_geom = result.get_geometry()
new_data = result.get_data()
date = os.path.split(netcdf_file)[-1].split('_')[0]
v = Vector(geometry=new_geom,
data=new_data,
projection=result.projection,
keywords={
'category':
'hazard',
'subcategory':
'flood',
'title': ('%d hour flood forecast regions '
'in Jakarta at %s' % (hours, date))
})
print 'polyforecast_filepath', polyforecast_filepath
v.write_to_file(polyforecast_filepath)
print 'Wrote tagged polygons to %s' % polyforecast_filepath
# zip all file
if os.path.isfile(zip_filename):
print 'Has been zipped to %s' % zip_filename
else:
zip_shp(polyforecast_filepath,
extra_ext=['.keywords'],
remove_file=True)
print 'Zipped to %s' % zip_filename
def test_clip_raster_by_polygons(self):
"""Raster grids can be clipped by polygon layers
# See qgis project in test data: raster_point_and_clipping_test.qgs
"""
# Name input files
poly = join(TESTDATA, 'kabupaten_jakarta_singlepart.shp')
grid = join(TESTDATA, 'population_5x5_jakarta.asc')
# Get layers using API
P = read_layer(poly)
R = read_layer(grid)
M = len(P)
N = len(R)
assert N == 56
# Clip
C = clip_raster_by_polygons(R, P)
assert len(C) == M
# Check points inside polygon
tot = 0
for c in C:
tot += len(c)
assert tot == 14
# Check that points are inside the right polygon
for i, polygon in enumerate(P.get_geometry()):
points = C[i][0]
values = C[i][1]
# Sanity first
for point in points:
assert is_inside_polygon(point, polygon)
# Specific tests against raster pixel values inside polygons
# The values are read from qgis
if i == 0:
assert len(points) == 6
assert numpy.allclose(values[0], 200951)
assert numpy.allclose(values[1], 283237)
assert numpy.allclose(values[2], 278385)
assert numpy.allclose(values[3], 516061)
assert numpy.allclose(values[4], 207414)
assert numpy.allclose(values[5], 344466)
elif i == 1:
assert len(points) == 2
msg = ('Got wrong coordinates %s, expected %s'
% (str(points[0, :]), str([106.8125, -6.1875])))
assert numpy.allclose(points[0, :], [106.8125, -6.1875]), msg
assert numpy.allclose(points[1, :], [106.8541667, -6.1875])
assert numpy.allclose(values[0], 331942)
assert numpy.allclose(values[1], 496446)
elif i == 2:
assert len(points) == 7
assert numpy.allclose(values[0], 268579)
assert numpy.allclose(values[1], 155795)
assert numpy.allclose(values[2], 403674)
assert numpy.allclose(values[3], 259280)
assert numpy.allclose(values[4], 284526)
assert numpy.allclose(values[5], 334370)
assert numpy.allclose(values[6], 143325)
elif i == 3:
assert len(points) == 0 # Degenerate
elif i == 4:
assert len(points) == 0 # Degenerate
elif i == 5:
assert len(points) == 8
assert numpy.allclose(values[0], 279103)
assert numpy.allclose(values[1], 205762)
assert numpy.allclose(values[2], 428705)
assert numpy.allclose(values[3], 331093)
assert numpy.allclose(values[4], 227514)
assert numpy.allclose(values[5], 249308)
assert numpy.allclose(values[6], 215739)
assert numpy.allclose(values[7], 147447)
elif i == 6:
assert len(points) == 6
assert numpy.allclose(values[0], 61836.4)
assert numpy.allclose(values[1], 165723)
assert numpy.allclose(values[2], 151307)
assert numpy.allclose(values[3], 343787)
assert numpy.allclose(values[4], 303627)
assert numpy.allclose(values[5], 225232)
# Generate layer objects
values = [{'value': x} for x in C[i][1]]
point_layer = Vector(data=values, geometry=points,
projection=P.get_projection())
if len(point_layer) > 0:
# Geometry is only defined for layers that are not degenerate
assert point_layer.is_point_data
polygon_layer = Vector(geometry=[polygon],
projection=P.get_projection())
assert polygon_layer.is_polygon_data
# Generate spatial data for visualisation with e.g. QGIS
if False:
point_layer.write_to_file('points_%i.shp' % i)
polygon_layer.write_to_file('polygon_%i.shp' % i)
