def create_valid_aggregation(layer):
"""Create a local copy of the aggregation layer and try to make it valid.
We need to make the layer valid if we can. We got some issues with
DKI Jakarta dataset : Districts and Subdistricts layers.
See issue : https://github.com/inasafe/inasafe/issues/3713
:param layer: The aggregation layer.
:type layer: QgsVectorLayer
:return: The new aggregation layer in memory.
:rtype: QgsVectorLayer
"""
cleaned = create_memory_layer('aggregation', layer.geometryType(),
layer.crs(), layer.fields())
# We transfer keywords to the output.
cleaned.keywords = layer.keywords
try:
use_selected_only = layer.use_selected_features_only
except AttributeError:
use_selected_only = False
cleaned.use_selected_features_only = use_selected_only
copy_layer(layer, cleaned)
return cleaned
def create_valid_aggregation(layer):
"""Create a local copy of the aggregation layer and try to make it valid.
We need to make the layer valid if we can. We got some issues with
DKI Jakarta dataset : Districts and Subdistricts layers.
See issue : https://github.com/inasafe/inasafe/issues/3713
:param layer: The aggregation layer.
:type layer: QgsVectorLayer
:return: The new aggregation layer in memory.
:rtype: QgsVectorLayer
"""
cleaned = create_memory_layer(
'aggregation', layer.geometryType(), layer.crs(), layer.fields())
# We transfer keywords to the output.
cleaned.keywords = layer.keywords
try:
use_selected_only = layer.use_selected_features_only
except AttributeError:
use_selected_only = False
cleaned.use_selected_features_only = use_selected_only
copy_layer(layer, cleaned)
return cleaned
def prepare_new_layer(self, input_layer):
"""Prepare new layer for the output layer.
:param input_layer: Vector layer.
:type input_layer: QgsVectorLayer
:return: New memory layer duplicated from input_layer.
:rtype: QgsVectorLayer
"""
# create memory layer
output_layer_name = os.path.splitext(input_layer.name())[0]
output_layer_name = unique_filename(
prefix=('%s_minimum_needs_' % output_layer_name),
dir='minimum_needs_calculator')
output_layer = create_memory_layer(
output_layer_name,
input_layer.geometryType(),
input_layer.crs(),
input_layer.fields())
# monkey patching input layer to make it work with
# prepare vector layer function
temp_layer = input_layer
temp_layer.keywords = {
'layer_purpose': layer_purpose_aggregation['key']}
# copy features to output layer
copy_layer(temp_layer, output_layer)
# Monkey patching output layer to make it work with
# minimum needs calculator
output_layer.keywords['layer_purpose'] = (
layer_purpose_aggregation['key'])
output_layer.keywords['inasafe_fields'] = {
displaced_field['key']: self.displaced.currentField()
}
if self.aggregation_name.currentField():
output_layer.keywords['inasafe_fields'][
aggregation_name_field['key']] = (
self.aggregation_name.currentField())
# remove unnecessary fields & rename inasafe fields
clean_inasafe_fields(output_layer)
return output_layer
def prepare_new_layer(self, input_layer):
"""Prepare new layer for the output layer.
:param input_layer: Vector layer.
:type input_layer: QgsVectorLayer
:return: New memory layer duplicated from input_layer.
:rtype: QgsVectorLayer
"""
# create memory layer
output_layer_name = os.path.splitext(input_layer.name())[0]
output_layer_name = unique_filename(
prefix=('%s_minimum_needs_' % output_layer_name),
dir='minimum_needs_calculator')
output_layer = create_memory_layer(
output_layer_name,
input_layer.geometryType(),
input_layer.crs(),
input_layer.fields())
# monkey patching input layer to make it work with
# prepare vector layer function
temp_layer = input_layer
temp_layer.keywords = {
'layer_purpose': layer_purpose_aggregation['key']}
# copy features to output layer
copy_layer(temp_layer, output_layer)
# Monkey patching output layer to make it work with
# minimum needs calculator
output_layer.keywords['layer_purpose'] = (
layer_purpose_aggregation['key'])
output_layer.keywords['inasafe_fields'] = {
displaced_field['key']: self.displaced.currentField()
}
if self.aggregation_name.currentField():
output_layer.keywords['inasafe_fields'][
aggregation_name_field['key']] = (
self.aggregation_name.currentField())
# remove unnecessary fields & rename inasafe fields
clean_inasafe_fields(output_layer)
return output_layer
def load_path_vector_layer(path, **kwargs):
"""Return the test vector layer.
:param path: Path to the vector layer.
:type path: str
:param kwargs: It can be :
clone=True if you want to copy the layer first to a temporary file.
clone_to_memory=True if you want to create a memory layer.
with_keywords=False if you do not want keywords. "clone_to_memory" is
required.
:type kwargs: dict
:return: The vector layer.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
if not exists(path):
raise Exception('%s do not exist.' % path)
path = os.path.normcase(os.path.abspath(path))
name = splitext(basename(path))[0]
extension = splitext(path)[1]
extensions = [
'.shp', '.shx', '.dbf', '.prj', '.gpkg', '.geojson', '.xml', '.qml'
]
if kwargs.get('with_keywords'):
if not kwargs.get('clone_to_memory'):
raise Exception('with_keywords needs a clone_to_memory')
if kwargs.get('clone', False):
target_directory = mkdtemp()
current_path = splitext(path)[0]
path = join(target_directory, name + extension)
for ext in extensions:
src_path = current_path + ext
if exists(src_path):
target_path = join(target_directory, name + ext)
shutil.copy2(src_path, target_path)
if path.endswith('.csv'):
# Explicitly use URI with delimiter or tests fail in Windows. TS.
uri = 'file:///%s?delimiter=%s' % (path, ',')
layer = QgsVectorLayer(uri, name, 'delimitedtext')
else:
layer = QgsVectorLayer(path, name, 'ogr')
if not layer.isValid():
raise Exception('%s is not a valid layer.' % name)
monkey_patch_keywords(layer)
if kwargs.get('clone_to_memory', False):
keywords = layer.keywords.copy()
memory_layer = create_memory_layer(name, layer.geometryType(),
layer.crs(), layer.fields())
copy_layer(layer, memory_layer)
if kwargs.get('with_keywords', True):
memory_layer.keywords = keywords
return memory_layer
else:
return layer
def zonal_stats(raster, vector):
"""Reclassify a continuous raster layer.
Issue https://github.com/inasafe/inasafe/issues/3190
The algorithm will take care about projections.
We don't want to reproject the raster layer.
So if CRS are different, we reproject the vector layer and then we do a
lookup from the reprojected layer to the original vector layer.
:param raster: The raster layer.
:type raster: QgsRasterLayer
:param vector: The vector layer.
:type vector: QgsVectorLayer
:return: The output of the zonal stats.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
output_layer_name = zonal_stats_steps['output_layer_name']
exposure = raster.keywords['exposure']
if raster.crs().authid() != vector.crs().authid():
layer = reproject(vector, raster.crs())
# We prepare the copy
output_layer = create_memory_layer(
output_layer_name,
vector.geometryType(),
vector.crs(),
vector.fields()
)
copy_layer(vector, output_layer)
else:
layer = create_memory_layer(
output_layer_name,
vector.geometryType(),
vector.crs(),
vector.fields()
)
copy_layer(vector, layer)
input_band = layer.keywords.get('active_band', 1)
analysis = QgsZonalStatistics(
layer,
raster,
'exposure_',
input_band,
QgsZonalStatistics.Sum)
result = analysis.calculateStatistics(None)
LOGGER.debug(tr('Zonal stats on %s : %s' % (raster.source(), result)))
output_field = exposure_count_field['field_name'] % exposure
if raster.crs().authid() != vector.crs().authid():
output_layer.startEditing()
field = create_field_from_definition(
exposure_count_field, exposure)
output_layer.addAttribute(field)
new_index = output_layer.fields().lookupField(field.name())
old_index = layer.fields().lookupField('exposure_sum')
for feature_input, feature_output in zip(
layer.getFeatures(), output_layer.getFeatures()):
output_layer.changeAttributeValue(
feature_input.id(), new_index, feature_input[old_index])
output_layer.commitChanges()
layer = output_layer
else:
fields_to_rename = {
'exposure_sum': output_field
}
if qgis_version() >= 21600:
rename_fields(layer, fields_to_rename)
else:
copy_fields(layer, fields_to_rename)
remove_fields(layer, list(fields_to_rename.keys()))
layer.commitChanges()
# The zonal stats is producing some None values. We need to fill these
# with 0. See issue : #3778
# We should start a new editing session as previous fields need to be
# committed first.
layer.startEditing()
request = QgsFeatureRequest()
expression = '\"%s\" is None' % output_field
request.setFilterExpression(expression)
request.setFlags(QgsFeatureRequest.NoGeometry)
index = layer.fields().lookupField(output_field)
for feature in layer.getFeatures():
if feature[output_field] is None:
layer.changeAttributeValue(feature.id(), index, 0)
layer.commitChanges()
layer.keywords = raster.keywords.copy()
layer.keywords['inasafe_fields'] = vector.keywords['inasafe_fields'].copy()
layer.keywords['inasafe_default_values'] = (
raster.keywords['inasafe_default_values'].copy())
key = exposure_count_field['key'] % raster.keywords['exposure']
# Special case here, one field is the exposure count and the total.
layer.keywords['inasafe_fields'][key] = output_field
layer.keywords['inasafe_fields'][total_field['key']] = output_field
layer.keywords['exposure_keywords'] = raster.keywords.copy()
layer.keywords['hazard_keywords'] = vector.keywords[
'hazard_keywords'].copy()
layer.keywords['aggregation_keywords'] = (
vector.keywords['aggregation_keywords'])
layer.keywords['layer_purpose'] = (
layer_purpose_aggregate_hazard_impacted['key'])
layer.keywords['title'] = output_layer_name
check_layer(layer)
return layer
def prepare_vector_layer(layer, callback=None):
"""This function will prepare the layer to be used in InaSAFE :
* Make a local copy of the layer.
* Make sure that we have an InaSAFE ID column.
* Rename fields according to our definitions.
* Remove fields which are not used.
:param layer: The layer to prepare.
:type layer: QgsVectorLayer
:param callback: A function to all to indicate progress. The function
should accept params 'current' (int), 'maximum' (int) and 'step' (str).
Defaults to None.
:type callback: function
:return: Cleaned memory layer.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
output_layer_name = prepare_vector_steps['output_layer_name']
output_layer_name = output_layer_name % layer.keywords['layer_purpose']
processing_step = prepare_vector_steps['step_name']
if not layer.keywords.get('inasafe_fields'):
msg = 'inasafe_fields is missing in keywords from %s' % layer.name()
raise InvalidKeywordsForProcessingAlgorithm(msg)
feature_count = layer.featureCount()
cleaned = create_memory_layer(
output_layer_name, layer.geometryType(), layer.crs(), layer.fields())
# We transfer keywords to the output.
cleaned.keywords = layer.keywords
copy_layer(layer, cleaned)
_remove_features(cleaned)
# After removing rows, let's check if there is still a feature.
request = QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry)
iterator = cleaned.getFeatures(request)
try:
next(iterator)
except StopIteration:
LOGGER.warning(
tr('No feature has been found in the {purpose}'
.format(purpose=layer.keywords['layer_purpose'])))
raise NoFeaturesInExtentError
_add_id_column(cleaned)
rename_remove_inasafe_fields(cleaned)
if _size_is_needed(cleaned):
LOGGER.info(
'We noticed some counts in your exposure layer. Before to update '
'geometries, we compute the original size for each feature.')
run_single_post_processor(cleaned, post_processor_size)
if cleaned.keywords['layer_purpose'] == 'exposure':
fields = cleaned.keywords['inasafe_fields']
if exposure_type_field['key'] not in fields:
_add_default_exposure_class(cleaned)
# Check value mapping
_check_value_mapping(cleaned)
cleaned.keywords['title'] = output_layer_name
check_layer(cleaned)
return cleaned
def zonal_stats(raster, vector, callback=None):
"""Reclassify a continuous raster layer.
Issue https://github.com/inasafe/inasafe/issues/3190
:param raster: The raster layer.
:type raster: QgsRasterLayer
:param vector: The vector layer.
:type vector: QgsVectorLayer
:param callback: A function to all to indicate progress. The function
should accept params 'current' (int), 'maximum' (int) and 'step' (str).
Defaults to None.
:type callback: function
:return: The output of the zonal stats.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
output_layer_name = zonal_stats_steps['output_layer_name']
processing_step = zonal_stats_steps['step_name']
layer = create_memory_layer(
output_layer_name,
vector.geometryType(),
vector.crs(),
vector.fields()
)
copy_layer(vector, layer)
input_band = layer.keywords.get('active_band', 1)
analysis = QgsZonalStatistics(
layer,
raster.source(),
'exposure_',
input_band,
QgsZonalStatistics.Sum)
result = analysis.calculateStatistics(None)
LOGGER.debug(tr('Zonal stats on %s : %s' % (raster.source(), result)))
layer.startEditing()
exposure = raster.keywords['exposure']
output_field = exposure_count_field['field_name'] % exposure
fields_to_rename = {
'exposure_sum': output_field
}
copy_fields(layer, fields_to_rename)
remove_fields(layer, fields_to_rename.keys())
layer.commitChanges()
# The zonal stats is producing some None values. We need to fill these
# with 0. See issue : #3778
# We should start a new editing session as previous fields need to be
# commited first.
layer.startEditing()
request = QgsFeatureRequest()
expression = '\"%s\" is None' % output_field
request.setFilterExpression(expression)
request.setFlags(QgsFeatureRequest.NoGeometry)
index = layer.fieldNameIndex(output_field)
for feature in layer.getFeatures():
if feature[output_field] is None:
layer.changeAttributeValue(feature.id(), index, 0)
layer.commitChanges()
layer.keywords = raster.keywords.copy()
layer.keywords['inasafe_fields'] = vector.keywords['inasafe_fields'].copy()
layer.keywords['inasafe_default_values'] = (
raster.keywords['inasafe_default_values'].copy())
key = exposure_count_field['key'] % raster.keywords['exposure']
# Special case here, one field is the exposure count and the total.
layer.keywords['inasafe_fields'][key] = output_field
layer.keywords['inasafe_fields'][total_field['key']] = output_field
layer.keywords['exposure_keywords'] = raster.keywords.copy()
layer.keywords['hazard_keywords'] = vector.keywords[
'hazard_keywords'].copy()
layer.keywords['aggregation_keywords'] = (
vector.keywords['aggregation_keywords'])
layer.keywords['layer_purpose'] = (
layer_purpose_aggregate_hazard_impacted['key'])
layer.keywords['title'] = output_layer_name
check_layer(layer)
return layer
def prepare_vector_layer(layer, callback=None):
"""This function will prepare the layer to be used in InaSAFE :
* Make a local copy of the layer.
* Make sure that we have an InaSAFE ID column.
* Rename fields according to our definitions.
* Remove fields which are not used.
:param layer: The layer to prepare.
:type layer: QgsVectorLayer
:param callback: A function to all to indicate progress. The function
should accept params 'current' (int), 'maximum' (int) and 'step' (str).
Defaults to None.
:type callback: function
:return: Cleaned memory layer.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
output_layer_name = prepare_vector_steps['output_layer_name']
output_layer_name = output_layer_name % layer.keywords['layer_purpose']
processing_step = prepare_vector_steps['step_name']
if not layer.keywords.get('inasafe_fields'):
msg = 'inasafe_fields is missing in keywords from %s' % layer.name()
raise InvalidKeywordsForProcessingAlgorithm(msg)
feature_count = layer.featureCount()
cleaned = create_memory_layer(
output_layer_name, layer.geometryType(), layer.crs(), layer.fields())
# We transfer keywords to the output.
cleaned.keywords = layer.keywords
copy_layer(layer, cleaned)
_remove_features(cleaned)
# After removing rows, let's check if there is still a feature.
request = QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry)
iterator = cleaned.getFeatures(request)
try:
next(iterator)
except StopIteration:
LOGGER.warning(
tr('No feature has been found in the {purpose}'
.format(purpose=layer.keywords['layer_purpose'])))
raise NoFeaturesInExtentError
_add_id_column(cleaned)
clean_inasafe_fields(cleaned)
if _size_is_needed(cleaned):
LOGGER.info(
'We noticed some counts in your exposure layer. Before to update '
'geometries, we compute the original size for each feature.')
run_single_post_processor(cleaned, post_processor_size)
if cleaned.keywords['layer_purpose'] == 'exposure':
fields = cleaned.keywords['inasafe_fields']
if exposure_type_field['key'] not in fields:
_add_default_exposure_class(cleaned)
# Check value mapping
_check_value_mapping(cleaned)
cleaned.keywords['title'] = output_layer_name
check_layer(cleaned)
return cleaned
def zonal_stats(raster, vector, callback=None):
"""Reclassify a continuous raster layer.
Issue https://github.com/inasafe/inasafe/issues/3190
:param raster: The raster layer.
:type raster: QgsRasterLayer
:param vector: The vector layer.
:type vector: QgsVectorLayer
:param callback: A function to all to indicate progress. The function
should accept params 'current' (int), 'maximum' (int) and 'step' (str).
Defaults to None.
:type callback: function
:return: The output of the zonal stats.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
output_layer_name = zonal_stats_steps['output_layer_name']
processing_step = zonal_stats_steps['step_name']
layer = create_memory_layer(
output_layer_name,
vector.geometryType(),
vector.crs(),
vector.fields()
)
copy_layer(vector, layer)
analysis = QgsZonalStatistics(
layer, raster.source(), 'exposure_', 1, QgsZonalStatistics.Sum)
result = analysis.calculateStatistics(None)
LOGGER.debug(tr('Zonal stats on %s : %s' % (raster.source(), result)))
layer.startEditing()
exposure = raster.keywords['exposure']
output_field = exposure_count_field['field_name'] % exposure
fields_to_rename = {
'exposure_sum': output_field
}
copy_fields(layer, fields_to_rename)
remove_fields(layer, fields_to_rename.keys())
layer.commitChanges()
# The zonal stats is producing some None values. We need to fill these
# with 0. See issue : #3778
# We should start a new editing session as previous fields need to be
# commited first.
layer.startEditing()
request = QgsFeatureRequest()
expression = '\"%s\" is None' % output_field
request.setFilterExpression(expression)
request.setFlags(QgsFeatureRequest.NoGeometry)
index = layer.fieldNameIndex(output_field)
for feature in layer.getFeatures():
if feature[output_field] is None:
layer.changeAttributeValue(feature.id(), index, 0)
layer.commitChanges()
layer.keywords = raster.keywords.copy()
layer.keywords['inasafe_fields'] = vector.keywords['inasafe_fields'].copy()
layer.keywords['inasafe_default_values'] = (
raster.keywords['inasafe_default_values'].copy())
key = exposure_count_field['key'] % raster.keywords['exposure']
# Special case here, one field is the exposure count and the total.
layer.keywords['inasafe_fields'][key] = output_field
layer.keywords['inasafe_fields'][total_field['key']] = output_field
layer.keywords['exposure_keywords'] = raster.keywords.copy()
layer.keywords['hazard_keywords'] = vector.keywords[
'hazard_keywords'].copy()
layer.keywords['aggregation_keywords'] = (
vector.keywords['aggregation_keywords'])
layer.keywords['layer_purpose'] = (
layer_purpose_aggregate_hazard_impacted['key'])
layer.keywords['title'] = output_layer_name
check_layer(layer)
return layer
def load_path_vector_layer(path, **kwargs):
"""Return the test vector layer.
:param path: Path to the vector layer.
:type path: str
:param kwargs: It can be :
clone=True if you want to copy the layer first to a temporary file.
clone_to_memory=True if you want to create a memory layer.
with_keywords=False if you do not want keywords. "clone_to_memory" is
required.
:type kwargs: dict
:return: The vector layer.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
if not exists(path):
raise Exception('%s do not exist.' % path)
path = os.path.normcase(os.path.abspath(path))
name = splitext(basename(path))[0]
extension = splitext(path)[1]
extensions = [
'.shp', '.shx', '.dbf', '.prj', '.gpkg', '.geojson', '.xml', '.qml']
if kwargs.get('with_keywords'):
if not kwargs.get('clone_to_memory'):
raise Exception('with_keywords needs a clone_to_memory')
if kwargs.get('clone', False):
target_directory = mkdtemp()
current_path = splitext(path)[0]
path = join(target_directory, name + extension)
for ext in extensions:
src_path = current_path + ext
if exists(src_path):
target_path = join(target_directory, name + ext)
shutil.copy2(src_path, target_path)
if path.endswith('.csv'):
# Explicitly use URI with delimiter or tests fail in Windows. TS.
uri = 'file:///%s?delimiter=%s' % (path, ',')
layer = QgsVectorLayer(uri, name, 'delimitedtext')
else:
layer = QgsVectorLayer(path, name, 'ogr')
if not layer.isValid():
raise Exception('%s is not a valid layer.' % name)
monkey_patch_keywords(layer)
if kwargs.get('clone_to_memory', False):
keywords = layer.keywords.copy()
memory_layer = create_memory_layer(
name, layer.geometryType(), layer.crs(), layer.fields())
copy_layer(layer, memory_layer)
if kwargs.get('with_keywords', True):
memory_layer.keywords = keywords
return memory_layer
else:
return layer
def zonal_stats(raster, vector):
"""Reclassify a continuous raster layer.
Issue https://github.com/inasafe/inasafe/issues/3190
The algorithm will take care about projections.
We don't want to reproject the raster layer.
So if CRS are different, we reproject the vector layer and then we do a
lookup from the reprojected layer to the original vector layer.
:param raster: The raster layer.
:type raster: QgsRasterLayer
:param vector: The vector layer.
:type vector: QgsVectorLayer
:return: The output of the zonal stats.
:rtype: QgsVectorLayer
.. versionadded:: 4.0
"""
output_layer_name = zonal_stats_steps['output_layer_name']
exposure = raster.keywords['exposure']
if raster.crs().authid() != vector.crs().authid():
layer = reproject(vector, raster.crs())
# We prepare the copy
output_layer = create_memory_layer(
output_layer_name,
vector.geometryType(),
vector.crs(),
vector.fields()
)
copy_layer(vector, output_layer)
else:
layer = create_memory_layer(
output_layer_name,
vector.geometryType(),
vector.crs(),
vector.fields()
)
copy_layer(vector, layer)
input_band = layer.keywords.get('active_band', 1)
analysis = QgsZonalStatistics(
layer,
raster,
'exposure_',
input_band,
QgsZonalStatistics.Sum)
result = analysis.calculateStatistics(None)
LOGGER.debug(tr('Zonal stats on %s : %s' % (raster.source(), result)))
output_field = exposure_count_field['field_name'] % exposure
if raster.crs().authid() != vector.crs().authid():
output_layer.startEditing()
field = create_field_from_definition(
exposure_count_field, exposure)
output_layer.addAttribute(field)
new_index = output_layer.fields().lookupField(field.name())
old_index = layer.fields().lookupField('exposure_sum')
for feature_input, feature_output in zip(
layer.getFeatures(), output_layer.getFeatures()):
output_layer.changeAttributeValue(
feature_input.id(), new_index, feature_input[old_index])
output_layer.commitChanges()
layer = output_layer
else:
fields_to_rename = {
'exposure_sum': output_field
}
if qgis_version() >= 21600:
rename_fields(layer, fields_to_rename)
else:
copy_fields(layer, fields_to_rename)
remove_fields(layer, list(fields_to_rename.keys()))
layer.commitChanges()
# The zonal stats is producing some None values. We need to fill these
# with 0. See issue : #3778
# We should start a new editing session as previous fields need to be
# committed first.
layer.startEditing()
request = QgsFeatureRequest()
expression = '\"%s\" is None' % output_field
request.setFilterExpression(expression)
request.setFlags(QgsFeatureRequest.NoGeometry)
index = layer.fields().lookupField(output_field)
for feature in layer.getFeatures():
if feature[output_field] is None:
layer.changeAttributeValue(feature.id(), index, 0)
layer.commitChanges()
layer.keywords = raster.keywords.copy()
layer.keywords['inasafe_fields'] = vector.keywords['inasafe_fields'].copy()
layer.keywords['inasafe_default_values'] = (
raster.keywords['inasafe_default_values'].copy())
key = exposure_count_field['key'] % raster.keywords['exposure']
# Special case here, one field is the exposure count and the total.
layer.keywords['inasafe_fields'][key] = output_field
layer.keywords['inasafe_fields'][total_field['key']] = output_field
layer.keywords['exposure_keywords'] = raster.keywords.copy()
layer.keywords['hazard_keywords'] = vector.keywords[
'hazard_keywords'].copy()
layer.keywords['aggregation_keywords'] = (
vector.keywords['aggregation_keywords'])
layer.keywords['layer_purpose'] = (
layer_purpose_aggregate_hazard_impacted['key'])
layer.keywords['title'] = output_layer_name
check_layer(layer)
return layer
