def run(self):
"""Run the impact function.
:returns: A new line layer with inundated roads marked.
:type: safe_layer
"""
target_field = self.target_field
# Get parameters from layer's keywords
road_class_field = self.exposure.keyword('road_class_field')
exposure_value_mapping = self.exposure.keyword('value_mapping')
# Get parameters from IF parameter
threshold_min = self.parameters['min threshold'].value
threshold_max = self.parameters['max threshold'].value
if threshold_min > threshold_max:
message = tr(
'The minimal threshold is greater than the maximal specified '
'threshold. Please check the values.')
raise GetDataError(message)
# reproject self.extent to the hazard projection
hazard_crs = self.hazard.layer.crs()
hazard_authid = hazard_crs.authid()
if hazard_authid == 'EPSG:4326':
viewport_extent = self.requested_extent
else:
geo_crs = QgsCoordinateReferenceSystem()
geo_crs.createFromSrid(4326)
viewport_extent = extent_to_geo_array(
QgsRectangle(*self.requested_extent), geo_crs, hazard_crs)
# Clip hazard raster
small_raster = align_clip_raster(self.hazard.layer, viewport_extent)
# Filter geometry and data using the extent
ct = QgsCoordinateTransform(
QgsCoordinateReferenceSystem("EPSG:4326"),
self.exposure.layer.crs())
extent = ct.transformBoundingBox(QgsRectangle(*self.requested_extent))
request = QgsFeatureRequest()
request.setFilterRect(extent)
# create template for the output layer
line_layer_tmp = create_layer(self.exposure.layer)
new_field = QgsField(target_field, QVariant.Int)
line_layer_tmp.dataProvider().addAttributes([new_field])
line_layer_tmp.updateFields()
# create empty output layer and load it
filename = unique_filename(suffix='.shp')
QgsVectorFileWriter.writeAsVectorFormat(
line_layer_tmp, filename, "utf-8", None, "ESRI Shapefile")
line_layer = QgsVectorLayer(filename, "flooded roads", "ogr")
# Create vector features from the flood raster
# For each raster cell there is one rectangular polygon
# Data also get spatially indexed for faster operation
index, flood_cells_map = _raster_to_vector_cells(
small_raster,
threshold_min,
threshold_max,
self.exposure.layer.crs())
if len(flood_cells_map) == 0:
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)
# Do the heavy work - for each road get flood polygon for that area and
# do the intersection/difference to find out which parts are flooded
_intersect_lines_with_vector_cells(
self.exposure.layer,
request,
index,
flood_cells_map,
line_layer,
target_field)
target_field_index = line_layer.dataProvider().\
fieldNameIndex(target_field)
# Generate simple impact report
epsg = get_utm_epsg(self.requested_extent[0], self.requested_extent[1])
output_crs = QgsCoordinateReferenceSystem(epsg)
transform = QgsCoordinateTransform(
self.exposure.layer.crs(), output_crs)
classes = [tr('Flooded in the threshold (m)')]
self.init_report_var(classes)
if line_layer.featureCount() < 1:
raise ZeroImpactException()
roads_data = line_layer.getFeatures()
road_type_field_index = line_layer.fieldNameIndex(road_class_field)
for road in roads_data:
attributes = road.attributes()
usage = attributes[road_type_field_index]
usage = main_type(usage, exposure_value_mapping)
geom = road.geometry()
geom.transform(transform)
length = geom.length()
affected = False
if attributes[target_field_index] == 1:
affected = True
self.classify_feature(classes[0], usage, length, affected)
self.reorder_dictionaries()
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')
impact_data = self.generate_data()
extra_keywords = {
'map_title': self.metadata().key('map_title'),
'legend_title': self.metadata().key('legend_title'),
'target_field': target_field
}
impact_layer_keywords = self.generate_impact_keywords(extra_keywords)
# Convert QgsVectorLayer to inasafe layer and return it
impact_layer = Vector(
data=line_layer,
name=self.metadata().key('layer_name'),
keywords=impact_layer_keywords,
style_info=style_info)
impact_layer.impact_data = impact_data
self._impact = impact_layer
return impact_layer
def run(self):
"""Run the impact function.
:returns: A new line layer with inundated roads marked.
:type: safe_layer
"""
target_field = self.target_field
# Get parameters from layer's keywords
road_class_field = self.exposure.keyword('road_class_field')
exposure_value_mapping = self.exposure.keyword('value_mapping')
# Get parameters from IF parameter
threshold_min = self.parameters['min threshold'].value
threshold_max = self.parameters['max threshold'].value
if threshold_min > threshold_max:
message = tr(
'The minimal threshold is greater than the maximal specified '
'threshold. Please check the values.')
raise GetDataError(message)
# reproject self.extent to the hazard projection
hazard_crs = self.hazard.layer.crs()
hazard_authid = hazard_crs.authid()
if hazard_authid == 'EPSG:4326':
viewport_extent = self.requested_extent
else:
geo_crs = QgsCoordinateReferenceSystem()
geo_crs.createFromSrid(4326)
viewport_extent = extent_to_geo_array(
QgsRectangle(*self.requested_extent), geo_crs, hazard_crs)
# Clip hazard raster
small_raster = align_clip_raster(self.hazard.layer, viewport_extent)
# Filter geometry and data using the extent
ct = QgsCoordinateTransform(
QgsCoordinateReferenceSystem("EPSG:4326"),
self.exposure.layer.crs())
extent = ct.transformBoundingBox(QgsRectangle(*self.requested_extent))
request = QgsFeatureRequest()
request.setFilterRect(extent)
# create template for the output layer
line_layer_tmp = create_layer(self.exposure.layer)
new_field = QgsField(target_field, QVariant.Int)
line_layer_tmp.dataProvider().addAttributes([new_field])
line_layer_tmp.updateFields()
# create empty output layer and load it
filename = unique_filename(suffix='.shp')
QgsVectorFileWriter.writeAsVectorFormat(
line_layer_tmp, filename, "utf-8", None, "ESRI Shapefile")
line_layer = QgsVectorLayer(filename, "flooded roads", "ogr")
# Create vector features from the flood raster
# For each raster cell there is one rectangular polygon
# Data also get spatially indexed for faster operation
index, flood_cells_map = _raster_to_vector_cells(
small_raster,
threshold_min,
threshold_max,
self.exposure.layer.crs())
if len(flood_cells_map) == 0:
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)
# Do the heavy work - for each road get flood polygon for that area and
# do the intersection/difference to find out which parts are flooded
_intersect_lines_with_vector_cells(
self.exposure.layer,
request,
index,
flood_cells_map,
line_layer,
target_field)
target_field_index = line_layer.dataProvider().\
fieldNameIndex(target_field)
# Generate simple impact report
epsg = get_utm_epsg(self.requested_extent[0], self.requested_extent[1])
output_crs = QgsCoordinateReferenceSystem(epsg)
transform = QgsCoordinateTransform(
self.exposure.layer.crs(), output_crs)
classes = [tr('Flooded in the threshold (m)')]
self.init_report_var(classes)
if line_layer.featureCount() < 1:
raise ZeroImpactException()
roads_data = line_layer.getFeatures()
road_type_field_index = line_layer.fieldNameIndex(road_class_field)
for road in roads_data:
attributes = road.attributes()
usage = attributes[road_type_field_index]
usage = main_type(usage, exposure_value_mapping)
geom = road.geometry()
geom.transform(transform)
length = geom.length()
affected = False
if attributes[target_field_index] == 1:
affected = True
self.classify_feature(classes[0], usage, length, affected)
self.reorder_dictionaries()
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')
impact_data = self.generate_data()
extra_keywords = {
'map_title': self.map_title(),
'legend_title': self.metadata().key('legend_title'),
'target_field': target_field
}
impact_layer_keywords = self.generate_impact_keywords(extra_keywords)
# Convert QgsVectorLayer to inasafe layer and return it
impact_layer = Vector(
data=line_layer,
name=self.map_title(),
keywords=impact_layer_keywords,
style_info=style_info)
impact_layer.impact_data = impact_data
self._impact = impact_layer
return impact_layer
def run(self):
"""Run the impact function.
:returns: A new line layer with inundated roads marked.
:type: safe_layer
"""
# Thresholds for tsunami hazard zone breakdown.
low_max = self.parameters['low_threshold'].value
medium_max = self.parameters['medium_threshold'].value
high_max = self.parameters['high_threshold'].value
target_field = self.target_field
# Get parameters from layer's keywords
road_class_field = self.exposure.keyword('road_class_field')
exposure_value_mapping = self.exposure.keyword('value_mapping')
# reproject self.extent to the hazard projection
hazard_crs = self.hazard.layer.crs()
hazard_authid = hazard_crs.authid()
if hazard_authid == 'EPSG:4326':
viewport_extent = self.requested_extent
else:
geo_crs = QgsCoordinateReferenceSystem()
geo_crs.createFromSrid(4326)
viewport_extent = extent_to_geo_array(
QgsRectangle(*self.requested_extent), geo_crs, hazard_crs)
# Clip hazard raster
small_raster = align_clip_raster(self.hazard.layer, viewport_extent)
# Create vector features from the flood raster
# For each raster cell there is one rectangular polygon
# Data also get spatially indexed for faster operation
ranges = ranges_according_thresholds(low_max, medium_max, high_max)
index, flood_cells_map = _raster_to_vector_cells(
small_raster,
ranges,
self.exposure.layer.crs())
# Filter geometry and data using the extent
ct = QgsCoordinateTransform(
QgsCoordinateReferenceSystem("EPSG:4326"),
self.exposure.layer.crs())
extent = ct.transformBoundingBox(QgsRectangle(*self.requested_extent))
request = QgsFeatureRequest()
request.setFilterRect(extent)
# create template for the output layer
line_layer_tmp = create_layer(self.exposure.layer)
new_field = QgsField(target_field, QVariant.Int)
line_layer_tmp.dataProvider().addAttributes([new_field])
line_layer_tmp.updateFields()
# create empty output layer and load it
filename = unique_filename(suffix='.shp')
QgsVectorFileWriter.writeAsVectorFormat(
line_layer_tmp, filename, "utf-8", None, "ESRI Shapefile")
line_layer = QgsVectorLayer(filename, "flooded roads", "ogr")
# Do the heavy work - for each road get flood polygon for that area and
# do the intersection/difference to find out which parts are flooded
_intersect_lines_with_vector_cells(
self.exposure.layer,
request,
index,
flood_cells_map,
line_layer,
target_field)
target_field_index = line_layer.dataProvider().\
fieldNameIndex(target_field)
# Generate simple impact report
epsg = get_utm_epsg(self.requested_extent[0], self.requested_extent[1])
output_crs = QgsCoordinateReferenceSystem(epsg)
transform = QgsCoordinateTransform(
self.exposure.layer.crs(), output_crs)
# Roads breakdown
self.init_report_var(self.hazard_classes)
if line_layer.featureCount() < 1:
raise ZeroImpactException()
roads_data = line_layer.getFeatures()
road_type_field_index = line_layer.fieldNameIndex(road_class_field)
for road in roads_data:
attributes = road.attributes()
affected = attributes[target_field_index]
if isinstance(affected, QPyNullVariant):
continue
else:
hazard_zone = self.hazard_classes[affected]
usage = attributes[road_type_field_index]
usage = main_type(usage, exposure_value_mapping)
geom = road.geometry()
geom.transform(transform)
length = geom.length()
affected = False
num_classes = len(self.hazard_classes)
if attributes[target_field_index] in range(num_classes):
affected = True
self.classify_feature(hazard_zone, usage, length, affected)
self.reorder_dictionaries()
style_classes = [
# FIXME 0 - 0.1
dict(
label=self.hazard_classes[0] + ': 0m',
value=0,
colour='#00FF00',
transparency=0,
size=1
),
dict(
label=self.hazard_classes[1] + ': >0 - %.1f m' % low_max,
value=1,
colour='#FFFF00',
transparency=0,
size=1
),
dict(
label=self.hazard_classes[2] + ': %.1f - %.1f m' % (
low_max + 0.1, medium_max),
value=2,
colour='#FFB700',
transparency=0,
size=1
),
dict(
label=self.hazard_classes[3] + ': %.1f - %.1f m' % (
medium_max + 0.1, high_max),
value=3,
colour='#FF6F00',
transparency=0,
size=1
),
dict(
label=self.hazard_classes[4] + ' > %.1f m' % high_max,
value=4,
colour='#FF0000',
transparency=0,
size=1
),
]
style_info = dict(
target_field=target_field,
style_classes=style_classes,
style_type='categorizedSymbol')
impact_data = self.generate_data()
extra_keywords = {
'map_title': self.metadata().key('map_title'),
'legend_title': self.metadata().key('legend_title'),
'target_field': target_field
}
impact_layer_keywords = self.generate_impact_keywords(extra_keywords)
# Convert QgsVectorLayer to inasafe layer and return it
impact_layer = Vector(
data=line_layer,
name=self.metadata().key('layer_name'),
keywords=impact_layer_keywords,
style_info=style_info)
impact_layer.impact_data = impact_data
self._impact = impact_layer
return impact_layer
def run(self):
"""Run the impact function.
:returns: A new line layer with inundated roads marked.
:type: safe_layer
"""
# Thresholds for tsunami hazard zone breakdown.
low_max = self.parameters['low_threshold'].value
medium_max = self.parameters['medium_threshold'].value
high_max = self.parameters['high_threshold'].value
target_field = self.target_field
# Get parameters from layer's keywords
road_class_field = self.exposure.keyword('road_class_field')
exposure_value_mapping = self.exposure.keyword('value_mapping')
# reproject self.extent to the hazard projection
hazard_crs = self.hazard.layer.crs()
hazard_authid = hazard_crs.authid()
if hazard_authid == 'EPSG:4326':
viewport_extent = self.requested_extent
else:
geo_crs = QgsCoordinateReferenceSystem()
geo_crs.createFromSrid(4326)
viewport_extent = extent_to_geo_array(
QgsRectangle(*self.requested_extent), geo_crs, hazard_crs)
# Clip hazard raster
small_raster = align_clip_raster(self.hazard.layer, viewport_extent)
# Create vector features from the flood raster
# For each raster cell there is one rectangular polygon
# Data also get spatially indexed for faster operation
ranges = ranges_according_thresholds(low_max, medium_max, high_max)
index, flood_cells_map = _raster_to_vector_cells(
small_raster, ranges, self.exposure.layer.crs())
# Filter geometry and data using the extent
ct = QgsCoordinateTransform(QgsCoordinateReferenceSystem("EPSG:4326"),
self.exposure.layer.crs())
extent = ct.transformBoundingBox(QgsRectangle(*self.requested_extent))
request = QgsFeatureRequest()
request.setFilterRect(extent)
# create template for the output layer
line_layer_tmp = create_layer(self.exposure.layer)
new_field = QgsField(target_field, QVariant.Int)
line_layer_tmp.dataProvider().addAttributes([new_field])
line_layer_tmp.updateFields()
# create empty output layer and load it
filename = unique_filename(suffix='.shp')
QgsVectorFileWriter.writeAsVectorFormat(line_layer_tmp, filename,
"utf-8", None,
"ESRI Shapefile")
line_layer = QgsVectorLayer(filename, "flooded roads", "ogr")
# Do the heavy work - for each road get flood polygon for that area and
# do the intersection/difference to find out which parts are flooded
_intersect_lines_with_vector_cells(self.exposure.layer, request, index,
flood_cells_map, line_layer,
target_field)
target_field_index = line_layer.dataProvider().\
fieldNameIndex(target_field)
# Generate simple impact report
epsg = get_utm_epsg(self.requested_extent[0], self.requested_extent[1])
output_crs = QgsCoordinateReferenceSystem(epsg)
transform = QgsCoordinateTransform(self.exposure.layer.crs(),
output_crs)
# Roads breakdown
self.init_report_var(self.hazard_classes)
if line_layer.featureCount() < 1:
raise ZeroImpactException()
roads_data = line_layer.getFeatures()
road_type_field_index = line_layer.fieldNameIndex(road_class_field)
for road in roads_data:
attributes = road.attributes()
affected = attributes[target_field_index]
if isinstance(affected, QPyNullVariant):
continue
else:
hazard_zone = self.hazard_classes[affected]
usage = attributes[road_type_field_index]
usage = main_type(usage, exposure_value_mapping)
geom = road.geometry()
geom.transform(transform)
length = geom.length()
affected = False
num_classes = len(self.hazard_classes)
if attributes[target_field_index] in range(num_classes):
affected = True
self.classify_feature(hazard_zone, usage, length, affected)
self.reorder_dictionaries()
style_classes = [
# FIXME 0 - 0.1
dict(label=self.hazard_classes[0] + ': 0m',
value=0,
colour='#00FF00',
transparency=0,
size=1),
dict(label=self.hazard_classes[1] + ': >0 - %.1f m' % low_max,
value=1,
colour='#FFFF00',
transparency=0,
size=1),
dict(label=self.hazard_classes[2] + ': %.1f - %.1f m' %
(low_max + 0.1, medium_max),
value=2,
colour='#FFB700',
transparency=0,
size=1),
dict(label=self.hazard_classes[3] + ': %.1f - %.1f m' %
(medium_max + 0.1, high_max),
value=3,
colour='#FF6F00',
transparency=0,
size=1),
dict(label=self.hazard_classes[4] + ' > %.1f m' % high_max,
value=4,
colour='#FF0000',
transparency=0,
size=1),
]
style_info = dict(target_field=target_field,
style_classes=style_classes,
style_type='categorizedSymbol')
impact_data = self.generate_data()
extra_keywords = {
'map_title': self.map_title(),
'legend_title': self.metadata().key('legend_title'),
'target_field': target_field
}
impact_layer_keywords = self.generate_impact_keywords(extra_keywords)
# Convert QgsVectorLayer to inasafe layer and return it
impact_layer = Vector(data=line_layer,
name=self.map_title(),
keywords=impact_layer_keywords,
style_info=style_info)
impact_layer.impact_data = impact_data
self._impact = impact_layer
return impact_layer
def run(self):
"""Run the impact function.
:returns: A vector layer with affected areas marked.
:type: safe_layer
"""
hazard_layer = self.hazard.layer
exposure = self.exposure.layer
# Thresholds for tsunami hazard zone breakdown.
group_parameters = self.parameters['group_threshold']
ver_low_unit = group_parameters.value_map['very_low_threshold'].unit
unit_abbrev = ver_low_unit.abbreviation
unaffected_threshold = group_parameters.value_map[
'unaffected_threshold']
unaffected_max = unaffected_threshold.value
very_low_max = group_parameters.value_map['very_low_threshold'].value
low_max = group_parameters.value_map['low_threshold'].value
medium_max = group_parameters.value_map['moderate_threshold'].value
high_max = group_parameters.value_map['high_threshold'].value
ranges = ranges_according_thresholds_list(
[unaffected_max, very_low_max, low_max,
medium_max, high_max, None])
hazard_value_to_class = {}
for i, interval in enumerate(ranges):
hazard_value_to_class[interval] = self.hazard_classes[i]
# Get parameters from layer's keywords
class_field = self.exposure.keyword('field')
# reproject self.extent to the hazard projection
hazard_crs = hazard_layer.crs()
hazard_authid = hazard_crs.authid()
if hazard_authid == 'EPSG:4326':
viewport_extent = self.requested_extent
else:
geo_crs = QgsCoordinateReferenceSystem()
geo_crs.createFromSrid(4326)
viewport_extent = extent_to_geo_array(
QgsRectangle(*self.requested_extent), geo_crs, hazard_crs)
small_raster = align_clip_raster(hazard_layer, viewport_extent)
# Create vector features from the flood raster
hazard_class_attribute = 'hazard'
vector_file_path = reclassify_polygonize(
small_raster.source(), ranges, name_field=hazard_class_attribute)
hazard = QgsVectorLayer(vector_file_path, 'ash vector', 'ogr')
# prepare objects for re-projection of geometries
crs_wgs84 = QgsCoordinateReferenceSystem('EPSG:4326')
hazard_to_exposure = QgsCoordinateTransform(
hazard.crs(), exposure.crs())
wgs84_to_hazard = QgsCoordinateTransform(
crs_wgs84, hazard.crs())
wgs84_to_exposure = QgsCoordinateTransform(
crs_wgs84, exposure.crs())
extent = QgsRectangle(
self.requested_extent[0], self.requested_extent[1],
self.requested_extent[2], self.requested_extent[3])
extent_hazard = wgs84_to_hazard.transformBoundingBox(extent)
extent_exposure = wgs84_to_exposure.transformBoundingBox(extent)
extent_exposure_geom = QgsGeometry.fromRect(extent_exposure)
# make spatial index of hazard
hazard_index = QgsSpatialIndex()
hazard_features = {}
for f in hazard.getFeatures(QgsFeatureRequest(extent_hazard)):
f.geometry().transform(hazard_to_exposure)
hazard_index.insertFeature(f)
hazard_features[f.id()] = QgsFeature(f)
# create impact layer
filename = unique_filename(suffix='.shp')
impact_fields = exposure.dataProvider().fields()
impact_fields.append(QgsField(self.target_field, QVariant.String))
writer = QgsVectorFileWriter(
filename, 'utf-8', impact_fields, QGis.WKBPolygon, exposure.crs())
# iterate over all exposure polygons and calculate the impact
_calculate_landcover_impact(
exposure, extent_exposure, extent_exposure_geom,
hazard_class_attribute, hazard_features, hazard_index,
hazard_value_to_class, impact_fields, writer)
del writer
impact_layer = QgsVectorLayer(filename, 'Impacted Land Cover', 'ogr')
if impact_layer.featureCount() == 0:
raise ZeroImpactException()
zone_field = None
if self.aggregator:
zone_field = self.aggregator.exposure_aggregation_field
impact_data = LandCoverReportMixin(
question=self.question,
impact_layer=impact_layer,
target_field=self.target_field,
ordered_columns=self.hazard_classes,
affected_columns=self.affected_hazard_columns,
land_cover_field=class_field,
zone_field=zone_field
).generate_data()
# Define style for the impact layer
style_classes = [
dict(
label=self.hazard_classes[0] + ': %.1f - %.1f %s' % (
unaffected_max, very_low_max, unit_abbrev),
value=self.hazard_classes[0],
colour='#2C6BA4',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[1] + ': %.1f - %.1f %s' % (
very_low_max + 0.1, low_max, unit_abbrev),
value=self.hazard_classes[1],
colour='#00A4D8',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[2] + ': %.1f - %.1f %s' % (
low_max + 0.1, medium_max, unit_abbrev),
value=self.hazard_classes[2],
colour='#FFEF36',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[3] + ': %.1f - %.1f %s' % (
medium_max + 0.1, high_max, unit_abbrev),
value=self.hazard_classes[3],
colour='#EFA951',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[4] + ': > %.1f %s' % (
high_max, unit_abbrev),
value=self.hazard_classes[4],
colour='#d62631',
border_color='#000000',
transparency=0),
]
style_info = dict(
target_field=self.target_field,
style_classes=style_classes,
style_type='categorizedSymbol')
extra_keywords = {
'map_title': self.metadata().key('map_title'),
'target_field': self.target_field
}
impact_layer_keywords = self.generate_impact_keywords(extra_keywords)
# Create vector layer and return
impact_layer = Vector(
data=impact_layer,
name=self.metadata().key('layer_name'),
keywords=impact_layer_keywords,
style_info=style_info)
impact_layer.impact_data = impact_data
self._impact = impact_layer
return impact_layer
def run(self):
"""Run the impact function.
:returns: A vector layer with affected areas marked.
:type: safe_layer
"""
hazard_layer = self.hazard.layer
exposure = self.exposure.layer
# Thresholds for tsunami hazard zone breakdown.
low_max = self.parameters['low_threshold'].value
medium_max = self.parameters['medium_threshold'].value
high_max = self.parameters['high_threshold'].value
ranges = ranges_according_thresholds(low_max, medium_max, high_max)
hazard_value_to_class = {}
for i, interval in enumerate(ranges):
hazard_value_to_class[interval] = self.hazard_classes[i]
# Get parameters from layer's keywords
class_field = self.exposure.keyword('field')
# reproject self.extent to the hazard projection
hazard_crs = hazard_layer.crs()
hazard_authid = hazard_crs.authid()
if hazard_authid == 'EPSG:4326':
viewport_extent = self.requested_extent
else:
geo_crs = QgsCoordinateReferenceSystem()
geo_crs.createFromSrid(4326)
viewport_extent = extent_to_geo_array(
QgsRectangle(*self.requested_extent), geo_crs, hazard_crs)
small_raster = align_clip_raster(hazard_layer, viewport_extent)
# Create vector features from the flood raster
hazard_class_attribute = 'hazard'
vector_file_path = reclassify_polygonize(
small_raster.source(), ranges, name_field=hazard_class_attribute)
hazard = QgsVectorLayer(vector_file_path, 'tsunami', 'ogr')
# prepare objects for re-projection of geometries
crs_wgs84 = QgsCoordinateReferenceSystem('EPSG:4326')
hazard_to_exposure = QgsCoordinateTransform(
hazard.crs(), exposure.crs())
wgs84_to_hazard = QgsCoordinateTransform(
crs_wgs84, hazard.crs())
wgs84_to_exposure = QgsCoordinateTransform(
crs_wgs84, exposure.crs())
extent = QgsRectangle(
self.requested_extent[0], self.requested_extent[1],
self.requested_extent[2], self.requested_extent[3])
extent_hazard = wgs84_to_hazard.transformBoundingBox(extent)
extent_exposure = wgs84_to_exposure.transformBoundingBox(extent)
extent_exposure_geom = QgsGeometry.fromRect(extent_exposure)
# make spatial index of hazard
hazard_index = QgsSpatialIndex()
hazard_features = {}
for f in hazard.getFeatures(QgsFeatureRequest(extent_hazard)):
f.geometry().transform(hazard_to_exposure)
hazard_index.insertFeature(f)
hazard_features[f.id()] = QgsFeature(f)
# create impact layer
filename = unique_filename(suffix='.shp')
impact_fields = exposure.dataProvider().fields()
impact_fields.append(QgsField(self.target_field, QVariant.String))
writer = QgsVectorFileWriter(
filename, 'utf-8', impact_fields, QGis.WKBPolygon, exposure.crs())
# iterate over all exposure polygons and calculate the impact
_calculate_landcover_impact(
exposure, extent_exposure, extent_exposure_geom,
hazard_class_attribute, hazard_features, hazard_index,
hazard_value_to_class, impact_fields, writer)
del writer
impact_layer = QgsVectorLayer(filename, 'Impacted Land Cover', 'ogr')
if impact_layer.featureCount() == 0:
raise ZeroImpactException()
zone_field = None
if self.aggregator:
zone_field = self.aggregator.exposure_aggregation_field
impact_data = LandCoverReportMixin(
question=self.question,
impact_layer=impact_layer,
target_field=self.target_field,
ordered_columns=self.hazard_classes,
affected_columns=self.affected_hazard_columns,
land_cover_field=class_field,
zone_field=zone_field
).generate_data()
# Define style for the impact layer
style_classes = [
dict(
label=self.hazard_classes[0] + ': 0m',
value=self.hazard_classes[0],
colour='#00FF00',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[1] + ': >0 - %.1f m' % low_max,
value=self.hazard_classes[1],
colour='#FFFF00',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[2] + ': %.1f - %.1f m' % (
low_max + 0.1, medium_max),
value=self.hazard_classes[2],
colour='#FFB700',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[3] + ': %.1f - %.1f m' % (
medium_max + 0.1, high_max),
value=self.hazard_classes[3],
colour='#FF6F00',
border_color='#000000',
transparency=0),
dict(
label=self.hazard_classes[4] + ' > %.1f m' % high_max,
value=self.hazard_classes[4],
colour='#FF0000',
border_color='#000000',
transparency=0),
]
style_info = dict(
target_field=self.target_field,
style_classes=style_classes,
style_type='categorizedSymbol')
extra_keywords = {
'map_title': self.map_title(),
'target_field': self.target_field
}
impact_layer_keywords = self.generate_impact_keywords(extra_keywords)
# Create vector layer and return
impact_layer = Vector(
data=impact_layer,
name=self.map_title(),
keywords=impact_layer_keywords,
style_info=style_info)
impact_layer.impact_data = impact_data
self._impact = impact_layer
return impact_layer