def test_analysis_summary(self):
"""Test we can aggregate the aggregate hazard to the analysis."""
aggregate_hazard = load_test_vector_layer(
'gisv4', 'intermediate',
'aggregate_classified_hazard_summary.geojson')
aggregate_hazard.keywords['hazard_keywords'] = {
'classification': 'generic_hazard_classes'
}
analysis = load_test_vector_layer('gisv4',
'intermediate',
'analysis.geojson',
clone=True)
number_of_fields = analysis.fields().count()
layer = analysis_summary(aggregate_hazard, analysis)
check_inasafe_fields(layer)
fields = aggregate_hazard.keywords['inasafe_fields']
hazard_class = fields[hazard_class_field['key']]
hazard_class_index = aggregate_hazard.fieldNameIndex(hazard_class)
unique_hazard = aggregate_hazard.uniqueValues(hazard_class_index)
# expected number of fields:
# - one field for each hazard class
# - 2 fields for analysis id and analysis name
# - 4 fields for total affected, not_affected, not exposed and total
self.assertEqual(layer.fields().count(),
len(unique_hazard) + number_of_fields + 4)
def test_aggregation_summary(self):
"""Test we can aggregate the aggregate hazard to the aggregation."""
aggregate_hazard = load_test_vector_layer(
'gisv4',
'intermediate',
'aggregate_classified_hazard_summary.geojson')
aggregation = load_test_vector_layer(
'gisv4',
'aggregation',
'aggregation_cleaned.geojson',
clone=True)
number_of_fields = aggregation.fields().count()
layer = aggregation_summary(aggregate_hazard, aggregation)
check_inasafe_fields(layer)
# I need the number of unique exposure
pattern = exposure_count_field['key']
pattern = pattern.replace('%s', '')
unique_exposure = []
inasafe_fields = aggregate_hazard.keywords['inasafe_fields']
for key, name_field in inasafe_fields.iteritems():
if key.endswith(pattern):
unique_exposure.append(key.replace(pattern, ''))
self.assertEqual(
layer.fields().count(),
len(unique_exposure) + number_of_fields + 1
)
def test_analysis_earthquake_summary(self):
"""Test we can compute summary after an EQ on population."""
hazard = load_test_raster_layer('gisv4', 'hazard', 'earthquake.asc')
exposure = load_test_raster_layer(
'gisv4', 'exposure', 'raster', 'population.asc')
aggregation = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.hazard = hazard
impact_function.exposure = exposure
impact_function.aggregation = aggregation
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
layer = impact_function.analysis_impacted
classification = hazard.keywords['classification']
classes = definition(classification)['classes']
for hazard_class in classes:
field_name = hazard_count_field['field_name'] % hazard_class['key']
message = '%s is not found in the EQ summary layer.' % field_name
self.assertNotEqual(-1, layer.fieldNameIndex(field_name), message)
check_inasafe_fields(impact_function.analysis_impacted)
check_inasafe_fields(impact_function.aggregation_summary)
def test_exposure_summary_table(self):
"""Test we can produce the breakdown for the exposure type."""
aggregate_hazard = load_test_vector_layer(
'gisv4', 'intermediate',
'aggregate_classified_hazard_summary.geojson')
aggregate_hazard.keywords['hazard_keywords'] = {
'classification': 'generic_hazard_classes'
}
# I need the number of unique exposure
unique_exposure = read_dynamic_inasafe_field(
aggregate_hazard.keywords['inasafe_fields'], exposure_count_field)
# I need the number of unique hazard
fields = aggregate_hazard.keywords['inasafe_fields']
hazard_class = fields[hazard_class_field['key']]
hazard_class_index = aggregate_hazard.fieldNameIndex(hazard_class)
unique_hazard = aggregate_hazard.uniqueValues(hazard_class_index)
layer = exposure_summary_table(aggregate_hazard, None)
check_inasafe_fields(layer)
self.assertEqual(len(unique_exposure), layer.featureCount())
# We should have
# one column per hazard
# one for the exposure
# one for total affected
# one for total not affected
# one for total not exposed
# one for total
self.assertEqual(layer.fields().count(), len(unique_hazard) + 5)
def test_aggregation_summary(self):
"""Test we can aggregate the aggregate hazard to the aggregation."""
aggregate_hazard = load_test_vector_layer(
'gisv4',
'intermediate',
'aggregate_classified_hazard_summary.geojson')
aggregation = load_test_vector_layer(
'gisv4',
'aggregation',
'aggregation_cleaned.geojson',
clone=True)
number_of_fields = aggregation.fields().count()
layer = aggregation_summary(aggregate_hazard, aggregation)
check_inasafe_fields(layer)
# I need the number of unique exposure
pattern = exposure_count_field['key']
pattern = pattern.replace('%s', '')
unique_exposure = []
inasafe_fields = aggregate_hazard.keywords['inasafe_fields']
for key, name_field in inasafe_fields.iteritems():
if key.endswith(pattern):
unique_exposure.append(key.replace(pattern, ''))
self.assertEqual(
layer.fields().count(),
len(unique_exposure) + number_of_fields + 1
)
def test_analysis_earthquake_summary(self):
"""Test we can compute summary after an EQ on population."""
hazard = load_test_raster_layer('gisv4', 'hazard', 'earthquake.asc')
exposure = load_test_raster_layer('gisv4', 'exposure', 'raster',
'population.asc')
aggregation = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.hazard = hazard
impact_function.exposure = exposure
impact_function.aggregation = aggregation
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
layer = impact_function.analysis_impacted
classification = hazard.keywords['classification']
classes = definition(classification)['classes']
for hazard_class in classes:
field_name = hazard_count_field['field_name'] % hazard_class['key']
message = '%s is not found in the EQ summary layer.' % field_name
self.assertNotEqual(-1, layer.fieldNameIndex(field_name), message)
check_inasafe_fields(impact_function.analysis_impacted)
check_inasafe_fields(impact_function.aggregation_summary)
def test_exposure_summary_table_productivity(self):
"""Test we can produce the breakdown for the exposure type."""
aggregate_hazard = load_test_vector_layer(
'gisv4',
'intermediate',
'summaries',
'land_cover_aggregate_hazard_impacted.geojson')
aggregate_hazard.keywords['hazard_keywords'] = {
'hazard': 'generic',
'classification': 'generic_hazard_classes'
}
aggregate_hazard.keywords['exposure_keywords'] = {
'exposure': 'land_cover'
}
exposure_summary = load_test_vector_layer(
'gisv4',
'intermediate',
'summaries',
'land_cover_exposure_summary.geojson'
)
# I need the number of unique exposure
unique_exposure = read_dynamic_inasafe_field(
aggregate_hazard.keywords['inasafe_fields'],
exposure_count_field)
# I need the number of unique hazard
fields = aggregate_hazard.keywords['inasafe_fields']
hazard_class = fields[hazard_class_field['key']]
hazard_class_index = aggregate_hazard.fields().lookupField(hazard_class)
unique_hazard = aggregate_hazard.uniqueValues(hazard_class_index)
layer = exposure_summary_table(aggregate_hazard, exposure_summary)
check_inasafe_fields(layer)
self.assertEqual(len(unique_exposure), layer.featureCount())
# We should have
# one column per hazard
# 1. one for the exposure
# 2. one for total affected
# 3. one for total not affected
# 4. one for total not exposed
# 5. one for total
# 6. one for affected productivity
# 7. one for affected production cost
# 8. one for affected production value
self.assertEqual(layer.fields().count(), len(unique_hazard) + 8)
def test_exposure_summary_table_productivity(self):
"""Test we can produce the breakdown for the exposure type."""
aggregate_hazard = load_test_vector_layer(
'gisv4',
'intermediate',
'summaries',
'land_cover_aggregate_hazard_impacted.geojson')
aggregate_hazard.keywords['hazard_keywords'] = {
'classification': 'generic_hazard_classes'
}
exposure_summary = load_test_vector_layer(
'gisv4',
'intermediate',
'summaries',
'land_cover_exposure_summary.geojson'
)
# I need the number of unique exposure
unique_exposure = read_dynamic_inasafe_field(
aggregate_hazard.keywords['inasafe_fields'],
exposure_count_field)
# I need the number of unique hazard
fields = aggregate_hazard.keywords['inasafe_fields']
hazard_class = fields[hazard_class_field['key']]
hazard_class_index = aggregate_hazard.fieldNameIndex(hazard_class)
unique_hazard = aggregate_hazard.uniqueValues(hazard_class_index)
layer = exposure_summary_table(aggregate_hazard, exposure_summary)
check_inasafe_fields(layer)
self.assertEqual(len(unique_exposure), layer.featureCount())
# We should have
# one column per hazard
# one for the exposure
# one for total affected
# one for total not affected
# one for total not exposed
# one for total
# one for affected productivity
# one for affected production cost
# one for affected production value
self.assertEqual(layer.fields().count(), len(unique_hazard) + 8)
def test_impact_summary(self):
"""Test we can aggregate the impact to the aggregate hazard."""
impact = load_test_vector_layer(
'gisv4',
'impacts',
'building-points-classified-vector.geojson')
aggregate_hazard = load_test_vector_layer(
'gisv4',
'intermediate',
'aggregate_classified_hazard.geojson',
clone=True)
aggregate_hazard.keywords['hazard_keywords'] = {
'hazard': 'generic',
'classification': 'generic_hazard_classes'
}
impact.keywords['classification'] = {
'classification': 'generic_structure_classes'
}
impact.keywords['exposure_keywords'] = {
'exposure': 'structure'
}
number_of_fields = aggregate_hazard.fields().count()
layer = aggregate_hazard_summary(impact, aggregate_hazard)
self.assertIn(total_field['key'], layer.keywords['inasafe_fields'])
check_inasafe_fields(layer)
fields = impact.keywords['inasafe_fields']
exposure_class = fields[exposure_class_field['key']]
exposure_class_index = impact.fields().lookupField(exposure_class)
unique_exposure = impact.uniqueValues(exposure_class_index)
# One field per exposure type
# Number of previous fields in the layer
# 3 : 1 fields for absolute values, 2 fields for affected and total.
self.assertEqual(
layer.fields().count(),
len(unique_exposure) + number_of_fields + 3
)
def test_impact_summary(self):
"""Test we can aggregate the impact to the aggregate hazard."""
impact = load_test_vector_layer(
'gisv4',
'impacts',
'building-points-classified-vector.geojson')
aggregate_hazard = load_test_vector_layer(
'gisv4',
'intermediate',
'aggregate_classified_hazard.geojson',
clone=True)
aggregate_hazard.keywords['hazard_keywords'] = {
'classification': 'generic_hazard_classes'
}
impact.keywords['classification'] = {
'classification': 'generic_structure_classes'
}
number_of_fields = aggregate_hazard.fields().count()
layer = aggregate_hazard_summary(impact, aggregate_hazard)
self.assertIn(total_field['key'], layer.keywords['inasafe_fields'])
check_inasafe_fields(layer)
fields = impact.keywords['inasafe_fields']
exposure_class = fields[exposure_class_field['key']]
exposure_class_index = impact.fieldNameIndex(exposure_class)
unique_exposure = impact.uniqueValues(exposure_class_index)
# One field per exposure type
# Number of previous fields in the layer
# 3 : 1 fields for absolute values, 2 fields for affected and total.
self.assertEqual(
layer.fields().count(),
len(unique_exposure) + number_of_fields + 3
)
def test_analysis_summary(self):
"""Test we can aggregate the aggregate hazard to the analysis."""
aggregate_hazard = load_test_vector_layer(
'gisv4',
'intermediate',
'aggregate_classified_hazard_summary.geojson')
aggregate_hazard.keywords['hazard_keywords'] = {
'classification': 'generic_hazard_classes'
}
analysis = load_test_vector_layer(
'gisv4',
'intermediate',
'analysis.geojson',
clone=True)
number_of_fields = analysis.fields().count()
layer = analysis_summary(aggregate_hazard, analysis)
check_inasafe_fields(layer)
fields = aggregate_hazard.keywords['inasafe_fields']
hazard_class = fields[hazard_class_field['key']]
hazard_class_index = aggregate_hazard.fieldNameIndex(hazard_class)
unique_hazard = aggregate_hazard.uniqueValues(hazard_class_index)
# expected number of fields:
# - one field for each hazard class
# - 2 fields for analysis id and analysis name
# - 4 fields for total affected, not_affected, not exposed and total
self.assertEqual(
layer.fields().count(),
len(unique_hazard) + number_of_fields + 4
)
def run_scenario(scenario, use_debug=False):
"""Run scenario.
:param scenario: Dictionary of hazard, exposure, and aggregation.
:type scenario: dict
:param use_debug: If we should use debug_mode when we run the scenario.
:type use_debug: bool
:returns: Tuple(status, Flow dictionary, outputs).
:rtype: list
"""
if os.path.exists(scenario['exposure']):
exposure_path = scenario['exposure']
elif os.path.exists(standard_data_path('exposure', scenario['exposure'])):
exposure_path = standard_data_path('exposure', scenario['exposure'])
elif os.path.exists(
standard_data_path(*(scenario['exposure'].split('/')))):
exposure_path = standard_data_path(*(scenario['exposure'].split('/')))
else:
raise IOError('No exposure file')
if os.path.exists(scenario['hazard']):
hazard_path = scenario['hazard']
elif os.path.exists(standard_data_path('hazard', scenario['hazard'])):
hazard_path = standard_data_path('hazard', scenario['hazard'])
elif os.path.exists(standard_data_path(*(scenario['hazard'].split('/')))):
hazard_path = standard_data_path(*(scenario['hazard'].split('/')))
else:
raise IOError('No hazard file')
if not scenario['aggregation']:
aggregation_path = None
else:
if os.path.exists(scenario['aggregation']):
aggregation_path = scenario['aggregation']
elif os.path.exists(
standard_data_path('aggregation', scenario['aggregation'])):
aggregation_path = standard_data_path('aggregation',
scenario['aggregation'])
elif os.path.exists(
standard_data_path(*(scenario['aggregation'].split('/')))):
aggregation_path = standard_data_path(
*(scenario['aggregation'].split('/')))
else:
raise IOError('No aggregation file')
impact_function = ImpactFunction()
impact_function.debug_mode = use_debug
layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
if not layer.isValid():
layer = QgsRasterLayer(hazard_path, 'Hazard')
impact_function.hazard = layer
layer = QgsVectorLayer(exposure_path, 'Exposure', 'ogr')
if not layer.isValid():
layer = QgsRasterLayer(exposure_path, 'Exposure')
impact_function.exposure = layer
if aggregation_path:
impact_function.aggregation = QgsVectorLayer(aggregation_path,
'Aggregation', 'ogr')
status, message = impact_function.prepare()
if status != 0:
return status, message, None
status, message = impact_function.run()
if status != 0:
return status, message, None
for layer in impact_function.outputs:
if layer.type() == QgsMapLayer.VectorLayer:
check_inasafe_fields(layer)
return status, impact_function.state, impact_function.outputs
def run_scenario(scenario, use_debug=False):
"""Run scenario.
:param scenario: Dictionary of hazard, exposure, and aggregation.
:type scenario: dict
:param use_debug: If we should use debug_mode when we run the scenario.
:type use_debug: bool
:returns: Tuple(status, Flow dictionary, outputs).
:rtype: list
"""
if os.path.exists(scenario['exposure']):
exposure_path = scenario['exposure']
elif os.path.exists(standard_data_path('exposure', scenario['exposure'])):
exposure_path = standard_data_path('exposure', scenario['exposure'])
elif os.path.exists(
standard_data_path(*(scenario['exposure'].split('/')))):
exposure_path = standard_data_path(*(scenario['exposure'].split('/')))
else:
raise IOError('No exposure file')
if os.path.exists(scenario['hazard']):
hazard_path = scenario['hazard']
elif os.path.exists(standard_data_path('hazard', scenario['hazard'])):
hazard_path = standard_data_path('hazard', scenario['hazard'])
elif os.path.exists(standard_data_path(*(scenario['hazard'].split('/')))):
hazard_path = standard_data_path(*(scenario['hazard'].split('/')))
else:
raise IOError('No hazard file')
if not scenario['aggregation']:
aggregation_path = None
else:
if os.path.exists(scenario['aggregation']):
aggregation_path = scenario['aggregation']
elif os.path.exists(standard_data_path(
'aggregation', scenario['aggregation'])):
aggregation_path = standard_data_path(
'aggregation', scenario['aggregation'])
elif os.path.exists(
standard_data_path(*(scenario['aggregation'].split('/')))):
aggregation_path = standard_data_path(
*(scenario['aggregation'].split('/')))
else:
raise IOError('No aggregation file')
impact_function = ImpactFunction()
impact_function.debug_mode = use_debug
layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
if not layer.isValid():
layer = QgsRasterLayer(hazard_path, 'Hazard')
impact_function.hazard = layer
layer = QgsVectorLayer(exposure_path, 'Exposure', 'ogr')
if not layer.isValid():
layer = QgsRasterLayer(exposure_path, 'Exposure')
impact_function.exposure = layer
if aggregation_path:
impact_function.aggregation = QgsVectorLayer(
aggregation_path, 'Aggregation', 'ogr')
status, message = impact_function.prepare()
if status != 0:
return status, message, None
status, message = impact_function.run()
if status != 0:
return status, message, None
for layer in impact_function.outputs:
if layer.type() == QgsMapLayer.VectorLayer:
check_inasafe_fields(layer)
return status, impact_function.state, impact_function.outputs
def check_input_layer(layer, purpose):
"""Function to check if the layer is valid.
The function will also set the monkey patching if needed.
:param layer: The layer to test.
:type layer: QgsMapLayer
:param purpose: The expected purpose of the layer.
:type purpose: basestring
:return: A tuple with the status of the layer and an error message if
needed.
The status is 0 if everything was fine.
The status is 1 if the client should fix something.
:rtype: (int, m.Message)
"""
if not layer.isValid():
title = tr('The {purpose} layer is invalid').format(purpose=purpose)
content = tr('The impact function needs a {exposure} layer to run. '
'You must provide a valid {exposure} layer.').format(
purpose=purpose)
message = generate_input_error_message(title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
# We should read it using KeywordIO for the very beginning. To avoid
# get the modified keywords in the patching.
try:
keywords = KeywordIO().read_keywords(layer)
except NoKeywordsFoundError:
title = tr('The {purpose} layer does not have keywords.').format(
purpose=purpose)
content = tr(
'The {purpose} layer does not have keywords. Use the wizard '
'to assign keywords to the layer.').format(purpose=purpose)
message = generate_input_error_message(title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
if keywords.get('layer_purpose') != purpose:
title = tr('The expected {purpose} layer is not an {purpose}.') \
.format(purpose=purpose)
content = tr('The expected {purpose} layer is not an {purpose}.') \
.format(purpose=purpose)
message = generate_input_error_message(title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
version = keywords.get(inasafe_keyword_version_key)
supported = is_keyword_version_supported(version)
if not supported:
parameters = {
'version': inasafe_keyword_version,
'source': layer.publicSource()
}
title = tr('The {purpose} layer is not up to date.').format(
purpose=purpose)
content = tr('The layer {source} must be updated to {version}.'
).format(**parameters)
message = generate_input_error_message(title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
layer.keywords = keywords
if is_vector_layer(layer):
try:
check_inasafe_fields(layer, keywords_only=True)
except InvalidLayerError:
title = tr('The {purpose} layer is not up to date.').format(
purpose=purpose)
content = tr(
'The layer {source} must be updated with the keyword '
'wizard. Your fields which have been set in the keywords '
'previously are not matching your layer.').format(
source=layer.publicSource())
message = generate_input_error_message(title, m.Paragraph(content))
del layer.keywords
return PREPARE_FAILED_BAD_INPUT, message
return PREPARE_SUCCESS, None
def check_input_layer(layer, purpose):
"""Function to check if the layer is valid.
The function will also set the monkey patching if needed.
:param layer: The layer to test.
:type layer: QgsMapLayer
:param purpose: The expected purpose of the layer.
:type purpose: basestring
:return: A tuple with the status of the layer and an error message if
needed.
The status is 0 if everything was fine.
The status is 1 if the client should fix something.
:rtype: (int, m.Message)
"""
if not layer.isValid():
title = tr(
'The {purpose} layer is invalid').format(purpose=purpose)
content = tr(
'The impact function needs a {exposure} layer to run. '
'You must provide a valid {exposure} layer.').format(
purpose=purpose)
message = generate_input_error_message(
title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
# We should read it using KeywordIO for the very beginning. To avoid
# get the modified keywords in the patching.
try:
keywords = KeywordIO().read_keywords(layer)
except NoKeywordsFoundError:
title = tr(
'The {purpose} layer does not have keywords.').format(
purpose=purpose)
content = tr(
'The {purpose} layer does not have keywords. Use the wizard '
'to assign keywords to the layer.').format(purpose=purpose)
message = generate_input_error_message(
title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
if keywords.get('layer_purpose') != purpose:
title = tr('The expected {purpose} layer is not an {purpose}.') \
.format(purpose=purpose)
content = tr('The expected {purpose} layer is not an {purpose}.') \
.format(purpose=purpose)
message = generate_input_error_message(
title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
version = keywords.get(inasafe_keyword_version_key)
supported = is_keyword_version_supported(version)
if not supported:
parameters = {
'version': inasafe_keyword_version,
'source': layer.publicSource()
}
title = tr('The {purpose} layer is not up to date.').format(
purpose=purpose)
content = tr(
'The layer {source} must be updated to {version}.').format(
**parameters)
message = generate_input_error_message(
title, m.Paragraph(content))
return PREPARE_FAILED_BAD_INPUT, message
layer.keywords = keywords
if is_vector_layer(layer):
try:
check_inasafe_fields(layer, keywords_only=True)
except InvalidLayerError:
title = tr('The {purpose} layer is not up to date.').format(
purpose=purpose)
content = tr(
'The layer {source} must be updated with the keyword '
'wizard. Your fields which have been set in the keywords '
'previously are not matching your layer.').format(
source=layer.publicSource())
message = generate_input_error_message(
title, m.Paragraph(content))
del layer.keywords
return PREPARE_FAILED_BAD_INPUT, message
return PREPARE_SUCCESS, None
