def test_polygonize(self):
"""Test if polygonize works"""
geometry = polygonize(
self.raster, threshold_min=1.0, threshold_max=1.5)
# Result is one square
self.assertTrue(geometry.isGeosValid())
self.assertFalse(geometry.isMultipart())
# noinspection PyArgumentEqualDefault
geometry = polygonize(self.raster, threshold_min=0.0)
# Result is several polygons
self.assertTrue(geometry.isGeosValid())
self.assertTrue(geometry.isMultipart())
expected = QgsVectorLayer(VECTOR_BASE + '.shp', 'test', 'ogr')
for feature in expected.getFeatures():
# the layer has one feature only
expected_geom = feature.geometry()
self.assertTrue((geometry.isGeosEqual(expected_geom)))
def run(self, layers):
"""Experimental impact function.
Input
layers: List of layers expected to contain
H: Polygon layer of inundation areas
E: Vector layer of roads
"""
target_field = self.parameters['target_field']
road_type_field = self.parameters['road_type_field']
threshold_min = self.parameters['min threshold [m]']
threshold_max = self.parameters['max threshold [m]']
if threshold_min > threshold_max:
message = tr('''The minimal threshold is
greater then the maximal specified threshold.
Please check the values.''')
raise GetDataError(message)
# Extract data
H = get_hazard_layer(layers) # Flood
E = get_exposure_layer(layers) # Roads
question = get_question(H.get_name(), E.get_name(), self)
H = H.get_layer()
E = E.get_layer()
# Get necessary width and height of raster
height = (self.extent[3] - self.extent[1]) / H.rasterUnitsPerPixelY()
height = int(height)
width = (self.extent[2] - self.extent[0]) / H.rasterUnitsPerPixelX()
width = int(width)
# Align raster extent and self.extent
raster_extent = H.dataProvider().extent()
xmin = raster_extent.xMinimum()
xmax = raster_extent.xMaximum()
ymin = raster_extent.yMinimum()
ymax = raster_extent.yMaximum()
x_delta = (xmax - xmin) / H.width()
x = xmin
for i in range(H.width()):
if abs(x - self.extent[0]) < x_delta:
# We have found the aligned raster boundary
break
x += x_delta
_ = i
y_delta = (ymax - ymin) / H.height()
y = ymin
for i in range(H.width()):
if abs(y - self.extent[1]) < y_delta:
# We have found the aligned raster boundary
break
y += y_delta
clip_extent = [x, y, x + width * x_delta, y + height * y_delta]
# Clip and polygonize
small_raster = clip_raster(H, width, height,
QgsRectangle(*clip_extent))
flooded_polygon = polygonize(small_raster, threshold_min,
threshold_max)
# Filter geometry and data using the extent
extent = QgsRectangle(*self.extent)
request = QgsFeatureRequest()
request.setFilterRect(extent)
if flooded_polygon is None:
message = tr('''There are no objects
in the hazard layer with
"value">'%s'.
Please check the value or use other
extent.''' % (threshold_min, ))
raise GetDataError(message)
# Clip exposure by the extent
extent_as_polygon = QgsGeometry().fromRect(extent)
line_layer = clip_by_polygon(E, extent_as_polygon)
# Find inundated roads, mark them
line_layer = split_by_polygon(line_layer,
flooded_polygon,
request,
mark_value=(target_field, 1))
# Find inundated roads, mark them
# line_layer = split_by_polygon(
# E,
# flooded_polygon,
# request,
# mark_value=(target_field, 1))
target_field_index = line_layer.dataProvider().\
fieldNameIndex(target_field)
# Generate simple impact report
epsg = get_utm_epsg(self.extent[0], self.extent[1])
output_crs = QgsCoordinateReferenceSystem(epsg)
transform = QgsCoordinateTransform(E.crs(), output_crs)
road_len = flooded_len = 0 # Length of roads
roads_by_type = dict() # Length of flooded roads by types
roads_data = line_layer.getFeatures()
road_type_field_index = line_layer.fieldNameIndex(road_type_field)
for road in roads_data:
attributes = road.attributes()
road_type = attributes[road_type_field_index]
if road_type.__class__.__name__ == 'QPyNullVariant':
road_type = tr('Other')
geom = road.geometry()
geom.transform(transform)
length = geom.length()
road_len += length
if road_type not in roads_by_type:
roads_by_type[road_type] = {'flooded': 0, 'total': 0}
roads_by_type[road_type]['total'] += length
if attributes[target_field_index] == 1:
flooded_len += length
roads_by_type[road_type]['flooded'] += length
table_body = [
question,
TableRow([
tr('Road Type'),
tr('Flooded in the threshold (m)'),
tr('Total (m)')
],
header=True),
TableRow([tr('All'), int(flooded_len),
int(road_len)])
]
table_body.append(TableRow(tr('Breakdown by road type'), header=True))
for t, v in roads_by_type.iteritems():
table_body.append(TableRow([t,
int(v['flooded']),
int(v['total'])]))
impact_summary = Table(table_body).toNewlineFreeString()
map_title = tr('Roads inundated')
style_classes = [
dict(label=tr('Not Inundated'),
value=0,
colour='#1EFC7C',
transparency=0,
size=0.5),
dict(label=tr('Inundated'),
value=1,
colour='#F31A1C',
transparency=0,
size=0.5)
]
style_info = dict(target_field=target_field,
style_classes=style_classes,
style_type='categorizedSymbol')
# Convert QgsVectorLayer to inasafe layer and return it
line_layer = Vector(data=line_layer,
name=tr('Flooded roads'),
keywords={
'impact_summary': impact_summary,
'map_title': map_title,
'target_field': target_field
},
style_info=style_info)
return line_layer
def run(self, layers):
"""
Experimental impact function
Input
layers: List of layers expected to contain
H: Polygon layer of inundation areas
E: Vector layer of roads
"""
target_field = self.parameters['target_field']
road_type_field = self.parameters['road_type_field']
threshold_min = self.parameters['min threshold [m]']
threshold_max = self.parameters['max threshold [m]']
if threshold_min > threshold_max:
message = tr('''The minimal threshold is
greater then the maximal specified threshold.
Please check the values.''')
raise GetDataError(message)
# Extract data
H = get_hazard_layer(layers) # Flood
E = get_exposure_layer(layers) # Roads
question = get_question(
H.get_name(), E.get_name(), self)
H = H.get_layer()
E = E.get_layer()
# Get necessary width and height of raster
height = (self.extent[3] - self.extent[1]) / H.rasterUnitsPerPixelY()
height = int(height)
width = (self.extent[2] - self.extent[0]) / H.rasterUnitsPerPixelX()
width = int(width)
# Align raster extent and self.extent
raster_extent = H.dataProvider().extent()
xmin = raster_extent.xMinimum()
xmax = raster_extent.xMaximum()
ymin = raster_extent.yMinimum()
ymax = raster_extent.yMaximum()
x_delta = (xmax - xmin) / H.width()
x = xmin
for i in range(H.width()):
if abs(x - self.extent[0]) < x_delta:
# We have found the aligned raster boundary
break
x += x_delta
_ = i
y_delta = (ymax - ymin) / H.height()
y = ymin
for i in range(H.width()):
if abs(y - self.extent[1]) < y_delta:
# We have found the aligned raster boundary
break
y += y_delta
clip_extent = [x, y, x + width * x_delta, y + height * y_delta]
# Clip and polygonize
small_raster = clip_raster(
H, width, height, QgsRectangle(*clip_extent))
flooded_polygon = polygonize(
small_raster, threshold_min, threshold_max)
# Filter geometry and data using the extent
extent = QgsRectangle(*self.extent)
request = QgsFeatureRequest()
request.setFilterRect(extent)
if flooded_polygon is None:
message = tr('''There are no objects
in the hazard layer with
"value">'%s'.
Please check the value or use other
extent.''' % (threshold_min, ))
raise GetDataError(message)
# Clip exposure by the extent
extent_as_polygon = QgsGeometry().fromRect(extent)
line_layer = clip_by_polygon(
E,
extent_as_polygon
)
# Find inundated roads, mark them
line_layer = split_by_polygon(
line_layer,
flooded_polygon,
request,
mark_value=(target_field, 1))
# Find inundated roads, mark them
# line_layer = split_by_polygon(
# E,
# flooded_polygon,
# request,
# mark_value=(target_field, 1))
target_field_index = line_layer.dataProvider().\
fieldNameIndex(target_field)
# Generate simple impact report
epsg = get_utm_epsg(self.extent[0], self.extent[1])
output_crs = QgsCoordinateReferenceSystem(epsg)
transform = QgsCoordinateTransform(E.crs(), output_crs)
road_len = flooded_len = 0 # Length of roads
roads_by_type = dict() # Length of flooded roads by types
roads_data = line_layer.getFeatures()
road_type_field_index = line_layer.fieldNameIndex(road_type_field)
for road in roads_data:
attributes = road.attributes()
road_type = attributes[road_type_field_index]
if road_type.__class__.__name__ == 'QPyNullVariant':
road_type = tr('Other')
geom = road.geometry()
geom.transform(transform)
length = geom.length()
road_len += length
if not road_type in roads_by_type:
roads_by_type[road_type] = {'flooded': 0, 'total': 0}
roads_by_type[road_type]['total'] += length
if attributes[target_field_index] == 1:
flooded_len += length
roads_by_type[road_type]['flooded'] += length
table_body = [
question,
TableRow([
tr('Road Type'),
tr('Flooded in the threshold (m)'),
tr('Total (m)')],
header=True),
TableRow([
tr('All'),
int(flooded_len),
int(road_len)])]
table_body.append(TableRow(
tr('Breakdown by road type'), header=True))
for t, v in roads_by_type.iteritems():
table_body.append(
TableRow([t, int(v['flooded']), int(v['total'])])
)
impact_summary = Table(table_body).toNewlineFreeString()
map_title = tr('Roads inundated')
style_classes = [dict(label=tr('Not Inundated'), value=0,
colour='#1EFC7C', transparency=0, size=0.5),
dict(label=tr('Inundated'), value=1,
colour='#F31A1C', transparency=0, size=0.5)]
style_info = dict(target_field=target_field,
style_classes=style_classes,
style_type='categorizedSymbol')
# Convert QgsVectorLayer to inasafe layer and return it
line_layer = Vector(data=line_layer,
name=tr('Flooded roads'),
keywords={'impact_summary': impact_summary,
'map_title': map_title,
'target_field': target_field},
style_info=style_info)
return line_layer