def analysis_execution():
from safe.test.utilities import get_qgis_app
# get_qgis_app must be called before importing Analysis
QGIS_APP, CANVAS, IFACE, PARENT = get_qgis_app()
from safe.utilities.analysis import Analysis
from safe.utilities.keyword_io import KeywordIO
analysis = Analysis()
arg = AnalysisArguments.read_arguments()
register_impact_functions()
registry = ImpactFunctionManager().registry
function = registry.get_instance(arg.impact_function_name)
hazard_layer = safe_to_qgis_layer(read_layer(arg.hazard_filename))
exposure_layer = safe_to_qgis_layer(read_layer(arg.exposure_filename))
if arg.aggregation_filename:
aggregation_layer = safe_to_qgis_layer(read_layer(
arg.aggregation_filename))
keywords_io = KeywordIO()
try:
analysis.map_canvas = IFACE.mapCanvas()
analysis.hazard_layer = hazard_layer
analysis.hazard_keyword = keywords_io.read_keywords(hazard_layer)
analysis.exposure_layer = exposure_layer
analysis.exposure_keyword = keywords_io.read_keywords(exposure_layer)
if aggregation_layer:
analysis.aggregation_layer = aggregation_layer
analysis.aggregation_keyword = keywords_io.read_keywords(
aggregation_layer)
analysis.impact_function = function
analysis.setup_analysis()
print 'Setup analysis done'
analysis.run_analysis()
print 'Analysis done'
except Exception as e:
print e.message
impact = analysis.impact_layer
qgis_impact = safe_to_qgis_layer(impact)
generate_styles(impact, qgis_impact)
copy_impact_layer(impact, arg.impact_filename)
def analysis_execution():
from safe.test.utilities import get_qgis_app
# get_qgis_app must be called before importing Analysis
QGIS_APP, CANVAS, IFACE, PARENT = get_qgis_app()
from safe.utilities.analysis import Analysis
from safe.utilities.keyword_io import KeywordIO
analysis = Analysis()
arg = AnalysisArguments.read_arguments()
register_impact_functions()
registry = ImpactFunctionManager().registry
function = registry.get_instance(arg.impact_function_name)
hazard_layer = safe_to_qgis_layer(read_layer(arg.hazard_filename))
exposure_layer = safe_to_qgis_layer(read_layer(arg.exposure_filename))
if arg.aggregation_filename:
aggregation_layer = safe_to_qgis_layer(
read_layer(arg.aggregation_filename))
keywords_io = KeywordIO()
try:
analysis.map_canvas = IFACE.mapCanvas()
analysis.hazard_layer = hazard_layer
analysis.hazard_keyword = keywords_io.read_keywords(hazard_layer)
analysis.exposure_layer = exposure_layer
analysis.exposure_keyword = keywords_io.read_keywords(exposure_layer)
if aggregation_layer:
analysis.aggregation_layer = aggregation_layer
analysis.aggregation_keyword = keywords_io.read_keywords(
aggregation_layer)
analysis.impact_function = function
analysis.setup_analysis()
print 'Setup analysis done'
analysis.run_analysis()
print 'Analysis done'
except Exception as e:
print e.message
impact = analysis.impact_layer
qgis_impact = safe_to_qgis_layer(impact)
generate_styles(impact, qgis_impact)
copy_impact_layer(impact, arg.impact_filename)
def run_analysis(hazard,
exposure,
function,
aggregation=None,
generate_report=False):
"""Run analysis"""
hazard_file = download_layer(hazard)
exposure_file = download_layer(exposure)
aggregation_file = None
if aggregation:
aggregation_file = download_layer(aggregation)
arguments = CommandLineArguments()
arguments.hazard = hazard_file
arguments.exposure = exposure_file
arguments.aggregation = aggregation_file
arguments.impact_function = function
# generate names for impact results
# create date timestamp
date_folder = datetime.datetime.now().strftime('%Y%m%d')
deploy_dir = os.path.join(DEPLOY_OUTPUT_DIR, date_folder)
try:
os.mkdir(deploy_dir)
except:
pass
# create temporary file name without extension
tmp = tempfile.mktemp(dir=deploy_dir)
arguments.output_file = tmp
impact_layer = run_impact_function(arguments)
if impact_layer.is_raster:
new_name = '%s.tif' % tmp
else:
new_name = '%s.shp' % tmp
# if asked to generate report
if generate_report:
arguments.report_template = ''
arguments.output_file = new_name
build_report(arguments)
# generating qml styles file
qgis_impact_layer = safe_to_qgis_layer(impact_layer)
generate_styles(impact_layer, qgis_impact_layer)
# archiving the layer
new_name = archive_layer(new_name)
# new_name is a file path to archived layer
# we need to return the url
new_basename = os.path.basename(new_name)
output_url = urlparse.urljoin(DEPLOY_OUTPUT_URL,
'%s/%s' % (date_folder, new_basename))
return output_url
def run_analysis(hazard, exposure, function, aggregation=None,
generate_report=False):
"""Run analysis"""
hazard_file = download_layer(hazard)
exposure_file = download_layer(exposure)
aggregation_file = None
if aggregation:
aggregation_file = download_layer(aggregation)
arguments = CommandLineArguments()
arguments.hazard = hazard_file
arguments.exposure = exposure_file
arguments.aggregation = aggregation_file
arguments.impact_function = function
# generate names for impact results
# create date timestamp
date_folder = datetime.datetime.now().strftime('%Y%m%d')
deploy_dir = os.path.join(DEPLOY_OUTPUT_DIR, date_folder)
try:
os.mkdir(deploy_dir)
except:
pass
# create temporary file name without extension
tmp = tempfile.mktemp(dir=deploy_dir)
arguments.output_file = tmp
impact_layer = run_impact_function(arguments)
if impact_layer.is_raster:
new_name = '%s.tif' % tmp
else:
new_name = '%s.shp' % tmp
# if asked to generate report
if generate_report:
arguments.report_template = ''
arguments.output_file = new_name
build_report(arguments)
# generating qml styles file
qgis_impact_layer = safe_to_qgis_layer(impact_layer)
generate_styles(impact_layer, qgis_impact_layer)
# archiving the layer
new_name = archive_layer(new_name)
# new_name is a file path to archived layer
# we need to return the url
new_basename = os.path.basename(new_name)
output_url = urlparse.urljoin(
DEPLOY_OUTPUT_URL,
'%s/%s' % (date_folder, new_basename)
)
return output_url
def test_run(self):
function = TsunamiRasterLandcoverFunction.instance()
hazard_path = test_data_path('hazard', 'tsunami_wgs84.tif')
exposure_path = test_data_path('exposure', 'landcover.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsRasterLayer(hazard_path, 'Tsunami')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Land Cover', 'ogr')
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
rect_extent = [106.5, -6.5, 107, -6]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
self.assertEqual(impact.dataProvider().featureCount(), 72)
features = {}
exposure_field = function.exposure.keyword('field')
for f in impact.getFeatures():
type_tuple = f[exposure_field], f[function.target_field]
features[type_tuple] = round(f.geometry().area(), 1)
expected_features = {
(u'Population', u'Dry Zone'): 7977390.3,
(u'Population', u'Low Hazard Zone'): 403.8,
(u'Population', u'Medium Hazard Zone'): 156692.3,
(u'Population', u'High Hazard Zone'): 298791.1,
(u'Population', u'Very High Hazard Zone'): 8884.6,
(u'Water', u'Dry Zone'): 403.8,
(u'Water', u'Low Hazard Zone'): 65836.7,
(u'Water', u'Medium Hazard Zone'): 34746.7,
(u'Water', u'High Hazard Zone'): 9310.4,
(u'Water', u'Very High Hazard Zone'): 807.7,
(u'Meadow', u'Dry Zone'): 2512444.0,
(u'Forest', u'Dry Zone'): 1000000.0
}
self.assertEqual(len(expected_features.keys()), len(features.keys()))
for key, value in expected_features.iteritems():
result = features[key]
msg = '%s is different than %s, I got %s' % (key, value, result)
self.assertEqual(value, result, msg)
def test_run(self):
function = ClassifiedPolygonHazardLandCoverFunction.instance()
hazard_path = standard_data_path('hazard', 'landcover_hazard.shp')
exposure_path = standard_data_path('exposure', 'landcover.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Land Cover', 'ogr')
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
rect_extent = [106.5, -6.5, 107, -6]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
self.assertEqual(impact.dataProvider().featureCount(), 7)
features = {}
exposure_field = function.exposure.keyword('field')
for f in impact.getFeatures():
type_tuple = f[exposure_field], f[function.target_field]
features[type_tuple] = round(f.geometry().area(), 1)
expected_features = {
(u'Water', u'High Hazard Zone'): 500000.0,
(u'Water', u'Medium Hazard Zone'): 500000.0,
(u'Population', u'High Hazard Zone'): 3000000.0,
(u'Population', u'Medium Hazard Zone'): 1500000.0,
(u'Population', u'Low Hazard Zone'): 1500000.0,
(u'Forest', u'High Hazard Zone'): 500000.0,
(u'Forest', u'Low Hazard Zone'): 500000.0,
}
self.assertEqual(len(expected_features.keys()), len(features.keys()))
for key, value in expected_features.iteritems():
result = features[key]
msg = '%s is different than %s, I got %s' % (key, value, result)
self.assertEqual(value, result, msg)
# check if generic notes are returned
self.assertIn(
u'Areas reported for land cover have not been rounded.',
function.notes())
def test_run(self):
function = ClassifiedPolygonHazardLandCoverFunction.instance()
hazard_path = standard_data_path('hazard', 'landcover_hazard.shp')
exposure_path = standard_data_path('exposure', 'landcover.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Land Cover', 'ogr')
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
rect_extent = [106.5, -6.5, 107, -6]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
self.assertEqual(impact.dataProvider().featureCount(), 7)
features = {}
exposure_field = function.exposure.keyword('field')
for f in impact.getFeatures():
type_tuple = f[exposure_field], f[function.target_field]
features[type_tuple] = round(f.geometry().area(), 1)
expected_features = {
(u'Water', u'High Hazard Zone'): 500000.0,
(u'Water', u'Medium Hazard Zone'): 500000.0,
(u'Population', u'High Hazard Zone'): 3000000.0,
(u'Population', u'Medium Hazard Zone'): 1500000.0,
(u'Population', u'Low Hazard Zone'): 1500000.0,
(u'Forest', u'High Hazard Zone'): 500000.0,
(u'Forest', u'Low Hazard Zone'): 500000.0,
}
self.assertEqual(len(expected_features.keys()), len(features.keys()))
for key, value in expected_features.iteritems():
result = features[key]
msg = '%s is different than %s, I got %s' % (key, value, result)
self.assertEqual(value, result, msg)
# check if generic notes are returned
self.assertIn(u'Areas reported for land cover have not been rounded.',
function.notes())
def direct_execution():
arg = AnalysisArguments.read_arguments()
register_impact_functions()
registry = ImpactFunctionManager().registry
function = registry.get_instance(arg.impact_function_name)
function.hazard = SafeLayer(read_layer(arg.hazard_filename))
function.exposure = SafeLayer(read_layer(arg.exposure_filename))
impact = calculate_impact(function)
qgis_impact = safe_to_qgis_layer(impact)
generate_styles(impact, qgis_impact)
copy_impact_layer(impact, arg.impact_filename)
def direct_execution():
arg = AnalysisArguments.read_arguments()
register_impact_functions()
registry = ImpactFunctionManager().registry
function = registry.get_instance(arg.impact_function_name)
function.hazard = SafeLayer(read_layer(arg.hazard_filename))
function.exposure = SafeLayer(read_layer(arg.exposure_filename))
impact = calculate_impact(function)
qgis_impact = safe_to_qgis_layer(impact)
generate_styles(impact, qgis_impact)
copy_impact_layer(impact, arg.impact_filename)
def test_run(self):
function = AshRasterLandCoverFunction.instance()
hazard_path = standard_data_path('hazard', 'ash_raster_wgs84.tif')
exposure_path = standard_data_path('exposure', 'landcover.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsRasterLayer(hazard_path, 'Ash')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Land Cover', 'ogr')
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
rect_extent = [106.5, -6.5, 107, -6]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
self.assertEqual(impact.dataProvider().featureCount(), 7L)
features = {}
exposure_field = function.exposure.keyword('field')
for f in impact.getFeatures():
type_tuple = f[exposure_field], f[function.target_field]
features[type_tuple] = round(f.geometry().area(), 1)
expected_features = {
(u'Forest', u'Low'): 1000000.0,
(u'Population', u'High'): 18721.0,
(u'Population', u'Moderate'): 589677.8,
(u'Water', u'Low'): 2000000.0,
(u'Meadow', u'Low'): 3971158.6,
(u'Meadow', u'Moderate'): 28841.4,
(u'Population', u'Low'): 8391601.2
}
self.assertEqual(len(expected_features.keys()), len(features.keys()))
for key, value in expected_features.iteritems():
result = features[key]
msg = '%s is different than %s, I got %s' % (key, value, result)
self.assertEqual(value, result, msg)
def test_run(self):
function = AshRasterLandCoverFunction.instance()
hazard_path = standard_data_path('hazard', 'ash_raster_wgs84.tif')
exposure_path = standard_data_path('exposure', 'landcover.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsRasterLayer(hazard_path, 'Ash')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Land Cover', 'ogr')
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
rect_extent = [106.5, -6.5, 107, -6]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
self.assertEqual(impact.dataProvider().featureCount(), 7L)
features = {}
exposure_field = function.exposure.keyword('field')
for f in impact.getFeatures():
type_tuple = f[exposure_field], f[function.target_field]
features[type_tuple] = round(f.geometry().area(), 1)
expected_features = {
(u'Forest', u'Low'): 1000000.0,
(u'Population', u'High'): 18721.0,
(u'Population', u'Moderate'): 589677.8,
(u'Water', u'Low'): 2000000.0,
(u'Meadow', u'Low'): 3971158.6,
(u'Meadow', u'Moderate'): 28841.4,
(u'Population', u'Low'): 8391601.2
}
self.assertEqual(len(expected_features.keys()), len(features.keys()))
for key, value in expected_features.iteritems():
result = features[key]
msg = '%s is different than %s, I got %s' % (key, value, result)
self.assertEqual(value, result, msg)
def run_impact_function(command_line_arguments):
"""Runs an analysis and delegates producing pdf and .shp results.
An impact layer object is created and used to write a shapefile.
The shapefile path is given by user and used by build_report
function to read from.
.. versionadded:: 3.2
:param command_line_arguments: User inputs.
:type command_line_arguments: CommandLineArguments
"""
hazard = get_hazard(command_line_arguments)
exposure = get_exposure(command_line_arguments)
aggregation = get_layer(command_line_arguments.aggregation)
analysis = analysis_setup(command_line_arguments, hazard, exposure, aggregation)
analysis.run_analysis()
impact_layer = analysis.impact_layer
qgis_impact_layer = safe_to_qgis_layer(impact_layer)
write_results(command_line_arguments, impact_layer)
return impact_layer
def run_impact_function(command_line_arguments):
"""Runs an analysis and delegates producing pdf and .shp results.
An impact layer object is created and used to write a shapefile.
The shapefile path is given by user and used by build_report
function to read from.
.. versionadded:: 3.2
:param command_line_arguments: User inputs.
:type command_line_arguments: CommandLineArguments
"""
hazard = get_hazard(command_line_arguments)
exposure = get_exposure(command_line_arguments)
aggregation = get_layer(command_line_arguments.aggregation)
analysis = analysis_setup(command_line_arguments, hazard, exposure,
aggregation)
analysis.run_analysis()
impact_layer = analysis.impact_layer
qgis_impact_layer = safe_to_qgis_layer(impact_layer)
write_results(command_line_arguments, impact_layer)
return impact_layer
def test_run(self):
"""TestClassifiedPolygonPeopleFunction: Test running the IF."""
# 1. Initializing function with necessary data
function = ClassifiedPolygonHazardPolygonPeopleFunction.instance()
hazard_path = standard_data_path('hazard',
'classified_generic_polygon.shp')
exposure_path = standard_data_path('exposure', 'census.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Exposure', 'ogr')
# 1.1 Asserting if the provided data are valid
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
# 2.Choosing the extent to run analysis
extent = hazard_layer.extent()
rect_extent = [
extent.xMinimum(),
extent.yMaximum(),
extent.xMaximum(),
extent.yMinimum()
]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
# 3. Running the analysis
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
# Asserting for the number of features in the impact
# layer
self.assertEqual(impact.dataProvider().featureCount(), 6L)
# 4. Asserting about the results found
features = {}
for feature in impact.getFeatures():
area = feature.geometry().area() * 1e8
features[feature['id']] = round(area, 1)
# expected features changes accordingly
# to the impact features
expected_features = {1: 6438.5, 2: 5894.1, 3: 8534.3}
self.assertEqual(features, expected_features)
expected_results = [[u'High Hazard Zone', 7271.431538053051],
[u'Medium Hazard Zone', 72852.05080801852],
[u'Low Hazard Zone', 11459.170311153292],
[u'Total affected people', 91583.0],
[u'Unaffected people', 17269.0],
[u'Total people', 108852]]
result = function.generate_data()['impact summary']['fields']
for expected_result in expected_results:
self.assertIn(expected_result, result)
def test_run(self):
function = TsunamiRasterLandcoverFunction.instance()
hazard_path = standard_data_path('hazard', 'tsunami_wgs84.tif')
exposure_path = standard_data_path('exposure', 'landcover.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsRasterLayer(hazard_path, 'Tsunami')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Land Cover', 'ogr')
self.assertTrue(hazard_layer.isValid())
self.assertTrue(exposure_layer.isValid())
rect_extent = [106.5, -6.5, 107, -6]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
expected = {
'data':
[[u'Population', u'Dry Zone', None, 793.6916054134609],
[u'Water', u'Low Hazard Zone', None, 16.298813953855912],
[
u'Population', u'Very High Hazard Zone', None,
12.45623642166847
],
[u'Water', u'Very High Hazard Zone', None, 0.08036139883589728],
[u'Water', u'Medium Hazard Zone', None, 12.1033540507973],
[u'Population', u'Low Hazard Zone', None, 28.866862427357326],
[u'Water', u'Dry Zone', None, 164.67113858186028],
[u'Meadow', u'Dry Zone', None, 249.95443689559693],
[u'Population', u'Medium Hazard Zone', None, 30.69211822286981],
[u'Water', u'High Hazard Zone', None, 5.835228232982915],
[u'Population', u'High Hazard Zone', None, 29.72789895440279],
[u'Forest', u'Dry Zone', None, 99.489344261353]],
'groups': ('landcover', 'hazard', 'zone')
}
ordered_columns = function.impact.impact_data.get('ordered columns')
affected_columns = function.impact.impact_data.get('affected columns')
expected = FlatTable().from_dict(
groups=expected['groups'],
data=expected['data'],
)
expected = PivotTable(expected,
row_field='landcover',
column_field='hazard',
columns=ordered_columns,
affected_columns=affected_columns)
self.assertEqual(impact.dataProvider().featureCount(), 72)
table = function.impact.impact_data['impact table']
table = FlatTable().from_dict(
groups=table['groups'],
data=table['data'],
)
table = PivotTable(table,
row_field='landcover',
column_field='hazard',
columns=ordered_columns,
affected_columns=affected_columns)
for index, value in enumerate(expected.total_rows):
self.assertAlmostEqual(value, table.total_rows[index])
for index, value in enumerate(expected.total_columns):
self.assertAlmostEqual(value, table.total_columns[index])
for index, value in enumerate(expected.total_rows_affected):
self.assertAlmostEqual(value, table.total_rows_affected[index])
for index, value in enumerate(expected.rows):
self.assertAlmostEqual(value, table.rows[index])
for index, value in enumerate(expected.columns):
self.assertAlmostEqual(value, table.columns[index])
for index, value in enumerate(expected.affected_columns):
self.assertAlmostEqual(value, table.affected_columns[index])
# This is a list of list so we unpack both
for index, value in enumerate(expected.data):
for value_index, value_value in enumerate(value):
self.assertAlmostEqual(value_value,
table.data[index][value_index])
self.assertAlmostEqual(expected.total_affected, table.total_affected)
def test_run(self):
"""TestClassifiedPolygonPeopleFunction: Test running the IF."""
# 1. Initializing function with necessary data
function = ClassifiedPolygonHazardPolygonPeopleFunction.instance()
hazard_path = test_data_path(
'hazard', 'classified_generic_polygon.shp')
exposure_path = test_data_path('exposure', 'census.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Exposure', 'ogr')
# 1.1 Asserting if the provided data are valid
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
# 2.Choosing the extent to run analysis
extent = hazard_layer.extent()
rect_extent = [
extent.xMinimum(), extent.yMaximum(),
extent.xMaximum(), extent.yMinimum()]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
# 3. Running the analysis
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
# Asserting for the number of features in the impact
# layer
self.assertEqual(impact.dataProvider().featureCount(), 6L)
# 4. Asserting about the results found
features = {}
for feature in impact.getFeatures():
area = feature.geometry().area() * 1e8
features[feature['id']] = round(area, 1)
# expected features changes accordingly
# to the impact features
expected_features = {
1: 6438.5,
2: 5894.1,
3: 8534.3
}
self.assertEqual(features, expected_features)
expected_results = [
[u'High Hazard Zone', 7271.431538053051],
[u'Medium Hazard Zone', 72852.05080801852],
[u'Low Hazard Zone', 11459.170311153292],
[u'Total affected people', 91583.0],
[u'Unaffected people', 17269.0],
[u'Total people', 108852]
]
result = function.generate_data()['impact summary']['fields']
for expected_result in expected_results:
self.assertIn(expected_result, result)
def test_run(self):
function = TsunamiRasterLandcoverFunction.instance()
hazard_path = standard_data_path('hazard', 'tsunami_wgs84.tif')
exposure_path = standard_data_path('exposure', 'landcover.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsRasterLayer(hazard_path, 'Tsunami')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Land Cover', 'ogr')
self.assertTrue(hazard_layer.isValid())
self.assertTrue(exposure_layer.isValid())
rect_extent = [106.5, -6.5, 107, -6]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
expected = {
'data':
[[u'Population', u'Dry Zone', None, 793.6916054134609],
[u'Water', u'Low Hazard Zone', None, 16.298813953855912],
[u'Population', u'Very High Hazard Zone', None,
12.45623642166847],
[u'Water', u'Very High Hazard Zone', None,
0.08036139883589728],
[u'Water', u'Medium Hazard Zone', None, 12.1033540507973],
[u'Population', u'Low Hazard Zone', None, 28.866862427357326],
[u'Water', u'Dry Zone', None, 164.67113858186028],
[u'Meadow', u'Dry Zone', None, 249.95443689559693],
[u'Population', u'Medium Hazard Zone', None,
30.69211822286981],
[u'Water', u'High Hazard Zone', None, 5.835228232982915],
[u'Population', u'High Hazard Zone', None, 29.72789895440279],
[u'Forest', u'Dry Zone', None, 99.489344261353]],
'groups': ('landcover', 'hazard', 'zone')}
ordered_columns = function.impact.impact_data.get('ordered columns')
affected_columns = function.impact.impact_data.get('affected columns')
expected = FlatTable().from_dict(
groups=expected['groups'],
data=expected['data'],)
expected = PivotTable(
expected,
row_field='landcover',
column_field='hazard',
columns=ordered_columns,
affected_columns=affected_columns)
self.assertEqual(impact.dataProvider().featureCount(), 72)
table = function.impact.impact_data['impact table']
table = FlatTable().from_dict(
groups=table['groups'],
data=table['data'],)
table = PivotTable(
table,
row_field='landcover',
column_field='hazard',
columns=ordered_columns,
affected_columns=affected_columns)
for index, value in enumerate(expected.total_rows):
self.assertAlmostEqual(value, table.total_rows[index])
for index, value in enumerate(expected.total_columns):
self.assertAlmostEqual(value, table.total_columns[index])
for index, value in enumerate(expected.total_rows_affected):
self.assertAlmostEqual(value, table.total_rows_affected[index])
for index, value in enumerate(expected.rows):
self.assertAlmostEqual(value, table.rows[index])
for index, value in enumerate(expected.columns):
self.assertAlmostEqual(value, table.columns[index])
for index, value in enumerate(expected.affected_columns):
self.assertAlmostEqual(value, table.affected_columns[index])
# This is a list of list so we unpack both
for index, value in enumerate(expected.data):
for value_index, value_value in enumerate(value):
self.assertAlmostEqual(
value_value, table.data[index][value_index])
self.assertAlmostEqual(expected.total_affected, table.total_affected)
def test_run(self):
"""TestClassifiedPolygonPeopleFunction: Test running the IF."""
# 1. Initializing function with necessary data
function = ClassifiedPolygonHazardPolygonPeopleFunction.instance()
hazard_path = test_data_path('hazard',
'classified_generic_polygon.shp')
exposure_path = test_data_path('exposure', 'census.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Exposure', 'ogr')
# 1.1 Asserting if the provided data are valid
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
# 2.Choosing the extent to run analysis
extent = hazard_layer.extent()
rect_extent = [
extent.xMinimum(),
extent.yMaximum(),
extent.xMaximum(),
extent.yMinimum()
]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
# 3. Running the analysis
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
# Asserting for the number of features in the impact
# layer
self.assertEqual(impact.dataProvider().featureCount(), 6L)
# 4. Asserting about the results found
features = {}
for feature in impact.getFeatures():
area = feature.geometry().area() * 1e8
features[feature['id']] = round(area, 1)
# expected features changes accordingly
# to the impact features
expected_features = {1: 6438.5, 2: 5894.1, 3: 8534.3}
self.assertEqual(features, expected_features)
expected_impact_summary = [
'**High Hazard Zone**, 4,600------',
'**Medium Hazard Zone**, 65,700------',
'**Low Hazard Zone**, 11,500------',
'**Total affected people**, 81,600------',
'**Unaffected people**, 17,300------',
'**Total people**, 98,900---'
]
for row in expected_impact_summary:
self.assertIn(row, function.impact_summary().to_text())
def test_run(self):
"""TestClassifiedPolygonPeopleFunction: Test running the IF."""
# 1. Initializing function with necessary data
function = ClassifiedPolygonHazardPolygonPeopleFunction.instance()
hazard_path = test_data_path(
'hazard', 'classified_generic_polygon.shp')
exposure_path = test_data_path('exposure', 'census.shp')
# noinspection PyCallingNonCallable
hazard_layer = QgsVectorLayer(hazard_path, 'Hazard', 'ogr')
# noinspection PyCallingNonCallable
exposure_layer = QgsVectorLayer(exposure_path, 'Exposure', 'ogr')
# 1.1 Asserting if the provided data are valid
self.assertEqual(hazard_layer.isValid(), True)
self.assertEqual(exposure_layer.isValid(), True)
# 2.Choosing the extent to run analysis
extent = hazard_layer.extent()
rect_extent = [
extent.xMinimum(), extent.yMaximum(),
extent.xMaximum(), extent.yMinimum()]
function.hazard = hazard_layer
function.exposure = exposure_layer
function.requested_extent = rect_extent
# 3. Running the analysis
function.run()
impact = function.impact
impact = safe_to_qgis_layer(impact)
# Asserting for the number of features in the impact
# layer
self.assertEqual(impact.dataProvider().featureCount(), 6L)
# 4. Asserting about the results found
features = {}
for feature in impact.getFeatures():
area = feature.geometry().area() * 1e8
features[feature['id']] = round(area, 1)
# expected features changes accordingly
# to the impact features
expected_features = {
1: 6438.5,
2: 5894.1,
3: 8534.3
}
self.assertEqual(features, expected_features)
expected_impact_summary = [
'**High Hazard Zone**, 4,600------',
'**Medium Hazard Zone**, 65,700------',
'**Low Hazard Zone**, 11,500------',
'**Total affected people**, 81,600------',
'**Unaffected people**, 17,300------',
'**Total people**, 98,900---'
]
for row in expected_impact_summary:
self.assertIn(row, function.impact_summary().to_text())