def test_plugin_compatibility(self):
"""Default plugins perform as expected
"""
# Upload a raster and a vector data set
hazard_filename = os.path.join(UNITDATA, 'hazard',
'jakarta_flood_design.tif')
hazard_layer = save_to_geonode(hazard_filename)
check_layer(hazard_layer, full=True)
exposure_filename = os.path.join(UNITDATA, 'exposure',
'buildings_osm_4326.shp')
exposure_layer = save_to_geonode(exposure_filename)
check_layer(exposure_layer, full=True)
# Test
plugin_list = get_admissible_plugins()
assert len(plugin_list) > 0
geoserver = {'url': settings.GEOSERVER_BASE_URL + 'ows',
'name': 'Local Geoserver',
'version': '1.0.0',
'id': 0}
metadata = get_metadata(geoserver['url'])
msg = 'There were no layers in test geoserver'
assert len(metadata) > 0, msg
# Characterisation test to preserve the behaviour of
# get_layer_descriptors. FIXME: I think we should change this to be
# a dictionary of metadata entries (ticket #126).
reference = {'geonode:buildings_osm_4326':
{'layertype': 'vector',
'category': 'exposure',
'subcategory': 'structure',
'title': 'buildings_osm_4326'},
'geonode:jakarta_flood_like_2007_with_structural_improvements':
{'layertype': 'raster',
'category': 'hazard',
'subcategory': 'flood',
'title': 'Jakarta flood like 2007 with structural improvements'}
}
for name, keywords in reference.items():
msg = 'Expected layer %s in %s' % (name, metadata.keys())
assert name in metadata.keys(), msg
values = metadata[name]['keywords']
for key in keywords.keys():
refval = keywords[key]
val = values[key]
msg = ('Got value "%s" for key "%s" '
'Expected "%s"' % (val, key, refval))
assert refval == val, msg
plugins = get_admissible_plugins(keywords=reference.values())
msg = 'No compatible layers returned'
assert len(plugins) > 0, msg
def test_non_existing_file(self):
"""RisikoException is returned for non existing file
"""
sampletxt = os.path.join(UNITDATA, 'smoothoperator.shp')
msg = ('Expected an exception for non existing file')
with self.assertRaises(GeoNodeException):
save_to_geonode(sampletxt, user=self.user)
def test_extension_not_implemented(self):
"""RisikoException is returned for not compatible extensions
"""
sampletxt = os.path.join(UNITDATA, 'exposure', 'buildings_osm_4326.lic')
try:
save_to_geonode(sampletxt, user=self.user)
except RisikoException, e:
pass
def test_plugin_selection_http(self):
"""Verify the plugins can recognize compatible layers (HTTP).
"""
# Upload a raster and a vector data set
hazard_filename = os.path.join(UNITDATA, 'hazard',
'jakarta_flood_design.tif')
hazard_layer = save_to_geonode(hazard_filename,
user=self.user,
overwrite=True)
check_layer(hazard_layer, full=True)
msg = 'No keywords found in layer %s' % hazard_layer.name
assert hazard_layer.keywords.count() > 0, msg
exposure_filename = os.path.join(UNITDATA, 'exposure',
'buildings_osm_4326.shp')
exposure_layer = save_to_geonode(exposure_filename)
check_layer(exposure_layer, full=True)
msg = 'No keywords found in layer %s' % exposure_layer.name
assert exposure_layer.keywords.count() > 0, msg
# make sure the keywords for the flood building impact
# function are present.
hazard_keywords = [k.name for k in hazard_layer.keywords.all()]
exposure_keywords = [k.name for k in exposure_layer.keywords.all()]
assert 'category:hazard' in hazard_keywords
assert 'subcategory:flood' in hazard_keywords
assert 'category:exposure' in exposure_keywords
assert 'subcategory:building' in exposure_keywords
c = Client()
functions_url = reverse('safe-functions')
rv = c.get(functions_url)
self.assertEqual(rv.status_code, 200)
self.assertEqual(rv['Content-Type'], 'application/json')
data = json.loads(rv.content)
assert 'functions' in data
functions = data['functions']
for function in functions:
if function['name'] == 'Flood Building Impact Function':
layers = function['layers']
msg_tmpl = 'Expected layer %s in list of compatible layers: %s'
hazard_msg = msg_tmpl % (hazard_layer.typename, layers)
assert hazard_layer.typename in layers, hazard_msg
exposure_msg = msg_tmpl % (exposure_layer.typename, layers)
assert exposure_layer.typename in layers, exposure_msg
def test_keywords(self):
"""Keywords are read correctly from the .keywords file
"""
for filename in ['jakarta_flood_design.tif',
'multipart_polygons_osm_4326.shp']:
_, ext = os.path.splitext(filename)
thefile = os.path.join(UNITDATA, 'hazard', filename)
uploaded = save_to_geonode(thefile, user=self.user, overwrite=True)
# Get uploaded keywords from uploaded layer object
uploaded_keywords = uploaded.keyword_list()
msg = 'No keywords found in layer %s' % uploaded.name
assert len(uploaded_keywords) > 0, msg
# Get reference keywords from file
keywords_file = thefile.replace(ext, '.keywords')
f = open(keywords_file, 'r')
keywords_list = []
for line in f.readlines():
keywords_list.append(unicode(line.strip()).replace(': ', ':'))
f.close()
# Verify that every keyword from file has been uploaded
for keyword in keywords_list:
msg = 'Could not find keyword "%s" in %s' % (keyword,
uploaded_keywords)
assert keyword in uploaded_keywords, msg
def test_metadata_available_after_upload(self):
"""Test metadata is available after upload
"""
# Upload hazard data for this test
name = 'jakarta_flood_design.tif'
exposure_filename = os.path.join(UNITDATA, 'hazard', name)
exposure_layer = save_to_geonode(exposure_filename,
user=self.user, overwrite=True)
layer_name = exposure_layer.typename
server_url = settings.GEOSERVER_BASE_URL + '/ows'
wcs = WebCoverageService(server_url, version='1.0.0')
layer_appears_immediately = layer_name in wcs.contents
wait_time = 0.5
time.sleep(wait_time)
wcs2 = WebCoverageService(server_url, version='1.0.0')
layer_appears_afterwards = layer_name in wcs2.contents
msg = ('Layer %s was not found after %s seconds in WxS contents '
'on server %s.\n'
'WCS contents: %s\n' % (layer_name,
wait_time,
server_url,
wcs.contents))
assert layer_appears_afterwards, msg
msg = ('Layer %s was not found in WxS contents on server %s.\n'
'WCS contents: %s\n' % (layer_name, server_url, wcs.contents))
assert layer_appears_immediately, msg
def test_geotransform_from_geonode(self):
"""Geotransforms of GeoNode layers can be correctly determined
"""
for filename in ['lembang_mmi_hazmap.asc',
'test_grid.asc']:
# Upload file to GeoNode
f = os.path.join(TESTDATA, filename)
layer = save_to_geonode(f, user=self.user)
# Read raster file and obtain reference resolution
R = read_layer(f)
ref_geotransform = R.get_geotransform()
# Get geotransform from GeoNode
layer_name = layer.typename
metadata = get_metadata(INTERNAL_SERVER_URL, layer_name)
geotransform_name = 'geotransform'
msg = ('Could not find attribute "%s" in metadata. '
'Values are: %s' % (geotransform_name, metadata.keys()))
assert geotransform_name in metadata, msg
gn_geotransform = metadata[geotransform_name]
msg = ('Geotransform obtained from GeoNode for layer %s '
'was not correct. I got %s but expected %s'
'' % (layer_name, gn_geotransform, ref_geotransform))
assert numpy.allclose(ref_geotransform, gn_geotransform), msg
def test_shapefile(self):
"""Shapefile can be uploaded
"""
thefile = os.path.join(UNITDATA, 'exposure', 'buildings_osm_4326.shp')
layer = save_to_geonode(thefile, user=self.user, overwrite=True)
check_layer(layer, full=True)
assert isinstance(layer.geographic_bounding_box, basestring)
def test_non_existing_dir(self):
"""RisikoException is returned for non existing dir
"""
sampletxt = os.path.join(UNITDATA, 'smoothoperator')
try:
uploaded_layers = save_to_geonode(sampletxt, user=self.user)
for uploaded in uploaded_layers:
print uploaded
except RisikoException, e:
pass
def test_repeated_upload(self):
"""The same file can be uploaded more than once
"""
thefile = os.path.join(UNITDATA, 'hazard', 'jakarta_flood_design.tif')
uploaded1 = save_to_geonode(thefile, overwrite=True,
user=self.user)
check_layer(uploaded1, full=True)
uploaded2 = save_to_geonode(thefile, overwrite=True,
user=self.user)
check_layer(uploaded2, full=True)
uploaded3 = save_to_geonode(thefile, overwrite=False,
user=self.user)
check_layer(uploaded3, full=True)
msg = ('Expected %s but got %s' % (uploaded1.name, uploaded2.name))
assert uploaded1.name == uploaded2.name, msg
msg = ('Expected a different name when uploading %s using '
'overwrite=False but got %s' % (thefile, uploaded3.name))
assert uploaded1.name != uploaded3.name, msg
def test_asciifile_without_prj(self):
"""ASCII file with without prj file is rejected
"""
thefile = os.path.join(gisdata.BAD_DATA,
'grid_without_projection.asc')
try:
uploaded = save_to_geonode(thefile, user=self.user)
except RisikoException, e:
pass
def handle(self, *args, **options):
verbosity = int(options.get('verbosity'))
ignore_errors = options.get('ignore_errors')
user = options.get('user')
overwrite = True
skip = False
keywords = options.get('keywords').split()
start = datetime.datetime.now()
output = []
for path in args:
out = save_to_geonode(path, user=user, ignore_errors=ignore_errors,
overwrite=overwrite, skip=skip,
keywords=keywords, verbosity=verbosity)
output.extend(out)
updated = [dict_['file'] for dict_ in output if dict_['status']=='updated']
created = [dict_['file'] for dict_ in output if dict_['status']=='created']
skipped = [dict_['file'] for dict_ in output if dict_['status']=='skipped']
failed = [dict_['file'] for dict_ in output if dict_['status']=='failed']
finish = datetime.datetime.now()
td = finish - start
duration = td.microseconds / 1000000 + td.seconds + td.days * 24 * 3600
duration_rounded = round(duration, 2)
if verbosity > 1:
print "\nDetailed report of failures:"
for dict_ in output:
if dict_['status'] == 'failed':
print "\n\n", dict_['file'], "\n================"
traceback.print_exception(dict_['exception_type'],
dict_['error'],
dict_['traceback'])
if verbosity > 0:
print "\n\nFinished processing %d layers in %s seconds.\n" % (
len(output), duration_rounded)
print "%d Created layers" % len(created)
print "%d Updated layers" % len(updated)
print "%d Skipped layers" % len(skipped)
print "%d Failed layers" % len(failed)
if len(output) > 0:
print "%f seconds per layer" % (duration * 1.0 / len(output))
def test_native_raster_resolution(self):
"""Raster layer retains native resolution through Geoserver
Raster layer can be uploaded and downloaded again with
native resolution. This is one test for ticket #103
"""
hazard_filename = os.path.join(UNITDATA, 'hazard', 'jakarta_flood_design.tif')
# Get reference values
H = read_layer(hazard_filename)
A_ref = H.get_data(nan=True)
depth_min_ref, depth_max_ref = H.get_extrema()
# Upload to internal geonode
hazard_layer = save_to_geonode(hazard_filename, user=self.user)
hazard_name = '%s:%s' % (hazard_layer.workspace, hazard_layer.name)
# Download data again with native resolution
bbox = get_bounding_box_string(hazard_filename)
H = download(INTERNAL_SERVER_URL, hazard_name, bbox)
A = H.get_data(nan=True)
# Compare shapes
msg = ('Shape of downloaded raster was [%i, %i]. '
'Expected [%i, %i].' % (A.shape[0], A.shape[1],
A_ref.shape[0], A_ref.shape[1]))
assert numpy.allclose(A_ref.shape, A.shape, rtol=0, atol=0), msg
# Compare extrema to values reference values (which have also been
# verified by QGIS for this layer and tested in test_engine.py)
depth_min, depth_max = H.get_extrema()
msg = ('Extrema of downloaded file were [%f, %f] but '
'expected [%f, %f]' % (depth_min, depth_max,
depth_min_ref, depth_max_ref))
assert numpy.allclose([depth_min, depth_max],
[depth_min_ref, depth_max_ref],
rtol=1.0e-6, atol=1.0e-10), msg
# Compare data number by number
assert nanallclose(A, A_ref, rtol=1.0e-8)
def test_metadata(self):
"""Metadata is retrieved correctly for both raster and vector data
"""
# Upload test data
filenames = [os.path.join('hazard', 'jakarta_flood_design.tif'),
os.path.join('exposure', 'buildings_osm_4326.shp')]
layers = []
paths = []
for filename in filenames:
path = os.path.join(UNITDATA, filename)
layer = save_to_geonode(path, user=self.user, overwrite=True)
# Record layer and file
layers.append(layer)
paths.append(path)
# Check integrity
for i, layer in enumerate(layers):
if filenames[i].endswith('.shp'):
layertype = 'vector'
elif filenames[i].endswith('.tif'):
layertype = 'raster'
else:
msg = ('Unknown layer extension in %s. '
'Expected .shp or .tif' % filenames[i])
raise Exception(msg)
layer_name = '%s:%s' % (layer.workspace, layer.name)
metadata = get_metadata(INTERNAL_SERVER_URL,
layer_name)
assert 'id' in metadata
assert 'title' in metadata
assert 'layertype' in metadata
assert 'keywords' in metadata
assert 'bounding_box' in metadata
assert len(metadata['bounding_box']) == 4
# Check integrity between Django layer and file
assert_bounding_box_matches(layer, paths[i])
# Check integrity between file and OWS metadata
ref_bbox = get_bounding_box(paths[i])
msg = ('Bounding box from OWS did not match bounding box '
'from file. They are\n'
'From file %s: %s\n'
'From OWS: %s' % (paths[i],
ref_bbox,
metadata['bounding_box']))
assert numpy.allclose(metadata['bounding_box'],
ref_bbox), msg
assert layer.title == metadata['title']
assert layer_name == metadata['id']
assert layertype == metadata['layertype']
# Check keywords
if layertype == 'raster':
category = 'hazard'
subcategory = 'flood'
elif layertype == 'vector':
category = 'exposure'
subcategory = 'structure'
else:
msg = 'Unknown layer type %s' % layertype
raise Exception(msg)
keywords = metadata['keywords']
msg = 'Did not find key "category" in keywords: %s' % keywords
assert 'category' in keywords, msg
msg = 'Did not find key "subcategory" in keywords: %s' % keywords
assert 'subcategory' in keywords, msg
msg = ('Category keyword %s did not match expected %s'
% (keywords['category'], category))
assert category == keywords['category'], msg
msg = ('Subcategory keyword %s did not match expected %s'
% (keywords['subcategory'], category))
assert subcategory == keywords['subcategory'], msg
def test_tiff(self):
"""GeoTIF file can be uploaded
"""
thefile = os.path.join(UNITDATA, 'hazard', 'jakarta_flood_design.tif')
uploaded = save_to_geonode(thefile, user=self.user, overwrite=True)
check_layer(uploaded, full=True)
def test_exceptions_in_calculate_endpoint(self):
"""Wrong bbox input is handled nicely by /safe/api/calculate/
"""
# Upload input data
hazardfile = os.path.join(TESTDATA, 'lembang_mmi_hazmap.asc')
hazard_layer = save_to_geonode(hazardfile, user=self.user)
hazard_name = '%s:%s' % (hazard_layer.workspace, hazard_layer.name)
exposurefile = os.path.join(UNITDATA, 'exposure', 'buildings_osm_4326.shp')
exposure_layer = save_to_geonode(exposurefile, user=self.user)
exposure_name = '%s:%s' % (exposure_layer.workspace,
exposure_layer.name)
bbox_correct = '105.592,-7.809,110.159,-5.647'
bbox_with_spaces = '105.592, -7.809, 110.159, -5.647'
bbox_non_numeric = '105.592,-7.809,x,-5.647'
bbox_list = [1, 2, 3, 4]
bbox_list_non_numeric = [1, '2', 3, 4]
bbox_none = None
bbox_wrong_number1 = '105.592,-7.809,-5.647'
bbox_wrong_number2 = '105.592,-7.809,-5.647,34,123'
bbox_empty = ''
bbox_inconsistent1 = '110,-7.809,105,-5.647'
bbox_inconsistent2 = '105.592,-5,110.159,-7'
bbox_out_of_bound1 = '-185.592,-7.809,110.159,-5.647'
bbox_out_of_bound2 = '105.592,-97.809,110.159,-5.647'
bbox_out_of_bound3 = '105.592,-7.809,189.159,-5.647'
bbox_out_of_bound4 = '105.592,-7.809,110.159,-105.647'
data = dict(hazard_server=INTERNAL_SERVER_URL,
hazard=hazard_name,
exposure_server=INTERNAL_SERVER_URL,
exposure=exposure_name,
bbox=bbox_correct,
impact_function='Earthquake Building Damage Function',
keywords='test,schools,lembang')
calculate_url = reverse('safe-calculate')
# First do it correctly (twice)
c = Client()
rv = c.post(calculate_url, data=data)
rv = c.post(calculate_url, data=data)
# Then check that spaces are dealt with correctly
data['bbox'] = bbox_with_spaces
rv = c.post(calculate_url, data=data)
# Then with a range of wrong bbox inputs
for bad_bbox in [bbox_list,
bbox_none,
bbox_empty,
bbox_non_numeric,
bbox_list_non_numeric,
bbox_wrong_number1,
bbox_wrong_number2,
bbox_inconsistent1,
bbox_inconsistent2,
bbox_out_of_bound1,
bbox_out_of_bound2,
bbox_out_of_bound3,
bbox_out_of_bound4]:
# Use erroneous bounding box
data['bbox'] = bad_bbox
# FIXME (Ole): Suppress error output from c.post
rv = c.post(calculate_url, data=data)
self.assertEqual(rv.status_code, 200)
self.assertEqual(rv['Content-Type'], 'application/json')
data_out = json.loads(rv.content)
msg = ('Bad bounding box %s should have raised '
'an error' % bad_bbox)
assert 'errors' in data_out, msg
def test_data_resampling_example(self):
"""Raster data is unchanged when going through geonode
"""
# Name file names for hazard level, exposure and expected fatalities
hazard_filename = os.path.join(TESTDATA, '..', 'hazard', 'maumere_aos_depth_20m_land_wgs84.asc')
exposure_filename = os.path.join(TESTDATA, 'maumere_pop_prj.shp')
#------------
# Hazard data
#------------
# Read hazard input data for reference
H_ref = read_layer(hazard_filename)
A_ref = H_ref.get_data()
depth_min_ref, depth_max_ref = H_ref.get_extrema()
# Upload to internal geonode
hazard_layer = save_to_geonode(hazard_filename, user=self.user)
hazard_name = '%s:%s' % (hazard_layer.workspace, hazard_layer.name)
# Download data again
bbox = get_bounding_box_string(hazard_filename) # The biggest
H = download(INTERNAL_SERVER_URL, hazard_name, bbox)
A = H.get_data()
depth_min, depth_max = H.get_extrema()
# FIXME (Ole): The layer read from file is single precision only:
# Issue #17
# Here's the explanation why interpolation below produce slightly
# different results (but why?)
# The layer read from file is single precision which may be due to
# the way it is converted from ASC to TIF. In other words the
# problem may be in raster.write_to_file. Float64 is
# specified there, so this is a mystery.
#print 'A', A.dtype # Double precision
#print 'A_ref', A_ref.dtype # Single precision
# Compare extrema to values from numpy array
assert numpy.allclose(depth_max, numpy.nanmax(A),
rtol=1.0e-12, atol=1.0e-12)
assert numpy.allclose(depth_max_ref, numpy.nanmax(A_ref),
rtol=1.0e-12, atol=1.0e-12)
# Compare to reference
assert numpy.allclose([depth_min, depth_max],
[depth_min_ref, depth_max_ref],
rtol=1.0e-12, atol=1.0e-12)
# Compare extrema to values read off QGIS for this layer
assert numpy.allclose([depth_min, depth_max], [0.0, 16.68],
rtol=1.0e-6, atol=1.0e-10)
# Investigate difference visually
#from matplotlib.pyplot import matshow, show
#matshow(A)
#matshow(A_ref)
#matshow(A - A_ref)
#show()
#print
for i in range(A.shape[0]):
for j in range(A.shape[1]):
if not numpy.isnan(A[i, j]):
err = abs(A[i, j] - A_ref[i, j])
if err > 0:
msg = ('%i, %i: %.15f, %.15f, %.15f'
% (i, j, A[i, j], A_ref[i, j], err))
raise Exception(msg)
#if A[i,j] > 16:
# print i, j, A[i, j], A_ref[i, j]
# Compare elements (nan & numbers)
id_nan = numpy.isnan(A)
id_nan_ref = numpy.isnan(A_ref)
assert numpy.all(id_nan == id_nan_ref)
assert numpy.allclose(A[-id_nan], A_ref[-id_nan],
rtol=1.0e-15, atol=1.0e-15)
#print 'MAX', A[245, 283], A_ref[245, 283]
#print 'MAX: %.15f %.15f %.15f' %(A[245, 283], A_ref[245, 283])
assert numpy.allclose(A[245, 283], A_ref[245, 283],
rtol=1.0e-15, atol=1.0e-15)
#--------------
# Exposure data
#--------------
# Read exposure input data for reference
E_ref = read_layer(exposure_filename)
# Upload to internal geonode
exposure_layer = save_to_geonode(exposure_filename, user=self.user)
exposure_name = '%s:%s' % (exposure_layer.workspace,
exposure_layer.name)
# Download data again
E = download(INTERNAL_SERVER_URL, exposure_name, bbox)
# Check exposure data against reference
coordinates = E.get_geometry()
coordinates_ref = E_ref.get_geometry()
assert numpy.allclose(coordinates, coordinates_ref,
rtol=1.0e-12, atol=1.0e-12)
attributes = E.get_data()
attributes_ref = E_ref.get_data()
for i, att in enumerate(attributes):
att_ref = attributes_ref[i]
for key in att:
assert att[key] == att_ref[key]
# Test safe's interpolation function
I = assign_hazard_values_to_exposure_data(H, E, attribute_name='depth')
icoordinates = I.get_geometry()
I_ref = assign_hazard_values_to_exposure_data(H_ref, E_ref, attribute_name='depth')
icoordinates_ref = I_ref.get_geometry()
assert numpy.allclose(coordinates,
icoordinates,
rtol=1.0e-12, atol=1.0e-12)
assert numpy.allclose(coordinates,
icoordinates_ref,
rtol=1.0e-12, atol=1.0e-12)
iattributes = I.get_data()
assert numpy.allclose(icoordinates, coordinates)
N = len(icoordinates)
assert N == 891
# Set tolerance for single precision until issue #17 has been fixed
# It appears that the single precision leads to larger interpolation
# errors
rtol_issue17 = 2.0e-3
atol_issue17 = 1.0e-4
# Verify interpolated values with test result
for i in range(N):
interpolated_depth_ref = I_ref.get_data()[i]['depth']
interpolated_depth = iattributes[i]['depth']
assert nanallclose(interpolated_depth,
interpolated_depth_ref,
rtol=rtol_issue17, atol=atol_issue17)
pointid = attributes[i]['POINTID']
if pointid == 263:
#print i, pointid, attributes[i],
#print interpolated_depth, coordinates[i]
# Check that location is correct
assert numpy.allclose(coordinates[i],
[122.20367299, -8.61300358],
rtol=1.0e-7, atol=1.0e-12)
# This is known to be outside inundation area so should
# near zero
assert numpy.allclose(interpolated_depth, 0.0,
rtol=1.0e-12, atol=1.0e-12)
if pointid == 148:
# Check that location is correct
#print coordinates[i]
assert numpy.allclose(coordinates[i],
[122.2045912, -8.608483265],
rtol=1.0e-7, atol=1.0e-12)
# This is in an inundated area with a surrounding depths of
# 4.531, 3.911
# 2.675, 2.583
assert interpolated_depth < 4.531
assert interpolated_depth < 3.911
assert interpolated_depth > 2.583
assert interpolated_depth > 2.675
#print interpolated_depth
# This is a characterisation test for bilinear interpolation
assert numpy.allclose(interpolated_depth, 3.62477215491,
rtol=rtol_issue17, atol=1.0e-12)
# Check that interpolated points are within range
msg = ('Interpolated depth %f at point %i was outside extrema: '
'[%f, %f]. ' % (interpolated_depth, i,
depth_min, depth_max))
if not numpy.isnan(interpolated_depth):
assert depth_min <= interpolated_depth <= depth_max, msg
def test_earthquake_exposure_plugin(self):
"""Population exposure to individual MMI levels can be computed
"""
# Upload exposure data for this test
# FIXME (Ole): While this dataset is ok for testing,
# note that is has been resampled without scaling
# so numbers are about 25 times too large.
# Consider replacing test populations dataset for good measures,
# just in case any one accidentally started using this dataset
# for real.
name = 'Population_2010'
exposure_filename = '%s/%s.asc' % (TESTDATA, name)
exposure_layer = save_to_geonode(exposure_filename,
user=self.user, overwrite=True)
exposure_name = '%s:%s' % (exposure_layer.workspace,
exposure_layer.name)
# Check metadata
assert_bounding_box_matches(exposure_layer, exposure_filename)
exp_bbox_string = get_bounding_box_string(exposure_filename)
check_layer(exposure_layer, full=True)
# Upload hazard data
filename = 'lembang_mmi_hazmap.asc'
hazard_filename = '%s/%s' % (TESTDATA, filename)
hazard_layer = save_to_geonode(hazard_filename,
user=self.user, overwrite=True)
hazard_name = '%s:%s' % (hazard_layer.workspace,
hazard_layer.name)
# Check metadata
assert_bounding_box_matches(hazard_layer, hazard_filename)
haz_bbox_string = get_bounding_box_string(hazard_filename)
check_layer(hazard_layer, full=True)
calculate_url = reverse('safe-calculate')
# Run calculation
c = Client()
rv = c.post(calculate_url, data=dict(
hazard_server=INTERNAL_SERVER_URL,
hazard=hazard_name,
exposure_server=INTERNAL_SERVER_URL,
exposure=exposure_name,
bbox=haz_bbox_string,
impact_function='Earthquake Building Damage Function',
keywords='test,population,exposure,usgs'))
self.assertEqual(rv.status_code, 200)
self.assertEqual(rv['Content-Type'], 'application/json')
data = json.loads(rv.content)
if 'errors' in data:
errors = data['errors']
if errors is not None:
msg = ('The server returned the error message: %s'
% str(errors))
raise Exception(msg)
assert 'success' in data
assert 'hazard_layer' in data
assert 'exposure_layer' in data
assert 'run_duration' in data
assert 'run_date' in data
assert 'layer' in data
assert data['success']
# Download result and check
layer_name = data['layer'].split('/')[-1]
result_layer = download(INTERNAL_SERVER_URL,
layer_name,
get_bounding_box_string(hazard_filename))
assert os.path.exists(result_layer.filename)
# Check calculated values
keywords = result_layer.get_keywords()
assert 'mmi-classes' in keywords
assert 'affected-population' in keywords
mmi_classes = [int(x) for x in keywords['mmi-classes'].split('_')]
count = [float(x) for x in keywords['affected-population'].split('_')]
# Brute force count for each population level
population = download(INTERNAL_SERVER_URL,
exposure_name,
get_bounding_box_string(hazard_filename))
intensity = download(INTERNAL_SERVER_URL,
hazard_name,
get_bounding_box_string(hazard_filename))
# Extract data
H = intensity.get_data(nan=0)
P = population.get_data(nan=0)
brutecount = {}
for mmi in mmi_classes:
brutecount[mmi] = 0
for i in range(P.shape[0]):
for j in range(P.shape[1]):
mmi = H[i, j]
if not numpy.isnan(mmi):
mmi_class = int(round(mmi))
pop = P[i, j]
if not numpy.isnan(pop):
brutecount[mmi_class] += pop
for i, mmi in enumerate(mmi_classes):
assert numpy.allclose(count[i], brutecount[mmi], rtol=1.0e-6)
def test_linked_datasets(self):
"""Linked datesets can be pulled in e.g. to include gender break down
"""
# Upload exposure data for this test. This will automatically
# pull in female_pct_yogya.asc through its "associates" keyword
name = 'population_yogya'
exposure_filename = '%s/%s.asc' % (TESTDATA, name)
exposure_layer = save_to_geonode(exposure_filename,
user=self.user, overwrite=True)
exposure_name = '%s:%s' % (exposure_layer.workspace,
exposure_layer.name)
# Check metadata
assert_bounding_box_matches(exposure_layer, exposure_filename)
exp_bbox_string = get_bounding_box_string(exposure_filename)
check_layer(exposure_layer, full=True)
# Upload hazard data
filename = 'eq_yogya_2006.asc'
hazard_filename = '%s/%s' % (TESTDATA, filename)
hazard_layer = save_to_geonode(hazard_filename,
user=self.user, overwrite=True)
hazard_name = '%s:%s' % (hazard_layer.workspace,
hazard_layer.name)
# Check metadata
assert_bounding_box_matches(hazard_layer, hazard_filename)
haz_bbox_string = get_bounding_box_string(hazard_filename)
check_layer(hazard_layer, full=True)
calculate_url = reverse('safe-calculate')
# Run calculation
c = Client()
rv = c.post(calculate_url, data=dict(
hazard_server=INTERNAL_SERVER_URL,
hazard=hazard_name,
exposure_server=INTERNAL_SERVER_URL,
exposure=exposure_name,
bbox=haz_bbox_string,
impact_function='Empirical Fatality Function',
keywords='test,fatalities,population,usgs'))
self.assertEqual(rv.status_code, 200)
self.assertEqual(rv['Content-Type'], 'application/json')
data = json.loads(rv.content)
if 'errors' in data:
errors = data['errors']
if errors is not None:
msg = ('The server returned the error message: %s'
% str(errors))
raise Exception(msg)
assert 'success' in data
assert 'hazard_layer' in data
assert 'exposure_layer' in data
assert 'run_duration' in data
assert 'run_date' in data
assert 'layer' in data
assert data['success']
# Download result and check
layer_name = data['layer'].split('/')[-1]
result_layer = download(INTERNAL_SERVER_URL,
layer_name,
get_bounding_box_string(hazard_filename))
assert os.path.exists(result_layer.filename)
# Check calculated values
keywords = result_layer.get_keywords()
assert 'caption' in keywords
def test_the_earthquake_fatality_estimation_allen(self):
"""Fatality computation computed correctly with GeoServer Data
"""
# Simulate bounding box from application
viewport_bbox_string = '104.3,-8.2,110.04,-5.17'
# Upload exposure data for this test
name = 'Population_2010'
exposure_filename = '%s/%s.asc' % (TESTDATA, name)
exposure_layer = save_to_geonode(exposure_filename,
user=self.user, overwrite=True)
workspace = exposure_layer.workspace
layer_name = exposure_layer.name
msg = 'Expected layer name to be "%s". Got %s' % (name, layer_name)
assert layer_name == name.lower(), msg
exposure_name = '%s:%s' % (workspace, layer_name)
# Check metadata
assert_bounding_box_matches(exposure_layer, exposure_filename)
exp_bbox_string = get_bounding_box_string(exposure_filename)
check_layer(exposure_layer, full=True)
# Now we know that exposure layer is good, lets upload some
# hazard layers and do the calculations
filename = 'lembang_mmi_hazmap.asc'
# Save
hazard_filename = '%s/%s' % (TESTDATA, filename)
hazard_layer = save_to_geonode(hazard_filename,
user=self.user, overwrite=True)
hazard_name = '%s:%s' % (hazard_layer.workspace,
hazard_layer.name)
# Check metadata
assert_bounding_box_matches(hazard_layer, hazard_filename)
haz_bbox_string = get_bounding_box_string(hazard_filename)
check_layer(hazard_layer, full=True)
calculate_url = reverse('safe-calculate')
# Run calculation
c = Client()
rv = c.post(calculate_url, data=dict(
hazard_server=INTERNAL_SERVER_URL,
hazard=hazard_name,
exposure_server=INTERNAL_SERVER_URL,
exposure=exposure_name,
#bbox=viewport_bbox_string,
bbox=exp_bbox_string, # This one reproduced the
# crash for lembang
impact_function='I T B Fatality Function',
keywords='test,shakemap,usgs'))
self.assertEqual(rv.status_code, 200)
self.assertEqual(rv['Content-Type'], 'application/json')
data = json.loads(rv.content)
if 'errors' in data:
errors = data['errors']
if errors is not None:
msg = ('The server returned the error message: %s'
% str(errors))
raise Exception(msg)
assert 'success' in data
assert 'hazard_layer' in data
assert 'exposure_layer' in data
assert 'run_duration' in data
assert 'run_date' in data
assert 'layer' in data
assert data['success']
# Download result and check
layer_name = data['layer'].split('/')[-1]
result_layer = download(INTERNAL_SERVER_URL,
layer_name,
get_bounding_box_string(hazard_filename))
assert os.path.exists(result_layer.filename)
def test_keywords_download(self):
"""Keywords are downloaded from GeoServer along with layer data
"""
# Upload test data
filenames = ['padang_tsunami_mw8.tif',]
filenames = ['jakarta_flood_design.tif',]
layers = []
paths = []
for filename in filenames:
basename, ext = os.path.splitext(filename)
path = os.path.join(UNITDATA, 'hazard', filename)
# Upload to GeoNode
layer = save_to_geonode(path, user=self.user, overwrite=True)
# Record layer and file
layers.append(layer)
paths.append(path)
# Check integrity
for i, layer in enumerate(layers):
# Get reference keyword dictionary from file
L = read_layer(paths[i])
ref_keywords = L.get_keywords()
# Get keywords metadata from GeoServer
layer_name = '%s:%s' % (layer.workspace, layer.name)
metadata = get_metadata(INTERNAL_SERVER_URL,
layer_name)
assert 'keywords' in metadata
geo_keywords = metadata['keywords']
msg = ('Uploaded keywords were not as expected: I got %s '
'but expected %s' % (geo_keywords, ref_keywords))
for kw in ref_keywords:
# Check that all keywords were uploaded
# It is OK for new automatic keywords to have appeared
# (e.g. resolution) - see issue #171
assert kw in geo_keywords, msg
assert ref_keywords[kw] == geo_keywords[kw], msg
# Download data
bbox = get_bounding_box_string(paths[i])
H = download(INTERNAL_SERVER_URL, layer_name, bbox)
dwn_keywords = H.get_keywords()
msg = ('Downloaded keywords were not as expected: I got %s '
'but expected %s' % (dwn_keywords, geo_keywords))
assert geo_keywords == dwn_keywords, msg
# Check that the layer and its .keyword file is there.
msg = 'Downloaded layer %s was not found' % H.filename
assert os.path.isfile(H.filename), msg
kw_filename = os.path.splitext(H.filename)[0] + '.keywords'
msg = 'Downloaded keywords file %s was not found' % kw_filename
assert os.path.isfile(kw_filename), msg
# Check that keywords are OK when reading downloaded file
L = read_layer(H.filename)
read_keywords = L.get_keywords()
msg = ('Keywords in downloaded file %s were not as expected: '
'I got %s but expected %s'
% (kw_filename, read_keywords, geo_keywords))
assert read_keywords == geo_keywords, msg
def test_metadata_twice(self):
"""Layer metadata can be correctly uploaded multiple times
"""
# This test reproduces ticket #99 by creating new data,
# uploading twice and verifying metadata
# Base test data
filenames = ['jakarta_flood_design.tif', ]
for org_filename in filenames:
org_basename, ext = os.path.splitext(os.path.join(UNITDATA, 'hazard',
org_filename))
# Copy data to temporary unique name
basename = unique_filename(dir='/tmp')
cmd = '/bin/cp -f %s.keywords %s.keywords' % (org_basename, basename)
os.system(cmd)
# Not needed since we are dealing with a raster
#cmd = '/bin/cp -f %s.prj %s.prj' % (org_basename, basename)
#os.system(cmd)
if ext == '.tif':
layertype = 'raster'
filename = '%s.tif' % basename
cmd = '/bin/cp %s.tif %s' % (org_basename, filename)
os.system(cmd)
elif ext == '.shp':
layertype = 'vector'
filename = '%s.shp' % basename
for e in ['shp', 'shx', 'sbx', 'sbn', 'dbf']:
cmd = '/bin/cp %s.%s %s.%s' % (org_basename, e,
basename, e)
os.system(cmd)
else:
msg = ('Unknown layer extension in %s. '
'Expected .shp or .asc' % filename)
raise Exception(msg)
# Repeat multiple times
for i in range(3):
# Upload
layer = save_to_geonode(filename, user=self.user,
overwrite=True)
# Get metadata
layer_name = '%s:%s' % (layer.workspace, layer.name)
metadata = get_metadata(INTERNAL_SERVER_URL,
layer_name)
# Verify
assert 'id' in metadata
assert 'title' in metadata
assert 'layertype' in metadata
assert 'keywords' in metadata
assert 'bounding_box' in metadata
assert len(metadata['bounding_box']) == 4
# Check integrity between Django layer and file
assert_bounding_box_matches(layer, filename)
# Check integrity between file and OWS metadata
ref_bbox = get_bounding_box(filename)
msg = ('Bounding box from OWS did not match bounding box '
'from file. They are\n'
'From file %s: %s\n'
'From OWS: %s' % (filename,
ref_bbox,
metadata['bounding_box']))
assert numpy.allclose(metadata['bounding_box'],
ref_bbox), msg
assert layer.title == metadata['title']
assert layer_name == metadata['id']
assert layertype == metadata['layertype']
# Check keywords
if layertype == 'raster':
category = 'hazard'
subcategory = 'flood'
else:
msg = 'Unknown layer type %s' % layertype
raise Exception(msg)
keywords = metadata['keywords']
msg = 'Did not find key "category" in keywords: %s' % keywords
assert 'category' in keywords, msg
msg = ('Did not find key "subcategory" in keywords: %s'
% keywords)
assert 'subcategory' in keywords, msg
msg = ('Category keyword %s did not match expected %s'
% (keywords['category'], category))
assert category == keywords['category'], msg
msg = ('Subcategory keyword %s did not match expected %s'
% (keywords['subcategory'], category))
assert subcategory == keywords['subcategory'], msg
def test_raster_scaling(self):
"""Raster layers can be scaled when resampled
This is a test for ticket #168
Native test .asc data has
ncols 5525
nrows 2050
cellsize 0.0083333333333333
Scaling is necessary for raster data that represents density
such as population per km^2
"""
for test_filename in ['jakarta_flood_design.tif']:
raster_filename = os.path.join(UNITDATA, 'hazard', test_filename)
# Get reference values
R = read_layer(raster_filename)
R_min_ref, R_max_ref = R.get_extrema()
native_resolution = R.get_resolution()
# Upload to internal geonode
raster_layer = save_to_geonode(raster_filename, user=self.user)
raster_name = '%s:%s' % (raster_layer.workspace,
raster_layer.name)
# Test for a range of resolutions
for res in [0.01, 0.005, 0.002, 0.001, 0.0005, 0.0002]:
bbox = get_bounding_box_string(raster_filename)
R = download(INTERNAL_SERVER_URL, raster_name,
bbox, resolution=res)
A_native = R.get_data(scaling=False)
A_scaled = R.get_data(scaling=True)
sigma = (R.get_resolution()[0] / native_resolution[0]) ** 2
# Compare extrema
expected_scaled_max = sigma * numpy.nanmax(A_native)
msg = ('Resampled raster was not rescaled correctly: '
'max(A_scaled) was %f but expected %f'
% (numpy.nanmax(A_scaled), expected_scaled_max))
assert numpy.allclose(expected_scaled_max,
numpy.nanmax(A_scaled),
rtol=1.0e0, atol=1.0e-1), msg
expected_scaled_min = sigma * numpy.nanmin(A_native)
msg = ('Resampled raster was not rescaled correctly: '
'min(A_scaled) was %f but expected %f'
% (numpy.nanmin(A_scaled), expected_scaled_min))
assert numpy.allclose(expected_scaled_min,
numpy.nanmin(A_scaled),
rtol=1.0e0, atol=1.0e-1), msg
# Compare elementwise
msg = 'Resampled raster was not rescaled correctly'
assert nanallclose(A_native * sigma, A_scaled,
rtol=1.0e0, atol=1.0e-1), msg
# Check that it also works with manual scaling
A_manual = R.get_data(scaling=sigma)
msg = 'Resampled raster was not rescaled correctly'
assert nanallclose(A_manual, A_scaled,
rtol=1.0e0, atol=1.0e-1), msg
# Check that an exception is raised for bad arguments
try:
R.get_data(scaling='bad')
except:
pass
else:
msg = 'String argument should have raised exception'
raise Exception(msg)
try:
R.get_data(scaling='(1, 3)')
except:
pass
else:
msg = 'Tuple argument should have raised exception'
raise Exception(msg)
# Check None option without existence of density keyword
A_none = R.get_data(scaling=None)
msg = 'Data should not have changed'
assert nanallclose(A_native, A_none,
rtol=1.0e-0, atol=1.0e-1), msg
# Try with None and density keyword
R.keywords['density'] = 'true'
A_none = R.get_data(scaling=None)
msg = 'Resampled raster was not rescaled correctly'
assert nanallclose(A_scaled, A_none,
rtol=1.0e2, atol=1.0e2), msg
R.keywords['density'] = 'Yes'
A_none = R.get_data(scaling=None)
msg = 'Resampled raster was not rescaled correctly'
assert nanallclose(A_scaled, A_none,
rtol=1.0e2, atol=1.0e2), msg
R.keywords['density'] = 'False'
A_none = R.get_data(scaling=None)
msg = 'Data should not have changed'
assert nanallclose(A_native, A_none,
rtol=1.0e2, atol=1.0e2), msg
R.keywords['density'] = 'no'
A_none = R.get_data(scaling=None)
msg = 'Data should not have changed'
assert nanallclose(A_native, A_none,
rtol=1.0e2, atol=1.0e2), msg
def test_specified_raster_resolution(self):
"""Raster layers can be downloaded with specific resolution
This is another test for ticket #103
Native test data:
maumere....asc
ncols 931
nrows 463
cellsize 0.00018
Population_Jakarta
ncols 638
nrows 649
cellsize 0.00045228819716044
Population_2010
ncols 5525
nrows 2050
cellsize 0.0083333333333333
Here we download it at a range of fixed resolutions that
are both coarser and finer, and check that the dimensions
of the downloaded matrix are as expected.
We also check that the extrema of the subsampled matrix are sane
"""
hazard_filename = os.path.join(UNITDATA, 'hazard', 'jakarta_flood_design.tif')
# Get reference values
H = read_layer(hazard_filename)
depth_min_ref, depth_max_ref = H.get_extrema()
native_resolution = H.get_resolution()
# Upload to internal geonode
hazard_layer = save_to_geonode(hazard_filename, user=self.user)
hazard_name = '%s:%s' % (hazard_layer.workspace,
hazard_layer.name)
# Test for a range of resolutions
for res in [0.01, 0.005, 0.002, 0.001, 0.0005, # Coarser
0.0002, 0.0001, 0.00006, 0.00003]: # Finer
# Set bounding box
bbox = get_bounding_box_string(hazard_filename)
compare_extrema = True
bb = bboxstring2list(bbox)
# Download data at specified resolution
H = download(INTERNAL_SERVER_URL, hazard_name,
bbox, resolution=res)
A = H.get_data()
# Verify that data has the requested bobx and resolution
actual_bbox = H.get_bounding_box()
msg = ('Bounding box for %s was not as requested. I got %s '
'but '
'expected %s' % (hazard_name, actual_bbox, bb))
assert numpy.allclose(actual_bbox, bb, rtol=1.0e-6)
# FIXME (Ole): How do we sensibly resolve the issue with
# resx, resy vs one resolution (issue #173)
actual_resolution = H.get_resolution()[0]
# FIXME (Ole): Resolution is often far from the requested
# see issue #102
# Here we have to accept up to 5%
tolerance102 = 5.0e-2
msg = ('Resolution of %s was not as requested. I got %s but '
'expected %s' % (hazard_name, actual_resolution, res))
assert numpy.allclose(actual_resolution, res,
rtol=tolerance102), msg
# Determine expected shape from bbox (W, S, E, N)
ref_rows = int(round((bb[3] - bb[1]) / res))
ref_cols = int(round((bb[2] - bb[0]) / res))
# Compare shapes (generally, this may differ by 1)
msg = ('Shape of downloaded raster was [%i, %i]. '
'Expected [%i, %i].' % (A.shape[0], A.shape[1],
ref_rows, ref_cols))
assert (ref_rows == A.shape[0] and
ref_cols == A.shape[1]), msg
# Assess that the range of the interpolated data is sane
if not compare_extrema:
continue
# For these test sets we get exact match of the minimum
msg = ('Minimum of %s resampled at resolution %f '
'was %f. Expected %f.' % (hazard_layer.name,
res,
numpy.nanmin(A),
depth_min_ref))
assert numpy.allclose(depth_min_ref, numpy.nanmin(A),
rtol=0.0, atol=0.0), msg
# At the maximum it depends on the subsampling
msg = ('Maximum of %s resampled at resolution %f '
'was %f. Expected %f.' % (hazard_layer.name,
res,
numpy.nanmax(A),
depth_max_ref))
if res < native_resolution[0]:
# When subsampling to finer resolutions we expect a
# close match
assert numpy.allclose(depth_max_ref, numpy.nanmax(A),
rtol=1.0e-10, atol=1.0e-8), msg
elif res < native_resolution[0] * 10:
# When upsampling to coarser resolutions we expect
# ballpark match (~20%)
assert numpy.allclose(depth_max_ref, numpy.nanmax(A),
rtol=0.17, atol=0.0), msg
else:
# Upsampling to very coarse resolutions, just want sanity
assert 0 < numpy.nanmax(A) <= depth_max_ref
def test_jakarta_flood_study(self):
"""HKV Jakarta flood study calculated correctly using the API
"""
# FIXME (Ole): Redo with population as shapefile later
# Expected values from HKV
expected_value = 1537920
# Name files for hazard level, exposure and expected fatalities
population = 'Population_Jakarta_geographic'
plugin_name = 'Flood Evacuation Function'
# Upload exposure data for this test
exposure_filename = '%s/%s.asc' % (TESTDATA, population)
exposure_layer = save_to_geonode(exposure_filename,
user=self.user, overwrite=True)
workspace = exposure_layer.workspace
exposure_name = '%s:%s' % (workspace, exposure_layer.name)
# Check metadata
assert_bounding_box_matches(exposure_layer, exposure_filename)
exp_bbox_string = get_bounding_box_string(exposure_filename)
check_layer(exposure_layer, full=True)
# Now we know that exposure layer is good, lets upload some
# hazard layers and do the calculations
filename = 'jakarta_flood_design.tif'
hazard_filename = os.path.join(UNITDATA, 'hazard', filename)
exposure_filename = os.path.join(TESTDATA, population)
# Save
hazard_layer = save_to_geonode(hazard_filename,
user=self.user, overwrite=True)
hazard_name = '%s:%s' % (hazard_layer.workspace,
hazard_layer.name)
# Check metadata
assert_bounding_box_matches(hazard_layer, hazard_filename)
haz_bbox_string = get_bounding_box_string(hazard_filename)
check_layer(hazard_layer, full=True)
calculate_url = reverse('safe-calculate')
# Run calculation
c = Client()
rv = c.post(calculate_url, data=dict(
hazard_server=INTERNAL_SERVER_URL,
hazard=hazard_name,
exposure_server=INTERNAL_SERVER_URL,
exposure=exposure_name,
bbox=exp_bbox_string,
impact_function=plugin_name,
keywords='test,flood,HKV'))
self.assertEqual(rv.status_code, 200)
self.assertEqual(rv['Content-Type'], 'application/json')
data = json.loads(rv.content)
if 'errors' in data:
errors = data['errors']
if errors is not None:
raise Exception(errors)
assert 'hazard_layer' in data
assert 'exposure_layer' in data
assert 'run_duration' in data
assert 'run_date' in data
assert 'layer' in data