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_profiling(self):
"""Test running impact function on test data."""
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'building-points.geojson')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.run()
self.assertEqual(ANALYSIS_FAILED_BAD_INPUT, status, message)
impact_function.prepare()
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
message = impact_function.performance_log_message().to_text()
expected_result = get_control_text(
'test-profiling-logs.txt')
for line in expected_result:
line = line.replace('\n', '')
if line == '' or line == '-':
continue
self.assertIn(line, message)
# Notes(IS): For some unknown reason I need to do this to make
# test_provenance pass
del hazard_layer
def test_profiling(self):
"""Test running impact function on test data."""
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'building-points.geojson')
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.run()
self.assertEqual(ANALYSIS_FAILED_BAD_INPUT, status, message)
impact_function.prepare()
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
message = impact_function.performance_log_message().to_text()
expected_result = get_control_text('test-profiling-logs.txt')
for line in expected_result:
line = line.replace('\n', '')
if line == '' or line == '-':
continue
self.assertIn(line, message)
# Notes(IS): For some unknown reason I need to do this to make
# test_provenance pass
del hazard_layer
def prepare_impact_function(self):
"""Create analysis as a representation of current situation of IFCW."""
# Impact Functions
impact_function = ImpactFunction()
impact_function.callback = self.progress_callback
# Layers
impact_function.hazard = self.parent.hazard_layer
impact_function.exposure = self.parent.exposure_layer
aggregation = self.parent.aggregation_layer
if aggregation:
impact_function.aggregation = aggregation
impact_function.use_selected_features_only = (
setting('useSelectedFeaturesOnly', False, bool))
else:
mode = setting('analysis_extents_mode')
if self.extent.user_extent:
# This like a hack to transform a geometry to a rectangle.
# self.extent.user_extent is a QgsGeometry.
# impact_function.requested_extent needs a QgsRectangle.
wkt = self.extent.user_extent.exportToWkt()
impact_function.requested_extent = wkt_to_rectangle(wkt)
impact_function.requested_extent_crs = self.extent.crs
elif mode == HAZARD_EXPOSURE_VIEW:
impact_function.requested_extent = (
self.iface.mapCanvas().extent())
impact_function.requested_extent_crs = self.extent.crs
# We don't have any checkbox in the wizard for the debug mode.
impact_function.debug_mode = False
return impact_function
def test_old_fields_keywords(self):
"""The IF is not ready with we have some wrong inasafe_fields."""
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4',
'exposure',
'building-points.geojson',
clone=True)
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.prepare()
# The layer should be fine.
self.assertEqual(PREPARE_SUCCESS, status, message)
# Now, we remove one field
exposure_layer.startEditing()
field = exposure_layer.keywords['inasafe_fields'].values()[0]
index = exposure_layer.fieldNameIndex(field)
exposure_layer.deleteAttribute(index)
exposure_layer.commitChanges()
# It shouldn't be fine as we removed one field which
# was in inasafe_fields
status, message = impact_function.prepare()
self.assertNotEqual(PREPARE_SUCCESS, status, message)
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_old_fields_keywords(self):
"""The IF is not ready with we have some wrong inasafe_fields."""
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'building-points.geojson',
clone=True)
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.prepare()
# The layer should be fine.
self.assertEqual(PREPARE_SUCCESS, status, message)
# Now, we remove one field
exposure_layer.startEditing()
field = exposure_layer.keywords['inasafe_fields'].values()[0]
index = exposure_layer.fieldNameIndex(field)
exposure_layer.deleteAttribute(index)
exposure_layer.commitChanges()
# It shouldn't be fine as we removed one field which
# was in inasafe_fields
status, message = impact_function.prepare()
self.assertNotEqual(PREPARE_SUCCESS, status, message)
def run_impact_function(cli_arguments):
"""Runs an analysis and delegates producing pdf and .geojson output layers.
.. versionadded:: 3.2
:param cli_arguments: User inputs.
:type cli_arguments: CommandLineArguments
"""
hazard = get_layer(cli_arguments.hazard, 'Hazard Layer')
exposure = get_layer(cli_arguments.exposure, 'Exposure Layer')
aggregation = None
if cli_arguments.aggregation:
aggregation = get_layer(cli_arguments.aggregation, 'Aggregation Layer')
# Set up impact function
impact_function = ImpactFunction()
impact_function.hazard = hazard
impact_function.exposure = exposure
impact_function.aggregation = aggregation
# Set the datastore
impact_function.datastore = Folder(cli_arguments.output_dir)
impact_function.datastore.default_vector_format = 'geojson'
# Set the extent
if cli_arguments.extent:
impact_function.requested_extent_crs = \
QgsCoordinateReferenceSystem(4326)
try:
impact_function.requested_extent = QgsRectangle(
float(cli_arguments.extent[0]),
float(cli_arguments.extent[1]),
float(cli_arguments.extent[2]),
float(cli_arguments.extent[3])
)
except AttributeError:
print "Extent is not valid..."
pass
# Prepare impact function
status, message = impact_function.prepare()
if status != PREPARE_SUCCESS:
print message.to_text()
return status, message, None
status, message = impact_function.run()
if status != ANALYSIS_SUCCESS:
print message.to_text()
return status, message, None
return status, message, impact_function
def test_vector_post_minimum_needs_value_generation(self):
"""Test minimum needs postprocessors on vector exposure.
Test with vector exposure data with population_count_field exists.
Minimum needs postprocessors is defined to only generate values when
exposure contains population data.
"""
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'tsunami_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'population.geojson')
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
return_code, message = impact_function.run()
self.assertEqual(return_code, ANALYSIS_SUCCESS, message)
# minimum needs fields should exists in the results
self._check_minimum_fields_exists(impact_function)
expected_value = {
u'population': 69,
u'total': 9.0,
u'minimum_needs__rice': 491,
u'minimum_needs__clean_water': 11763,
u'minimum_needs__toilets': 8,
u'minimum_needs__drinking_water': 3072,
u'minimum_needs__family_kits': 35,
u'male': 34,
u'female': 34,
u'youth': 17,
u'adult': 45,
u'elderly': 6,
u'total_affected': 6.0,
}
self._check_minimum_fields_value(expected_value, impact_function)
def test_vector_post_minimum_needs_value_generation(self):
"""Test minimum needs postprocessors on vector exposure.
Test with vector exposure data with population_count_field exists.
Minimum needs postprocessors is defined to only generate values when
exposure contains population data.
"""
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'tsunami_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'population.geojson')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
return_code, message = impact_function.run()
self.assertEqual(return_code, ANALYSIS_SUCCESS, message)
# minimum needs fields should exists in the results
self._check_minimum_fields_exists(impact_function)
expected_value = {
u'population': 69,
u'total': 9.0,
u'minimum_needs__rice': 491,
u'minimum_needs__clean_water': 11763,
u'minimum_needs__toilets': 8,
u'minimum_needs__drinking_water': 3072,
u'minimum_needs__family_kits': 35,
u'male': 34,
u'female': 34,
u'youth': 17,
u'adult': 45,
u'elderly': 6,
u'total_affected': 6.0,
}
self._check_minimum_fields_value(expected_value, impact_function)
def impact_function_setup(command_line_arguments,
hazard,
exposure,
aggregation=None):
"""Sets up an analysis object.
.. versionadded:: 3.2
:param command_line_arguments: User inputs.
:type command_line_arguments: CommandLineArguments
:param hazard: Hazard layer
:type hazard: QgsLayer
:param exposure: Exposure Layer
:type exposure: QgsLayer
:param aggregation: Aggregation Layer
:type aggregation: QgsLayer
:raises: Exception
"""
# IF
impact_function = ImpactFunction()
impact_function.hazard = hazard
impact_function.exposure = exposure
impact_function.aggregation = aggregation
impact_function.map_canvas = CANVAS
# QSetting context
settings = QSettings()
crs = settings.value('inasafe/user_extent_crs', '', type=str)
impact_function.requested_extent_crs = QgsCoordinateReferenceSystem(crs)
try:
impact_function.requested_extent = QgsRectangle(
float(command_line_arguments.extent[0]),
float(command_line_arguments.extent[1]),
float(command_line_arguments.extent[2]),
float(command_line_arguments.extent[3]))
except AttributeError:
print "No extents"
pass
return impact_function
def impact_function_setup(
command_line_arguments, hazard, exposure, aggregation=None):
"""Sets up an analysis object.
.. versionadded:: 3.2
:param command_line_arguments: User inputs.
:type command_line_arguments: CommandLineArguments
:param hazard: Hazard layer
:type hazard: QgsLayer
:param exposure: Exposure Layer
:type exposure: QgsLayer
:param aggregation: Aggregation Layer
:type aggregation: QgsLayer
:raises: Exception
"""
# IF
impact_function = ImpactFunction()
impact_function.hazard = hazard
impact_function.exposure = exposure
impact_function.aggregation = aggregation
impact_function.map_canvas = CANVAS
# QSetting context
settings = QSettings()
crs = settings.value('inasafe/user_extent_crs', '', type=str)
impact_function.requested_extent_crs = QgsCoordinateReferenceSystem(crs)
try:
impact_function.requested_extent = QgsRectangle(
float(command_line_arguments.extent[0]),
float(command_line_arguments.extent[1]),
float(command_line_arguments.extent[2]),
float(command_line_arguments.extent[3])
)
except AttributeError:
print "No extents"
pass
return impact_function
def test_provenance_with_aggregation(self):
"""Test provenance of impact function with aggregation."""
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'building-points.geojson')
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
hazard = definition(hazard_layer.keywords['hazard'])
exposure = definition(exposure_layer.keywords['exposure'])
hazard_category = definition(hazard_layer.keywords['hazard_category'])
expected_provenance = {
provenance_gdal_version['provenance_key']:
gdal.__version__,
provenance_host_name['provenance_key']:
gethostname(),
provenance_map_title['provenance_key']:
get_map_title(hazard, exposure, hazard_category),
provenance_map_legend_title['provenance_key']:
exposure['layer_legend_title'],
provenance_user['provenance_key']:
getpass.getuser(),
provenance_os['provenance_key']:
readable_os_version(),
provenance_pyqt_version['provenance_key']:
PYQT_VERSION_STR,
provenance_qgis_version['provenance_key']:
QGis.QGIS_VERSION,
provenance_qt_version['provenance_key']:
QT_VERSION_STR,
provenance_inasafe_version['provenance_key']:
get_version(),
provenance_aggregation_layer['provenance_key']:
aggregation_layer.source(),
provenance_aggregation_layer_id['provenance_key']:
aggregation_layer.id(),
provenance_exposure_layer['provenance_key']:
exposure_layer.source(),
provenance_exposure_layer_id['provenance_key']:
exposure_layer.id(),
provenance_hazard_layer['provenance_key']:
hazard_layer.source(),
provenance_hazard_layer_id['provenance_key']:
hazard_layer.id(),
provenance_analysis_question['provenance_key']:
get_analysis_question(hazard, exposure),
provenance_aggregation_keywords['provenance_key']:
deepcopy(aggregation_layer.keywords),
provenance_exposure_keywords['provenance_key']:
deepcopy(exposure_layer.keywords),
provenance_hazard_keywords['provenance_key']:
deepcopy(hazard_layer.keywords),
}
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
self.maxDiff = None
expected_provenance.update({
provenance_action_checklist['provenance_key']:
impact_function.action_checklist(),
provenance_analysis_extent['provenance_key']:
impact_function.analysis_extent.exportToWkt(),
provenance_impact_function_name['provenance_key']:
impact_function.name,
provenance_impact_function_title['provenance_key']:
impact_function.title,
provenance_notes['provenance_key']:
impact_function.notes(),
provenance_requested_extent['provenance_key']:
impact_function.requested_extent,
provenance_data_store_uri['provenance_key']:
impact_function.datastore.uri_path,
provenance_start_datetime['provenance_key']:
impact_function.start_datetime,
provenance_end_datetime['provenance_key']:
impact_function.end_datetime,
provenance_duration['provenance_key']:
impact_function.duration
})
self.assertDictContainsSubset(expected_provenance,
impact_function.provenance)
output_layer_provenance_keys = [
provenance_layer_exposure_summary['provenance_key'],
provenance_layer_aggregate_hazard_impacted['provenance_key'],
provenance_layer_aggregation_summary['provenance_key'],
provenance_layer_analysis_impacted['provenance_key'],
provenance_layer_exposure_summary_table['provenance_key']
]
for key in output_layer_provenance_keys:
self.assertIn(key, impact_function.provenance.keys())
def test_ratios_with_raster_exposure(self):
"""Test if we can add defaults to a raster exposure.
See ticket #3851 how to manage ratios with a raster exposure.
"""
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'tsunami_vector.geojson')
exposure_layer = load_test_raster_layer('gisv4', 'exposure', 'raster',
'population.asc')
# Set up impact function
impact_function = ImpactFunction()
impact_function.debug_mode = True
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.prepare()
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
for layer in impact_function.outputs:
if layer.keywords['layer_purpose'] == (
layer_purpose_analysis_impacted['key']):
analysis = layer
if layer.keywords['layer_purpose'] == (
layer_purpose_aggregate_hazard_impacted['key']):
impact = layer
# We check in the impact layer if we have :
# female default ratio with the default value
index = impact.fieldNameIndex(female_ratio_field['field_name'])
self.assertNotEqual(-1, index)
unique_values = impact.uniqueValues(index)
self.assertEqual(1, len(unique_values))
female_ratio = unique_values[0]
# female displaced count and youth displaced count
self.assertNotEqual(
-1,
impact.fieldNameIndex(female_displaced_count_field['field_name']))
self.assertNotEqual(
-1,
impact.fieldNameIndex(youth_displaced_count_field['field_name']))
# Check that we have more than 0 female displaced in the analysis layer
index = analysis.fieldNameIndex(
female_displaced_count_field['field_name'])
female_displaced = analysis.uniqueValues(index)[0]
self.assertGreater(female_displaced, 0)
# Let's check computation
index = analysis.fieldNameIndex(displaced_field['field_name'])
displaced_population = analysis.uniqueValues(index)[0]
self.assertEqual(int(displaced_population * female_ratio),
female_displaced)
# Check that we have more than 0 youth displaced in the analysis layer
index = analysis.fieldNameIndex(
female_displaced_count_field['field_name'])
value = analysis.uniqueValues(index)[0]
self.assertGreater(value, 0)
# Let do another test with the special aggregation layer
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'tsunami_vector.geojson')
exposure_layer = load_test_raster_layer('gisv4', 'exposure', 'raster',
'population.asc')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid_ratios.geojson')
# This aggregation layer has :
# * a field for female ratio : 1, 0.5 and 0
# * use global default for youth ratio
# * do not ust for adult ratio
# * use custom 0.75 for elderly ratio
# Set up impact function
impact_function = ImpactFunction()
impact_function.debug_mode = True
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.aggregation = aggregation_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# We should have a female_ratio with many values
index = impact.fieldNameIndex(female_ratio_field['field_name'])
self.assertNotEqual(-1, index)
values = impact.uniqueValues(index)
self.assertEqual(3, len(values))
# We should have a youth_ratio with global default
index = impact.fieldNameIndex(youth_ratio_field['field_name'])
self.assertNotEqual(-1, index)
values = impact.uniqueValues(index)
self.assertEqual(1, len(values))
# We should not have an adult_ratio
index = impact.fieldNameIndex(adult_ratio_field['field_name'])
self.assertEqual(-1, index)
# We should have a elderly_ratio = 0.75
index = impact.fieldNameIndex(elderly_ratio_field['field_name'])
self.assertNotEqual(-1, index)
values = impact.uniqueValues(index)
self.assertEqual(1, len(values))
self.assertEqual(0.75, values[0])
def test_ratios_with_vector_exposure(self):
"""Test if we can add defaults to a vector exposure."""
# First test, if we do not provide an aggregation,
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'population.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.prepare()
# Let's remove one field from keywords.
# We monkey patch keywords for testing after `prepare` & before `run`.
fields = impact_function.exposure.keywords['inasafe_fields']
del fields[female_count_field['key']]
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# We check the field exist after the IF with only one value.
field = impact.fieldNameIndex(female_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertEqual(1, len(unique_ratio), unique_ratio)
self.assertEqual(unique_ratio[0],
female_ratio_default_value['default_value'])
# Second test, if we provide an aggregation without a default ratio 0.2
expected_ratio = 1.0
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'population.geojson')
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.debug_mode = True
impact_function.prepare()
# The `prepare` reads keywords from the file.
impact_function.aggregation.keywords['inasafe_default_values'] = {
elderly_ratio_field['key']: expected_ratio
}
fields = impact_function.exposure.keywords['inasafe_fields']
del fields[female_count_field['key']]
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# We check the field exist after the IF with only original values.
field = impact.fieldNameIndex(female_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertEqual(3, len(unique_ratio), unique_ratio)
# We check the field exist after the IF with only one value.
field = impact.fieldNameIndex(elderly_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertEqual(1, len(unique_ratio), unique_ratio)
self.assertEqual(expected_ratio, unique_ratio[0])
# Third test, if we provide an aggregation with a ratio and the
# exposure has a count, we should a have a ratio from the exposure
# count.
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'population.geojson')
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.debug_mode = True
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.aggregation = aggregation_layer
impact_function.prepare()
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# Check that we have don't have only one unique value since the ratio
# depends on the "population / female count" and we should have at
# least different ratios.
field = impact.fieldNameIndex(female_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertNotEqual(1, len(unique_ratio), unique_ratio)
def test_minimum_extent(self):
"""Test we can compute the minimum extent in the IF."""
# Without aggregation layer
hazard_layer = load_test_vector_layer(
'hazard', 'flood_multipart_polygons.shp')
exposure_layer = load_test_vector_layer('exposure', 'roads.shp')
impact_function = ImpactFunction()
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent without an aggregation layer is '
'failing.')
self.assertTrue(
compare_wkt(
'Polygon (('
'106.8080099999999959 -6.19531000000000009, '
'106.8080099999999959 -6.16752599999999962, '
'106.83456946836641066 -6.16752599999999962, '
'106.83456946836641066 -6.19531000000000009, '
'106.8080099999999959 -6.19531000000000009))',
impact_function.analysis_extent.exportToWkt()),
message
)
# Without aggregation layer but with a requested_extent
hazard_layer = load_test_vector_layer(
'hazard', 'flood_multipart_polygons.shp')
exposure_layer = load_test_vector_layer('exposure', 'roads.shp')
impact_function = ImpactFunction()
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.requested_extent = wkt_to_rectangle(
'POLYGON (('
'106.772279 -6.237576, '
'106.772279 -6.165415, '
'106.885165 -6.165415, '
'106.885165 -6.237576, '
'106.772279 -6.237576'
'))')
impact_function.requested_extent_crs = QgsCoordinateReferenceSystem(
4326)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent without an aggregation layer but '
'with a requested extent is failing.')
self.assertTrue(
compare_wkt(
'Polygon (('
'106.8080099999999959 -6.19531000000000009, '
'106.8080099999999959 -6.16752599999999962, '
'106.83456946836641066 -6.16752599999999962, '
'106.83456946836641066 -6.19531000000000009, '
'106.8080099999999959 -6.19531000000000009))',
impact_function.analysis_extent.exportToWkt()),
message
)
# With an aggregation layer, without selection
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'building-points.geojson')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.use_selected_features_only = False
impact_function.aggregation.select(0)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent with an aggregation layer is '
'failing.')
self.assertTrue(
compare_wkt(
'Polygon ((106.9033179652593617 -6.18324454090033182, '
'106.90331796525939012 -6.2725478115989306, '
'106.72365490843547775 -6.2725478115989306, '
'106.72365490843547775 -6.18324645462287137, '
'106.72365490843547775 -6.09392810187095257, '
'106.81348643684744104 -6.09392810187095257, '
'106.9033179652593617 -6.09392810187095257, '
'106.9033179652593617 -6.18324454090033182))',
impact_function.analysis_extent.exportToWkt()),
message
)
# With an aggregation layer, with selection
impact_function.use_selected_features_only = True
impact_function.aggregation = aggregation_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent with an aggregation layer and '
'a selection is failing.')
self.assertTrue(
compare_wkt(
'Polygon ((106.72365490843547775 -6.09392810187095257, '
'106.81348643684744104 -6.09392810187095257, '
'106.81348643684744104 -6.18324645462287137, '
'106.72365490843547775 -6.18324645462287137, '
'106.72365490843547775 -6.09392810187095257))',
impact_function.analysis_extent.exportToWkt()),
message
)
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 test_provenance_with_aggregation(self):
"""Test provenance of impact function with aggregation."""
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'building-points.geojson')
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
hazard = definition(hazard_layer.keywords['hazard'])
exposure = definition(exposure_layer.keywords['exposure'])
hazard_category = definition(hazard_layer.keywords['hazard_category'])
expected_provenance = {
'gdal_version': gdal.__version__,
'host_name': gethostname(),
'map_title': get_map_title(hazard, exposure, hazard_category),
'map_legend_title': exposure['layer_legend_title'],
'user': getpass.getuser(),
'os': readable_os_version(),
'pyqt_version': PYQT_VERSION_STR,
'qgis_version': QGis.QGIS_VERSION,
'qt_version': QT_VERSION_STR,
'inasafe_version': get_version(),
'aggregation_layer': aggregation_layer.source(),
'aggregation_layer_id': aggregation_layer.id(),
'exposure_layer': exposure_layer.source(),
'exposure_layer_id': exposure_layer.id(),
'hazard_layer': hazard_layer.source(),
'hazard_layer_id': hazard_layer.id(),
'analysis_question': get_analysis_question(hazard, exposure),
'aggregation_keywords': deepcopy(aggregation_layer.keywords),
'exposure_keywords': deepcopy(exposure_layer.keywords),
'hazard_keywords': deepcopy(hazard_layer.keywords),
}
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
self.maxDiff = None
expected_provenance.update({
'action_checklist':
impact_function.action_checklist(),
'analysis_extent':
impact_function.analysis_extent.exportToWkt(),
'impact_function_name':
impact_function.name,
'impact_function_title':
impact_function.title,
'notes':
impact_function.notes(),
'requested_extent':
impact_function.requested_extent,
'data_store_uri':
impact_function.datastore.uri_path,
'start_datetime':
impact_function.start_datetime,
'end_datetime':
impact_function.end_datetime,
'duration':
impact_function.duration
})
self.assertDictEqual(expected_provenance, impact_function.provenance)
def test_provenance_with_aggregation(self):
"""Test provenance of impact function with aggregation."""
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'building-points.geojson')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
hazard = definition(hazard_layer.keywords['hazard'])
exposure = definition(exposure_layer.keywords['exposure'])
hazard_category = definition(hazard_layer.keywords['hazard_category'])
expected_provenance = {
'gdal_version': gdal.__version__,
'host_name': gethostname(),
'map_title': get_map_title(hazard, exposure, hazard_category),
'map_legend_title': exposure['layer_legend_title'],
'user': getpass.getuser(),
'os': readable_os_version(),
'pyqt_version': PYQT_VERSION_STR,
'qgis_version': QGis.QGIS_VERSION,
'qt_version': QT_VERSION_STR,
'inasafe_version': get_version(),
'aggregation_layer': aggregation_layer.source(),
'aggregation_layer_id': aggregation_layer.id(),
'exposure_layer': exposure_layer.source(),
'exposure_layer_id': exposure_layer.id(),
'hazard_layer': hazard_layer.source(),
'hazard_layer_id': hazard_layer.id(),
'analysis_question': get_analysis_question(hazard, exposure),
'aggregation_keywords': deepcopy(aggregation_layer.keywords),
'exposure_keywords': deepcopy(exposure_layer.keywords),
'hazard_keywords': deepcopy(hazard_layer.keywords),
}
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
self.maxDiff = None
expected_provenance.update({
'action_checklist': impact_function.action_checklist(),
'analysis_extent': impact_function.analysis_extent.exportToWkt(),
'impact_function_name': impact_function.name,
'impact_function_title': impact_function.title,
'notes': impact_function.notes(),
'requested_extent': impact_function.requested_extent,
'data_store_uri': impact_function.datastore.uri_path,
'start_datetime': impact_function.start_datetime,
'end_datetime': impact_function.end_datetime,
'duration': impact_function.duration
})
self.assertDictEqual(expected_provenance, impact_function.provenance)
def test_provenance_with_aggregation(self):
"""Test provenance of impact function with aggregation."""
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'building-points.geojson')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
hazard = definition(hazard_layer.keywords['hazard'])
exposure = definition(exposure_layer.keywords['exposure'])
hazard_category = definition(hazard_layer.keywords['hazard_category'])
expected_provenance = {
provenance_gdal_version['provenance_key']: gdal.__version__,
provenance_host_name['provenance_key']: gethostname(),
provenance_map_title['provenance_key']: get_map_title(
hazard, exposure, hazard_category),
provenance_map_legend_title['provenance_key']: exposure[
'layer_legend_title'],
provenance_user['provenance_key']: getpass.getuser(),
provenance_os['provenance_key']: readable_os_version(),
provenance_pyqt_version['provenance_key']: PYQT_VERSION_STR,
provenance_qgis_version['provenance_key']: QGis.QGIS_VERSION,
provenance_qt_version['provenance_key']: QT_VERSION_STR,
provenance_inasafe_version['provenance_key']: get_version(),
provenance_aggregation_layer['provenance_key']:
aggregation_layer.source(),
provenance_aggregation_layer_id['provenance_key']:
aggregation_layer.id(),
provenance_exposure_layer['provenance_key']:
exposure_layer.source(),
provenance_exposure_layer_id['provenance_key']:
exposure_layer.id(),
provenance_hazard_layer['provenance_key']: hazard_layer.source(),
provenance_hazard_layer_id['provenance_key']: hazard_layer.id(),
provenance_analysis_question['provenance_key']:
get_analysis_question(hazard, exposure),
provenance_aggregation_keywords['provenance_key']: deepcopy(
aggregation_layer.keywords),
provenance_exposure_keywords['provenance_key']:
deepcopy(exposure_layer.keywords),
provenance_hazard_keywords['provenance_key']: deepcopy(
hazard_layer.keywords),
}
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
self.assertDictEqual({}, impact_function.provenance)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
self.maxDiff = None
expected_provenance.update({
provenance_action_checklist['provenance_key']:
impact_function.action_checklist(),
provenance_analysis_extent['provenance_key']:
impact_function.analysis_extent.exportToWkt(),
provenance_impact_function_name['provenance_key']:
impact_function.name,
provenance_impact_function_title['provenance_key']:
impact_function.title,
provenance_notes['provenance_key']: impact_function.notes(),
provenance_requested_extent['provenance_key']: impact_function.
requested_extent,
provenance_data_store_uri['provenance_key']: impact_function.
datastore.uri_path,
provenance_start_datetime['provenance_key']: impact_function.
start_datetime,
provenance_end_datetime['provenance_key']:
impact_function.end_datetime,
provenance_duration['provenance_key']: impact_function.duration
})
self.assertDictContainsSubset(
expected_provenance, impact_function.provenance)
output_layer_provenance_keys = [
provenance_layer_exposure_summary['provenance_key'],
provenance_layer_aggregate_hazard_impacted['provenance_key'],
provenance_layer_aggregation_summary['provenance_key'],
provenance_layer_analysis_impacted['provenance_key'],
provenance_layer_exposure_summary_table['provenance_key']
]
for key in output_layer_provenance_keys:
self.assertIn(key, impact_function.provenance.keys())
def test_ratios_with_raster_exposure(self):
"""Test if we can add defaults to a raster exposure.
See ticket #3851 how to manage ratios with a raster exposure.
"""
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'tsunami_vector.geojson')
exposure_layer = load_test_raster_layer(
'gisv4', 'exposure', 'raster', 'population.asc')
# Set up impact function
impact_function = ImpactFunction()
impact_function.debug_mode = True
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.prepare()
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
for layer in impact_function.outputs:
if layer.keywords['layer_purpose'] == (
layer_purpose_analysis_impacted['key']):
analysis = layer
if layer.keywords['layer_purpose'] == (
layer_purpose_aggregate_hazard_impacted['key']):
impact = layer
# We check in the impact layer if we have :
# female default ratio with the default value
index = impact.fieldNameIndex(female_ratio_field['field_name'])
self.assertNotEqual(-1, index)
unique_values = impact.uniqueValues(index)
self.assertEqual(1, len(unique_values))
female_ratio = unique_values[0]
# female displaced count and youth displaced count
self.assertNotEqual(
-1, impact.fieldNameIndex(
female_displaced_count_field['field_name']))
self.assertNotEqual(
-1, impact.fieldNameIndex(
youth_displaced_count_field['field_name']))
# Check that we have more than 0 female displaced in the analysis layer
index = analysis.fieldNameIndex(
female_displaced_count_field['field_name'])
female_displaced = analysis.uniqueValues(index)[0]
self.assertGreater(female_displaced, 0)
# Let's check computation
index = analysis.fieldNameIndex(
displaced_field['field_name'])
displaced_population = analysis.uniqueValues(index)[0]
self.assertEqual(
int(displaced_population * female_ratio), female_displaced)
# Check that we have more than 0 youth displaced in the analysis layer
index = analysis.fieldNameIndex(
female_displaced_count_field['field_name'])
value = analysis.uniqueValues(index)[0]
self.assertGreater(value, 0)
# Let do another test with the special aggregation layer
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'tsunami_vector.geojson')
exposure_layer = load_test_raster_layer(
'gisv4', 'exposure', 'raster', 'population.asc')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid_ratios.geojson')
# This aggregation layer has :
# * a field for female ratio : 1, 0.5 and 0
# * use global default for youth ratio
# * do not ust for adult ratio
# * use custom 0.75 for elderly ratio
# Set up impact function
impact_function = ImpactFunction()
impact_function.debug_mode = True
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.aggregation = aggregation_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# We should have a female_ratio with many values
index = impact.fieldNameIndex(female_ratio_field['field_name'])
self.assertNotEqual(-1, index)
values = impact.uniqueValues(index)
self.assertEqual(3, len(values))
# We should have a youth_ratio with global default
index = impact.fieldNameIndex(youth_ratio_field['field_name'])
self.assertNotEqual(-1, index)
values = impact.uniqueValues(index)
self.assertEqual(1, len(values))
# We should not have an adult_ratio
index = impact.fieldNameIndex(adult_ratio_field['field_name'])
self.assertEqual(-1, index)
# We should have a elderly_ratio = 0.75
index = impact.fieldNameIndex(elderly_ratio_field['field_name'])
self.assertNotEqual(-1, index)
values = impact.uniqueValues(index)
self.assertEqual(1, len(values))
self.assertEqual(0.75, values[0])
def test_ratios_with_vector_exposure(self):
"""Test if we can add defaults to a vector exposure."""
# First test, if we do not provide an aggregation,
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'population.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.prepare()
# Let's remove one field from keywords.
# We monkey patch keywords for testing after `prepare` & before `run`.
fields = impact_function.exposure.keywords['inasafe_fields']
del fields[female_count_field['key']]
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# We check the field exist after the IF with only one value.
field = impact.fieldNameIndex(
female_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertEqual(1, len(unique_ratio), unique_ratio)
self.assertEqual(
unique_ratio[0], female_ratio_default_value['default_value'])
# Second test, if we provide an aggregation without a default ratio 0.2
expected_ratio = 1.0
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'population.geojson')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.debug_mode = True
impact_function.prepare()
# The `prepare` reads keywords from the file.
impact_function.aggregation.keywords['inasafe_default_values'] = {
elderly_ratio_field['key']: expected_ratio
}
fields = impact_function.exposure.keywords['inasafe_fields']
del fields[female_count_field['key']]
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# We check the field exist after the IF with only original values.
field = impact.fieldNameIndex(
female_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertEqual(3, len(unique_ratio), unique_ratio)
# We check the field exist after the IF with only one value.
field = impact.fieldNameIndex(
elderly_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertEqual(1, len(unique_ratio), unique_ratio)
self.assertEqual(expected_ratio, unique_ratio[0])
# Third test, if we provide an aggregation with a ratio and the
# exposure has a count, we should a have a ratio from the exposure
# count.
hazard_layer = load_test_vector_layer(
'gisv4', 'hazard', 'classified_vector.geojson')
exposure_layer = load_test_vector_layer(
'gisv4', 'exposure', 'population.geojson')
aggregation_layer = load_test_vector_layer(
'gisv4', 'aggregation', 'small_grid.geojson')
# Set up impact function
impact_function = ImpactFunction()
impact_function.debug_mode = True
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.aggregation = aggregation_layer
impact_function.prepare()
status, message = impact_function.run()
self.assertEqual(ANALYSIS_SUCCESS, status, message)
impact = impact_function.impact
# Check that we have don't have only one unique value since the ratio
# depends on the "population / female count" and we should have at
# least different ratios.
field = impact.fieldNameIndex(
female_ratio_field['field_name'])
self.assertNotEqual(-1, field)
unique_ratio = impact.uniqueValues(field)
self.assertNotEqual(1, len(unique_ratio), unique_ratio)
def run_task(self, task_item, status_item, count=0, index=''):
"""Run a single task.
:param task_item: Table task_item containing task name / details.
:type task_item: QTableWidgetItem
:param status_item: Table task_item that holds the task status.
:type status_item: QTableWidgetItem
:param count: Count of scenarios that have been run already.
:type count:
:param index: The index for the table item that will be run.
:type index: int
:returns: Flag indicating if the task succeeded or not.
:rtype: bool
"""
self.enable_busy_cursor()
for layer_group in self.layer_group_container:
layer_group.setItemVisibilityChecked(False)
# set status to 'running'
status_item.setText(self.tr('Running'))
# .. see also:: :func:`appendRow` to understand the next 2 lines
variant = task_item.data(QtCore.Qt.UserRole)
value = variant[0]
result = True
if isinstance(value, str):
filename = value
# run script
try:
self.run_script(filename)
# set status to 'OK'
status_item.setText(self.tr('Script OK'))
except Exception as e: # pylint: disable=W0703
# set status to 'fail'
status_item.setText(self.tr('Script Fail'))
LOGGER.exception(
'Running macro failed. The exception: ' + str(e))
result = False
elif isinstance(value, dict):
# start in new project if toggle is active
if self.start_in_new_project:
self.iface.newProject()
# create layer group
group_name = value['scenario_name']
self.layer_group = self.root.addGroup(group_name)
self.layer_group_container.append(self.layer_group)
# Its a dict containing files for a scenario
success, parameters = self.prepare_task(value)
if not success:
# set status to 'running'
status_item.setText(self.tr('Please update scenario'))
self.disable_busy_cursor()
return False
directory = self.output_directory.text()
if self.scenario_directory_radio.isChecked():
directory = self.source_directory.text()
output_directory = os.path.join(directory, group_name)
if not os.path.exists(output_directory):
os.makedirs(output_directory)
# If impact function parameters loaded successfully, initiate IF.
impact_function = ImpactFunction()
impact_function.datastore = Folder(output_directory)
impact_function.datastore.default_vector_format = "geojson"
impact_function.hazard = parameters[layer_purpose_hazard['key']]
impact_function.exposure = (
parameters[layer_purpose_exposure['key']])
if parameters[layer_purpose_aggregation['key']]:
impact_function.aggregation = (
parameters[layer_purpose_aggregation['key']])
elif parameters['extent']:
impact_function.requested_extent = parameters['extent']
impact_function.crs = parameters['crs']
prepare_status, prepare_message = impact_function.prepare()
if prepare_status == PREPARE_SUCCESS:
LOGGER.info('Impact function ready')
status, message = impact_function.run()
if status == ANALYSIS_SUCCESS:
status_item.setText(self.tr('Analysis Success'))
impact_layer = impact_function.impact
if impact_layer.isValid():
layer_list = [
impact_layer,
impact_function.analysis_impacted,
parameters[layer_purpose_hazard['key']],
parameters[layer_purpose_exposure['key']],
parameters[layer_purpose_aggregation['key']]]
QgsProject.instance().addMapLayers(
layer_list, False)
for layer in layer_list:
self.layer_group.addLayer(layer)
map_canvas = QgsProject.instance().mapLayers()
for layer in map_canvas:
# turn of layer visibility if not impact layer
if map_canvas[layer].id() == impact_layer.id():
self.set_layer_visible(
map_canvas[layer], True)
else:
self.set_layer_visible(
map_canvas[layer], False)
# we need to set analysis_impacted as an active layer
# because we need to get all qgis variables that we
# need from this layer for infographic.
if self.iface:
self.iface.setActiveLayer(
impact_function.analysis_impacted)
report_directory = os.path.join(
output_directory, 'output')
# generate map report and impact report
try:
error_code, message = (
impact_function.generate_report(
all_default_report_components,
report_directory))
except BaseException:
status_item.setText(
self.tr('Report failed to generate.'))
else:
LOGGER.info('Impact layer is invalid')
elif status == ANALYSIS_FAILED_BAD_INPUT:
LOGGER.info('Bad input detected')
elif status == ANALYSIS_FAILED_BAD_CODE:
LOGGER.info(
'Impact function encountered a bug: %s' % message)
else:
LOGGER.warning('Impact function not ready')
send_error_message(self, prepare_message)
else:
LOGGER.exception('Data type not supported: "%s"' % value)
result = False
self.disable_busy_cursor()
return result
def test_minimum_extent(self):
"""Test we can compute the minimum extent in the IF."""
# Without aggregation layer
hazard_layer = load_test_vector_layer('hazard',
'flood_multipart_polygons.shp')
exposure_layer = load_test_vector_layer('exposure', 'roads.shp')
impact_function = ImpactFunction()
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent without an aggregation layer is '
'failing.')
self.assertTrue(
compare_wkt(
'Polygon (('
'106.8080099999999959 -6.19531000000000009, '
'106.8080099999999959 -6.16752599999999962, '
'106.83456946836641066 -6.16752599999999962, '
'106.83456946836641066 -6.19531000000000009, '
'106.8080099999999959 -6.19531000000000009))',
impact_function.analysis_extent.exportToWkt()), message)
# Without aggregation layer but with a requested_extent
hazard_layer = load_test_vector_layer('hazard',
'flood_multipart_polygons.shp')
exposure_layer = load_test_vector_layer('exposure', 'roads.shp')
impact_function = ImpactFunction()
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.requested_extent = wkt_to_rectangle(
'POLYGON (('
'106.772279 -6.237576, '
'106.772279 -6.165415, '
'106.885165 -6.165415, '
'106.885165 -6.237576, '
'106.772279 -6.237576'
'))')
impact_function.requested_extent_crs = QgsCoordinateReferenceSystem(
4326)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent without an aggregation layer but '
'with a requested extent is failing.')
self.assertTrue(
compare_wkt(
'Polygon (('
'106.8080099999999959 -6.19531000000000009, '
'106.8080099999999959 -6.16752599999999962, '
'106.83456946836641066 -6.16752599999999962, '
'106.83456946836641066 -6.19531000000000009, '
'106.8080099999999959 -6.19531000000000009))',
impact_function.analysis_extent.exportToWkt()), message)
# With an aggregation layer, without selection
hazard_layer = load_test_vector_layer('gisv4', 'hazard',
'classified_vector.geojson')
exposure_layer = load_test_vector_layer('gisv4', 'exposure',
'building-points.geojson')
aggregation_layer = load_test_vector_layer('gisv4', 'aggregation',
'small_grid.geojson')
impact_function = ImpactFunction()
impact_function.aggregation = aggregation_layer
impact_function.exposure = exposure_layer
impact_function.hazard = hazard_layer
impact_function.use_selected_features_only = False
impact_function.aggregation.select(0)
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent with an aggregation layer is '
'failing.')
self.assertTrue(
compare_wkt(
'Polygon ((106.9033179652593617 -6.18324454090033182, '
'106.90331796525939012 -6.2725478115989306, '
'106.72365490843547775 -6.2725478115989306, '
'106.72365490843547775 -6.18324645462287137, '
'106.72365490843547775 -6.09392810187095257, '
'106.81348643684744104 -6.09392810187095257, '
'106.9033179652593617 -6.09392810187095257, '
'106.9033179652593617 -6.18324454090033182))',
impact_function.analysis_extent.exportToWkt()), message)
# With an aggregation layer, with selection
impact_function.use_selected_features_only = True
impact_function.aggregation = aggregation_layer
status, message = impact_function.prepare()
self.assertEqual(PREPARE_SUCCESS, status, message)
message = (
'Test about the minimum extent with an aggregation layer and '
'a selection is failing.')
self.assertTrue(
compare_wkt(
'Polygon ((106.72365490843547775 -6.09392810187095257, '
'106.81348643684744104 -6.09392810187095257, '
'106.81348643684744104 -6.18324645462287137, '
'106.72365490843547775 -6.18324645462287137, '
'106.72365490843547775 -6.09392810187095257))',
impact_function.analysis_extent.exportToWkt()), message)
def run_task(self, task_item, status_item, count=0, index=''):
"""Run a single task.
:param task_item: Table task_item containing task name / details.
:type task_item: QTableWidgetItem
:param status_item: Table task_item that holds the task status.
:type status_item: QTableWidgetItem
:param count: Count of scenarios that have been run already.
:type count:
:param index: The index for the table item that will be run.
:type index: int
:returns: Flag indicating if the task succeeded or not.
:rtype: bool
"""
self.enable_busy_cursor()
for layer_group in self.layer_group_container:
layer_group.setVisible(False)
# set status to 'running'
status_item.setText(self.tr('Running'))
# .. see also:: :func:`appendRow` to understand the next 2 lines
variant = task_item.data(QtCore.Qt.UserRole)
value = variant[0]
result = True
if isinstance(value, str):
filename = value
# run script
try:
self.run_script(filename)
# set status to 'OK'
status_item.setText(self.tr('Script OK'))
except Exception as e: # pylint: disable=W0703
# set status to 'fail'
status_item.setText(self.tr('Script Fail'))
LOGGER.exception('Running macro failed. The exception: ' +
str(e))
result = False
elif isinstance(value, dict):
# start in new project if toggle is active
if self.start_in_new_project:
self.iface.newProject()
# create layer group
group_name = value['scenario_name']
self.layer_group = self.root.addGroup(group_name)
self.layer_group_container.append(self.layer_group)
# Its a dict containing files for a scenario
success, parameters = self.prepare_task(value)
if not success:
# set status to 'running'
status_item.setText(self.tr('Please update scenario'))
self.disable_busy_cursor()
return False
# If impact function parameters loaded successfully, initiate IF.
impact_function = ImpactFunction()
impact_function.hazard = parameters[layer_purpose_hazard['key']]
impact_function.exposure = (
parameters[layer_purpose_exposure['key']])
if parameters[layer_purpose_aggregation['key']]:
impact_function.aggregation = (
parameters[layer_purpose_aggregation['key']])
elif parameters['extent']:
impact_function.requested_extent = parameters['extent']
impact_function.requested_extent_crs = parameters['crs']
prepare_status, prepare_message = impact_function.prepare()
if prepare_status == PREPARE_SUCCESS:
LOGGER.info('Impact function ready')
status, message = impact_function.run()
if status == ANALYSIS_SUCCESS:
status_item.setText(self.tr('Analysis Success'))
impact_layer = impact_function.impact
if impact_layer.isValid():
layer_list = [
impact_layer,
parameters[layer_purpose_hazard['key']],
parameters[layer_purpose_exposure['key']],
parameters[layer_purpose_aggregation['key']]]
QgsMapLayerRegistry.instance().addMapLayers(
layer_list, False)
for layer in layer_list:
self.layer_group.addLayer(layer)
map_canvas = QgsMapLayerRegistry.instance().mapLayers()
for layer in map_canvas:
# turn of layer visibility if not impact layer
if map_canvas[layer].id() == impact_layer.id():
self.legend.setLayerVisible(
map_canvas[layer], True)
else:
self.legend.setLayerVisible(
map_canvas[layer], False)
# generate map report and impact report
try:
# this line is to save the impact report in default
# InaSAFE directory.
generate_impact_report(impact_function, self.iface)
generate_impact_map_report(
impact_function,
self.iface)
# this line is to save the report in user specified
# directory.
self.generate_pdf_report(
impact_function,
self.iface,
group_name)
except:
status_item.setText(
self.tr('Report failed to generate.'))
else:
LOGGER.info('Impact layer is invalid')
elif status == ANALYSIS_FAILED_BAD_INPUT:
LOGGER.info('Bad input detected')
elif status == ANALYSIS_FAILED_BAD_CODE:
LOGGER.info('Impact function encountered a bug')
else:
LOGGER.warning('Impact function not ready')
send_error_message(self, prepare_message)
else:
LOGGER.exception('Data type not supported: "%s"' % value)
result = False
self.disable_busy_cursor()
return result
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
