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 test_clean_inasafe_fields(self):
"""Test clean_inasafe_fields."""
layer = load_test_vector_layer(
'gisv4', 'exposure', 'population_multi_fields.geojson', clone=True)
original_female_fields = [
'F_0_4',
'F_5_9',
'F_9_15',
'F_15_30',
'F_30_60',
'F_60_100'
]
layer.keywords = {
'layer_purpose': 'exposure',
'exposure': 'population',
'inasafe_fields': {
'exposure_id_field': 'exposure_id',
'population_count_field': 'population',
'female_count_field': original_female_fields
}
}
clean_inasafe_fields(layer)
# Check if the female count name does exist
female_count_field_idx = layer.fields().lookupField(
female_count_field['field_name'])
self.assertGreater(female_count_field_idx, -1)
# Check the keyword is updated properly
expected_inasafe_fields = {
population_count_field['key']: population_count_field[
'field_name'],
female_count_field['key']: female_count_field['field_name'],
exposure_id_field['key']: exposure_id_field['field_name']
}
self.assertDictEqual(
expected_inasafe_fields, layer.keywords['inasafe_fields'])
# Check if the original fields are gone
for original_female_field in original_female_fields:
self.assertEqual(layer.fields().lookupField(
original_female_field), -1)
